Background: for patients with endocarditis, guidelines recommend repeating blood cultures until they become negative, but with very limited evidence. Methods: a literature review was done on the incidence and duration of persistent bacteremia and persistent fever in endocarditis patients, compared to their associations with persistent infection at day 7. Results: persistent bacteremia and persistent fever are common in the first few days after starting antibiotic therapy, a normal duration for either at or around < 3-7 days. Persistent bacteremia is more prevalent and longer lasting in Staphylococcus (especially MRSA) and Enterococcus species than in Streptococcus species. In one study the risk for persistent infection at day 7 was 50% in those with positive blood cultures at 48-72 hours while it was 32% in those with negativization of blood cultures. Both persistent bacteremia at 48-72 hours and persistent infection at day 7 are predictive of in-hospital mortality. Conclusion: persistent bacteremia after treatment for endocarditis is common and often accompanied by persistent fever. Persistent infection at 7 days (as indication for urgent surgery) cannot be reliably predicted by positive or negative blood cultures at 48-72 hours. The recommendation of performing survey blood cultures in all patients therefore needs to be reconsidered.

This paper studies the Bondi-Metzner-Sachs group in homogeneous projective coordinates, because it is then possible to write all transformations of such a group in a manifestly linear way. The 2-sphere metric, Bondi-Metzner-Sachs metric, asymptotic Killing vectors, generators of supertranslations, as well as boosts and rotations of Minkowski spacetime, are all re-expressed in homogeneous projective coordinates. Last, the integral curves of vector fields which generate supertranslations are evaluated in detail. This work prepares the ground for more advanced applications of the differential geometry of asymptotically flat spacetimes in projective coordinates.

Ranked Set Sampling (RSS) is a useful technique for improving the estimator of population mean when the sampling units in a study can be easily ranked than the actual measurement. RSS performs better than simple random sampling (SRS) when the mean of units corresponding to each rank is used. The performance of RSS can be increased further by assigning weights to the ranked observations. In this paper, we propose weighted RSS procedures to estimate the population mean of positively skew distributions. It is shown that the gain in the relative precisions of the population mean for chosen distributions are uniformly higher than those based on RSS. The gains in relative precisions are substantially high. Further, the relative precisions of our estimator are slightly higher than the ones based on Neyman’s optimal allocation model for small sample sizes. Moreover, it is shown that, the performance of the proposed estimator increases as the skewness increases by using the example of lognormal family of distributions.

As modern technologies, particularly home assistant devices, become more integrated into our daily lives, they are also making their way into the domain of energy management within our homes. Homeowners, now acting as prosumers, have access to detailed information in 15-minute or even 5-minute intervals, including weather forecasts, outputs from Renewable Energy Sources (RES)-based systems, appliance schedules and the current energy balance, which details any deficits or surpluses along with their quantities and the predicted prices on the Local Energy Market (LEM). The goal for these prosumers is to reduce costs while ensuring their home’s comfort levels are maintained. However, given the complexity and the rapid decision-making required in managing this information, the need for a supportive system is evident. This is particularly true given the routine nature of these decisions, highlighting the potential for a system that provides personalized recommendations to optimize energy consumption, whether that involves adjusting the load or engaging in transactions with the LEM. In this context, we propose a recommendation system powered by Large Language Models (LLM), Scikit-llm and Zero-Shot Classifiers, designed to evaluate specific scenarios and offer tailored advice for prosumers based on the available data at any given moment. Two scenarios for a prosumer of 5.9 kW are assessed using candidate labels, such as Decrease, Increase, Sell and Buy.

As technology continues to play a central role in shaping global industries, the performance of technology firms on the NASDAQ has significant implications for broader economic trends. Investors, facing an increasingly complex landscape, require detailed insights to make informed decisions and navigate market volatility. Moreover, amid the ongoing digital transformation, understanding the operational dynamics of technology companies is critical for policymakers and regulatory bodies to create frameworks that foster innovation while ensuring market stability. In the current context, characterized by rapid technological advancements, market uncertainties, and evolving consumer demands, the need for a comprehensive study on the operational efficiency of NASDAQ-listed technology companies is more pertinent than ever. Objective of our study is to identify relationships and patterns among selected financial metrics to assess the operational efficiency of NASDAQ-listed technology companies between 2011 to 2023. Financial metrics used in the study include following variables namely revenues, cost of goods sold, operating expenses, research, and development expenses, selling and general administrative expenses, and operating income. Johansen's cointegration methodology is employed to unveil long-term relationships and equilibrium adjustments among the considered variables. Results of our study underscore the paramount importance of efficiently managing the cost of goods sold (COGS) for achieving superior operating performance among these leading technology firms. The findings point to a nuanced interplay among these operational metrics, highlighting the interconnectedness and sustained relationships among them. This suggests that the top technology companies exhibit a sophisticated understanding of the dynamics between these variables, allowing them to navigate the complexities of the industry with strategic finesse.

Entropy generation, formulated by combining the first and second laws of thermodynamics with an appropriate thermodynamic potential, emerges as the difference between a phenomenological entropy function and a reversible entropy function. The phenomenological entropy function is evaluated over an irreversible path through thermodynamic state space via real time measurements of thermodynamic states. The reversible entropy function is calculated along an ideal reversible path through the same state space. Entropy generation models for various classes of systems—thermal, externally loaded, internally reactive, open and closed––are developed via selection of suitable thermodynamic potentials. Here we simplify thermodynamic principles to specify convenient and consistently accurate system governing equations and characterization models. The formulations introduce a new and universal Phenomenological Entropy Generation (PEG) theorem. The systems and methods presented––and demonstrated on grease degradation, battery charging and discharging, metal fatigue and pump flow––can be used for design, analysis, and support of diagnostic monitoring and optimization.

Partial differential representation of self-similarity feature has been derived from notion of the homogenous function in general sense. This representation allows consideration of stochastic self-similar systems. As well as the partial differential representation allows consideration of Stochastic Partial Differential Equation.

Parkinson-like events are side effects that may persist for an extended period even after drug administration is discontinued. Although these events can be triggered by various drugs, the mechanisms underlying their diverse symptoms remain largely unclear. To investigate this, we used the Japanese Adverse Drug Event Reporting Database, which is maintained by the Phar-maceuticals and Medical Devices Agency, to analyze the risk factors associated with Parkinson-like events along with associated drug trends and characteristics. Our findings indicate that similar to　Parkinson’s disease, age-related differences affect the onset of these events, with older individuals being more susceptible. Hierarchical clustering and principal component analysis revealed that the mechanisms triggering these Parkinson-like events are consistent across reports, suggesting a common underlying cause. However, even with a consistent mechanism, side effects can vary depending on the site of action. These insights underline the importance of swift identification of the drugs suspected of causing these events and implementation of measures to reduce their side effects.

The study assesses the direct effects of climate change by 2060, including extreme events, on the productivity of regional crop farming and livestock in Greece, and the broader socio-economic effects on the agri-food and other sectors. Different approaches (i.e., agronomic models, statistical regression models, equations linking thermal stress to livestock output) were combined to estimate the effects on productivity from changes in the average values of climatic parameters, and subsequently the direct economic effects from this long-term climate change. Recorded damages from extreme events together with climatic thresholds per event and crop were combined to estimate the direct economic effects of these extremes. The broader socio-economic effects were then estimated through input-output analysis. Under average levels of future extreme events, the total direct economic losses for the Greek agriculture due to climate change will be significant, from €437 million/ year to €1 billion/ year. These losses approximately double when indirect effects on other sectors using agricultural products as inputs (e.g., food and beverage, hotels, restaurants) are considered, and escalate further under a tenfold impact of extreme events. Losses in the GDP and employment are moderate at the national level, but significant in regions where the contribution of agriculture is high.

Many risk-modifying factors affect cancer incidence and mortality rates. We present an ecological study of incidence and/or mortality rates for cancers during 2007–2016 of 17 anatomical sites with respect to solar ultraviolet-B (UVB) doses and obesity prevalence. Solar UVB reduces cancer risk by producing vitamin D, which has many mechanisms to reduce risk of cancer incidence, progression, and metastasis. Obesity increases cancer risk through several mechanisms, including increased systemic inflammation. Data were averaged for 12 geographical regions. Solar UVB doses were significantly inversely correlated with mortality rates for five cancers for males and four for females. Obesity prevalence was directly correlated with mortality rates for three cancers for males and seven for females. The population attributable fraction of cancer mortality rates ascribed to low solar UVB dose was 0.03 for both males and females, whereas that for obesity prevalence was 0.05 for males and 0.08 for females. Thus, cancer mortality rates in France could be reduced through vitamin D supplementation and reducing the prevalence of obesity. Doing so also could reduce risk of other adverse health outcomes.

The nuclear factor-ĸB (NF-ĸB) transcriptional system is a major effector pathway involved in inflammatory responses. Previous studies found that a Gardenia decoction (GD) inhibited the expression of NF-κB in a lipopolysaccharide (LPS)-stimulated mouse intestinal injury model. Herein, we hypothesized that geniposide (GE), a component of Gardenia jasminoides Ellis, also exerts anti-inflammatory effects and inhibits NF-ĸB activity in LPS-induced intestinal epithelial cells (IEC-6). IEC-6 cells were stimulated with LPS, following which the effects of GE on NF-ĸB signaling in the IEC-6 cells were examined by western blotting to detect IĸB phosphorylation/degradation. The expression of NF-κB was determined by immunofluorescence assay (IFA). Enzyme-linked immunosorbent assay (ELISA) was used to detect the inhibitory effect of GE on the release of tumor necrosis factor-α (TNF-α), interleukin-6 (IL-6) and interleukin-1β (IL-1β) activated by LPS in IEC-6 cells. In addition, the migration ability of IEC-6 cells was observed by the scratch method. These results showed that GE dose-dependently downregulated levels of the proinflammatory cytokines TNF-α, IL-6 and IL-1β that had been upregulated by LPS and suppressed the phosphorylation of IĸB and NF-ĸB induced by LPS. Our findings indicated that GE could reduce LPS-induced NF-ĸB signaling and proinflammatory expression in IEC-6 cells and significantly enhance the migration of IEC-6 cells. Moreover, GE inhibited the expression of NF-κB, nuclear transfer, and transcriptional activity in IEC-6 cells. GE could block the synthesis of inflammatory factors of IEC-6 cells by inhibiting activation of the IĸB/NF-κB signaling pathway induced by LPS.

(1) Background: With the global population aging, the demand for effective rehabilitation products for the elderly is increasing. Traditional products often fail to meet the comprehensive needs of elderly users, who require solutions addressing physical, psychological, and social aspects; (2) Methods: Using the Analytic Hierarchy Process, Quality Function Deployment, Axiomatic Design, and the System Usability Scale to identify and prioritize user needs, market research and user interviews were conducted to understand the preferences of the elderly and obtain design specifications. The focus was on multimodal sensory feedback, which was validated through the study; (3) Results: Elderly users have a strong preference for rehabilitation products that are durable, easy to use and have comprehensive sensory feedback. Intelligent rehabilitation bed as the carrier, strengthened structure, high strength material, ergonomic adjustment, integrated health monitoring system. Using digital technology for real-time health monitoring and personalized feedback to provide a comprehensive recovery experience, high user satisfaction was reported in the evaluation; (4) Conclusion: It is important to emphasize user-centered design and integrate multi-modal sensory feedback to meet the comprehensive rehabilitation needs of elderly users. Future studies should expand user samples and expert opinions to refine and validate the design and improve its effectiveness and usability.

The Zero Trust Architecture (ZTA) security system follows the "never trust, always verify" principle. The process constantly verifies users and devices trying to access resources. This paper describes how Microsoft Azure uses ZTA to enforce strict identity verification and access rules across the cloud environment to improve security. Implementation is time-consuming and difficult. Azure's extensive services and customizations require careful design and implementation. Azure administrators struggle to navigate and change configurations due to its complex user interface (UI). Each Azure ecosystem component must meet ZTA criteria. ZTA's comprehensive policy definitions, multi-factor and pass-wordless authentication, and other advanced features are tested in a mid-size business scenario. These configuration changes require a solid grasp of Azure's architecture and Zero Trust. Implementing an Azure ZTA reduces vulnerabilities and restricts authorized users' access to critical resources. Implementation is time-consuming and expensive, requires a significant commitment to changing IT procedures, and can be confusing because the same features are available in multiple places. Azure ZTA has shown great potential for both hybrid and cloud-native companies.

The present work provides an updated overview of the application of the Oxford Nanopore^® MinION^™ sequencer in cultural heritage biodeterioration studies, while also providing a holistic discussion of possible future perspectives for their utilization in this research field. Due to the peculiar characteristics of this device, the last few years have seen the steady rise on the application of this system in a variety of cultural heritage materials, having been useful to understand microbial biodeteriogens diversity and some of their metabolic and biodeteriogenic features. Considering the immense potential for application of this system, this manuscript discusses further possibilities of the technique aiming to help understand critical questions on the cultural heritage biodeterioration area. Its application in various differential contexts, has opened the doors for their putative usage on other interesting sub-areas of research worthy of future investigations, including: biodeteriogens genome and transcriptome analysis, metatranscriptomics, biodeteriorative metabolism studies, inter and intra kingdom interactions analysis, resistome profiling, object history and context studies, in situ applications, bioprospecting and biotechnology.

