Age-related changes in behavior and sensory perception have been observed in a wide variety of animal species. In ants and other eusocial insects, workers often progress through an ordered sequence of olfactory-driven behavioral tasks. Notably, these behaviors are plastic, and workers adapt and rapidly switch tasks in response to changing environmental conditions. In the Florida carpenter ant, smaller minors typically perform most of the work needed to maintain the colony while the larger majors are specialized for nest defense and rarely engage in these routine tasks. Here, we investigate the effects of age and task group on olfactory responses to a series of odorant blends in minor and major worker castes. Consistent with their respective roles within the colony, we observed significant age-associated shifts in the olfactory responses of minors as they transitioned between behavioral states, whereas the responses of majors remained consistently low regardless of age. Furthermore, we identified a unitary compound, 3-methylindole, which elicited significantly higher responses and behavioral aversion in minor nurses than in similarly aged foragers suggesting that this compound may play an important role in brood care. Taken together, our results suggest that age- and task-associated shifts in olfactory physiology may play a critical role in the social organization of ant colonies.

In this paper, mineralogical and elemental geochemical characteristics of massive sulfide samples collected from Jade hydrothermal field, located in the Izena depression in the central graben of Okinawa Trough, were analyzed by means of optical microscopy, scanning electron microscopy and electron probe. The results show that the sulfide in Jade hydrothermal area can be divided into Zn-Cu-Pb rich massive sulfide and Zn-Fe rich massive sulfide. The former is composed of sphalerite, galena, anglesite, chalcopyrite and pyrite, and its formation stage can be divided into pyrite stage, sphalerite-chalcopyrite stage, anglesite stage and colloidal pyrite stage. The latter is mainly composed of sphalerite, pyrite, marcasite and a small amount of galena, which can be divided into galena stage, pyrite stage, sphalerite stage, pyrite and marcasite stage. Cu and Zn in pyrite may exist in the form of microinclusions, while Ag and Pb may exist in pyrite in the form of fine galena inclusions containing Ag. Fe and Cu may enter sphalerite in the form of ion replacement. Zn may enter chalcopyrite in the form of ion replacement, and As and Pb may be inclusions in chalcopyrite as As-bearing galena inclusions. Consistent with the previous understanding, the metal elements in the hydrothermal liquid system in Jade hydrothermal field mostly migrate with the hydrothermal fluid as sulfur complexes, and when the hydrothermal fluid mixes with seawater, the physical and chemical conditions of the fluid change, resulting in sulfide mineral precipitation. However, the chemical structure of chalcopyrite is still controversial, which restricts the understanding of the substitution mechanism of trace elements during chalcopyrite precipitation.

Abstract: This study aims to analyze the physico-mechanical properties and dynamic models of tissue-simulating hydrogels, specifically the photoacoustic (PA) response signals, by varying the concentrations of polyvinyl alcohol (PVA) and molecular weight (MW). A state space model (SSM) is proposed to study the PVA hydrogels to retrieve the PA-related signal's damping ratio and nat-ural frequency. Nine box-shaped PVA hydrogels containing saline solution were used, with five concentrations of PVA (7, 9, 12, 15, 20%) for MW1 and four for MW2. The results indicated that the concentration of PVA and MW played an important role in the PA wave's amplitude, arrival time, and speed of sound over the hydrogels. The SSM parameters showed that increasing PVA and MW concentrations improved the hydrogels' ability to absorb and transfer energy under the PA effect. These parameters were also found to be correlated with density and modulus of elasticity. Addi-tionally, the concentrations of PVA and MW affected the absorption and optical scattering coeffi-cients. The physical-mechanical properties, including porosity, density, and modulus of elasticity, improved as the concentration of PVA and MW increased. The ultimate goal of this study is to develop hydrogels as phantoms that can be used for tissue simulation and imaging.

Human rhabdomyosarcomas are rarely cured by surgical resection alone. This is also true for high grade soft tissue sarcomas in dogs. Dogs with spontaneous sarcoma are good models for clinical responses to new cancer therapies. Strategic combinations of immunotherapy and oncolytic virotherapy (OV) could improve treatment responses in canine and human cancer patients. To develop an appropriate combination of immunotherapy and OV for dogs with soft tissue sarcoma (STS), canine cancer cells were inoculated with myxoma viruses (MYXVs) and gene transcripts were quantified. Next, cytokine concentrations in canine cancer cells were altered to evaluate their effect on MYXV replication. These studies indicated that, as in murine and human cells, type I interferons (IFN) play an important role in limiting MYXV replication in canine cancer cells. To reduce type I IFN production during OV, oclacitinib (a JAK1 inhibitor) was administered twice daily to dogs for 14 days starting ~7 days prior to surgery. STS tumors were excised and MYXV deleted for serp2 (MYXV∆SERP2) was administered at the surgical site at two time points post-operatively to treat any remaining microscopic tumor cells. Tumor regrowth in dogs treated with OV was decreased relative to historical controls. However, regrowth was not further inhibited in patients given combination therapy.

Plant phenotype plays an important role in crop breeding and planting. Leaf phenotype is an important part of plant phenotype. In order to analyze the leaf phenotype, the target leaf is required to be segmented from the complex background image. In this paper, an automatic soybean leaf segmentation method based on object detection and interactive segmentation models is proposed. Firstly, the Libra R-CNN object detection algorithm is used to detect all soybean leaves in the image. Then, based on the idea that the target soybean leaf is located in the center of the image and the area is large, the detection bounding box of the target leaf is selected. In order not to destroy the segmentation result, the bounding box is optimized to completely enclose the whole leaf. Finally, according to the optimized bounding box, the prior channels of foreground and background are constructed using Gaussian model. The two channels together with the original image are as the input of the interactive object segmentation with inside-outside guidance model to segment the target soybean leaf. A large number of qualitative and quantitative experimental results show that the method has high segmentation accuracy and strong generalization capacity.

Triatoma infestans (Klug) is an insect recognized as not only an important vector of South-American trypanosomiasis (Chagas disease) but also a model of specific cellular morphofunctional organization and epigenetic characteristics. The purpose of the present review is to highlight certain cellular processes that are particularly unveiled in T. infestans, such as 1) somatic polyploidy involving nuclear and cell fusions that generate giant nuclei; 2) diversification of nuclear phenotypes in the Malpighian tubules during insect development; 3) heterochromatin compartmentalization into large bodies with specific spatial distribution and presumed mobility in the cell nuclei; 4) chromatin remodeling and co-occurrence of necrosis and apoptosis in the Malpighian tubules under stress conditions; 5) epigenetic markers; 6) unexplained response of heterochromatin to valproic acid, an epidrug that inhibits histone deacetylases and induces DNA demethylation in other cell systems. These cellular processes and epigenetic characteristics emphasize the role of T. infestans as an attractive model for cellular research.

Self-compacting concrete (SCC) production is a complex operation that requires finding a good combination and a suitable dosage of each of its constituents. Several formulation methods have been developed to meet the workability requirements of SCC. In this paper, the relationships between the fresh properties of SCC based on local metakaolin (MK) and the spreading of its mortar was investigated. The results showed the existence of good correlations between the spreading of the mortar and the fresh state properties of the related SCC and that the MK substitution rate did not affect these correlations. The choice of the mortar flow rate should target appropriate fresh properties of the SCC and a viscosity enhancing agent (VEA) could be used if the mix is too fluid and present an instability.

The endosomal sorting complex required for transport (ESCRT) is an essential molecular machinery in eukaryotic cells that facilitates the invagination of endosomal membranes, leading to the formation of multivesicular bodies (MVBs). It participates in various cellular processes, including lipid bilayer remodeling, cytoplasmic separation, autophagy, membrane fission and remodeling, plasma membrane repair, as well as the invasion, budding, and release of certain enveloped viruses. The ESCRT complex consists of five complexes, ESCRT-0 to ESCRT-III and VPS4, along with several accessory proteins. ESCRT-0 to ESCRT-II form soluble complexes that shuttle between the cytoplasm and membranes, mainly responsible for recruiting and transporting membrane proteins and viral particles, as well as recruiting ESCRT-III for membrane neck scission. ESCRT-III, a soluble monomer, directly participates in vesicle scission and release, while VPS4 hydrolyzes ATP to provide energy for ESCRT-III complex disassembly, enabling recycling. Studies have confirmed the hijacking of ESCRT complexes by enveloped viruses to facilitate their entry, replication, and budding. Recent research has focused on the interaction between various components of the ESCRT complex and different viruses. In this review, we discuss how different viruses hijack specific ESCRT regulatory proteins to impact the viral life cycle, aiming to explore commonalities in the interaction between viruses and the ESCRT system.

Paper is a material whose mechanical properties are highly dependent on humidity and temperature. Which naturally also builds the relationship between the stiffness and strength of corrugated board and changing weather conditions. In this paper, attention is focused on the dependence of the physical properties of the cardboard on changes in humidity and temperature, which undergo dynamic fluctuations both during the production of corrugated board and during its storage. Two techniques were used to test this effect, namely numerical homogenization and global sensitivity analysis. Both methods were implemented to determine the theoretical relationships between the change in humidity and/or temperature in each layer of corrugated board and its global bending, compression and shear stiffness. The procedure was used to analyze different types of 5-ply and 3-ply cardboard. The obtained results allowed to build a complete map of the relationship between the change in humidity of selected layers and the strength characteristics of the full assembly.

Mycobacterium avium ssp paratuberculosis (MAP) is the causative agent of Johne’s disease (JD) in animals and a suspected cause of Crohn’s disease (CD) in humans. Crohn’s Disease is a progressive, detrimental granulomatous enteritis of which common therapies are targeted to suppressing certain components of the immune system. The efficacy of these treatments can be variable and temporary with no clear process of selection for the individual patient. However, diagnosis of MAP has been elusive in patients with Crohn’s Disease. In animals it can be detected by several different techniques, including bacterial cell culture, polymerase chain reaction (PCR), and immunological targets. To move to an understanding of the possible pathogenicity of MAP and the sup-posed cause of CD in humans, it is necessary to demonstrate the presence of cell wall deficient mycobacterial (CWDM) forms of MAP in blood and tissue cultures from patients with CD. From this, more tailored and accurate therapies can be implemented and be developed to eradicate this infectious organism from humans. Current anti-mycobacterial antibiotics have limited efficacy as MAP is subtly different from tuberculosis. Newer methods, such as vaccination and gut microbiome remediation will be essential as part of combination therapies.

Antibiotics are released into the environment either directly in an unchanged form or in a partially metabolized form. The discharge is usually through untreated waste or industrial treatment effluents. The potential concern is the uptake of these antibiotics by crops irrigated by treated wastewater. This study collected wastewater from eight points at the Pagla, Kadamtali, Dhaka treatment plant. Here we consider three crucial antibiotics, Doxycycline, Ciprofloxacin, and Tetracycline, used mainly during the last two years of the pandemic. A PDA detector was used in high-performance liquid chromatography (HPLC) analysis to determine the raw and processed effluent antibiotics. The most frequently seen antibiotics in natural wastewater were Doxycycline and Ciprofloxacin, with the highest concentration of 0.23µgL-1and 0.20 µgL-1(raw water), respectively. Tetracycline was not detected in natural water. Contrarily, Doxycycline was discovered in the Pagla plant's completed water and had the highest concentration (0.12 gL-1), whereas Ciprofloxacin and Tetracycline were not found in the dead water. The findings of this study showed that Doxycycline was still present in both the raw and processed effluent. Both natural and finished wastewater was subjected to a microbial-resistant test in the presence of all three antibiotics. The results revealed that the samples detected both heterotrophic bacteria and total coliform. The viable aerobic heterotrophic bacteria ranged between 5.421 and 4.754 log cfu/ml. Total bacteria load gradually decreased in the finished wastewater.

The Onion Route Network (also called TOR) is by far the most efficient and widely used anonymity platform with millions of users daily and an expanding size and capacities. Since its public deployment in 2002, the Onion Routing network (also known as TOR) has maintained its leading position and dozens of propositions aiming to improve its performance and enhance the security (anonymity and privacy) have been made. Given the significance of this research area, this work seek to contribute into the improvement of TOR by investigating and testing revolutionary cryptographic and routing mechanism. This work is justified by the current TOR vulnerability and observed weaknesses, and set the challenging aim of covering these security flaws by proposing the relevant security and performances improvement such as the authenticated-encryption for onion construction, the lightened onion encapsulation approach and the secured circuit selection and cell routing mechanisms. The obtained results from implementing the proposed improvements and testing them into a TOR-like simulation platform permit to validate not only, the performances and security contributions brought by the improvement, but also the suitability of their potential implementation into the real TOR network.

Laurencia seaweed species synthesize a broad range of secondary metabolites mainly terpenes, such as the elatol exhibiting ecological roles, such as defense against fouling and herbivores. Recently, an intricate cellular machinery was evidenced concerning terpenes biosynthetic pathways, storage inside corps en cerise - CC and regulated exocytosis in these species. But for seaweeds in general, the proteins involved in transmembrane transport of secondary metabolites remains unknown. Assays with Rhodamine-123 and cyclosporine A (CSA) revealed the presence of ABC transporters in CC membrane of Laurencia dendroidea. In vivo incubation assays with CSA resulted in CC morphological changes, reduced intracellular elatol concentrations and increased biofouling cover on the seaweed surface. Cultivation assays in the presence of a marine pathogenic bacteria induced the expression of ABC proteins belonging to the subfamilies ABCB, ABCD, ABCF and ABCG. The later subfamily is known to associated in the transport terpenes in plants. Our results shed new light on the role of ABC proteins in key mechanisms of the defensive system in seaweeds against fouling and herbivory.

