The article investigates the impact of the Environmental, Social, and Governance (ESG) criteria on the current tax systems worldwide. The ESG principles, although yet to be codified in hard law in most countries, are gaining increasing prominence in shaping business practices and policies. The article explores how these principles might influence the interpretation and application of existing tax rules, even without explicit legal mandates. It delves into four key areas where ESG considerations could play a significant role: the calculation of business income, transfer pricing regulations, the application of anti-avoidance rules, and the interpretation of the "business purpose" test. It argues that ESG principles, by redefining the purpose of a business beyond mere profit maximisation, could lead to a broader understanding of deductible costs, influence transfer pricing decisions, and impact the application of anti-avoidance measures. It concludes by emphasising the potential of ESG principles to shape the future of taxation, promoting a more sustainable and equitable approach to economic growth.

Sputum induction (SI) is a non-invasive technique to obtain lower airway samples from people who do not spontaneously produce sputum. Since its introduction in 1958, its use has significantly increased for various respiratory conditions, especially with the establishment of standardized techniques. It has been used in pediatric research since 2002, starting with asthma studies. It is a safe and repeatable procedure for non-expectorating children. The ability to analyze both cellular and fluid components of sputum provides valuable information about lung diseases. This work reviews the utility of sputum induction in pediatric respiratory research and its potential clinical applications. We also discuss the safety, tolerability, and side effects profile of the procedure, emphasizing its significance in pediatric respiratory research. Despite the valuable insights gained from SI studies, challenges remain for widespread clinical utilization, requiring further refinement of the technique and increased accessibility in clinical settings.

Indoor air quality (IAQ) is a critical determinant of human health, with fungal contamination posing significant risks. In 2023, a total of 160 samples were collected from 40 selected rooms. These samples were cultured on Sabouraud Dextrose Agar (SDA) medium using a portable air sampler and incubated at 28°C for 7 days. Initial identification of fungal isolates was performed based on their morphology. Suspected isolates underwent further analysis using internal transcribed spacer (ITS) rDNA analysis. The results revealed 11 species across 8 genera in various rooms. The most prevalent fungi were Aspergillus niger (183 CFU) , Penicillium chrysogenum (139 CFU) and Cladosporium halotolerans (135 CFU). On the other hand, Curvularia hawaiiensis and A. ustus were rarely isolated (10 and 19 respectively). Effective treatment involves a combination of preventive measures, such as controlling humidity and ensuring proper ventilation, alongside targeted interventions like antifungal treatments and thorough cleaning. Continuous monitoring and management of indoor environments are essential to reduce fungal contamination, enhance air quality, and protect human health from the harmful effects of airborne fungi. This abstract underscore the importance of addressing indoor fungal contamination to promote safer, healthier living and working spaces.

Objective: To examine the dose-response relationship between average daily temperature and sunlight hours with daily steps across a 35-week period in school-aged children, and to evaluate whether there were differences by sex. Methods: We conducted a follow-up study involving 655 children (50.8% girls, mean age 10.45 ± 0.95) from six public primary schools in Cuenca, Spain. We measured daily steps using Xiaomi Mi Band 3 Smart Bracelets from October 2022 to June 2023 (over 35 weeks). We collected daily average temperature from the local weather station in Cuenca and sunlight hours during the same period. We used ANCOVA models and LOESS regression to examine the dose-response relationship between average daily temperature and daily hours of sunlight with daily steps. Additionally, we performed a multiple linear regression model. Results: Our findings revealed significant variations in daily steps across the 35 weeks. The relationship between environmental factors and daily steps was non-linear, in both girls and boys. The optimal values for higher activity levels were an average temperature of 14°C and 13 hours of sunlight. Furthermore, a 1 ºC increase in temperature was associated with an increase of 74 ± 130 steps/day, while an increase of one hour of sunlight was associated with an increase of 315 ± 237 steps/day. However, sunlight hours may act as a moderating factor. Conclusion: Our study showed a non-linear association between t average daily temperature and sunlight hours with daily steps over a 35-week period. Additional strategies may be necessary to encourage increased physical activity during periods of extreme temperatures or sunlight exposure.

Traumatic brain injury (TBI) is a global healthcare concern affecting millions, with wide-ranging symptoms including sensory and behavioral changes that can persist long-term. Due to similarities with human brain cytoarchitecture and inflammation, minipig models are advantageous for translational TBI research. However, gaps in knowledge exist regarding their behavioral and sensory sequelae following injury. Therefore, in this study, we assessed changes in approachability using a forced human approach task (FHAT) and mechanical nociception using the von Frey Test in adult male and female Yucatan minipigs for up to one week following a sham or central fluid percussion injury (cFPI). Specifically, the FHAT assessed each animal’s response to a forced interaction with either a known or unknown experimenter. To evaluate changes in nociceptive sensory sensitivity, von Frey monofilaments ranging from 0.008 to 300 grams of force were applied to the pinna of the ear or base of the tail. We found that forced approachability was affected by experimenter familiarity as well as cFPI in a sex-specific manner at subacute timepoints. We also found reductions in sensitivity following cFPI on the ear in male minipigs and on the tail in female minipigs. Overall, the current study demonstrates that cFPI produces both behavioral and sensory changes in minipigs up to one-week post-injury.

Background: In the field of brain-computer interfaces, neural decoding plays a crucial role in translating neural signals into meaningful physical actions. These signals are transmitted to processors for decoding via wired or wireless channels, often encountering data loss, commonly referred to as "packet loss." Despite its importance, the impact of different types and degrees of packet loss on neural decoding has yet to be comprehensively studied. Understanding this impact is critical for advancing neural signal processing and data filtering. Methods: This paper addresses this gap by constructing four distinct packet loss models, simulating congestion packet loss, distributed packet loss, and burst packet loss scenarios. Using macaque superior arm-movement decoding experiments, we evaluate the effects of these packet loss types on decoding performance. Results: Our findings reveal that continuous burst packet loss significantly degrades decoding performance at the same packet loss probability, and decoding parameters that are sensitive to data continuity are more heavily impacted by packet loss. Conclusions: This study provides an analysis of the relationship between packet loss and neural decoding results, offering valuable insights for future strategies aimed at preventing and handling packet loss in neural signal acquisition.

Background/Objectives: The growing interest in nutritional psychology has sparked exploration into how eating habits impact emotional, cognitive, and physical health. The Theory of Food (ToF) posits that childhood eating patterns shape food choices in adulthood, influenced by cognitive and associative representations formed early in life. This study examined the relationship between childhood eating habits and implicit attitudes toward food in adulthood, testing the ToF hypothesis. Methods: One hundred nineteen participants completed a recall questionnaire about their childhood eating habits and an Implicit Association Test (IAT) to assess implicit attitudes toward food groups. The primary hypotheses were that greater fruit consumption in childhood would lead to more positive attitudes toward fruit, and higher snack consumption would result in more favorable attitudes toward snacks. Results: The results did not support the initial hypotheses, indicating no direct relationship between childhood consumption of fruits or snacks and implicit attitudes in adulthood. However, further analyses revealed a significant difference in implicit attitudes toward fruit between participants with low versus high childhood fruit consumption, particularly among women. Conclusions: These findings highlight the complexity of the relationship between childhood eating habits and implicit food attitudes. While no direct associations were found for the overall sample, the significant differences in attitudes based on childhood fruit consumption in women suggest gender-specific patterns. These results emphasize the need for further research to unravel the intricate connections between early eating behaviours and later food attitudes.

Multimodal sentiment analysis is rapidly gaining traction due to its ability to comprehensively interpret opinions expressed in video content, which is ubiquitous across various digital platforms. Despite its promising potential, the field is hindered by the limited availability of high-quality, annotated datasets, which poses substantial challenges to the generalizability of predictive models. Models trained on such scarce data often inadvertently assign excessive importance to irrelevant features, such as personal attributes (e.g., eyewear), thereby diminishing their accuracy and robustness. To address this issue, we propose an Enhanced Modal Fusion Learning (EMFL) methodology aimed at significantly improving the generalization capabilities of neural networks. EMFL achieves this by optimizing the integration and interpretation processes of multimodal data, ensuring that sentiment-relevant features are prioritized over confounding attributes. Through extensive experiments conducted on multiple benchmark datasets, we demonstrate that EMFL consistently elevates the accuracy of sentiment predictions across verbal, acoustic, and visual modalities. These findings underscore EMFL's efficacy in mitigating the impact of non-relevant features and enhancing the overall performance of multimodal sentiment analysis models.

Increases in water temperature caused by climate change will challenge water and species management in the San Francisco Estuary. Our goals were to describe spatial and seasonal patterns in water temperature across the upper Estuary, and evaluate how temperature stress and suitability vary across the aquatic ecosystem. We synthesized 10 years of continuous water temperature data at 75 stations across six regions of the Estuary between 2010 and 2019. We identified stressful temperature thresholds for species of interest using published physiological limits and observed distribution, including ESA-listed native (e.g., osmerids, salmonids), non-ESA-listed native (e.g., cyprinids), non-native (e.g., centrarchids, bivalves), and nuisance species such as invasive aquatic vegetation, and harmful cyanobacteria. We then quantified thermal stress across varying spatial and temporal scales and metrics. Analyses indicated there were detectable regional temperature differences, and that Suisun Bay was the only region to provide regular thermal refuge during the warmer parts of the year, though portions of the Confluence and Suisun Marsh also provided potential thermal refuge during summer/fall and during cooler parts of the day. Meanwhile, the Central and South Delta experienced the warmest temperatures, exceeding thresholds for listed species throughout summer and early fall. We found that listed species such as juvenile salmonids and osmerids experience more thermal stress across a number of metrics. Fishes with higher heat tolerance (including non-natives and select natives), aquatic vegetation, and Microcystis (a harmful cyanobacteria) had the lowest average number of thermal stress days. This study demonstrates that the Estuary is already exhibiting stressful conditions for species of concern, and thermal stress will only increase with climate change. We identify at what times of year and where the Estuary may provide refuge from thermal stress conditions which has important implications for restoration prioritization and design and species management.

Objective: Although much of the research literature has found that individuals tend to perceive their friends as similar to themselves, we hypothesized that individuals with strong narcissistic traits may be less likely to do so because of their tendency to view themselves as unique. Method: We used self-reports and friend-reports in two studies with 129 participants from Germany and 131 participants from the US to examine the moderating effects of narcissistic personality features on the tendency to perceive one’s friends as having similar humor styles. Results: The results revealed that individuals generally tend to view themselves as similar to their friends in terms of humor styles. As expected, we found a moderating effect of narcissism such that higher levels of narcissism were associated with lower levels of perceived similarity. Interestingly, individuals high in grandiose narcissism tended to devalue their close friends’ humor, and individuals high in vulnerable narcissism tended to enhance their friends’ humor compared with themselves. Conclusion: The results suggest that narcissistic individuals may tend to view their friends through a particular lens, regardless of their friends’ actual traits. This mechanism may be related to the narcissistic need to feel unique.

Background/Objectives: Chronic postoperative pain remains a significant barrier in postoperative management, particularly in patients who have undergone shoulder surgery. We evaluated the predictors of chronic pain following shoulder arthroscopy. Methods: This was a retrospective, observational study of patients who underwent shoulder arthroscopy at a university hospital between 2012 and 2017. Telephone contact was established with 178 patients who met the study criteria. Demographic data, comorbidities, preoperative interscalene block application, intraoperative opioid use, and records of postoperative patient-controlled analgesia were obtained by reviewing patient files. Upon contact, each patient's psychological state and pain level were assessed. Results: Interscalene block was administered to 33 (18.5%) of the patients, while patient-controlled analgesia was provided to 97 (54.5%). The analgesic method of 48 patients’ were not achieved from the records. Chronic pain was identified in 92 patients (51.7%). Body weight, comorbidities, and the combined use of opioids and non-opioids were found to be significant risk factors (p-values of 0.024, 0.016, and 0.010, respectively) for chronic pain. Multivariate Logistic Regression analysis revealed that the risk of chronic pain in patients with comorbidities and combined opioid-non-opioid use was 9.27 times higher than in those without comorbidities. In the presence of comorbidities, the risk of chronic pain was found to be 7.18 times higher in patients who did not use a combination of opioids and non-opioids. Conclusion: This study indicates that higher body weight, the presence of comorbidities, and the use of both opioids and non-opioids are significant predictors of increased chronic postoperative pain following shoulder arthroscopy.

Despite significant advancements in neuro-oncology, glioblastoma remain a formidable challenge. Over the last century, the role and goals of surgery for patients with glioblastoma has evolved dramatically, with surgical intervention maintaining a central role in patient care. Here, we provide of an overview of this evolution and speak to anticipated changes in the future.

Ox Tongue (Echium amoenum) is an important medicinal plant rich in secondary metabolites, including alkaloids, quinones, and unsaturated fatty acids. The present study examined the concentration of oil, fatty acid profiles, and antioxidant activity of six different Iranian Echium accessions. The oil concentration varied across these populations, ranging from 16.20% to 22.36% in the first year and from 21.00% to 25.50% in the second year. The major fatty acids identified in the oils were oleic acid (18.35% to 19.40%), linoleic acid (23.80% to 26.20%), and α-linolenic acid (32.30% to 34.20%) during the first year. In the second year, the predominant fatty acids were oleic acid (15.82% to 19.32%), linoleic acid (21.55% to 24.70%), and α-linolenic acid (33.95% to 37.40%). Principal component analysis revealed distinct profiles for each population: Sari was notable for its high α-linolenic acid and γ-linolenic acid content, Fasa was distinguished by its high stearidonic acid levels, Roodsar had a high concentration of stearic acid, Vazneh Sar was rich in linoleic acid and palmitic acid, and Leron had the highest oleic acid content. The Sari population had the highest oil content at 25.50%, while Fasa had the highest α-linolenic acid content at 37.40% during the establishment year. Leron exhibited the highest antioxidant attributes. These findings indicate that selecting elite Echium populations with high levels of unsaturated fatty acids and potent antioxidant properties could be advantageous for the food industry, as they offer enhanced nutritional and functional qualities.

This study investigates the optimization of boron coating parameters for medium carbon steels, specifically AISI 1137, and their subsequent effects on mechanical properties, which are crucial for industrial applications. Despite extensive research on boronizing processes, an understanding of the optimal conditions that enhance wear resistance and hardness while maintaining structural integrity is still lacking. To address this gap, we systematically examined the impact of boronizing temperatures (850 °C and 950 °C) and durations (2, 4, and 8 hours) on the structural and mechanical properties of AISI 1137 steel. Our findings indicate the need for improved surface properties in medium carbon steels used in demanding environments, such as automotive and machinery components. The boronizing process was carried out using Ekabor 1 powder, with characterization performed through optical microscopy, pin-on-disk wear tests, and Vickers hardness analysis. Results showed that the thickness of the boronized layer ranged from 50.6 μm to 64.8 μm, with wear resistance increasing by 1.8 to 3.9 times at 950 °C compared to 850 °C. The measured hardness of the boronized surface layers varied between 1963.7 HV and 219.3 HV, decreasing from the boronized layer toward the base material. The optimal parameters for wear resistance and hardness were found to be a temperature of 950 °C and a duration of 8 hours, facilitating the formation of FeB and Fe2B phases, which significantly enhanced the steel's mechanical properties. This research provides valuable insights into the boronizing process and establishes a foundation for optimizing surface treatments to extend the lifespan and performance of medium carbon steels in industrial use.