Background: We aimed to 1) Understand the level of knowledge about sex trafficking of minors among school personnel and the determinants of such knowledge; 2) Test the effectiveness of short educational videos in increasing awareness about sex trafficking of minors among school personnel. Methods: We employed an online survey to gather responses from 741 teachers and school counselors living in the US. The McNemar test was used to test for differences in awareness before and after exposure to the videos. Logistic regression was used to identify predictors of awareness based on the respondents’ characteristics. Results: Predictors of knowledge about sex trafficking were years of experience, level of education and being a female. Exposure to the educational videos improved the respondents’ level of awareness about this crime and prompted respondents to seek additional educational material. There is a need to develop training initiatives for school personnel on sex trafficking and response protocols to support victims of this crime. Conclusion: School personnel have a high level of awareness of risk factors for sexual abuse but less awareness of what constitutes sex trafficking in children. Exposure to short educational videos can increase such awareness.

Cured-in-place pipe (CIPP) lining is a widely adopted method for pipeline renewal, offering advantages such as rapid installation and cost-effectiveness. However, concerns regarding the environmental impacts of volatile organic compound (VOC) emissions during the installation process have raised issues regarding the CIPP method. The literature review conducted in this paper indicated the need for stringent monitoring and management practices to mitigate adverse effects, emphasizing the importance of safe installation protocols. This paper presents the initial results of a case study focusing on VOC emissions, specifically investigating non-styrene polyester resins and water curing. To capture emissions from CIPP activities, the methodology involved air sampling using various equipment, including photoionization detectors (PID), summa canisters, passive worker sampler sorbent tubes, and method 13 cartridges. The preliminary findings indicate that non-styrene polyester resins do not exceed the exposure limits set out by the OSHA and USEPA. The future phases of this project will explore different resins and curing methods.

The United Nations’ Agenda 2030 has established a series of Sustainable Development Goals to address global challenges, including poverty, food insecurity, access to education, and social inequality. In this context, charitable organizations such as Caritas play a crucial role in mitigating the negative effects of these challenges and promoting fair and sustainable development. This study aims to analyze prevalent needs among individuals seeking assistance from Caritas in Campania and examine how the organization contributes to achieving the Agenda 2030 Goals in the region. The statistical investigation techniques considered include tandem analysis [], which considers a dimension-reduction technique, such as multiple factor analysis, and, then cluster analysis to identify similar groups of individuals. These exploratory data analysis methods have allowed for the identification of common needs, including food assistance, support for education, employment, and housing assistance. Subsequently, Caritas programs and initiatives aimed at meeting these needs and promoting sustainable development are explored. The results indicate that Caritas plays a significant role in addressing the urgent needs of the vulnerable population in Campania and contributes to the goals of Agenda 2030, particularly those related to poverty alleviation, immigration, health promotion, education, employment, and reduction of social inequalities. This study provides an important perspective on the relevance and effectiveness of Caritas’ work in the context of Agenda 2030.

(1) Background: This paper illustrates an innovative methodological approach chosen to study and map the colors of the Medieval wall painting of Santa Maria Antiqua in the Roman forum, one of the pilot sites of the EHEM project (Enhancement of Heritage Experiences: The Middle Ages. Digital Layered Models of Architecture and Mural Paintings over Time); (2) Methods: We chose to use two methods for gathering information about colors and mapping, specifically colorimetry by spot measurements and hypercolorimetric multispectral imaging (HMI) to map those same colors sampled through colorimetry; (3) Results: Chromatic data of all colors in the wall paintings were obtained in the CIELAB color space. In those same points, chromatic similarity maps were performed by the innovative HMI system, a multispectral imaging technique able to obtain also color data information by means of the advanced calibration software named SpectraPick®: this allowed to have a complete knowledge of the color characteristics and distribution; (4) Conclusion: The color measurements and mapping was an important result to improve the reading of Medieval wall paintings, fragmentary and stratigraphically complex, giving a new light in the knowledge of the colors and allowing to better understand the original appearance of the iconographic patterns, reconstructed with colors as faithfully as possible similar to the originals.

Orb web spiders are common and highly diversified animals found in almost all habitats. They have remarkable plasticity against biotic and abiotic factors, making them excellent indicators of environmental health. The web-creation behavior of spiders is influenced by disturbances in the environment. The aim of the research was to observe the alteration in the web-building behavior of Neoscona vigilans caused by human activities, specifically traffic disturbance. Spider webs were located and photographed at nighttime along the roadside, and their web characteristics were calculated. Spiders were captured from webs for their body measurements. Spider 4^th leg length, carapace width, and body length had a significant association with web size and diameter, CTL, capture area, and mesh size. The quantity of trapped prey, the height of the plant, and the foliage radius increased with the distance from the road. Conversely, anchor points and web elevation from the ground dropped. The highest and lowest proportion of anomalies (modifications/defects) were recorded as holes (52.7%) in 105 webs (100%) and supernumerary (0.7%) in 55 webs (52.4%), respectively. Road disturbance had a negative influence on the spider’s behavior as the webs formed in close proximity to the road had a higher frequency of anomalies with a gradual decrease distantly. We can gain further insight into how different environmental changes, disruptions, and pollutants lead to this imperfection in the otherwise flawless perfect structure of spider webs.

Pyrocumulonimbus (pyroCb) thunderclouds, produced from extreme bushfires, can initiate frequent cloud-to-ground (CG) lightning strikes containing extended continuing currents. This, in turn, can ignite new spotfires and inflict massive harm on the environment and infrastructures. This study presents a 3D numerical thundercloud model for estimating the lightning of different types and its striking zone for the conceptual tripole thundercloud structure which is theorized to elucidate the lightning phenomenon in pyroCb storms. More emphasis is given to the lower positive charge structure thundercloud to thoroughly examine various electrical parameters including the longitudinal electric field, electric potential, and surface charge density. The simulation outcomes on pyroCb thunderclouds with a tripole structure confirm the presence of negative longitudinal electric field initiation at the cloud’s lower region. This initiation is accompanied by enhancing the lower positive charge region, resulting in an overall positive electric potential increase. Consequently, negative surface charge density appears underneath the pyroCb thundercloud which has the potential to induce positive cloud-to-ground (+CG) lightning flashes. The suggested model would establish the basis for identifying the potential area impacted by lightning and could also be expanded to analyze the dangerous conditions that may arise in wind energy farms or power substations in times of severe pyroCb events.

Nanoporous materials, such as Metal-Organic Frameworks (MOFs), are renowned for their high selectivity as gas adsorbents due to their specific surface area, nanoporosity, and active surface chemistry. A significant challenge for their widespread application is their behavior and reduced gas uptake in wet conditions, attributed to competitive adsorption between gas and water. The current understanding of gas adsorption in wet materials is constrained by studies that utilize only small amounts of powdered porous materials (in the milligram range) within very small reactors (1-5 mL). This leaves a significant gap in knowledge about gas adsorption behaviors in larger reactors and when MOF sample sizes are increased (to the gram scale) for scaling up the process. Additionally, there is a notable dearth of experimental research in situations where MOFs are heavily saturated with water. To address these gaps, this study measures CH4 adsorption in MOFs under conditions of high moisture content, using larger samples of MOFs (in grams) and a large volume reactor. We selected commercially available MOFs, including HKUST-1, ZIF-8, MOF-303, and activated carbon. A high-pressure isotherms (at T = 274.15 K) using volumetric approach were measured to qualitatively compare the moles of gas adsorbed under both dry and wet conditions across different MOFs and weights. Experimental results show that the presence of water led to a decrease in total CH4 mmol adsorption in MOFs, with a more significant decrease observed in hydrophilic MOFs compared to hydrophobic ones. For hydrophilic MOFs, presence of crossover isotherms at crossover pressure provided evidence of water's conversion to hydrate and its positive role in enhancing total gas uptake, which varied among different hydrophilic MOFs. Oversaturated MOFs showed a larger deviation between dry and wet cases at higher pressures. The high-pressure isotherm data confirm the positive role of hydrophilic MOFs in the conversion of water to hydrate in oversaturated MOFs when MOFs sample size is large.

The shortage of physicians in rural communities contributes to increased mortality rates among Medicare beneficiaries. This increase in mortality risk is commonly due to diseases such as heart disease and cancer, including melanoma and non-melanoma skin cancer (NMSC). Mohs micrographic surgery (MMS) is considered the gold-standard treatment for NMSC tumors, however, due to a shortage of dermatologists and Mohs surgeons in rural areas, access to MMS is limited. In these areas, image guided superficial radiation therapy (IGSRT) serves as a viable option for the treatment of NMSC lesions, with fewer recurrences and 99% cure rates, which are comparable to MMS cure rates. IGSRT is performed in dermatology clinics with support from a multidisciplinary team, including radiation therapists, medical physicists, radiation oncologists, and dermatologists. As IGSRT is able to be performed by general dermatologists, Medicare beneficiaries in rural communities will have an increase in access to treatment options and a decrease in delayed skin cancer treatment.

In this study, a carbon fiber microelectrode (CF) was applied for the investigation of electrochemical behavior and determination of natural antioxidant, apocynin (APO). Given the limited solubility of APO in water, a mixture of anhydrous acetic acid (AcH) with 20%, v/v acetonitrile (AN) and 0.1 mol L-1 sodium acetate (AcNa) was used. The electrochemical properties of APO were examined through linear sweep voltammetry (LSV), differential pulse voltammetry (DPV), and cyclic voltammetry (CV). The anodic oxidation of APO, which is the basis of the method used, proved to be diffusion-controlled and proceeded with a two-electron and one proton exchange. Both radicals and radical cations, arising from the first and second step of electrode reactions, respectively, underwent subsequent chemical transformations to yield more stable final products (EqCiEiCi mechanism). Using optimized DPV conditions, the anodic peak current of APO at potential of 0.925 V vs Ag/AgCl showed a good linear response within the concentration range of 2.7×10-6 – 2.6×10-4 mol L-1. The detection and quantification limits were determined as 8.9×10-7 and 2.7×10-6 mol L-1, respectively. The developed DPV method enabled the successful determination of APO in herbal extracts and in dietary supplements. It should be noted that this is the first method of voltammetric determination of APO.

The quasi-experimental study examines the role of contemporary technologies, such as artificial intelligence and humanoid robots, in enhancing sustainability education for future teachers, emphasizing their impact on shaping sustainable beliefs in future generations. Involving 112 pre-service teachers, the research compares various contemporary and traditional learning methods. Pre- and post-test evaluations were conducted to assess changes in participants’ understanding of sustainability concepts and the variability of their responses. Results reveal significant improvements in sustainability awareness, with methods involving humanoid robots showing higher response variability. The study also identifies the development of new literacies crucial for effectively utilizing advanced technologies in promoting environmental sustainability. While artificial intelligence and humanoid robots match the efficacy of traditional methods, they notably engage young educators more effectively in sustainability topics. These findings highlight the need to integrate such technologies into educational framework to deepen the understanding of environmental issues and prepare youth for future challenges. However, further research is required to explore long-term effects and broader demographics. The research contributes significantly to educational technology and sustainability in education, showcasing the transformative potential of incorporating contemporary technologies in educational settings.

Trace amines are a separate, independent group of biogenic amines, close in structure to classical monoamine neurotransmitters such as dopamine, serotonin and norepinephrine. G protein-coupled Trace Amine-Associated Receptors (TAAR) are mostly investigated for their involvement in the pathogenesis of neuropsychiatric disorders, but expression of TAAR family receptors is observed also in various populations of cells of the immune system. The review is focused on the basic information on the interaction of trace amines and their receptors with cells of the general immune system of humans and other mammals, as well as on data on TAARs role in the function of individual populations of myeloid and lymphoid cells. With further research on the regulatory role of the trace amine system in the pathogenesis of the immune response and determination of the biological mechanisms for their action it would be possible to develop new methods for treating diseases related to immune system dysfunctions.

Measurements of temperature and salinity in the Amazon River plume in the open ocean of the western tropical North Atlantic are considered. The measurements were carried out using the AML CTD probe in the upper layer and a flow-through system that measures salinity and turbidity of seawater while the vessel is on the way. Additionally, archive oceanographic data from the WOD18 database, data of satellite altimetry measurements (AVISO), and satellite salinity data from Aquarius and SMOS were used. It is shown that the width of the Amazon plume is about 300–400 km, the depth of desalination is from 50 to 100 m. Surface salinity decreases compared to the background (36 PSU) by 0.5 PSU in February and more than by 3 PSU in September during the period of maximum development of the plume, which is determined from satellite measurements of surface salinity. Lagrangian modeling of the back-in-time advection of passive markers simulating freshwater particles was carried out. It was shown that the source of fresh water in the measurement area is the discharge of the Amazon.

Tuberculosis (TB) remains a global public health issue, particularly in developing countries. Hematopoietic stem cell transplant (HSCT) recipients are at elevated risk for TB due to immunosuppression. This retrospective study (2005-2022) assessed a preemptive latent tuberculosis infection (LTBI) screening and treatment strategy in 338 HSCT recipients and their donors. Screening included tuberculin skin test (TST) or QuantiFERON-TB Gold (QFT), and pulmonary imaging, with positive cases receiving isoniazid (INH) therapy. Statistical analyses aimed to compare TB reactivation rates, overall survival (OS), and relapse-free survival (RFS) across HSCT groups. Of 338 patients, 92 (27%) were diagnosed with LTBI. Screening involved TST in 325 cases and QFT in 13. INH therapy was completed by 81 patients, with 5 discontinuing due to hepatotoxicity. The cumulative incidence of active TB was 0.6%, and LTBI reactivation rate in patients who received INH was 1.2%. LTBI status did not affect OS or RFS. Our study exemplifies the effectiveness of LTBI protocols incorporating TST/QFT and CT-scan testing, followed by INH therapy, in reducing TB reactivation among HSCT recipients in a high-burden region.

