The spectra and global distributions of the X-ray emissions generated by the solar wind charge-exchange (SWCX) process in the terrestrial magnetosheath are investigated based on a global hybrid model and a global geocoronal hydrogen model. The solar wind O6+ ions which are the primary charge state for oxygen ions in solar wind are considered. The line emissivity of the charge-exchange born O5+ ions are calculated by Spectral Analysis System for Astrophysical and Lab oratory (SASAL). It is found that the emission lines from the O5+ ranges from 105.607 to 118.291 eV with the strong line at 107.047 eV. We then simulated the magnetosheath X-ray emission intensity distributions with a virtual camera at two positions of north pole and dusk at six stages during the passing of a perpendicular interplanetary shock combined with a tangential discontinuity structure through the Earth’s magnetosphere. During this process, the X-ray emission intensity increases with time, and the maximum value is 27.11 keV cm-2 s-1 sr-1 on the dayside, which is 4.5 times that before the solar wind structure reaches the Earth. A clear shock structure can be seen in the magnetosheath and moves earthward. The maximum emission intensity seen at dusk is always higher than that seen at north pole.

Abiotic stress is responsible for significant reduction in crop plant productivity worldwide. Ultraviolet (UV) radiation is a natural component of sunlight and a permanent environmental stimulus. This study investigated the distinct responses of young wheat and einkorn plants to excessive UV-B radiation (180 min at λmax 312 nm) following foliar pretreatment with 1 µM synthetic cytokinin 4PU-30. Results demonstrated that UV radiation significantly amplified hydrogen peroxide levels in both wheat and einkorn, with einkorn exhibiting more pronounced increase compared to wheat. This elevation indicated the induction of oxidative stress by UV radiation in the two genotypes. Intensified antioxidant enzyme activities and increased accumulation of typical stress markers and non-enzyme protectants were evidenced. Transcriptional activity of genes encoding key antioxidant enzymes was also investigated aiming to elucidate the genetic regulation of the antioxidant systems in both wheat and einkorn seedlings. Our results suggested a role for POX1 and POX7 genes in the UV-B tolerance of the two wheat species as well as a cytokinin stimulated UV-B stress response in einkorn mediated through upregulation of the tau subfamily gene GSTU6. Based on these findings it could be concluded that 4PU-30 had the potential of alleviating oxidative stress by attenuating the symptoms of superfluous UV-B illumination in the two examined plant species.

The study assessed the trapping efficacy of locally-modified 1) Gravid Aedes Trap(GAT) lined with insecticide-treated net (ITN) as a killing agent, 2) Autocidal Gravid Ovitrap(AGO) with sticky board in the semi-field system (SFS) and field setting. Fully-balanced Latin square experiments were conducted to compare GAT lined with ITN vs AGO, both with either yeast or grass infusion. Biogents-Sentinel (BGS) with BG-Lure and no CO2 was used as standard trap for Aedes mosquitoes. In the SFS, GAT outperformed AGO in collecting both nulliparous (65% vs 49%,OR=2.22,[95%CI:1.89-2.60],p

Background: Asthma is a widespread chronic respiratory disease that poses a significant public health challenge. The current study investigated the associations between air pollution and asthma severity among individuals residing near the Sohar industrial port (SIP) in Oman. Despite the presence of multiple major industrial complexes in Oman, limited knowledge regarding their impact on respiratory health is accredited. Hence, the primary objective of this study is to offer valuable insights into the respiratory health consequences of industrial air pollution in Al Batinah North. Methods: The state health clinics' records for patient visits related to asthma were collected for the timeframe spanning 2014 to 2022. Exposure was defined as the distance from SIP, Majan Industerial Area (MIA) and Sohar Industerial Zone (SIZ) to determine high, intermediate, and low exposure zones (12 km, respectively). Exposure effect modifications by age, gender, and smoking status were also examined. Results: The conducted cross-sectional study of 410 patients (46.1% males and 53.9% females) living in over 17 areas around SIP revealed that 73.2% of asthmatics were under 50 years old, with severity significantly associated with closeness to the port. Risk ratios were estimated to be (RR:2.42; CI95%: 1.01–5.78), (RR:1.91; CI95%: 1.01–3.6), and (RR:1.68; CI95%: 0.92–3.09) for SIP, MIP and SIZ areas, respectively, compared to the control area. Falaj Al Qabail (6.4 km) and Majees (6 km) had the highest number of asthma patients (N. 69 and N. 72), and highest percentages of severe asthma cases among these patients (28% and 24%) with significant risk ratios (RR:2.97; CI95%: 1.19–7.45 and RR:2.55; CI95%: 1.00–6.48), correspondingly. Moreover, severe asthma prevalence peaked in the 25-50 age group (RR:2.05; CI95%: 1.26–3.33), and this linkage between asthma and age was much more pronounced in males than females. Smoking and exposure to certain contaminant (dust and smoke) increased also the risk of severe asthma symptoms, but their effects were less important in the high risk zone, suggesting much more important risk factor. A neural network model accurately predicted asthma risk (94.8% accuracy), with proximity to Sohar Industrial Port as the most influential predictor. Conclusion: The study highlights the High asthma burden near Sohar Industrial Port, linked to port proximity and smoking and wind direction as major risk factors. These findings inform vital public health policies to reduce air pollution and improve respiratory health in the region, prompting national policy review.

Techniques have been developed to determine whether a horse is in resting or running mode by measuring at least one of the following: the horse's body temperature, heart rate, oxygen saturation, and exercise level. However, the existing technology has not reached a level where a trainer can accurately assess a horse's running conditions, such as speed, acceleration, stride, limb rotation, ground impact, and frontal balance, during the training of racehorses. In addition, data is needed to quickly detect abnormalities during training and provide a basis for changing the intensity of training or deciding to give a rest to the horse. Devices that detect abnormalities in equine gait with high sensitivity will contribute to animal welfare and increase the athletic longevity of horses. This paper reports the development results of a new IoT device that acquires, processes, and analyzes information such as heart rate, position, speed, acceleration, pitch, stride, and ground contact during a training of racehorses. The purpose of this development is to provide an information on a novel processing system, device, method, and program that can analyze training condition of racehorses from multiple angles.

This research investigates the application of Fused Filament Fabrication (FFF) in producing WC-10Co hardmetals, focusing binder formulations and understanding its influence on extrusion force and the influence of printing variables on green density of the samples. By examining the interplay between different binder compositions and backbone contents, the study aims to enhance the mechanical properties of the sintered parts while reducing defects inherent in the printing process. Evidence suggested that formulated feedstocks influenced the hardness of the sintered hardmetal, not due to microstructural changes but to macrostructural responses like macro defects introduced during printing, debinding and sintering of the samples. The results demonstrate the critical role of PP-MA content in improving part density and sintered hardness, suggesting the need for specific thermal debinding protocols tailored to each feedstock. The study provides insights into the formulation of feedstocks for hardmetal FFF, proposing a path toward refining manufacturing processes for better quality and performance of 3D printed hardmetal components.

Exploring for green and affordable protection of perishable fruit like cherry tomato is of significance. Here the protective efficacy and its underpinnings of coating with oleaster gum, alone or incorporated with cuminal, on cherry tomatoes stored at ambient temperature were investigated. The composite coating of oleaster gum with 0.1% cuminal reduced decay, respiration rate, weight loss, and softening of the fruit and decelerated their decreases of total soluble solids, titratable acidity, and soluble proteins, and therefore maintained their marketability. Furthermore, it reduced the accumulation of O•− 2and H2O2 in fruit, and mitigated cell membrane lipid oxidation and permeabilization, thereby retarding their senescence. Instrumentally, it elevated the activities of superoxide dismutase, catalase, peroxidase, and ascorbate peroxidase and the levels of ascorbic acid and glutathione. This potentiation of the fruit antioxidant system makes the composite coating a promising approach to keeping the postharvest quality of perishable fruit.

This study presents an innovative approach for the utilization of industrial by-products and municipal waste in the production of sustainable and environmentally friendly cement mortar. We explored stabilized stainless-steel reduced slag (SSRS) and polyethylene (PE) plastic waste as partial replacements for aggregates. Various engineering properties of the resulting cement mortar specimens, including slump, slump flow, compressive strength, flexural strength, tensile strength, water absorption, and ultrasonic pulse velocity (UPV), were investigated through comprehensive experimental tests. The influence of different water-cement (w/c) ratios and substitution amounts on the engineering properties of the cement mortar samples was thoroughly examined. The findings revealed that an increase in PE substitution adversely affected the overall workability of the cement mortar mixtures, whereas an increase in SSRS amount contributed to enhanced workability. As for the hardened properties, a consistent trend was observed for both cases, with higher w/c ratios and substitution amounts leading to reduced mechanical properties. Water absorption and UPV test results validated the increased formation of porosity with higher w/c ratios and substitution amounts. This study proposes a promising method to effectively repurpose industrial by-products and municipal wastes, transforming them into sustainable construction and building materials. Additionally, a comparative analysis of transportation costs and carbon footprint emissions between SSRS-cement mortar and PE-cement mortar was conducted to assess their environmental impact and sustainability. Generally, higher w/c ratios and replacement levels corresponded to reduced carbon footprint. The geographical location of the source of SSRS and PE remains a challenge and studies to overcome this challenge must be further explored.

Meningitis is a severe disease associated with death in children under five with highest rates of infections under age of one. Vaccines for Neisseria meningitides and Haemophilus influenza are used to prevent the main causative agents of meningitis. Administration of H. influenzae type b (Hib) vaccine is recommended at 2, 4 and 6 months with a booster dose at 18 months. N. meningitidis has two commercially available vaccines, the pure polysaccharide is recommended at 24 months meanwhile the protein-conjugated vaccines at 12 months. We sought in this study to examine if coadministering the vaccines for the two main meningitis causing bacteria might be synergistic as a preliminary step towards the possibility of shuffling immunization schedule. So, we coadministered Hib vaccine with commercially available vaccines either quadrate (ACWY) polysaccharide meningococcal (Men) or conjugated meningococcal (Nim) vaccines in Balb/C mice (n = 6/group) and compared to each vaccine administered separately and controls. Thirty-five days post immunization, we measured specific antibodies titers. Hib vaccine increased Men antibody titers significantly for serotypes Y and W. When Hib vaccine was coadministrated with Nim, antibody titer for Y, W and A significantly increased. For serotype C, there was no significant difference in antibody titers among immunized groups. As for effect of meningococcal vaccines on Hib, Men significantly increased Hib antibody titers while Nim had no effect. Collectively, our data suggested that coadministration of Hib and Men or Nim vaccines was safe and had synergistic effect on immune responses elicited to both vaccines. Further studies are needed before immunization schedule modifications. Such immunization schedule recommendation should provide better protection against this life-threatening disease in young children.

Interferon-gamma (IFN-γ) is an important cytokine in host defense against tuberculosis infection. In some cases, administration of IFN-γ during tuberculosis infection can promote faster cure. In the present work, we have shown that in a mouse model, human interferon-gamma, exhibits some anti-tuberculosis activity, especially in combination with isoniazid.

Background: Fiber-reinforced composites (FRCs) have been proposed as an alternative to traditional metal alloys for the realization of frameworks in full-arch implant supported prostheses. The aim of the present in vitro study was to evaluate the deflection under load of seven prostheses endowed with frameworks made of different materials, including different types of fiber reinforced composites (FRCs). Methods: A master cast with four implant analogues in correspondence of the two lateral incisors and the two first molars was used to create full-arch fixed prostheses with the same shape and different materials. Prostheses were made in different materials (framework+veneering material): gold alloy+resin (Au+R), titanium+resin (Ti+R), FRC with multi-directional carbon fibers+resin (ICFRC+R), FRC with unidirectional carbon fibers+composite (UCFRC+C), FRC with glass fibers+resin (GFRC+R), FRC with glass fibers+composite (GFRC+C), resin (R, full-acrylic prosthesis). Flexural tests were conducted using Zwick/Roell Z 0.5 machine and the deflection of the lower surface of the prosthesis was measured in order to obtain load/deflection graphs. Results: Greater rigidity and less deflection were recorded for UCFRC+C, GFRC+C, followed by Ti+R, and Au+R. The greatest deformations were observed for resin alone, ICFRC+R and GFRC+R. The results were slightly different in the incisal region probably due to the greater amount of veneering material in this area. Conclusions: When used to realize full-arch frameworks, Au and Ti allow a predictable mechanical behavior with gradual deformations with increasing load. UCFRC also demonstrated good outcomes and less deflection than ICFRCs when loaded. The GFRC full-arch framework may be a valid alternative, however showed greater deflections. Further studies are needed in order to evaluated how different prosthesis design and material thickness might affect the outcomes.

Lung cancer (LC) continues to be an important public health problem being the most common form of cancer and a major cause of cancer deaths worldwide. Despite the great bulk of research to identify genetic susceptibility genes by genome-wide association studies, only few loci associated to nicotine dependence have been consistently replicated. Our previously published study in few phenotypically discordant sib-pairs identified a combination of germline truncating mutations in known cancer susceptibility genes in never smoker early-onset LC patient does not present in their healthy sib. These results firstly demonstrated the presence of an oligogenic combination of disrupted cancer predisposing genes in non-smokers patients, giving experimental support to a model of a “private genetic epidemiology”. Here, we used a combination of whole-exome and RNA sequencing coupled with a discordant sib’s model in a novel cohort of pairs of never-smokers early-onset LC patients and in their healthy sibs used as controls. We selected rare germline variants predicted as deleterious by CADD and SVM bio-informatics tools and absent in the healthy sib. Overall, we identified an average of 200 variants per patient, about 10 of which in cancer predisposing genes. In most of them, RNA sequencing data reinforced the pathogenic role of the identified variants showing: i) downregulation in LC tissue (indicating “second hit” in tumor suppressor genes); ii) upregulation in cancer tissue (likely oncogene); iii) downregulation in both normal and cancer tissue (indicating transcript instability). The combination of the two techniques demonstrates that each patient has an average of six (with a range from four to eight) private mutations with functional effect in tumor predisposing genes. The presence of a unique combination of disrupting events in the affected subjects may explain the absence of familial clustering of non-small cell lung cancer. In conclusion, these findings indicate that each patient has his/her own “predisposing signature” to cancer development and suggest the use of personalized therapeutic strategies in lung cancer.

