This study compares the Melbourne Decision-Making Questionnaire (MDMQ) and the General Decision-Making Style (GDMS), two of the most widely used decision-making questionnaires in the literature, in a large age- and sex-weighted general population sample of 714 men (45.7%) and 848 women (54.3%) between 18 and 90 years old. The objective was to evaluate the convergent and construct validity between several aspects of decision-making styles questionnaires. The results indicate that the two questionnaires replicate the factorial structure of four and five factors reported in the original studies respectively, through exploratory and confirmatory procedures in our cross-cultural context. The domains of both questionnaires that represent a strong or large correlation are Vigilance with Rational (.50), Hypervigilance, Buck-passing, and Procrastination with Avoidant (.45, .52 and .60). A Structural Equations Model (SEM) between both questionnaires indicates that both latent factors formed by the domains of the MDMQ and the GDMS obtain a correlation of .96. It is concluded that the two questionnaires measure similar aspects of the decision-making construct.

This study presents the complexity and sensitivity of chaotic system dynamics in the case of the double pendulum. It applied detailed numerical analyses of the double pendulum in multiple computing platforms in order to demonstrate the complexity in behavior of the system of double pendulums. The equations of motion were derived from the Euler-Lagrange formalism, in order to capture the system's dynamics, which is coupled nonlinearly. These were solved numerically using the efficient Runge-Kutta-Fehlberg method, implemented in Python, R, GNU Octave, and Julia, while runtimes and memory usage were extensively benchmarked across these environments. Time series analyses, including the calculation of Shannon entropy and the Kolmogorov-Smirnov test, quantified the system's unpredictability and sensitivity to infinitesimal perturbations of the initial conditions. Phase space diagrams illustrated the intricate trajectories and strange attractors, as further confirmation of the chaotic nature of the double pendulum. All the findings have a clear indication of the importance of accurate measurements of the initial condition in a chaotic system, contributing to an increased understanding of nonlinear dynamics. Future research directions are faster simulations using Numba and GPU computing, stochastic effects, chaotic synchronization, and applications in climate modeling. This work will be useful for understanding chaos theory and efficient computational approaches in complex systems of dynamical nature.

Scheduling and optimization have a central place in the research area of computing because it is increasingly important to achieve fully automated production processes to adjust manufacturing systems to the requirements of Industry 4.0. In this paper, we demonstrate how an automated wet-etch scheduling problem for a semiconductor industry can be solved by constraint answer set programming (CASP) and, its solver called clingcon. The considered scheduling problem includes a robot for lot transfers between the baths. CASP is a hybrid approach in automated reasoning that combines different research areas such as answer set programming, Constraint Processing and Satisfiability Modulo Theories. For a long time, exact methods such as constraint programming have displayed difficulties in solving real large-scale problem instances. Currently, the performance of state-of-the-art constrains solvers is comparatively better than a decade ago, and some complex combinatorial problems can be optimally solved. These theoretical and technical achievements open new horizons for declarative programming applications such as logistics. A successful solution to this problem is achieved and we found that in most cases tested, CASP is faster and obtains in most cases similar makespan values than solutions based on mixed integer linear programming and constraint paradigms.

Thyroid hormones are essential for regulating the metabolic rate, growth, development, and maintenance of many physiological processes in vertebrates. They are synthesized by the thyroid gland, which is an ancient organ that evolved early in vertebrate evolution. This study aims to characterize the evolutionary path of polymorphic variants associated with the hypothalamus-pituitary-thyroid (HPT) axis by comparing ancient DNA (aDNA) sequences of Late Pleistocene-Holocene hominin populations with those of modern humans. We evaluated the genetic sequences of several populations, including Neanderthals, Denisovans, Palaeolithic hunter-gatherers from European Russia and Sunghir, and Neolithic hunter-gatherers/farmers from Anatolia focusing on genes involved in the development of the thyroid gland and thyroid hormone (TH) biosynthesis, secretion, and transport. Results showed interesting variants in the DIO2 (rs225014), TPO (rs4927611), and TG (rs2069556 and rs1133076) genes. All SNPs seemed to confirm that Neanderthals, and in part Denisovas, were physiologically hypothyroidic. Probably they had lower T3 levels due to defective production or peripheral conversion. From the moment that the most favourable alleles in terms of T3 production appear during the Paleolithic, we are inclined to assume that their selection was linked to environmental pressure.Our study supports insight into the evolutionary history of the endocrine system and can help in providing understanding into the evolution of physiological systems and their adaptation to changing environments. Understanding the evolution of thyroid hormones can also shed light on the mechanisms underlying thyroid disorders in humans.

Calicioids form a research field that has encompassed ascomycetous fungi with stalked ascomata similar to those of the lichen genus Calicium. Early generic circumscriptions in calicioid lichens and fungi were mainly based on morphological and secondary chemistry information. After the introduction of molecular data, taxonomy in the group has been reconsidered. Here, based on a broad geographical sampling, Coniocybe Ach. was revised using molecular and morphological features. Three loci (ITS, LSU and rpb1) were compared to infer its phylogenetic position, and a total of 52 new sequences (14 ITS, 24 LSU and 14 rpb1) were produced. Coniocybe was revised and emended to include, apart for its type C. furfuracea, also C. brachypoda and C. confusa. In addition, a new species Coniocybe eufuracea, was described, and a key to the species of Coniocybe provided.

Currently, agro-industrial residues have been used to obtain bioactive compounds. The fermentation process is an alternative for the use of these residues and to be able to accumulate metabolites that may be of interest to different industrial sectors. The aim of this study was to evaluate solid-state fermentation conditions using pineapple waste as substrate with Aspergillus niger spp., to release polyphenolic compounds using a Plackett-Burman exploratory design. Temperature, humidity, inoculum, NaNO3, MgSO4, KCl and KH2PO4 conditions in the fermentation process were evaluated. The results revealed that the Aspergillus niger HT3 strain reached a hydrolyzable tannins accumulation of 10.00 mg/g, while Aspergillus niger Aa20 reached a condensed tannins release of 82.59 mg/g. The KH2PO4 affect the release of condensed tannins with A. niger Aa20 and MgSO4 affect the release of hydrolyzable tannins with A. niger HT3. In addition, a positive antioxidant activity was demonstrated for the DPPH, ABTS and FRAP technique. The HPLC analysis was able to identify compounds in the fermented pineapple peel such as 3-feruloylquinic acid, caffeic acid, lariciresinol and 3-hydroxyphloretin 2'-O-xylosyl-glucoside, among others. The solid-state fermentation process is a biotechnological alternative for the release of bioactive compounds.

Systemic hypertension is not a recognized association in patients with transfusion depended thalassaemia. In patients with high cardio-vascular morbidity due to iron overload and pulmonary hypertension this previously unrecognized disease should not be overlooked.

This research focuses on exploring generalized electron emissions in one-dimensional conducting materials, specifically examining field emission and thermionic emission. Additionally, the study investigates one-dimensional thermal radiation. The current density is derived for both one-dimensional thermionic emission and one-dimensional field emission. A generalized current density in one dimension is devised, taking into account arbitrary accelerating fields and temperature conditions. The formula for the one-dimensional current density is depicted with accelerating field and temperature across various work function materials. The current is also represented as a function of both temperature and electric field for various temperatures.

Researchers have asserted that, as patients rely on external powerful sources to control their disorders, in addition to their own internal powers and virtues, examining their coping mechanisms can lead to a better understanding of the initiation and progression of chronic diseases and uncover potential opportunities to balance and enhance their psycho-spiritual well-being and possibly their treatment and recovery. This review serves as a user’s manual for investigators who choose to use the CSI-SF to conduct their research on coping behaviors. The CSI-SF that measures four coping strategies based on 16 items was first assessed using the Jackson Heart Study (JHS) cohort in 2007. The reliability and construct validity of the CSI-SF was also later assessed among hemodialysis patients across 13 countries. In this study, the CSI-SF was assessed to be a reliable and valid instrument for measuring coping strategies. The CSI-SF serves the purpose of developing an inner voice that can assist with understanding how people cope with everyday life. The information gathered from administration of the CSI-SF can inform investigators about environmental cues and triggers that can also impact individual health.