The objective of this study was to investigate the relationship between high-performance work systems and a company’s social performance, taking into account the organizational climate as a situational variable. Specifically, this study aimed to analyze the impact of perceptions of a high-performance work system on the perception of a company’s social responsibility (CSR) among employees of Jordanian companies with an organizational size of 300 or more. This study used 175 valid questionnaires, and SPSS and AMOS 24 were used to test the hypotheses. The results showed that there was a positive relationship between the perception of a high-performance work system and the perception of a company’s CSR. Furthermore, this study found that a positive diversity climate could enhance the positive relationship between the two. These findings suggest that high-performance work systems can contribute to the development of sustainable human resource management systems and that a positive diversity climate is essential in shaping these systems. Based on these results, it is recommended that companies implement HPWSs and encourage workforce diversity to maximize the value of CSR activities and ensure their sustainability.

Over recent years, the swine industry has witnessed the withdrawal of antibiotics and continuous regulation of zinc and copper oxides in the early-life nutrition of piglets. Due to this development, alternative ingredients or additives from plant sources have been tremendously explored. Therefore, this study's objective was to evaluate the effect of dietary supplementation with tannins on weaned piglets’ growth performance, serum antioxidant capacity, and immune status using a meta-analysis approach. With only the inclusion of non-challenged weaned piglets, a total of 16 studies with parameters of interest were deemed eligible after a two-step screening process following a comprehensive literature search in the scientific databases of Web of Science, Scopus, ScienceDirect, PubMed, and Google Scholar. Two main categories of data, including the study’s characteristics and response variables (growth performance, serum antioxidant, and immune indices), were extracted. Applying the random-effects models, Hedges’ g effect size of supplementation with tannins was calculated using the R software to determine the standardized mean difference (SMD) at a 95% confidence interval. Sub-group analysis and meta-regression further explored heterogeneity (PSMD 0.05, I2 50%, n ≥10). Supplementation with tannin reduced average daily gain (p = 0.20) and feed conversion ratio (p 0.01); however, it increased average daily feed intake (p = 0.07) and final body weight (p 0.01). Meta-regression models indicated that tannin dosage and supplementation duration were directly associated with tannins' effectiveness on productive performance. In the serum, the concentration of glutathione peroxidase, superoxide dismutase, and total antioxidant capacity were elevated (p 0.01) in response to tannins supplementation, while malondialdehydes was reduced (p 0.01). Likewise, decreased immunoglobin A (p = 0.47) and increased immunoglobin M and G levels (p 0.01) were detected. In conclusion, dietary supplementation with tannins, particularly with chestnut and grape seed proanthocyanidins, increases the productivity of weaned piglets. At the same time, it is a possible nutritional strategy to mitigate oxidative stress and stimulate gut health. Thus, supplementing chestnut and grape seed proanthocyanidin tannins in the early phase of swine production could be used to alleviate the incidence of diarrhea.

The use of unmanned aerial aircrafts (UAVs) is governed by strict regulatory frameworks that prioritize safety. To guarantee safety, it is necessary to acquire and maintain situational awareness (SA) throughout the operation. Existing Canadian regulations require pilots to operate their aircrafts in visual line-of-sight. Therefore, the task of acquiring and maintaining SA primary falls to the pilots. However, the development of aerial transport is entering a new era with the adoption of a highly dynamic and complex system known as advanced air mobility (AAM), which involves UAV operating autonomously beyond visual line-of-sight. SA must therefore be acquired and maintained primarily by each UAV through specific technologies and procedures. In this paper, we review these technologies and procedures in order to decompose the SA of the UAV in the AAM. We then use the system modeling language to provide a high-level structural and behavioral representation of the AAM as a system having UAV as its main entity. In a case study, we analyze one of the flagships UAVs of our industrial partner. Results show that this UAV doesn’t have all the technologies and methodologies necessary to achieve all the identified SA goals identified for the safety of the AAM. This work is a theoretical framework intended to contribute to the realization of the AAM, and we also expect to impact the future design and utilization of UAVs.

This study was carried out with a low-cost electronic nose prototype based on eight metal oxide sensors (MQ) in order to characterize samples of lemons treated with 0.5% and 0.1% of sodium benzoate. The MQ sensors designed are sensitive to one or more chemicals to detect the presence of a variety of chemicals in the air. The sensor MQ135 detects ammonia, hydrogen sulphide and benzene. Signal data were studied to obtain a pattern recognition of rotten in lemon fruits. Network analysis was used to obtain a calibration of measures among the stage of lemons. In this article, an electronic nose prototype based on 8 MQ metal oxide sensors has been used in order to analyze and characterize different lemon varieties to which different chemical treatments have been applied in pre-harvest. PCA-based data analyzes were used to observe clusters in the data. Through the combined use of the data obtained by the nose and these Sequential Neural Networks (SNNs) a classification tool for lemon varieties and applied treatments has been obtained. It is shown the ability of this device to be used as a reliable discrimination method, in addition to providing low cost and optimization of time and expert resources.

Phosphorus (P) concentration in rivers and lakes receives greater attention due to its significance in contributing to eutrophication. This study aimed at profiling phosphorus species in Vembanad lake (Ramsar site) and its adjoining rivers. Four phosphorus fractions (total reactive phosphorus (TRP), total acid hydrolysable phosphorus (TAHP), total organic phosphorus (TOP) and total phosphorus (TP)) were monitored according to premonsoon and postmonsoon seasons. Meenachil river mouth is a hotspot for eutrophication with high values of most of the phosphorus fractions. Among the four fractions TRP, TOP and TP were recorded maximum concentration during the premonsoon and postmonsoon seasons. Each fraction of TRP, TAHP, TOP, and TP had an average concentration of more than 300 µgL-1 P throughout two seasons, which is highly eutrophic. The result reveals that the surface water of Vembanad lake is highly polluted with phosphorus input and it may trigger algal growth and consequent destruction of the biodiversity rich wetland system.

Anthropogenic lighting elicits positive phototaxis responses (i.e., attraction) in birds, insects, and many other species across ecosystems. Impacts from lights in marine systems are poorly understood, despite evidence that vessel lighting can cause seabird disorientation and collisions, potentially leading to injury or mortality. The level of attraction generated by different types of lighting, including light-emitting diodes (LEDs), is also not well understood in most seabirds. Using fairy prions (Pachyptila turtur), a species showing strong positive phototaxis particularly to artificial lights on vessels, we investigated the effects of LED colour and lumen output at a colony during the breeding season. We used six random treatment groups (control (dark), red light, amber low lumen, amber high lumen, white low lumen, and white high lumen) and measured attraction and disorientation. Data was analysed using generalised linear mixed-effects models while accounting for environmental variables. Results showed that the control (“dark”) and red light attracted fewest birds, and attraction/disorientation did not differ between these. Medium responses were elicited by amber low/high and white low, while white high lumen induced the highest abundance and attraction/disorientation response. These results agreed with our desktop study, which predicted response rankings based on each light treatment’s colour spectrum and lumen output and a related species’ spectral response. Furthermore, time of night increased bird counts, as did higher humidity, increased moon illumination, and reduced moon visibility. Our data highlight the need to consider LED colour, lumen output, and time of night to reduce anthropogenic lighting impacts on land and at sea.

Drones have experienced rapid technological advancements, leading to the proliferation of small, low-cost, remotely controlled, and autonomous aerial vehicles with diverse applications, from package delivery to personal transportation. However, integrating these drones into the existing air traffic management (ATM) system poses significant challenges. The current ATM infrastructure, designed primarily for traditional manned aircraft, requires enhanced capacity, workforce, and cost-effectiveness to coordinate the large numbers of drones expected to operate at low altitudes in complex urban environments. To address this critical issue, this study aims to develop an intelligent, highly automated drone management system for integration into smart city transportation networks. The key objectives include: i) Developing a conceptual framework for an intelligent total transportation management system tailored for future smart cities, focusing on incorporating drone operations; ii) Designing an advanced air traffic management and flight control system capable of managing individual drones and drone swarms in complex urban environments; iii) Improving drone management methods by leveraging drone-following models and emerging technologies such as the Internet of Things (IoT) and the Internet of Drones (IoD); and iv) Investigating the landing processes and protocols for unmanned aerial vehicles (UAVs) to enable safe and efficient operations.

Detection methods have been developed to prevent transmission of zoonotic or xenozoonotic porcine viruses after transplantation of pig organs or cells to the recipient (xenotransplantation). Eleven xenotransplantation-relevant viruses including porcine cytomegalovirus, a porcine roseolovirus (PCMV/PRV), porcine lymphotropic herpesviruses -1, -2, -3 (PLHV-1, 2, 3), porcine parvovirus (PPV), porcine circovirus 2, 3, 4 (PCV2, 3, 4), hepatitis E virus genotype 3 (HEV3), porcine endogenous retrovirus-C (PERV-C) and recombinant PERV-A/C have been selected. In the past, several pig breeds, minipigs and genetically modified pigs generated for xenotransplantation had been analyzed using these methods. Here, spleen, liver and blood samples from 10 German slaughterhouse pigs were screened using both, PCR-based and immunological assays. Five viruses: PCMV/PRV, PLHV-1, PLHV-3 and PERV-C were found in all animals, and PCV3 in one animal. Some animals were latently infected with PCMV/PRV as only virus-specific antibodies were detected. Others were also PCR positive in spleen and/or liver, indicative of an ongoing infection. These results provide important information on the viruses that infect German slaughterhouse pigs and together with results of previous studies revealed that the methods and test strategies efficiently work under field conditions.

Let $\mathcal{\mathcal{S}}_{\cos}^{\ast}$ denote the class of normalized analytic functions $f$ in the open unit disk $\mathbb{D}$ satisfying the subordination $\dfrac{zf^{\prime}(z)}{f(z)}\prec\cos z$. In the second section of this article we find the sharp upper bounds for the initial coefficients $a_{3}$, $a_{4}$ and $a_{5}$ and the sharp upper bound for module of the Hankel determinant $|H_{2,3}(f)|$ for the functions from the class $\mathcal{S}_{\cos}^{\ast}$. The first result of the next section deals with the sharp upper bounds of the logarithmic coefficients $\gamma_{3}$ and $\gamma_{4}$ and we found in addition the sharp upper bound for $\left|H_{2,2}\left(F_{f}/2\right)\right|$. For obtaining these results we used the very useful and appropriate Lemma 2.4 of N.E. Cho et al. [Filomat 34(6) (2020), 2061--2072], and the technique for finding the maximum value of a three variable function on a closed cuboid. All the maximum found values were checked by using MAPLE\texttrademark{} computare software, and we also found the extremal functions in each cases. All of our present results are the best ones and give sharp versions of those recently published in [Hacet. J. Math. Stat. 52, 596--618, 2023].

Deep learning architectures like ResNet and Inception have produced accurate predictions for classifying benign and malignant tumors in the healthcare domain. This enables healthcare institutions to make data-driven decisions and potentially enable early detection of malignancy by employing computer-vision-based deep learning algorithms. These Convolutional Neural Network algorithms, in addition to requiring huge amounts of data, can identify higher and lower-level features that are significant while classifying tumors into benign or malignant. However, these algorithms have limitations concerning explainability and identifying the exact features that are of importance and contributing to the final classification of tumors as benign or malignant. In this paper, we implement several explainable AI techniques, namely, LIME, Saliency Map, Occlusion Analysis, Grad-CAM, SHAP, and Smooth Grad to interpret the results of a custom ResNet60 classifier in the classification of ovarian tumors as benign or malignant. The ResNet60 model attained an accuracy of 97.50% for the test dataset.

Pulsating high frequency voltage injection can be used for sensorless control of SPMSM at zero and low speed ranges. However, the sensorless capability still faces challenges to the requirements of industrial application, especially at heavy load status. Aiming at this issue, this article proposes a sensorless capability expansion method for SPMSM based on inductance parameter identification. First, incremental inductances at d-q-axis and cross-coupling inductance are identified by three steps combining the rotating high frequency voltage injection and pulsating high frequency voltage injection, then, using polynomial curve fitting algorithm, apparent inductances are calculated. Second, positive DC current injection at d-axis is proposed to enhance the saliency ratio based on the analysis of parameter identification results. Compared with the conventional =0 or &lt; 0 method, when positive DC current is injected at d-axis, saliency ratio is enhanced. Third, convergence region is expanded at heavy load status and accuracy of rotor position estimation is improved using the proposed method. Finally, the experiment results validate that the sensorless capability of SPMSM is expanded.

Sesame seeds are abundant in sesamin, which exerts health-promoting effects such as extending the lifespan of adult Drosophila and suppression of oxidative stress accumulation by activating the Nrf2 transcription factor. Here, we investigated whether sesamin activated Nrf2 in larval tissues and induced the expression of Nrf2 target genes. In sesamin-fed larvae, Nrf2 was activated in the central nervous system (CNS), gut, and salivary glands. However, ectopic expression of Keap1 (Nrf2 inhibitor) in glial cells inhibited sesamin-induced Nrf2 activation in all tissues except in the neurons, indicating that sesamin activates Nrf2 in glia. We labeled the astrocytes as well as cortex and surface glia with red fluorescence to identify these glial cell types in which Nrf2 was activated; we observed their activation in both cell types. These data suggest that sesamin may stimulate the expression of antioxidative genes in glial cells. Among the 17 candidate Nrf2 targets, the mRNA levels of Cyp6a2 and Cyp6g1 in cytochrome P450 were elevated in the CNS, gut, and salivary glands of sesamin-fed larvae. However, this did not lead to resistance against imidacloprid, which is detoxified by these enzymes. Our results suggest that sesamin may exert similar health-promoting effects on the human CNS and digestive tissues.