We study the electron tunneling (ET) and local Andreev reflection (AR) processes in a quantum dot (QD) coupled to the left and right ferromagnetic leads with noncollinear ferromagnetisms. In particular, we consider that the QD is also side-coupled to a nanowire hosting Majorana bound states (MBSs) at its ends. Our results show that when one mode of the MBSs is coupled simultaneously to both spin-up and spin-down electrons on the QD, the height of the central peak is quite different from that if the MBS is coupled to only one spin component electrons. The ET and AR conductances which are mediated by the dot-MBS hybridization strongly depend on the angle between the left and right magnetic moments in the leads, which result in sign change of the angle-dependent tunnel magnetic resistance. This result is very different from case when the QD is coupled to regular fermonic mode, and can be used for detecting the existence of MBSs, a current challenge in condensed matter physics under extensive investigations.

This paper proposed a three-layer distributed simulation network architecture: 1. Distributed virtual simulation network, 2. Perception and control sub-network, and 3. Collaborative communication service network. This simulation architecture runs on a distributed platform. The platform can provide a unique virtual scenario and several simulation services to verify the individual robot system's basic perception, control, and planning algorithms and the distributed collaborative algorithms of heterogeneous multi-robot systems. Furthermore, we designed a simulation experiment scenario for classical heterogeneous robot systems such as unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs). At last, We gave a rough estimation model of the bandwidth.

The backwater lowland habitats of large rivers, like the Mississippi River in North America, present complex often inaccessible environments for traditional capture-based fish biodiversity sampling. Our knowledge of the assemblages of fishes that occupy such habitats are often incomplete, and this can compromise management efforts. We employed environmental DNA (eDNA) metabarcoding methods to sample a Mississippi River bottom wetland system to assess ichthyofaunal diversity, and assemblage structure across habitat types, and we compared our results to capture-based survey records for the same habitats. We collected water samples in spring and fall of 2022 from slough, ditch, shallow lake and bayou habitats that varied in depth, vegetation, seasonal variability, and connectivity to the Mississippi River channel. We detected a diverse array of fish species that included 51 taxa. Nearly all species previously documented in the habitats were detected by eDNA metabarcoding, and we increased the number of documented species by more than a third. Most of the species were ubiquitous across the range of habitats, but there was also substantial assemblage structure, with some species exhibiting clear habitat specificity. Fall sampling was limited to the deeper bayou habitats where seasonal variation between spring and fall was minimal. eDNA metabarcode sampling was demonstrated to be effective at detecting invasive species as well as uncommon species, which included several species of conservation concern.

As prominent oil producers, the Gulf Cooperation Council (GCC) countries have played a significant role in the global energy market. However, as the world's attention increasingly shifts towards environmental sustainability, understanding the implications of the GCC's economic activities on CO2 emissions becomes indispensable. This research paper investigates the relationship between specific economic indicators and their impact on CO2 emissions in the GCC from 2001 to 2021. The study employs quantile regression, a powerful statistical method that estimates the conditional quantiles of a response variable given a set of predictor variables. The findings reveal several important insights: Financial institution efficiency is significant and negative at a 1% level at the lower (10th) -83537.3 and the higher quantile (90th) -549002.3. The relationship between GDP per capita and CO2 emissions varies across quantiles, highlighting the complexity of the growth-environment nexus. Total patents exhibit a positive and significant relationship with emissions, underscoring the importance of directing innovation towards environmentally sustainable solutions. Renewable energy consumption displays a nuanced relationship with CO2 emissions, with a stronger negative impact observed at higher consumption levels. This underscores the potential of renewable energy to mitigate emissions when integrated at scale. The study's outcomes hold crucial policy implications for the GCC countries as they seek to align economic growth with environmental sustainability. The findings emphasize the importance of fostering financial institution efficiency, promoting green innovation, and expanding renewable energy sources to reduce emissions

Background: this interventional pilot study aimed to evaluate the short-term (3 years) efficacy of focal laser ablation (FLA) in treating the index lesion of low-intermediate risk prostate cancer, along with assessing the safety of the procedure (ClinicalTrials.gov ID NCT04045756). Methods: forty patients aged between 46 and 86 with histologically proven organ-confined prostate cancer and low to intermediate progression risk were included. FLA was performed under percutaneous fusion magnetic resonance/ultrasound guidance in a Day Hospital setting under local anesthesia. Patients underwent regular clinical assessments, PSA measurements, post-procedure MRI scans, and biopsies at 36 months or if positive findings were detected earlier. Statistical analyses were conducted to assess trends in PSA levels and cavity dimensions over time. Results: forty patients were initially included, with 15 lost to follow-up. At 36 months, a mean PSA reduction of 60% was observed, and 80% of MRI scans showed no signs of in-field clinically significant residual/recurrent cancer. Biopsies at 36 months revealed no malignant findings in 20 patients. No deterioration in sexual function or urinary symptoms was recorded. Conclusions: FLA appears to be safe, feasible and effective in the index lesion treatment of low-intermediate risk prostate cancer, with a high rate of tumor eradication and preservation of quality of life.

In recent years, the AHRS has become an important research area. In order to improve the orientation measurement accuracy of AHRS, this paper first expounds the algorithm principle of the AHRS. Then, aiming at the problem of poor stability of the traditional gradient descent method under high dynamics or large magnetic field interference, a gain-scheduled anti-interference AHRS orientation algorithm is designed. By using the switching architecture designed with this algorithm for gain scheduling, it can ensure stable performance while being subjected to apparent acceleration and ferromagnetic interference. Finally, experimental verification is conducted, and the experimental results show that: in the presence of interference, the roll angle error is 0.0350°, the pitch angle error is 0.0277°, and the yaw angle error is 0.9611°, thereby verifying the strong anti-interference performance of the gain-scheduled AHRS orientation algorithm proposed in this paper.

Background: This study aimed to investigate the impact of the COVID-19 pandemic on breast reconstruction trends in the United States, focusing on implant-based and autologous techniques, as well as the timing of reconstruction (immediate vs. delayed). Methods: A retrospective analysis of data from the American Society of Plastic Surgeons' National Plastic Surgery Statistics from 2015 to 2022 was conducted. Annual trends in breast reconstruction procedures were analyzed, comparing the pre-pandemic (2015-2019) and pandemic (2020-2022) periods. Results: The total number of breast reconstructions increased from 106,338 in 2015 to 151,641 in 2022. The proportion of implant-based reconstructions decreased from 81.41% pre-pandemic to 76.51% during the pandemic (p < 0.001), with a notable rise in direct-to-implant procedures from 10.37% to 19.12% (p < 0.001). Autologous reconstructions increased from 18.59% to 23.49% (p < 0.001). Among autologous techniques, DIEP flaps remained the most popular. Immediate reconstruction rates increased from 72.61% pre-pandemic to 75.57% during the pandemic, while delayed recon-struction rates decreased from 27.39% to 24.43% (p < 0.001). Conclusions: The COVID-19 pandemic has significantly influenced breast reconstruction trends in the United States, with a shift towards autologous techniques, particularly DIEP flaps, and an in-crease in immediate reconstructions. These changes may reflect adaptations in surgical practice and decision-making processes in response to the unique challenges posed by the pandemic. Further research is needed to assess the long-term outcomes and patient satisfaction associated with these trends.

This study investigates the impact of intellectual capital on the sustainable performance of banks in Saudi Arabia, focusing on the period from 2012 to 2022. Utilizing data from ten major Saudi banks, the research examines how different components of intellectual capital—Human Capital Efficiency (HCE), Structural Capital Efficiency (SCE), and Capital Employed Efficiency (CEE)—influence key financial performance indicators such as Return on Equity (ROE) and Net Profit Margin (NPM). The study is grounded in the resource-based view of the firm, which suggests that a firm’s internal resources can provide a sustainable competitive advantage. The analysis employs panel data techniques, including fixed and random effects models, to assess the relationships between intellectual capital components and bank performance while controlling for variables like bank size, financial leverage, GDP growth, inflation, and the impact of the COVID-19 pandemic. The findings reveal that intellectual capital significantly enhances bank performance in Saudi Arabia, with human capital efficiency showing the most decisive influence on ROE and NPM. Structural capital and capital employed efficiency also contribute positively but vary in their impact on different performance measures. This research contributes to the theoretical and practical understanding of the role of intellectual capital in promoting sustainable banking practices. It underscores the importance of strategic management of intellectual capital in enhancing financial performance and achieving sustainability goals, particularly in the context of Saudi Arabia's Vision 2030. The study's insights are relevant for bank managers and policymakers who leverage intellectual capital for economic diversification and sustainable development.

Despite Low Power Wide Area Networks’ ability to offer an extended range, it might still encounter challenges with coverage blind spots in the network. This article proposes an innovative energy-efficient nature-inspired relay selection algorithm for LoRa-based LPWAN networks, serving as a solution for challenges related to poor signal range in areas with limited coverage. A behavior swarm-inspired approach has been utilized to select the relays’ localization in the network, providing network energy efficiency and radio signal extension. These relays help bridge communication gaps, significantly reducing the impact of coverage blind spots by forwarding signals from devices with poor direct connectivity with the gateway. The proposed algorithm considers critical factors for the LoRa standard, such as the Spreading Factor or device energy budget analysis. The simulation experiments validate the proposed scheme’s effectiveness in terms of energy efficiency under diverse multi-gateway topology scenarios involving thousands of devices. Specifically, it has been verified that the proposed approach outperforms the reference method in preventing the battery depletion of relays, which is vital for battery-powered IoT devices. Furthermore, for some large-scale problems, the proposed heuristic method achieves over twice the speed of the exact method with a negligible accuracy loss of less than 2%.

Food production is a complex matter, affecting people’s lives, organizations’ profits, and the well-being of the whole planet and has multifaceted ethical considerations surrounding its production, distribution, and consumption. This paper addresses the pressing need to confront ethical challenges within the food system, encompassing issues such as environmental sustainability, food security, and individual food choices for better oral and systemic health of all individuals around the globe. From agricultural practices to global trade and food waste, ethical implications are addressed across various domains, highlighting the interconnectedness of ethical decision-making in the food industry. Central themes explored include the ethical dimensions of food production methods, the impact of global trade on food ethics, and the role of individuals in making ethically informed food choices. Additionally, the paper dives into the spiritual and physical significance of food, particularly through the lens of oral health as a gateway to holistic well-being. Recognizing the complexity of the food ecosystem, the paper calls for serious interventions in legislation and economics to promote ethical protocols and techniques for sustainability reasons. It emphasizes the importance of ethical considerations in food safety management systems, regulatory frameworks, and quality standards. Moreover, the paper underscores the need for a comprehensive approach to address ethical dilemmas and moral values inherent in the food industry and oral health policies, advocating for the adoption of the precautionary principle and ethical decision-making frameworks. The article aims to serve as a call to action for stakeholders across the food industry and the healthcare sector, to prioritize ethical practices, promote transparency, rearrange economic parameters and work towards a more sustainable and equitable food system for inner and outer oral and systemic health and human sustainability for all.

Commuting is a vital travel channel for college students throughout their higher education career; nevertheless, excessive commute time negatively impacts students’ school satisfaction, academic achievement, health, and quality of life. Meanwhile, few studies have explored students’ commute time, covering a large population and scope. Therefore, this study analyzes the dwelling type that influences college and graduate students’ school commute times in the Seoul Metropolitan Area, using data from the 2016 Household Travel Diary Survey. This study uses spatial data on housing development to classify five dwelling types (i.e., new town, housing site development, Seoul, Incheon, and Gyeonggi-do). A multiple linear regression model empirically analyses students’ household and personal characteristics. The results reveal that dwelling type significantly affects students’ commute time. Specifically, Students living in Seoul have a shorter commute to school than those living in new towns. Socioeconomic characteristics have less effect on college and graduate students' school commute time. This study discusses the problem of excessive commuting of college and graduate students in new towns.

A new class of nano-cube core-shell heterostructures containing Ag coating on the top of WO₃ was fabricated. Physical vapor deposition was used to produce WO₃ based nano-heterostructures. All kind of wet toxic chemical process was avoided to make the process simple and contaminant free. Sputtering of WO₃ and a subsequent thermal annealing process was done to create nano-cubes of WO₃. After that, sputtering of Ag was performed to form the Ag-WO₃ core-shell nano-heterostructures (CSNH). The CSNHs were characterized using field emission scanning electron microscopy (FESEM), energy dispersive spectroscopy (EDS), X-ray diffraction analysis (XRD) and UV-vis spectroscopy. The morphologies, elemental analysis, interfaces, crystallinity, phases, and chemical compositions were analyzed. The bottom-up growth of WO₃ nanocubes was studied using different time periods at 900°C. Ag coating was also studied before and after annealing. Finally, an optical property (band gap) was also analyzed using Tauc plot derive from absorption spectra. The tailoring the band gap of WO₃ from ~2.9eV to ~ 2.45 eV was observed while Ag-WO₃ CSNH formed.