Lead-acid batteries utilised in electrical substations release hydrogen and oxygen when these are charged. These gases could be dangerous and cause a risk of fire if they are not properly ventilated. Therefore, this research seeks to design and implement a network control panel for heating, ventilation, and air-conditioning systems (HVACS). This is done using a specific range of controllers, which have more than thirty loops of proportional, integral and derivative (PID) control to achieve a cost-effective design. It performs the required function of extracting hydrogen, oxygen, and maintaining the desired temperature of the battery storage room within the recommended limits (i.e. 25°C ±1°C tolerance) without compromising quality as set out in the user requirement specification in Appendix-A. The system control panel allows the user to access control parameters such as changing temperature set-points, fan-speed, sensor database amongst others. The hardware is configured to detect extreme hydrogen and oxygen gas content in the battery room and ensure that the HVACS extract the gas content to the outside environment. The results of the system show that the network control panel effectively operates as per the recommended system requirements. Therefore, the effective operation of the HVACS ensures sufficient gas ventilation, thus mitigating the risk of fire in a typical battery storage room. Furthermore, the effective operation of HVACS enhances battery lifespan because of regulated operating temperature, which is conducive to minimise the effect of sulfation in lead acid Batteries (LABs).

This study explores the impact of regular physical exercise on the quality of life and body image among Para-athletes, emphasizing the necessity of such activities for physical, social, and psychological health. This qualitative study employs content analysis and ethnomethodology to evaluate seven Para-athletes from the Navy's Paralympic Project, using focus group interviews to assess their perceptions. The findings reveal that participation in structured sports programs positively influences body image and quality of life, leading to improved performance in training, social interactions, and competitive events. The analysis suggests that motivation and self-esteem are fundamental to the sporting success of Paralympic athletes. Both external and internal motivations are crucial for sustaining athletic careers and overcoming challenges. Self-esteem enables athletes to remain confident in their abilities, even after setbacks.

The discovery of the quantum tunnelling effect---the transmission of particles through a high potential barrier---was one of the most impressive achievements of quantum mechanics made in the 1920s. Responding to the contemporary challenges, I introduce a novel deep neural network (DNN) architecture that processes information using the effect of quantum tunnelling. I demonstrate the ability of the quantum tunnelling DNN (QT-DNN) to recognise optical illusions like a human. Hardware implementation of QT-DNN is expected to result in an inexpensive and energy-efficient neuromorphic chip suitable for applications in autonomous vehicles. The optical illusions recognition tests developed in this paper should lay foundations for cognitive benchmarking tasks for AI systems of the future, benefiting the fields of sociophysics and behavioural science.

This paper explores the relationships between marketing strategies, social media platforms, the adoption and diffusion of products and services, and organizational resilience to gain an understanding of the ability of organizations to cope with disruptive events (e.g., COVID-19). This can be achieved through effective marketing strategies and the efficient use of social media platforms. In fact, resilience thinking can help organizations maintain their operations by increasing the adoption and diffusion of their products and services through the use of effective marketing strategies. To achieve this article’s objectives, a literature review is conducted to help develop a conceptual framework that highlights a clear relationship between the previously discussed concepts. In addition, the novel nature of the relationship between marketing strategies and organizational resilience is dissected and its significance for organizations is demonstrated. In fact, the findings of this study suggest that effective marketing strategies that consider the "what," "who," and "how" dichotomies and the efficient use of social media to promote the adoption and diffusion of products and services can significantly enhance the resilience of organizations. These relationships can serve as a starting point for further studies examining and empirically analyzing marketing strategies and their positive effect on strengthening organizational resilience.

Introduction: Senescence-resembling alterations on lymphocytes of dialysis patients have been widely described. However, pathophysiology behind these phenomena has not been clarified. In this study, we examine the impact of dialysis prescription and residual renal function on T and B lymphocytes, in dialysis patients. Methods: T and B cell subsets were determined with flow cytometry in 36 hemodialysis and 26 hemodiafiltration patients, according to the expression of CD45RA, CCR7, CD31, CD28, CD57 and PD1 for T cells, and IgD and CD27 for B cells. Immune phenotype was associated with dialysis modality, hemofiltration volume, and mortality. Results: Compared to hemodialysis, hemodiafiltration patients had significantly decreased percentage of CD4+CD28-CD57- T cells [3.8(2.4-5.3) vs 2.1(1.3-3.3)%, respectively, P=0.002] and exhausted CD4+ T cells [14.1(8.9-19.4) vs 8.5(6.8-11.7)% , respectively, P=0.005]. Additionally, hemofiltration volume was negatively correlated to CD8+ EMRA T cells (r=-0.46, P=0.03). Finally, exhausted CD4+ T cells percentage could predict all-cause mortality in dialysis patients, independently of age. Conclusion: Hemodiafiltration, especially with high hemofiltration volume, may have beneficial effects on senescence-related immune phenotype. Immune phenotype may also be a predicting factor for mortality in dialysis patients.

Piscine lactococcosis is a disease caused by Lactococcus garvieae, L. petauri and L. formosensis. It is considered to be an emerging disease and poses a risk to global aquaculture production. Studies of the genetic diversity of Lactococcus spp. strains have epidemiological importance since they provide information on the genetic relationships between isolates and indicate geographic and temporal distribution. The aim of this study was to evaluate the genetic diversity of Brazilian Lactococcus spp. isolates obtained from native fish species using PCR-based DNA fingerprinting techniques. For this, 36 isolates were selected and submitted to gyrB sequencing, molecular serotyping, REP-, BOX-, and RAPD-PCR approaches. The discriminatory power and the congruence between the typing methods were calculated. After the correct taxonomic discrimination of the isolate, a total of 14, 5 and 17 isolates were reclassified as L. garvieae, L. formosensis and L. petauri, respectively. L. garvieae and L. petauri are related to serotype I, while L. formosensis strains were classified as serotype II. The typing methods tested are useful for evaluating the genetic diversity of isolates and a comprehensive indication of the diversity was found. Heterogeneous and homogeneous populations were observed for L. garvieae and L. petauri, respectively. RAPD-PCR demonstrated a greater discriminatory power for L. formosensis and L. petauri, while REP-PCR showed better results for L. garvieae strains, thus these methodologies are recommended for genotyping these bacterial species. In conclusion, Brazilian isolates of Lactococcus spp. obtained from native fish species constitute a genetically diverse population and the techniques used in this study allowed a better genetic characterization of the isolates.

A 23-month-old neutered male dog of unknown ancestry presented with a history of progressive neurological signs that included anxiety, cognitive impairment, tremors, seizure activity, ataxia, and pronounced visual impairment. The clinical signs were accompanied by global brain atrophy. Due to progression in the severity of disease signs, the dog was euthanized at 26 months of age. Examination of tissues collected at necropsy revealed dramatic intracellular accumulations of autofluorescent inclusions in the brain, retina, and cardiac muscle. The inclusions were immunopositive for subunit c of mitochondrial ATP synthase, and their ultrastructural appearances were similar to those of lysosomal storage bodies that accumulate in some of the neuronal ceroid lipofuscinosis (NCL) diseases. The also dog exhibited widespread neuroinflammation. Based on these findings, the dog was deemed likely to have suffered from a form of NCL. A whole genome sequence analysis of the proband’s DNA revealed a homozygous C to T substitution that altered the intron 3 – exon 4 splice site of CLN6. Other mutations in CLN6 cause NCL diseases in humans and animals including dogs. CLN6 protein was undetectable with immunolabeling in the tissues of the proband. Based on the clinical history, fluorescence and electron-microscopy, immunohistochemistry, and molecular genetic findings, the disorder in this dog is classified as an NCL resulting from the absence of CLN6 protein. Screening the dog’s genome for a panel of breed-specific polymorphisms indicated that its ancestry included numerous breeds, with no single breed predominating. This suggests that the CLN6 disease variant is likely to be present in other mixed breed dogs and at least some of the ancestral breeds.

This research aims to explore factors that influence sustainable music education from a psychological perspective, and innovatively constructs a combination of qualitative and quantitative approaches. For first time, combines stochastic nonlinear system of control theory and identifies relevant factors affecting sustainable music learning by establishing a data system for questionnaire answering and a quantitative model for actual academic performance. Existing research mainly looks at several factors that affect fragmented music education from perspective of teachers' teaching rules, emphasizing phased teaching state and learning goals of teachers as main body, thus ignoring sustainable music education and students, who are a large group of music learning objects. The research fills gap in this type of research object, focusing on sustainable music education from an emotional perspective and students who occupy a dominant position in music learning, so as to more accurately explore impact of their emotional influencing factors on sustainable music learning. The most prominent innovation of this study lies in construction of stochastic nonlinear system for psychological influencing factors of sustainable student music learning and a quantitative model for actual learning effect. Through analysis of nonlinear system, weight values of several negative emotions on sustainable music learning are obtained.

In recent times, there has been significant enthusiasm for the development of all solid state batteries. This interest stems from a dual focus on safety—addressing concerns related to toxic and flammable organic liquid electrolytes—and the pursuit of high energy density. \cite{SCHNELL2018160,Zheng2018}. While liquid electrolyte batteries constitute for now the vast majority of commercial cells, solid electrolyte batteries show great promise. In parallel with experimental research, computational models \cite{GrazioliEtAlCM2016} clarify the several fundamental physics \cite{LiMonroeARCBM2020} that take place throughout battery operations. We review some classical models, emphasizing the conceptual advancements documented in the most recent works.