Alternative splicing is an essential regulatory mechanism for gene expression in mammalian cells contributing to protein, cellular, and species diversity. Isoform switching, the process where cells alter the expression of various splice forms (isoforms) of a gene, plays a critical role in cellular function and adaptation. Our study provides a comprehensive analysis of splice forms prevailing across ten of the most studied human cell lines using public RNAseq data. We analyzed the occurrence of splice forms and found substantial justification for revising the canonical sequences for 56 genes, suggesting that these alternative splice forms should be recognized as canonical. Additionally, distinct profiles of splice form prevalence across these cell lines offer new insights into their specific biological roles. Our findings reinforce and expand upon previous insights into the link between isoform expression and oncological processes. Notably, we identified three genes exhibiting statistically significant changes between cancerous and normal tissues. Moreover, a comparative analysis of prevailing isoforms across diverse cell lines with prior research unveiled 140 common splice variants associated with cancer, highlighting their importance for prognostication and understanding oncogenesis. We revealed unique patterns and variations in isoform switching of these lines that provide new insights into the importance of selecting specific ones for research.

This study examines the optimization of ground source heat pump (GSHP) systems and energy piles for sustainable urban development, with a focus on Southeast Asia. GSHPs, which utilize geothermal energy for indoor HVAC needs, offer a sustainable alternative to traditional systems by utilizing consistent subsurface temperatures for heating and cooling. The study highlights the importance of understanding thermal movement within the soil, especially in soft marine clays prevalent in Southeast Asia, to improve GSHP system efficiency. Using a one-dimensional finite-difference model, the study examines the effects of soil thermal conductivity and density on system performance. The results show that GSHP systems, especially when integrated with energy piles, significantly reduce electricity consumption and greenhouse gas emissions, underscoring their potential to mitigate the urban heat island effect in densely populated areas. Despite challenges posed by the region's hot and humid climate, which could affect long-term effectiveness, the study highlights the need for further study, including field experiments and advanced modeling techniques, to optimize GSHP configurations and fully exploit geothermal energy in urban environments. The study's insights into soil thermal dynamics and system design optimization contribute to the advancement of sustainable urban infrastructure development.

The development of reliable predictive algorithm for house price as the housing market is a stand-out among the most involved regarding valuing the price and continues to fluctuate, is constantly a need for socio-economic advancement and welfare of citizen. In this paper, we develop machine learning algorithms for forecasting UK housing Price, and find an optimal algorithm that forecasts housing price accurately on the premises of the presence of many features or covariates. After applying correlation analysis to remove correlated variables in order to avoid multicollinearity, thereby increasing the statistical power, a novel method of using regression analysis to first of all understand and select statistically significant features for the various regions in England based on North South divide is adopted. These features are then used in the machine learning algorithm to further increase the statistical power of the algorithm, increase the level of accuracy for each of them and ultimately increase the predictive values for the algorithms. The model construction involves 3 stages: 1- correlation analysis to identify and remove correlated variables thereby avoiding multicollinearity and increasing the statistical power of the linear regression, 2 - using linear regression to determine variables that are statistically significant and 3 - building the machine learning algorithms based on the variables that are statistically significant from the linear regression. A comprehensive dataset of UK Paid housing Price from 2010 to 2019 was linked to a number of other datasets to generate a total 21 variables or features used for the models. Catboost, Gradient Boosting, Bagging, Random Forest, Extra Tree all achieved the excellent models performance result in all the regions considered. The comparison of the seven models showed that Extra Tree algorithm consistently achieved the best performance in term of level of accuracy in all the regions. K-Nearest Neighbours (KNN) is the only algorithm with less than 50% level of accuracy. Noticeably, the regions considered had varying or differing insignificant variables, implying that although many variables are common (statistically significant) to all the regions, there are regional differences and impact when modelling or predicting housing prices. This study validates the practicability of developing a machine learning methodology for the prediction of housing price. This research offers a reference for future house price prediction based on machine learning.

Hypoxia is one of the common abiotic stresses that negatively affects the development and productivity of agricultural crops. Quercetin is used to protect plants from oxidative stress when exposed to environmental stressors. O2 deficiency leads to impaired development and morphometric parameters in wheat varieties Orenburgskaya 22 (Triticum aestivum) and varieties Zolotaya (Triticum durum). Cytological analysis revealed various types of changes in the cytoplasm under conditions of hypoxia and treatment with quercetin. The most critical changes in the cytoplasm occur in the Zolotaya variety during pretreatment with quercetin followed by hypoxia, and in the Orenburgskaya 22 variety during hypoxia. Quercetin has a protective effect only on the Orenburgskaya 22 variety, and also promotes more effective recovery after exposure to low O2 content. Hypoxia causes an increase in ROS and activates the antioxidant system. It has been shown that the most active components of the antioxidant system in the Orenburgskaya 22 variety are MnSOD and Cu/ZnSOD, and in the Zolotaya variety GSH. We have shown that quercetin provides resistance only to the wheat genotype Orenburgskaya 22, as a protective agent against abiotic stress, which indicates the need for a comprehensive study of the effects of exogenous protectors before use in agriculture.

A testable hypothesis with quantitative predictions is put forward, proposing that strong acids produced on land at a rate correlated with global population are an increas-ing cause of increasing atmospheric CO2 pressure (pCO2). This hypothesis widens the imbalance assumed between the global uptake of CO2 by photosynthesis and emissions of CO2 from all sources, including the combustion of fossil fuels, causing greater atmos-pheric pCO2. Our modelling tests for reactions of dissolved inorganic carbon show that increasing atmospheric CO2 is caused thermodynamically by falling land surface pH values, but only with bicarbonate present. Strong acids generated by oxygen from re-duced inorganic compounds of nitrogen and sulphur emit CO2 almost stoichiometrically from dissolved bicarbonate in the pH range of most global soils, between 6 to above 8. We show that each decrease of aqueous pH value of 0.01 units from acidification of sur-face water near pH 8 potentially increases the pCO2 in the atmosphere by about 7 ppmv. The surface pH value of the ocean near 8.10 in 2000 has been shown to decrease at this rate, a result of equilibrating with the rising atmospheric pCO2. Therefore, our qualita-tive estimates of increasing atmospheric CO2 driven by irreversible acidification on land are critical and need broad scale validation. Unfortunately, these acidifying processes on land from excessive nitrogen fertiliser, export of alkaline produce from farmlands and other processes were not considered by previous biogeochemical reviews. However, several very recent research studies showing CO2 emissions from soil during nitrifica-tion are consistent with our hypothesis. Despite counter measures to curb excessive CO2 emissions, including carbon capture and geological storage, the increasing Keeling curve for pCO2 may continue to rise because zero carbon policies do not address these causes. We recommend that this hypothesis be further tested by in situ experiments in neutral soils and water, designed to compare CO2 emissions under the acidifying conditions de-scribed in this article. Corrective counter measures can then be designed and applied.

Artificial Intelligence (AI) emerges as a powerful catalyst poised to reshape the global sustaina-bility landscape by facilitating the attainment of Sustainable Development Goals (SDGs). This comprehensive Delphi study meticulously probes the insights of domain experts, shedding light on the strategic utilization of AI to advance these critical sustainability objectives. Employing rigorous statistical techniques, encompassing measures of central tendency and interquartile de-viation, this research scrutinizes consensus dynamics among experts and elucidates potential variations in their viewpoints. The findings resoundingly convey experts' collective positive perspective regarding AI's pivotal role in propelling the SDGs forward. Through two iterative rounds of extensive discussions, a compelling consensus crystallizes—AI indeed exerts an overall positive impact, exemplified by a robust mean score of 78.8%. Intriguingly, distinct SDGs manifest varied propensities toward AI intervention, with Goals 6, 7, 8, 9, 11, 13, 14 and 15 basking in the radiance of highly positive impacts. Goals 1, 2, 3, 4, 5, 10 and 12 exhibit positive impact scores, indicating a juncture ripe for positive advancements. Meanwhile, Goal 16 and Goal 17 languish with neutral scores, signifying a juncture demanding nuanced deliberations about AI's impact on peace, justice, and strong institutions as well as on partnerships for the goals respectively. This paper underscores AI as a formidable instrument poised to address humanity's most pressing challenges while harmonizing seamlessly with the overarching SDG objectives. It gracefully dovetails into established practices across pivotal domains such as health, education, and resilient infrastructures, amplifying the collective global endeavor to navigate the path toward a more sustainable future.

To solve large scale linear equations involved in the Fast Multipole Boundary Element Method (FM-BEM) efficiently, an iterative method named the generalized minimal residual method (GMRES)(m)algorithm with Variable Restart Parameter (VRP-GMRES(m) algorithm) is proposed. By properly changing a variable restart parameter for the GMRES(m) algorithm, the iteration stagnation problem resulting from improper selection of the parameter is resolved efficiently. Based on the framework of the VRP-GMRES(m) algorithm and the relevant properties of generalized inverse matrix, the projection of the error vector r_m+1 on r_m is deduced. The result proves that the proposed algorithm is not only rapidly convergent but also highly accurate. Numerical experiments further show that the new algorithm can significantly improve the computational efficiency and accuracy. Its superiorities will be much more remarkable when it is used to solve larger scale problems. Therefore, it has extensive prospects in the FM-BEM field and other scientific and engineering computing.

The African society is one of the societies with rich culture and traditions. Apart from the indigenous religion of Africa, Christianity and Islam are worshiped as the major religions of the African society. Literature reflects a great amount of influence of religions on the existing societies, people and cultures. African literature often mirrors the clash of indigenous religion with Christianity. In the writings of African authors one can find the elements of Christian beliefs and practices. The present paper, however, is focused on the African woman novelist Buchi Emecheta’s selected four novels: Second-Class Citizen (1974), The Bride Price (1976), The Slave-Girl (1977) and The Joys of Motherhood (1979). The paper attempts to discuss the impact of Christianity on the social and cultural aspects of the African society with special focus on African women. The findings reveal the positive as well as negative impacts of the new religion on African people and on the position of African women through the characters present in the selected novels. With the medium of writing and through Christianity, Emecheta seek to educate her society and improve upon the position of the African women.

A hallmark of Alzheimer’s disease (AD) are the proteinaceous aggregates formed by the amyloid-beta peptide (Aβ) that is deposited inside the brain as amyloid plaques. The accumulation of aggregated Aβ may initiate or enhance pathologic processes in AD. According to the amyloid hypothesis any agent that has the capability to inhibit Aβ aggregation and/or destroy amyloid plaques represents a potential disease modifying drug. In 2023, a humanized IgG1 monoclonal antibody (lecanemab) against the Aβ soluble protofibrils was approved by US FDA for AD therapy thus providing compelling support to the amyloid hypothesis. To acquire a deeper insight on the in vivo Aβ aggregation, various animal models, including aged herbivores and carnivores, non-human primates, transgenic rodents, fish and worms are widely exploited. This review is based on the recent data obtained using transgenic animal AD models and presents experimental verification of the critical role in Aβ aggregation seeding of the interactions between zinc ions, Aβ with the isomerized Asp7 (isoD7- Aβ) and the α4β2 nicotinic acetylcholine receptor.

Capsaicin, vitamin C, carotenoids and phenolic compounds from cumari-do-Pará peppers (Capsicum chinense Jacq.) harvested from two different locations from Pará, Brazil, and at different ripening stages were extracted employing ultrasonic-assisted extraction (UAE). Edible vegetable oils from soybean (Glycine max), Brazilian nuts (Bertholettia excelsa H.B.), and palm olein were used as the extraction solvent, as an alternative to organic solvents combined with UAE. The proximate composition of the pepper extracts and vitamin C were determined through AOAC methods, while total phenolic compounds and carotenoids were assessed by UV/Vis spectrophotometry, and capsaicin, by high-performance liquid chromatography. The antioxidant activities of cumari-do-Pará extracts were evaluated by the ABTS radical scavenging and β-carotene/linoleic acid system assays. Bioactive compounds and antioxidant activity varied with harvesting location and pepper ripening stage. Soybean oil was the most effective in extracting hydrophobic molecules particularly linoleic acid, corresponding to about 60% of the total fatty acid. Carotenoids were extracted whith highest yields by all oil extracts . Oily cumari-do-Pará extracts can be used as spices in foodstuffs and as additives in pharmaceuticals and nutraceuticals. Edible vegetable oils combined with UAE are, thus, efficient for bioactive compound extraction, also comprising an environmentally friendly, safe, low-cost, and fast alternative.

This article critically examines existing wastewater management legislation, highlighting its detrimental impact on environmental and public health. It emphasizes the urgent need for a mentality shift among water managers, advocating responsible stewardship of water resources. By promoting collaboration between regulatory bodies and scientific communities, the article seeks tailored solutions for complex challenges. It underscores the necessity of integrating technological innovation, rigorous monitoring, and public engagement for sustainable management. Additionally, it calls for the implementation of easy-to-adopt technological solutions, alongside rigorous monitoring and financial support. Ultimately, the article advocates for a paradigm shift in wastewater management policies towards accountability, innovation, and environmental sustainability. Directives governing wastewater management in Europe, particularly in Spain, have faced scrutiny due to significant shortcomings. Legislation has inadvertently facilitated untreated or poorly treated wastewater discharge, resulting in widespread pollution. Despite EU efforts, punitive measures have proven ineffective, with fines often borne by the public sector, although private sector responsibility. The lack of robust monitoring mechanisms and technical support exacerbates the situation, perpetuating a regressive mindset among water managers. Urgent reforms are needed to enforce strict discharge prohibitions, promote reuse, and provide financial and technical assistance. However, systemic barriers and entrenched mentalities pose formidable challenges to meaningful change.