VE is a powerful technique for analyzing a design with a focus on functionality, reducing costs, and increasing value. However, in order to proceed with the design of VE, the theoretical basis for the VE target selection process, which must be preceded in the preparation stage, is lacking, and as a result, it is difficult to verify the most effective target selection. Thus, a theoretical basis is needed. In this study, we intend to quantify the WORTH value of the COST TO WORTH technique and present an objective model of the target selection method using the derived Value Index (VI). For this purpose, cost worth (WORTHC) was calculated based on the performance data of 1,008 cases of 15 building types provided by the Domestic Public Procurement Service and the share of 83 detailed processes in 7 fields. Then, a survey was conducted targeting the ordering companies, and the final worth (WORTHF) was calculated by multiplying the derived customer value (WORTHV ) weight for each detailed work type. We calculated the Value Index (VI) by comparing COST and WORTHF for each detailed construction type of the VE project and developed a model to select construction types that exceed the VI standard value derived using the standard error of the population. Both cost experts and non-cost experts can use the developed model to specify the VE target selection criteria in order to easily select the key target, objectively sort the values that serve as the basis for calculating the value index and make it possible to more easily select the VE target selection criteria based on theoretical evidence. Also, the model can be used to obtain effective detailed design VE results.

When there is uncertainty in the value of parameters of the input random components of a stochastic simulation model, two-level nested simulation algorithms are used to estimate the expectation of performance variables of interest. In the outer level of the algorithm (n) observations are generated for the parameters, and in the inner level (m) observations of the simulation model are generated with the value of parameters fixed at the value generated in the outer level. In this article, we consider the case in which the observations at both levels of the algorithm are independent, showing how the variance of the observations can be decomposed into the sum of a parametric variance and a stochastic variance. Next, we derive central limit theorems that allow us to compute asymptotic confidence intervals to assess the accuracy of the simulation-based estimators for the point forecast and the variance components. Under this framework, we derive analytical expressions for the point forecast and the variance components of a Bayesian model to forecast sporadic demand; and we use these expressions to illustrate the validity of our theoretical results by performing simulation experiments using this forecast model.

Automatic and real-time pose estimation is important in monitoring animal behavior, health and welfare. In this paper, we utilized pose estimation for monitoring farrowing process to prevent piglet mortality and preserve the health and welfare of sow. State-of-the-art Deep Learning (DL) methods have lately been used for animal pose estimation. The aim of this paper was to probe the generalization ability of five common DL networks (ResNet50, ResNet101, MobileNet, EfficientNet and DLCRNet) for sow and piglet pose estimation. These architectures predict body parts of several piglets and the sow directly from input video sequences. Real farrowing data from a commercial farm was used for training and validation of the proposed networks. The experimental results demonstrated that MobileNet was able to detect seven body parts of the sow with median test error of 0.61 pixels.

Precise binding affinity predictions are essential for structure-based drug discovery (SBDD). Focal adhesion kinase (FAK) is a member of the tyrosine kinase protein family and is overexpressed in a variety of human malignancies. Inhibition of FAK using small molecules is a promising therapeutic option for several types of cancer. Here, we conducted computational modeling of FAK targeting inhibitors using 3-dimensional structure-activity relationship (3D-QSAR), molecular dynamics (MD), and hybrid topology-based free energy perturbation (FEP) methods. The structure-activity relationship (SAR) studies between the physicochemical descriptors and inhibitory activities of the chemical compounds were performed with reasonable statistical accuracy using CoMFA and CoMSIA. These are two well-known 3D-QSAR methods based on the principle of supervised machine learning (ML). Essential information regarding residue-specific binding interactions was determined using the MD and MM-PB/GBSA methods. Finally, physics-based relative binding free energy (〖∆∆G〗_RBFE^(A→B)) values of analogous ligands were estimated using the alchemical FEP simulation. An acceptable agreement was observed between the experimental and computed relative binding free energies. The overall results using ML and physics-based hybrid approaches could be useful for the rational optimization of accessible lead compounds with similar scaffolds targeting the FAK receptor.

Sequential hypothesis test and change-point detection when the distribution parameters are unknown is a fundamental problem in statistics and machine learning. We show that for such problems, detection procedures based on sequential likelihood ratios with simple one-sample update estimates such as online mirror descent are nearly second-order optimal. This means that the upper bound for the algorithm performance meets the lower bound asymptotically up to a log-log factor in the false-alarm rate when it tends to zero. This is a blessing, since although the generalized likelihood ratio (GLR) statistics are optimal theoretically, but they cannot be computed recursively, and their exact computation usually requires infinite memory of historical data. We prove the nearly second-order optimality by making a connection between sequential analysis and online convex optimization and leveraging the logarithmic regret bound property of online mirror descent algorithm. Numerical and real data examples validate our theory.

Purpose. This paper aims to present a unique perspective that emphasizes the intricate interplay between energy, dietary proteins, and amino acid composition, underscoring their mutual dependence for health-related considerations. Energy and protein synthesis are fundamental to biological processes, crucial for the sustenance of life and growth of organisms. Methods and Results. We explore the intricate relationship between energy metabolism, protein synthesis, regulatory mechanisms, protein sources, amino acid availability, and autophagy, in order to elucidate how these elements collectively maintain cellular homeostasis. We underscore the vital role this dynamic interplay has in preserving cell life. Conclusion. A deeper understanding of the link between energy and protein synthesis is essential to comprehend fundamental cellular processes. This insight could have wide-ranging impact in several medical fields, such as nutrition, metabolism, and disease management.

High dimensional datasets are highly likely to have redundant, irrelevant, and noisy features that negatively affect the performance of the classification algorithms. Selecting the most relevant features and reducing the dimensions of datasets by removing the undesired features is a dimensional reduction technique called Feature Selection (FS). In this paper, we propose an FS approach based on the Black Hole Algorithms (BHO) with a mutation technique called MBHO. Generally, BHO contains two major phases. At the exploitation phase, a set of stars are modified based on some rule and according to some objective function, the best star is selected as the black hole which attracts other stars. Furthermore, when a star gets closer to the event horizon, it will be swallowed and a new one will be randomly generated in the search space which thus is the exploration phase. However, randomness may cause the algorithm to fall into the trap of local optima, and to overcome such complications, inversion mutation is used. Furthermore, we modify a widely utilized objective function in most of the proposed works for wrapper feature selection by combining two new terms that are based on the correlation among the selected subset of features and the features and the classification label. We also utilize a transfer function, known as the V2 transfer function, to convert continuous values into discrete ones to enhance search. We assess our approach via extensive evaluation experiments using fourteen benchmark datasets. We benchmark the performance of a wrapper FS approach called Binary Cuckoo Search (BCS), and three filter-based FS approaches (namely Mutual Information Maximisation (MIM), Joint Mutual Information (JMI), and minimum Redundancy Maximum Relevance (mRMR)). Our evaluation has shown that the proposed model is an effective approach for FS, in selecting better features that enhance the performance metrics on the classifiers. Thus, MBHO can be utilized as one alternative to the existing state-of-art-approaches. We release the source codes of our implementation for the community to build on with new methods and datasets.

Cisplatin is a widely used anticancer drug for treating solid tumors, but it is associated with severe side effects, including nephrotoxicity. Various studies have suggested that the nephrotoxicity of cisplatin could be overcome; nonetheless, an effective adjuvant drug has not yet been established. Oleanolic acid acetate (OAA), a triterpenoid isolated from Vigna angularis, is commonly used to treat inflammatory and allergic diseases. This study aimed to investigate the protective effects of OAA against cisplatin-induced apoptosis and necroptosis using TCMK-1 cells and a mouse model. In cisplatin-treated TCMK-1 cells, OAA treatment significantly reduced Bax and cleaved-caspase3 expression, whereas increased Bcl-2 expression. Moreover, in cisplatin-induced kidney injury mouse model, OAA treatment alleviated weight loss in the body and major organs and also relieved cisplatin-induced nephrotoxicity symptoms. RNA sequencing analysis of kidney tissues identified lipocalin-2 as the most upregulated gene by cisplatin. Additionally, necroptosis-related genes such as receptor interacting protein kinase (RIPK) and mixed lineage kinase domain like (MLKL) were identified. In vitro study, the phosphorylation of RIPKs and MLKL was reduced by OAA pretreatment in both cisplatin-treated cells and cells boosted by co-treatment with z-VAD-FMK. In conclusion, OAA could protect the kidney from cisplatin-induced nephrotoxicity and may serve as an anticancer adjuvant.

Cultivated adlay or Job’s tear (Coix lacryma-jobi L.) is an important food crop having numerous therapeutic and nutraceutical health benefits. Our study aimed to determine nutrients, minerals, fatty acid composition, and functional groups of seven wild Adlay accessions (brown, black, yellow, grey, green, off-white, and purple) to find out their scope as cereal crops using simple, rapid, and modern analytical techniques. Results revealed variations among bulk densities, specific densities, percent empty spaces, and corresponding grain counts per 10g of sample are valuable characteristics in distinguishing the accessions. Contents of fat, protein, ash, and fibre were found to be comparable to cultivated Adlay. Brown adlay was measured with the highest protein, fat, and fibre contents, 15.82%, 4.76% and 2.37%, respectively. Phosphorus, potassium, calcium, and sodium ranged 0.3% - 2.2%, whereas boron, iron, copper, zinc, and manganese were in the range 1.6mg/kg - 20.8mg/kg. Wild adlay triglyceride composition constituted of polyunsaturated fatty acids as primary fraction followed by olein and palmitic acid as prominent fatty acids. Distinguishing functional groups expressed infra-red frequencies in narrow bands and fingerprint region of proteins associated with out-of-plane region evident structural differences among adlay accessions. Frequency of functional groups in seven accessions indicated black genotype promising for varietal development.

The analysis of chemical warfare agents and their degradation products has become increasingly important for public and military safety in recent years. In the article, we drew attention to the possibilities of the HPLC-ICP-MS analytical technique, which has been relatively rarely used for identifying and quantitatively analyzing highly toxic and hazardous substances in environmental samples. This technique enables the identification and determination of minimal amounts (ppt range) of chemicals in various matrices. This fact is important for the analysis of chemical warfare agents and other highly harmful compounds, even small amounts of which can have serious consequences for living organisms. The article critically analyzes the results of scientific research on the identification and quantitative analysis of extremely toxic organophosphorus, organosulfur and organoarsenic substances, their derivatives and degradation products using high-performance liquid chromatography (HPLC) coupled with inductively coupled plasma mass spectrometry (ICP-MS).

This paper presents a comparative study of fundamental similarity functions for Siamese networks in semantic textual similarity (STS) tasks. We evaluate various similarity functions using the STS Benchmark dataset, analyzing their performance and stability. Additionally, we introduce a multi-objective approach for optimal threshold selection. Our findings provide insights into the effectiveness of different similarity functions and offer a straightforward method for threshold selection optimization, contributing to the advancement of Siamese network architectures in STS applications.

Following technological advances, autonomous and remote-controlled ships are performing trials in some sea areas; a mandatory goal-based MASS code, expected to enter into force on 1 January 2032, is under discussion in the International Maritime Organization (IMO). However, there are no unified standards regarding verification methods to define operating limitations for cutting-edge technologies, which are expected to be elements of MASS, so it is difficult to assess the risk factors for the management and operation of MASS. This paper outlines the regulatory framework for MASS, followed by a discussion of its application, considering the differences between MASS and automated driving, and how to develop safety management and operation using standards for automated driving. A requirements management framework developed as a system and software engineering standards to build safety management and operation of MASS is proposed. It is also suggested that the requirements management framework could be used not only for MASS development but also for regulatory review from a requirements management view.

Researchers have explored primary colour-geometric shape associations since Kandinsky's correspondence theory. However, there is a gap in the literature regarding interior colour applications on surface shapes. To address this gap, an online study was employed to gather data with one hundred participants who were asked to choose their preferred colours for shapes on bedroom walls with follow-up questions on the colour-shape semantic associations, their preference of colours and shapes on bedroom walls independently in addition to their favourite colour, their favourite shape, and colour-shape pairs without interior context. The results revealed that colour-shape preferences in interiors differ from those found in psychology studies, other colour applications on bedroom walls, and other preferences, indicating that colour preference is context-dependent. Interestingly, the most popular colour for surface shapes on bedroom walls is purple, followed by brown and blue. The study contributes to the existing literature by providing colour charts for bedroom applications for professionals in the industry, their clients/users, and future studies.

Energy storage systems play a crucial role in the overall performance of hybrid electric vehicles. Therefore, the state of the art in energy storage systems for hybrid electric vehicles has been discussed in this paper along with appropriate background information for facilitating future research in this domain. Specifically, we have compared the key parameters such as cost, power density, energy density, cycle life, and response time for various energy storage systems. For the energy storage systems employing ultra capacitors, we have presented the characteristics such as cell voltage, cycle life, power density and energy density. Furthermore, we have discussed and evaluated the interconnection topologies for the existing energy storage systems. We have also discussed the hybrid battery-flywheel energy storage system as well as the mathematical modeling of the battery-ultracapacitor energy storage system. Toward the end, we have discussed energy efficient powertrain for hybrid electric vehicles.

According to the requirement of 20kg load of casting barrel, we design a three-dimensional model of the robot and analyze the three stages of liquid level change in the casting barrel during the casting process. Through the analysis, it is determined that the time and angle function is an implicit function, and it is impossible to find the analytical expression of time about angle. The kinetic function of the casting barrel is simulated by MATLAB, and it is found that the function image has mutation points, and when the original function is fitted and approximated by fifth-degree polynomial interpolation, the fifth-degree polynomial function image of the time versus the angular acceleration has a large amplitude of oscillation, especially the mutation points. A PID algorithm based on the discretization of the time and acceleration function is introduced for correction, and the results show that this method effectively reduces the oscillation amplitude of the image and improves the coincidence with the original function.