In this paper, a new full-Newton step feasible interior point method for convex quadratic programming is presented and analyzed. The idea behind this method is to replace the complementarity condition with a non-negative variable weight vector and use the algebraic equivalent transformation for the obtained equation. Under the selection of appropriate parameters, the quadratic rate of convergence of the new algorithm is established. In addition, the iteration complexity of the algorithm is obtained. Finally, some numerical results are presented to demonstrate the practical performance of the proposed algorithm.

Cervical cancer is caused by a persistent and high-grade infection, caused by the Human Papilloma Virus (HPV), which, when entering cervical cells, alters their physiology and generates serious lesions. HPV 18 - is among those most involved in carcinogenesis in this region, but there are still no drug treatments that cause cure or total remission of lesions caused by HPV. Knowing that L-Asparaginase is an amidohydrolase, which plays a significant role in the pharmaceutical industry, particularly in the treatment of specific cancers, due to its antitumor properties, some studies have demonstrated its cytotoxic effect against cervical cancer cells. However, the commercial version of this enzyme has side effects, such as hypersensitivity, allergic reactions and silent inactivation due to the formation of antibodies. To mitigate these adverse effects, several alternatives have been explored, including the use of L-asparaginase from other microbiological sources, which is the case with the use of the fungus Aspergillus niger, a high producer of L-asparaginase. The study investigated the influence of the type of fermentation, precipitant, purification, characterization and in vitro cytotoxicity of L-asparaginase. The results revealed that semisolid fermentation produced higher enzymatic activity and protein concentration of A. niger. The characterized enzyme showed excellent stability at pH 9.0, temperature of 50ºC, resistance to surfactants and metallic ions, and an increase in enzymatic activity was also noted with the organic solvent ethanol. Furthermore, it exhibited low cytotoxicity in GM and RAW cells, and significant cytotoxicity in HeLa cells. These findings indicate that L-asparaginase derived from Aspergillus niger may be a promising alternative for pharmaceutical production. Its attributes, including stability, activity and low toxicity in healthy cells, suggest that this modified enzyme could overcome challenges associated with antitumor therapy.

Nano surface finishing can be achieved from the recently developed electrophoretic deposition-assisted polishing (EPDAP) process. This state-of-art work presents a comparison of the effect of surface roughness and material removal rate on the grit size, axial load, rotational speed, polishing time, etc. for SS304, SS316L and alumina ceramics. The EPDAP process can assess the surface's characteristics' quantity, and quality on different materials which have been tried on SS316L, SS304, inner bore of SS304, and Al2O3 in our laboratory. Uniform dispersion of homogeneous micro-sized abrasive grains was accomplished by electrophoretic deposition (EPD) to create the polishing tool employed in this process. Polishing time, axial loading, grit size, and speed of rotation of the polishing tool was selected as the control parameters. The polishing tool undergoes erosion of blunt-edged-abrasive grains due to abrasion during the EPDAP process. Therefore, the polishing tool was continuously revitalized by adding fresh abrasives. The analysis of the experiments is conducted using ANOVA and the evolutionary algorithm teaching-learning method. EPDAP process revealed improved surface reflection as well as improvement in surface finish. Thus, optimization of the polishing parameters was conducted for the experiments. The surface roughness achieved from the experiments is 0.04557 microns for SS316L, 0.038 microns for SS304, and 0.404 microns for Al2O3. Therefore, 93.92%, 97.64 %, and 73.75 % of improvement in the surface finish were achieved in SS316L, SS304, and Al2O3, respectively.

Background and Objectives: The trends in metabolic dysfunction-associated steatotic liver disease (MASLD) and related metabolic dysfunctions in Japan is unknown. Thus, we aimed to clarify the trends of these before the novel coronavirus disease 2019 pandemic in Japan. Materials and Methods: We included Japanese individuals aged 25-79 years who underwent health examinations at our center. We analyzed anthropometry, lifestyle-related disease, and nutritional intake in relation to MASLD trends from 2010-2019. Results: The prevalence of MASLD increased in all ages and body mass index (BMI) classes, reaching 30.3% in males and 16.1% in females, with MASLD accounting for 75% of steatotic liver cases and more than half of all type 2 diabetes mellitus (T2DM) and high waist circumference (HWC) cases. The increase in the prevalence of MASLD was due to an increase in that of steatotic liver itself, and there was no increase in the prevalence of other factors, such as overweight, T2DM, hypertension, and dyslipidemia. The prevalence of glucose metabolic disorders (GMDs) and hypertension decreased. National nutritional data showed an increase in energy intake, total fat, saturated fatty acids, monounsaturated fatty acids, and polyunsaturated fatty acids, which correlated with a decrease in GMDs. Salt intake also decreased, which correlated with hypertension. The MASLD group had a higher prevalence of all related metabolic factors than the non-MASLD group, especially HWC, T2DM, and hyperlipidemia. Conclusion: The prevalence of MASLD increased with that of steatotic liver, regardless of age or BMI. A relationship between increased dietary fat, increased steatotic liver, and decreased GMDs was suggested.

Glioblastoma (GBM) is an aggressive brain cancer characterized by significant molecular and cellular heterogeneity, complicating treatment efforts. Current standard therapies, including surgical resection, radiation, and temozolomide (TMZ) chemotherapy, often fail to achieve long-term remission due to tumor recurrence and resistance. A pro-oxidant environment is in-volved in glioma progression, with oxidative stress contributing to the genetic instability that leads to gliomagenesis. However, the generation of reactive oxygen species (ROS) results in the dysregulation of antioxidant defenses in GBM cells, creating a vulnerability that can be thera-peutically exploited. Evaluating pro-oxidant therapies in brain tumors is crucial due to their po-tential to selectively target and eradicate cancer cells by exploiting the elevated oxidative stress levels inherent in these malignant cells, thereby offering a novel and effective strategy for overcoming resistance to conventional therapies. This study investigates the therapeutic potential of doxorubicin (DOX) and photodynamic therapy (PDT) with Me-ALA, focusing on their effects on redox homeostasis. Basal ROS levels and antioxidant gene expression (NFE2L2, CAT, GSR) were quantitatively assessed across GBM cell lines, revealing significant variability probably linked to genetic differences. DOX and PDT treatments, both individually and in combination, were ana-lyzed for their efficacy in inducing oxidative stress and cytotoxicity. An in silico analysis further explored the relationship between gene mutations and oxidative stress in GBM patients, providing insights into the molecular mechanisms underlying treatment responses. Our findings suggest that pro-oxidant therapies, such as DOX and PDT in combination, could selectively target GBM cells, highlighting a promising avenue for improving therapeutic outcomes in GBM.

Previous research on consumer perceptions of salmon has often neglected Indigenous rights within the Canadian salmon industry. This study acknowledges the decline in salmon farm licenses in British Columbia and aims to achieve three main objectives: (1) gain a comprehensive understanding of four consumer perceptions—environmental sustainability, economic considerations, Indigenous rights, and price increase—across diverse consumer profiles through a cross-national online survey; (2) identify factors influencing these four consumer perceptions; and (3) assess the impact of these perceptions, along with socio-demographic variables and consumer motivations, on seven purchasing behaviors related to Canadian salmon products. Data analysis employs the graded response model and cumulative link models. The results illustrate how consumer profiles influence the four perceptions and their key determinants. Additionally, the study quantifies the impact of environmental sustainability, economic considerations, Indigenous rights, and a price increase on consumer purchasing behaviors.

In this study, the causal-effect between carbon dioxide emissions and forestry production and trade was investigated in Ghana by employing a data spanning from 1961 to 2014 by using the VECM and ARDL model. Evidence of the long-run equilibrium relationship in the VECM shows that, a 1% increase in veneer sheet production reduces carbon dioxide emissions by 1.47% in the long-run. There was evidence of a bidirectional causality between carbon dioxide emissions and veneer sheet production, carbon dioxide emissions and wood charcoal production, and a unidirectional causality running from carbon dioxide emissions to wood fuel production and plywood production to carbon dioxide emissions. Evidence from the long-run equilibrium relationship in the ARDL model shows that; a 1% increase in plywood production will increase carbon dioxide emissions by 0.17% in the long-run, a 1% increase in sawnwood production will increase carbon dioxide emissions by 0.17% in the long-run, a 1% increase in wood charcoal production will increase carbon dioxide emissions by 0.36% in the long-run and a 1% increase in wood fuel production will increase carbon dioxide emissions by 0.37% in the long-run.