Abstract The aim of the present review is to discuss the roles of vitamin K and vitamin K-dependent proteins, and the combined action of the vitamins K and D, for maintenance of bone health. The most relevant vitamin K-dependent proteins in this respect are osteocalcin and matrix Gla-protein (MGP). When carboxylated these proteins appear to have the ability to chelate and import calcium from the blood to the bone, thereby reducing the risk of osteoporosis. Carboxylated osteocalcin appears to contribute directly to bone quality and strength. Adequate vitamin K status is required for carboxylation of MGP and osteocalcin. In addition, vitamin K acts on bone metabolism by other mechanism, such as a ligand for the nuclear steroid and xenobiotic receptor (SXR). In this narrative review, we examine the evidence for increased bone mineralization through dietary adequacy of vitamin K (phylloquinone or menaquinone). Summarizing the evidence for a synergistic effect of vitamin K and vitamin D3 we find that an adequate supply of vitamin K on top of an optimal vitamin D status seems to add to the benefit for maintaining bone health. More research related to synergism and possible mechanisms of vitamins D3 and K interaction in bone health is needed.

Non-coding RNAs (ncRNAs) comprise a diverse class of non-protein coding transcripts that regulate critical cellular processes associated with cancer. Advances in RNA-sequencing (RNA-Seq) have led to the characterization of non-coding RNA expression across different types of human cancers. Through comprehensive RNA-Seq profiling, a growing number of studies demonstrate that ncRNAs, including long non-coding RNA (lncRNAs) and microRNAs (miRNA), play central roles in progenitor B-cell Acute Lymphoblastic Leukemia (B-ALL) pathogenesis. Furthermore, due to their central roles in cellular homeostasis and their potential as biomarkers, the study of ncRNAs continues to provide new insight into the molecular mechanisms of B-ALL. This article reviews the ncRNA signatures reported for all B-ALL subtypes, focusing on technological developments in transcriptome profiling and recently discovered examples of ncRNAs with biologic and therapeutic relevance in B-ALL.

Matrices and their inverses allow accurate calculations to be produced quickly and compactly and can be used to control any process represented by a system of equations. Singular matrices require extensive workarounds (costing time and money) to solve these systems of equations because they have no inverse. Finding their inverse involves division by zero. Nevertheless, recently a new number set called semi-structured complex numbers was developed to enable division by zero in algebraic equations. The aim of this research was to demonstrate that the inverse of a singular matrix can be found using semi-structured complex numbers. This research reveals (1) Singular matrices and their inverses can be used to find a unique solution to a pair of simultaneous equations that appear to have infinitely many solutions or appear to have no solution; (2) Singular matrices map coordinates in projective space to coordinates in Euclidean space and their inverse maps coordinates in Euclidean space to coordinates in projective space; (3) the inverse of a singular matrix proves that parallel lines in Euclidean space do not intersect but in projective space intersect at a “point at infinity” and (4) collinear lines that intersect at infinitely many points in Euclidean space only intersect at one point in projective space.

Equine hepacivirus (EqHV, Flaviviridae, Hepacivirus) is a small, enveloped, RNA virus generally causing sub-clinical hepatitis with occasional fatalities. EqHV is reported in equids worldwide, but for Italy data are limited. To address this, a survey study was set up to estimate prevalence at national level and among different production categories (equestrian, competition, work and meat and reproduction) and national macro-regions (North, Central, South and Islands). Data obtained testing 1801 horse serum samples by Real-Time RT PCR were compared within the categories and regions. The NS3 fragment of the PCR-positive samples was sequenced by Sanger protocol for phylogenetic and mutational analysis. The tertiary structure of the NS3 protein was also assessed. The estimated national prevalence was 4.27% [1.97-6.59, 95%CI] and no statistical differences were detected among production categories and macro-regions. The phylogenesis confirmed the distribution in Italy of the three known EqHV subtypes, suggesting also a possible fourth sub-type that however requires further confirmation. Mutational profiles that could also affect the NS3 binding affinity to the viral RNA were detected. The present paper demonstrates that EqHV should be included in diagnostic protocols when investigating causes of hepatitis and in quality control protocols for blood derived products, due to its parental transmission.

Parkinson's disease (PD) is recognized as the second most prevalent primary chronic neurodegenerative disorder of the central nervous system. Clinically, PD is characterized as a movement disorder, exhibiting an incidence and mortality rate that is increasing faster than any other neurological condition. In recent years, there has been a growing interest concerning the role of the gut microbiome in the etiology and pathophysiology of PD. The establishment of a brain-gut microbiome axis is now real, with evidence denoting a bidirectional communication between the brain and the gut microbiota through metabolic, immune, neuronal, and endocrine mechanisms and pathways. Among these, the vagus nerve represents the most direct form of communication between the brain and the gut. Given the potential interactions between bacteria and drugs, it has been observed that the therapies for PD can have an impact on the composition of the microbiome. Therefore, in the scope of the present review, we will discuss the current understanding of gut microbiome on PD and whether this may be a new paradigm for treating this devastating disease.

Background The operator's ability in performing carotid stenting (CAS) has improved clinical outcomes. However, more than 3% of patients need to be treated again after CAS. Most of the cases requiring further intervention are affected by hyperplasia. The recommended procedure is the DEBalloon. On the other hand, the literature reports a small number of carotid neoatherosclerosis cases and is recommended to be treated using elective Micronet-covered stent. Discriminating between the two types of in-stent-restenosis ISR (hyperplasia or neoatherosclerosis) is critical for a positive outcome.Case summary We describe a case in which a patient treated with carotid stenting 8 years before, was diagnosed with ISR. Due to the development of neurological symptoms and progressive increases in Peak Systolic Velocity (PSV) eight years following carotid stenting, a DEBalloon was used in a carotid in-stent-restenosis (ISR) standard procedure. About ten minutes after the procedure, the patient developed hemiplegia consistent with the treated carotid territory. The implantation of a MicroNet-covered stent excluded the thrombus and reverted symptoms with a normal MR control at 24 h. Conclusion This case illustrates that when in-stent stenosis evolves years after the stent implantation, neoatherosclerosis should be assessed, and a MicroNet-covered stent should be considered.

Background: The COVID-19 outbreak has accelerated the huge difference between medical care and disease prevention in Chinese medical institutions. This study aimed to investigated the relationship between the symbiotic units, environments, models, and effects of the integration of medical and disease prevention. Methods: This cross-sectional study involved 762 employees of public hospitals in 11 cities in Zhejiang Province by random stratified sampling. We analyzed the influence paths of elements in the mechanism of integration of medical and disease prevention and the mediating effect of symbiotic models among symbiotic units, symbiotic environments, and effects for on this integration. Results: The path coefficient of symbiotic unit on the symbiosis model was 0.46 (p&lt;.001), the path coefficient of symbiotic environment on symbiosis model was 0.52 (p&lt;.001). The path coefficient of the symbiotic unit and environment was 0.91 (p&lt;.001). The symbiotic models exhibited a partial mediation effect between symbiotic units and the effect of this integration. Sobel test = 3.27, β = 0.152, and the mediating effect accounted for 34.6%. Conclusions: It is suggested that Health policy-makers and public hospital managers should provide sufficient symbiotic units, establish collaborative symbiotic models, and improve the effects of integration of medical and disease prevention in public hospitals.

This research evaluates the feasibility of addressing computer vision problems with limited resources, particularly in the context of medical data where patient privacy concerns restrict data availability. (1) Background: The study focuses on diagnosing skin diseases using five distinct transfer learning models based on convolutional neural networks. Two versions of the dataset were created, one imbalanced (4092 samples) and the other balanced (5182 samples), using simple data augmentation techniques. Preprocessing techniques were employed to enhance the quality and utility of the data, including image resizing, noise removal, and blur techniques. The performance of each model was assessed using fresh data after preprocessing. According to the research findings, (2) Methods: the VGG-19 model achieved an accuracy of 95.00% on the imbalanced dataset. After applying augmentation on the balanced data, the best-performing model was VGG-16-Aug with an accuracy of 97.07%. (3) Results: These results suggest that low-resource approaches, coupled with preprocessing techniques, can effectively identify skin diseases, particularly when utilizing the VGG-16-Aug model with a balanced dataset. (4) Conclusions: The study addresses rare skin disorders that have received limited attention in past research, including acne, vitiligo, hyperpigmentation, nail psoriasis, and SJS-TEN. The findings highlight the potential of simple data augmentation techniques moreover, explainable AI: Grad-CAM interpreted the model outcome by showing image contours visually as well as identifying uncommon skin conditions and overcoming the data scarcity challenge. The implications of these research findings are significant for the development of machine learning-based diagnostic systems in the medical field. Further investigation is necessary to explore the generalizability of these findings to other medical datasets.

There is a lack of studies on the level of stress and health of families of workers in road transport. This study aimed to evaluate the perceived stress level and Family Effectiveness of family members of road transport workers. A quantitative study was carried out with family members of road transport workers in the southern region of Brazil. For the data collection, a sociodemographic form, the Perceived Stress Scale (PSS), and the Evaluation of Family Effectiveness Strategies were used. The data were analyzed by simple frequency, Spearman correlation coefficient (ρ) (p &lt; 0.05), and descriptive analysis from the perspective of the Systemic Organization. 49 family members of road transport workers were participants. Perceived stress was higher in family members who had more than nine years of schooling, the targets of Control and Growth were higher in the evaluation of Family Effectiveness. The Control target was also higher in families with more than three people. The Coherence dimension had higher levels in families with health problems and whose income was less than $792.00 US dollars per month. In the Individuation dimension, income over $792.00 had better results. The Maintenance dimension of the system was higher in families whose drivers’ activity was as an intercity driver, as well as in the Stability target. In conclusion, the social factors such as schooling, income, diseases, type of worker activity in road transport, and number of people in the family influenced perceived stress and Family Effectiveness, which demonstrates the need to increase the promotion of health care of the families of road transport workers.

The study conducts a comparative analysis of solar radiation estimation methods, assessing the efficacy of the Heliosat-2 algorithm against ground measurements across seven distinct countries: Netherlands, Spain, Japan, Namibia, South Africa, Saudi Arabia, and India. To achieve this, it utilizes two distinct satellite data sources—Himawari-8 for Japan and Metosat Second Generation-MSG for the rest of the countries—spanning the years Jan 2022 to April 2024. A robust methodology for determining albedo parameters specific to Heliosat-2 was developed. During cloudy days, the estimates provided by Heliosat-2 generally exceeded the ground measurements in all the countries. Conversely, on clear days, there was a tendency for underestimation, as indicated by the median value of the mean bias (MB) across most of the countries. The Heliosat-2 model slightly underestimates daily radiation values, with a median MB ranging from −27.5 to +10.2 W.m⁻². Notably, the median root mean squared error (RMSE) on clear days is significantly lower, with values ranging from 24.8 to 108.7 W.m⁻², compared to cloudy days where RMSE values lie between 75.3 and 180.2 W.m⁻². In terms of R² values, both satellites show a strong correlation between the estimated and actual values, with a median value consistently above 0.86 on a monthly scale and over 92% of daily data points falling within ±2 standard deviation.

Carbon Quantum Dots (CQDs) have emerged as promising nanomaterials for enhancing the performance of supercapacitors, offering unique advantages such as high surface area, excellent electrical conductivity, and tunable surface chemistry. This review provides a comprehensive overview of recent advancements in the synthesis, characterization, and integration of CQDs into supercapacitor devices. Various synthesis methods, including chemical oxidation, hydrothermal/solvothermal methods, microwave-assisted synthesis, and pyrolysis, are discussed, highlighting their impact on the structural and electrochemical properties of CQDs. Characterization techniques such as transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman spectroscopy, and photoluminescence (PL) spectroscopy are elucidated for assessing the morphology, crystallinity, and optical properties of CQDs. The integration of CQDs into supercapacitors, including their utilization in composite electrodes, binder-free electrodes, and doping strategies, is explored to enhance specific capacitance, energy density, power density, and cycle stability of the devices. Challenges and future perspectives in the field are outlined, emphasizing the need for scalable synthesis methods, enhanced electrochemical performance, and sustainable device engineering to realize the full potential of CQD-based supercapacitors for various energy storage applications. This review aims to provide insights into the current state of research and guide future endeavors towards developing high-performance and environmentally sustainable energy storage technologies.

Mechanically homogenized composite of expanded graphite and cobalt(II) rhenate(VII) has been described. Cobalt(II) rhenate(VII) was obtained in a reaction of perrhenic acid with cobalt(II) nitrate. A simple mortar homogenization method was used to enhance intercalation of cobalt species within carbon matrix. The specific capacity of composite was enhanced by 50% in comparison to bare expanded graphite. The electrochemical characteristic was significantly improved including better cyclability, lower resistance of electrode material, lower iR drop, with respect to expanded graphite without cobalt(II) rhenate(VII) active species. Expanded graphite with its unique specific surface area and pore size diameter was proved as potential and cheap carbon support.