Since the beginning of the internet era, there has been an explosion of growth in structured data (such as numbers, symbols, and labels) as well as unstructured data (including images, videos, and text). Efficient and accurate mixed query of these two types of data is a key technology to achieve high-quality information retrieval, and it is also a major challenge that needs to be solved urgently in the industry. In this study, we employ an advanced Transformer model that combines strategies and fine-tuning techniques for multi-task learning. Specifically, the model is first pre-trained on a large-scale, general-purpose dataset to learn different types of data representations and basic language comprehension skills. After that, we fine-tuned the parameters of the model to better suit these specific data processing tasks for specific application scenarios, such as image annotation, video content analysis, and structured data query. At the heart of the model is the self-attention mechanism, which allows the model to automatically emphasize the important parts and ignore irrelevant information when processing the input data. In addition, we have introduced task-specific adaptation layers that are designed to add additional processing power to the original Transformer architecture, such as a semantic analysis layer for unstructured text data and a relational extraction layer for structured data. This combination of general pre-training and task-specific fine-tuning allows the model to flexibly process and integrate information from different data sources, improving processing efficiency and accuracy. Experimental results show that the model performs well in a variety of data processing tasks, significantly improves the accuracy and efficiency of information retrieval, and verifies the strong potential and adaptability of large language models in processing mixed data types.

The process of oxygenic photosynthesis is primarily driven by two multiprotein complexes known as photosystem II (PSII) and photosystem I (PSI). PSII facilitates the light–induced reactions of water–splitting and plastoquinone reduction, while PSI functions as the light–driven plastocyanin-ferredoxin oxidoreductase. In contrast to the highly conserved structure of PSII among all oxygen–evolving photosynthetic organisms, the structures of PSI exhibit remarkable variations, especially for photosynthetic organisms that grow in special environments. In this review, we make a concise overview of the recent investigations of PSI from photosynthetic microorganisms including prokaryotic cyanobacteria and eukaryotic algae from the perspective of structural biology. All known PSI complexes contain a highly conserved heterodimeric core; however, their pigment compositions and peripheral light-harvesting proteins are substantially flexible. This structural plasticity of PSI reveals the dynamic adaptation to environmental changes for photosynthetic organisms.

This paper reviews the requirements for the production, quality, and quality assurance of solid recovered fuels (SRF) that are increasingly used for the substitution of fossil fuels in the indus-trial utilities. The economical, technological and environmental aspects should be considered before using SRF as an alternative fuel. In general, the most important factors determining the commercial production of SRF referred to the calorific values and their available amounts adopted in the starting materials. Furthermore, the low-melting impurities and undesired constituents/elements, including chlorine, sulfur, potassium and sodium, may pose negative impacts on air pollutant emission and slagging & fouling in the process utilities. In this regard, the vent emitted from the industrial utilities must comply with the effluent standards of station-ary sources like particulate, sulfur oxides, nitrogen oxides, heavy metals (e.g., lead, cadmium, and mercury) and dioxins. For these reasons, this work will summarize the legal or regulatory requirements under development in Asian countries (i.e., Japan, South Korea, and Taiwan) and European Union (EU). Finally, the outlook of solid recovered fuel (SRF) in the waste manage-ment and industrial sectors will be addressed to echo the sustainable development goals (SDGs).

Quaking aspen (Populus tremuloides Michx.) landscapes are valued for their biodiversity, water retention, fire mitigation, aesthetics, and recreation opportunities. Across North America, some aspen populations are experiencing population declines as they face uninhibited ungulate browsing, drought, fire suppression, insects, disease, and inappropriate management. Increased human development and recreational use within aspen landscapes can serve as additive stressors, though there is a dearth of literature examining these elements. At a popular recreational area in Utah, USA, identifying the cause of apparent decline within a larger aspen community is complicated by development upstream and recreation-related activities. We sought to: 1) assess the overall condition of the aspen at the site, 2) understand key variables that influence aspen conditions, and 3) elucidate how aspen fitness varies across the site. We collected data from forty-five plots using established aspen sampling methods, including ungulate presence, tree characteristics, soil chemistry, and environmental descriptors. Results suggest that a combination of higher levels of browsing and elevated soil sodium may be causing premature mortality and limiting aspen recruitment in a portion of the study area. These findings will inform future management at this site, as well as similar recreational forest settings experiencing compound stressors.

The mechanisms underlying the establishment of asymmetric structures during development remain elusive. The wing of Drosophila is asymmetric along the Anterior-Posterior (AP) axis, despite that its growth signals that drive its growth are presumably symmetric. Here, we investigated the contribution of cell recruitment, a process that drives wing fate differentiation in Drosophila, to the asymmetric shape and pattern of the adult wing. Genetic impairment of cell recruitment results in a significant reduction in adult wing asymmetry, primarily affecting the region between longitudinal vein 5 and the wing margin (L5-M). Morphometric analysis reveals that the lack of cell recruitment results in a more symmetric wing with respect to the AP, suggesting a contribution of cell recruitment to the establishment of asymmetry in the adult wing. A close examination of the expression of the wing selector gene vestigial (vg) in wing disc does not support this hypothesis. However, the circularity of the Vg pattern significantly increase in recruitment-impaired wing disc, suggesting that while the decrease of the L5-M region in the adult wing may not be attributed to cell recruitment, it could contribute to the overall asymmetry of the adult wing. We conclude that cell recruitment, a widespread mechanism that participates in growth and patterning of several developing systems, could drive, at least partially, the asymmetric shape of the Drosophila wing.

This study aimed to review the dietary risk factors for root caries prevalence in older adults, from socially active people to frail patients. A comprehensive search strategy was used to select studies from PubMed and Scopus databases. Two evalua-tors performed data extraction, screening, and quality assessment independently. Only studies written in English were included. Caries is very common in the elderly, as there are several aggravating factors such as the decrease of the ability to self-care and, by extension, insufficient oral hygiene, a carious diet, limited exposure to fluoride, xero-stomia, gingival recession, limited access to dental care. Root caries is prevalent in the elderly due to gingival recession and root exposure to the oral environment. Dietary risk factors significantly affect root caries prevalence in older adults, including high intake of sugars and an alteration of their composition preference in this age group. Caries risk appears more significant in frail, standardized patients who feed with even softer food or supplements.

The social- and self-directed behaviours of two golden lion tamarins (Leontopithecus rosalia) was investigated while having residence in the tropical house of Aalborg Zoo, Denmark. The behaviour of the female had been distinct from the male since 2018. Despite several diagnostic examinations and medicinal treatments, the cause of the aberrant and apparently stereotypical behavioural patterns remained undetermined, which initiated this study. The pair were recorded throughout a predetermined observation period and these recordings were analysed to illuminate the behaviours of the individuals. The results showed that there were differences in the type, frequency, and durations of both social- and self-directed behaviours between the sick female and the healthy male. The female expressed both social- and self-directed behaviours more frequently and for longer durations, while the male were more socially reserved and did not engage in social behaviours as frequently. Furthermore, subsequent necropsy of the female revealed uro-genital disease.

Antibiotic resistance is a global health problem. The human gut microbiome is implicated in the dynamics of antibiotic resistance acquisition and transmission, with the gut microbiota thought to play a crucial role. This study aimed to determine the potential influence of human gut bacteria microbiota on the gut resistome and the relationship between gut background microbiota and Escherichia coli resistome. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines was used to systematically review studies that characterised gut microbiota and resistome using metagenomic analysis and/or those that reported gut E. coli resistome in healthy individuals. Changes in the diversity and abundance of bacterial gut microbiota and the resistome across different groups and the microbiota composition of the gut harbouring antibiotic-resistant E. coli were summarised. Findings suggest that lower bacterial microbiota diversity is likely associated with an increased abundance of the overall gut resistome. Age-related differences were observed, with younger infants exhibiting lower microbiota diversity and higher ARG abundance compared to older infants and adults. Studies that reported correlation revealed positive correlations between the compositional relative abundance of Proteobacteria and ARGs abundance, mainly driven by members within the Enterobacteriaceae family, particularly E. coli. This study also revealed that human gut microbiome studies that investigate gut resistome using metagenomic sequencing approaches in apparently healthy individuals are at least uncommon.

Epigenetic mechanisms, including histone post-translational modifications (PTMs), play a critical role in regulating pain perception and the pathophysiology of burn injury. However, the epigenetic regulation and molecular mechanisms underlying burn injury-induced pain remain insufficiently explored. Spinal dynorphinergic (Pdyn) neurons contribute to heat hyperalgesia induced by severe scalding-type burn injury through p-S10H3-dependent signaling. Beyond p-S10H3, burn injury may impact various other histone H3 PTMs. Double immunofluorescent staining and histone H3 protein analyses demonstrated significant hypermethylation at H3K4me1 and H3K4me3 sites and hyperphosphorylation at S10H3 within the spinal cord. By analyzing Pdyn neurons in the spinal dorsal horn, we found evidence of chromatin activation with a significant elevation in p-S10H3 immunoreactivity. We used RNA-seq analysis to compare the effects of burn injury and forma-lin-induced inflammatory pain on spinal cord transcriptomic profiles. We identified 98 DEGs for burn injury and 86 DEGs for formalin-induced inflammatory pain. A limited number of shared differentially expressed genes (DEGs) suggest distinct central pain processing mechanisms between burn injury and formalin models. KEGG pathway analysis supported this divergence, with burn injury activating Wnt signaling. This study enhances our understanding of burn injury mechanisms and uncovers converging and diverging pathways in pain models with different origins.

Infection with human immunodeficiency virus (HIV) and induced acquired immune deficiency syndrome (AIDS) represent one of the greatest health burdens worldwide. The complex pathophysiological pathways that link highly active antiretroviral therapy (HAART) and HIV infection per se with dyslipidemia make the management of lipid disorders and the subsequent increase in cardiovascular risk essential for the treatment of people living with HIV (PLHIV). Amongst the HAART regimens, darunavir and atazanavir in terms of protease inhibitors, tenofovir disoproxil fumarate, nevirapine or rilpivirine in terms of nucleoside reverse transcriptase inhibitors and non-nucleoside reverse transcriptase inhibitors respectively, and especially integrase inhibitors, have demonstrated the most favorable lipid profile emerging as sustainable options in HAART substitution. To this day, statins remain the cornerstone pharmacotherapy for dyslipidemia in PLHIV, although important drug-drug interactions with different HAART agents should be taken into account upon treatment initiation. For those intolerant or not meeting therapeutic goals, the addition of ezetimibe, PCSK9, bempedoic acid, fibrates or fish oils should also be considered. This review summarizes the current literature on the multifactorial etiology and intricate pathophysiology of hyperlipidemia in PLHIV, with an emphasis on the role of different HAART agents, while also providing valuable insights into potential switching strategies and therapeutic options.

Mental disorders impact a significant portion of the global population, presenting substantial challenges to healthcare systems due to high hospitalization costs and resource demands. This narrative review explores the economic implications of mental health disorders, focusing on hospitalization costs, the effectiveness of interventions, and the outcomes of recent research. Materials and Methods: A narrative review was conducted, sourcing articles from PubMed and Google Scholar published between 2014 and 2024. The search terms included combinations related to mental illness, costs, hospital care, and mental healthcare interventions. A total of 1,110 articles were initially identified, with 37 studies meeting the inclusion criteria after rigorous screening by two independent researchers. These studies included quantitative and qualitative data covering a range of outcomes such as hospital admission rates, consumer satisfaction, and quality of life. The findings of the present review reveal that mental disorders significantly increase hospitalization costs due to frequent admissions, extended stays, and the need for specialized treatments. Additionally, physical comorbidities in individuals with mental disorders lead to higher healthcare costs and resource use. Integrated care models, early intervention, and preventive strategies show promise in reducing these costs and improving patient outcomes. Conclusions: Our review emphasizes the critical need for integrated healthcare strategies that address both mental and physical health to reduce hospitalization costs and improve outcomes. Effective management of mental health disorders requires comprehensive approaches, including complex outpatient services and preventive care. Future research should focus on standardizing methodologies to provide clearer insights into the economic impact of mental health conditions and guide effective healthcare strategies.

In the context of evolving perceptions of sexuality, particularly within the realm of health and disability, this study investigates the impact of multiple sclerosis (MS) on female sexual function and quality of life. A quantitative study involving 130 female MS patients aged 35 to 50 was conducted, employing measures such as The Female Sexual Function Index (FSFI), The Multiple Sclerosis Intimacy and Sexuality Questionnaire-19 (MSISQ-19), and The Fatigue Severity Scale (FSS). Results indicate a significant association between greater sexual dysfunction and poorer quality of sex life, alongside the correlation of increased fatigue with diminished sexual satisfaction. Factors such as education level, time of diagnosis, and treatment regimen also influenced outcomes. Findings underscore the importance of supportive interventions, including counseling, to enhance the quality of sex life for women with disabilities, particularly those with MS.