Ferroptosis is a recently identified iron-dependent programmed cell death with lipid peroxides accumulation and condensation and compaction of the mitochondria. Recent study indicated that ferroptosis played a pivotal role in ischemic cardiac injury with the mechanisms remained largely unknown. This study demonstrated that iron overload occurred in the ischemia/reperfusion (I/R) cardiac tissues, which initiated myocardial ferroptosis. The expression levels of mitochondrial inner membrane protein MPV17 were reduced when ferroptosis occurred in cardiomyocytes treated with high levels of iron or in the ischemic cardiac tissues. Overexpression of MPV17 delivered via adenovirus significantly reduced ferroptosis in both cardiomyocytes subject to high levels of iron and cardiac I/R tissues. Mitochondrial glutathione (mtGSH), crucial for reactive oxygen species (ROS) scavenging and mitochondrial homeostasis maintenance, was depleted during myocardial ferroptosis caused by iron overload. The mechanistic study showed that MPV17 could increase mtGSH levels through maintaining the protein homeostasis of SLC25A10, which was a mitochondrial inner-membrane glutathione transporter. The absence of MPV17 during iron overload resulted in the ubiquitination-dependent degradation of SLC25A10, leading to impaired mitochondrial glutathione import. Moreover, we found that MPV17 was the targeted gene of Nrf2, which played a pivotal role in preventing lipid peroxides accumulation and ferroptosis. The decreased expression levels of Nrf2 led to the inactivation of MPV17 during iron overload-induced myocardial ferroptosis. In summary, this study demonstrated the critical role of MPV17 in protecting cardiomyocytes from ferroptosis and elucidated the Nrf2-MPV17-SLC25A10/mtGSH signaling pathway in the regulation of myocardial ferroptosis.

We recently identified that cerebral mRNA expression for inducible costimulator (ICOS) and its ligans, ICOSL, both significantly increases during elimination of Toxoplasma gondii cysts from the brains of infected mice by perforin-mediated cytotoxic activity of CD8⁺ T cells. In the present study, we examined the role of ICOS in activating the effector activity of CD8⁺ T cells in response to the cysts in infected mice. Following adoptive transfer of splenic CD8⁺ T cells from chronically infected ICOS-deficient (ICOS^-/-) and wild-type (WT) mice to infected SCID mice, fewer CD8⁺ T cells were detected in the brains of the recipients of ICOS^-/- than WT CD8⁺ T cells. However, such lower numbers of ICOS^-/- CD8⁺ T cells, which migrated into the brains of the recipients, eliminated T. gondii cysts more efficiently than WT CD8⁺ T cells did. Consistently, the ICOS^-/- CD8⁺ T cells secreted greater amounts of granzyme B in response to T. gondii antigens in vitro than did WT CD8⁺T cells. We identified that ICOS^-/- CD8⁺ T cells express significantly greater levels of CD28 on their surface than WT CD8⁺ T cells, and relative expression levels of CD28 mRNA in ratios to CD8b mRNA levels in the brains of the recipients of those CD8⁺ T cells strongly correlated with their relative expression levels of mRNA for T-bet transcription factor and perforin. Furthermore, blocking of CD28 signaling by a combination of anti-CD80 and anti-CD86 antibodies abolished the increased cytotoxic activity of the ICOS^-/- CD8⁺ T cells in vitro. The present study uncovered notable compensatory interactions between ICOS and CD28 to secure the cytotoxic effector activity of CD8⁺ T cells against a microbial infection in a murine model of chronic infection with T. gondii.

Solution combustion synthesis (SCS) is often utilized to prepare crystalline nanoparticles of transition metal oxides, in particular Mn oxides. The structure and composition of the final product depend on the conditions of the synthesis, in particular on the composition of metal precursors, its molar ratio to the fuel component, and the mode of heating. In the present work the study of chemical phenomena which may occur in the during SCS process has been studied for the conventional nitrate-glycine synthesis of Mn oxide, as well as for nitrate-citrate-glycine and nitrate-citrate-urea synthesis. In the case of nitrate-glycine synthesis, formation of a weak complex of Mn(II) and glycine provides the conditions of instantaneous SCS reaction upon heating, resulting in slight sintering of final oxide nanoparticles. However, partial hydrolysis of Mn precursor during slow solvent evaporation results in formation of mixture of oxides, namely MnO and Mn3O4. Formation of MnO is completely suppressed in the presence of ammonium citrate in the initial mixture, and pure Mn3O4 phase is obtained. SCS reaction in this case is slower, resulting in stronger sintering of the nanoparticles. The study of electrochemical properties of synthesized oxides demonstrated that the SCS with nitrate-citrate-urea mixture provides the highest charge capacitance in 1M NaOH: 130 F/g at 2 A/g. Impedance characterization of materials allowed to propose a tentative mechanism of degradation of electrode materials during the galvanostatic cycling.

Crowd abnormal behavior recognition is one of the research hotspots in computer vision. Its goal is to use computer vision technology and abnormal behavior detection models to accurately perceive, predict, and intervene in potential abnormal behaviors of the crowd, and monitor the status of the crowd system in public places in real-time, to effectively prevent and deal with public security risks and ensure public life safety and social order. To this end, focusing on the crowd abnormal behavior recognition technology in the computer vision system, a systematic review study of its theory and cutting-edge technology is conducted. First, the crowd level and abnormal behaviors in public places are defined, and the challenges faced by crowd abnormal behavior recognition are expounded. Then, from the dimensions based on traditional methods and based on deep learning, the mainstream technologies of abnormal behavior recognition are discussed, and the design ideas, advantages, and limitations of various methods are analyzed. Next, the mainstream software tools are introduced to provide a comprehensive reference for the technical framework; Secondly, typical abnormal behavior datasets at home and abroad are sorted out, and the characteristics of these datasets are compared in detail from multiple perspectives such as scale, characteristics and uses, and the performance indicators of different algorithms on the datasets are compared and analyzed; Finally, the full text is summarized and the future development direction of crowd abnormal behavior recognition technology is prospected.

The external bonding system using CFRP composite was widely used for strengthening of different structures worldwide. However, premature debonding in this strengthening technique is the critical failure that leads to the fiber not reaching its ultimate capacity. In order to enhance the capacity of the externally bonded (EB) FRP and to slow the premature debonding failure mechanism, numerous anchoring techniques have been applied to improve the bonding capacity. The externally-bonded reinforcement on grooves (EBROG) technology is one of the strategies that have been recently developed to postponing the debonding issue. Although the extensive studies have been conducted in literature on (EBROG) method, most of these studies have been focused on the bonding characteristics of longitudinal grooves direction, and there is lack in studies about effect of different design and configurations (width, height, and spacing) of transverse grooves direction. In present study, an experimental investigation was carried out to study the bond behavior of the externally bonded reinforcement on transverse grooves (EBROTG) technique on the CFRP-to-concrete joints involving different parameters, including groove width, depth, spaces between grooves, strain values, and bond stress-slip relationships. 24 concrete prisms, divided into 8 groups of three specimens, were tested using a single-lap shear test set-up. The result of testing proved that the EBROTG method furnished a proper anchor system and highly enhanced the bonding force of the tests. The increasing range in bond strength with the specimens reinforced by the transverse grooving method was ranging from 11 to 86 % compared with the externally bonded reinforcement (EBR) reflecting the effect of different width, depth and distance between grooves

The tunable work function of titanium dioxide (TiO₂) nanoparticles of various sizes was measured using the Kelvin Probe Force Microscopy (KPFM) technique. The analysis of the contact potential difference (CPD) across TiO₂ nanoparticles of different sizes revealed a clear relationship between nanoparticle size, surface roughness, and work function. The study observed work function values ranging from 4.49 eV to 4.57 eV for particle sizes between 3 nm and 85 nm, which were higher than those of bulk TiO₂, likely due to quantum confinement effects. Additionally, electrostatic force microscopy (EFM) measurements showed significant charge-trapping behavior within TiO₂ nanoparticles under different applied bias voltages. The optical analysis also revealed a quantum confinement-induced band gap of 3.35 eV, larger than that of bulk TiO₂, and distinct photoluminescence peaks at 383 nm and 403 nm, corresponding to near-band-edge excitonic emissions and defect-related states. By analyzing the conduction band (CB) and valence band (VB) of TiO₂ nanoparticles using KPFM, the CB and VB positions were calculated based on work function data and bandgap. The results indicated that as particle size increases, both CB and VB energies shift slightly towards lower values, where smaller nanoparticles exhibit larger band gaps and higher work functions.

Leveraging the liquid phase immiscibility effect and phase diagram calculations, a sequence of alloy powders with varying Fe content was designed and fabricated utilizing gas atomization method. Microstructural characterizations, employing SEM, EDS, and XRD analyses, revealed the successful formation of incomplete shell on the surfaces of Al-Bi-Fe powders, obviating the need for Sn doping. This study systematically investigated the microstructure, hydrolysis performance, and hydrolysis process of these alloys in deionized water. Notably, Al-10Bi-7Fe exhibited the highest hydrogen production, reaching 961.0 Nml/g, while Al-10Bi-10Fe demonstrated the peak conversion rate at 92.99%. The hydrolysis activation energy of each Al-Bi-Fe alloy powder was calculated using the Arrhenius equation, indicating a reduction in activation energy achieved through Fe doping.

In the standard model (SM) and general relative theory (GR) based on the 4-D Minkowski space, the graviton and photon are massless. In that case, two particles with the positive masses are attracted to each other by the gravitational (graviton) waves. The origin of the attractive gravitational force is not understood in terms of SM and GR. In the present work, the 3-D quantized space model (TQSM) based on the 4-D Euclidean space is applied to explain the attractive gravitational force. The repulsive Coulomb force between two particles with the positive charges is explained by using the destructive interference of the electric waves emitted from two particles. Therefore, the destructive interference of the gravitational (graviton) waves emitted from two particles with the positive masses should make the repulsive gravitational force (F_r). The observance of the attractive gravitational force (F_g) indicates the non-zero graviton mass because the attractive gravitational force can be explained if the gravitational (graviton) waves are the oscillating mass waves. The masses lost during the destructive interference of the gravitational (graviton) waves are converted to the gamma rays. These induced gamma rays make the new attractive force (F_a). The observed attractive gravitational force (F_g) should be originated by the equation of F_g = F_a – F_r > 0. This can explain the reason why the gravitational force (F_g) between the elementary particles is so weak when compared with the Coulomb forces. The properties of elementary particles in terms of the TQSM model are analyzed by the wave mechanics of G, E and M waves of the 3-D quantized photon space. The G wave is the time fluctuations along the (absolute) time axis and E (electric) and M (magnetic) waves are the space fluctuations along the space axes. The elementary particles exist as the particle forms with the constant (rest) masses (m) at the low speed. The elementary particles at the high speed have the (particle) wave forms with the oscillating masses or the particle forms with the relativistic masses (gm). The graviton has the very small mass moving with the very high-speed close to the light speed of c. This means that most of the gravitons exist as the graviton wave forms. The particle waves are coupled with the photon waves (2EM, gamma rays) because of the energy conservation. It is concluded that the gravitational waves are the coupled oscillating forms (GEM waves) of the graviton waves and photon waves. The existence of the wave forms for the particles can explain the double slit experiment for the electron beams. And the attractiveness of the dark matter, weak and strong forces is explained by the virtual two boson processes with the TC symmetry and total energy conservation. All elementary bosons and neutrinos are considered as the wave forms with the high speed close to the light speed of c. Because of the charge and energy conservations, only the neutrino oscillations and dark matter (baston) oscillations are allowed.

Adeno-associated viruses (AAVs) have been used for liver gene therapy. Hemgenix and Roctavian are AAV-based treatments for hemophilia B and A, respectively. They cost $3 million and $2.8 million per dose, respectively. While AAV vectors may eventually be cheaper to mass produce, a bacteria-based DNA delivery system might be much cheaper for patients. Also, “bactofection” would allow for the delivery of much larger DNA packages. Such a bacterial system may now be possible, and a prototype for the liver could possibly be developed immediately.

In recent years, there has been a significant demand for Instructional Design (ID) professionals due to the rise of remote work, increased reliance on digital learning solutions for professional development, and the integration of digital technologies in formal and informal learning spaces. However, practical and authentic personalized courses are unavailable for professionals who want to transition into the field. This study addresses the gaps in most of the available ID courses and details the design of an Instructional Design Skill-Strength Assessment System (IDSSAS) that evaluates gaps in users' skills and offers them courses and mentors to help them bridge them in preparation for work as an ID in the corporate space. Employing a User-Centered Design (UCD) approach, the system prioritizes personalization, real-world application, and practical skills that better position them to be more employable, a significant improvement over the mostly available traditional, theory-focused ID training programs. IDSSAS, which is integrable with any Learning Management System (LMS) or Learning Experience Platform (LXP), was developed with Storyline 360, and it offers personalized learning and feedback as well as provides users with the agency to choose a mentor that is best aligned with their area of interest. The design was grounded in Self-Determination Theory (SDT) and incorporates design features like a progress bar, feedback loop, challenges, social interaction, and agency to support students' motivation and promote Autonomy, Relatedness, and Competence. IDSSAS, in its manual and present automated form, has been successfully used to mentor some transitioning ID professionals globally who are now gainfully employed.

Objective The healthcare industry has witnessed a paradigm shift with the adoption of Electronic Patient Records (EPRs), transitioning from traditional Paper and Pencil (P&P) methods to sophisticated, technology-driven documentation systems. However, the integration of EPRs into clinical settings has introduced new challenges. This study investigates workflow consequences of switching from P&P to EPR systems. Methods In this study, two independent observers audited surgical ward rounds to assess the effects of transitioning from P&P to EPR. These audits captured number of medical personnel and five key aspects before and after EPR implementation. Additionally, the EPR system's usability was gathered through the System Usability Scale (SUS) and the Post Study System Usability Questionnaire (PSSUQ). Results A total of 192 observations using P&P and 160 with the EPR system were analyzed. Results indicated that physicians spent a lower proportion of time in patient rooms using the P&P modality (median = 0.14, IQR = [0.06, 0.24]) compared to the EPR system (median = 0.19, IQR = [0.12, 0.29]). Conversely, nurses spent more time with the P&P modality (median = 0.13, IQR = [0.08, 0.18]) than with the EPR system (median = 0.10, IQR = [0.06, 0.13]). The typical team in the P&P modality comprised two physicians and four nurses, while teams in the EPR system generally included two or three physicians and three nurses. Usability assessments yielded scores rated as "Not Acceptable." Conclusion The EPR is already known to contribute to an increased administrative burden. Our findings generally align with this view in the physician sample, whereas nurses did not encounter difficulties switching systems. However, usability scores indicated that the EPR system falls short of meeting user acceptance expectations. Given the continuous increase in administrative workload, our results suggest that ururcing administrative tasks could enhance the efficiency of medical duties performed at patient's bedside.