The legume-rhizobia symbiosis is one of the most important plant-microbe interactions in sustainable agriculture due to its ability to provide much needed N to cropping systems. This interaction is mediated by the mutual recognition of signaling molecules from the two partners, namely legumes and rhizobia. With legumes, these molecules are in the form of flavonoids and anthocyanins, which are responsible for the pigmentation of plants parts, such as seeds, flowers, fruits and even leaves. Seed coat pigmentation in legumes is a dominant factor influencing gene expression relating to N2 fixation, and may be responsible for the different N2-fixing abilities observed among legume genotypes under field conditions in African soils. Cowpea, Kersting’s bean and Bambara groundnut landraces with black seed coat color are reported to release higher concentrations of nod-gene-inducing flavonoids and anthocyanins when compared to the Red and Cream landraces, hence the black seed coat pigmentation is considered a biomarker for enhanced nodulation and N2 fixation. Cowpea, Bambara groundnut and Kersting’s bean with differing seed coat colors are known to attract different native soil rhizobia, confirmable by PCR-RFLP analysis of bacterial DNA from root nodules of these legumes. Even when seeds of the same legume with diverse seed coat colors were planted together in one hole, the nodulating bradyrhizobia clustered differently in the PCR-RFLP dendrograms. In one study, Kersting’s groundnut, Bambara groundnut and cowpea with differing seed coat colors were selectively nodulated by different bradyrhizobial species. Multilocus sequence analysis showed that different Bradyrhizobium species nodulated the Kersting's bean based on seed coat color. Phylogenetic analysis also placed the bradyrhizobial isolates in close proximity to different Bradyrhizobium species such as B. vignae 7-2T, B. subterraneum 58 2-1T, B. kavangense 14-3T, B. liaoningense 2281 (USDA 3622)T, B. yuanmingense LMG 21827T, B. huanghuaihaiense CCBAU 23303T, B. pachyrhizi PAC48T, and a reference type strain of B. elkanii according to seed coat color. Using 16S rDNA amplicon sequencing, we also found significant selective influences of seed coat pigmentation on microbial community structure in the rhizosphere of five Kersting’s groundnut landraces. For example, the rhizosphere of Belane Mottled landrace was dominated by Proteobacteria, while Bacteroidetes dominated the rhizospheres of the other landraces. With legumes, seed coat pigmentation therefore plays a dominant role in the selection of the bacterial symbiotic partner.

To advance probiotic research, a comprehensive understanding of bacterial interactions with human physiology at the molecular and cellular levels is fundamental. Lacticaseibacillus rhamnosus LGG® is a bacterial strain that has long been recognized for its beneficial effects on human health. Probiotic effector molecules derived from LGG®, including secreted proteins, surface-anchored proteins, polysaccharides, and lipoteichoic acids, that interact with host physiological processes have been identified. In vitro and animal studies have revealed that specific LGG® effector molecules stimulate epithelial cell survival, preserve intestinal barrier integrity, reduce oxidative stress, mitigate excessive mucosal inflammation, enhance IgA secretion, and provide long-term protection through epigenetic imprinting. Pili on the cell surface of LGG® promote adhesion to the intestinal mucosa and ensure close contact to host cells. Extracellular vesicles produced by LGG® recapitulate many of these effects through their cargo of effector molecules. Collectively, the effector molecules of LGG® exert a significant influence on both the gut mucosa and immune system, that promotes intestinal homeostasis and immune tolerance.

Purpose To compare and adjust activated clotting time (ACT) between two systems and to optimize ACT during atrial fibrillation (AF) ablation. Methods Electromagnetic detection using a rotation tube (EM system; Hemochron Response, Soma Tech Intl, Bloomfield, CT, USA) and photo-optical detection using a cartridge immersed in blood (PO system; ACT CA-300TM, APEL) were compared. Results The EM system showed an ACT of 320 ± 44 s (average ± 1 standard deviation), with a range of 156–487 s, from 3363 measurements in 1161 patients during uncomplicated procedures. An ACT >400 s was observed in 3.7% (124/3364) of patients. The pre-ablation ACT measured by the EM method was 143 ± 28 s. Cardiac tamponade was observed in 4/2085 ablations (0.19%) over 5 years. The ACT associated with cardiac tamponade ranged from 330 to 391 in the EM system. The regression equation was ACT-EM system = 1.19 × ACT-PO system + 9.03 (p

Acne Vulgaris is a multifactorial skin disorder affecting many adolescents involving a complex array of factors. Previous extensive research has delved into the correlation between acne outbreaks and specific diet consumption, and while there have been a variety of treatment indications for decreasing acne in patients, many do not involve the significant impact a holistic approach can take. This case reports on the relationship between cystic acne and dietary habits, presenting a possible treatment approach for acne vulgaris by eliminating dairy consumption.

Background: Endoscopic sphincterotomy (EST) has been employed for the endoscopic treatment of common bile duct stones (CBDSs), and a high success rate of stone removal has been reported. However, EST is associated with the risk of bleeding, perforation, and sphincter of Oddi function disruption. To avoid these risks, endoscopic papillary balloon dilation (EPBD) is an option for CBDS. Sphincter of Oddi function preservation decreases long-term biliary infection and gallstone recurrence. EPBD may have advantages in children who require a long follow-up. However, there have been few reports on pediatric cases, particularly in infants. Methods: From September 2017 to December 2023, we performed EPBD for four pediatric CBDSs. The patients were aged from 5 months to 8 years; including two infants aged 5 and 6 months. Furthermore, we reviewed the stone removal rate and complications of 545 ESTs performed at high-volume centers and 13 EPBD-reported cases in children with CBDSs. Results: CBDSs of all patients who underwent EPBD in our institution were successfully removed. No bleeding or perforation was noted, and pancreatitis was observed in three patients. In an analysis of 545 ESTs in children, the stone removal rate was high, ranging from 83% to 100% (mean, 96%). The incidence of pancreatitis was 0%–9.6% (mean, 4.4%), and the grade of pancreatitis was almost mild. The bleeding frequency was 1.3%–5.4% (mean, 2.7%). According to the grade of bleeding, seven and four cases were mild (64%) and moderate (36%), respectively, Compared with adult cases who underwent EST, the frequency of pancreatitis and bleeding was almost similar in children.; however once bleeding occur, it has a higher risk of leading to blood transfusion in children. Stone removal by EPBD in children was 100% successful. All complications were pancreatitis, and its frequency was 46% (6/13 patients, including five mild cases and one moderate case), which is higher than that of EST and adult cases who underwent EPBD. In most children with pancreatitis, pancreatic enzyme levels returned to normal within 2–3 days following EPBD, and no severe cases caused by EPBD were reported. Conclusions: CBDS removal by EPBD in children has a high success rate with very low risk of bleeding and perforation. Although pancreatitis frequently occurs, most cases are mild. Sphincter of Oddi function preservation by EPBD is expected to prevent long-term stone recurrence and biliary tract infection, and EPBD is considered an effective method for CBDS removal in children.

Potential permanent magnet (Fe0.7Co0.3)2B has large saturation magnetization and high Curie temperature but a moderate magnetocrystalline anisotropy (MCA) and displays relatively low coercivity. One way to improve coercivity is to combine the contribution from magnetocrystalline- and magnetic shape anisotropy by preparing (Fe0.7Co0.3)2B nanowires. We study the effect of size, morphology, and surface defect on the hard magnetic properties of nanowires using micromagnetic simulation. The hard magnetic properties of (Fe0.7Co0.3)2B nanowire bonded magnet have been estimated, including the role of inter-wire magnetostatic interaction. By considering the existence of local reduction of MCA energy up to 30% on the surface layer of nanowires, the anisotropic bonded magnet with 65% vol. of (Fe0.7Co0.3)2B nanowires displays typical magnetic properties of remanence Br=8.4 kG, coercivity Hci=9.9 kOe, and maximum energy product (BH)m=17.8 MGOe. Developing effective technology for synthesizing nanowires and fabricating corresponding bonded magnets is promising for manufacturing practical magnets based on magnetic phase with relatively low or moderate MCA, such as (Fe0.7Co0.3)2B.