In directional forming processes such as rolling and extrusion, the microstructure is strongly elongated in the forming direction. This results in a preferred alignment of the crystal orientations of the initially randomly oriented grains. These preferred orientations – the texture – and elongations of the grains are the cause of the material anisotropy. This anisotropy leads to phenomena such as earing, which occur during further forming processes, e.g., during deep drawing of sheet metal. Considering anisotropic properties in numerical simulations allows to investigate the effects of texture-dependent defects in forming processes and the development of possible solutions. Purely phenomenological models for modelling anisotropy work by fitting material parameters or applying measured R-values in experiments which are applied to all elements of the part and remain constant over the duration of the simulation. In contrast, methods such as the Visco-Plastic Self-Consistent (VPSC) model, which has been used in this work, provide a deeper insight into the development of the material microstructure. By experimentally measuring the initial texture and using it as an initial condition for the simulations, it is possible to predict the evolution of the microstructure and the resulting effect on the mechanical properties during forming operations. The results of the simulations with VPSC show good qualitative agreement with tests typically used for rolled stock.

Myocardial fibrosis is a pivotal pathophysiological step of various cardiovascular diseases, which eventually leads to heart failure and death. Cardiac fibroblasts activation and subsequently differentiate into myofibroblasts are pivotal pathophysiological step in myocardial fibrosis. Phosphoglycerate mutase 1 (PGAM1) directly interacts with α-smooth muscle actin (ACTA2) and participate in fibrosis regulation. Allosteric inhibitor of PGAM1 could attenuates fibrosis through break the interaction of PGAM1 and ACTA2. In this study, we aimed to screen and identify novel ligand of PGAM1 in natural product library. Firstly, various natural products were screened via DARTS assay and Carthamus tinctorius L. was identified as a target pool for molecular docking. Then, in silico screening assay identified baicalein as a novel ligand. In addition, baicalein could directly bind to the PGAM1 protein with a KD value of 34.6 μM. Molecular dynamics simulation revealed that baicalin and PGAM1 interactions were stable. These findings indicate that PGAM1 is a direct pharmacological target of baicalein. Immunoblot analysis further demonstrated that baicalin inhibits the activation of fibroblasts in vitro. Finally, the anti-myocardial fibrosis effect of baicalein was verified in vivo. Taken together, our findings suggest that baicalein is a novel PGAM1 templates for developing new therapeutics against myocardial fibrosis.

The Double Random Phase Encoding (DRPE) image encryption method has garnered significant attention in color image processing and optical encryption, thanks to its parallel encryption of R, G, B. However, DRPE-based color image encryption faces two challenges. Firstly, it disregards the correlation of R, G, and B, compromising the encrypted image's robustness. Secondly, DRPE schemes relying on Discrete Fourier Transform (DFT) and Discrete Fractional Fourier Transform (DFRFT) are vulnerable to linear attacks, such as Known Plaintext Attack (KPA) and Chosen Plaintext Attack (CPA). Quantum walk stands out as a remarkable tool for designing modern cryptographic mechanisms, offering resistance to potential attacks from both classical and quantum computers.Therefore, this study presents an optical color image encryption algorithm that combines two-dimensional quantum walk with 24-bit plane permutation, dubbed OCT. This approach employs pseudo-random numbers generated by Two-Dimensional Quantum Walking (TDQW) for phase modulation in DRPE and scrambles the encrypted image's real and imaginary parts using the Generalized Arnold Transform. The 24-bit plane permutation helps reduce correlation of the R, G, B, while the Generalized Arnold Transform bolsters DRPE's resistance to linear attacks. By incorporating TDQW, the key space is significantly expanded. Experimental results validate the effectiveness and security of proposed method.

Verticillium dahliae invades the roots of host plants and causes vascular wilt, which seriously diminishes the yield of cotton and other important crops. The protein AAC (ADP, ATP carrier) is responsible for transferring ATP from the mitochondria into the cytoplasm. When V. dahliae protoplasts were transformed with short interfering RNAs (siRNAs) targeting the VdAAC gene, fungal growth and sporulation were significantly inhibited. To further confirm a role for VdAAC in fungal development, we generated knockout mutants (ΔVdACC), which were hypersensitive to stresses such as UV light and high concentrations of NaCl or sorbitol. Compared with wild-type V. dahliae (Vd wt), ΔVdAAC was impaired in germination and virulence; these impairments were rescued in the complementary strains (ΔVdAAC-C). Moreover, when an RNAi construct of VdAAC under the control of the 35S promoter was used to transform Nicotiana benthamiana, the expression of VdAAC was downregulated in the transgenic seedlings, and they had elevated resistance against V. dahliae. The results of this study suggest that VdAAC contributes to fungal development, virulence and response to stresses and is a promising candidate gene to control V. dahliae. In addition, RNAi is a highly efficient way to silence fungal genes and provides a novel strategy to improve disease resistance in plants.

Perilla frutescens leaves are expected to exhibit antioxidant activity and amyloid-β (Aβ) aggregation inhibitory activity due to the presence of polyphenol-type compounds, etc. These activities fluctuate daily; however, measuring the contents of constituents and functionalities is cumbersome and unsuitable for instantaneous measurements in the field. In this study, we developed a facile method to analyze the activity and content of the components in leaves on-site based on the fluorescence spectra obtained by irradiating the perilla leaves with excitation light. The constituent contents (Chlorophyl (Chl), Total polyphenol content (TPC), Total flavonoid content (TFC), rosmarinic acid (RA) and functional properties DPPH radical scavenging activity, ferric reducing antioxidant power (FRAP), oxygen radical absorbance capacity (ORAC), Aβ aggregation inhibitory activity) were evaluated using established analytical techniques. The correlation between the fluorescence spectrum and the contents and activities was calculated using normalized difference spectral index (NDSI), ratio spectral index (RSI), and difference spectral index (DSI) analyses. We identified a predictive model with a high coefficient of determination R² ≥ 0.57 for content of the constituents, and R² ≥ 0.49 for functional properties. This allows convenient, simultaneous, and non-destructive monitoring of the constituent contents and the functionalities of perilla leave and a simple harvest-time diagnosis. The model established using this method is simple and suggesting that it can simultaneously infer the constituents and functionalities of perilla leaves.

The Philippines has the highest HIV incidence rate in the Asia-Pacific region. Previous studies identified multilevel factors contributing to this phenomenon. This scoping review describes the extent of the literature on HIV contributory factors and identifies gaps to guide directions for HIV prevention research. The keywords HIV incidence, individual, sociocultural, environmental factors, and Philippines, were used to search for evidence on Google Scholar, PubMed, Scopus, and Web of Science databases. A total of 1,017 peer-reviewed articles published in the English language from 2014 to 2024 were reviewed using the Joanna Briggs Institute Scoping Review protocol. Thirty articles were included in this review. The majority of the available evidence was quantitative studies published between 2020 and 2024. Individual, sociocultural, economic, educational, political, and environmental factors shaped the Philippines’ HIV epidemic. Low levels of HIV knowledge, low testing rates, high-risk sex behaviors, stigma, lifestyle, location, lack of HIV education in schools, conservative society, and restrictive policies are HIV contributing factors. The Philippine HIV epidemic is multifactorial. Identifying the contributory factors is crucial in developing targeted interventions for high-risk populations. A dedicated HIV research program is needed to provide evidence-based information to guide the development of HIV preventive programs and research.

The efficacy and cost-effectivness of Multigene Panel Next-Generation Sequencing (NGS) in directing patients towards genomically matched therapies remains uncertain. This study investigated metastatic colorectal cancer (mCRC) patients who underwent NGS analysis on formalin-fixed paraffin-embedded tumor samples. Data from 179 patients were analyzed, revealing no mutations in 39 patients (21.8%), one mutation in 83 patients (46.4%), and two or more mutations in 57 patients (31.8%). KRAS mutations were found in 87 patients (48.6%), including KRAS G12C mutations in 5 patients (2.8%), PIK3CA mutations in 40 patients (22.4%), BRAF mutations in 26 patients (14.5%). Less common mutations were identified: ERBB2 in 5 patients (2.8%) and SMO in 4 patients (2.2%). Additionally, MAP2K1, CTNNB1, and MYC were mutated in 3 patients (2.4%). Two mutations (1.1%) were observed in ERBB3, RAF1, MTOR, JAK1, and FGFR2. No significant survival differences were observed based on mutation numbers. 40% of patients had druggable molecular alterations, but only 1.1% received genomically guided treatment, suggesting limited application in standard practice. Despite this, expanded gene panel testing can identify actionable mutations, aiding personalized treatment strategies in metastatic CRC, although current eligibility for biomarker-guided trials remains limited.

Depictions of robots as romantic partners for humans are frequent in popular culture. As robots are becoming part of human society, they gradually assume the role of partners for humans wherever necessary: as assistants, collaborators, or companions. Companion robots are sup-posed to provide social contact to those humans who could not have it otherwise. These com-panion robots are usually not designed to fulfill one of the most important human needs: the one for romantic and intimate contact. Human-robot intimacy remains a vastly unexplored ter-ritory. In this article, we review the state-of-the-art research in intimate robotics. We discuss major issues limiting acceptance of robots as intimate partners, public perception of robots in in-timate roles, and the possible influence of cross-cultural differences in these domains. We also discuss possible negative effects human-robot intimacy may have on human-human contact. Most importantly, we propose a new term “Intimate companion robots” to reduce the negative connotations of other terms used so far and improve the social perception of research in the domain. With this article, we provide an outlook on prospects for the development of intimate companion robots, considering the specific context of their use.

Abstract Background: Analysis of different type of consolidation in dogs and cats relay on parenchymal and vascular criteria. Hypothesis: the vascular criteria of the consolidation it’s possible to perform in dogs and cats and vascularisation is different in shred, tissue, nodule, wedge sign and mass. Animals: 347 cats and 634 dogs with different types of consolidations. Methods: Retrospective study between 2018-2023. Lung ultrasound performed in dogs and cats with different types of consolidations. Characteristic of bronchogram: air dynamic and static bronchogram, fluid bronchogram or absence of bronchogram. Types of vascularisations in consolidation: tree like type, residual, chaotic vascularisation and penetrating from the chest wall to consolidation and “vascular sign”. Conclusion and Clinical Importance: Analysis of bronchogram and type of vascularisation in consolidation is possible to perform in dogs and cat. The analysis of mentioned criteria had an impact on subsequent diagnostic and therapeutic decisions

Hemoglobin S (Hb S) is genetically inherited variant of hemoglobin affecting around 300 000 infants are born annually. Facilitates for universal population testing of carrier state are available only in developed countries. The screening tests for Hb S have their respective limitations and the confirmatory tests are costly and require experts for conduct and interpretation. The use of two tests will enhance the overall diagnostic accuracy at the level of screening. We have considered two scenarios for population screening for SCD – community based in health camp mode / house to house survey and facility-based mode at health center. The combination of lateral flow immunoassay based POCT with sickling test can be used in absence of HPLC for population screening. However, for antenatal women portable microelectrophoresis based test is recommended as it flags the presence other hemoglobin variants along with Hb S.

This paper proposes the GD (Geometric Distribution) algorithm, a novel approach to enhance the default Adaptive Data Rate (ADR) mechanism in the Long Range Wide Area Network (LoRaWAN). By leveraging the Probability Mass Function (PMF) of the GD model, the GD algorithm effectively addresses massive device distribution challenges in real-life scenarios. To evaluate the algorithm's performance, the LoRaWAN simulations were conducted using the fixed node pattern derived from actual locations of dairy farms in Ratchaburi province, Thailand. The research established scenarios for assessing the network's performance namely, DER (Data Extraction Rate) and SF (Spreading Factor) assignment. Comparative analyses were performed against the uniform random node pattern and established algorithms, including the default ADR scheme, EXPLoRa, Quantile Classification of Variance from the Mean (QCVM), and Standard Deviation (SD). The GD algorithm demonstrated significant improvements over existing methodologies for both fixed and uniform random patterns. The fixed pattern exhibited an enhancement of 14.3%, while the uniform random pattern showed 4.8% enhancement over the default ADR scheme. Further assessments covered the coverage area, payload size, and energy consumption. The GD algorithm consistently achieved the optimal DER values with a coverage area and payload size, albeit often at the expense of increased energy consumption.

This research aims to propose a novel approach to evaluate and minimize the scrap rate in the industrial production of premium food cans with distortion printing. Beyond cost considerations, a critical aspect of modern food can manufacturing is the aesthetic quality of the graphical display. In addition to traditional formability requirements, a waving requirement is defined. Detailed real production conditions are provided and discussed. The material of interest is a double cold-reduced (DR) low-carbon steel sheet and chromium-coated tin-free steel with a thickness of 0.16 mm. These sheets are laminated on both sides with PET film before distortion printing on the exterior. A material parameter identification method is proposed and illustrated to address the challenges in characterizing such a thin sheet. The thickness profile and flange length are key criteria for this identification. Digital image correlation (DIC) and a microscope are used to measure the thickness distribution and flange length. Within the manufacturing system, uncertainties arising from material properties and forming processes can lead to scraps or defects. Finite element analysis (FEA) is adopted for process analysis and validated with experiment. Uncertainty propagation via metamodeling, employing radial basis function (RBF) neural networks, is adopted for the scrap rate evaluation. The study concludes with process optimization recommendations to reduce scrap.