The RSA cryptosystem has long been a fundamental component of contemporary public key in- frastructure. However, recent developments in quantum computing and mathematical theory have introduced signicant challenges to its security. A fully operational quantum computer would allow for the application of Shor's algorithm, enabling the ecient factoring of large integers, thereby com- promising the integrity of RSA and other cryptographic methods dependent on discrete logarithms. Although Grover's algorithm poses a comparatively smaller threat to symmetric encryption systems, it still presents a vulnerability by accelerating key search processes. The looming threat from quan- tum technologies has driven a surge in research aimed at developing quantum-resistant cryptography. These eorts focus on cryptographic techniques grounded in error-correcting codes, lattice structures, and multivariate public key systems, all of which leverage the complexity of NP-hard problemssuch as solving multivariate quadratic equationsto preserve security in a post-quantum world. This pa- per reviews the current progress in quantum-resistant encryption methods, particularly emphasizing the role of robust trapdoor functions. Additionally, it provides a comprehensive analysis of critical multivariate cryptosystem frameworks, such as Matsumoto-Imai, Oil and Vinegar, and Polly Cracker schemes. It also examines advances in lattice-based systems like Kyber and Crystals-Dilithium, which are undergoing assessment by NIST for potential standardization. As quantum computing continues to evolve, the demand for cutting-edge cryptographic solutions to safeguard digital communications grows increasingly pressing.

Pilostyles, an endoparasitic genus within the Apodanthaceae family, grows inside host stems, with flowers and fruits being the only external manifestations. Previous studies of P. berteroi growing on Adesmia trijuga provided limited details of the endophyte and omitted the origin of flowers and synker structure. This study, using classical methods of optical microscopy applied to the analysis with scanning electron microscopy and confocal laser scanning microscopy, expands the understanding of the P. berteroi/A. trijuga complex. We find that P. berteroi develops isophasically with its host, forming meristematic patches between secondary phloem cells. The parasitized Adesmia stem’s cambium primarily produces inward parenchyma cells, with limited vessel production and ceased fiber formation. The polarization of meristematic patches led to the formation of floral meristems. Flowers develop endogenously and emerge by the breakthrough of the host stem. Flowers connect to the host cambium via chimeric synkers, combining P. berteroi parenchyma and tracheoids with Adesmia vessels. Unlike previous studies that show uniformity among Pilostyles species, our analysis reveals new insights into the structural interaction between P. berteroi and A. trijuga. Further ultrastructural investigations are needed to explore potential direct or indirect connections between the vascular systems of the two taxa.

Education plays a key role in human societies and the development of nations. Providing social justice in a country creates educational justice, and educational justice grants equal opportunities for growth and prosperity to the members of the society. In reality, there are differences between urban and rural educational facilities, as well as between girls and boys. Deprived and rural areas are full of losses, from economic problems to intellectual and cultural blockages. Failure to enhance these areas leads to further decline in these environments, and one of its consequences in education is the dropout of students. Girls are especially exposed to this problem due to gender discrimination, traditional and religious views, and living conditions. The purpose of this research was to obtain in-depth information about the experiences and reactions of girls in deprived areas and to identify its factors. This case study was conducted in the Khuzestan province of Iran using the grounded theory, and the results of the interviews were categorized after coding and its paradigm model was presented. In the end, solutions were presented to reduce the dropout rate of girls in deprived areas and prevent this problem.

Introduction: Leptin and ghrelin are two hormones that play a role in weight homeostasis. Leptin, which is produced primarily by adipocytes and is dependent on body fat mass, suppresses appetite and increases energy expenditure. Conversely, ghrelin is the “hunger hormone”, it stimulates appetite and promotes fat storage. Bariatric surgery significantly alters the levels and activity of these hormones, contributing to weight loss and metabolic improvements. Clarifying the interplay between bariatric surgery, weight loss, physical exercise, leptin, and ghrelin is essential for developing comprehensive strategies for optimizing long-term outcomes for candidates for bariatric surgery, especially sarcopenic patients. Methods: This was a randomized controlled study with two groups (n=22). The patients in both groups have obesity and sarcopenia. A Roux-en-Y-gastric bypass (RYGB) procedure was performed in all patients. The intervention group participated in a structured exercise program three times per week beginning one month after surgery and lasting 16 weeks. Patient assessment was performed before surgery (baseline) and after completion of the exercise program. The control group received the usual standard of care and was assessed similarly. Results: After surgery, weight, BMI and lean mass decreased significantly in both groups from baseline to the second assessment. Leptin was not significantly different from baseline to the second assessment in the physical exercise group but was significantly lower in the control group (p=0.05). Ghrelin increased over time in both groups, but the differences were not significant. When we associated leptin (the dependent variable) with weight (the independent variable), we found that lower weight was associated with lower leptin levels. A similar relationship was also observed between leptin and sarcopenia parameters (muscle strength and mass), as well as with bone health parameters (bone mineral density and t-score). Higher ghrelin levels were significantly associated with higher t-scores and z-score (p

Fairness-related decision-making often involves a conflict between egoistic and prosocial motives. Previous research based on Terror Management Theory (TMT) indicates that mortality salience can promote both selfish and prosocial behaviors, leaving its effect on fairness-related decision-making uncertain. By integrating TMT with the strength model of self-control, we propose that managing death-related thoughts depletes self-control strength, thereby impairing individuals' ability to resist selfish impulses during fairness-related decision-making tasks. Additionally, this effect is moderated by dispositional self-control. We tested these hypotheses in two studies. Participants were primed with either mortality salience or negative affect and then asked to made a series of binary choices (equal allocation vs. unequal allocation favoring themselves) to distribute monetary resources. In both studies, mortality salience heightened selfish tendencies, leading allocate resources less equitably. Study 2 further revealed that this effect occurred among participants with low, but not high, self-control. These findings indicate that mortality salience promotes selfishness and inequitable resource allocation, but that self-control can buffer these effects.

The genetic transformation of Coffea arabica L. is an alternative strategy for obtaining plants with agronomic traits of interest that is less time-consuming than conventional breeding methods. Given the importance of coffee cultivation in Colombia, this study evaluated the main factors interfering with the genetic transformation of C. arabica using Agrobacterium tumefaciens. An effi-cient and reproducible method was accordingly established that involved the propagation of “early” embryogenic tissue in a liquid proliferation medium, supplemented with 3 mg l−1 BAP for eight months, which was subsequently sonicated for 300 sec in a suspension of LBA4405 OD600 of 0.5 harboring pC1301 and incubated in this same suspension for 1 hr. This plasmid contained the uidA gene under control of the 35S promoter. The Agrobacterium suspen-sion was subsequently removed from the embryogenic tissue using a micropipette, after which the tissue was deposited on filter paper to remove the remaining Agrobacterium suspension. The embryogenic tissue was co-cultured for four days in a solid differentiation medium supple-mented with 100 µM acetosyringone on filter paper. Subsequently, the tissue was post-cultured for four days in liquid differentiation medium under orbital shaking at 100 rpm with 300 mg l−1 Claforan (Hoechst), followed by selection with 50 mg l-1 hygromycin at 26 °C in the dark, with subcultures at 20-day intervals until somatic embryos were formed for subsequent culturing in germination medium. Molecular analysis confirmed the presence of the uidA gene in coffee seedlings transformed with strains LBA4405 and EHA105 and vectors pC1301 and pC2301. This method successfully enables the stable integration of genes of interest in the coffee plant ge-nome

Recycling solar panels is crucial to mitigating the environmental impact of the growing volume of end-of-life photovoltaic waste and conserving valuable resources, while achieving high purity in recovered materials ensures their effective reuse in the manufacturing of new solar panels, con-tributing to a sustainable and circular economy. This study proposes a two-step leaching process to recover Ag and Al from the silicon fraction of EoL photovoltaics (PVs). In the first stage laboratory scale tests, 99% Al was extracted using 5% HCl at room temperature for 3 hrs. The Al was precip-itated as oxide from the solution. The silicon residue was then leached with 0.5 M HNO3 at 80°C for 2 hrs extracting 99% Ag and producing Si with 99.83% purity. The silver was precipitated to produce metallic Ag with >99.9% purity. Methods to mitigate the effluent solutions were recom-mended and the entire process was presented in a flowsheet.

The glucocorticoid receptor alpha (GRα), a pivotal component of the ancient glucocorticoid (GC) signaling system that emerged nearly 450 million years ago, has been instrumental in directing vertebrate evolution and is essential for survival, regulating fertility and fetal development, the function of every organ and circulating cells, metabolism, immune responses, and adaptation to stress. While its anti-inflammatory properties have been recognized since the mid-20th century, GRα’s broader role as the master regulator of homeostatic corrections, particularly in health and critical illness, has only recently been fully appreciated.GRα orchestrates three key phases of homeostatic correction: the Priming Phase, where it rapidly activates early immune responses, mobilizes energy reserves, and prepares the body to mount an immediate defense against various physiological stressors, including infection and injury. During this phase, GRα enhances glucose metabolism, supports mitochondrial function, and facilitates the release of key immune cells to the site of damage, ensuring the body is equipped to handle the initial assault. The Modulatory Phase follows, in which GRα fine-tunes the inflammatory response to prevent excessive tissue damage. By balancing pro- and anti-inflammatory signals, GRα helps contain the immune response, preventing the harmful effects of prolonged inflammation while maintaining immune surveillance. This phase also involves the regulation of oxidative stress, vascular tone, and the preservation of cellular integrity to protect vital organs from injury. Finally, in the Restorative Phase, GRα plays a critical role in resolving inflammation and initiating tissue repair. During this phase, GRα supports cellular regeneration, promotes the clearance of apoptotic cells and debris, and restores anatomical and physiological balance. It aids in rebuilding tissue architecture and returning the neuroendocrine-immune system to its baseline state, ensuring long-term recovery and stability.Throughout these phases, GRα manages complex interactions, including recently discovered co-regulation with pro-inflammatory transcription factors, while also regulating mitochondrial function to ensure bioenergetic and metabolic stability during stress. In critically ill patients, depletion of bioenergetic and micronutrient reserves severely impairs GRα’s capacity to regulate immune responses, heightening the risk of morbidity and mortality.This review, in light of this new understanding, underscores the need to re-evaluate current glucocorticoid (GC) treatment strategies, emphasizing the incorporation of micronutrient support to optimize GRα function across all phases of homeostatic correction. This integrated therapeutic approach has the potential to enhance both immediate immune responses and long-term recovery in critically ill patients, offering a more comprehensive strategy for managing the complex pathobiology of critical illness. Furthermore, this integrative approach could decrease glucocorticoid dose and duration requirements and potential side effects.

This paper presents an 8x8 channel optoelectronic readout array (ORA) realized in a 180-nm CMOS process for the applications of short-range light detection and ranging (LiDAR) sensors. We propose several circuit techniques in this work including an amplitude-to-voltage (A2V) converter that reduces the notorious walk-errors by intensity compensation, and a time-to-voltage (T2V) converter that acquires the linear slope of the output signals by exploiting a charging circuit, thus extending the input dynamic range significantly from 5 uApp to 1.1 mApp, i.e. 46.8 dB. These results correspond to the maximum detection range of 8.2 meters via the action of the A2V converter and the minimum detection range of 56 centimeters with the aid of the proposed T2V converter. Optical measurements utilizing an 850-nm laser diode confirm that the proposed 8 x 8 ORA with 64 on-chip avalanche photodiodes (APDs) can successfully recover the narrow 5-ns light pulses even at the shortest distance of 56 centimeters. Hence, this work provides a potential CMOS solution for low-cost, low-power short-range LiDAR sensors.

As a coping mechanism to job creation and income poverty reduction, people in the rural areas are engaging in commercial farm activities commonly known as agribusinesses including tree farming. The study assessed the contribution of tree farming by smallholder farmers on livelihood assets in the study area before and after their engagement. Household survey and key informant interviews were used to collect data from 270 respondents randomly selected from 4 Wards of Njombe Distrct to include Ihanga, Iwungilo Kifanya and Lugenge which mostly practice tree farming; and 4 key informants’ interviews were done to the district officers in the Department of Agriculture, Irrigation and Cooperative. Seven out of nine livelihood asset ownerships were found to have significantly improved after farmers’ being engaged in tree farming. A paired sample ttest was conducted to evaluate the possession of assets by respondents and it was found that household assets before tree farming was (M= 1.80, SD= 0.752) and after engaging in tree farming was (M=2.00, SD= 0.199), t (269) = 8.706, p<0.0005(two-tailed). The mean increase score in houses ownership for instance was 0.2 at 95% confidence interval ranging from -0.433 to 0.033. The eta squared statistic of (0.219) indicated a strong effect on tree farmers’ livelihood in the study area and a significant improvement in livelihood assets after engagement in tree farming. It is concluded that, this activity has contributed to income poverty reduction by giving smallholder farmers a good purchasing power for the livelihood assets. It is recommended that; the government should control the market of forest related products and ensure price stability.

The spatial expansion of urban agglomerations is a direct manifestation of regional urbanization, reflecting the changes in scale and morphological characteristics of urban in temporal and spatial dimensions, which affects the efficiency of regional urbanization. This study employed a range of analytical techniques, including the urban spatial intensity index, center-of-gravity model, synergy index, inverse distance weighting interpolation method, and Geodetector, to examine the spatiotemporal evolution pattern and driving factors of the Beibu Gulf Urban Agglomeration in Guangxi, China between 2012 and 2022. The findings indicate that: (1) The Beibu Gulf Urban Agglomeration in Guangxi has been in a stable expansion trend over the past decade. However, the polarization effect of the central city space has gradually weakened, and the spatial expansion differences between cities have gradually narrowed, indicating an extensional development mode. (2) The economic and social gravity centers show a tendency of "eastward and southward" migration, which is opposite to the direction of the urban gravity center's displacement. The displacement directions of population and ecological gravity centers are roughly consistent with that of urban center. The distribution of economic and social resources are not aligned with the configuration of urban development, and the trajectory of the center of gravity of various development dimensions has shifted. (3) Economic and social expansion is significantly faster than population and ecology, but slower than urban expansion. The intensity of urban expansion is inconsistent with the distribution of synergies. The spatial differences in synergies between cities are gradually narrowing. The central city's radiation-driven role is insufficient. The development of nodal cities is less than expected. However, the benefits of urbanization in coastal cities are constantly being strengthened. (4) The disposable income of urban residents and per capita arable land area are the primary driving forces of urban expansion, while population density and urban green space area are significant contributors to urban expansion. Based on the above findings, it is recommended that the Beibu Gulf Urban Agglomeration of Guangxi should continue to enhance the scale efficiency of population agglomeration, optimize economic development and industrial resource allocation, promote urban-rural integration, strengthen inter-city connections, optimize spatial layout, and improve the overall production and living efficiency of regional cities and towns.