Excretory-secretory products (ESPs) are the main research targets for investigating the hosts and helminths interaction. Parasitic worms can migrate to parasitic sites and avoid the host immune response by secreting this product. Angiostrongylus cantonensisis an important food-borne zoonotic parasite that causes severe neuropathological damage and symptoms, including eosinophilic meningitis or meningoencephalitis in humans. Benzaldehydes are organic compounds composed of a benzene ring and formyl substituents. This compound has anti-inflammatory and antioxidation properties. Previous studies showed that 3-hydroxybenzaldehyde (3-HBA) and 4-hydroxybenzaldehyde (4-HBA) can reduce apoptosis in A. cantonensis ESPs treated astrocytes. These results on the protective effect underlying benzaldehyde have primarily focused on cell survival. The study was designed to investigate the molecular mechanisms of endoplasmic reticulum stress (ER stress) and oxidative stress in astrocytes in A. cantonensis ESPs treated astrocytes and to evaluate the therapeutic consequent of 3-HBA and 4-HBA. First, we initially established the RNA-seq dataset in each group, including Normal, ESPs, ESPs+3-HBA, and ESPs+4-HBA. We also found that benzaldehyde (3-HBA and 4-HBA) can stimulate astrocytes to express ER stress-related molecules after ESP treatment. The level of oxidative stress could also be decreased in astrocytes by elevating antioxidant activity and reducing ROS generation. These results suggested that benzaldehyde may be a potential therapeutic compound for human angiostrongyliasis to support brain cell survival by inducing the expression levels of ER stress- and oxidative stress-related pathway.

Sporotrichosis’ clinical manifestations, lesions in the cutaneous or subcutaneous tissues, it is caused by dimorphic fungi of the Sporothrix complex, is a cosmopolitan mycosis that affects humans and animals. This study aimed to identify prevalent species in Minas Gerais, Brazil, and characterize virulence profiles and antifungal susceptibility associated with Sporothrix isolates. Isolates were identified using macro and micro-morphological traits as well molecular biology techniques. Antifungal susceptibility was determined using the Minimal Inhibitory Concentration test, while, virulence factors such as growth at different temperatures, biofilm formation, melanin production, and urease activity were assessed. Our findings revealed S. brasiliensis as a predominant species isolated. Urease activity was a crucial factor associated with growth at 50°C in S. brasiliensis isolates, highlighting their high thermotolerance. Furthermore, strains isolated from humans produced a more robust biofilm compare to those from felines. Strains of S. brasiliensis isolated from Felis catus exhibited faster melanin production, decreased susceptible to antifungal agents tested, and superior growth capacity at 50°C to strains isolated from humans. Therefore, our study highlights the prevalence of S. brasiliensis causing sporotrichosis in both human and felines. However, it underscores the circulation of different strains, with varying levels of virulence and susceptibility to antifungal agents.

Financial market data analysts are increasingly turning towards machine learning techniques for data analysis and making decisions. This paper explores how knowledge graphs, essentially a network of real entities and their relationships, can be used to improve collaborative financial market data analysis and make it more efficient and user friendly. This paper reviews the current state of financial market data analysis, the challenges in deploying machine learning models in industrial environments, and the concepts such as ML-Ops and knowledge graphs. A software architecture comprising various roles, layers and services such as Data Engineers, Data Analysts, public users, APIs, workflows, analytics libraries, UX layer, Business Layer, etc. is introduced and described in detail. Then, it discusses how knowledge graphs can be used to enhance collaborative financial market data analysis. Finally, a case study is presented to demonstrate the usage of the whole system, within the context of financial market data analytics of equities.

Liver cancer imposes a pervasive global health challenge, ranking among the most prevalent cancers worldwide. Its prevalence and mortality rates are on a concerning upward trajectory and exacerbated by the dearth efficacious treatment options. The Hippo signaling pathway, originally discovered in Drosophila, comprises four core components: MST1/2, WW45, MOB1A/B, and LATS1/2. This pathway regulates the cellular localization of the transcriptional coactivator YAP/TAZ (Yes-associated protein/PDZ-binding motif) through a series of enzymatic reactions. The Hippo/YAP/TAZZ pathway maintains a balance between cell proliferation and apoptosis, regu-lates tissue and organ sizes, and stabilizes the internal environment. Abnormalities of any genes within the Hippo signaling pathway, such as deletion or mutation, disturb the delicate balance between cell proliferation and apoptosis, creating a favorable condition for tumor initiation and progression. Mutations or epigenetic alterations in the Hippo signaling pathway components can lead to its inactivation. Consequently, YAP/TAZ becomes overexpressed and activated, promoting excessive cell proliferation and inhibiting apoptosis. This dysregulation is closely associated with the development of liver cancer. This review discusses the pivotal role of the Hippo signaling pathway in the pathogenesis and progression of liver cancer. By elucidating its mechanisms, we aim to offer new insights into potential therapeutic targets for effectively combating liver cancer.

An online survey assessed the awareness of Nelson region’s residents, comparing responses between those who experienced the installation and those who did not. Findings indicated that eco-art installations can significantly enhance public understanding of ALAN's environmental and health impacts. The installation successfully increased specific knowledge about ALAN, with 92% of visitors reporting learning something new, however overarching knowledge and levels of concern were largely similar between the groups. Emotional engagement was high, with 62% of viewers stating that the installation invoked an emotional response. While the study did not measure behavioural changes, 94% of festival participants found it at least ‘somewhat appropriate’ and 64% ‘very’ or ‘entirely appropriate’ to raise awareness of these issues at such events, suggesting a potential foundation for future action. This research underscores the promise of art-science collaborations in environmental education and public engagement.

The present paper reports exact results for the muon self-energy and anomalous g-factor. A unique to the muon cut-off terms that remove the radial singularity in the system and regularize the corresponding electrodynamics are presented. Equations of motion and a transcendental equation satisfied by the muon anomalous g-factor are derived, with solution a_m=0.001165920162(198). The obtained value matches the latest experimental one found in the literature to about 0.43 ppb ruling out a possible tension between theory and experiment.

Introduction: Rural Americans face significant health disparities due to limited access to healthcare services. Telehealth has emerged as a promising solution to mitigate these disparities by facilitating remote access to medical care. This paper comprehensively reviews the advantages, challenges, and implementation strategies of telehealth in rural areas.Method: A narrative review methodology was employed to synthesize existing literature and case studies on telehealth in rural settings. Databases such as PubMed, Google Scholar, and JSTOR were searched for relevant studies published in the last three decades. Keywords such as "telehealth," "rural health," and "healthcare disparities" guided the search process. The review focused on studies assessing the impact of telehealth on healthcare access, cost-effectiveness, and quality of care in rural areas.Results: The review findings indicate that telehealth significantly enhances healthcare access by reducing travel distances, increasing availability of specialist consultations, and promoting patient engagement. It improves chronic disease management and patient satisfaction by enabling convenient access to healthcare services at home. Despite initial setup costs and challenges such as broadband access and regulatory issues, telehealth demonstrates long-term cost savings through reduced travel expenses and improved healthcare efficiency. Quality of care is enhanced through improved communication between healthcare providers and patients, leading to better treatment adherence and health outcomes.Conclusion: Telehealth represents a transformative approach to address healthcare disparities in rural areas. It offers a cost-effective solution to improve access to healthcare services, enhance patient outcomes, and reduce healthcare costs in the long run. However, successful implementation requires addressing infrastructure challenges, refining reimbursement policies, and ensuring regulatory support. Future efforts should focus on expanding broadband infrastructure, refining policy frameworks, and conducting further research to optimize telehealth's impact on rural healthcare delivery.

This paper presents the five-parameter Exponentiated Weibull Weibull (EWW) distribution with Weibull base failure rate parameterization, developed to model the dropout times of students in an online class module. Parameters of the model were estimated using both Maximum Likelihood and Bayesian estimation procedures to determine the most effective estimation method. Simulation results indicate that, across various hazard types and censoring levels, Bayesian estimates are more accurate and precise than Maximum Likelihood estimates. Real-life data analysis of online students module presentation supports these findings, showing significantly lower standard deviations for Bayesian estimates compared to Maximum Likelihood estimates, highlighting the efficiency of Bayesian estimation for the EWW distribution. Additionally, a comparative goodness-of-fit analysis demonstrated that the EWW distribution better fits the student dropout times dataset than Weibull Weibull (WW), Weibull Exponential (WE), and Exponential Weibull (EW) distributions. The median dropout time estimated using the EWW distribution is 24 days, suggesting that instructors should closely monitor student attendance around this period.

Cancer is a highly heterogeneous disease and remains a global health challenge affecting millions of human lives worldwide. Despite advancements in conventional treatments like surgery, chemotherapy, and immunotherapy, the rise of multidrug resistance, tumor recurrence, and severe side effects necessitates innovative therapeutic approaches. The complex nature of the tumor microenvironment (TME) further compromises the efficacy of traditional chemotherapy drugs. Recently, stimulus-responsive nanomedicines designed to target TME characteristics (e.g., pH, redox, enzymes) have gained attention for their potential to enhance anticancer efficacy while minimizing adverse effects. Among various nanocarriers, hydrogels are an interesting class of nanocarriers used in cancer therapy due to their high water content, adjustable mechanical characteristics, and ability to respond to external/internal stimuli. These properties make hydrogels an ideal nanocarrier for controlled drug release within the TME. This review comprehensively surveys the latest advancements in stimulus-responsive hydrogels for cancer therapy, exploring various stimuli-responsive mechanisms, including biological (e.g., pH, redox), chemical (e.g., enzymes, glucose), and physical (e.g., temperature, light), as well as dual- or multi-stimuli responsiveness. This review will offer novel perspectives on the development of stimulus-responsive hydrogels for cancer therapy.