This study addresses the problem of accurately predicting azimuth and elevation angles of signals impinging on an antenna array employing Machine Learning (ML). Using the information obtained at a receiving system when a transmitter’s signal hits it, a Decision Tree (DT) model is trained to estimate azimuth and elevation angles simultaneously. Simulation results demonstrate the robustness of the proposed DT-based method, showcasing its ability to predict the Direction of Arrival (DOA) in diverse conditions beyond the ones present in the training dataset, i.e., the results display the model’s generalization capability. Additionally, the comparative analysis reveals that DT-based DOA estimation outperforms the state-of-the-art MUltiple SIgnal Classification (MUSIC) algorithm, establishing DTs as competitive alternatives for DOA estimation in signal reception systems.

Hybrid organic–inorganic perovskites (HOIPs) are promising materials in several fields related to electronics, offering long carrier-diffusion lengths, high absorption coefficients, tunable band gaps, and long spin lifetimes. Recently, chiral perovskites have attracted a huge interest thanks to the possibility of further widening the applications of HOIPs. Chiral materials, being intrinsically non-centrosymmetric, display several attractive physico-chemical properties, including circular dichroism, circularly polarized photoluminescence, nonlinear optics, ferroelectricity, and spin-related effects. Recent studies have shown that chirality can be transferred from the chiral organic ligands into the inorganic perovskite framework, resulting in materials combining the advantages of both chirality and perovskite superior optoelectronic characteristics. Thus, chiral HOIPs have emerged as promising materials for chiroptoelectronic, spintronic, and ferroelectric applications. Here, we report a summary of the latest advances in the field of chiral HOIPs, with a specific focus on lead-free materials and on the first attempts to understand the correlation between the crystal structure features and the chirality-induced functional properties

Some p53 mutants lose their tumor suppressor activity and acquire new oncogenic functions, known as a gain of function. Recent studies have shown that p53 mutants can exert oncogenic effects through specific miRNAs. We identified the differentially expressed miRNA profiles of the three most frequent p53 mutants (p53R273C, p53R248Q, and p53R175H) in the Saos-2 cell line (null p53) transfected as compared with p53WT transfected cells. The association between these miRNAs and the signaling pathways in which they might participate was performed through the miRPath Software. QRT-PCR was employed to validate the miRNAs profiles. In addition, we explored if the induction of cell migration and invasion by the p53R48Q mutant was dependent on the miR-182-5p. We observed that p53 mutants have an overall negative effect on miRNA expression. Likewise, we found miRNAs differentially expressed associated with regulating Oncogenic signaling pathways. We found overexpression of miR-182-5p, which is associated with processes such as cell migration and invasion. Inhibition of mutant p53R248Q and miR-182-5p increased FOXF2-MTSS1 levels and decreased cell migration and invasion. Our results suggest that p53 mutants increase the expression of miR-182-5p, and this miRNA is also necessary to induce cell migration and invasion by the p53R248Q mutant in a cancer cell model.

The present paper provides a new definition for dual spline curves in a geometric intuitive way based on adaptive curve refinement techniques. The dual spline is an implementation of the interpolatory subdivision scheme for curve modeling, which is comprised of polynomial segments of different degrees. Specially, the dual spline curves are mainly aims to solve the difficult geometry defeaturing problems in the existing computer-aided technology. Dual spline curves maintain various desirable properties of conventional curve modeling methods, such as local adaptive subdivision, high interpolation accuracy and convergence, continuous and discontinuous boundary approximation. By adding fictitious and intrinsic nodes inside or at the vertices of interpolation elements, the dual spline is flexible and convenient for approximating a set of ordered points or discrete segments. Combined with the Lagrange interpolation polynomial and meshless method, the proposed approach is capable of approximating the non-smooth boundary for geometry defeaturing. Experimental results are given to verify the validity, robustness, and accuracy of the proposed method.

Background: Frail elderly patients are exposed to suffering the consequences of heart diseases that are not managed timely such as receiving anticoagulation to prevent stroke associated to atrial fibrillation (AF). Referral to the cardiological outpatient department can be cumbersome as it often requires repeated visits. The aim of this project was to use AF as a showcase to develop and implement CardioShare, a shared-care model where primary care leads patient management, using an easy-to-use compact Holter monitor device with asynchronous remote support from cardiologists. Methods: This complex intervention has been developed during a feasibility phase, tested in a pragmatic cluster-randomization trial (primary care clinic as clusters) and its implementation potential evaluated with an escalation test. Mixed methods were used to evaluate the impact of the intervention, comprising quantitative observations, semi-structured interviews, and workshops. Results: Between February 2020 and December 2021, 314 patients (30% frail) were included of whom 75% had AF diagnosed/not found within 13 days. More than 80% in both groups avoided referral to cardiologists. Patients felt safe and primary care clinicians satisfied. In the escalation test, 58 primary-care doctors used CardioShare to manage 93 patients over three months with remote support from four hospitals in the Capital Region of Denmark. Conclusions: CardioShare was successfully implemented for AF evaluation in primary care.

We generalize the concept of a fuzzy metric by introducing its approximating counterpart in order to make it more appropriate for the study of some problems related to words combinatorics. We establish close relations between fuzzy approximating metrics in case of special $t$-norms and approximating parametrized metrics, discuss some relations between fuzzy approximating metrics and fuzzy partial metrics as well as show some possible applications of approximating parametrized metrics in the problems of words combinatorics.

Chatbots are computer programs that use artificial intelligence to imitate human conversations. Recent advancements in deep learning have shown interest in utilizing language transformers, which do not rely on predefined rules and responses like traditional chatbots. This study provides a comprehensive review of previous research on chatbots that employ deep learning and transfer learning models. Specifically, it examines the current trends in using language transformers with transfer learning techniques to evaluate the ability of Arabic chatbots to understand conversation context and demonstrate natural behavior. The proposed methods explore the use of AraBERT, CAMeLBERT, AraElectra-SQuAD, and AraElectra (Generator/Discriminator) transformers, with different variants of these transformers and semantic embedding models. Two datasets were used for evaluation: one with 398 questions and corresponding documents, and another with 1395 questions and 365,568 documents sourced from Arabic Wikipedia. Extensive experimental works were conducted, evaluating both manually crafted questions and the entire set of questions, using confidence and similarity metrics. The experimental results showed that the AraElectra-SQuAD model achieved an average confidence score of 0.6422 and an average similarity score of 0.9773 on the first dataset, and an average confidence score of 0.6658 and similarity score of 0.9660 on the second dataset. The study concludes that the AraElectra-SQuAD model consistently outperformed other models, displaying remarkable performance, high confidence, and similarity scores, as well as robustness, highlighting its potential for practical applications in natural language processing tasks for Arabic chatbots. The study suggests that the AraElectra-SQuAD model can be further enhanced and applied in various tasks such as chatbots, virtual assistants, and information retrieval systems for Arabic-speaking users. By combining the power of transformer architecture with fine-tuning on SQuAD-like large data, this trend demonstrates its ability to provide accurate and contextually relevant answers to questions in Arabic.

The study examined eating timing, diet, and the ratio of sleep phases in people with social jetlag (SJL). The study involved 83 participants who filled out a questionnaire, and 21 of them took part in the study of sleep phases by electroencephalography during the week. SJL was associated with a higher incidence rate of eating jetlag, eating phase delays, an increase in calorie intake after 9 p.m., a decrease in dietary fiber intake for breakfast, and melatonin-containing product consumption for dinner. Young people with SJL had a reduction in total sleep and light sleep phase duration by 60 and 36 min on work/school days and an increase in total sleep and REM sleep phase duration by 66 and 60 min on weekends, respectively. Young people consuming foods with more than 4234.5 ng of melatonin for dinner, compared with their peers consuming less than 313.2 ng of melatonin, showed a decrease in SJL and sleep debt by 54 and 90 min and an increase in the total sleep and the deep sleep phase duration by 66 and 30 min, respectively. Thus, the consumption of melatonin-containing foods for dinner is associated with a decrease in circadian misalignment and a sleep quality improvement.

In the last decades, cultivation of chia (Salvia hispanica L.) has expanded around the world and the seeds have become well known due to their rich composition in nutrients and bioactive compounds. The aim of this work was to evaluate the physical, chemical and nutritional profile of eight chia seeds grown in different Latin-American countries (Argentina, Bolivia, Chile, Ecuador, Mexico, Paraguay and Peru). The results showed that several nutritional parameters such as the protein content and amino acid profile, dietary fiber content, lipid content, mineral composition and phytate present in the seeds depend on the location they were grown in. Other parameters such as ash content, fatty acid profile or physical parameters were uniform across locations (except for color parameters). The results support the notion that nutritional characteristics of seeds are determined by the seed's origin, further analysis is needed to define the exact mechanisms that control the changes in the seeds nutritional properties.

Tulou dwellings in Southeast China have captivated global interest due to their distinctive appearance, sustainable construction materials and technologies, and their defensive and collective housing functions. Despite several recognized as World Cultural Heritage sites, the vast majority of tulou buildings are undergoing irreversible decline and destruction, necessitating a comprehensive and systematic study. Taking 83 Tulou buildings in Raoping County, Chaozhou City, Guangdong Province as the research object, this study reconstructs the historical scenes and systematically reveals the emergence, popularity, and consolidation process of tulou dwellings as integrated defensive and residential buildings for ordinary people by conducting a comprehensive analysis of historical documents and local chronicles. Based on an extensive field investigation, the study systematically analyzes the geospatial distribution and the spatial characteristics of Raoping tulou and its residential unit. The results demonstrate the adaptability and flexibility of tulou dwellings, showcasing their developmental process and revealing the inclusive nature of these traditional residences, as well as the initiative of those who reside within them. The research findings contribute to a more dynamic, comprehensive, and authentic understanding of tulou and Chinese traditional residences, providing valuable references for the preservation and sustainable development of tulou architectural heritage.

Background:As cyber-physical systems (CPS) continue to grow, it is progressively crucial to address the challenges of data protection using artificial intelligence (AI). Objective:The goal of this research is to provide an up-to-date overview of the security and privacy issues of CPS that incorporate AI techniques. Method:To achieve this, the author conducted a systematic literature review, focusing on 35 relevant articles. Results:The data collected from these studies was then categorized into three main areas: 1) different security and privacy issues, 2) application areas and vulnerabilities, and 3) the AI techniques used to address security and privacy concerns. The literature review highlights that intrusion detection and cyberattacks are the most commonly studied areas in CPS, while Machine Learnning (ML)-based attacks and vessel trajectory are less explored. The review identifies various CPS applications such as water treatment, energy, healthcare, and transportation that address security and privacy concerns. However, a relatively small proportion of studies focused on the manufacturing domain. The review also notes that while supervised machine learning algorithms under the classification category are commonly used to address data protection issues, there are comparatively fewer studies that have implemented automation processes using robots and deep learning. Limitations:The articles related to blockchain-based research were not included in this review to focus solely on AI techniques. Conclusion:The results of this analysis indicate that there is a significant need for innovative AI/ML techniques to protect intelligent systems and networks from ML-based security threats.

Cardiac hypertrophy is an adaptive response to various pathological insults including hypertension. However, sustained hypertrophy can cause impaired calcium regulation, cardiac dysfunction, and remodeling, accompanied by cardiac fibrosis. Our previous study identified miR-25 as a regulator of SERCA2a, and that inhibition of miR-25 improved cardiac function and reduced fibrosis by restoring SERCA2a expression in a murine heart failure model. However, the precise mechanism underlying the reduction of fibrosis by miR-25 inhibition remains unclear. Therefore, we postulate that miR-25 may have additional targets that contribute to regulating cardiac fibrosis. Using in silico analysis, Krüppel-like factor 4 (KLF4) was identified as an additional target of miR-25. Further experiments confirmed that KLF4 was directly targeted by miR-25 and that its expression was reduced by long-term treatment with Angiotensin II, a major hypertrophic inducer. Subsequently, treatment with a miR-25 inhibitor alleviated the cardiac dysfunction, fibrosis, and inflammation induced by Angiotensin II. These findings indicate that inhibiting miR-25 not only enhances calcium cycling and cardiac function via SERCA2a restoration but also reduces fibrosis by restoring KLF4 expression. Therefore, targeting miR-25 may be a promising therapeutic strategy for treating hypertensive heart diseases.

Antimicrobial resistance (AMR) remains a challenge in Kenya, while the extent remains unknown. To assess the knowledge, cultural beliefs, practices, and behavioral patterns among multisectoral stakeholders in Kenya. The cross-sectional survey was conducted in August 2021 among farmers, animal health service providers and AMR researchers. Regional digital data collection tool developed by FAO was shared and responses obtained through mail, phone calls and direct interviews. Descriptive and inferential analysis were conducted. Antimicrobials were mostly sourced from agro-veterinary shops and from veterinary professionals. Farmers, often implement self-treatment and reported overuse, unnecessary use, and sometimes fail to complete the dosage in livestock. More farmers reported to have heard about antibiotics as compared to antimicrobials, mostly from friends and radio program, however only 9.2% could correctly differentiate the two. Animal Health Service Providers (AHSP) were the source of information to farmers regarding AMR. AHSPs mainly relied on suppliers and distributors for information about antibiotics. Both farmers and AHSPs treated viral infections with antibiotics. One Health Partners (OHPs) had higher knowledge and largely favorable attitudes towards AMR. Up to 72.7% of OHPs from training institutions had AMR included in training curriculum however, they were optimistic livestock farmers and government were less concerned about AMR. Gaps in knowledge and practice on Antimicrobial Stewardship (AMS) were observed in all categories of stakeholders. Given the documented knowledge-practice gap, innovative solutions are needed for both AHSPs and farmers to promote good antimicrobial stewardship practices and to mitigate burdens of AMR. Outcomes of this research should deepen the understanding of critical information and trigger behavioral change in usage and stewardship of antimicrobials.