Adolescents most often experience mild acute COVID-19 but may still face fatigue and persistent symptoms such as post-COVID-19 condition (PCC) and post-infective fatigue syndrome (PIFS). We explored the fecal microbiota in a prospective controlled cohort of 136 non-hospitalized SARS-CoV-2-positive and 32 SARS-CoV-2-negative controls aged 12–25 years. With a targeted qPCR approach, the quantities of 100 fecal bacterial taxa were measured at baseline (early convalescent stage) and after six months. Results: Faecalibacterium prausnitzii M21.2 and Gemmiger formicilis (both p&lt;0.001) were enriched in the SARS-CoV-2-positive participants compared to controls at baseline. Lower baseline abundance of Faecalibacterium prausnitzii M21/2 (p=0.013) and higher abundance of Clostridium spiroforme (p=0.006), Sutterella wadsworthensis (p&lt;0.001) and Streptococcus thermophilus (p=0.039) were associated with six-month fatigue. Sutterella wadsworthensis and Streptococcus thermophilus enrichment was additionally associated with PCC in the SARS-CoV-2-positive group (p&lt;0.001 and 0.042 respectively). Conclusions: In mild SARS-CoV-2 infection in adolescents and young adults, beneficial Faecalibacterium prausnitzii M21/2 and Gemmiger formicilis were enriched compared to SARS-CoV-2 negative controls. Additionally, both known (Faecalibacterium prausnitzii, Streptococcus thermophilus) and new (Clostridium spiroforme, Sutterella wadsworthensis) bacteria were associated with persistent symptoms in the COVID-19 infected group, warranting further exploration of the role of these bacteria in COVID-19 disease and PCC pathophysiology.

A study was conducted to determine the estimated parasitic infestation and associated risk factors (Water quality, Farm management practices and External factors such as Intermediate hosts and Wild fish entry) of farmed Nile tilapia in Pond grow-out, Cage grow-out (lake), Cage grow-out (reservoir) farms and Hatcheries in the Lake Victoria Crescent, Uganda. Sixteen parasite genera and 65% (418/640) infestation rate were obtained. However, Pond grow-out farms and Hatcheries did not only constitute 81% and 63% of the parasite genera, but also had the highest mean number of parasite genera per farm of 1 to 7 and 4 to 8 respectively. Cage grow-out (reservoir) farms and Hatcheries had the highest mean prevalence of >0.7. Water quality parameters, farm management practices and external factors varied across the 4 farming systems, with Cage grow-out farms (lake) with the best water quality parameters, farm management practices and control over intermediate hosts and wild fish entry. Using Spatial Areal Unit Modelling with Conditional Autoregressive Priors, out of 16 risk factors, only Intermediate hosts had a significant effect on estimated parasitic infestation. Estimated parasitic infestation of 0.28 (low) or 0.55 (high) prevalence was obtained. All Cage grow-out (reservoir) farms and Hatcheries, and 78% (14/18) of Pond grow-out farms had high estimated parasitic infestation despite their locations, while 75% (3/4) of Pond grow-out farms that had low estimated parasitic infestation were located in Masaka (an area with many minor and less polluted rivers). Fifty-six percent (5/9) of Cage grow-out (lake) had low estimated parasitic infestation and were located in the Southern part of Wakiso, Southern part of Mukono and Southern part of Jinja but far from the Napoleon Gulf. The Cage grow-out farms with high estimated parasitic infestation were found in the Southeastern part of Buikwe (an area with sugar cane plantations and factories) and Southern part of Jinja in the polluted Napoleon Gulf. Therefore, the type of farming system and its location (spatial component) need to be given at-most importance when coming up with management and sanitary control strategies to encounter parasite infestation.

Cancer immunobiology is one of the hot topics of discussion amongst researchers today, and immunotherapeutic modalities are among the selected few emerging approaches to cancer treatment that have exhibited a promising outlook. However, immunotherapy is not a new kid on the block; it has been around for centuries. The origin of cancer immunotherapy in modern medicine can be traced back to the initial reports of spontaneous regression of malignant tumors in some patients following an acute febrile infection, at the turn of the twentieth century. This review briefly revisits the historical accounts of immunotherapy, highlighting some of the significant developments in the field of cancer immunobiology, that have been instrumental in bringing back the immunotherapeutic approaches to the forefront of cancer research. Some of the topics covered are: Coley's toxin - the first immunotherapeutic; the genesis of the theory of immune surveillance; discovery of T-lymphocytes and dendritic cells and their roles; the role of tumor antigens; relevance of tumor microenvironment; anti-tumor (therapeutic) ability of Bacillus Calmette Guerin; Melacine - the first therapeutic vaccine engineered; theories of immunoediting and immunophenotyping of cancer; and Provenge – the first FDA approved therapeutic vaccine. In this review, head and neck cancer has been taken as the reference tumor, for narrating the progression of cancer immunobiology, particularly, for highlighting the advent of immunotherapuetic agents.

The standard molar enthalpies of formation in the liquid phase for ethyl (E)-cinnamate and ethyl hydrocinnamate, two cinnamate derivatives with notable flavor and fragrance characteristics, were determined experimentally using combustion calorimetry in an oxygen atmosphere. To derive the gas-phase enthalpies of formation for these derivatives, their enthalpies of vaporization were measured using a high-temperature Calvet microcalorimeter and the vacuum drop micro-calorimetric technique. Additionally, a computational analysis employing the G3(MP2)//B3LYP composite method was conducted to calculate the gas-phase standard enthalpies of formation at T = 298.15 K for both compounds. These findings enabled a detailed assessment and analysis of the structural and energetic effects of the vinyl and ethane moieties between the phenyl and carboxylic groups in the studied com-pounds. Considering the structural features of ethyl (E)-cinnamate and ethyl hydrocinnamate, a gas-phase enthalpy of hydrogenation analysis was conducted to explore their energetic profiles more thoroughly.

Background: Leprosy control remains challenging in Brazil and has been aggravated by the Covid-19 pandemic. Objective: To analyze the impact of the Covid-19 pandemic on the epide-miological scenario of leprosy through the detection rate of new cases, risk of illness and hidden prevalence according to high-risk micro-region in Minas Gerais, Brazil. Methods: Ecological study conducted in the health micro-regions, using data on new leprosy cases diagnosed between 2015 and 2023. The annual detection rate of new cases, the Risk of Illness Index and the Hidden Preva-lence were evaluated. The time trend was evaluated by calculating the Annual Percentage Change (APC) of the detection rate, based on segmented linear regression. Results: A reduction in the detection of new cases was identified in most of the micro-regions evaluated. Minas Gerais and some micro-regions showed a positive increase in the variation of the overall detection rate in 2021. The reduction in hidden prevalence in certain micro-regions is linked to the reduction in diagnoses, especially those cases with installed physical disability. Despite the reduction in the risk of becoming ill with leprosy in some micro-regions, Minas Gerais showed an increase in risk. Conclusions: The pandemic has had a considerable and heterogeneous impact on the detection of new cases, as well as on the risk of becoming ill and the hidden prevalence, with repercussions for the control of the endemic in populations. There is a need to implement public health policies that prioritize the early identification of cases and ensure that vulnerable populations are monitored.

At the beginning of any electric arc welding process, a regime called transient regime will always occur, characterized by the continuous variation of the energy flow, also resulting in the variation of the cooling rate of the welded joint. Consequently, the weld bead hardness varies from a maximum value to an approximately constant value, and this phenomenon can be represented by an asymptotic exponential function. For several welded specimens, it would be possible to fit a non-linear regression for each specimen, however, it would be a difficult task to combine different regressions in a single analysis. The objective of this study is to evaluate the applicability of mixed-effects models and artificial neural networks to predict the longitudinal hardness of the weld bead in the initial transient regime. To this end, linearized and nonlinear mixed-effects models and artificial neural networks with different architectures were fitted. Finally, valid models were obtained with all approaches, with artificial neural network model slightly better fitted. However, the explainability capacity of the linearized mixed-effects model was superior, showing that the relative thickness, one of the predictor variables, was responsible for 48% of the variation in longitudinal hardness of weld bead.

Bacterial infections pose a serious threat to human health, and the overuse of antibiotics has led to the rise of multidrug-resistant bacteria. Numerous current wound dressings, which may cause skin irritation or allergies are insufficient in handling large wounds, often leading to infections. This highlights the need for better antibacterial materials. Nypa fruticans (Nipa palm), native to Southeast Asia, has long been utilized for various purposes because of its multiple benefits such as its antimicrobial properties, presence of probiotics, and high cellulose content. This study evaluates the use of cellulose hydrogel from nipa fronds, loaded with probiotics (ProbioGel), as an antimicrobial agent to prevent infections. The study involved an in-vitro assay using the Kirby-Bauer method to evaluate the gel’s antimicrobial properties against common wound pathogens. Additionally, whole genome sequencing and promoter analysis were done to identify genes supporting their biochemical properties. The results showed ProbioGel exhibited significant antimicrobial activity against Staphylococcus aureus, Escherichia coli, Staphylococcus epidermidis, and Candida albicans due to the presence of genes encoding lysozyme, carnobacteriocin B2, and fatty acid ABC transporter ATP binding in the Lacticaseibacillus paracasei BCRC-16100. This study highlighted the potential of ProbioGel as an innovative and effective antimicrobial and anti-infection agent for wound care. The discovery of genes in the probiotic strain responsible for encoding antimicrobial peptides further supports its therapeutic potential.

In today’s fast-paced technological landscape, businesses must adapt to evolving business models and harness the power of data to thrive. Small and Medium-sized Enterprises (SMEs) face significant challenges in aligning IT infrastructure with business objectives while navigating digital transformation. This systematic review, conducted using PRISMA 2020 guidelines, investigates the role of Enterprise Architecture (EA) and Information Management (IM) in driving IT growth and sustaining competitive performance in SMEs. Through a synthesis of academic research, industry analysis, and case studies from the last decade, this review identifies key frameworks—such as TOGAF, Zachman, and FEAF—that support the alignment of IT capabilities with organizational goals. The integration of IM within EA frameworks is found to enhance decision-making, resource allocation, and operational efficiency. Emerging technologies like Artificial Intelligence (AI) and cloud computing are highlighted for their transformative impact, enabling real-time data analysis, improved scalability, and enhanced agility. Our review reports that 43.44% of the studies focused on cloud-based solutions, while 24.59% adopted hybrid models, offering SMEs scalable and flexible IT infrastructures. The findings emphasize the necessity of strong governance frameworks to ensure compliance, adaptability, and long-term sustainability in a dynamic environment. This research contributes to a comprehensive roadmap for SMEs, enabling them to leverage EA and IM for sustained growth and competitive advantage in the digital era.

The etiology of autism spectrum disorder (ASD) has not yet been completely elucidated. Through time, multiple attempts have been made to uncover the causes of ASD. Different theories have been proposed, such as that it is caused by “Gods Wrath,” alterations in the gut–brain axis with an emphasis on gut dysbiosis, post vaccine complications, and genetic or even autoimmune causes. In this review we present data covering over 170 000 participants at age ranging from 2 to 14 years focusing on human cell changes rather than using animal models found in previous studies. The male/female ratio was 4:1. Data collection occurred in many countries covering ethnically diversified subjects. Moreover, we aimed to show how the progress in genetic techniques influences the explanation of medical White Papers in ASD area.

There is an extensive body of research in the literature focusing on predicting the mechanical properties of concrete, such as compressive strength. Summarizing the current studies following the valuable contributions of researchers will serve as a guide for future studies and researchers. To this end, this study aims to identify the key authors, sources, institutions, and countries that have contributed to the prediction of concrete compressive strength. Additionally, it aims to provide researchers with comprehensive information on prominent research themes, trends, and gaps in the literature related to the prediction of concrete compressive strength. For this purpose, 2319 articles on the prediction of concrete compressive strength published from 2000 to 19th August 2024 were identified through the Scopus Database. The scientific measurement analyses were conducted using VOSviewer software. Upon reviewing the relevant research, it was found that machine learning methods are frequently used in predicting concrete compressive strength. In this context, the study will make significant contributions to the literature by examining leading institutions, countries, authors, and sources in the field, synthesizing data, and highlighting research areas, gaps, and trends related to concrete compressive strength prediction.

World Health Organization is encouraging countries to include contact screening and single dose of rifampicin administration as preventive chemotherapy for contacts of leprosy patients in their leprosy control activities. However, no study has been conducted to assess the safety of SDR-PEP and acceptability and feasibility of this intervention in Togo. To assess the safety of SDR-PEP we used a cohort design and for acceptability and feasibility we used a mixed method combining a quantitative study to assess the safety of SDR-PEP in a cohort of contacts from recently diagnosed leprosy patients followed by a qualitative study to identify the social, cultural or institutional factors that would influence the adoption of single dose rifampicin as post-exposure prophylaxis for contacts of leprosy patients in Togo. For the quantitative study, all identified index patients agreed to the disclosure of their status to their contacts and provided a list of their contacts. All the contacts found agreed to take part in the study and an appointment was made for screening. However, some contacts were absent on the screening day for no reason. All eligible contacts agreed to take SDR and were followed up after taking the drug. No severe adverse events were reported during follow-up. For the qualitative study, 72 interviews (66 semi-structured interviews and 6 focus groups) were carried out, and it emerged that overall, opinions were favorable on the acceptability and feasibility of implementing single dose rifampicin as post-exposure prophylaxis for contacts of leprosy patients in Togo. However, a number of conditions need to be considered for more effective results.

Background/Objectives: Current guidelines recommend intravenous thrombolysis (IVT) followed by mechanical thrombectomy (MT) for patients with acute ischemic stroke (AIS) caused by large vessel occlusion (LVO). This combined approach, known as bridging therapy (BT), is believed to increase the likelihood of a favorable functional outcome when administered within 4.5 hours of symptom onset. However, the benefits of BT over direct mechanical thrombectomy (d-MT) remain debated. This study aimed to compare the outcomes of AIS-LVO patients undergoing MT within 6 hours of symptom onset, with and without prior IVT. Methods: Within the prospective TINL STROKE-registry, AIS-LVO patients admitted to the Department of Neurology, University of Pécs, between February 2023 and June 2024 were investigated. The primary endpoint was the proportion of patients reaching functional independence at 90 days, defined as a modified Rankin Scale (mRS) score of 0-2. Secondary endpoints included clinical improvement at 72 hours (National Institute of Health Stroke Scale [NIHSS] score of ≤1 or a change from baseline [ΔNIHSS] of ≥4) and successful recanalization (modified Thrombolysis in Cerebral Infarction [mTICI] score ≥2). Safety outcomes were evaluated based on thrombus migration and intracranial hemorrhage (ICH). Results were compared using linear and logistic regression analyses adjusted for baseline variables. Results: Of 82 patients, 51 (62.2%) received BT, while 31 (37.8%) underwent d-MT. The BT group showed a significantly higher rate of functional independence (45.7% vs. 17.2%, p=0.014) and a lower 90-day mortality rate (13.7% vs. 35.5%, p=0.029). Multivariate analysis revealed that IVT was independently associated with favorable functional outcome (p=0.011) and reduced mortality (p=0.021). No significant differences were observed in terms of clinical improvement at 72 hours, successful recanalization, thrombus migration, or hemorrhagic transformation between the groups. Conclusions: This study supports current guidelines recommending BT for thrombectomy-eligible AIS-LVO patients, offering new insights into the ongoing clinical debate.