We consider creation of entanglement between the remote electron spins using a magnetic nanoparticle attached to a cantilever tip (CT). We assume that the frequency of the CT vibrations matches the Larmor frequency of the spin (the CT-spin resonance). In the conditions of the CT-spin resonance the CT-spin system is described by the exactly solvable Jaynes-Kummings model. In this work using the evolution operator of the Jaynes-Kummings model we show that a movable CT can create an entangled state between the remote spins. The most striking result is that the entanglement between the remote spins can be achieved without measurement of the vibrational state of the CT.

Affinity reagents, or target-binding molecules, are quite versatile and are major workhorses in molecular biology and medicine. Antibodies are the most famous and frequently used type and they have been used for a wide range of applications, including laboratory techniques, diagnostics, and therapeutics. However, antibodies are not the only available affinity reagents and they do have significant drawbacks, including laborious and costly production. Aptamers are one potential alternative that have a variety of unique advantages. They are single stranded DNA or RNA molecules that can be selected for binding to many targets including proteins, carbohydrates, and small molecules – for which antibodies typically have low affinity. There are also a variety of cost-effective methods for producing and modifying nucleic acids in vitro without cells, whereas antibodies typically require cells or even whole animals. While there are also significant drawbacks to using aptamers in therapeutic applications, including low in vivo stability, aptamers have had success in clinical trials for treating a variety of diseases and two aptamer-based drugs have gained FDA approval. Aptamer development is still ongoing, which could lead to additional applications of aptamer therapeutics, including antitoxins, and combinatorial approaches with nanoparticles and other nucleic acid therapeutics that could improve efficacy.

A correlation of basic science and clinical symptoms in the human to propose a new theory for how the vestibular system works Neil S. Longridge Professor Emeritus, Division of Otolaryngology Department of Surgery, Faculty of Medicine, University of British Columbia Vancouver, BC CANADA *Arthur I. Mallinson, Clinical Associate Professor, Division of Otolaryngology Department of Surgery, Faculty of Medicine, University of British Columbia Vancouver, BC CANADA NS Longridge † *AI Mallinson † These authors contributed equally to this work. ABSTRACT; Bipedalism is unique among mammals. Until modern times, a fall and resulting leg fracture could be fatal. Balance maintenance after a destabilizing event requires instantaneous decision-making. The vestibular system plays an essential role in this process, initiating an emergency response. The afferent otolithic neural response is the first directionally oriented information to reach the cortex, and can then be used to initiate an appropriate protective response. Some vestibular efferent axons feed directly into the type I vestibular hair cells. This allows for rapid vestibular feedback via the striated organelle (STO), which has been largely ignored in most texts. We propose that this structure is essential in emergency fall prevention, and also that the system of sensory detection and resultant motor response works by having efferent movement information transmitted to the maculae simultaneously with the movement commands. This results in the otolithic membrane positioning itself precisely for the planned movement, and any error is due to an unexpected external cause. Error is fed back via the vestibular afferent system. The efferent system through the STO causes macular otolithic membrane movement which occurs simultaneously with the initiating motor command. As a result, no vestibular afferent activity occurs unless an error must be dealt with.

This paper presents a novel framework for Collaborative Learning Networks (CLNs) in classrooms, aiming to optimize resource utilization and enhance educational services. The study addresses the inefficiencies of traditional education models, particularly the underutilization of computational resources and limited access to specialized software. The proposed framework employs a mix of task-based and random allocation strategies to distribute computational tasks within the CLN, considering each device’s capabilities and task requirements. The findings show significant improvement in resource utilization, facilitated by device-to-device collaboration and task sharing, thus enriching students’ learning experiences. This work contributes to optimizing resource utilization in education, advancing the field of CLNs.

In the quest for robust and efficient digital communication, this paper introduces cutting-edge key exchange protocols leveraging tropical semirings’ computational prowess and block matrices’ structural resilience. Moving away from the conventional use of finite fields, these protocols deliver markedly faster processing speeds and heightened security. We present two implementations of our concept, each utilizing a different platform for the set of commuting matrices: one employing tropical polynomials of matrices and the other employing Linde-de la Puente matrices. The inherent simplicity of tropical semirings leads to a decrease in operational complexity, and using block matrices enhances our protocols’ security profile. The security of these protocols relies on the Matrix Decomposition Problem. We also provide a comparative analysis of our protocols against existing matrix block-based protocols in finite fields. This research marks a significant shift in cryptographic protocol design, specifically tailored for demanding engineering applications, and sets a new standard in secure and efficient digital communication.

A substantial spike in the need for quality healthcare has resulted from people being more cognizant of health issues. With blockchain, healthcare providers may safely share patient information electronically, which is especially important given the sensitive nature of the data contained inside them. However, flaws in the current blockchain design have surfaced since the dawn of quantum computing systems. The study proposes a novel quantum inspired blockchain system (Qchain) and constructs a unique entangled quantum medical record (EQMR)system with an emphasis on privacy and security. This Qchain relies on entangled states to connect its blocks. Automated production of the chronology indicator reduces storage capacity requirements by connecting entangled BloQ (blocks with quantum properties) with controlled activities. One qubit is used to store the hash value of each block. A lot of information regarding quantum internet is included in the protocol for the entangled quantum medical record (EQMR). EQMR can be accessed in Medical Internet of Things (M-IoT) systems may be kept private and secure, and their where-abouts can be monitored in the event of an emergency. The protocol also uses quantum authentication in place of more conventional methods like encryption and digital signatures. Mathematical research shows that the quantum converged blockchain (QCB) is highly safe against attacks such as the External attack, Intercept-Measure-Repeat attack, and Entanglement-Measure attack. The reliability and auditability evaluations of the entangled BloQ, as well as the quantum circuit design for computing the hash value, are presented. There's also a comparison between the suggested approach and several other quantum blockchain designs.

Trade-offs in ecosystem services (ES) manifest when the enhancement of one service leads to the diminishing of another. These trade-offs pose a notable challenge, impacting the sustainability of particular socio-ecological systems peri-urban landscapes (PULs). This issue arises from the dynamic processes associated with peri-urbanization, posing threats to natural ecosystems and their services in peri-urban areas. Additionally, the escalating demand for ecosystem services in PULs contributes to these trade-offs. Policy making and planning concerning ecosystem ES trade-offs in PULs should prioritize the promotion of a balance between conflicting services and foster synergies among them. However, it is noteworthy that ES trade-offs in PULs are not given high priority on policy and planning agendas. Knowledge regarding policy development and planning for ES trade-offs in PULs often remains concealed within specific country and regional case studies. Consequently, this research seeks to characterize the ES trade-offs in the selected PUL case studies, with the objective of identifying potential commonalities among them. Furthermore, the study aims to identify: (i) the factors driving ES trade-offs, (ii) challenges pertaining to how policy-making and planning address ES trade-offs in PULs, and (iii) recommendations for enhancing governance practices to better manage peri-urban ES trade-offs. We designed a semi-quantitative survey and collected information about 23 different case studies, located across the world. Answers from this survey were analyzed with the help of Principal Component Analysis approach. The results showed that the most common trade-off occurred between “cultural and provisioning” and “regulating and provisioning” ES. It was found that urban development is the basic driver behind emerging of the examined trade-offs. To tackle this issue at the governance level, the study recommends establishing mechanisms to facilitate collaboration among stakeholders. This should be accompanied by robust dissemination efforts and the promotion of awareness among actors regarding the fundamental concepts of ES and PULs.

Only a handful of microbial mosquito larval pathogens have been described to date. Sampling of several natural enzootic infections of mosquito larvae in southwestern Florida indicated the presence of microbial pathogens capable of extensive larval mortality. Microscopic analysis of one sample site revealed extensive apparent growth of a Pythium-like microbe on mosquito lar-vae, with highest infection observed on the siphon and head regions. Structures consistent with sporangia were seen on infected insects after lactophenol blue staining, and higher resolution scanning electron micrographs (SEM) showed sporangia and encysted zoospores targeting the head and siphon regions. The isolate was single colony purified and molecular identification targeting the ITS and COX1 loci coupled to phylogenetic reconstruction indicated that the isolate belonged to the Pythium genus, but was distinct from its closest characterized species, P. angusta-tum. Morphological features were characterized, with the isolate showing rapid growth on all mycological media tested and relatively high thermotolerance, capable of robust growth at 37oC, and hence was designated, P. thermoculicivorax. Sampling from a second series of natural infec-tions of mosquito larvae resulted in the molecular identification of three Trichoderma isolates, one with high similarity to T. strigosum, and the other two clustering with, but distinct from, T. asperellum. These data highlight the occurrence of natural enzootic infections of mosquito larvae, potentially as a resource for the identification of new mosquito pathogens.