Our objective was to evaluate whether pregnancy is prolonged by use of a proteomics-based maternal serum screening test followed by treatment interventions. This is a secondary analysis of the PREVENT-PTB randomized trial comparing screening with the PreTRM test versus no screening. The primary trial analysis found no significant between-group difference in preterm birth rate. Rather than considering a dichotomous outcome (preterm vs term), we treated gestational age at birth as a continuous variable using survival analysis. We also evaluated between-group difference in NICU length of stay and duration of respiratory support. Results indicated that pregnancy was significantly prolonged in subjects screened with PreTRM test compared to controls (adjusted hazard ratio 0.53, 95% confidence interval 0.36-0.78, P <0.01). Newborns of screened subjects had significantly shorter NICU stay but no significant decrease in duration of respiratory support. In the PreTRM screen-positive group, interventions that were associated with pregnancy prolongation included care management and low-dose aspirin but not 17-hydroxyprogesterone caproate. We concluded that screening with the PreTRM test followed by interventions for screen-positive pregnancies can prolong pregnancy and reduce NICU-LOS.

The prediction of system degradation is very important as it serves as an important basis for the formulation of condition-based maintenance strategies. An effective health indicator (HI) plays a key role in the prediction of system degradation as it enables vital information for critical tasks ranging from fault diagnosis to remaining useful life prediction. To address this issue, a method for monitoring data fusion and health indicator construction based on autoencoder (AE) and long short-term memory (LSTM) network is proposed to improve the predictability and effectiveness of health indicator in this study. Firstly, an unsupervised method and overall framework for HI construction is built based on deep autoencoder and LSTM neural network. The neural network is trained fully based on the normal operating monitoring data and then the construction error of the AE model is adopted as the health indicator of the system. Secondly, we propose related machine learning techniques for monitoring data processing to overcome the issue of data fusion, like mutual information for sensor selection and t-distributed stochastic neighbor embedding (T-SNE) for operating condition identification, etc. Thirdly, in order to verify the performance of the proposed method, experiments are conducted based on CMAPSS dataset and results are compared with algorithms of principal component analysis (PCA) and vanilla autoencoder model. Result shows that LSTM-AE model outperforms the PCA and Vanilla-AE model in metrics of monotonicity, trendability, prognosability and fitness. Fourthly, in order to analyze the impact of the time step of the LSMT-AE model on HI construction, we construct and analyze the system HI curve under different time steps of 5, 10, 15, 20, and 25 cycles. Finally, the results demonstrate that the proposed method for HI construction can effectively characterize the health state of system, which is helpful for further failure prognostics and converting the scheduled maintenance into condition-based maintenance.

Metabolic-associated fatty liver disease (MAFLD) and its potential impact on the severity of COVID-19 have gained significant attention during the pandemic. This review aimed to explore the genetic determinants associated with MAFLD, previously recognized as non-alcoholic fatty liver disease (NAFLD), and their potential influence on COVID-19 outcomes. Various genetic polymorphisms, including PNPLA3 (rs738409), GCKR (rs780094), TM6SF2 (rs58542926), and LYPLAL1 (rs12137855), have been investigated in relation to MAFLD susceptibility and progression. Genome-wide association studies and meta-analyses have revealed associations between these genetic variants and MAFLD risk, as well as their effects on lipid metabolism, glucose regulation, and liver function. Furthermore, emerging evidence suggests a possible connection between these MAFLD-associated polymorphisms and the severity of COVID-19. Studies exploring the association between indicated genetic variants and COVID-19 outcomes have shown conflicting results. Some studies observed a potential protective effect of certain variants against severe COVID-19, while others reported no significant associations. This review highlights the importance of understanding the genetic determinants of MAFLD and its potential implications for COVID-19 outcomes. Further research is needed to elucidate the precise mechanisms linking these genetic variants to disease severity and to develop gene profiling tools for early prediction of COVID-19 outcomes. If confirmed as determinants of disease severity, these genetic polymorphisms could aid in identifying high-risk individuals and improving the management of COVID-19.

This critical review illuminates the transformative potential of Artificial Intelligence (AI) and sensor technologies in the dairy livestock export industry, an area facing mounting pressure for heightened efficiency and sustainability. We rigorously scrutinize the uptake of these novel technologies in identifying 'shy feeders,' automating weight monitoring of individual livestock, and refining cattle enumeration procedures. The investigation unravels their capacity to bolster animal welfare standards, minimize supply chain discrepancies, and amplify operational productivity. Moreover, the research delves into how these innovations may enhance market access and competitiveness in a swiftly shifting global dairy landscape. We further highlight the challenges encountered and future trajectories, providing a strategic framework for technology integration within the livestock export sector. Ultimately, this review underlines the importance of adopting AI and sensor technologies, indicating a shift towards precision digital livestock farming that amalgamates efficiency, animal welfare, and profitability.

Pure monocular 3D reconstruction is an ill-posed problem that has attracted the research community's interest due to the affordability and availability of RGB sensors. SLAM, VO, and SFM are disciplines formulated to solve the 3D reconstruction problem and estimate the camera’s ego-motion, so many methods have been proposed. However, most of these methods were not evaluated in large datasets, under various motion patterns, had not been tested under the same metrics, and most of them had not been evaluated following a taxonomy, making their comparison and selection difficult. In this research, we performed a comparison of ten publicly available SLAM and VO methods following a taxonomy, including one method for each category of the primary taxonomy, three machine learning-based methods, and two updates of the best methods, to identify the advantages and limitations of each category of the taxonomy and test if the addition of machine learning or the updates made on those methods improved them significantly. Thus, we evaluated each algorithm under the TUM-Mono benchmark and performed an inferential statistical analysis to identify significative differences through its metrics. Results determined that sparse-direct methods significantly outperformed the rest of the taxonomy, and fusing them with machine learning techniques significantly improves the performance of geometric-based methods from different perspectives.

Plant roots host various microorganisms around and inside their roots, known as the root microbiome. To become healthy and productive, plants should keep under surveillance niches around the roots to recognize disease-causing microbes and similarly exploit the services of beneficial microorganisms in nutrient acquisition, stress mitigation and growth promotion. Here we presented the communication strategies between plant roots and root-associated microbes in improving plant growth and yield. Understanding how plant root and root-associated microbes communicate is vital in designing ecofriendly strategies for targeted disease suppression and improved plant growth that will help in sustainable agriculture.

The COVID-19 pandemic has led to the growth of hybrid and online learning environments and the trend to introduce more technology into the classroom. One such change would be the use of smart synchronous hybrid learning environments (SSHLE), which are settings with both in-person and online students concurrently, and in which technology plays a key role in sensing, analyzing, and reacting throughout the teaching and learning process. These changing environments and the incorporation of new technologies can place a greater orchestration load on participants and a reduction in teacher agency. In this context, the aim of this paper is to analyse the orchestration load and teacher agency in different SSHLEs. The NASA-TLX model was used to measure the orchestration load in several scenarios. Questionnaires and interviews were used to measure teacher agency. The results obtained indicate that the orchestration load of the teacher tends to be high (between 60 and 70 points out of 100 of the NASA-TLX workload), especially when they lack experience in synchronous hybrid learning environments, and the orchestration load of the students tends to have average values (between 50 and 60) in the SSHLEs analysed. Meanwhile, the teacher agency does not appear to be altered but shows potential for improvement.

Background and Objectives: Intramedullary spinal cord tumors (IMSCT) are rare entities. Especially, a location in the upper cervical spine as a highly eloquent region carries the risk of postoperative neurological deficits, such as tetraparesis or respiratory dysfunction. Evidence for respiratory dysfunction is scarce. The aim of this study was to describe the early and late postoperative clinical course of this highly eloquent tumours. Patients and Methods: This is a single-centre retrospective cohort study. We included 35 patients with IMSCT at levels of craniocervical junction to C4 who underwent surgical treatment between January 2008 and December 2022. The authors analysed the patients' preoperative status, tumour- and surgery-specific characteristics, and follow-up functional status. Results: The study cohort included 22 patients with grade II ependymoma (62.9%), 2 low-grade astrocytomas (5.7%), 2 glioblastomas (5.7%), 6 hemangioblastomas (17.1%), 2 metastases (5.7%), and 1 patient with partially intramedullary schwannoma (2.9%). Gross total resection was achieved in 76% of patients. Early dorsal column related symptoms and motor deterioration occurred in 64% and 44% of patients, respectively. At a follow-up of 3.27 ± 3.83 years, 43% and 33% of patients preserved postoperative sensory and motor deterioration, respectively. The median McCormick Scale grade was 2 in the preoperative and late postoperative periods, respectively (p=0.0897, α=0.05). Only two out of 35 patients (5.7%) developed new intermittent respiratory dysfunction, of whom two were transient. There were no surgery-related deaths. Conclusions: The surgery of IMSCT of the upper cervical spine could be performed without major procedure-related risk. Roughly a half of the patients develop new neurological deficit in the immediate postoperative period. However, most of the patients still maintain functional independence. The rate of respiratory insufficiency is low and is strongly influenced by the rapid neurological deterioration in high-grade tumours.

Detection of partial discharge (PD) activities in high-voltage equipment can be done according to the several mechanisms of signal detection, which are electromagnetic wave signal detection, acoustic signal detection, chemical reactions, electrical signal detection, or optical emission detection. Recently, multiple methods of detection and localization of partial discharge activities occurred in power transformers and gas-insulated switchgear (GIS) have been proposed to monitor the health condition of high-voltage equipment, especially when the awareness regarding preventive maintenance has been emphasized at the industrial level and electrical providers. In aligning the needs of industrial and the improvement of PD detection methods, this manuscript focused on reviewing the current practice methods for the detection and localization of PD signals in high-voltage equipment and comparing their efficacy, in summarizing the future direction of research work-related methods of PD detection. The comparative reviews are discussed in terms of the mechanism of PD signal detection, indication parameters, calibration technique, advantages, and limitations of each method of PD measurement in detail.

Iapetus, a Saturn moon, shows the most differentiated albedo dichotomy of the Solar System. The dark leading side has a lower albedo than the bright trailing side. Spectral data on the visible light reveal the existence of two types of materials on the surface. The darkening in the leading side is thought to be originated by the presence of organic material and carbonaceous compounds on surface, while the trailing side is covered by water ice due to migration processes from the dark side. On airless bodies like Iapetus, the surface escape speed is greater than the speed of water molecules, resulting in the retention of a H2O atmosphere that allows some species to get diffused through it. Here, there were performed simulations of the evolution of the surface temperature for each of the two hemispheres of Iapetus. The results showed a slow yet steady increment of temperatures for both sides, with a steeper slope for the dark hemisphere. It was also simulated how much energy budget can be accumulated in both sides and its consequences. Finally, we calculated the diffusion coefficients for ammonia, methane, and water ice. The results let us infer how these compounds could evolve over time.

Vitamin E is a group of eight compounds divided into two subgroups: four tocopherols (α-, β-, γ-, and δ-) and four tocotrienols (α-, β-, γ-, and δ-). α-Tocopherol is considered the most biologically active form. This review paper summarizes the current knowledge and historical progression of vitamin E research, with particular emphasis on its role in animal nutrition. Early studies in the 1920s identified vitamin E’s role in preventing neonatal mortality in rats. Over the following decades, scientists discovered the compound’s chemical structure and its importance for the immune system, skin health, anti-inflammatory properties, hormonal balance, and other bodily functions. Production of vitamin E products has evolved, starting with isolating the vitamin from natural sources and advancing to synthesizing it with greater efficiency and standardized potency units. Early animal studies focused on reproductive health and growth disorders, but further research demonstrated the importance of vitamin E in preventing encephalomalacia in domestic fowl and muscular dystrophy in rabbits and other animals. Today, vitamin E is commonly used as a feed additive to meet animals’ requirements and assure immune function and overall health. Despite much knowledge on vitamin E’s role in animal nutrition, many questions remain unanswered, and current research aims to determine optimal supplementation levels, interactions with other nutrients, impacts on gene expression, cell signaling and communication, and effects of supranutritional dosages in livestock. Vitamin E has a long and fascinating history in scientific research, with significant advancements in understanding its chemical structure and biological activity. In animal nutrition, vitamin E continues to play an important role in improving animal health, and ongoing research will continue to expand our understanding of its benefits and mechanisms of action.

The nature of the fracture and fragmentation process of concrete medium under blast loading is the transformation process of the medium from continuum to discontinuity, coupled with the significant rate correlation of concrete medium, its mechanical behavior presents a high degree of complexity. Problems such as grid distortion and even negative volume are often encountered in the finite element method and others when solving this problem, while the material point method can effectively avoid these problems. In addition, the widely used HJC concrete constitutive model does not take into account the segmented characteristics of the calculation function for dynamic increasing factor. Therefore, in this paper, firstly, the calculation function for dynamic increasing factor in the HJC concrete model is modified by SHPB experiment, and the improved HJC concrete model is proposed; secondly, the material point method simulation program is developed, and the improved HJC concrete model is embedded into the simulation program; finally, the simulation program is verified by numerical examples, and the results show that the developed simulation program can better simulate the fracture and fragmentation process of concrete medium under blast loading, especially the pulverization characteristics of the medium in the near zone of the load.