The objective of the study was to analyze the climate change experienced in Spain between 1971 and 2022 and to estimate the future climate (2050). The main objectives were: 1) to analyze the temporal evolution of temperature from 1971 to the present, to quantify the warming process experienced in the case study and to evaluate the increase in ex-treme heat events (heatwaves); 2) to study the evolution of the precipitation regime to determine whether there is a statistically representative trend towards a drier climate and an increase in extreme precipitation; 3) to investigate the interaction between annual precipitation and the continuous increase in temperature; and 4) to estimate the future climate scenario for mainland Spain and the Balearic Islands towards 2050, analyzing the trends in land aridity and predicting a possible change from a Mediterranean climate to a warm steppe climate, according to the Köppen classi-fication. In this study, we used the E-OBS dataset provided by the European Climate Assessment and Dataset (ECA&D) project. E-OBS is a high-resolution gridded daily climate dataset. Its advantage over other databases is that it is based on direct climate information from the weather stations included in the Copernicus ECA&D. Furthermore, a detailed interpolation and refinement process allows a complete, uniform view of the studied territory. This dataset has pro-vided daily weather information since 1950 and is presented as a complete dataset of the European region. It is availa-ble on a regular grid of 0.1 and 0.25 degrees for the elements of daily average temperature (TG), daily minimum tem-perature (TN), daily maximum temperature (TX) and the sum of daily precipitation (RR), among other climatic varia-bles. In this study, we obtained daily temperature data, including the average, maximum and minimum temperature, and precipitation from 1971 to 2022, using the 27.0e dataset. We used information from E-OBS from 1 January 1971 to 31 December 2022, with a resolution of 0.25 degrees. The main purpose of this study was to analyze whether there is a temporal evolution of the precipitation regime in Spain towards less precipitation, and to study the relationship between annual precipitation and the tendency to-wards progressive warming. Specifically, the aim was to test the hypothesis that the increase in temperature resulting from the global warming process implies a tendency towards progressive drought. The hypothesis is + T  - RR. Given the extreme annual variability of the climate, in addition to the ordinary least squares methodology, the techniques mainly used in this study were the Mann-Kendall test and the Kendall-Theil-Sen regression. The Mann-Kendall test confirmed the statistical significance of the relationship between RR and TX, with a statistical relia-bility close to 99.9%. The KTS regression predicted a reduction of 38.25 mm for each 1°C increase. If the warming trend experienced in recent years (1973– 2022) continues, it is foreseeable that by 2050 there will be a reduction in precipitation in Spain of between 14% and 23% with respect to the precipitation of the reference period (understood as the average between 1971 and 2000). Spain’s climate is likely to vary from Mediterranean to warm steppe in the Köppen classification system (from “C” to “B”).

Background : The multisystem manifestations of Fabry disease can create major challenges in patient care. Although enzyme replacement therapy with recombinant agalsidase beta has demonstrated clinical benefits, the standard fortnightly, multihour infusion regimen imposes a substantial burden on patients. Methods : We assessed the safety and feasibility of shortening the agalsidase beta infusion time to 90 minutes in adult patients with classic or later-onset Fabry disease in the absence of premedication. A total of 39 consecutive adult patients (agalsidase-naive: n=6; significant comorbidities: n=15) with no recent infusion-associated reactions underwent a total of 85 agalsidase beta infusions in our tertiary reference center for lysosomal diseases. Each infusion was administered at a constant rate (between 0.78 and 1.17 mg/min, depending on the patient’s body weight). Results : No adverse events of any type (including discomfort and infusion-associated reactions) were reported during or after infusions. The patients’ vital signs remained stable, and patient satisfaction was high. Seven patients requested even shorter infusions (50 to 60 minutes) under strict medical supervision. Conclusions : Our results suggest that shortening the agalsidase beta infusion time to 90 minutes is safe and feasible in stably treated adult patients with Fabry disease and no recent infusion-associated reactions.

The transition to renewable and sustainable energy sources is critical to solving the environmental and socioeconomic problems associated with the use of fossil fuel. This study uses an interdisciplinary approach to analyze the evolution, challenges and prospects of a sustainable energy transition in the context of recent discovery and exploitation of fossil resources. We study the case of Senegal from 2000 to 2027 and the role of natural gas in its energy transition. In 2000, Senegal's energy mix consisted of about 97% for fossil energy and only 3% for renewable energy. Nowadays, although fossil fuels are still dominant, but they account for about 70% of total electricity production. The country has indeed undertaken tremendous efforts to develop renewable energy sources including, solar, hydro and wind power, which currently account for about 30% of the total energy mix. Socio-economic indicators show that over the past two decades, Senegal's population and electricity production have grown significantly, leading to an increased energy demand/need. This growth has resulted in a five-fold increase in per capita energy consumption over the same period. Combining the strategic use of natural gas as a transition energy source with the continued development of renewable energy sources could make Senegal as a model for West Africa’s energy transition. The projections for 2027 suggest a structural shift in the energy mix, with natural gas, oil, and renewables at 47%, 32%, and 21%, respectively.

This study analyzed the influence of attitude toward innovation and creativity, entrepreneurial self-efficacy, and institutional support in the consolidation of an entrepreneurial culture among Peruvian university students, using the Theory of Planned Behavior (TPB) as the theoretical framework. Data were collected from 948 students through a validated 29-item questionnaire, and the data analysis was conducted using the PLS-SEM method. The results showed that both attitude toward innovation and entrepreneurial self-efficacy have a significant positive impact on entrepreneurial culture, and entrepreneurial self-efficacy acted as a partial mediator in this relationship. However, external resources and institutional support were not significant mediators between entrepreneurial intention and entrepreneurial culture. This study expands the understanding of TPB in the Peruvian context, highlighting the importance of fostering self-efficacy and an innovative attitude in students to strengthen entrepreneurial culture in universities. Educational institutions should consider these key factors when designing programs that promote entrepreneurship.

Increased wildfire activity is the most significant natural disturbance affecting forest ecosystems, with a strong impact on their natural regeneration. This study presents a comprehensive analysis of post-fire forest recovery using Landsat time series data from 2000 to 2023 in the Middle Volga region of the Russian Federation. The analyses utilised the LandTrendr algorithm in Google Earth Engine (GEE) cloud computing platform to examine Normalized Burn Ratio (NBR) spectral metrics and quantify the forest recovery at low, moderate, and high burn severity (BS) levels. To assess the spatio-temporal trends of the recovery, the Mann–Kendall statistical test and Theil–Sen’s slope estimator was applied. The results suggested that the post-fire spectral recovery is significantly influenced by the degree of the BS on affected areas. The higher the class of BS, the faster and more extensive the reforestation of the area occurs. About 91% (40,446 ha) of the first 5-year forest recovery after the wildfire belong to the BS classes of moderate and high severity. A regression model showed that land surface temperature (LST) was more significant to post-fire recovery than the variability in precipitation (Pr), explaining about 65% of the variance in post-fire recovery. This study provides new insights into the post-fire forest recovery dynamics and scientific bases for the cost-effective management strategies under changing climate conditions.

This study introduces a novel, robust, and efficient method for the simultaneous quantitative determination of three sunscreen filters namely 4-methylbenzylidene camphor, octyl methoxycinnamate, and avobenzone, in a moisturizing sunscreen cream specifically designed for acne-prone skin. The method employs high performance liquid chromatography with photodiode-array detection, providing reliable separation of the analytes. Chromatographic separation was achieved using a Fortis Phenyl analytical column (150.0 x 2.1 mm, 5 μm), with isocratic elution at a flow rate of 0.4 mL/min. The mobile phase was composed of a 57/43 (v/v) mixture of acetonitrile/45 mM aqueous ammonium formate solution, ensuring sufficient resolution and peak symmetry for the target compounds. The method was validated comprehensively for critical performance parameters, including linearity, precision, accuracy, and robustness. Linearity was established across a suitable range for all three analytes, with high correlation coefficients. Precision was confirmed with intra-run and total precision coefficients of variation of ≤ 4.6 %, while accuracy assessments yielded a percent recovery between 98.6 and 100.4, for all quality control levels. Additionally, the method was able to effectively separate the sunscreen filters from other cosmetic ingredients, such as [β-(1.3), (1.6)-D-glucan], Low Molecular Weight (LMW) hyaluronic acid and plant extracts ensuring specificity in complex formulations. This straightforward and time efficient sample preparation process, involving methanol extraction followed by serial dilution, makes the method suitable for routine quality control in cosmetic laboratories. The method was successfully applied to the analysis of two different lots of a commercial sunscreen cream, achieving excellent recovery for all filters, ranging between 94.6% and 99.8%, thus demonstrating its reliability and applicability for the quality control of cosmetics.

Hypertrophic cardiomyopathy (HCM) poses a significant health burden worldwide, characterized by myocardial hypertrophy and increased risk of sudden cardiac death. Recent studies have revealed the involvement of exosome-derived microRNAs (miRNAs) in the pathogenesis of HCM, shedding light on novel regulatory mechanisms in cardiac remodeling and dysfunction. This literature review synthesizes current evidence on the role of exosome-derived miRNAs in HCM. It discusses key miRNAs identified from diverse cellular origins, including cardiomyocytes, stem cells, and conduction cells, elucidating their contributions to hypertrophic signaling pathways, fibrosis, and changes in cellular metabolism. Notable miRNAs highly expressed in exosomes such as miR-1, miR-133, and miR-208 are highlighted for their implications in HCM pathophysiology. Moreover, the review explores the diagnostic and therapeutic potential of exosome-derived miRNAs as biomarkers and therapeutic targets in HCM management. The studies summarized in this review demonstrate that exosome-derived miRNAs play a crucial role in orchestrating the molecular events underlying HCM, offering new insights into disease mechanisms and potential therapeutic avenues. Understanding the intricate interplay between exosome-mediated miRNA communication and HCM pathophysiology holds promise for the development of personalized diagnostic tools and targeted therapies to improve patient outcomes in HCM.

In this paper, a completely different metaheuristic algorithm called the Orangutan Optimization Algorithm (OOA) is introduced, which replicates the complex and adaptive behaviors of Orangutans in their natural habitat. The main inspiration for OOA lies in the strategic foraging techniques of Orangutans, alongside their highly developed nesting abilities. More words are used to provide a detailed theoretical explanation of OOA, followed by a comprehensive modeling of the algorithm’s implementation in two key phases: exploration and exploitation. These phases are mathematically structured to ensure the balance required for optimal search processes. The performance of OOA is rigorously evaluated using twenty-nine benchmark functions from the CEC 2017 test suite, with problem dimensions of 10, 30, 50, and 100. More sentences are included to elaborate on the optimization outcomes, which reveal that OOA effectively balances the exploration and exploitation stages, yielding suitable and competitive solutions across the benchmark functions. Additionally, to further validate its quality, the results from OOA are compared against twelve other well-established metaheuristic algorithms. The analysis of these simulation results demonstrates that OOA consistently outperforms competing algorithms by achieving superior results across most benchmark functions. Furthermore, to assess its real-world applicability, OOA is implemented on a set of twenty-two constrained optimization problems drawn from the CEC 2011 test suite. The extended simulation results clearly indicate that OOA is highly efficient in solving real-world optimization challenges, consistently delivering a superior performance when compared to other competitor algorithms.

This study explores the synergistic integration of Artificial Intelligence (AI) in information technology with photochemical methods to optimize nanoparticle synthesis. By leveraging machine learning algorithms and predictive modeling, we demonstrate significant enhancements in the precision, efficiency, and scalability of nanoparticle production. AI-driven analysis of reaction parameters, optical properties, and structural characteristics enables real-time monitoring and adaptive optimization of photochemical reactions.The developed framework utilizes deep learning techniques to correlate reaction conditions with nanoparticle size, shape, and composition, facilitating the synthesis of tailored nanoparticles for various applications. Results show improved monodispersity, increased yield, and reduced synthesis time compared to traditional methods.This innovative approach paves the way for the rapid development of high-performance nanoparticles in fields such as biomedical imaging, energy storage, and catalysis. By harnessing the power of AI in information technology, this research unlocks new possibilities for the precise and efficient synthesis of nanoparticles via photochemical methods.

Federated unlearning represents a sophisticated evolution in the domain of machine learning, particularly within federated learning frameworks. In financial applications, where data privacy and security are paramount, federated unlearning allows institutions to selectively remove or “unlearn” specific data from trained models without compromising their overall performance and accuracy. This capability is essential for ensuring that models remain adaptable, secure, and compliant with regulatory requirements, while minimizing the need for expensive retraining. In this paper, we explore various financial applications where federated unlearning can have a significant impact, including fraud detection, portfolio management, and credit risk modeling. By allowing targeted removal of outdated, erroneous, or sensitive data, federated unlearning enhances the agility of financial models, enabling institutions to keep pace with the dynamic financial landscape. Using practical numerical examples, we demonstrate how unlearning improves model accuracy and decision-making while maintaining data privacy across distributed systems. This paper underscores the critical role of federated unlearning in addressing the challenges of modern financial institutions, offering insights into its practical applications and future potential.

The integration of advanced nanotechnology solutions in healthcare presents unparalleled opportunities for transformative care and cost savings. However, market penetration remains hindered by regulatory, technological, and adoption barriers. This study explores business analytics strategies facilitating successful market integration of nanotechnology innovations in healthcare. A mixed-methods approach combining qualitative expert interviews, quantitative survey analysis, and data-driven modeling is employed.Key findings highlight the critical role of data-driven decision-making, collaborative partnerships, and tailored market segmentation in overcoming adoption hurdles. Specifically, predictive analytics and machine learning algorithms are identified as essential tools for optimizing nanotechnology product development, pricing strategies, and supply chain efficiency. Furthermore, strategic partnerships with healthcare stakeholders and tailored market segmentation enable targeted commercialization and accelerated diffusion.This research contributes to the existing literature by providing actionable insights for nanotechnology firms, policymakers, and healthcare administrators seeking to harness the transformative potential of nanotechnology in healthcare. The proposed business analytics framework offers a valuable roadmap for navigating the complex healthcare landscape and ensuring the sustainable market integration of advanced nanotechnology solutions.

Within education, we make assumptions the correct manner of teaching a student, and with that, we assume further that regardless of the intellectual content that a student should engage with, the acculturation for the customary (and always rather traditional) means of religious apprehension for the purpose of an assumedly universal and beneficial role. This article instead promotes the view that such determinations are (1) unsuitable for modern society and (2) causal to a disjunction with a truly proper manner of education in the form of the matheticism – a term rather unfortunately applied in educational theory.

The integration of nanoparticles in biomedical applications requires precise analysis of their photochemical properties. However, computational simulations of these properties are computationally intensive, hindering rapid advancement. This study explores the implementation of Graphics Processing Unit (GPU) acceleration techniques to enhance computational efficiency in analyzing nanoparticle photochemistry within bioinformatics frameworks.By leveraging GPU parallel processing capabilities, we developed optimized algorithms for photochemical property simulations, achieving significant speedup over traditional Central Processing Unit (CPU)-based methods. Our GPU-accelerated framework demonstrated substantial performance gains in computing photochemical properties, such as absorption spectra and energy transfer rates.