Evans' Syndrome (ES) is a rare autoimmune disorder characterized by the simultaneous occurrence of immune thrombocytopenia (ITP) and autoimmune hemolytic anemia (AIHA). Thrombotic complications in ES patients are uncommon, particularly involving Buerger's Disease (BD). We report a case of a 49-year-old male with ES and a history of diabetes and heavy smoking, presenting with a necrotic wound on his right great toe. Diagnostic evaluations revealed severe stenosis and thrombosis in the lower limb arteries, diagnosed as BD. The patient underwent successful popliteal-tibioperoneal artery bypass surgery and subsequent disarticulation and revision of the distal phalanx, followed by the application of an acellular dermal matrix (ADM) to promote healing. Post-surgery, the patient showed significant improvement in blood flow and complete epithelialization without complications. This case highlights the importance of a multidisciplinary approach in managing complex wounds in ES patients, suggesting potential treatment pathways for future cases involving BD

In response to the fairness issue arising from the unequal delay of vehicles in different phases at intersections, considering the actual situation of small and variable delays for vehicles in low-saturation intersection phases, this paper proposes the concept of "sacrificing efficiency for fairness." Firstly, the universality of unfair delay phenomena at intersection phases is explained, especially at low-saturation intersections where the fluctuation in phase delays is 1.87 times higher than at other intersections. Then, a fairness evaluation index is constructed using information entropy, and the feasibility of the proposed approach is demonstrated. Subsequently, a signal optimization model that balances efficiency and fairness is proposed. Finally, the proposed model is validated through case studies, showing that it not only simultaneously considers efficiency and fairness but also has minimal impact on efficiency. Moreover, the changes to timing schemes in the efficiency model are much smaller compared to the model that only considers fairness. Sensitivity analysis reveals that the model performs better under low-saturation intersection conditions.

Applied talent is not only a builder of human civilization but also a promoter of economic development. They not only need systematic and solid engineering theoretical knowledge but also rich engineering practical experience. Applied undergraduate colleges are the cradle for cultivating applied talent and shoulder the important mission of cultivating various types of applied talent for society. With the rapid development of higher education, the number of applied undergraduate institutions has sharply increased, but the quality of applied talent cultivated by them has shown a significant decline, which greatly restricts the pace of industrial development in the world. This article proposes a new concept of promoting the "three certificates" (graduation certificate, degree certificate, and skill certificate) education model in applied undergraduate colleges, which is of great significance for the country to cultivate composite talents with the ability of "product design, production management, and product processing" at the same time.

This paper addresses the evolving landscape of electricity markets in Europe, with a focus on the integration of Renewable Energy Communities as introduced by the Renewable Energy Directive 2018/2001. Residents within a postal code area are highly incentivized to join a community, which enables them to exchange energy among themselves at lower procurement costs. Thereby, energy management systems optimize the operation of respective energy systems, with electrical load forecasting playing a key role. Given that prosumers may switch between communities on a daily basis, electricity demands within these groups will vary, leading to data that is non-stationary, discontinuous as well as non-identical and independently distributed. To encounter this issue, we propose a sophisticated forecasting model that applies federated learning, using informations from various distributed communities to learn domain-invariant features. To achieve this, we initially utilize synthetic electrical load time series at district level and aggregate them to profiles of Renewable Energy Communities with dynamic portfolios. Subsequently, we develop a forecasting model that accounts for the composition of residents of a Renewable Energy Community, adapt data pre-processing in accordance with the time series process, and detail a federated learning algorithm that incorporates weight averaging and data sharing. Following the training of various experimental setups, we ultimately evaluate their effectiveness. The findings suggest that our proposed framework is capable of effectively forecast non-stationary and discontinuous time series and that it can be applied to new, unseen data through the integration of knowledge from multiple sources.

Examining contemporary developments and cutting-edge approaches in the field, this literature review explores how antenna design for transmission lines is changing. Review findings are compiled from a variety of academic sources, including pertinent technical reports published as recently as 2018, conference papers, journal articles, and reports. A variety of antenna topologies suited for transmission lines are evaluated in this paper, including microstrip, slot, and patch antennas, with a focus on theoretical frameworks and practical implementations. This overview clarifies the complex relationship between antenna design and transmission line characteristics by looking at important factors like impedance matching, bandwidth, and radiation pattern management. Notable developments in materials, fabrication methods, and numerical simulations are also examined and their effects on antenna performance explained. Through a comprehensive analysis of the literature, this review offers valuable insights into the state-of-the-art antenna design practices for transmission lines, facilitating informed decision-making and inspiring future research endeavors in this field.

Abstract: With the growing integration of the Internet of Things (IoT) in smart buildings, it is crucial to ensure the precise implementation and operation of wireless sensor networks (WSNs). This paper aims to study the implementation aspect of Wireless Sensor Networks (WSNs) in a commercial multi-story building, specifically addressing the difficulty of dealing with variable environmental conditions on each floor. This research addresses the disparity between simulated situations and actual deployments, offering valuable insights that have the potential to signifi-cantly improve the efficiency and responsiveness of building management systems. We obtain real-time sensor data to analyze and evaluate the system’s performance. Our investigation is grounded in the growing importance of incorporating WSNs into buildings to create intelligent environments. By leveraging the capabilities of Contiki operating system, this study employs a specialized simulator to generate simulated data, allowing for a comparison between real-world and simulated scenarios. We provide an in-depth analysis to scrutinize the disparities and commonalities between the datasets obtained from real-world deployments and simulated en-vironments. We highlight the necessity of precise simulation to validate real-life sensor data, shedding light on the challenges and opportunities associated with implementing WSNs in in-telligent buildings. Results obtained show the significance of accurate simulation models for re-liable data representation, providing a roadmap for further developments in the integration of WSNs into intelligent building scenarios. The findings highlight the potential for optimizing living and working conditions based on the real-time monitoring of critical environmental pa-rameters. This includes insights into temperature, humidity, and light intensity, offering oppor-tunities for enhanced comfort and efficiency in intelligent environments.

Understanding morphological and genetic diversity of forest trees is essential to facilitate their conservation, sustainable management and genetic improvement for addressing the economic and environmental demands and challenges. We have examined variation in morphometric seed and pod traits and seed germination of multipurpose and widely distributed forest tree Albizia lebbek (Indian siris) from 12 provenances covering the species’ range in northern India and its relationships with bioclimatic factors. Highly significant inter-provenance variation was observed in seed size (seed length (SL), seed width (SW), SW/SL, SL×SW), seed mass (1000 seed weight), pod size (pod length (PL), pod width (PW), PW/PL), seed germination, number of seeds per pod, and insect infected seeds (IIS). The provenance effect contributed a major portion to the total phenotypic variance. Morphometric variation in all traits except for IIS was not clinal related to longitude, latitude, altitude or rainfall. There was an indication of the presence of ecotypic variation. IIS showed clinal variation with significant negative correlation with latitude. Most seed size and pod size traits showed positive correlations with several temperature bioclimatic factors and negative correlations with several precipitation bioclimatic factors. Our results have significance for genetic improvement, population genetics and genomics studies and conservation and sustainable management of A. lebbek genetic resources.

This paper presents a comprehensive comparative analysis of four different computational vision algorithms for implementing an unpalleting system in a factory environment, under typical edge computing constraints. The primary objective is to automate the process of detecting and locating specific variable-shaped objects on a pallet, enabling a robotic system to accurately unstack them. The four algorithms evaluated are Pattern Matching, Scale-Invariant Feature Transform, Oriented FAST and Rotated BRIEF, and Haar cascade classifiers. Each technique is described in detail in this paper, and their implementations are outlined. Experimental results are thoroughly analyzed, assessing the algorithms’ performance based on accuracy, robustness to variability, computational speed, detection sensitivity, and resource consumption. The findings reveal the strengths and limitations of each algorithm, providing valuable insights for selecting the most appropriate technique based on the specific requirements of the unpalleting system. This research contributes to the advancement of automated object detection and localization in industrial environments, paving the way for more efficient and reliable unpalleting systems.

The relationship between the structure characteristics and performances of coal based hydrogenation isomeric base oil (CTL) and metallocene catalyzed coal based polyalphaolefin (mPAO) base oil was clarified here. CTL and mPAO were compared with typical petroleum based and natural gas based commercial API Class III and IV base oils. Pressurized differential scanning calorimetry (PDSC), Rotary Bomb Oxidation Test (RBOT) and four-balls friction tester were used to evaluate the oxidation stability and lubrication performance of base oils under different working conditions. The sensitivity of different base oils to typical antioxidants and extreme pressure antiwear agents was compared. Specially, the composition and structure of CTL base oil are obviously different from GTL and mineral base oil. The coal-based CTL and mPAO base oils exhibit commendable viscosity-temperature properties, characteristics, coupled with low-temperature fluidity, fire safety, and minimal evaporation loss. The lubricating properties, oxidation stability and the sensitivity to extreme pressure antiwear agents of CTL are close to those of similar base oils. But the sensitivity of CTL to typical antioxidants is relatively poor. Besides, compared with commercial PAO base oil, mPAO has lower isomerization degree and fewer isomerization types. The oxidation stability and sensitivity to typical antioxidants of mPAO base oil are comparable with those of commercial PAO base oil, while its lubrication performance and sensitivity to typical extreme pressure antiwear agents are significantly better than those of commercial PAO base oil.

We assessed depression, anxiety, and stress in healthcare workers (HCWs) in 2023 and the evo-lution of depression in 2023 compared with 2022. In September-November 2023, 181 HCWs from the Infectious Diseases Hospital, Cluj-Napoca, Romania, completed the Depression, Anxiety, and Stress 21 Scale (DASS-21 R), the Patient Health Questionnaire-9 (PHQ-9), and the Hamilton Anxiety Rating Scale (HAM-A). The prevalence of moderate-to-severe levels was 13.81% for DASS-Depression, 18.79% for DASS-Anxiety, 16.02% for DASS-Stress, 19.89% for PHQ-9, and 12.16% for HAM-A. Moderate-to-severe PHQ-9 clinical depression was found in 19.89% of respondents, and moderate-to-severe HAM-A clinical anxiety in 12.16%. Moderate-to-severe PHQ-9 depres-sion was significantly lower in the 2023 study group (19.89%, N=181) compared with 2022 (30.60%, N=114) (p=0.036), also within the 2022-2023 follow-up study group (N=88) (p=0.026). We did not find significant statistical differences between those infected vs. non-infected, vaccinated vs. non-vaccinated, working with vs. non-working with SARS-CoV-2 infected patients. Males were significantly more stressed (p=0.018) and anxious (p=0.034), and physicians in training had the highest prevalence of moderate-to-severe depression (31.60%), followed by physicians (25.64%). In 2023, depression, anxiety, and stress symptoms decreased but remained within a concerning range. By addressing these psychological issues, we can prevent professional crises in the healthcare system.

Energy metabolism regulates the proliferation of stem cells by regulating energy production and the production of substrates through biosynthetic pathways. It is an important target for cell regulation and stem cell applications, and is crucial for determining the pluripotency and cell fate of stem cells. In this context, this article focuses on reviewing the latest research progress on the association between glucose metabolism, amino acid metabolism, fatty acid metabolism, and mitophagy with stem cell function, elucidating how key energy metabolism pathways affect stem cell function by regulating signal transduction and epigenetic modifications. In this review, we discuss the key factors affecting energy metabolism and their association with stem cell function. The integration of energy metabolism and stem cell fate regulation will open up a new path for future regenerative medicine practices.

Selenium is essential for the synthesis and function of various selenoenzymes, such as glutathione peroxidases, selenoprotein P, and thioredoxin reductase, which play an important role in both antioxidant defense and limiting oxidative damage. Associations between serum selenium concentration and obstetric complications as well as pregnancy outcomes has been reported in many studies. The aim of this study was to determine whether the dietary intake of selenium, its concentration in serum and the activity of glutathione peroxidase in subsequent trimesters of pregnancy affect the birth condition of newborns assessed on the basis of the Apgar score in the 1st and 5th minute of life, birth weight, body length and head and chest circumference in physiological and complicated pregnancy course. Twenty-seven pregnant women at a mean age 29.6 ± 4.8 years from the Lower Silesia region of Poland were recruited to the study, 55% of studied group had pregnancy complications. The mean reported Se intake and serum selenium content for Polish pregnant women was in the first trimester – 56.53 μg/day and 43.75 μg/l, the second trimester – 61.79 μg/day and 41.77 μg/l and the third trimester – 58.37 μg/day and 42.13 μg/l, respectively. In the subgroup of pregnant women with a physiological pregnancy course, a weak, although statistically significant, positive correlation was found in the first trimester between Se intake and the length (R=0.48, p=0.019) and birth weight of newborns (R=0.472, p=0.022), and in the second trimester with the APGAR score at 1 (R=0.680, p=0.005) and 5 minutes (R=0.55, p=0.033), as well as in the third trimester with th APGAR score at 1 minut (R=0.658, p=0.019). The GPX value had a strong positive correlation with the APGAR score at 1 min. (R=0.650, p=0.008) in the second trimester and with the birth weight of the newborns (R=0.598, p=0.039) in the third trimester. There was no correlation between newborns' birth measurements and serum selenium concentration. In the subgroup of pregnant women with pregnancy complications, a strong, statistically significant, negative correlation was found between Se intake in the second trimester and gestational age (R=-0.618, p=0.032), and in the third trimester, a positive correlation between Se concentration in serum and head circumference (R=0.587, p=0.021). The obtained results indicate that there is a relationship between the maternal selenium status during pregnancy, both in terms of the intake of this element, its serum concentration as well as the glutathione peroxidase activity, and the anthropometric parameters of the newborn, such as birth weight, length and APGAR score, especially in the group with physiological course of pregnancy, but when pregnancy complications occur, these relationships lose their importance.