Hospital readmission and length of stay prediction provide info to manage hospitals’ bed capacity and the number of required staff, especially during pandemics. We present a hybrid deep model called Genetic Algorithm-Optimized Convolutional Neural Network (GAOCNN) with a unique preprocessing method to predict hospital readmission and the length of stay in patients having various conditions. GAOCNN uses one-dimensional convolutional layers to predict hospital readmission and length of stay. The parameters of the layers are optimized using a genetic algorithm. To show the performance of the proposed model in patients with various conditions, we evaluate the model under three healthcare datasets; the Diabetes 130-US hospitals dataset, the COVID-19 dataset, and the MIMIC-III dataset. The diabetes 130-US hospitals dataset has information on both readmission and the length of stay, while COVID-19 and MIMIC-III datasets just include information on the length of stay. Experimental results show that the proposed model’s accuracy for hospital readmission is 97.2% for diabetic patients. Also, the accuracy of the length of stay prediction is 89%, 99.4%, and 94.1% for diabetic, COVID-19, and ICU patients, respectively. These results confirm the superiority of the proposed model compared to existing methods. Our findings offer a platform for managing healthcare funds and resources for patients with various diseases.

Cadmium (Cd) contamination in rice grains is posing a significant threat to global food security. To restrict the transport of Cd in the soil-rice system, an efficient way is to use the ionomics strate-gy. Since calcium (Ca) and Cd have similar ionic radii, their uptake and translocation may be linked in multiple aspects in rice. However, the underlying antagonistic mechanisms are still not fully understood. Therefore, we first summarized the current knowledge on the physiological and molecular footprints of Cd translocation in plants and then explored the potential antagonistic points between Ca and Cd in rice, including exchange adsorption on roots, plant cell wall compo-sition, co-transporter gene expression, and transpiration inhibition. This review provides sugges-tions for the Ca/Cd interacting study in rice and introduces the ionomics research to better control the accumulation of Cd in plants.

The accommodative response of the human eye is predominantly driven by foveal vision but reacts also to off-foveal stimuli. Here, we report on monocular accommodation measurements using parafoveal and perifoveal annular stimuli centered around the fovea and extending up to 8 degree radial eccentricity for young emmetropic and myopic subjects. The stimuli were presented through a sequence of random defocus step changes induced by a pupil-conjugated tunable lens. A Hartmann-Shack wavefront sensor with an infrared beacon was used to measure real-time changes of ocular aberrations up to and including the 4th radial order across a 3 mm pupil at 20 Hz. Our findings show a significant reduction in accommodative response with increased radial eccentricity.

Domestic cats (Felis catus) are widespread worldwide as the most popular pets. This medium-sized carnivore have well-known negative effects on biodiversity, but there is still need to better understand the proximate causes of its predation. Based on a citizen science project, we assessed the role of spatiotemporal (i.e., latitude, longitude and seasons), climatic (i.e., rainfall), anthropogenic (i.e., human footprint, HFI) and individual (i.e., sex and age) variables on the number of preys returned home by cats in metropolitan France. Over the 5 048 cats monitored between 2015 and 2022, prey from 12 different classes (n= 36 568) were returned, being 68% mammals, 21% birds and 8% squamates. Shrews brought home by cats peaked during summer, while rodents were recorded during summer-autumn. Birds brought home by cats peaked in spring-summer and in autumn, and lizards in spring and in late summer. Lower HFI was associated with more voles and mice brought home and the opposite trend was observed for lizards and birds. Younger cats were more prone to bring home shrews, birds and reptiles. Although environmental factors play a minor role in prey brought home by cats, some geographical characteristics of prey species distribution partly explains the hunting behaviour of cats.

Gliomas are aggressive, primary central nervous system tumours arising from glial cells. Glioblastomas are the most malignant. They are known for their poor prognosis or median overall survival. Current standard of care is overwhelmed by the heterogeneous, immunosuppressive tumour microenvironment promoting immune evasion and tumour proliferation. The advent of immunotherapy with its various modalities – immune checkpoint inhibitors, cancer vaccines, oncolytic viruses, chimeric antigen receptor T cells and NK cells have shown promise. Clinical trials incorporating combination therapies of the above have overcome the microenvironment resistance and yielded survival and prognostic benefit. Rolling these new therapies out in the real-world scenario in a low cost, high throughput manner is the unmet need of the hour. These will bring practice changing implications to the glioma treatment landscape. In this review article, we focus on describing the hallmarks of the glioma microenvironment and its interplay with the different emerging modalities of immunotherapy.

Silicon-based photodetectors, as low-cost and environmentally friendly optical sensors, are attractive. Also, their compatibility with complementary metal-oxide-semiconductor (CMOS) technology is advantageous for the development of silicon photonics systems. However, extending optical responsivity of silicon-based photodetectors to the mid-infrared (mid-IR) wavelength range remains challenging. In developing mid-IR infrared Schottky detectors, nanoscale metals are critical. Nonetheless, one key factor is the Fermi level pinning effect at the metal/silicon interface and the presence of metal-induced gap states (MIGS). Here, we demonstrate the utilization of the passivated surface layer on semiconductor materials as an insulating material in metal-insulator-semiconductor (MIS) contacts to mitigate the Fermi level pinning effect. The removal of Fermi level pinning effectively reduces the Schottky barrier height by 12.5% to 16%. The demonstrated devices exhibit a high responsivity of up to 234 μA/W at a wavelength of 2 μm, 48.2 μA/W at 3 μm, and 1.75 μA/W at 6 μm. The corresponding detectivities at 2 and 3 μm are 1.17×10^8 cm Hz^1/2 W^-1 and 2.41×10^7 cm Hz^1/2 W^-1, respectively. The expanded sensing wavelength range contributes to the application development of future silicon photonics integration platforms.

(1) Background: Angiotensin II, a major culprit in cardiovascular disease, activates mediators that are also involved in pathological cardiac remodelling. We aimed at investigating the effects of two of them: aldosterone (Ald) and transforming growth factor-beta-1 (TGF-β1 ), on cardiac remodelling in an in vivo model. (2) Methods: Six-week-old male wild-type (WT) and TGF-β1 -overexpressing transgenic (TGF-β1 -TG) mice were infused with subhypertensive doses of Ald for 2 weeks, and/or treated orally with eplerenone from postnatal day 21. Heart’s ventricles were examined: by morphometry, immunoblotting to assess intracellular signalling pathways, RT qPCR to determine hypertrophy and fibrosis marker genes. (3) Results: TGF-β1 -TG mice spontaneously developed cardiac hypertrophy and interstitial fibrosis, exhibited higher baseline phosphorylation of p44/42 and p38 kinases, fibronectin and ANP mRNA expression. Ald induced a comparable increase in ventricular heart weight-to-body-weight ratio and cardiomyocyte diameter in both strains, but less pronounced increase in interstitial fibrosis in transgenic compared to WT mice (23.6% vs 80.9%, p<0.005). Ald increased phosphorylation of p44/42 and p38 in WT but not TGF-β1 -TG mice. While eplerenone-enriched chow partially prevented Ald-induced cardiac hypertrophy in both genotypes and interstitial fibrosis in WT controls, it completely protected from additional fibrosis in transgenic mice. (4) Conclusions: Ald appears to induce cardiac hypertrophy independently of TGF-β1 , while in case of fibrosis downstream signalling pathways of these two factors probably converge

Prostate cancer (PCa) is the most diagnosed non-cutaneous cancer in men. Despite therapies such as radical prostatectomy, which is considered curative, distant metastases may form resulting in biochemical recurrence (BCR). This study used radiomic features calculated from multi-parametric magnetic resonance imaging (MP-MRI) to evaluate their ability to predict BCR and PCa presence. Data from a total of 279 patients, of which 46 experienced BCR, undergoing MP-MRI prior to surgery were assessed for this study. After surgery, the prostate was sectioned using patient-specific 3D-printed slicing jigs modeled using the T2-weighted imaging (T2WI). Sectioned tissue was stained, digitized, and annotated by a GU-fellowship trained pathologist for cancer presence. Digitized slides and annotations were co-registered to the T2WI and radiomic features were calculated across the whole prostate and cancerous lesions. A tree regression model was fitted to assess the ability of radiomic features to predict BCR, and a tree classification model was fitted with the same radiomic features to classify regions of cancer. We found that 10 radiomic features predict eventual BCR with an AUC of 0.97 and classifying cancer at an accuracy of 89.9%. This study showcases the application for a radiomics-based tool to screen for the presence of prostate cancer and assess patient prognosis, as determined by biochemical recurrence.

The octopus keel is a trait that has been hypothesized to be connected with burrowing in octopuses, but has never been explored in any detail. This research aimed to test for anWe investigated the association between these two traits phylogenies using two approaches independent sets of methods. First, we examined phylogenetic correlation between presence of a keel and known burrowing behavior in incirrate octopuses.by using a phylogenetic approach, benthic octopuses as a group were examined for known burrowing and the presence of a keel to determine whether an evolutionary relationship exists between these traits. Second, burrowing and non-burrowing captive Muusoctopus leioderma were evaluated for keel prominence to determine whether the keel is lost more rapidly in non-burrowing individuals. Pagel’s test for the coevolution of binary characteristics showed the model of best fit for the resulting phylogenetic tree to be one of evolutionary interdependence, and that non-burrowing Muusoctopus leioderma lost their keels over time, while burrowing individuals maintained their keels. Together, these results indicate the keel may be a trait associated with burrowing in octopuses.

The leachate discharges generated in sanitary landfills contain many pollutants that are harmful to the environment; treatments are scarce and should be carried out better. The use of coagulation-flocculation processes has been one of the most widely used, but that; Due to the complexity of the characterization of the leachate, the dosing strategy of coagulants and biopolymers needs to be clarified. Therefore, the present study is carried out to determine the doses of coagulants and biopolymers suitable for coagulation-flocculation processes in the treatment of leachates by using computational models of machine learning techniques such as Artificial Neural Networks (ANN); these allow to decrease the operations of the tests of jars in the laboratory; optimizing resources. Through laboratory experimentation, there are real results of the effectiveness of applying biopolymers in leachate treatments at different concentration levels. The laboratory results were taken as input variables for the algorithms used; after the validation and calibration process, we proceeded to estimate predicted data with the computational model, obtaining predictions of optimal doses for treatment with high statistical adjustment indicators. It is verified that the applied coagulation-flocculation treatments reduce the turbidity values in the leachate and contaminants associated with suspended solids. In this way, the jar tests are optimized so that the operational costs decrease without affecting the results of adequate dosing.

Two reversible furan-maleimide resins, in which there are rigid -Ph-CH2-Ph- structure and flexible -(CH2)6- structures in bismaleimides, were synthesized from furfuryl glycidyl ethers (FGE), 4,4′-diaminodiphenyl ether (ODA), N,N'-4,4'-diphenylmethane-bismaleimide (DBMI) and N,N'-hexamethylene-bismaleimide (HBMI). The structures of the resins were confirmed by Fourier transform infrared analysis, and the thermoreversibility was evidenced by differential scanning calorimetry (DSC) analysis as well as sol-gel transformation process. Mechanical properties and recyclability of the resins were preliminarily evaluated by the flexural test. The results show the Diels-Alder (DA) reaction occurs at about 90°C and reversible DA reaction does at 130-140°C for the furan-maleimide resin. Thermally reversible furan-maleimide resins have high mechanical properties. The flexural strength of cured FGE-ODA-HBMI resin arrives at 141 MPa. The resins have a repair efficiency of over 75%. After being hot-pressed for three times, two resins display higher flexural strength than 80 MPa.

The increased emergence of multidrug-resistant Helicobacter pylori influences the prevention of stomach cancer. Zingiber officinale is a plant usually used in folk medicine to treat a variety of diseases involving infections, nausea, vomiting, peptic ulcer, dyspepsia, and inflammation. This study was conducted to evaluate the ability of Z. officinale extract to combat resistant H. pylori. The disc diffusion, microdilution, and microplate assays were performed to evaluate the susceptibility to antibiotics, and the antibacterial and antibiofilm activities of the Z. officinale extracts. Using the checkerboard method, the combined effects of the gentamicin and Z. officinale extract were investigated. In addition, anti-inflammatory activity and GC-MS analysis were determined by the modified protocol. According to the findings, H. pylori isolates exhibited resistance rates of 56.33, 50.0, and 45.85 for metronidazole, gentamicin, and tetracycline, respectively. The methanolic extract of Z. officinale had the strongest effectiveness against resistant H. pylori isolates with MIC of 20.0 to 50.0 µg/ml against both H. pylori isolates and the stranded strain NCTC 11637. Z. officinale extract suppress the biofilm formed by H. pylori isolates with a percentage of 92.96% at 50.0µg/ml, compared with 97.19% for gentamicin at the same concentration. According to FICI values, combination of methanolic Z. officinale extract to gentamicin increases bacterial sensitivity to such drugs. Moreover, the Z. officinale extract exhibits strong anti-inflammatory activity. The GC-MS analysis of Z. officinale extract exhibits 17 different chemical compounds. Conclusions: The Z. officinale extract contain the anti-inflammatory compound gingerol as the main constituent which inhibits the growth of H. pylori and its biofilm, are a promising natural therapeutic alternative or enhance antibiotics activity

(1) Background. Cognitive impairment in people with Multiple Sclerosis (MS) has been studied in relation to some clinical variables (e.g., motor disability and disease duration) and lifestyle fac-tors such as Cognitive Reserve (CR). However, only very few studies have considered the interac-tion of clinical variables and cognitive reserve in preserving the integrity of the neuropsychologi-cal profile. In this paper, we hypothesised that a higher level of CR might predict good cognitive efficiency by modulating the clinical outcome of the disease. (2) Methods. A sample of 100 partic-ipants with MS (age range 30-74), was recruited and assessed remotely with a questionnaire to measure CR and a cognitive screening test. Data were analysed through Generalized Additive Models. (3) Results. We found that the model analysing the interaction between CR and disease duration, and between CR and motor disability was able to explain a significant percentage of cognitive performance. In particular, higher levels of CR predicted better cognitive performance despite long disease duration, unless the motor disability was severe. (4) Conclusion. This study highlights the crucial role of CR in modulating cognitive efficiency in people with MS.