This research investigates the influence of yoga on social intelligence and academic performance of business students. Employing a randomised controlled experiment with Executive MBA participants, the research explores the mediating role of mindfulness in these relationships. Results indicate that yoga positively influences social intelligence, decision-making skills as reflected in case study scores, and overall academic performance. Mindfulness is found to partially mediate these relationships, accounting for a significant portion of the observed effects. The study reveals that yoga directly contributes 43% to increased social intelligence, with improved mindfulness accounting for 57%. Similarly, yoga directly accounts for 46% of improved academic achievement, while enhanced mindfulness contributes 54%. These findings suggest that incorporating yoga into business education curricula could potentially enhance both the interpersonal capabilities and academic outcomes of students, preparing them more holistically for the challenges of the modern corporate world.

Background/Objectives: The COVID-19 pandemic has significantly impacted global health, with varying vaccine effectiveness (VE) across different regions and vaccine platforms. In Africa, where vaccination rates are relatively low, inactivated vaccines like Sinopharm and Sinovac have been widely used. This study evaluated the real-world effectiveness of licensed inactivated COVID-19 vaccines in Zimba-bwe during a period dominated by Omicron variants. Methods: We conducted a prospective test-negative case-control study among symptomatic adults across six Zimbabwean provinces from November 2022 to October 2023. Participants were categorized based on vaccination status, and na-sopharyngeal swabs were collected for SARS-CoV-2 PCR testing. Vaccine effective-ness was assessed using conditional logistic regression, adjusting for various co-variates such as age, sex, and comorbidities. Results: Among 5,175 participants, 701 tested positive for SARS-CoV-2, and 4,474 tested negative. The overall adjusted VE against symptomatic COVID-19 was 31% (95% CI: 5.3%-49.7%) among verified vaccinated individuals. Boosted individuals demonstrated a higher VE of 59.8% (95% CI: 40.3%-72.9%). VE decreased signifi-cantly to 24% (95% CI: -4.1%-44.8%) in individuals vaccinated over a year prior. Similar VE was observed for Sinopharm (36.8%, 95% CI: 11.4%-54.9%) and Sino-vac (38.1%, 95% CI: 16.3%-54.2%). Conclusions: The study indicates modest protection from inactivated COVID-19 vaccines against symptomatic Omicron infection, with significant enhancement fol-lowing booster doses. These findings highlight the need for continued vaccine eval-uation, particularly in resource-limited settings, to inform public health strategies and optimize vaccination programs.

The rat osteosarcoma cell line UMR-106 is widely used for the study of bone cancer biology. We have characterized UMR-106 with a combination of optical genome mapping (OGM), long-read sequencing (for identification of variants and 5mC methylation), and short-read RNA sequencing for expression. Genome sequence was compared to a Sprague-Dawley control animal, the strain from which UMR-106 was derived, and expression data were compared to a public rat osteoblast dataset. Using the COSMIC database to identify the most affected genes in human osteosarcomas (OS) we found somatic mutations in Tp53 and H3f3a in UMR-106. OGM identified a relatively small number of differences between the cell line and a strain-matched control animal but did detect a ~45 Mb block of amplification that included Myc on chromosome 7 which was confirmed by long-read sequencing. The amplified region showed several blocks of non-contiguous rearranged sequence implying complex rearrangements during their formation and included 14 genes reported as biomarkers in human osteosarcoma, many of which also showed increased transcription. A comparison of 5mC methylation from the nanopore reads of tumor and control identified several genes with distinct differences including the OS marker Cdkn2a. This dataset illustrates the value of long DNA methods for the characterization of cell lines and how inter-species analysis can inform about the genetic nature underlying mutations that underpin specific tumor types. The data should be a valuable resource for investigators studying osteosarcoma, in general, and specifically the UMR-106 model.

Tussilago farfara L. is a traditional medicinal plant valued for its potentially health-promoting metabolites. Its herbal raw material has been recognized and used since ancient times and continues to be widely used in traditional medicine. Introducing these plants to in vitro cultivation is a challenging task, but once the protocol is developed, such cultures can provide an abundant and inexhaustible source of plant material. In this study, we report the successful induction and growth of vigorous T. farfara L. callus in vitro. Callus induction was achieved on solid media in darkness, whereas it appeared inefficient under light conditions and in suspension culture. We present a detailed description of callus growth kinetics, morphological analysis, photosynthetic activity and biochemical parameters (including protein content and photosynthetic pigments) supported by histological studies. Furthermore, we observed potential for organogenesis and somatic embryogenesis. This method for in vitro propagation of T. farfara, along with callus culture maintenance, offers a wide range of applications in pharmacy and could benefit the environment by minimizing the depletion of natural populations of this species.

Non-immunoglobulin based scaffold proteins (SPs) represent one of the key therapeutic target-specific and high-affinity binders in modern medicine. Among their cellular targets are signaling receptors, in particular, receptor tyrosine kinases, whose dysfunction leads to the development of cancer and other serious diseases. Successful applications of SPs have been reported for HER receptor type 2 (HER2), the member of the human epidermal growth factor receptor family that regulates the cell growth and differentiation. To extend blood residence of SPs and prevent their high accumulation in kidney, these proteins are often fused with serum albumin. Promising results for the HER2-binding activity were obtained for SP G3 from DARPins (Designed Ankyrin Repeat Proteins) family fused with albumin-binding domain (ABD) [1]. Interestingly, detected HER2-G3 binding strongly depended on the position of G3 module in the sequence of the constructs. Further improvement of these constructs for biomedical applications requires deciphering the molecular mechanism responsible for this effect. Here, we investigate the structural and dynamic aspects of ABD-G3 and G3-ABD chimeras using NMR spectroscopy and molecular modeling. Based on biophysical data, we came to the conclusion that extensive interdomain contacts form in both constructs, although the binding interfaces and complex stability are somewhat different. Also, it was shown that the domain linker plays an important role – it limits the accessibility of detected protein-protein binding sites depending on the order of the domains in chimeric molecules. The results create a solid structural basis for the rational design of new effective SP-constructs targeting signaling receptor in the cell.

Is there a qualitative difference between apes’ and human Theory-of-Mind (or ability to estimate others’ mental states)? After opting for the idea that expectations are empty profiles that recognize a particular content when it arrives, I apply the same description to ‘vicarious expectations’ –very probably present in apes. Thus, (empty) vicarious expectations and one’s own (full) contents are distinguished without need of meta-representation. Then, three proposals are made. First, vicarious expectations are enough to support apes’ Theory-of-Mind (including ‘spontaneous altruism’). Second, since vicarious expectations require a profile previously built in the subject that activates them, this subject cannot activate any vicarious expectation of mental states that are intrinsically impossible for him. Third, your mental states that think of me as a distal individual are intrinsically impossible states for me, and therefore, to estimate them, I must estimate your mental contents. This ability (the original nucleus of human Theory-of-Mind) is essential in human lifestyle. It is involved in unpleasant and pleasant self-conscious emotions, which respectively contribute to ‘social order’ and to cultural innovations. More basically, it makes possible the human (prelinguistic or linguistic) communication, since it originally made possible the understanding of others’ mental states as states that are addressed to me, and that are therefore impossible for me.

Despite offering several potential benefits over standard prosthetic aortic valve replacement, the use of the pulmonary autograft has been limited to date, due to concerns over the risk of pulmonary autograft expansion and the need for reintervention. Several techniques using materials with biomimetic potential have been developed to reduce this complication. The incidence, risk factors and pathophysiology of pulmonary autograft dilatation are discussed in this article. This seminar will provide an overview of the techniques of external pulmonary autograft support and their advantages and limitations. It also considers future directions for further investigation and future clinical applications of external pulmonary autograft support. Dilatation of the autograft is more likely to occur in patients with aortic regurgitation and a dilated aortic annulus. External scaffolding may prevent autograft stretching and expansion in these specific cases. However, from a biomimetic point of view, any permanent scaffold potentially restricts the movement of the autograft root. This reduces some of the benefits associated with the use of autologous tissue, which is the priority of the Ross procedure. To address this issue, several bioresorbable matrix could be used to support the root during its initial adaptive phase. Control of blood pressure with aggressive therapy is the first line to avoid this problem in the first year after pulmonary autograft implantation, together with support of the annular and sino-tubular junction in some selected cases. This is the best way to maintain stable autograft root dimensions while preserving root dynamics. However, to determine the efficacy of this combined external support and best medical management, it is important to perform regular imaging and clinical follow-up.

Gene therapy is a medical approach capable of correcting genetic and epigenetic alterations in pathological conditions, including cancer. Different strategies have been pursued for cancer gene therapy, aiming to restore the function of tumor suppressor genes or inhibit oncogenes. These comprise the use of CRISPR/Cas9 gene editing technology and therapeutic oligonucleotides, such as microRNAs, anti-microRNAs, small interfering RNAs, DNAzymes, and epigenetic modifiers. However, despite great potential, their broad clinical use is hindered due to the lack of safe and efficient systems for targeted delivery to cancer cells. To this purpose, aptamers could represent an ideal tool. They are short single-stranded oligonucleotides that bind receptors selectively present or overexpressed on cancer cell membranes, often undergoing cell-specific internalization. Thanks to this last feature, numerous internalizing aptamers have been investigated as targeting moiety to deliver therapeutic oligonucleotides, viral vectors, and nanoparticle-based systems in preclinical studies. Here, we summarize the state-of-the-art of aptamer applications in cancer gene therapy, providing key examples and discussing their advantages, limitations, and clinical perspectives.

The immune system attempts to eliminate foreign substances, such as pathogens and viruses, that invade the body. As normal cells transform into cancerous cells, the immune system can eliminate these cells and suppress cancer onset. The immune system is regulated so that it does not become overactive or attack normal cells. When cancer cells transform from normal cells, they acquire various characteristics, and some cancer cells influence the regulatory function of the immune system to suppress it and escape immune attack. Therefore, treatments have been developed to eliminate the suppression of the immune system by cancer cells and to restore the immune system's ability to eliminate cancer cells. Immunotherapies include immune checkpoint inhibitors, cytokines, cancer vaccines, and effector cell therapies. Cytokine therapy activates the immune system by injecting substances produced by immune cells (such as interleukin 2 and interferon alpha) into the body, thereby increasing the ability of the immune system to attack cancer cells. Cancer vaccine therapy enhances the attack on cancer cells by injecting substances (antigens) that serve as markers for cancer cells into the body to make it easier for immune cells to detect the cancer. Depending on the type of antigen, cancer peptides, tumor cells, and dendritic cell vaccines are available. Effector cell therapy is a treatment method in which immune cells that directly attack cancer cells (CD8+ T cells, NK cells, etc.) are taken from the patient's body, expanded outside the body, activated, and returned to the body to attack cancer cells. To develop these treatments, it is essential to understand the cells and molecules related to immunity as well as the local tumor environment. In this article, we consider the factors related to antitumor immunity.

Cow milk is rich in proteins, fats, carbohydrates, and minerals, and its nutrient content depends on various factors. We tested differences in fatty acid and protein contents of milk from seven breeds and regions, including three dairy breed samples: Holstein milk from Beijing, China (BH); Holstein milk from Hebei province, China; Jersey milk (JS); and four dairy/meat cow samples: Sanhe milk, Xinjiang brown milk (XH), Simmental milk, and Shu Xuanhua milk. Breed significantly affected total fat, fatty acid, and protein contents. The region significantly affected the contents of different fatty acids, α-lactalbumin, and lactoferrin. JS had the highest total fat, most fatty acids, and casein contents. XH performed well with significantly higher unsaturated fatty acid content than BH, which was not significantly different from JS, and its protein composition of low β-lactoglobulin and high lactoferrin was more similar to breast milk, which may thus be favorable to the growth and development of children. Our results may inform the development of dairy products from different cow breeds and advance the process of accurate breed identification.

Oncolytic measles virus (MeV) is a promising anti-cancer treatment. However, the production of high titers of infectious MeV (typically 10⁷–10⁹ TCID₅₀ per dose) is challenging because the virus is unstable under typical production conditions. The objective of this study was to investigate how the multiplicity of infection (MOI) and different media – serum-containing (SCM), serum-free (SFM) and chemically-defined (CDM) – affect MeV production. We infected Vero cells at MOIs of 0.02, 0.2 or 2 TCID₅₀ mL^-1 and the lowest MOI resulted in the largest number of infected cells towards the end of the production period. However, this did not equate to higher maximum MeV titers, which were similar for all MOIs. The medium had a moderate effect, generating maximum titers of 0.89–2.17 × 10⁶, 1.08–1.25 × 10⁶ and 4.58–9.90 × 10⁵ TCID₅₀ mL^‑1 for SCM, SFM and CDM, respectively. Infection at a low MOI often required longer process times to reach maximum yields. Our findings show that SCM, SFM and CDM are equally suitable for MeV production in terms of yield and process time. This will allow MeV production in serum-free conditions, addressing the safety risks and ethical concerns associated with the use of serum.

Despite improvements in participation in population-based screening programs, colorectal cancer remains a major cause of cancer-related mortality worldwide. Targeted interventions are desirable to reduce the health and economic burden of this disease. Two-dimensional monolayers of colorectal cancer cell lines represent the traditional in vitro models for disease and are often used for diverse purposes, including delineation of molecular pathways associated with disease aetiology or to gauge drug efficacy. The lack of complexity in such models, chiefly the limited epithelial cell diversity and differentiation, attenuated mucus production, lack of microbial interactions and mechanical stresses, has driven interest in development of more holistic and physiologically relevant in vitro model systems. In particular, established ex vivo patient-derived explant and patient-derived tumour xenograft models have been supplemented by progress in organoid and microfluidic organ-on-a-chip cultures. Here we discuss the applicability of advanced culturing technologies, such as organoid systems, as models for colorectal cancer and for testing chemotherapeutic drug sensitivity and efficacy. We highlight current challenges associated with organoid technologies and discuss their future for more accurate disease modelling and personalized medicine.

Evaluating aviation emissions and examining the dispersion properties of contaminants are crucial for understanding atmospheric pollution. To more properly assess the pollutant emissions and dispersion of aircraft during the landing and take-off (LTO) cycle, and to more effectively address air pollution surrounding the airport resulting from flight operations, this study assessed emissions throughout the LTO phase utilizing Quick Access Recorder (QAR) data in conjunction with the first-order approximation method. An improved Gaussian diffusion model for mobile point sources is employed to examine the diffusion characteristics of contaminants. Additionally, CFD calculation outcomes for various exhaust velocities and wind speeds were utilized to validate the trustworthiness of the improved Gaussian model. The discussion also encompasses the influence of diffusion time, wind direction, wind speed, temperature gradient, and particle deposition on the concentration distribution of contaminants. The findings indicated that the Gaussian diffusion model aligned with the results of the CFD calculations. The diffusion distribution of contaminants around airports varies over time and is significantly influenced by atmospheric environmental factors, including wind direction, wind speed, and atmospheric stability.