Background: Breast cancer incidence and mortality exhibit a rising trend globally among both premenopausal and postmenopausal women suggesting that there are serious errors in our preventive and therapeutic measures.Purpose: Providing a series of valuable, but misunderstood inventions highlighting the role of increasing estrogen signaling in prevention and therapy of breast cancer instead of its inhibition. Results: 1. Breast cells and breast cancer cells with germline BRCA1/2 mutations similarly show defect in liganded estrogen receptor (ER) signaling demonstrating its role in genomic instability and cancer initiation. 2. In breast cancers, the increased expression of certain receptor family is an effort for self directed improvement of genomic defects, while the weakness or loss of receptors indicates a defect requiring medical repair. 3. ER overexpression in breast cancer cells is capable of strengthening estrogen signaling and DNA repair, while in ER negative tumors, HER2 overexpression tries to upregulate unliganded ER activation and genome stabilization. 4. ER positive breast cancers responsive to endocrine therapy may show a compensatory ER overexpression resulting in a transient tumor response. Breast tumors, non responsive to endocrine therapy, show HER2 overexpression for compensation the complete blockade of liganded ER activation. 5. In breast tumors, somatic mutations serve upregulation of liganded or unliganded activation of ERs helping genome stabilization and apoptotic death. 6. The dynamic communication between breast cancer and its microenvironment is a wonderful collaboration among molecular players fighting for genomic repair and apoptosis in the tumor. 7. In breast cancers, there is no resistance to genotoxic or immune blocker therapies, but rather the non responsive tumor cells exhausted all compensatory possibilities against therapeutic damages. Conclusion: Understanding the behavior and ambition of breast cancer cells may achieve a turn in therapy via applying a supportive care instead of genotoxic measures.

Safety signal detection, an integral component of Pharmacovigilance (PhV), aims to identify new or known adverse events (AEs) resulting from the use of pharmacotherapeutic products. Post-marketing spontaneous reports from different sources are commonly utilized as a data source for detecting these signals but there are underlying challenges arising from data complexity. This paper investigates the implementation of the Apriori algorithm, a popular method in association rule mining, to identify frequently co-occurring drugs and AEs within safety data. We discuss previous applications of the Apriori algorithm for safety signal detection and conduct a detailed study of an improved method specifically tailored for this purpose. This enhanced approach refines the classical Apriori method to effectively reveal potential associations between drugs/vaccines and AEs from post-marketing safety monitoring datasets, especially when AEs are rare. Detailed comparative simulation studies across varied settings, coupled with the application of the method to vaccine safety data from the Vaccine Adverse Event Reporting System (VAERS), demonstrate the efficacy of the improved approach. In conclusion, the improved Apriori algorithm is shown to be a useful screening tool for detecting rarely occurring potential safety signals from the use of drugs/vaccines using post-marketing safety data.

Abstract: Cancer, notably breast cancer, is a significant health concern globally, with a substantial burden in Asia, particularly in Pakistan. Late diagnosis exacerbates mortality rates, emphasizing the importance of robust screening programs. This article examines the effectiveness of breast cancer screening initiatives and intervention four years after initial pilot study that spanned 2015-2019, using data from the Islamabad Federal Breast Screening Centre, to assess readiness for national guideline implementation in Pakistan and beyond. Methods: This retrospective cross-sectional study, conducted at the Federal Breast Screening Center (FBSC), involved 5,580 patients undergoing mammography screening over an four-year period from 2015 to 2023. The study examined patients' data, including Breast Imaging Reporting and Data System (BIRADS) categories through double reading mammography and complementary ultrasound (USG) findings. Demographic information, including age, ethnicity, education status, socio-economic factors, breastfeeding history, breast density, and family history, was recorded to analyze its correlation with breast cancer diagnosis and subsequent management. Data analysis was performed using SPSS 2021. Results: The study included a total of 5580 patients who visited the Federal Breast Screening Centre from 2020 to 2023. The mean age of patients attending screenings from 2020 to 2023 was 48.50 ± 9.55 years, with the most common age group being 41-45 years 1,364 (24.4%), followed by 46-50 years 1,008 (18.1%). The ethnicity with the highest frequency was Punjabi 4,647 (83.3%). The distribution of patients across BI-RADS categories was as follows: BI-RADS 0 (n=175, 3.10%), BI-RADS I (n=1,933, 34.60%), BI-RADS II (n=1,691, 30.30%), BI-RADS III (n=642, 11.50%), BI-RADS IV (n=612, 11.00%), BI-RADS V (n=389, 7.00%), and BI-RADS VI (n=138, 2.50%). The prevalence rate of invasive breast cancer during these four years was 10.4%. Conclusion:In conclusion, breast cancer poses an escalating challenge associated with increasing mortality rates. Pakistan, alongside its South Asian counterparts, is witnessing a surge in cases, emphasizing the urgency for comprehensive interventions. Research endeavors such as this provide valuable insights into demographic profiles, aiding in the formulation of tailored guidelines. Moreover, the establishment of additional federal centers for screening is imperative to enhance patient access and mitigate the issue of delayed diagnoses, aligning Pakistan's healthcare infrastructure with that of developed nations.

Stagnating low renovation rates, vacancies and underused town centers, unprecedentedly high levels of land sealing and excessive consumption of resources through the construction of new buildings and infrastructure as well as the effects of climate change were some of the reasons for carrying out the monumentum ad usum research project.Thermodynamic simulations were used to carry out in-depth analyses of specific building parameters such as energy balances and how they are influenced by the effects of climate change. Life cycle analyses under ecological and economic aspects examined the aspects of sustainability and the individual behaviour of predominantly listed existing buildings under standardized conditions.The project results show that sustainable refurbishment can significantly increase the attractiveness of using historic and listed buildings for non-profit building owners. The results and conclusions of the project are as varied as the recommendations derived from them. In practice, old buildings consume significantly less energy than predicted in the structural calculations. Correction factors are to be developed and thermodynamic simulation calculations are to be used instead of energy performance certificates for more realistic forecasts of energy requirements and emission savings potential. The aspects of sustainability in refurbishment are essential for the protection of our architectural heritage.

Interaction with social agents employing natural language have been discussed especially since Weizenbaum (1966) observed the social effects of his chatbot named 'Eliza', which imitated a cli-ent-centered conversation. With Nass and Reeves’ media equation theory and computers as social actors paradigm, a well-tested framework has been introduced to the study of human-computer interaction. In the 1990s, there was a renewed focus on natural language analysis, which has be-come a crucial area of research in machine learning. Recent advancements in data processing and storage capacities have led to the development of AI-generated utterances that closely resemble human utterances. As a result, AI-based systems can now mimic social relationships to a signifi-cant extent. In light of these technological developments, the article explores whether quasi-social relationships should be considered within the field of social psychology and examines the poten-tial advantages and challenges of this approach.

In the rapidly evolving landscape of AI-supported programming education, there's a growing interest in leveraging such tools to support students helping about what good code makes out. This study investigates the impact of ChatGPT on code quality among part-time undergraduate students enrolled in introductory Java programming courses. With no prior Java experience, students from two separate groups completed identical programming exercises emphasizing coding conventions and code quality. Utilizing static code analysis tools, we assessed adherence to a common coding convention ruleset and calculated cyclomatic and cognitive complexity metrics for submitted code. Our comparative analysis highlights significant improvements in code quality for the ChatGPT-assisted group (treatment group), with marked reductions in rule violations and both cyclomatic and cognitive complexities. Specifically, the treatment group demonstrated greater adherence to coding standards, with fewer violations across several rules, and produced code with lower complexity. These results suggest that ChatGPT can be a valuable tool in programming education, aiding students in writing cleaner, less complex code and better adhering to coding conventions. However, the study's limitations, including the small sample size and the novice status of the participants, necessitate further research with larger, more diverse populations and in different educational contexts.

Traffic accidents are among the most common causes of death worldwide. According to statistics from the World Health Organization (WHO), 50 million people are involved in traffic accidents every year. Canada, particularly Montreal, is not immune to this problem. Data from the Société de l’Assurance Automobile du Québec (SAAQ) shows that there were 392 deaths on Québec roads in 2022, 38 of them related to the city of Montreal. This value represents an increase of 29.3% for the city of Montreal compared to the average for the years 2017 to 2021. In this context, it is important to take concrete measures to improve traffic safety in the city of Montreal. In this article, we present a web-based solution based on machine learning that predicts the severity of traffic accidents in the city of Montreal. This solution uses dataset of traffic accidents that occurred in Montreal between 2012 and 2021. Classification algorithms such as eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), Random Forest (RF) and Gradient Boosting (GB) were used to develop the prediction model. When evaluating the prediction model, performance metrics such as precision, recall, F1 score, and accuracy are taken into account. The performance analysis shows an excellent accuracy of 96% for the prediction model based on the XGBoost classifier. The other models (CatBoost, RF, GB) achieved 95%, 93% and 89% accuracy, respectively. The prediction model based on the XGBoost classifier was deployed using a client-server web application managed by Swagger-UI and the Flask Python framework.

With the increase in technological advancements, architects and engineers over the past couple of decades have been trying to achieve high efficiency within construction projects. Their goals also include reducing global warming effects from construction and building new construction faster for the growing population in urban cities. This requires using a construction method that is less harmful to the environment and faster than other traditional methods. Modular construction, also known as modular construction, is the method that has the potential to make this happen. This review paper discusses what modular construction is and how it is different from the traditional on-site construction. Environmental impacts of using modular construction and what leads to it being more efficient and faster than on-site construction. The study doesn’t suggest that modular construction is the solution to all the problems being faced in the construction industry today, but it is a potential solution that if used in the right situation and correct manner, can have a huge positive impact on the construction industry.

Objective: To analyze prevalence of tuberculosis among the people who presented PIMS with complaints of fever, cough, difficulty in breathing during COVID pandemic.Study Design: Retrospective/ Cross-sectional study.Place and Duration: Department of Radiology, Pakistan Institute of Medical Sciences, Islamabad. 2020-2023. Methods: Total 17121 patients who presented PIMS during COVID pandemic with complaints of high grade fever, cough, difficulty in breathing ,were included in this study. Following the acquisition, the HRCT scans were conducted by a skilled and experienced technician and researcher, utilizing GE Healthcare equipment for HRCT Chest procedures. The scans covered the lung apices to the bases and were executed with maximal inspiration, employing a CT scanner from Toshiba Aquilion. Frequency of TB among all cases was recorded. SPSS 21.0 was used to analyze all data.Results: This study incorporated a total of 17,121 patients, comprising 9,961 (58.1%) males and 7,160 (41.8%) females. The mean age of the enrolled cases was 49.11±7.67 years, demonstrating consistency with the findings of a prior study [33]. This study also examined the prevalence of Tuberculosis in different years based on imaging findings of HRCT chest as follows: in 2020, 582 cases out of 2,450, equivalent to 23.7%; in 2021, 2,377 cases out of 9,584, equivalent to 24.8%; in 2022, 1,099 cases out of 3,913, equivalent to 28.1% and in 2023, 295 cases out of 1,174, equivalent to 25.1%. The average prevalence of TB cases from 2020 to 2023 was determined to be 4,353 cases out of 17,121, which is equal to 25.42%.Conclusion: As per the National Tuberculosis Program (NTP) in Pakistan, the prevalence rate of tuberculosis stands at 340 cases per 100,000 population, equivalent to 0.34%. However, our study reveals an exceptionally high frequency of TB cases. Specifically, the prevalence of Tuberculosis in 2020 was 23.7% (582 out of 2,450), in 2021 it was 24.8% (2,377 out of 9,584), in 2022 it surged to 28.1% (1,099 out of 3,913), and in 2023 it was 25.1% (295 out of 1,174). The average prevalence of TB cases over the period from 2020 to 2023 was calculated at 25.4% (4,353 out of 17,121). Consequently, our findings suggest the presence of a substantial tuberculosis burden in Pakistan, equating to a TB Tsunami in Pakistan.

Isokinetic testing of the knee joint is the “gold standard” in strength assessment in sport especially in soccer, where it is part of pre-season screening to establish norms in case of injuries. There are many devices on the market that make it difficult to use of normative data. Isokinetics literature in females’ soccer players is scarce in comparison to males. Furthermore, evaluation protocols strongly differ from each other, using different ranges of speeds, movement patterns and output data. Thus, it is difficult for the researcher and the clinician to choose a correct protocol for isokinetic evaluation in female soccer players. The indexes of isokinetic performance that are widely accepted are the hamstring/quadriceps (H/Q) ratio and dominant/non-dominant (D/ND) ratio as reference. In this review are highlighted some common features of isokinetic testing in female soccer players of different levels of qualification. From this study, it emerges that, for a reliable test, 3 reps at the speed of 60°/sec in knee flexion/extension is preferable due to the high reliability and that an optimal H/Q ratio in healthy female soccer players of different level of qualification and age is 50%, while the interlimb differences (D/ND) should be below 10%.

Studies on evolution have made significant progress in multiple disciplines, but evolutionary theories remain scattered and controversial. Here we deduce that, thermodynamically, many carbon-based entities (CBEs) on the Earth tend to absorb energy from widespread relatively temperate heat streams on the Earth flowing from the solar, geothermal, and other energy sources, to form higher-hierarchy CBEs (HHCBEs). This has been the driving force of evolution leading to accumulation of HHCBEs for billions of years. We further deduce three progressive mechanisms of evolution including natural selection from the driving force. We hence establish the CBE evolutionary theory (CBEET) which reinterprets the major aspects of evolution in a comprehensive and comprehensible way. The CBEET provides novel explanations for natural selection, origin of life (abiogenesis), macroevolution, sympatric speciation, and evolutionary tempos. It suggests that evolution is driven hierarchy-wise by thermodynamics and favors fitness and diversity. It elucidates that altruism, collaboration, and obeying rules with balanced freedom are important throughout the CBE evolution which includes chemical evolution, biological evolution, and animal group evolution. The CBEET refutes several erroneous views including negative entropy and survival of the fittest. It integrates with research advances in multiple disciplines and links up laws of physics, evolution in biology, and harmonious development of human society.