The study aims to examine the effects of artificial intelligence (AI) on the consistency and analysis of financial statements in hotels in ASEZA, Jordan. This research is an exploratory, empirical study, which uses the methodology of data collection and interpretation to draw conclusions. The researchers used the arithmetic mean, standard deviation, T-test and ANOVA test to calculate the degree of significance of the study questions. The findings of a basic linear regression study of the impact of AI implemented in Jordanian hotels on the integration of accounting information systems and the association between AI and the integration of accounting information systems (R = 59.6%) also indicate that the fixed limit value amounted to (2.060) and the value of (Beta) for T-test

MultiCal is an affordable, high-precision measuring device designed for the on-site calibration of industrial robots. Its design features a long measuring rod with a spherical tip that is attached to the robot. By restricting the rod’s tip to multiple fixed points under different rod orientations, the relative positions of these points are accurately measured beforehand. A common issue with MultiCal is the gravity deformation of the long measuring rod, which introduces measurement errors into the system. This problem becomes especially serious when calibrating large robots, as the length of the measuring rod needs to be increased to enable the robot to move in a sufficient space. To address this issue, we propose two improvements in this paper. Firstly, we suggest the use of a new design of the measuring rod that is lightweight yet has high rigidity. Secondly, we propose a deformation compensation algorithm. Experimental results have shown that the new measuring rod improves calibration accuracy by 20% to 39%, while by using the deformation compensation algorithm, the accuracy increases by 6% to 16%. In the best configuration, the calibration accuracy is similar to that of a measuring arm with a laser scanner, producing an average positioning error of 0.274 mm and a maximum positioning error of 0.838 mm. The improved design is cost-affordable, robust, and has sufficient accuracy, making MultiCal a more reliable tool for industrial robot calibration.

The Qiushuwan Cu-Mo deposit, located in the East Qinling molybdenum belt, which is a major mining site recognized for its enormous reserves of medium-sized molybdenum. In order to enhance our comprehension and ascertain supplementary mineral resources, it is critical to conduct an in-depth investigation of both the deep and peripheral regions. The primary goal of this study is to investigate the Qiushuwan Copper Molybdenum Mine, which is located in Zhenping County, Henan Province. The spread spectrum-induced polarization (SSIP) method is utilized as a means of conducting mining exploratory analysis. Significant findings have been obtained through the collection of SSIP data, geological analysis, and electrical parameter study of rock and ore samples along profile-80. By conducting a meticulous examination of the SSIP data at suitable frequencies, two prominent conductive ore bodies, specifically C2 and C4, have been successfully discovered. C2 exhibits a correlation with granite porphyry and molybdenum veins, while C4 is linked to a skarn deposit that contains a concentration of copper ore. The spatial differences in conductivity within the research area have been precisely characterized using resistivity models obtained from the SSIP data. The precision and dependability of our conclusions have been confirmed through the integration of borehole data and the matching of geological sections with inversion models. The recovered core samples show a diverse range of minerals, containing both valuable ores and minerals that have undergone alteration. Pyrite constantly appears with molybdenite in the majority of samples. The aforementioned results provide a strong foundation for future exploration initiatives and sustainable resource exploitation, enabling informed decision-making in the effective use and administration of natural resources. This study adds to the existing body of knowledge on the Qiushuwan Cu-Mo deposit and improves exploration methods in the region by utilizing the SSIP approach. The findings are a useful asset for geologists, mining experts, and stakeholders, offering essential knowledge for future exploration and sustainable utilization of resources.

Increased anthropogenic pressure on forest resources leads to deforestation and forest degradation, significantly limiting the regeneration capacity of native woody species and consequently the restoration of miombo woodlands in anthropized habitats within the rural area of Lubumbashi. This study assessed the diversity and natural regeneration capacity of miombo species through floristic inventories in three different habitats (unexploited forests, degraded forests, and post-cultivation fallows). The results reveal that for the adult’s stratum unexploited and degraded forests exhibit higher dendrometric (density, mean square diameter, basal area) and floristic parameter (taxa, genera, families) values compared to post-cultivation fallows. Furthermore, the regeneration of miombo woody species is higher in degraded forests (21 taxa; 105 juveniles/plot). However, regarding the sapling’s stratum (1 cm ≤ dbh &lt; 10 cm), the three habitats display nearly similar situations. Additionally, the floristic composition and diversity of unexploited and degraded forests show a significantly higher similarity (76.50%) among them compared to these habitats and the post-cultivation fallows (56.00%). These findings indicate that miombo woodlands have the potential to regenerate and maintain floristic diversity. To sustain this natural regeneration capacity of miombo woody species and promote the restoration of forest mass and its floristic diversity, it is imperative to determine the rotation period after habitat exploitation and regulate anthropogenic activities and late bush fires, particularly in anthropized habitats at the village level.

This study outlines the development of an innovative method utilizing UHPLC-PDA for the simultaneous identification of polyphenols and bitter acids (alpha-acids, beta-acids, and iso-alpha-acids) in beer samples. The resulting chemical profiles were leveraged to distinguish the characteristics of four bergamot-flavored beers, each representing distinct styles (IPA, Lager, Blanche, and ALE), produced on a pilot-scale plant. In a streamlined 29-minute analysis, twenty-nine polyphenols and fourteen bitter acids were successfully identified under optimized separation conditions. Rigorous validation, encompassing parameters such as Limit of Detection (LOD), Limit of Quantification (LOQ), R-squared (R2), repeatability, and reproducibility, was conducted for polyphenol quantification using constructed calibration curves with seven levels. Exploring polyphenolic components as potential discriminators among different beer styles, a total of thirty-two polyphenolic compounds were identified and quantified, including characteristic bergamot peel polyphenols like neoeriocitrin, naringin, and neohesperidin. The determination of bitter units and total phenols further aided in style differentiation. Multivariate analysis provided additional insights into variations among specific beer styles, revealing discrepancies in the presence or relative concentrations of specific compounds linked to brewing ingredients and processes. This research enhances to trace the fingerprinting of the chemistry governing beer quality through a straightforward and cost-effective analytical approach, readily applicable in common laboratories.

Silicon carbide particle-reinforced aluminum matrix (SiCp/Al) composites are significant lightweight metal matrix composites extensively utilized in precision instruments and aerospace sectors. Nevertheless, the inclusion of rigid SiC particles exacerbates tool wear in mechanical machining, resulting in a decline in the quality of surface finish. This work undertakes a comprehensive investigation into the problem of tool wear in SiCp/Al composite materials throughout the machining process. Initially, a comprehensive investigation was conducted to analyze the effects of cutting velocity vc, feed per tooth fz, milling depth ap, and milling width ae on tool wear during high-speed milling under SCCO2-MQL (Supercritical Carbon Dioxide Minimum Quantity Lubrication) ultrasonic vibration conditions. Furthermore, a prediction model for tool wear was developed by employing the orthogonal test method and multiple linear regression. The model's relevance and accuracy were confirmed using F-tests and t-tests. Ultimately, through the utilization of a genetic algorithm, the milling parameters were optimized, resulting in the identification of the most optimal combination of parameters. Empirical findings suggest that the careful selection of milling parameters can significantly mitigate tool wear, extend the lifespan of the tool, and enhance the quality of the surface. This work serves as a significant point of reference for the processing of SiCp/Al composite materials.

Background: Despite advances in the treatment of hepatocellular carcinoma (HCC) over the last few decades, treatment opportunities for patients with HCC remain limited. HCC is the most common form of liver cancer, accounting for approximately 90% of all cases worldwide. Moreover, apart from the current pharmacological interventions, hepatic resection and liver transplantation are the mainstay curative approaches for patients with HCC. Methods: This systematic review included phase I, II, III, and IV clinical trials (CTs) and randomized controlled trials (RCTs) on current treatments for patients with HCC in an Asian population (2013–2023). A total of 427 articles were screened, and 184 non-duplicate publications were identified. After screening titles and abstracts, 96 publications were excluded, and another 28 were excluded after full-text screening. The remaining 60 eligible RCTs/CTs were finally included. Results: Sixty clinical trials fulfilled our inclusion criteria and screened 36 drugs as monotherapy or combination therapy for HCC. Most studies used sorafenib alone or in combination with any of the treatment regimens. Lenvatinib or atezolizumab with bevacizumab was used for HCC after initial sorafenib treatment. Eighteen studies compared the efficacy of sorafenib with that of other drugs, including lenvatinib, cabozantinib, tepotinib, tigatuzumab, linifanib, erlotinib, resminostat, brivanib, tislelizumab, selumetinib, and refametinib. Conclusion: This study provides comprehensive insights into effective treatment interventions for HCC in Asian populations. The overall assessment indicated that sorafenib alone or in combination with atezolizumab and bevacizumab has been the first treatment choice in the past decade to achieve better outcomes in patients with HCC in an Asian population

The Eurasian grapevine (Vitis vinifera L.) is the most widely grown horticultural crop in the world and is important for the economy of many countries. In the wine production chain, grape varieties play an important role as they directly influence the authenticity and classification of the product. Identifying the different grape varieties is therefore fundamental for quality control and inspection activities, as well as for regulating production. Currently, ampelography and molecular analysis are the main approaches to identifying grape varieties. However, both methods have limitations. Ampelography is subjective and prone to errors and is experiencing enormous difficulties as ampelographers are increasingly scarce. On the other hand, molecular analyses are very demanding in terms of cost and time. In this scenario, Deep Learning (DL) and Machine Learning (ML) methods have emerged as a classification alternative to deal with the scarcity of ampelographs and avoid molecular analyses. In this study, the most recent and current methods for identifying grapevine varieties using DL classification-based approaches are presented through a systematic literature review. The classification pipeline of the 31 studies found in the literature was described, highlighting its pros and cons. Most of the studies used DL-based models trained with leaf images acquired in a controlled environment at a maximum distance of 1.2 metres to classify grape varieties. In addition, there is a large gap between practical applications and the datasets used: a great lack of varieties, limited data acquired in the field and a lack of tests on plants under adverse conditions. Potential directions for improving this area of research were also presented.

Smart City has emerged as the mainstream paradigm for urban governance innovation, sustainable development, and strategy upgrades, which is drawing attention from scholars worldwide. However, current frameworks for Smart City assessment remain incomplete and simplistic. In is paper, 30 national or provincial capitals in China were selected and we designed a tri-dimensional SPI model—Social, Physical, and Information Space—for smart city spatial development assessment. Utilizing methods such as entropy weighting, coupled coordination degree models, and the Dagum Gini coefficient, this study assesses the spatial development and coupled coordination of 30 cities from 2011 to 2019. Finally, by means of BP neural networks, the study examines the contribution of each indicator to the spatial coupled coordination. The results indicated that with a narrowing disparity in development speeds among different regions, the spatial coupled coordination development level of smart capitals in China has steadily increased, presenting a pattern of staggered distribution. Moreover, the IS subsystem plays the most significant role in coupled coordination. The significance of this research lies in its tri-dimensional spatial perspective of the spatial development and coupled coordination differences of the Smart City, providing evidence-based support for the regional layout and optimization in China.

Grain quality, cooking quality and nutritional quality traits are some of the major attributes that enhance uptake and utilisation of improved cowpea varieties. Therefore, there is need for a better understanding of the genetic variation and inter-relationships among these quality traits in cowpea to integrate them in cowpea breeding programs. The study was conducted to determine genetic variability among 306 cowpea genotypes for grain quality, cooking quality and nutritional quality traits and to understand the interrelationships among these traits for exploitation in breeding programs. The results showed highly significant differences (P

Introduction: Laeverin is an extravillous trophoblast marker playing a significant role in the trophoblast migration. The purpose of this study was to evaluate the association between the amniotic and serum laeverin concentrations at 16-22 weeks of gestation and the fetal and placental ultrasound measurements in healthy, unaffected pregnancies. Materials and methods: This was a prospective cross-sectional study. Pregnant women with singleton pregnancies undergoing amniocentesis were recruited consecutively. Fetal structural malformations and/or aneuploidy were exclusion criteria. Fetal biometric parameters and placental growth/perfusion were measured in 44 high-risk pregnancies who had no pregnancy complication and any other chronic disease. Maternal serum and amniotic levels of laeverin were essayed with sandwich enzyme-linked immunosorbent assay. Results: Serum laeverin levels are decreasing slightly with the maternal age in mid-gestation. Serum laeverin level correlated negatively slightly with head size of the fetus with the gestational length at delivery (β=-0.38, 95% confidence interval (CI) -0.03-0.01), while the amniotic laeverin level correlated strongly with the abdominal circumference of the fetus (β=-0.64, 95% CI: -0.03-0.01). Furthermore, laeverin level in the amnion correlated moderately and positively with the placental volume (β=0.46, 95% CI: 0.01-0.08). Conclusions: Laeverin levels detected in the serum and in the amniotic fluid denotes the fetoplacental growth in uncomplicated high-risk pregnancies.

In this paper, a new axial-type magnetic gear with auxiliary flux-enhancing structure (AFS-AMG) is proposed. Compared to conventional AFS-AMG, it has the higher torque density and higher permanent magnet (PM) utilization factor. Firstly, the design rules and operating principles of proposed AFS-AMG are elaborated. Then, the mapping relation between the radial-type magnetic gears (RMGs) and AMGs are elucidated. Compared to its counterpart in RMGs, AFS-AMGs achieve small size. Then, the geometrical parameters of AFS-AMGs are optimized to obtain the better electromagnetic performances, where the torque density per volume and per PM volume is adopted as the evaluation standard. Finally, three different AMG topologies are constructed in finite element analysis (FEA) software for comparison. It is proven that the AFS-AMG has the largest torque density per volume and per PM volume.

The design complexity of the new generation of civil aero-engines results in higher demands on engines’ components, higher component temperature, higher heat generation, and, finally, critical thermal management issues. This paper will propose a methodological approach to create physics-based models for heat loads developed by sources as well as a systematic sensitivity analysis to identify the effects of design parameters on the thermal behaviour of civil aero-engines. The ranges and levels of heat loads generated by heat sources (e.g., accessory gearbox, bearing, pumps, etc.) and heat absorption capacity of heat sinks (e.g., engine fuel, oil, and air) are discussed systematically. The practical research challenges for thermal management system design and development for the new and next generation of turbofan engines will then be addressed through a sensitivity analysis of the heat load values as well as the heat sinks flow rates. The potential solutions for thermal performance enhancements of propulsion systems will be proposed and discussed accordingly.