Older people with sleep disturbances also have other chronic pathologies that may interfere with these disturbances. One of the comorbidities that is frequently present is type II diabetes. Objetives: This research aims to find out whether type 2 diabetes mellitus present in elderly people affects the level of severity of obstructive sleep apnoea syndrome (OSAS). Methods: Cross-sectional descriptive study, with a sample of 75 elderly people who attended the Sleep Unit of Doctor Sagaz Hospital in Jaen to be diagnosed with OSAS, and classified according to severity. Results: Significant differences were obtained in the severity of OSAHS between the participants who had type II diabetes mellitus and those who did not, with the former showing higher scores (U=326, p=0.02). Conclusions: Therefore, the presence of type 2 diabetes in the el-derly in our study was associated with more severe OSA. The main discrepancies when compar-ing this research with other studies result from the lack of research addressing these variables in this population group, as well as from the great heterogeneity of methods and techniques used in the different studies (different sample sizes, age range of the population, and diagnostic methods used), causing great variability in the results found. Given the findings obtained in this research, we hope to contribute to future translational research and improve the quality of life of this population.

Approximate unlearning is an emerging field in machine learning that addresses the challenge of efficiently removing specific data points from models without the need for full retraining. In the financial sector, where models are built on sensitive customer data and market information, the ability to unlearn data is crucial for meeting privacy regulations like GDPR and ensuring model adaptability in real-time environments. This paper explores the categorization of approximate unlearning into two main approaches: data-driven approximation and model-driven approximation. Data-driven approximation focuses on selectively retraining parts of the dataset to simulate the removal of data, while model-driven approximation adjusts the model’s internal parameters to nullify the influence of unwanted data points. Both methods offer computational and memory-efficient ways to balance the need for privacy compliance with the performance demands of financial models. The paper discusses practical applications in algorithmic trading, fraud detection, and risk assessment, and highlights the challenges associated with each approach. Through case studies and literature references, we demonstrate how approximate unlearning can be applied to maintain system efficiency, data privacy, and regulatory compliance in the financial domain. This research provides a roadmap for future developments in approximate unlearning, particularly in the context of real-time financial systems and federated learning environments.

Human activities continuously alter the delivery of ecosystem services (ESs), which play a crucial role in human well-being. There is a pressing need for effective ecological management strategies that consider the spatial heterogeneity of ESs to support the transition from trade-offs to synergies. This study focuses on the Haba River Basin and examines characteristics of land use change and the shift from trade-offs to synergies. The results indicate that from 1990 to 2000, the initial phase of land development, 10.65% of the land experienced change. Subsequently, during the intensive period of land development from 2000 to 2010, 30.29% of the land underwent significant transformation, with approximately 78% of grassland, sparse grassland, forested land, and desert converted into arable land. However, between 2010 and 2020, as the focus shifted towards the establishment of native vegetation and the intensity of land development decreased, only a small percentage (3.65%) of the total area underwent changes. Based on an in-depth analysis of spatial heterogeneity from 1990 to 2020, it is believed there has been a shift from trade-offs to co-benefits between 2000-2010 and 2010-2020. The years 2010 and 2020 were pivotal time nodes for the transition from trade-offs to synergies and for reducing trade-offs, with NPP identified as a critical driving factor for Comprehensive ES （CES） functions. By considering the trade-offs/synergies relationship and hotspots of ecological service functions, combined with unified water resource management policies, comprehensive ecological management measures tailored to different regions are proposed. These measures have facilitated the implementation of robust ecological protection policies to shift ES development from trade-offs to synergies in arid areas, thereby enhancing overall ecosystem service functions in the Haba River Basin. The research findings offer crucial scientific support and guidance for ecosystem management in arid areas, particularly within Central Asia.

Music has been proposed for a long time as a treatment for mental disorders. However, some special types of music or stimulating sounds might induce negative emotions. Herein, 8-week-old male mice were exposed to two specific genres of music, hip-hop (HH) and heavy metal (HM), and construction noise (CN), and a series of behavioral experiments were performed to evaluate the impact of these music or sounds on the emotion of mice. The experiment lasted 1 week in which 8-week-old male mice were used as animal models. We found that long term exposure HM, HH, and CN induced depressive symptoms with a decrease in dopamine receptor 1 and BDNF in the mixture of hippocampus and frontal cortex of mice. Our results have highly addressed that certain special types of sound or music might induce negative emotions and loss of dopaminergic neurons in mice, and it is necessary to intervene in adolescences who are exposed to these music or sounds for a long time.

Cutaneous squamous cell carcinoma (cSCC) is the second most common form of skin cancer, with an increasing global incidence. While most cases are successfully treated with surgical excision, a subset can metastasize, leading to significant morbidity and mortality. Current staging systems based on clinical and histopathological features have shown limitations in accurately predicting metastatic risk. This review examines the role of gene expression profiling (GEP), particularly the 40-gene expression profile (40-GEP) test, in improving risk stratification and management of cSCC. We assess the prognostic value of the 40-GEP test, its integration with current staging systems, and its impact on clinical decision-making. Recent studies suggest that incorporating GEP results with traditional staging methods can enhance the identification of high-risk patients, potentially leading to more personalized treatment strategies. The review also explores the challenges of implementing GEP in routine clinical practice, including cost-effectiveness considerations and the need for standardization. Finally, we discuss the implications for future cSCC management and highlight areas for further research. As molecular profiling techniques continue to evolve, GEP represents a promising approach to optimizing care for cSCC patients, aligning with the growing emphasis on personalized medicine in oncology.

The infections of bacterial origin represent a significant problem to public healthcare worldwide both in clinical and community settings. Recent decade was marked by limiting treatment options for bacterial infections due to growing antimicrobial resistance (AMR) acquired and transferred by various bacterial species, especially the ones causing healthcare-associated infections, which has become a dangerous issue noticed by the World Health Organization. Numerous reports shown that the spread of AMR is often driven by several species-specific lineages usually called the ‘global clones of high risk’. Thus, it is essential to track the isolates belonging to such clones and investigate the mechanisms of their pathogenicity and AMR acquisition. Currently, the whole genome-based analysis is increasingly used for these purposes, including epidemiological surveillance and analysis of mobile elements involved in resistance transfer. However, in spite of the exponential growth of available bacterial genomes, their representation usually lack uniformity and availability of supporting metadata, which creates a bottleneck for such investigations. In this dataset, we provide the results of a comprehensive genomic epidemiology analysis of 61,857 genomes of a dangerous bacterial pathogen Klebsiella pneumoniae. Important typing information including multilocus sequence typing (MLST)-based sequence types (STs), assignment of the isolates to known global clones, capsular (KL) and lipooligosaccharide (O) types, presence of CRISPR-Cas systems, and cgMLST profiles are given, and the presence of AMR and virulence genes within the genomes is also reported. This dataset will be useful for researchers in the field of K. pneumoniae genomic epidemiology, resistance analysis and prevention measure development.

This paper introduces an open-source active high-precision signal amplifier designed for enhancing biodata acquisition, specifically focusing on EEG signals. The compact device, with a diameter of 18 mm, seamlessly integrates electronics, signal processing, and meticulous design considerations. Incorporated within the single board are circuits for low-noise amplification, an analog interface equipped with bandpass filters, and an integrated ADC for precise digitization. A comprehensive evaluation of signal quality has been conducted, encompassing aspects such as noise levels, electrode bias tolerance, and common mode rejection ratio. To facilitate this evaluation, the widely recognized Silver Chloride electrode (Ag/AgCl) has been employed. Additionally, this paper delves into an extensive discussion concerning diverse sources of noise, along with strategies to curtail input noise and minimize noise originating from electrodes and amplifiers. Leveraging the substantial advancements achieved in the design of dry contact electrodes, this specific device is poised to carve a notable niche in the realm of brain-computer interface.

Contaminated soils are a challenge for implementing biotechnology in bioremediation, recovery of Critical and Strategic Raw Materials (CRMs and SRMs), and food security. European Union (EU) Governments have established strict limits on As, Pb, Cd, and Hg in foods (Document 32023R0915), and requested the recovery of 34 CRMs within a circular economy (CE) (5th CRMs list). This study proposed a biotechnological tool for the decontamination of soil with heavy metal(loids) by arbuscular mycorrhizal (AM)-assisted phytoextraction and subsequent recovery of CRMs, or by phytostabilization to prevent their entry into the food chain. It consisted of placing Baccharis salicifolia plants, inoculated or non-inoculated with AM fungi, into Bioreactors (BRs) containing mining soil with Cd, Ni, and Cu, according to the argentinian Patent (AR090183B1). The bioextractive potential (BP) was also estimated at the highest Technological Readiness Level (TRL) using a Vegetable Depuration Module (VDM, TRL 6). Inoculated plants showed significantly higher aerial bioaccumulation coefficients (Cd: 68.62; P: 2.99; Ni: 2.51; Cu: 0.18) in BRs, and the BP values reached 1.16 g, 9.75 g, 2.40 g, and 213.1 g for Ni, Cd, Cu, and P, respectively. Finally, those CRMs and SRMs could be recovered from biomass through hydrometallurgy within a CE framework.

In the industrial sector, intelligent sensors in fault diagnosis are becoming more critical in recent technological improvements. The prediction accuracy can be enhanced in fault diagnosis using 3-dimensional, sequential, real-time, and image data. Sensors that capture the vibration, sound, and image data are more critical in predicting unbalancing, tool wear, crack, misalignment, etc, in the rotating machinery to increase productivity and to provide an effective maintenance management system. Due to the fast development of industry 4.0 techniques, monitoring of mechanical machinery is experiencing explosive growth and getting more attention in the area of fault diagnosis (FD). Machine learning and Deep learning methods give promising results and accuracy in predicting faults in rotating machinery on shop floors. The success of AI-based models is due to the availability of comprehensive labeled data. Federated Learning (FL) is the machine learning subfield aiming to train an algorithm with a heterogeneous dataset. Data transmission from local facilities to a central server in AI models creates data privacy and security issues. Heterogeneous data analysis is a complicated process in predicting the machine fault in the central server because of millions of data during real-time condition monitoring. Decentralized data handling and analysis is mandatory in condition monitoring because of heterogeneity in data processing, data privacy, and security advantages. The application of federated learning in fault diagnosis has been getting more attention in recent days, and this study is a review of FL applications that address fault diagnosis in rotating machinery in the first phase. A comparison between the types of FL approaches in FD and the use of aggregation algorithms and their applications will also be discussed in Phase 1. In phase 2, a novel methodology has been proposed using Federated learning to diagnose rotating machinery faults. The proposed method, FLOACOS, addresses how prediction challenges are solved using federated learning approaches by optimizing and standardizing the data at local facilities. This work will be helpful for future condition monitoring researchers and gives an overview of a novel method of the FL technique used in predicting faults and the progress made in the maintenance management of rotating machinery.

In this study, we provided an empirical testability of the FF3FM against the co-moment-augmented FF3FM using the Newey–West GMM methods to account for potential endogeneity. The results showed that value risk is not significantly priced, and systematic skewness and systematic kurtosis play more important roles in explaining asset return than market and size factors. We discovered that there is much to gain in moving from the incumbent FF3FM to the co-moment-augmented FF3FM. By extending this study to Nigeria and using out-of-sample data that span across the recent COVID-19 period, the study has contributed to existing knowledge significantly. The study concludes that the co-moment-augmented FF3FM is superior to the incumbent FF3FM in pricing assets, and the anomalies associated with the return-size risk factor relationship are reduced by accounting for systematic skewness and systematic kurtosis in the FF3FM. Therefore, we recommend that investors should take a long position in size-hedged portfolios and hold systematic skewness and kurtosis as constant, and vice visa.

Sex differences in brain metabolism and their relationship to neurodegenerative diseases like Alzheimer's are an important emerging topic in neuroscience. Intrinsic anatomic and metabolic differences related to male and female physiology have been described, underscoring the importance of considering biological sex in studying brain metabolism and associated pathologies. The hippocampus is a key structure exhibiting sex differences in volume and connectivity. Adult neurogenesis in the dentate gyrus, dendritic spine density, and electrophysiological plasticity contribute to the hippocampus' remarkable plasticity. Glucose transporters GLUT3 and GLUT4 are expressed in human hippocampal neurons, with proper glucose metabolism being crucial for learning and memory. Sex hormones play a major role, with the aromatase enzyme that generates oestradiol increasing in neurons and astrocytes as an endogenous neuroprotective mechanism. Inhibition of aromatase increases gliosis and neurodegeneration after brain injury. Genetic variants of aromatase may confer higher Alzheimer's risk. Oestrogen replacement therapy in postmenopausal women prevents hippocampal hypometabolism and preserves memory. Insulin is also a key regulator of hippocampal glucose metabolism and cognitive processes. Dysregulation of the insulin-sensitive glucose transporter GLUT4 may explain the comorbidity between type II diabetes and Alzheimer's. GLUT4 colocalizes with the insulin-regulated aminopeptidase IRAP in neuronal vesicles, suggesting an activity-dependent glucose uptake mechanism. Sex differences in brain metabolism are an important factor in understanding neurodegenerative diseases and future research must elucidate the underlying mechanisms and potential therapeutic implications of these differences.

The idea of developing a robot controlled by iris movement to assist physically disabled individuals is indeed innovative and has the potential to significantly improve their quality of life. This technology can empower individuals with limited mobility and enhance their ability to interact with their environment. Disability of movement has huge impact on the life of physically disabled people. Therefore, there is need to develop a robot which can be controlled using iris movement. The main idea of this work revolves around iris recognition from an eye image, specifically identifying the centroid of the iris. The centroid's position is then utilized to issue commands to control the robot. This innovative approach leverages iris movement as a means of communication and control, offering a potential breakthrough in assisting individuals with physical disabilities. The proposed method aims to improve the precision and effectiveness of iris recognition by incorporating advanced segmentation techniques and fuzzy clustering methods. The fast gradient filters using a fuzzy inference system (FIS) is employed to separate the iris from its surroundings. Then, the bald eagle search (BES) algorithm is employed to locate and isolate the iris region. Subsequently, the Fuzzy KNN algorithm is applied for the matching process. This combined methodology aims to improve the overall performance of iris recognition systems by leveraging advanced segmentation, search, and classification techniques. The results of the proposed model are validated using True Success Rate (TSR) and compared to other existing models. The results highlight the effectiveness of the proposed method for the 400 tested images representing 40 people.

Trajectory planning determines whether a UAV can successfully complete its mission, and the reasonable planning of UAV trajectory in 3D environment is a complex global optimization problem, which needs to take into account many constraints such as urban environment, mountain terrain, obstacles, no-fly zones, flight boundaries, flight distances, and trajectory change rates. In view of the shortcomings of the whale optimization algorithm in 3D trajectory planning, such as slow convergence speed, low accuracy and easy to fall into the local optimum, this paper increases the diversity of the initial population through the introduction of the reverse learning mechanism, and optimizes the coordination of the global and local search ability by integrating the nonlinear convergence factor and the random number generating mechanism, so as to realize the improved whale optimization algorithm that can cope with the higher degree of freedom and the more complex constraints. The simulation results show that the optimization algorithm has improved the convergence accuracy by 22.1% and reduced the standard deviation by 74.1%, which can effectively deal with the 3D UAV path planning problem.