Industry 4.0 is an industrial paradigm that is causing changes in form and substance in factories, companies and businesses around the world, and is impacting work and education in general. In fact, the disruptive technologies that frame the fourth industrial revolution have the potential to improve and optimize manufacturing processes and the entire value chain, which can lead to an exponential evolution in the production and distribution of goods and services. All these changes imply that the fields of engineering knowledge must be oriented towards the concept of Industry 4.0, for example Mechanical Engineering. The development of various physical assets that are used by cyber-physical systems and digital twins is based on Mechanics. However, the specialized literature on Industry 4.0 says little about the importance of Mechanics in the new industrial era and more importance is given to the evolution of Information and Communication Technologies and Artificial Intelligence. This article presents a frame of reference about the importance of Mechanical Engineering in Industry 4.0 and proposes an extension to the concept of Mechanics 4.0, recently defined as the relationship between Mechanics and Artificial Intelligence. For the analysis of Mechanical Engineering in Industry 4.0, the criteria of the four driving forces that defined Mechanics in the third industrial revolution was used. An analysis of Mechanical Engineering Education in Industry 4.0 is presented, and the concept of Mechanical Engineering 4.0 Education is improved. Finally, the importance of making changes in the educational models of engineering education is described.

The aim of this study was to evaluate whether alterations in food availability compromise the metabolic homeostasis of honey bees exposed to three fungicides alone or together. Ten honey bee colonies were utilized, with half receiving energy-protein supplementation for 15 weeks while another five colonies had their protein supply reduced with pollen traps. Subsequently, forager bees were collected and exposed by contact to 1 or 7 µg of bixafen, prothioconazole, and trifloxystrobin, either individually or in combination. After 48 hours, abdomens without the intestine was used for the analysis of expression of antioxidant genes (SOD-1, CAT, and GPX-1), detoxification genes (GST-1 and CYP306A1), the storage protein gene vitellogenin, and immune system antimicrobial peptide genes (Defensin-1, Abaecin, Hymenoptaecin, and Apidaecin), through real-time PCR. All pesticide treatments induced changes in gene expression, with bixafen showing the most prominent upregulation. Exposure to 1 µg of each of the three pesticides resulted in upregulation of genes associated with detoxification and nutrition processes, and downregulation of immune system genes. When the three pesticides were combined at a dose of 7 µg each, there was a pronounced downregulation of all genes. Dietary supplementation led to a slight reduction in gene expression alterations provoked by the fungicides.

Abstract: This narrative review challenges the recent World Workshop Consensus (WWC) conferences failure to classify aggressive periodontitis (AP) in young adults as distinct from adult periodontitis. Deficiencies in the consensus process, results of these deficiencies, and their impact on disease classification are presented. Support for retaining localized aggressive periodontitis (LAgP) in adolescents as a unique disease, focuses on the; 1) age of onset, 2) rate of bone loss in those affected, and 3) unique microbiological etiological associations. Examples of, 1) unique clinical signs and symptoms of LAgP are presented, and 2) the microbial subgingival consortia that precedes these clinical signs and symptoms are described. Tables show, 1) decreased publications for AP since publication of WWC guidelines and 2) Bradford-Hill guidelines that support the unique etiological consortia replicated in clinically well-defined longitudinal studies. The review describes major deficiencies in the WWC as compared to other medically-related well-run consensus conferences that, 1) set pre-conference standards for 70 – 80% agreement of expert participants, and 2) published the dissenting point of view. In contrast, the WWC conference was decided by a mere majority, and never presented the dissenting view. The review concludes that averaging of mean pocket depth reduction, or attachment gain can misrepresent disease and/or success of treatment in aggressive diseases. In contrast, clinical assessment of time to recurrence of subgingival re-infection with possible translocation of oral microbes to distant sites is presented as an alternative measurement of success. Other questions and future directions are presented.

Granulites and associated dykes from the less well studied southern Ivrea-Verbano Zone (IVZ; around Ivrea town) are characterized by combining field, macro, micro and chemical (major and trace-element mineral composition) data in order to identify chemical and rheological variations in the lower crust that could be relevant for geodynamic implications. The Ivrea granulites are similar to those belonging to the Lower Mafic Complex of the central IVZ. The mafic lithologies experienced a stealth metasomatism (pargasitic amphibole and An-rich plagioclase) that occurred at suprasol-idus conditions by a pervasive reactive porous flow of mantle-derived orogenic (hydrous) basaltic melts infiltrated along relatively few, likely deformation-assisted, channels. Similar metasomatic melts are already reported in the central and northern IVZ, suggesting a massive regional hydration of the lowermost Southalpine mafic crust during the Early Mesozoic. The plastic behavior of the lowermost part of the crust, induced by its metasomatic hydration, could have promoted the Tri-assic extension of the Variscan crust and the beginning of the Alpine cycle.

In Kenya, reports of Rift Valley fever (RVF), one of the worst climate-sensitive zoonosis, have been common. Despite the fact that several empirical studies have demonstrated that Machine learning techniques perform better than time series models in forecasting time series data, there is little evidence of their use in predicting disease outbreaks in Africa. Recently, the literature has mentioned a number of other uses of machine learning to support intelligent decision-making in the healthcare industry and public health but there is limited knowledge on the use of the XGBoost model in the prediction of disease outbreaks. Among the Kenyan provinces, Rift valley fever cases were more pronounced in Rift valley (26.80%) and Eastern (20.60%) regions. The study explored the relationship be-tween RVF incidence and various climatic factors, such as humidity, clay content, elevation, slope, and rainfall. The strongest correlation, a meager 0.02903 for rainfall, was found in the correlation matrix, which showed weak linear relationships between various climatic factors and RVF cases. These climate variables were used to train the XGBoost model, which showed remark-able performance with an AUC of 0.8908, accuracy of 99.74%, precision of 99.75%, and recall of 99.99%. Rainfall was found to be the most important predictor in the feature importance analysis. These findings are consistent with other research showing how important weather conditions are to RVF outbreaks. According to the study's findings, the use of sophisticated machine learning models that take a variety of climatic factors into account can greatly improve RVF outbreak prediction and control.

In this study, AlSi12 alloy was fabricated using the selective laser melting (SLM) technique to produce high density components with complex and customized parts for railway applications. Nonetheless, the production of dense samples necessitates the optimization of production process parameters. As a statistical design of experimental technique, the response surface methodology was used to optimise different combination of SLM parameters. The results were analysed using analyse of variance (ANOVA) and the signal-to-noise(S/N) ratios. The relationship between the hardness response to the process parameters (scanning speed and lase power) for determining the optimal processing conditions were examined. A hardness value of 133 HV was obtained. The process parameters were successfully optimized and the relationship between the parameters and the structures of the fabricated samples were reported.

Direct-acting antivirals (DAAs) revolutionized therapeutics of chronic hepatitis C. The emergence and transmission of HCV variants with resistance-associated substitutions (RASs) can undermine HCV treatment. This study aimed to assess the prevalence and temporal trends of RASs in HCV with a particular focus on the clinically-relevant RASs (cr-RASs). Near-complete HCV GenBank sequences archived in the Los Alamos HCV Database were analyzed. The study period was divided into two phases; before 2011 and 2011 onwards. Identification of RASs across three DAA classes; NS3, NS5A, and NS5B inhibitors was based on the 2020 EASL guidelines. The AASLD-IDSA recommendations were used to identify cr-RASs for three HCV genotypes/subtypes (1a, 1b, and 3) for four DAA regimens; ledipasvir/sofosbuvir; elbasvir/grazoprevir; sofosbuvir/velpatasvir; and glecaprevir/pibrentasvir. The final HCV dataset comprised 3443 sequences and the prevalences of RASs were 50.4%, 60.2%, and 25.3% in NS3, NS5A, and NS5B, respectively. In subtype 1a, resistance to ledipasvir/sofosbuvir was 32.8%, while resistance to elbasvir/grazoprevir was 33.0%. For genotype 3, resistance to sofosbuvir/velpatasvir and glecaprevir/pibrentasvir was 4.2% and 24.9%, respectively. Significant increase in cr-RASs was observed across the two study phases as follows: for ledipasvir/sofosbuvir in subtype 1a, cr-RASs increased from 30.2% to 35.8% (p=0.019); for elbasvir/grazoprevir in subtype 1a, cr-RASs increased from 30.4% to 36.1% (p=0.018); In subtype 1b, neither ledipasvir/sofosbuvir nor elbasvir/grazoprevir showed any cr-RASs in the first phase, but both were present at a prevalence of 6.5% in the second phase (p<0.001); for sofosbuvir/velpatasvir in genotype 3, cr-RASs increased from 0.9% to 5.2% (p=0.006); and for glecaprevir/pibrentasvir, cr-RASs increased from 12.0% to 29.1% (p<0.001). Rising prevalence of HCV RASs and cr-RASs was discernible. This highlights the necessity for ongoing surveillance and adaptation of novel therapeutics to manage resistance effectively. Updating of the clinical guidelines and treatment regimens are recommended to counteract the evolving resistance to DAAs.