Recent technological advancements in conservation genetics and genomics have resulted in diverse tools for aiding conservation of species. The precision and resolution of high throughput sequencing technologies provide valuable insights to aid conservation decisions, but these technologies are often financially unfeasible or unavailable in resource constrained countries. Inter-Simple Sequence Repeat (ISSR) markers, when combined with sensitive automated detection systems, provide a simple, cheap means to investigate genetic diversity and discriminate closely related species. Here we apply this technology to assess genetic diversity and taxonomic delimitation in the Encephalartos eugene-maraisii species complex, a highly threatened, taxonomically dubious group of cycads in South Africa. Our analyses support taxonomic singularity of E. dyerianus, E. dolomiticus and E. eugene-maraisii. Relationships between E. nubimontanus and E. cupidus remain uncertain. E. middelburgensis samples showed no clustering but had poor amplification success. This study demonstrates the suitability of automated ISSR fingerprinting as a method for plant conservation studies, especially in resource-constrained countries, and we make recommendations as to how this methodology can be effectively implemented.

The spread of micro- (MPs) and nanoplastics (NPs) in the environment has become a significant environmental concern, necessitating effective removal strategies. In this comprehensive scientific review, we examine the use of magnetic nanoparticles (MNPs) as a promising technology for the removal of MPs and NPs from water. We first describe the issue of MPs and NPs and their impact on the environment and human health. Then the fundamental principles of using MNPs for the removal of these pollutants will be presented, emphasizing that MNPs enable selective binding and separation of MPs and NPs from water sources. Furthermore, we provide a short summary of various types of MNPs that have proven effective in the removal of MPs and NPs. These include ferromagnetic nanoparticles, MNPs coated with organic polymers, as well as nanocomposites and magnetic nanostructures. We also review their properties, such as magnetic saturation, size, shape, surface functionalization and stability, and their influence on removal efficiency. Next, we describe different methods of utilizing MNPs for the removal of MPs and NPs. We discuss their advantages, limitations, and potential for further development in detail. In the final part of the review, we provide an overview of existing studies and results demonstrating the effectiveness of using MNPs for the removal of MPs and NPs from water. We also address challenges that need to be overcome, such as nanoparticle optimization, process scalability, and the removal and recycling of nanoparticles after the completion of the process. This comprehensive scientific review offers an extensive insight into the use of MNPs for the removal of MPs and NPs from water. With improved understanding and the development of advanced materials and methods, this technology can play a crucial role in addressing the issue of MPs and NPs and preserving a clean and healthy environment.

As matrix representations of magic labelings of related hypergraphs, magic squares and their various variants have been applied to many domains. Among various subclasses, trimagic squares have been investigated for over a hundred years. The existence problem for trimagic squares with singly even orders and orders 16n has been solved completely. However, very little is known for the existence of trimagic squares with other even orders except for the only three examples and three families. We construct normal trimagic squares by using product constructions, row-square magic rectangles, and trimagic pairs of orthogonal diagonal Latin squares. We give a new product construction: For positive integers p, q, and r having the same parity other than 1, 2, 3, 6, if normal p × q and r × q row-square magic rectangles exist, then a normal trimagic square with order pqr exists. As its application, we construct normal trimagic squares of orders 8q^3 and 8pqr for all odd integers q not less than 7 and p,r ∈ {7, 11, 13, 17, 19, 23, 29, 31, 37}. Our construction can easily be extended to construct multimagic squares.

Previously, we described a 19-base pair double-stranded RNA with 3'-trinucleotide overhangs, acting as immunostimulatory RNA (isRNA). This molecule demonstrated notable antiproliferative effects on cancer cells, inhibited tumor growth, and elicited immunostimulatory and antiviral responses by inducing cytokine and interferon production. Within this study, we compared the efficiency of lung fibrosis development, initiated in mice by BLM or LPS using different schemes of induction. Then we compared the effect of isRNA used in a preventive or therapeutic regimen on the development of fibrosis in selected BLM- and LPS-induced mouse models and showed that isRNA can be used in pathological conditions accompanied by the development of inflammation and the risk of fibrosis formation, without adverse side effects. Prophylactic regimen of isRNA application is beneficial for prevention of the development of pulmonary fibrosis.

In this study, we investigated the features of co-infection with SARS-CoV-2 and nonpathogenic strain LEV8 of coxsackievirus A7 or enterovirus A71 for Vero E6 cells and Syrian hamsters. The investigation of co-infection with SARS-СoV-2 and LEV-8 or EV-A71 in the cell model was shown that a competitive inhibitory effect for these viruses were especially significant against SARS-CoV-2. Pre-infection with enteroviruses in animals caused more than a 100-fold decrease in the levels of SARS-CoV-2 virus replication in the respiratory tracts and more rapid clearance of the lower respiratory tract from infectious SARS-CoV-2. Co-infection with SARS-CoV-2 and LEV-8 or EV-A71 also reduced the severity of clinical manifestations of the SARS-CoV-2 infection for animals. Additionally, the histological data illustrated that co-infection with nonpathogenic coxsackievirus decreased the level of pathological changes by SARS-CoV-2 in the lungs. Research into the chemokine/cytokine profile demonstrated that the studied enteroviruses efficiently triggered this part of antiviral immune response, which can be associated with significant inhibition of SARS-CoV-2 infection. These results demonstrate that there exists a strong viral interference between the studied nonpathogenic strain of coxsackievirus A7 or enteroviruses A71 and SARS-CoV-2 pathogenic for humans in vitro and in vivo.

Population-based data on hematologic malignancies (HM) are rare in Greece regarding adults (≥18 years old). The aim of this study was the assessment of the burden of these malignant neoplasms (MN) for adults in Crete. The study assessed temporal trends of incidence and mortality, depicted their spatial distribution and extracted net-survival curves of patients. Population-data on these MN were obtained from the database of the Cancer Registry of Crete, for a 22 year time period (1/1/1992-31/12/2013). All HM were classified into four main groups of diseases: (1) Hodgkin’s lymphoma (HL); (2) Non-Hodgkin’s lymphomas (NHLs); (3) Multiple myeloma (MM); and (4) All chronic and acute leukemias. Annual, gender-specific, age standardized incidence and mortality rates were estimated (ASIR/100.000/year; ASMR/100.000/year). A total of 3,380 newly diagnosed cases were included in the final analyses; All ASIRs/100,000 increased significantly throughout the study period presenting differences in their geographical distribution of rates among municipalities of Crete. ASIRs for NHLs, HL, MM, leukemias and for all 4 MN were 13.1, 2.6, 4.7, 11.7 and 32.1, respectively, in 2013. Five-year net-survival for patients diagnosed with NHLs, HL, MM and leukemias were: 82%, 85%, 52% and 56%, respectively. This first research article studying a long period of time for adults in Greece generates hypotheses on the existence of risk factors that may partly explain this variation of rates.

Wilms tumor (WT), the most prevalent type of renal cancer in children, exhibits overall survival rates exceeding 90%. However, chemotherapy resistance, which occurs in approximately 10% of WT cases, is a major challenge for the treatment of WT, particularly for advanced-stage patients. In this study, we aimed to discover potential mutation markers and drug targets associated with chemotherapy resistance in advanced stage WT. We performed exome sequencing to detect somatic mutations and molecular targets in 43 WT samples, comprising 26 advanced stage WTs, of which 7 cases are chemotherapy-resistant. Our analysis revealed four genes (ALPK2, C16orf96, PRKDC, and SVIL) that correlated with chemotherapy resistance and reduced disease-free survival in ad-vanced-stage WT. Additionally, we identified driver mutations in 55 genes within the chemo-therapy-resistant group, including 14 druggable cancer driver genes. Based on the mutation profile of the resistant WT samples, we propose potential therapeutic strategies involving platinum-based agents, PARP inhibitors, and antibiotic/antineoplastic agents. Our findings provide insights into the genetic landscape of WT and offer potential avenues for targeted treatment, particularly for patients with chemotherapy resistance.

Building Information Modeling (BIM) is undeniably the most important trend in the digitization of the construction sector in recent years. BIM models currently being built are extremely geometrically rich, that is, they are modeled at a high level of detail in terms of geometry. Thanks to object-oriented programming paradigms, BIM models include high-level relationships to ensure interactions between objects, rapid view generation and documentation. However, these models are not always equally rich in non-graphical data. This is true for parameters at the library object level, with which building object models are saturated, but also at the project, site, building or floor level according to the structure of the interoperable Industry Foundation Classes (IFC) format. For this reason, experimental work was undertaken on semantic enrichment in non-graphical data of a public building (Public Kindergarten, Secemin, Poland), which has its BIM model at a high level of geometric detail but is poor in non-graphical data. As a result of the research and development work, all levels of the IFC structure were saturated with non-graphical data, validated, and the possibilities of their use were shown from the perspective of the facility manager. The article contributes to the discussion on semantic enrichment from CAD3D to BIM by presenting a detailed process for entering non-graphical data into a BIM model.

Functional partially linear regression model, contains a functional linear part and a non-parametric part, in which testing the linear relationship between the response and the functional predictor is of fundamental importance. When functional data cannot be approximated with a few principal components, based on a pseudo estimate for the unknown non-parametric component, we develop a U-statistic of order-two in this paper. Under some regularity conditions, we use the martingale central limit theorem to prove that the proposed test statistic is asymptotically normal. The finite sample performance with simulation studies and real data application are assessed to verify the proposed test procedure.

This research examines sustainable approaches in academic career development by analyzing the interactions between job satisfaction, professional commitment, and research performance among early-career researchers in Romanian institutions. Using a quantitative cross-sectional design, data were collected from 96 individuals classified as R1 and R2 by the European Commission. A detailed questionnaire and Web-Assisted Personal Interviewing (WAPI) identified key relationships. Findings show a significant positive correlation between job satisfaction and research perfor-mance, underscoring the role of professional satisfaction in fostering sustainable academic ex-cellence. Professional commitment is also a crucial predictor of research performance, aligning with existing studies and highlighting the importance of sustainable career practices. Statistical analysis via SPSS version 23.0 validated the initial hypotheses, emphasizing each dimension's significance in a sustainable academic career. Results reflect Romania's research environment, emphasizing the need for sustainable working conditions, effective research evaluation, sup-portive career frameworks, and strong professional commitment to motivate young researchers. This research proposes innovative, sustainable practices for enhancing academic performance and career management, advocating clear objectives, leadership development, continuous competency improvement, and a collaborative, inclusive work environment. Understanding these factors aids individuals and institutions in making informed decisions that support sustainable academic career trajectories and professional growth.

In the area of dental healthcare services, where patients and professionals deal with multiple auditory stimuli, this cross-sectional study reports on the intricate dynamics of sound preferences, noise obstacles, and the profound impact of music on anxiety reduction within dental office set-tings. The sample comprises of 134 dental patients, primarily females (56.7%), with varying age groups, education levels, and therapy durations in the university clinics of the department of Dentistry, National and Kapodistrian University of Athens and four private dental offices at the metropolitan area of Athens, Greece. Notably, 92.5% of the participants report no hearing loss, and 56.7% exhibit some level of noise sensitivity. The study reveals a moderate to good perceived health status (M=3.84, SD=0.95) among participants, with low perceived noise disturbance in university dental clinics. Preferences for instrumental music, foreign pop, and classical music are prominent during waiting times. Potential irritations include impersonal treatment (44%) and staff behavior (41.8%). Music player usage within the settings of the dental clinic involves radios (49.3%) and headphones (41.0%). Correlations and predictors indicate associations between health status, music preferences, and noise disturbances. More specifically, visiting the university dental clinics (β = .300, p = .005) as well as younger age (β = .300, p = .034) were significant predictors of better perceived health status. Clearer perception of external sounds while using the music player (β = .190, p = .039) was a significant predictor of better perceived health status, while poorer health was predicted by the preference of Greek folk songs (β = -.200, p = .030). Also, the use of smartphones for playing music was related to poorer health (β = -.370, p < .001). Following, younger age (β = -.270, p = .015), lower education (β = -.210, p = .035), higher noise sensitivity (β = .190, p = .027), as well as feelings of anxiety and nervousness due to ambient noise from people and machines (β = .510, p = .027) were significant predictors of noise disturbance from machines. Also, visiting private clinics (β = .240, p = .018), preferences of specific playlist (β = .310, p = .012), no music (β = .280, p = .016) and use of smartphones to play music (β = .230, p = .029) were significant predictors of noise disturbance from patients or staff. Finally, the preference of listening to a specific playlist was related to better health status (r = .190, p < .05). Findings aim to optimize eco-soundscapes in dental offices, con-tributing to enhanced patient well-being. The research underscores the potential of music inter-ventions to alleviate dental anxiety and improve the overall dental experience and quality care.

The purpose of this study is to establish whether digital literacy and insurtech adoption influence insurance inclusion in Uganda. Principally, we sought to determine whether insurtech adoption mediates the nexus between digital literacy and insurance inclusion. This study adopted a cross-sectional and quantitative correlational approach. The study’s sample was 391 individuals who had used digital platforms such as mobile phones and computers to access insurance products and services in Uganda. Data were collected using structured survey questionnaires. Partial Least Squares Structural Equation Modelling (PLSEM) was employed to test the hypothesised relationships. The results demonstrate that both digital literacy and insurtech adoption significantly and positively influence insurance inclusion. We also found digital literacy to be a significant and positive determinant of insurtech adoption. Markedly, it was found that insurtech adoption mediates the association between digital literacy and insurance inclusion in Uganda. However, this study was conducted in a developing country with an underdeveloped insurance market and with low technological advancement. This may affect generalisation of the study findings. This study’s novelty lies in establishing how digital literacy and insurtech adoption interplay to influence insurance inclusion in Uganda. This is the first study to examine the effect of digital literacy and insurtech adoption on insurance inclusion.