This paper presents a comprehensive analysis of the scholarly footprint of ChatGPT, an AI language model, using bibliometric and scientometric methods. The study aims to understand the evolution of research output, citation patterns, collaborative networks, application domains, and future research directions related to ChatGPT. By analyzing data from the Scopus database, 533 relevant articles were identified for analysis. The findings reveal the prominent publication venues, influential authors, and countries contributing to ChatGPT research. Collaborative networks among researchers and institutions are visualized, highlighting patterns of co-authorship. The application domains of ChatGPT, such as customer support and content generation, are examined. Moreover, the study identifies emerging keywords and potential research areas for future exploration. The methodology employed includes data extraction, bibliometric analysis using various indicators, and visualization techniques such as Sankey diagrams. The analysis provides valuable insights into ChatGPT's influence in academia and offers researchers guidance for further advancements. This study stimulates discussions, collaborations and innovations to enhance ChatGPT's capabilities and impact across domains.

Background: Limited research has explored sex-specific differences in death predictors of HF pa-tients with ischemic (iCMP) and nonischemic (niCMP) cardiomyopathy. This study assessed sex differences in niCMP and iCMP prognosis. Methods: We studied 7,487 patients with HF between February 2017 and September 2020. Clini-cal features and echocardiographic findings were collected. We used Kaplan-Meier, Cox propor-tional hazards models, and score chi-square of Cox regression to determine death predictors in women and men. Results: mean age was 64.3±14.2 years, with 4,417 (59%) males. Women with iCMP and niCMP exhibited significantly higher mean age, higher mean left ventricular ejection fraction, and smaller left ventricular diastolic diameter than men. Over 2.26 years of follow-up, 325 (14.7%) women and 420 (15.7%) men, and 211 women (24.5%) and 519 men (29.8%) died in niCMP (p=NS) and iCMP (p=0.004), respectively. Cumulative incidence of death was higher in men with iCMP (log-rank p<0.0001) but similar in niCMP. Cox regression showed chronic kidney disease, dia-betes, stroke, atrial fibrillation, age, and myocardial infarction, as main predictors of death for iCMP in women and men. Conclusion: Women exhibited a better prognosis than men in iCMP, but similar for niCMP. Nevertheless, sex was not an independent predictor of death for both CMP.

This paper studies the pilot control strategy and workload of tilt-rotor aircraft dynamic conversion procedure between helicopter mode and fixed-wing mode. A nonlinear flight dynamics model of tilt-rotor aircraft with full flight modes is established. On this basis, a nonlinear optimal control model of dynamic conversion is constructed, considering factors such as conversion corridor limitations, pilot control, flight attitude, engine rated power, and wing stall effects. To assess pilot workload, an analytical method based on wavelet transform is proposed, which examines the mapping relationship between pilot control input's amplitude, constituent frequencies, and control tasks. By integrating the nonlinear optimal control model and the pilot workload evaluation method, the analysis of pilot control strategy and workload during the conversion procedure is conducted, leading to the identification of strategies to reduce pilot workload. The results indicate that incorporating the item of pilot workload in the performance index results in a notable reduction in the magnitude of collective stick inputs and longitudinal stick inputs. Moreover, it facilitates smoother adjustments in altitude and pitch attitude. Additionally, the conversion of the engine nacelle can be achieved at a lower and constant angular velocity. In summary, the conversion and reconversion procedures are estimated to have a low workload (Level 1 ~ Level 2), with relatively simple and easy manipulation for the pilot.

Microwave transversal filters, which are implemented based on the transversal filter structure in digital signal processing, offer a high reconfigurability for achieving a variety of signal processing functions without changing hardware. When implemented using microwave photonic (MWP) technologies, also known as MWP transversal filters, they provide competitive advantages over their electrical counterparts, such as low loss, large operation bandwidth, and strong immunity to electromagnetic interference. Recent advances in high-performance optical microcombs provide compact and powerful multi-wavelength sources for MWP transversal filters that require a larger number of wavelength channels to achieve high performance, allowing for the demonstration of a diverse range of filter functions with improved performance and new features. Here, we present a comprehensive performance analysis for microcomb-based MWP spectral filters based on the transversal filter approach. First, we investigate the theoretical limitations in the filter spectral response induced by finite tap numbers. Next, we analyze the distortions in the filter spectral response resulting from experimental error sources. Finally, we assess the influence of input signal’s bandwidth on the filtering errors. These results provide a valuable guide for the design and optimization of microcomb-based MWP transversal filters for a variety of applications.

The vacuolar H+-ATPase is a multisubunit enzyme which plays an essential role in the acidification and functions of lysosomes, endosomes, and synaptic vesicles. Many genes encoding subunits of V-ATPases, namely ATP6V0C, ATP6V1A, ATP6V0A1 and ATP6V1B2, have been associated with neurodevelopmental disorders and epilepsy. The autosomal dominant ATP6V1B2 p.Arg506* variant can cause both deafness, congenital, with onychodystrophy, autosomal dominant (DDOD) and deafness, onychodystrophy, osteodystrophy, mental retardation, and seizures syndromes (DOORS). Some but not all individuals with this truncating variant have intellectual disability and/or epilepsy, suggesting incomplete penetrance and/or variable expressivity. To further explore the impact of the p.Arg506* variant in neurodevelopment and epilepsy, we generated Atp6v1b2emR506* mutant mice and performed standardized phenotyping using the International Mouse Phenotyping Consortium (IMPC) pipeline. In addition, we assessed the EEG profile and seizure susceptibility of Atp6v1b2emR506* mice. Behavioral tests revealed that the mice present locomotor hyperactivity and show less anxiety-associated behaviors. Moreover, EEG analyses indicate that Atp6v1b2emR506* mutant mice have interictal epileptic activity and that both heterozygous (like patients) and homozygous mice have reduced seizure thresholds to pentylenetetrazol. Our results confirm that variants in ATP6V1B2 can cause seizures and that the Atp6v1b2emR506* heterozygous mouse model is a valuable tool to further explore the pathophysiology and potential treatments for vacuolar ATPases-associated epilepsy and disorders.

Mosquitoes transmit pathogens that cause human diseases such as malaria, Dengue fever, Chikungunya, yellow fever, Zika fever, and filariasis. Chemical pesticides are effective instruments for reducing disease transmission and managing mosquito populations. However, these chemicals have drawbacks such as high production costs and negative effects on the environment and non-target organisms. Furthermore, as mosquitoes develop resistance to chemical insecticides, they become less effective. As a result, researchers are investigating novel insecticides. Advances in microbial biotechnology have resulted in a wide range of value-added products, including biopesticides for agricultural and public health purposes. In this review, we highlight the mainly untapped biotechnological potential of microorganisms for vector mosquito control and disease transmission reduction. Also, we underline the importance of more basic research and improved translational research methodologies, encouraging efforts to bridge the gap between academic research on biopesticides and public health interventions.

The use of drones for various applications has become increasingly popular in recent years, and machine learning has played a significant role in this trend. In this paper, we provide a comprehensive survey of the classification and application of machine learning in drones. The paper begins with an overview of the different types of machine learning algorithms and their applications in drones, including supervised learning, unsupervised learning, and reinforcement learning. Next, we present a detailed analysis of various real-world applications of machine learning in drones, such as object recognition, route planning, obstacle avoidance, search area optimization, and autonomous search. The paper also discusses the challenges and limitations of using machine learning in drones, such as data privacy, data quality, and computational requirements. Finally, the paper concludes with a discussion of the future directions of machine learning in drones and its potential impact on various industries and fields. This paper provides a valuable resource for researchers, practitioners, and students interested in the intersection of machine learning and drones.

In bilaterians organism, the signaling of pyramidal neurons (PyrNs) is linked to the relative (prevalent) molecular chirality and physiological, perceptual, cognitive, and psychological functions and dysfunctions, providing the coupling of the central nervous system downstream and upstream evolutionary and developmental processes. The most apparent and discriminating morphological specificity of PyrNs is the geometry of the cell body. However, the question "why/how PyrNs soma gains the shape of quasi-tetrahedral symmetry" has never been explicitly articulated. If the basic function of PyrNs is sensory space perception, supporting the orientation, and movement coordination, then the pyramidal shape of soma is the best evolutionary-selected geometry to perform sensory-motor coupling. In biology, the impact of chiral symmetry (handedness) is evident at all levels of biological organization, from the prevalent symmetry of biological molecules to the morphology and function of bilateral organisms. How the tetrahedral symmetry of biomolecules is linked to the morphology and functions of bilateral organisms remains a challenging question. Cell chirality represents an intermediate point connecting two poles of biochirality. In this holistic perspective, examining the PyrNs' morphology-circuitry-function link is crucial to understanding the complex interaction between genetic, epigenetic, and environmental factors in the evolution of the CNS. The predictive power of our hypothesis can be partially expressed by the statement that the most integral and reliable biomarker of the neurodegenerative (including aging) and mental (including all variants of psychiatric illness) disorders would be the detection of the hemispheric asymmetry of D-amino acids (D-AAs) level in pyramidal neurons (PyrNs).

This study was carried out to evaluate the effect of exogenous proline on growth, biochemical responses, and plant recovery of drought-stressed oilseed rape plants after renewed irrigation. The experiment was conducted under controlled laboratory conditions. After 21 days of cultivation, 3-4 leaf stage seedlings were sprayed with proline (1 mM), then subjected to prolonged drought stress for 8 days to achieve a severe water deficit, then irrigation was resumed and recovery was assessed after 4 days. The results show that exogenous application of proline reduced drought-induced growth inhibition of seedlings while maintaining relative water content (RWC) and growth parameters closer to those of irrigated plants. Proline had a positive effect on chlorophyll accumulation and membrane permeability while decreasing ethylene, H2O2, and MDA levels. Moreover, after 4 days of recovery, the H2O2 content of the proline-treated plants was significantly lower (2-fold) and the MDA content was close to that of continuously irrigated plants. Thus, all these biochemical reactions influenced plant survival: after drought + proline treatment, the number of surviving plants was 2 times higher than that of drought-treated plants. The findings show that exogenous proline has antioxidant, osmotic, and growth-promoting properties that improve the drought tolerance of winter oilseed rape plants and is, therefore, beneficial for drought adaptation in oilseed rape.

The optimization of the energy grid is a critical task for ensuring a sustainable and efficient energy future. Deep machine learning techniques have the potential to improve energy grid optimization by predicting energy demands and supplies, optimizing energy production and distribution, and detecting and preventing fraud. However, there are also several challenges associated with the use of deep machine learning in energy grid optimization. These include the lack of standardized datasets and data quality issues, interpretability and explain-ability of machine learning models, ethical and social implications of using machine learning, and integration with existing energy infrastructure and regulatory frameworks. Having a clear understanding that continued research and developments in deep learning applications to energy field are crucial for achieving a sustainable and efficient energy future. This paper therefore reviewed existing literature for challenges and opportunities associated with deep machine learning in energy grid optimization; and highlights the importance of continued research and development in the field. The paper found out that opportunities for future research in deep machine learning for energy grid optimization include advancements in machine learning algorithms and techniques, development of new datasets and data collection methods, integration of machine learning with other emerging technologies. It also established needs for collaborative research and public-private partnerships.

A variable speed anti-tangling reel mechanism was designed to address the problems of tangling, hanging and rewinding of the tassel wheel and the high paddling loss in the current Chinese rape combine harvester cutting table. The kinematic equations of the reel mechanism were developed, and the analysis showed that the speed in the entry stage is low and the speed in the exit stage is high, and the attitude of the reel teeth change with the rape plant movement during the whole paddling process. A single-factor test and a multi-factor regression orthogonal combination test were carried out using the cutting table loss rate of rape harvesting as the evaluation index. The main and secondary factors affecting the cutting table loss of the variable speed reel were obtained as the reel speed, the machine travel speed and the ground angle of the frame. A mathematical model of regression of cutter loss and the main influencing factors was established, with the coefficient of determination R2 = 0.9918. The optimal combination of parameters for the variable speed reel was obtained with the lowest cutting table loss rate in rape harvesting as the optimization target: reel speed 25r/min, frame parallel to the ground and implement travel speed 0.7m/s. Field validation tests and comparative tests of cutting table loss of the two reels were carried out. The test results show that the regression mathematical model of the cutting table loss is more accurate, and the cutting table loss is reduced by 13.9% with the variable speed reel compared to the cam-action reel, and there are no problems with the paddle teeth hanging and tangling during the paddling process.

Turmeric, Curcuma longa L., is a type of medicinal plant characterized by its perennial nature and rhizomatous growth. It is a member of the Zingiberaceae family and is distributed across the world’s tropical and subtropical climates, especially in South Asia. Its rhizomes are highly valued for food supplements, spices, flavoring agents, and yellow dye in South Asia since ancient times. It exhibits a diverse array of therapeutic qualities that encompass its ability to combat diabetes, reduce inflammation, act as an antioxidant, exhibit anticancer properties, and promote anti-aging effects. In this study, organic extracts of C. longa rhizomes were subjected to HPLC separation followed by mass spectrometry analysis. The Global Natural Product Social Molecular Networking (GNPS) approach was utilized for the first time in this ethnobotanically important species to conduct an in-depth analysis of its metabolomes based on their fragments. A total of 30 metabolites including 16 diarylheptanoids, 1 diarylpentanoid, 3 bisabolocurcumin ethers, 4 sesquiterpenoids, 4 cinnamic acid derivatives, and 2 fatty acid derivatives were identified. Among 16 diarylheptanoids identified in this study, five of them are reported for the first time in this species.