Objectives: The aim of this study was to evaluate the levels of physical literacy (PA) in primary school children in Santiago, Chile, and to explore the relationship between PA and body mass index (BMI). In addition, gender and age differences were analyzed in relation to PA levels in a context where childhood obesity remains a public health challenge. Methods: 439 students in grades 5-8 were assessed using the Canadian Assessment of Physical Literacy - 2 (CAPL-2) questionnaire. Demographic variables (sex, age, and BMI) were correlated with levels of motivation to engage in physical activity and physical activity knowledge. Chi-square were applied with acceptable significance p<0.050 and good p<0.010. Results: The results revealed a significant correlation between motivation for physical activity and gender, with boys showing higher levels of motivation than girls. In addition, an inverse relationship was observed between BMI and motivation, suggesting that more motivated children tend to have a healthier BMI. Knowledge about physical activity increased with age, but did not have a significant influence on BMI. Conclusions: The findings highlight the need to design gender-specific interventions to promote PA and physical activity adherence, with motivation being a key factor in promoting a healthy lifestyle. Public health policies should address these factors to improve pediatric health in Chile.

Rice cultivation stands as a cornerstone of Sri Lanka's economy, serving as a vital source of em-ployment for rural communities. However, the constraints of limited land availability have prompted an escalating dependence on agrochemicals, notably for pest management, thereby posing significant threats to human health and the environment. This review delves into the ex-ploration of silica nanoparticles as a promising eco-friendly substitute for conventional pesticides in the context of Sri Lankan rice farming. It comprehensively examines various aspects including the synthesis methods of silica nanoparticles, their encapsulation with synthetic pesticides, and an evaluation of their efficacy in pest control. Furthermore, it sheds light on the innovative utilization of agricultural waste such as rice husk and straw in the production of silica-based nano-pesticides. This approach not only demonstrates a shift towards sustainable agricultural practices but also aligns with the principles of green chemistry and circular economy, offering a holistic solution to the challenges faced by the rice farming sector in Sri Lanka.

This study investigated the characteristics and outcomes of drug-resistant tuberculosis patients in selected rural healthcare facilities in the Eastern Cape, South Africa. A retrospective review of clinical records from 456 patients, covering the period from January 2018 to December 2020, revealed that a statistically significant relationship between DR-TB types and age groups (Chi-square statistic: 30.74, p-value: 0.015). Younger adults (19-35 years) and middle-aged adults (36-50 years) are more frequently affected by RR-TB and MDR-TB, which are the most prevalent forms of DR-TB. Less common types, including Pre-XDR, XDR, and INH TB, were observed in smaller numbers. The study suggests that DR-TB imposes a heavy burden on the working-age population. Gender analysis shows that while the frequency of DR-TB differs between males and females, the percentage distribution of DR-TB types is relatively equal. Both genders are predominantly affected by RR-TB and MDR-TB, which together account for nearly 90% of cases. Pre-XDR, XDR, and INH-resistant TB are much less common, comprising only a small percentage of cases in both males and females. High-risk behaviors such as smoking and drinking are linked to a wider diversity of DR-TB types, while occupations like mining and prison work show higher rates of RR-TB and MDR-TB. In HIV-positive individuals, DR-TB is more common, but the distribution of DR-TB types between HIV-positive and negative groups shows no statistically significant difference. However, HIV-positive individuals have a 20% lower survival rate (65%) compared to HIV-negative patients (85%). Financial stability and comorbidities also significantly influence outcomes, with patients having stable income and fewer high-risk comorbidities experiencing better survival and treatment outcomes. The findings underscore the importance of addressing socioeconomic disparities and strengthening healthcare infrastructure to improve DR-TB treatment outcomes in rural Eastern Cape.

Alzheimer's disease (AD) is the most prevalent form of dementia. With the global aging population, the incidence of AD and related dementias is projected to rise dramatically, posing significant public health challenges. Traditionally, the diagnosis of AD has relied on the detection of amyloid-beta (Aβ) plaques and neurofibrillary tangles of hyperphosphorylated tau in the brain, assessed through invasive cerebrospinal fluid (CSF) analysis and costly positron emission tomography scans. However, these methods are not feasible for widespread screening or use in low-resource settings. Recent advances in blood-based biomarkers offer a promising alternative for the early detection and monitoring of AD. These biomarkers provide a minimally invasive, cost-effective means of tracking the pathological progression of AD before the onset of clinical symptoms, potentially enabling earlier and more accurate diagnosis. Blood-based biomarkers, including those related to Aβ, phosphorylated tau, and neurofilament light polypeptide, have demonstrated significant potential in reflecting the underlying neuropathology of AD and correlating with traditional CSF and imaging biomarkers. This review synthesizes the latest research on blood-based biomarkers in AD, highlighting their role in the disease's etiopathogenesis, diagnostic accuracy, and prognostic value. We discuss the emerging evidence on proteinopathies, neuroinflammation, vascular pathology, and bioenergetic profiles, emphasizing the clinical applicability of these biomarkers. Furthermore, we explore the integration of blood-based biomarkers with advanced neuroimaging techniques and their potential to revolutionize the diagnostic landscape of AD, particularly in resource-limited settings. We have integrated protein-protein interaction (PPI) and miRNA network analyses to enhance the analysis. By incorporating these, we can explore the interactions and relationships between different proteomic, genomic, and epigenomic biomarkers, potentially unveiling new insights into the underlying biological mechanisms of AD. The continued development and validation of these biomarkers could lead to more accessible and equitable AD diagnostics, ultimately improving patient outcomes.

Ceratitis capitata (Wiedemann) (medfly) strongly affects Argentinean fruit production and export. Augmentative biological control using the exotic parasitoid Diachasmimorpha longicaudata (Ashmead) is currently applied. The ability to find and parasitize medfly larvae on a wide diversity of fruit host species is a key issue to be analyzed. This research assessed the effect of the physical features of fruit on the preference of foraging D. longicaudata females and the influence of varying release density on parasitoid performance as a pest mortality factor in three fruit species. Trials were performed inside field cages under semi-arid environmental conditions in Argentina's central–western fruit-growing region. Sweet orange, peach, and fig were tested. Fruits were inoculated with third-instar larvae of the Vienna-8 temperature-sensitive lethal medfly strain. Naïve, 5-d-old mated D. longicaudata females were released in cages at 20, 40, 80 and 160 parasitoid densities. The highest levels of medfly mortality and parasitoid emergence were recorded in fig and peach, although D. longicaudata also induced mortality in orange, a fruit with few physical features favorable to parasitism. The medfly mortality in all fruit host species significantly increased with increased parasitoid females released into field cages. Diachsmimorpha longicaudata has high potential as a medfly biocontrol agent.

Waveform generation as part of an on-chip built-in self-test (BIST) circuitry often necessitates sufficient linearity without expensive hardware overhead. Achieving high linearity is critical for accurate signal generation, especially in applications requiring high precision, such as biomedical and instrumentation. Currently, achieving the high linearity and precision required in signal generators often relies on costly hardware such as automated test equipment (ATE). This paper presents a DAC based hardware synthesizable arbitrary waveform generator. We use a low-cost DAC and a fully digital on-chip testing and calibration approach to nullify the effect of the DAC’s non-linearity on the generated waveform. The ultra-low cost and high linearity benefit of the proposed waveform generator makes it highly suitable for integration into resource-constrained systems. The proposed approach is validated using simulation results of the small-area DAC designed in TSMC 0.18um technology and the testing and calibration algorithms implemented in MATLAB. The DAC, designed with a matching accuracy at only the 5-bit level, is able to generate a signal with an ENOB of 12 bits alongside a SFDR and THD surpassing 100 dB. This high level of signal purity is consistently maintained across 100 Monte-Carlo simulations, demonstrating the robustness of the architecture against PVT variations as well as random mismatches.

Amphibians, which are essential components of ecosystems, are susceptible to pharmaceutical contamination, a phenomenon of increasing concern owing to the widespread consumption and detection of pharmaceutical compounds in environmental matrices. This review investigates oxidative stress (OS) as the primary mechanism of drug toxicity in these organisms. The evidence gathered reveals that various pharmaceuticals, from antibiotics to anesthetics, induce OS by altering biomarkers of oxidative damage and antioxidant defense. These findings underscore the deleterious effects of pharmaceuticals on amphibian health and development and emphasize the necessity of incorporating OS biomarkers into ecotoxicological risk assessments. Although further studies on diverse amphibian species, drug mixtures, and field studies are required, OS biomarkers offer valuable tools for identifying sublethal risks. Furthermore, the development of more refined OS biomarkers will facilitate early detection of adverse effects, which are crucial for protecting amphibians and their ecosystems. Ultimately, this review calls for continued research and mitigation strategies to safeguard biodiversity from pharmaceutical contamination.

Let $\mathcal{M}(\Spin(8,\mathbb{C}))$ be the moduli space of $\Spin(8,\mathbb{C})$-Higgs bundles over a compact Riemann surface $X$ of genus $g\geq 2$. The triality automorphism of $\Spin(8,\mathbb{C})$ acts on $\mathcal{M}(\Spin(8,\mathbb{C}))$ and those Higgs bundles that admit a reduction of structure group to $G_2$ are fixed points of this action. This defines a map of moduli spaces of Higgs bundles $\mathcal{M}(G_2)\rightarrow\mathcal{M}(\Spin(8,\mathbb{C}))$. In this work, the action of the triality automorphism is extended to an action on the Hitchin integrable system associated to $\mathcal{M}(\Spin(8,\mathbb{C}))$. In particular, it is checked that the map $\mathcal{M}(G_2)\rightarrow\mathcal{M}(\Spin(8,\mathbb{C}))$ restricts to a map at the level of Prym varieties. Necessary and sufficient conditions are also provided for the Prym varieties associated with the moduli spaces of $G_2$ and $\Spin(8,\mathbb{C})$-Higgs bundles to be disconnected. Finally, some consequences are drawn from the above results in relation to the geometry of the Prym varieties involved.

This research investigates the impact of Al and Ti elements on the formation of self-generated ordered phase in high-entropy alloys (HEA), which have been receiving widespread concentration in present times thanks to their remarkable multifunctional properties and wide range of component selection. By adjusting the dual elements of Al and Ti, the study explores the regulation of quantity and distribution of the in-situ self-generated ordered phases in the alloy. The results of the annealing heat treatment process demonstrated that, through accession Al and Ti elements, the Cr-Fe-Ni medium-entropy alloy transfer from BCC phase to BCC+FCC phase and the precipitation of new phases such as B2, L21, and σ. This led to a synergistic impact of second phase strengthening, and also of solid solution strengthening, resulting in improved compressive properties of HEA.

The adoption of social media metrics by small and medium-sized enterprises (SMEs) has become a critical tool for engaging customers and enhancing strategic outcomes. However, many SMEs face challenges in effectively tracking and evaluating social media investments, making it difficult to assess the effectiveness of their strategies. This systematic review identifies and analyses key social media activities and performance metrics that contribute to SME strategic success. Through an extensive review of literature from Google Scholar, Web of Science, and Scopus, we selected 138 studies published between 2014 and 2024. The analysis reveals that engagement metrics (e.g., likes, shares), brand awareness (e.g., mentions), and conversion metrics (e.g., click-through rates) significantly influence organizational performance and long-term success. SMEs leveraging detailed engagement metrics reported a 25% increase in customer retention, while brand awareness metrics led to a 30% improvement in customer acquisition. The review highlights areas requiring further research, including a need for sector-specific metric analysis and a deeper understanding of emerging social media platforms. These results offer practical insights for SMEs to enhance their strategic use of social media and adapt to rapidly changing market dynamics.

This study presents a novel predictive model to address the churn problem in the motor insurance sector using a dual-phase framework. The first phase employs a cave-degree perturbation technique for effective feature selection, while the second phase applies the Magnetic Force Perturbation Technique (MFPT) to optimize the search process and avoid local optima traps. Two metaheuristics are proposed: the Adaptive Random Forest-Assisted Large Neighborhood Feature Optimizer (ARALFO) and the Adaptive Random Forest Particle Swarm Optimizer (ARFPSO) to enhance churn prediction accuracy. The model was evaluated on two real-world motor insurance datasets, achieving a 95% accuracy rate and outperforming state-of-the-art algorithms. An ablation study confirmed the significant impact of the cave-degree and MFPT techniques in boosting predictive performance.

Aim of study: to evaluate the therapeutic impact of topically applied curcumin as Alternative or Complementary to Triamcinolone Acetonate in Treatment of Oral Lichen Planus. Background: Oral lichen planus (OLP) is a chronic inflammatory disorder affecting the mucous membranes, believed to be an immune-mediated condition. Its persisting nature can lead to extended discomfort for those affected. The primary symptoms are pain and a burning sensation, with a potential risk of malignancy if not properly managed, necessitating lifelong clinical monitoring. Presently, OLP is considered a significant challenge due to the absence of a definitive cure. Patients & patients: Thirty patients with oral lichen planus were divided into three groups, 10 patients each: Group A: ten patients with OLP were received topical triamcinolone acetonide. Group B: ten patients with OLP were received topical curcumin. Group C: ten patients with oral lichen planus were received topical triamcinolone acetonide combiend with topical curcumin. For six weeks. Each patient was examined at baseline, 1 and 3months of therapy. Pain was scored using the visual analogue scale. Salivary level of interleukin 6 were estimated at baseline, 1 and 3months evaluation periods. Results: Significant decrease in pain score was observed in all groups and there was a statistically significant difference between them at all treatment periods in favor to group C . 2 Additionally, all groups showed a decrease in the size of lesions which was greater in group A,C compared to the B group. A significant reduction of the mean interlukin6 continued down to 3 months in all groups with statistically insignificant difference between them at three months, while statistically significant difference in favor to group C at 1month was observed. Conclusion: The results proved the benefit of curcumin as a promising medication when used in combination with conventional therapy in treatment of OLP patients. However, further longterm studies with large sample size are needed.

The United States is facing an alarming surge in cyberattacks, with data breaches rising by 72% since 2021, presenting grave national security risks. Notable incidents, including Chinese hackers attempting to access high-level government information and Iranian-linked cyber groups targeting U.S. water systems, highlight the fragility of critical infrastructure. These attacks pose dangers not only to national security but also to economic stability and public health, amplified by the rapid growth of interconnected technologies and global digitalization. In response to these escalating threats, the U.S. must take a multifaceted approach. Key strategies include strengthening cybersecurity education and workforce development, enforcing more rigorous regulatory frameworks, and enhancing preparedness through incident response and recovery planning. Additionally, increased international cooperation is essential to address state-sponsored cyber threats and foster a global framework for cybersecurity defense. As cyber threats continue to evolve, future efforts will rely on technological advancements such as artificial intelligence (AI) for real-time threat detection, the adoption of zero-trust security models, and the development of adaptive, resilient cybersecurity infrastructures. Collaboration between the public and private sectors, coupled with ongoing innovation and education, will be critical to maintaining national security and promoting economic growth in an increasingly interconnected digital landscape.