In the present study we examine the relationship among sovereign yields, temperature and precipitation using a large monthly panel data set which consists of 20 eurozone members, over the period 1980M1 – 2023M4. To account for possible asymmetries along the distribution of the climate variables we assume a quadratic modelling specification and apply various mean panel estimation techniques of heterogeneous coefficients. At a next step, to consider possible nonlinearities in the distribution of the dependent variable (sovereign yields), we apply the quantile via moments methodology of Machado and Santos Silva (2019), which accounts for possible cross-sectional dependence and slope heterogeneity. We contribute to the existing literature in two main ways. First, by applying a quantile methodology that provides a more in-depth analysis of the climate effects along the distribution of the sovereign yields, especially in the presence of non-normally distributed data. Second, we find that climate change, as proxied by higher temperatures or lower precipitation (drought), will increase the sovereign risk of all countries, but the magnitude of the impact will be higher for countries that are already characterized by higher sovereign risk levels and/or face extreme weather conditions (hotter countries and/or countries with low levels of precipitation).

Concrete, the most-used construction material by weight, presents a significant environmental challenge due to its high production environmental footprint and huge quantities of demolition waste.Iran, with a thriving construction sector, faces escalating waste management issues.This paper provides a comprehensive review of strategies to increase concrete recycling in Iran. It explores the current state of concrete recycling practices, the environmental and economic benefits, and the existing barriers hindering wider adoption.The paper then analyzes various strategies across the concrete life cycle, including: demolition practices, collection and transportation systems, processing technologies, and market development for recycled concrete aggregates (RCAs).Several case studies are examined in order to identify best practices and strategies used by countries with successful concrete recycling programs that provide valuable insights about the factors contributing to their success which will be useful for implementation in Iran.Furthermore, the review concludes with recommendations tailored to the Iranian context, emphasizing the crucial role of collaboration between different stakeholders in Iran.

The construction industry plays a crucial role in shaping the built environment and contributes to the global economy. However, the construction process is associated with negative impacts on the environment and communities. This paper examines the environmental impacts of construction and presents strategies for mitigating them, focusing on sustainable construction practices. The research draws on a comprehensive literature review, case studies, and expert interviews to fully understand the construction industry and its environmental effects. The findings indicate that the implementation of greater supervision of every construction project phase, using alternative design practices, and the use of sustainable construction practices can reduce the negative impacts of construction on the environment and society. The study concludes that sustainable construction practices can contribute to a better environment for a better quality of life and should be embraced by the construction industry. The recommendations for future work include the adoption of green building standards, the use of renewable energy sources, the reduction of waste, and the promotion of stakeholder engagement. Future research should focus on the evaluation of the effectiveness of these strategies and their scalability.

This article presents multiple novel and compelling arguments to systematically disprove two widely accepted notions: one is that entropy is a measure of disorder, and the other is Schrödinger's notion of negative entropy (negentropy). These two notions have been cited hundreds of times annually in scientific literature for decades. To mathematically describe the second law of thermodynamics, the concept of entropy was created and defined in the 1860s as heat energy divided by thermodynamic temperature, and the entropy of an object increases when it absorbs heat. This is the uncontroversial and fundamental nature of entropy, which is pivotal to current thermodynamics and from which multiple facts are deduced. These facts consistently disprove the above two notions. Some biological facts, such as the one that life orderliness is encoded and provided by inherited genes rather than entropy decline, can also disprove Schrödinger's negentropy notion. Moreover, this article further clarifies the reasoning errors of the two notions. It also shows that the tendency of many natural or social systems to become more disordered over time does not result from the second law of thermodynamics.

This paper presents a compartmental model aimed at investigating the pharmacokinetics of medical THC after oral administration. The model was developed to be multi-compartmental, describing the kinetics of THC and its metabolites in bodily tissues. Utilizing the law of mass action, the model was converted into ordinary differential equations (ODEs), illustrating the rate of concentration changes of THC and its metabolites in each compartment. Subsequently, we applied the nonstandard finite difference (NSFD) method to construct numerical solution schemes. These schemes were implemented in the MATLAB program, along with estimated pharmacokinetic rate constants. The results of the investigation demonstrate that the simulation curves depicting the plasma concentration-time profiles of THC and THC-OH closely resemble the actual data samples, indicating that this model accurately describes the pharmacokinetics of medical THC and its metabolites. Moreover, the model exhibits predictive capabilities regarding the pharmacokinetics of THC and its metabolites in various tissues. Consequently, the model serves as a valuable tool for enhancing our understanding of the pharmacokinetics of THC and its metabolites and for guiding adjustments to dosage and administration durations for oral medical THC products.

The paradigm shift has revealed a need among industrial designers to have entrepreneurial capabilities. Being the most effective modality to exercise discipline today. The implementation of this approach requires reviewing the discursive scaffolding that the design has been using to set immovable high standards of complexity and quality, reducing the field of professional action and limiting the intervention alternatives. This article considers the dynamics and trends in people's lifestyles, explores possible strategies and specific content for the entrepreneurial training required by design.

Animals are distinguished by their complex developmental programs, in which transcription factors play essential roles in coordinating the regulation of the genome. Thus, it has been hypothesized that animal origins involved the evolution of increasingly complex transcriptional regulatory mechanisms that permit greater spatiotemporal control over gene expression. Here, we revisit this hypothesis in light of new genomic and functional data from diverse phylogenetically-relevant taxa, including early branching animals (sponges, ctenophores) and close relatives of animals (choanoflagellates, filastereans, ichthyosporeans). We argue that many of the mechanisms posited to explain animal transcriptional complexity, such as large increases in transcription factor numbers, new transcription factor families, and distal enhancers, did not factor significantly into animal origins. Instead, we propose that the re-purposing of pre-existing transcriptional regulatory modules through cis-regulatory evolution and gene duplication events, combined with new protein-protein interactions among TFs, may have been fundamental to the transcriptional regulatory architecture of the first animals.

The present study discusses how adopting cryptos affects financial inclusion in developing economies. Primary constructs like Financial Inclusion (FI), Perceived Economic Empowerment (PEE), Trust in Financial Institutions (TFI), User Satisfaction (US), and Cryptocurrency Adoption (CA) were tested through Structural Equation Modeling (SEM). The results indicated that CA significantly and positively influenced FI, US, TFI, and PEE. These relationships extend to the interaction effects: US, TFI, and PEE all positively related to FI. It is a reflection of cryptocurrencies as an opportunity to redress most of the afflictions characteristic of traditional finance systems and to promote financial inclusion and economic empowerment in developing countries. Future research should also investigate whether digital literacy and regulatory environments support cryptocurrency access.

Lung cancer is the leading cause of cancer-related deaths globally, with non-small cell lung cancer (NSCLC) accounting for over 85% of cases and poor prognosis in advanced stages. This study explored shifts in circulating metabolite levels in NSCLC patients versus healthy controls and examined the effects of conventionally fractionated radiation therapy (CFRT) and stereotactic body radiation therapy (SBRT). We enrolled 91 NSCLC patients (38 CFRT and 53 SBRT) and 40 healthy controls. Plasma metabolite levels were assessed using semi-targeted metabolomics, revealing 32 elevated and 18 reduced metabolites in patients. Key discriminatory metabolites included ethylmalonic acid, maltose, 3-phosphoglyceric acid, taurine, glutamic acid, glycocolic acid, and d-arabinose, with a combined Receiver Operating Characteristics curve indicating perfect discrimination between patients and controls. CFRT and SBRT affected different metabolites, but both changes suggested a partial normalization of energy and amino acid metabolism pathways. In conclusion, metabolomics identified distinct metabolic signatures in NSCLC patients with potential as diagnostic biomarkers. The differing metabolic responses to CFRT and SBRT reflect their unique therapeutic impacts, underscoring the utility of this technique in enhancing NSCLC diagnosis and treatment monitoring.

Climate change is an important threat to orchard production at Mediterranean basin. Diversification seems to be implemented at a farm level as an important strategy to face these challenges. This paper aims to analyse farmer’s perceptions on crop diversification as a way to enhance farm’s adaptive capacity in a context of current and future climate changes impacts. Our case study is focused in orchards growers from French department of Vaucluse recently diversifying their activities through pistachio (Pistacia vera L.). We did in-depth semi-structured farmers’ interviews in 2021. The results show that diversification is supposed to enhance 3 main components of farms adaptative capacity: (1) strengthening robustness through improvement of buffering capacities to climate impacts (trough robust and adapted plants), economic uncertainties (by exploring local/niche markets) and labour scarcity (by lowering workforce requirements and mechanization); (2) Learning by experimenting, monitoring and exchanging with pairs and advisors (3) Cope with change related with societal demands and helps to increase personal satisfaction. Finally, promote farm’s diversification can contribute to enhance farm’s adaptive capacity under climate change impacts.

The effect of Al or Cu content on the microstructure and mechanical properties of continuous casting and extrusion Zn alloys has been studied by room temperature tensile test, X-ray diffraction, and scanning electron microscope. With the increase of Al content, the microstructure of continuous casting and extrusion Zn alloys slightly coarsens and the lamellar eutectic structure increases. The changes in the above structural factors result in a slight decrease in strength and a significant increase in elongation of Zn-Al alloys. The strength of Zn alloys increases as the Cu content increases, due to the increased content and size of the second phase in the Zn alloys. This means that the mechanical properties of Zn alloys can be adjusted by continuous casting and extrusion process, and the improvement of equipment capacity can improve the structure and morphology of the alloys.

Globalization and digitalization have been associated with a number of challenges and opportunities. The purpose of this chapter is to analyze the impact of globalization and digitization on the Sustainable Development Goals (SDGs) and provide recommendations for achieving sustainable development. The study used a multidisciplinary approach that combined diverse research methods. This included a literature review, case studies, and empirical research findings. The findings suggest that while globalization has had both positive and negative impacts on the SDGs, it also poses challenges to social and environmental sustainability. Globalization's impact on sustainable development goals is complex and multifaceted, requiring policymakers to implement diverse measures to mitigate negative effects and promote sustainable development, particularly in less developed regions and marginalized communities. In conclusion, this chapter highlights the need for a coordinated and holistic approach to sustainable development that prioritizes the Sustainable Design Goals in policy and decision-making.

Viruses can induce the fusion of infected and neighboring cells, leading to the formation of syncytia. Cell-cell fusion is mediated by viral fusion proteins on the plasma membrane of infected cells that interact with cellular receptors on neighboring cells. Viruses use this mechanism to spread rapidly to adjacent cells or escape host immunity. For some viruses, syncytium formation is a hallmark of infection and a known pathogenicity factor. For others, the role of syncytium formation in viral dissemination and pathogenicity remains poorly understood. Human cytomegalovirus (HCMV) is an important cause of morbidity and mortality in transplant patients and the leading cause of congenital infections. Clinical HCMV isolates have broad cell tropism but differ in their ability to induce cell-cell fusions, and little is known about the molecular determinants. We developed a system to analyze HCMV glycoprotein B (gB) variants in a defined genetic background. HCMV strains TB40/E and TR were used as vectors to compare the fusogenicity of six gB variants from congenitally infected fetuses with those from three laboratory strains. Five of them conferred the ability to induce fusion of MRC-5 human embryonic lung fibroblasts to one or both backbone strains, as determined by a split GFP-luciferase reporter system. The same gB variants were not sufficient to induce syncytia in infected ARPE-19 epithelial cells, suggesting that additional factors are involved. The system described here allows a systematic comparison of the fusogenicity of viral envelope glycoproteins and may help to clarify whether fusion-promoting variants are associated with increased pathogenicity.

Bacteria’s ability to withstand the detrimental effects of antimicrobials may take the form of resistance or tolerance with the minimum inhibitory concentration (MIC), the mutant prevention concentration (MPC), and the mutant selection window as salient concepts. Isolates exposed for 30 days to different concentrations of selected antibiotics, biocides, and heavy metals, singly and in combination, were additionally exposed to very high (15 × MIC) concentrations of ampicillin., and their tolerance was calculated the time to kill 99.9% of the isolate population (MDK99.9). These values were increased by 30 to 50% in test isolates compared to the untreated control. BAC 10-exposed isolates had the highest tolerance increase, and the tolerance appeared to originate from two sources, i.e., stochastic persistence and genetic-induced persistence, involving multiple genes using diverse mechanisms. The mutant selection window of the isolates to ampicillin, amoxicillin, and oxytetracycline also slightly increased compared to the control, indicating the amplification of persister cells during the 30-day exposure. These findings indicate that bacterial exposure to sub-inhibitory concentrations of environmental chemical stressors may not always result in the development of antimicrobial resistance but could initiate this process by selecting for persisters that could evolve into resistant isolates.

As the global overprovisioning of electronic devices continues to rise, the management of electronic waste (e-waste) has developed as a significant challenge. E-waste is comprised of hazardous materials; moreover, the toxic constituents in them can impact the environment and public health through improper disposal. On the beneficial side, this e-waste also contains some valuable materials. If the valuable materials are recovered, they can reduce the dependence on new, raw materials. Conventional linear models of production and consumption have led to a momentous buildup of e-waste, posing environmental and economic risks. This paper examines how the adoption of a circular economy approach can improve e-waste recycling in Nairobi by evaluating its economic recovery potential and e-waste residuals. It introduces metrics to assess the development of circular economy practices to help in the handling of e-waste residuals and examines the economic consequences associated with the adoption of circular strategies.