Piceatannol is a naturally occurring polyphenolic compound that is widely found in grapes, blueberries, mushrooms, passion fruit and other edible fruits and vegetables. It has a variety of biological activities and pharmacological effects, including anti-inflammatory, antioxidation, antiaging, antiviral, antitumor, anticancer, antiatherosclerosis, antiparasitic, immunoregulatory, and cardiovascular protection effects. The aim of this study was to investigate the antiherpesvirus effects of piceatannol. Pseudorabies virus (PRV) belongs to the family Herpesviridae. PRV has a wide host range and can cause cytopathic effects (CPEs) in PK-15 cells. Therefore, PRV was used as a model to study the antiherpesvirus effect of piceatannol. In this study, we evaluated the antiviral activity of piceatannol against PRV in vitro and in vivo. The results showed that piceatannol could reatrain PRV multiplication in PK-15 cells in a dose-dependent manner. The 50% inhibitory concentration (IC50) was 0.0307 mg/mL, the IC50 was 0.0307 mg/mL, and the selectivity index (SI, CC50/IC50) was 3.68. The addition of piceatannol at different stages of PRV infection inhibited the viral adsorption and intracellular replication phases of PRV. Piceatannol significantly reduced the expression levels of the IE180, EP0, UL29, UL44, US6 and UL27 genes of PRV within 48 h, significantly reduced the expression levels of the PRV gB and gD proteins, and reduced PRV-induced apoptosis. Molecular docking showed that piceatannol had good binding activity with the PRV gB and gD proteins. The results of animal experiments in vitro indicated that piceatannol could delay the onset of disease, improve the survival rate of the mice (14.3%), reduce the viral load in the brain and kidney of the mice, alleviate the pathological changes in the mouse tissues and organs, and increase the levels of TNF-α, IEN-γ and IL-4 in the serum of the mice. These data indicate that piceatannol has good anti-PRV activity in vitro and in vivo, indicating that it could be a novel antiherpesvirus infection agent in the future.

Galectins have been shown to have roles in cancer progression via contributions to angiogenesis, metastasis, cell division, and evasion of immune destruction. This study analyses galectin-1, -3, and -9 serum concentrations in breast cancer patients by enzyme-linked immunosorbent assay (ELISA) against the characteristics of the patient and tumor such as stage, molecular subtype, and receptor expression. Galectin-9 was found to be statistically significantly increased in HER2 enriched tumors as well as being reduced in patients with hormone receptor positive tumors and increased in patients with HER2 amplified tissues. Galectin-1 was found to be statistically significantly increased in the serum of patients who had undergone hormonal, immunotherapy, or chemotherapy. These findings provide insight as to the changes in galectin levels during cancer progress, response to treatment and molecular phenotype. These findings are valuable in the further understanding of the relationships of galectin and tumor biology and can inform future research on therapeutic targets for galectin inhibitors and the utility of galectin biomarkers.

The global malaria community has picked up the theme of malaria elimination in greater than 90 % of the world’s population in the next decade. The recent reports of P. vivax in all sub-Saharan Africa, including Duffy negative individuals, threaten the efforts to achieve elimination. This is not only in view of strategies that are tailored only to P. falciparum elimination, but also due to currently revealed biological characteristics of P. vivax concerning the relapse patterns of hypnozoites and conservation of a large biomass at cryptic sites in the bone marrow and spleen. A typical scenario has been observed in Botswana from the period between 2008 to 2018, which palpably projects how P. vivax could endanger efforts at malaria elimination where the two parasites co-exist. The need for the global malaria community, NMPs, funding agencies and relevant stakeholders to engage in a forum to discuss and recommend clear pathways for sub-Saharan Africa regarding malaria elimination including P. vivax, is warranted.

Chiral interactions play a crucial role in both chemistry and biology. Understanding the behavior of chiral molecules and their interactions with other molecules is essential, and chiral interactions in solutions are particularly important for studying chiral compounds. Chirality influences the physical and chemical properties of molecules, including solubility, reactivity, and biological activity. In this work, we used Isothermal Titration Calorimetry (ITC), a powerful technique for studying molecular interactions, including chiral interactions in solutions. We conducted a series of ITC measurements to investigate the heat of dilution and the heat of racemization of several amino acids (Asn, His, Ser, Ala, Met, and Phe). We also performed ITC measurements under different solute concentrations and temperatures to examine the effects of these parameters on chiral interactions, as well as the heat of dilution and racemization. The results of our measurements indicated that the heat of dilution, specifically the interactions between the solvent (water) and solute (chiral molecules), had a significant impact compared to the chiral interactions in the solution, which were found to be negligible. This suggests that the interactions between chiral molecules and the solvent play a more dominant role in determining the overall behavior and properties of the system. By studying chiral interactions in solutions, we can gain valuable insights into the behavior of chiral compounds, which can have implications in various fields, including drug design, chemical synthesis, and biological processes.

Objectives: Essential thrombocythemia (ET) is a chronic myeloproliferative neoplasm characterized by elevated platelet counts and an increased risk of thrombotic events, including ischemic strokes. Methods: We conducted a retrospective analysis of data from consecutive ischemic stroke patients with ET between March 2014 and February 2023. Results: This case series describes the clinical presentation, radiological features, and management of five patients with ET-associated ischemic strokes, all harboring the JAK2 mutation. The diverse radiological findings suggest that both large and small vessel diseases may be influenced by the prothrombotic state induced by ET. A significant elevation in platelet count was observed to correlate with the emergence of new acute infarctions in some cases. Conclusions: The study highlights combined use of antiplatelet and cytoreductive therapy in preventing secondary stroke events in patients with ET and JAK2 mutations. The heterogeneity of stroke patterns in this population necessitates a comprehensive understanding of the underlying pathophysiological mechanisms and tailored therapeutic approaches.

The abnormal accumulation of cells in the human brain, if left untreated, may cause brain damage. Management and treatment of these tumours require an early and accurate diagnosis, while their prognostic characterisation can also be beneficial in the choice of care planning for the patient. CDSSs are being continuously developed and integrated into routine clinical practice as they assist clinicians and radiologists to deal with an enormous amount of medical data, reduce clinical errors, and improve diagnostic capabilities. They assist detection, classification, and grading of brain tumours as well as alerting physicians of requirement of change in treatment plans. The aim of this systematic review is to identify various CDSSs used in brain tumour diagnosis and prognosis, that rely on data captured by any imaging modality. Based on the 2020 Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) protocol, the literature search was conducted in PubMed and Engineering Village Compendex databases. This review examines various CDSS tool types, system features, techniques used, accuracy, and outcome, to provide the latest evidence available in the field of neuro-oncology. An overview of different types of CDSSs used to support clinical decision-making in the management and treatment of brain tumours, along with highlighting their benefits, challenges, and future perspectives has been provided.

The purpose of this work is to compare two fracture prediction models with real-world data. The pure Artificial Neural Network (ANN) model emphasizes regression analysis, while the hybrid model (SVM-ANN) focuses on the combination of regression and classification analysis or Support Vector Machine. The results were subsequently tested against logging data by combining the Machine Learning approach with advanced logging tools. In this context, we used electrical image logs and the dipole acoustic tool which together allowed the distinction of 404 open fractures and 231 closed fractures and, consequently the estimation of fracture porosity. The results are then fed into two machine-learning algorithms. Pure Artificial Neural Networks and hybrid models are used to establish comprehensive results, which are subsequently tested to check the accuracy of the models. The outputs obtained from the two methods demonstrate that the hybridized model has a lower Root Mean Square Error (RMSE) than pure ANN. The results of our approach strongly suggest that incorporating hybridized machine learning algorithms in fracture porosity estimations can contribute to the development of more trustworthy static reservoir models in simulation programs. Finally, the combination of Machine Learning (ML) and well-log analysis do permit reliable estimation of fracture porosity in the Ahnet field in Algeria, where, in many places, advanced logging data is absent and costly.

To date, only a few studies focused on carbon monoxide (CO) production during waste composting; all targeted on CO inside piles. Here, the CO net emissions from compost piles and the assessment of worker’s occupational risk of exposure to CO at large-scale composting plants are shown for the first time. CO net emissions were measured at two plants processing green waste, sewage sludge, or undersize fraction of municipal solid waste. Effects of the location of piles (hermetised hall vs. open yard) and turning (before vs. after) were studied. Higher CO net emission rates were observed from piles located in a closed hall. The average CO flux before turning was 23.25 and 0.60 mg‧m-2‧h-1 for hermetised and open piles, respectively, while after – 69.38 and 5.11 mg‧m-2‧h-1. The maximum CO net emissions occurred after the compost was turned (1.7x to 13.7x higher than before turning). The top sections of hermetised piles had greater CO emissions compared to sides. Additionally, 5% of measurement points of hermetised piles switched to ‘CO sinks’. The 1-h concentration in hermetised composting hall can reach max. ~50 mg CO∙m-3 before turning, and &gt;115 mg CO∙m-3 after, exceeding the WHO thresholds for a 1-h and 15-min exposures, respectively.

Tissue inhibitors of metalloproteinases (TIMPs) are essential players during tumor progression in various types of cancer, including breast cancer. TIMPs regulate the activity of matrix metallo-proteinases (MMPs) at different levels. However, a dual role for TIMPs in breast carcinogenesis, either promoting or inhibiting tumor progression, has been observed. By a comprehensive bioin-formatics analysis using different databases, we report that of the four TIMPs, only TIMP-1 is overexpressed in tumor breast tissue. However, TIMP-2, TIMP-3, and especially TIMP-4 present lower levels in breast tumor tissue than in normal tissue. Interestingly, high levels of TIMP-1 are associated with shorter survival in breast cancer patients. In contrast, low TIMP-2, TIMP-3, and TIMP-4 levels are associated with poor survival. Function enrichment analysis showed that TIMP-3 has the highest interactions with its target proteins and a higher number of processes re-lated to mammary carcinogenesis. We found differential expression of TIMP-1 concerning TIMP-3 and TIMP-4 in breast cancer and normal tissue. TIMP-4 has a significant relationship with cancer staging, including tumor size, lymph node spread, and metastasis. The correlation between immune cell infiltrates and TIMP expression is of great importance as they provide in-formation on breast cancer diagnosis, prognosis, progression, and response to treatment.

Cells are influenced by several biomechanical aspects of their microenvironment, such as substrate geometry. According to the literature, substrate geometry influences the behavior of muscle cells; in particular, the curvature feature improves cell proliferation. However, the effect of the substrate geometry on the myogenic differentiation process is not clear and needs to be further investigated. Here, we show that the 3D co-printing technique allows the realization of substrates. To test the influence of the co-printing technique on cellular behavior we realized linear polycaprolactone substrates with channels in which a fibrinogen-based hydrogel loaded with C2C12 cells was deposited. Cell viability and differentiation were investigated up to 21 days in culture. The results suggest that this technology significantly improves the differentiation at 14 days. Therefore, we investigate the substrate geometry influence by comparing three different co-printed geometries – linear, circular, and hybrid structures (linear and circular features combined). Based on our results, all structures exhibit optimal cell viability (&gt; 94%) but the linear pattern allows to increase the in-vitro cell differentiation, in particular after 14 days of culture. This study proposes an endorsed approach for creating artificial muscles for future skeletal muscle tissue engineering applications.

Aging is a major risk factor for Alzheimer's disease (AD). AD mouse models are frequently used to assess pathology, behavior, and memory in AD research. While the pathological characteristics of AD are well established, our understanding of the changes in the metabolic phenotypes with age and pathology is limited. In this work, we used the Promethion cage systems® to monitor changes in physiological metabolic and behavioral parameters with age and pathology in wild-type and 5xFAD mouse models. Then, we assessed whether these parameters could be altered by treatment with oleocanthal, a phenolic compound with neuroprotective properties. Findings demonstrated metabolic parameters such as body weight, food and water intake, energy expenditure, dehydration, and respiratory exchange rate, and the behavioral parameters of sleep patterns and anxiety-like behavior are altered by age and pathology. However, the effect of pathology on these parameters was significantly greater than normal aging, which could be linked to amyloid-β deposition and blood-brain barrier (BBB) disruption. In addition, and for the first time, our findings suggest an inverse correlation between sleep hours and BBB breakdown. Treatment with oleocanthal improved the assessed parameters and reduced anxiety-like behavior symptoms and sleep disturbances. In conclusion, aging and AD are associated with metabolism and behavior changes, with the changes being greater with the latter, which were rectified by oleocanthal. In addition, our findings suggest that monitoring changes in metabolic and behavioral phenotypes could provide a valuable tool to assess disease severity and treatment efficacy in AD mouse models.

We study two fundamental linguistic channels ‒ the Sentences and the Interpunctions channels ‒ and show they can reveal deeper connections between texts. The theory applied does not follow the actual paradigm of linguistic studies. As study‒case, we consider the Greek New Testament, with the purpose of determining mathematical connections between its texts and possible differences in writing style (mathematically defined) of writers, and in reading skill required to their readers. The analysis is based on deep‒language parameters and communication/information theory. To set the New Testament texts in the larger Greek Classical Literature, we consider texts written by Aesop, Polybius, Flavius Josephus and Plutarch. The results largely confirm what scholars have found about the New Testament texts giving, therefore, credibility to the theory. The gospel according to John is very similar to Fables written by Aesop. Surprisingly, the Epistle to the Hebrews and Apocalypse, are each other “photocopy” in the two linguistic channels, and not linked to all other texts. These two texts deserve further study by historians of the early Christian Church Literature at the level of meaning, readers and possible Old Testament texts which might have influenced them. The theory can guide scholars to study any literary corpus.