This paper presents geometric analyses of welded frames after free relaxing and vibratory stress relief (VSR). Respected frames were tested components of a prototype packaging machine. Two types of relaxation were carried out to remove stresses introduced as a result of welding process. One of the frame was subjected to free relaxing, while the other one to accelerated vibration relaxing. Detection of the frame geometry changes was performed using a photogrammetric system. In addition, an evaluation of the geometry change was conducted for fifteen variants of steel frame support. A comparative analysis of the geometric deviations of the frames after free and vibratory stress relief confirmed the assumption that the frame after vibration stress relief better reproduces the nominal dimensions. Nevertheless, it should be emphasized that after vibratory stress relief the frame is not subject to further deformation, which is a desirable effect. In the case of free relaxing, the frame undergoes dimensional changes in a random manner. In summary, carrying out accelerated vibratory stress relief allows control of spontaneous dimensional changes in the designed frame of a packaging machine resulting from spontaneous relaxation of stresses arising from the welding process. The shortening of the relaxation process of the welded frame is also an unquestionable advantage.

Accurate forecasting of available energy portion that corresponds to the reservoir inflow of the month(s) ahead provides important decision support for the hydropower plants in energy pro-duction planning for revenue maximization, as well as for the environmental impact prevention, and flood control at the upstream and downstream of a basin. Therefore, a reliable forecasting tool or model is deemed necessary and crucial. Considering the fluctuation and nonlinearity of data which significantly influence the forecasting results, this study develops an effective hybrid model by integrating Artificial Neural Network (ANN) and Particle Swarm Optimization (PSO) called “PSO-ANN” model based on the hydrological and meteorological data pre-processed by cross-correlation function (CCF), autocorrelation function (AFC), and normalization techniques for predicting the available energy portion corresponding to the reservoir inflow mentioned above for a case study hydropower plant in Laos namely, Theun-Hinboun hydropower plant (THHP). The model was evaluated by using correlation coefficient (r), relative error (RE), root mean square error (RMSE), and Taylor diagram plots in comparison with the popular single algorithm approaches such as ANN, and NARX models. Results demonstrated the superiority of the proposed PSO-ANN approach over the other two models.

This study aims to find countries that differ in their development of the agricultural sector in terms of environmental care and to examine the relationship between renewable and non-renewable energy consumption and agricultural sector production in European Union countries. The classification of countries was conducted using the principal component method and biplot. Panel data for the period 2000-2022 and a VAR model, an impulse response function (IRF) and causality tests were used for the study. The results indicate two distinct groups of countries that significantly differ in adopting green agricultural practices. Only seven EU countries stand out for sustainable agriculture with low pesticide use, a significant share of organic farms and high use of renewable energy in agriculture. Energy consumption affects agricultural production differently in the two groups of countries studied: in countries with sustainable agriculture, an increase in renewable energy consumption translates into a positive increase in agricultural production. On the other hand, an increase in non-renewable energy consumption shows a dampening effect on agricultural production growth, especially in countries with less sustainable agriculture. The study results highlight the need to promote renewable energy development in agriculture and raise awareness about the adverse environmental effects of intensive agriculture while emphasising the positive impact of organic agriculture on agricultural production.

Artificial intelligence (AI) tools, such as OpenAI's Chat Generative Pre-trained Transformer (ChatGPT), have great potential in various fields, such as healthcare, education, and industry. This review highlights the applications and challenges of the ChatGPT versions 3.5 and 4.0 in radiology. ChatGPT can process medical texts, analyze medical images, and generate reports and summaries for different audiences. ChatGPT can also answer patients' questions and translate complex medical information into a plain language. ChatGPT has shown impressive results in medical tests and quizzes, indicating its potential to enhance diagnostic accuracy and medical education. These models show promise for reducing diagnosis times and healthcare costs. However, ChatGPT also faces challenges and limitations, such as a lack of visual content, ethical and legal issues, data quality, and error detection. This review highlights the benefits and future directions of ChatGPT and artificial intelligence (AI) in radiology.

In Southern Asia, Bangladesh is a well-known developing country. Because of COVID-19, we continuously face challenges. Not only can these issues occur beyond economic or health concerns, but they also generate dangerous social problems, such as family abuse. Since the inception of this epidemic, multiple social crimes are looming. Remaining home during the lockout period enhances divorce rates. This research presents a customized forecast of family violence during the COVID-19 outbreak by using machine learning methods. In this paper, we have applied Random Forest, Logistic Regression, and Naive Bayes machine learning classifiers to predict family violence and discovered the feature importance. The performance of the classifiers is evaluated based on accuracy, precision, recall, and F-score. We have employed an oversampling strategy named synthetic minority oversampling technique (SMOTE) to solve the imbalance problem of our data. Even, we have tried to compare three machine learning model performances before and after balancing of normalization data. Finally, ROC analyses and confusion matrices were developed and analyzed by using data augmentation. Our proposed system with the random forest classifier performed better with 77% accuracy in comparison with other two machine learning classifiers.

With the rapid development of earth observation, satellite navigation, mobile communication and other technologies, the order of magnitude of the spatial data we acquire and accumulate is increasing, and higher requirements are put forward for the application and storage of spatial data. Under this circumstance, a new form of spatial data organization emerged-the global discrete grid. This form of data management can be used for the efficient storage and application of large-scale global spatial data, which is a digital multi-resolution the geo-reference model that helps to establish a new model of data association and fusion. It is expected to make up for the shortcomings in the organization, processing and application of current spatial data. There are different types of grid system according to the grid division form, including global discrete grids with equal latitude and longitude, global discrete grids with variable latitude and longitude, and global discrete grids based on regular polyhedrons. However, there is no accuracy evaluation index system for remote sensing images expressed on the global discrete grid to solve this problem. This paper is dedicated to finding a suitable way to express remote sensing data on discrete grids, and establishing a suitable accuracy evaluation system for modeling remote sensing data based on hexagonal grids to evaluate modeling accuracy. The results show that this accuracy evaluation method can evaluate and analyze remote sensing data based on hexagonal grids from multiple levels, and the comprehensive similarity coefficient of the images before and after conversion is greater than 98%, which further proves that the availability hexagonal grid-based remote sensing data of remote sensing images. And among the three sampling methods, the image obtained by the nearest interpolation sampling method has the highest correlation with the original image.

Plants are such important keys of biological part of our environment, supply the human life and creatures. Understanding how the plant’s functions react with our surroundings, helps us better to make plant growth and development of food products. It means the plant phenotyping gives us bio information which needs some tools to reach the plant knowledge. Imaging tools is one of the phenotyping solutions which consists of imaging hardware such as the camera and image analysis software analyses the plant images changings such as plant growth rates. In this paper, we proposed a preprocessing algorithm to eliminate the noise and separate foreground from the background which results the plant image to help the plant image segmentation. The preprocessing is one of important levels has effect on better image segmentation and finally better plant’s image labeling and analysis. Our proposed algorithm is focused on removing noise such as converting the color space, applying the filters and local adaptive binarization step such as Niblack. Finally, we evaluate our algorithm with other algorithms by testing a variety of binarization methods.

Background/Objectives: PEMF therapy has gained significant attention due to its potential benefits in promoting tissue repair and improving overall well-being. Recent publications in the field of exercise physiology, showed that pulsed electromagnetic fields (PEMFs) enhanced the velocity and the quantity of muscle O2 available and the rate of muscle oxygen extraction and utilization, in semi-professional cyclists, during a heavy constant-load exercise. In this paper, we investigate the effect of stimulation on muscular activation, in sedentary young people, during a constant-load exercise, performed at moderate intensity. Methods: Nine male sedentary young people, partic-ipated in this study. The response of the muscle activity, was recorded by surface EMG and assessed measuring the root mean square (RMS) normalized to the peak of the maximum voluntary con-traction. Data were collected in the right vastus Medialis (RVM) and right Biceps Femoris (RBF) at the baseline (standstill sitting), on warm-up (unloaded cycling) and during 30 minutes of con-stant-load exercise, in two experimental conditions (PEMF ON vs PEMF OFF). Results: The mul-tivariate analysis of variance performed on RVM showed a significant effect of PEMF in both warmup and exercise, while on RBF showed a significant effect of PEMF and warmup. Conclusions: PEMF strongly enhanced the amplitude of muscle activity in young sedentary people. The increase in the amplitude of the muscular response may lead to a higher oxygen consumption and release.

The diel variations of viruses (< 0.2 μm), picoplankton (0.2—2 μm; heterotrophic bacteria, Syn-echococcus spp., Prochlorococcus spp. and picoeukaryotes) and nanoplankton (2—20 μm; hetero-trophic nanoflagellates and pigmented nanoflagellates) were investigated for 2 days with about 4 hours of temporal sampling in spring 2024 in coastal surface waters of the subtropical western Pacific. A period of wind change associated with rain and increased turbulence, disrupted diel patterns of the overall microbial communities during the second cycle. The abundance of bacteria did not follow a consistent diel pattern, while viral abundance positively correlated with bacterial abundance. Synechococcus spp. and Prochlorococcus spp. grew during the light period and with peak abundance at night, exhibited marked diel variability, however, opposite patterns were observed in picoeukaryotes. According to Synechococcus spp. and Prochlorococcus spp. diel changes, nano-flagellate grazing could control their abundances and may explain temporally varying picocyanobacteria abundances. As we observed in the culture experiments, the results showed a significant increase in picoeukaryotic abundance from noon to nighttime, and a decrease in bacterial abundance during nighttime, to show the prey-predator cycle. Our study suggests picoeukaryotes could serve as bacteria predators by being mixotrophs. Future studies aiming to understand the interactions between prokaryotes and picoeukaryotes within marine microbial communities should take these differences into account.

The aim of the study was the comparison of conventional sintering versus additive manufacturing techniques for β-TCP bioceramics, focusing on mechanical properties and biocompatibility. A "critical" bone defect requires surgical intervention beyond simple stabilization. Autologous bone grafting is the gold standard treatment for such defects but it has its limitations. Alloplastic bone grafting using synthetic materials is becoming increasingly popular. The use of bone graft substitutes has increased significantly and current research was focused on optimizing these substitutes, whereas this study compares two existing manufacturing techniques and the thereby produced β-TCP implants. The 3D-printed β-TCP hybrid structure implant was fabricated using two components, a column structure and a freeze-foam, which were sintered together. The conventionally manufactured ceramics were made by pouring. Both scaffolds were characterized according to porosity, mechanical properties and biocompatibility. The hybrid structure had a total porosity of 74.4 ± 0.5%. Microporous β-TCP implants had a porosity of 43.5 ± 2.4%, while macroporous β-TCP implants had a porosity of 61.81%. Mechanical testing revealed that the hybrid structure had a compressive strength of 10.4 ± 6 MPa, significantly lower than the microporous β-TCP implant’s with 32.9 ± 8.7 MPa. Biocompatibility evaluations showed a steady increase in cell proliferation over time for all β-TCP implants, with minimal cytotoxicity. This study provides valuable insight into the potential of additive manufacturing for β-TCP bioceramics in the treatment of bone defects.

(1) Background: The aim of the research was to present and emphasize the importance of magnetic resonance imaging (MRI) in diagnosing Achilles tendon (AT) ruptures by presenting case reports. (2) Materials and Methods: The sample of respondents included 7 patients (4 males and 3 females, 2 athletes and 5 non-athletes), aged 25 to 58 years, with AT injuries, who were examined and treated at the Institute for Treatment and Rehabilitation "Niška Banja", Niš, Serbia. Ankle examinations with MRI were conducted using the Esaote O-scan 0.3 T machine. The examinations were performed without the application of a paramagnetic contrast agent and without the use of anesthesia. Results: The MRI method's sensitivity and overall diagnostic accuracy were excellent, with 100% true positives. In our study, the method accurately detected the presence, location, and severity of AT injuries in all cases. MRI is an important and reliable method for detecting AT injuries, classifying them, monitoring the course of recovery, and assessing the effects of therapy. Conclusions: An unrecognized or delayed diagnosis of an AT injury can lead to chronic changes. Timely diagnosis (clinical examination, ultrasonography, magnetic resonance imaging) and appropriate treatment (conservative or operative) enable patients to return to normal activities, including sports. Unfortunately, the use of MRI is limited by restricted access and the cost of the examination.

The paper provides and comments on the results of studies of the effect of sandstone-based abrasives and quartz sand alone on the wear of martensitic surfaces of wear-resistant steels. The wear process was examined on a ring-on-ring test rig seeking to determine the mass decrement parameter which characterised wear. The tests were conducted for three sandstone varieties: Carboniferous, Permian, and Cretaceous, and they made it possible to determine that the most intense process of deterioration of wear-resistant steels took place in the presence of quartz sand grain, while less intense wear was observed in the case of sandstone-based abrasives. The mass decrement values established in the presence of the sandstones in question did not differ significantly between individual sandstone varieties. Based on a surface damage analysis, the basic damage mechanism was found to be micro-scratching, however, with regard to the sandstones examined, it was also determined that individual grains could be pressed into surface irregularities, as well as that films of soft hematite cement developed in the Permian sandstone and that inclusions of carbonaceous matter were formed in the Carboniferous sandstone. With reference to the wear process observations, a wear model was described for the surface of the steels examined in the presence of sandstone-based abrasives.