Context. During the COVID-19 pandemic, patient care was mainly organised around the hospital. Pre-hospital care has, to our knowledge, never been evaluated. Objective: To evaluate the impact of pre-hospital pathways on hospitalisation during the last part of the pandemic. Design. This was a monocentric retrospective analysis of prospectively collected medical records. Data from patients admitted to our institute between 1 February and 7 March 2022 were analysed. Main Outcome Measure(s): The primary outcomes were defined as the number of hospitalisations, resuscitations, and deaths at the time of interview and in the subsequent 30 days. The main explanatory variables were times from onset of symptoms to care, age, gender, News2 score, comorbidities, and pre-hospital pathways and their duration. Results: Three pre-hospital pathways have been identified: a pathway in which the patient consults a general practitioner for a test (PHP1); a pathway in which the patient consulted for care (PHP2); and no pre-hospital pathway and direct admission to hospital (PHP3). Factors independently associated with outcome (hospitalisation) were being male (OR 95% CI; 2.21 [1.01–4.84], p=0,04), News2 score (OR 95% CI; 2.04 [1.65–2.51], p<0.001), obesity (OR 95% CI; 3.45 [1.48–8.09], p=0.005), D-dimers > 0.5 µg/ml (OR 95% CI; 3.45 [1.47–8.12], p=0.005), prolonged time from symptoms to hospital care (PHP duration) (OR 95% CI; 1.07 [1.01–1.14], p=0.03). All things being equal, patients with a “PHP2” pre-hospital pathway had a higher probability of hospitalisation compared to those with a “PHP3” pre-hospital pathway (OR 95% CI; 4.31 [1.48–12.55], p=0.007). Conclusions. Along with recognised risk factors such as gender, News 2 score, and obesity, the patient’s pre-hospital pathway is an important risk factor associated with hospitalisation.

This article addresses the problem of contact voltage increase caused by the low frequency oscillation of the train-grid system in the phase-separation process of the EMU. The article establishes the EMU-contact line-traction substation model, reveals the mechanism of low-frequency oscillation, and obtains the relationship between the separation phase angle of the pantograph with line and low-frequency oscillations. Methods to suppress the over-voltage during the low-frequency oscillation are proposed. The study shows that when the power phase angle of the pantograph-line separation is within the range of 60°~90° and 240°~270°, the voltage amplitude in the neutral zone is larger, the maximum amplitude can reach 52.2kV, and low-frequency oscillation will occur in the neutral zone. When low frequency oscillation occurs, the contact line voltage in the neutral zone is mainly 1/3 power frequency (16.7Hz). After installing an RC suppression device in the neutral zone, when the EMU enters the neutral zone, the absolute value of the voltage peak drops to below 20 kV. Compared with the situation where the suppression device is not connected, the absolute value of the voltage peak is reduced by nearly 60%. The study provides a basis for the design of the neutral zone of the contact line and the selection of the high-voltage equipment of the EMU.

Single-molecule magnets (SMMs) have garnered significant interest in the field of molecular magnetism due to their unique magnetic properties at the nanoscale. These molecular systems exhibit magnetisation behaviour reminiscent of conventional bulk magnets but with distinct advantages such as size-dependent properties and potential applications in quantum computing and high-density data storage. However, challenges remain in harnessing their properties for practical applications, including their susceptibility to degradation and limited control over their assembly and organisation.

Through the ACE2, a main enzyme of the renin-angiotensin system (RAS), the SARS-CoV2 gains access into the cell, resulting in different complications which may extend beyond the RAS and impact the Arachidonic Acid (ArA) pathway. The contribution of the RAS through ArA pathways metabolites in the pathogenesis of COVID-19 is unknown. We investigated whether RAS components and ArA metabolites can be considered biomarkers of COVID-19. We measured the plasma levels of RAS and ArA metabolites using an LC-MS/MS. Results indicate that Ang1-7 levels were significantly lower, whereas Ang II levels were higher in the COVID-19 patients than healthy control individuals. The ratio of Ang1-7/Ang II as an indicator of the RAS classical and protective arms balance was dramatically lower in COVID-19 patients. There was no significant increase in inflammatory 19-HETE and 20-HETE lev-els. The concentration of EETs was significantly increased in COVID-19 patients, whereas the DHETs concentration was repressed. Their plasma levels were correlated with Ang II concentration in COVID-19 patients. In conclusion, evaluating the RAS and ArA pathway biomarkers could provide helpful information for the early detection of high-risk groups, avoid delayed medical attention, facilitate resource allocation and improve patient clinical outcomes to prevent long COVID incidence.

Parkinson’s-disease (PD) is an incurable age-related neurodegenerative disease and its global prevalence of disability and death has increased exponentially. Although motor symptoms are the characteristic manifestations of PD, the clinical spectrum also contains a wide variety of non-motor symptoms, which are the main cause of disability and determinants of the decrease in a patient's quality of life. Noteworthy in this regard is the stress on the cardiac system that is often observed in the course of PD, however its effects have not yet been adequately researched. Here, an untargeted metabolomics approach was used to assess changes in cardiac metabolism in the 6-hydroxydopamine model of PD. Beta-sitosterol, campesterol, cholesterol, monoacylglycerol, α-tocopherol, stearic acid, beta-glycerophosphoric acid, o-phosphoethanolamine, myo-inositol-1-phosphate, alanine, valine and allothreonine, are the metabolites that significantly discriminate Parkinsonian rats from sham counterparts. Upon analysis of the metabolic pathways with the aim of uncovering the main biological pathways involved in concentration patterns of cardiac metabolites, biosynthesis of both phosphatidylethanolamine and phosphatidylcholine, glucose-alanine cycle, the glutathione metabolism and plasmalogen synthesis most adequately differentiated sham and Parkinsonian rats. Our results reveal that both lipid and energy metabolism are particularly involved in changes in cardiac metabolism in PD. These results provide insight into cardiac metabolic signatures in PD and indicate potential targets for further investigation.

This article presents the results of research on the influence of polymetallic dust aerial emissions on the pollution levels in the soil and plants by heavy metals which have been under impact of the “Severonickel” smelter complex on the Kola peninsula (Russia) for many years. Research using soil- and bio-indicators was carried out at fixed measuring points in the years 1980-1999 (high aerotechnogenic emissions) and 2000-2019 (low aerotechnogenic emissions). The organic horizon (forest litter) of the Al-Fe-humus podzol, leaves of Vaccinium myrtillus L., V. vitis-idaea L., V. uliginosum L., Empetrum hermaphroditum Hagerup and one-year old Scots pine needles Pinus sylvestris L. as well as tree rings of Pinus sylvestris L. were used for bioindication research. The content of heavy metals was determined by the AAS method. During these time periods, the volume of atmospheric emissions of sulfur dioxide decreased 5 fold, polymetallic dust by 3.5 times, while the level of forest litter pollution by heavy metals in the buffer zone increased by 2 times, and did not change significantly in the impact zone. The decrease in atmospheric emissions of pollutants led to a 1.5- fold increase in the width of the annual rings of pine trunks in the impact zone, while in the buffer zone the differences were insignificant. At present, the content of Ni and Cu in the leaves of the wild dwarf-shrubs and pine needles in the impact zone has decreased by 5 times compared with 1980-1999 due to a decrease in polymetallic dust on the leaf surface.

Cervical cancer is associated with persistent infections by high-risk HPV types that may have nucleotide polymorphisms and, consequently, different oncogenic potentials. Therefore, the objective of this study was to evaluate the genetic variability and structural effects of E7 oncogene of HPV58 in cervical scraping samples from Brazilian women. The study was carried out with patients from hospitals in metropolitan area of Recife, PE, Brazil. The most frequent HPV type was HPV16, 18 and 58, respectively. Phylogenetic analysis showed that the isolates were classified as sublineages A2, C1 and D2. Two positively selected mutations were found in E7: 63G and 64T. The mutations G41R, G63D and T64A in E7 protein were predicted to reduce the stability of the protein structure. Regarding the interaction of the E7 variant of HPV58 with the signaling of the NF-kB pathway, we observed that the variant HPV58/UFPE-54S decreased the activity of the pathway when compared to the prototype and the other variants behaved similarly to the prototype and the prototype increased the activity of the pathway when compared to pcDNA. In this study, it was possible to identify mutations that may interfere in the molecular interaction between the viral oncoproteins and host proteins.

The purpose of this article is to conduct a bibliometric review of literary production in terms of market interdependence. We investigate the effect of contagion on agricultural commodities and identify the commodities and methods used in the most cited publications over the decades. For this, we used the SCOPUS database, sorting with Rayyan, Excel, and finally, the Bibliometrix/R-project. The results showed that corn, wheat, soybeans, cotton, and sugar are the most studied commodities. There is no uniqueness concerning the methods used to identify interdependence and the contagion effect. Also, it is possible to perceive the growing scientific interest concerning the subject, with a diversity of authors and magazines. However, there is a direction of the and magazines most cited articles for analyzing agricultural commodities and energy, demonstrated a worldwide trend of studies relating natural resources, biofuels, clean energy, and efficiency. In addition, countries like China and the United States stand out in this scientific scenario as the countries that produce the most articles.

Acute vertigo and dizziness are frequent presenting symptoms in patients on the emergency department. With a broad differential diagnosis and symptoms/signs often subtle and transient, the diagnostic approach to the dizzy patient remains challenging. Previous work emphasized the value of combining structured history-taking and a targeted examination focusing on subtle oculomotor signs. Here I review different bedside algorithms proposed for the acutely dizzy patient. Comparing area-under-the-curve ROC-characteristics and sensitivity/specificity, highest diagnostic accuracy was observed for algorithms focusing on subtle oculomotor signs. Both the HINTS+ bedside-exam and the STANDING algorithm have demonstrated higher diagnostic accuracy for identifying strokes than early (<24-48h after symptom-onset) MRI-DWI. Importantly, HINTS and STANDING require moderate training to allow reliable application. Thus, for physicians lacking dedicated training, other approaches are needed. Various scores that rely on vascular risk-factors, clinical symptoms and focal neurologic findings have been proposed (e.g., ABCD2-score, PCI-score, TriAGe+-score). While these scores are more readily applicable for frontline providers, they provide intermediate diagnostic accuracy at best and often lack external validation, thus are an insufficient substitute for algorithms assessing subtle oculomotor findings. Providing dedicated training in HINTS+ or STANDING techniques will be key to improve the diagnostic accuracy and to avoid unnecessary brain imaging.

Wildlife tourism and wildlife trade may appear juxtaposed, but are two, potentially aligning, income generators that could benefit conservation in developing countries. Utilising data sets collated from Madagascar’s Ministère du Tourisme and CITES respectively for the period 2007 to 2018, this study estimated levels of income from wildlife tourism and wildlife trade for Madagascar. Between 2007-2018, tourism reported yearly incomes ranging from a low of US $1.4 million up to a high of US $15.7 million. However, it was unclear what percentage of this figure flowed to benefit local communities. Alternatively, using reported networks for the live wildlife trade, the estimated economic value reaching collectors and/or intermediaries on Madagascar was US $72,299.80 for the period 2007 to 2018. Both revenue generators operated within different geographical areas, with tourism opportunities presenting themselves to communities adjacent NPs, while wildlife trade networks were not restricted to NPs and operated sporadically across Madagascar. Hence, the economic benefits reached different Malagasy participants across the country. The management of both activities needs great care to ensure that environmental impacts and sustainability are core measures on any such activities. Whilst this study shines light on economic values and novel perspectives regarding these two trade types, it also highlighted knowledge gaps. Thus, indicating where much greater research attentions was required to allow better understanding of the specific benefits and risks from engaging with both trade types for local Malagasy people and their environments.

Agroforestry homegardens are integrated arrangements of common vegetable plants in areas close to residences, which follow a structure similar to that of tropical forests, with the cultivation of multiple species to meet the basic needs of families, such as the provision of food and medicine, as well as ensuring an environment for other family activities. Considering the importance of these environments, this work aimed to address the composition and use of plant species in agroforestry homegardens, in order to support society initiatives and government policies to strengthen the management of natural resources and individual and collective well-being in the region. For this, 119 homegardens were studied in the municipalities of Belterra, Mojuí dos Campos and Santarém, in the state of Pará, in the Brazilian Amazonia, comprising five different zones (peri-urban, urban, floodplain, indigenous land and tourist land), obtaining the data via questionnaires and guided visitation by the residents. A total of 5,323 vegetal individual plants were surveyed, distributed in 188 species and 62 botanical families. The data showed that 80.5% of the individual plants are concentrated in 18.6% of the species, with no significant difference in the average of species per homegarden in the five zones. The predominance of species for food use, primarily fruit-bearing, stands out, showing a possible direction for incentive actions and/or for the ordering of public policies and programs aimed at these spaces. Most homegardens have up to 17 plant species; less than half of homegardens have species intended for medicinal use; and there is percentage parity between native plant species and those of exotic origin, where native plants stand out for shading. Agroforestry homegardens play a crucial role in the conservation and cultivation of species for food purposes, with the cultivation or maintenance of plants based on their various purposes, showing distinct profiles of distribution and choice of species, evidencing their socioeconomic and environmental importance. Thus, it is important that these land use systems are valued, investing financial resources in actions and projects aimed at maintaining and enhancing their benefits for the region.

Humankind has entered a new era wherein a main characteristic is the convergence of various technologies providing services exerting major impact upon all aspects of human activity, be it social interactions as well as interactions with the natural environment. Fixed networks are about to play a major role in this convergence, since they form, along with mobile networks, the backbone that provides access to a broad gamut of services, accessible from any point of the globe. It is for this reason that we introduce a forward-looking approach for fixed networks, particularly focused on Fixed 6th Generation (F6G) networks. First, we adopt a novel classification scheme for the main F6G services, comprising six categories. This classification is based on the key service requirements, namely latency, capacity and connectivity. F6G networks differ from those of previous generations (F1G-F5G) in that they concurrently support multiple key requirements. We then propose concrete steps towards transforming the main elements of fixed networks, such as optical transceivers, optical switches etc. such that they satisfy the new F6G service requirements. Our study categorizes the main networking paradigm of optical switching into two categories namely ultra-fast and ultra-high capacity switching, tailored to different service categories. With regard to the transceiver physical layer, we propose: a) use of all-optical processing to mitigate performance barriers of analog to digital and digital to analog converters (ADC/DAC); b) exploitation of optical multi-band transmission, space division-multiplexing and adoption of more efficient modulation formats.

The security of several full homomorphic encryption (FHE) schemes depends on the hardness of the approximate common divisor (ACD) problem. The analysis of attack and defense against the system is one of the frontiers of cryptography research. In this paper, the performance of existing algorithms, including orthogonal lattice, simultaneous diophantine approximation, multivariate polynomial and sample pre-processing are reviewed and analyzed for solving the ACD problem. Orthogonal lattice (OL) algorithms are divided into two categories (OL-$\land$ and OL-$\vee$) for the first time. And an improved algorithm of OL-$\vee$ is presented to solve the GACD problem. This new algorithm works well in polynomial time if the parameter satisfies certain conditions. Compared with Ding and Tao's OL algorithm, the lattice reduction algorithm is used only once, and when the error vector $\mathbf{r}$ is recovered in Ding et al.'s OL algorithm, the possible difference between the restored and the true value of $p$ is given. It is helpful to expand the scope of OL attacks.

The new coronavirus SARS Cov2 disease from 2019. (COVID-19), started as a cluster of unexplained pneumonia cases in Wuhan in December 2019, has spread globally and caused a serious public health threat. People were scared due to the COVID-19 cases that were rapidly increasing all over the world and the quick changes in how people lived. The COVID-19 pandemic has affected various aspects of life, one of which is the increased use of the internet, especially social media platforms. Past research has clearly linked a pandemic with signs of stress, depression, anxiety, and suicide thoughts, as well as with excessive internet use. The findings of research conducted around the world indicate that the higher the level of stress associated with the COVID-19 pandemic in an individual, the greater the tendency to develop an addiction to the internet. The aim of this paper was to provide a brief overview of the available scientific findings on the impact of the COVID-19 pandemic on mental health and internet addiction. Methods: A sweep through available literature was performed using the database Medline via the PubMed interface for articles written in English, using keywords and MeSH terms "Internet addiction", "mental health" and "COVID-19". Results: With insight into the scientific literature on COVID-19, mental health, and internet addiction, we have concluded that during the COVID-19 pandemic, time spent on the internet increased. Conclusion: Additionally, due to reduced social activities, above mentioned consequently led to internet addiction and thus to psychological distress, increased loneliness and depression.

This study investigates how Electronic Livestock Health Recording Systems (ELHRs) facilitates the detection of disease burden and make cluster analysis by applying data analytics tools and techniques. A sample size of 18333 livestock disease cases reported from 2007-2015 by the Ministry of Agriculture of the Federal Democratic of Ethiopia was used for data collection. The results showed that ELHRs are important as livestock disease data preservers, saving costs, and facilitating the extraction of up-to-date and complete information. Euclidean and Manhattan distance performed well at 98%, while cosine distance measurement metrics performed poorly. Finally, with the application of the selected clustering techniques, metrics, tools, and dataset, it has been attempted to successfully detect an optimal number of disease clusters and meet the objectives of the study.

The paper analyzes the phenomenon that condition the durability and reliability of a type of dental bur based on the wear of the active part and with effect on its quality. For the experimental study, a conical-cylindrical dental bur and a sample dental material in cobalt-chromium alloy, cylindrical shape, tested on a specially made experimental installation were used. The paper was limited to the consideration of a single parameter (loss of mass, mw by wear of the active part of the dental bur tested) for the establishment the durability and reliability, useful for the extension of the lifetime or even optimization of its operation. The wear phenomenon of the active part of dental bur is studied based on the results and experimental data obtained in the work process that was validated by interpolation and led to polynomial functions which approximate very well the dependent parameter, mw, considered in the experimental program. The results of the interpolation showed that in the first 11 h of work, the dental bur works with high efficiency, after which it can be easily decommissioned (optimizing operation, possibly constructive solutions); i.e., it should be replaced with a new one (criterion for replacing of worn dental bur).

This study aimed to assess the physical characteristics of elite international soccer referees, compare them with other referee populations in the literature, and establish reference tolerance ellipses for the bioelectrical impedance vector analysis (BIVA) point graph. Forty-one elite international soccer referees (age 38.8 ± 3.6 years) participated in the study. the participants underwent body composition assessments, including dual-energy X-ray absorptiometry, BIVA, and somatotype. The Somatotype Attitudinal Distance (SAD), the two-sample Hotelling’s T2 test, and the Mahalanobis test were used to determine somatotype and bioelectrical vector differences with the literature. The average somatotype of the referees was a balanced mesomorph (2.8, 6.5, 2.8). Elite international referees significantly differed from other samples in the literature (SAD = 2.1, 2.6, 2.9 with respect to Zimbabwean, Brazilian, and South African referees, respectively). The bioelectrical vector was significantly different from the general population (T2  76.6; F = 38.8; D = 1.44; P < 0.001) and athletes (T2  25.3; F = 12.6; D = 0.8; P < 0.001). Somatotype values and tolerance ellipses from this study may be useful as a reference for developing training programs and improving the selection process of referees in soccer.

Crop disease classification has always been a critical and persistent problem in the field of agricultural and forestry sciences, where often we do not have access to a sufficient number of samples to know the distribution of real-world samples. How to make full use of the existing data is the starting point of our thinking. To address this problem, this paper proposes a supervised image augmentation method Negative Contrast, which uses the contrast images of existing disease samples after removing disease areas as negative samples for image augmentation when samples are relatively scarce. Numerous experiments have shown that several classical models using this augmentation method have improved in disease classification of four crops, rice, wheat, corn, and soybean, with a maximum accuracy improvement of 30.8%. In addition, the comparative analysis of attentional heat map shows that the model using Negative Contrast is more accurate and intense on the area of interest of diseases, and thus reflects better generalization ability in real-world disease classification. Our dataset and codes can be found in https://www.kaggle.com/datasets/w970704112/corn-wheat-rice-soybean and https://github.com/hiter0/contrastaug .

A high performance Driver State Monitoring (DSM) application for the detection of driver drowsiness is presented in this paper. It relies on the usage of an Ensemble of Regression Trees (ERTs) machine learning method that aligns 68 facial landmarks. Special focus is given on the acceleration of the frame processing using reconfigurable hardware. Reducing the frame processing latency saves time that can be used to apply frame-to-frame facial shape coherency rules. False face detection and false shape estimations can be ignored for higher robustness and accuracy in the operation of the DSM application without reducing the frame processing rate that can reach 65 frames per second. The sensitivity and precision in yawning recognition can reach 93% and 97%, respectively. The implementation of the employed DSM algorithm in reconfigurable hardware is challenging since the kernel arguments require large data transfers and the degree of data reuse in the computational kernel is low. Due to this, unconventional hardware acceleration techniques have been employed that can also be useful for the acceleration of several other applications.

Global warming causes an alarming increase in temperature which negatively affects growth, physiology, and yield of rice. To gain some insights into the impacts of booting HT (at 42°C, 3 h for 7 days), we investigated its effect in three rice genotypes, namely, N22, KDML105 and IR64. Booting HT caused an extended phenology and lower photosynthesis and plant growth rate but an increase in chalkiness. Although, prolonged phenology from dough to physiological maturity led to longer duration of grain filling, the negative effects of its was significantly lower yield components, yield and harvest index in all rice. Among cultivars, N22 presented adapted ability to maintain leaf gas exchange and compensated vegetative part by an increase in tiller numbers resulting in less affected growth rate. It prolonged phenology that caused extended grain filling. Consequence, N22 was the lowest reduction in number of seed panicle^–1, number of filled seeds hill^–1, yield, HI as well as the lowest percentage chalkiness. KDML105 adapted to booting HT by maintaining leaf gas exchange, increasing specific leaf area and prolonging phenology. The longest extended phenology together with the maintenance of high photosynthesis during dough grain were associated with moderate yield reduction and chalkiness. However, IR64 showed dramatic reductions in photosynthesis, growth rate, and yield but highest percentage grain chalkiness. Therefore, in response to booting HT, N22, KDML105 and IR64 could be indicated as being heat tolerant, moderately heat sensitive, and heat sensitive, respectively. This can be applied for crop modelling and rice heat tolerance in breeding program.

Although the Orthotropic steel decks (OSDs) have been widely used in the construction of long-span bridges, there are frequently reported fatigue cracks after years of operation, and the bridge deck overlay also presents severe damage due to OSD crack-induced stiffness reduction. The ultra-high performance concrete (UHPC), recognized as the most innovative cementitious composites and the next generation of high-performance materials, shows high strength, ductility, toughness and well performance on durability. After its first application to the OSD bridge in early 2000s, the orthotropic Steel-UHPC composite deck has been comprehensively studied worldwide. This review will summarize some important studies and findings on behavior and fatigue performance of orthotropic steel-UHPC composite deck. The existing studies and engineering application indicate that such deck system presents good bending behavior and high fatigue performance. The failure mode of shear studs in UHPC layer is dominated by shear fractures. The cracking of UHPC layer shall consider the superposition effect of stress from both the whole bridge structure and local decks. While some reasonable structural details in the traditional OSD may not work for the orthotropic steel-UHPC composite deck. It is recommended to evaluate the stress behavior and structural parameters, as well as fatigue life by conducting the field test under in-service traffic conditions.

While the debate on the association between Enterobius vermicularis (E. vermicularis) and acute appendicitis has not been settled, a few case reports of this very rare encounter are beginning to come to light. While E. vermicularis is one of the most common parasitic infestations around the world, acute appendicitis, on the other hand, is also a commonly encountered condition in general surgery. However, the association between the two remains controversial. Here we present a case report of a young woman with appendicitis associated with (E. vermicularis).

This article presents the results of the study on the elements and spaces that likes and dislikes’ historical urban landscape of Ibarra's city, Ecuador, based on the analysis of the urban image. This research aims to propose an objective way to intervene a historical landscape based on the opinion of the people who frequent the place. Our hypothesis is that the characteristics (age, gender, educational level, and frequency of visits) of the interviewees condition their judgment on liking and disliking. It is proposed to know which of these characteristics condition the judgment. The methodology has two parts: a descriptive statistical analysis with graphs and frequencies used to map each point on the maps, and a logistic regression model to study the relationships between liking and disliking with interviewee characteristics. As results, (1) it has been possible to obtain those elements or spaces that are liked and disliked in proportion graphs and in planimetry. (2) Explanatory analysis of liking and disliking through the logistic regression model and inference to study significant characteristics. It emphasizes that "frequency of visits" is the significant characteristic for the elements and spaces that dislike. It's concluded that the study carried out provides objective tools to obtain the opinion of people and it's useful seen it in planimetry. Also, could be establish priorities to urban authorities about improve and intervention on elements or spaces that people judge because they are liking or disliking.

The study examines malnutrition's triple burden, including anaemia, overweight, and stunting, among children aged 6-59 months. Using data from the National Family Health Survey-5 (2019-21), the study identifies risk factors and assesses the contribution at different levels to existing malnutrition burden. A random intercept multilevel logistic regression model and spatial analysis are employed to identify child, maternal, and household level risk factors for stunting, overweight, and anaemia. The study finds that 34% of children were stunted, 4% overweight, and 66% anaemic. Stunting and anaemia prevalence were higher in central and eastern regions, while overweight was more prevalent in the north-eastern and northern regions. At macro-level, the coexistence of stunting, overweight, and anaemia circumstantiates the triple burden of childhood malnutrition with substantial spatial variation (Moran’s I: stunting-0.53, overweight-0.41 and anaemia-0.53). Multilevel analysis reveals that child, maternal, and household variables play a substantial role in determining malnutrition burden in India. The nutritional health is significantly influenced by a wide range of determinants, necessitating multilevel treatments targeting households to address this diverse group of coexisting factors. Given the intra-country spatial heterogeneity, the treatment also needs to be tailor-made for various disaggregated levels.

Human papillomavirus (HPV) infection is a widespread sexually transmitted infection linked to various types of cancers. Although vaccination against HPV is available, global HPV vaccination rates remain low. This study aimed to evaluate the awareness and knowledge of the HPV vaccine and to identify predictors associated with vaccine hesitancy among health college students in Saudi Arabia. A cross-sectional survey was distributed to students enrolled in health colleges. The association of vaccine hesitancy with sociodemographic characteristics was examined using logistic regression analysis. The study found that approximately half of the students (49.9%) were aware of the HPV vaccine. Students from the College of Medicine showed the highest level of knowledge. Only a small proportion (5.2%) reported receiving the vaccine. The overall HPV vaccine hesitancy was 59.1% (43.9% for women and 75.9% for men). The most common reasons for vaccine hesitancy was not knowing enough about it. Men were twice as likely as women to believe that they did not need the HPV vaccine. The odds for HPV vaccine hesitancy were greater among men and younger age group compared to women and older age group. In conclusion, the study underscores the importance of awareness campaigns on HPV vaccination, targeting primarily male students.