Abstract: Aim: This study aimed to evaluate the antibiotic-prescribing attitudes of dental students during the management of pulpal and periapical pathologies. Material and methods: This cross-sectional descriptive study concerned all the students in clinical training registered the 5 faculties of dental medicine in Morocco. A self-administered questionnaire was used, and completed via email addresses. Data were analyzed with Jamovi software. Quantitative variables are expressed as mean and standard deviation and qualitative variables as numbers and percentages. X2 and ANOVA tests were performed. The significance level was set at p < 0.05. Results: Three sixty-five students participated in this study. The average duration was 5.87 ±1.45 No statistical difference was found between the different universities p >0.05. Of most students 83.8% prescribe Amoxicillin first ; Amoxcilin in combination with clavulanic acid is prescribed by 9.2%. For patients with penicillin allergy, clindamycin was the most prescribed 53.9%, after followed by azitromycin at 20.9%. Antibiotics are prescribed for all pulp and periapical pathologies, whether acute or chronic. For acute pulpitis, a difference was statistically significant (P=0.01). Regarding acute apical periodontitis, a statistically significant difference between the different faculties was noted (P= 0.03). For the apical abscess, the antibiotic prescription was higher at the public faculty of Casablanca 92.8% than in the other faculties (P = 0.02) Conclusion: It appears from this study the need for faculties of dentistry to develop innovative teaching models to improve the level of knowledge of students on antibiotics and their indications in endodontics.

From the existing millions of fungal species only a few cause disease. In this study, we investigated invasive fungal infections in the head and neck over a 19-year period (2005 to 2024) at a large academic healthcare system. Among 413 cases, 336 were noninvasive, and 77 were invasive. The highest incidence of invasive infections occurred in the sinonasal cavities, with a 15-fold difference compared to other sites. Most infections affected adults over 40 years old. The most common organisms were Mucorales (51%), hyaline molds (29%), and Candida (11%). Risk factors included malignancy, transplant, diabetes, and illicit drug use. Mortality was high in patients with malignancy and/or transplant. Infections affecting the mandible were usually a complication of osteoradionecrosis and were associated with coinfection of Candida and Actinomyces. At other sites, infections were rare and were usually the result of penetrating injuries or immunosuppression. Treatment typically involved a combination of antifungals and surgical procedures.

In the context of the Korean building structure standard KDS2022, wind loads can be readily calculated in terms of the along-wind, across-wind, and torsional components, based on a single wind direction. However, this approach falls short in accurately and safely evaluating the impact of winds from various directions. Therefore, in this study, we developed a Wind Load Calculation Program (WCP) capable of predicting wind loads with relative precision during the preliminary design phase. First, wind tunnel tests were conducted to identify the essential factors necessary for calculating wind loads and the variables influencing these factors. The building shape considered was a square, and the wind force coefficients and power spectral density were measured by combining 4 ground roughness values, 11 side ratios (), 4 aspect ratios (), and wind directions ranging from 0° to 90°. Subsequently, a generalized formulation was devised to facilitate wind load calculations across diverse conditions and a method for calculating load combination coefficients, considering response correlation and load simultaneity, was presented. Finally, the wind loads obtained from the wind tunnel tests were compared with those predicted by the WCP using an actual project model.

This article deals with the denoising of signals from sensors (current and voltage) in a photovoltaic conversion chain using wavelet theory. The idea is to reduce the noise as much as possible without distorting or losing the original signal information. To see the reliability of this proposed method, a comparative study between our proposed method (WDD) and the classic low-pass filter method was presented. The contribution in this work is the improvement of the DC-DC boost converter via the use of wavelet theory, however, that’s why we set two objectives: the first is to obtain reliable control of the DC-DC boost converter via the proposed WDD and the second to increase the overall system efficiency. The experimental results show a very great improvement in the quality of the signals of the proposed method compared to the classic method of filtering by low-pass filter.

Intrusion Detection Systems play a crucial role in a network. They can detect different network attacks and raise warnings on them. Machine learning-based IDSs are trained on datasets that, due to the context, are inherently large, since they can contain network traffic from different time periods and often include a large number of features. In this paper, we present two contributions: the study of the importance of feature selection when using an IDS dataset, while striking a balance between performance and the number of features; and the study of the feasibility of using a low-capacity device, the Nvidia Jetson Nano, to implement an IDS in a low-capacity network. The results, comparing the GA with other well-known techniques in feature selection and reduction, show that the GA has a higher F1-score of 76%, although the time to find the optimal set of features surpasses other methods; the reduction of the number of features reduces the processing time without a significant impact in f1-score. The Jetson Nano allows the classification of network traffic with an overhead of 10 times in comparison to a traditional server.

This study explores the stability of electrodeposited copper catalysts utilized in electrochemical CO2 reduction (ECR) across various amine media. The focus is on understanding the influence of different amine types, corrosion ramifications, and the efficacy of pulse ECR methodologies. Employing a suite of electrochemical techniques including potentiodynamic polarization, linear resistance polarization, cyclic voltammetry, and chronopotentiometry, the investigation reveals useful insights. The findings show that among the tested amines, CO2-rich monoethanolamine (MEA) exhibits the highest corrosion rate. However, in most cases the rates remain within tolerable limits for ECR operations. Primary amines, notably monoethanolamine (MEA), show enhanced compatibility with ECR processes, attributable to their resistance against carbonate salt precipitation and sustained stability in potential over extended durations. Conversely, tertiary amines such as methyldiethanolamine (MDEA) present challenges due to the formation of carbonate salts during ECR, impeding their effective utilization. The study highlights the effectiveness of pulse ECR strategies in stabilizing ECR. A noticeable shift in cathodic potential and reduced deposit formation on the catalyst surface through periodic oxidation underscores the efficacy of such strategies. These findings offer insights for optimizing ECR in amine media, thereby providing promising pathways for advancements in CO2 emission reduction technologies.

When examining the crucial role of civic competence in fostering sustainable societies, economies, and ecosystems, its significance for cultivating responsible and engaged citizens in our ever more interconnected global landscape must be recognized. Notably, education influences the development of civic competence throughout the learning experience at all levels of education. This research aims to explore the evolution of students’ self-assessment in terms of civic competence and its three sub-competences. The objective is to comprehend the present status of students’ self-assessments and explore their potential impact on the formation of a sustainable society. Data were collected for this study using an assessment tool elaborated in the ESF project “Development and Implementation of the Education Quality Monitoring System” for students’ generic competences. The tool, presented in a digital form using the QuestionPro platform, measures six generic competences, including civic competence. A total of 1,166 bachelor students and 354 Master’s students participated in the study, representing 22 Latvian higher education institutions. The study’s findings indicate that civic competence in the sample is considerably lower than the other generic competences measured, with a greater dispersion of results. The results also highlight specific areas within universities that require improvement during the learning process to cultivate individuals who are sustainable and socially responsible members of society.

In this paper, we introduce and investigate a new family of sequences called the generalized Fibospinomials (or the generalized Fibonacci polynomial spinors or Horadam polynomial spinors). Being particular cases, we handle with $(r,s)$-Fibonacci and $(r,s)$-Lucas polynomial spinors. After a short history on spinors and quaternions, we present Binet's formulas, generating functions and the summation formulas for these polynomials. In addition, we obtain some identities of generalized Fibonacci polynomial spinors, $(r,s)$-Fibonacci polynomial spinors and $(r,s)$-Lucas polynomial spinors. Moreover, we give some special identities such as Catalan's and Cassini's identities and we present matrices related with these polynomials.

Remote video imagery using shoreline edge detection is widely used in coastal monitoring in order to acquire measurements of nearshore and swash processes. Some of these systems have very limited flexibility due to their rigid structures and require considerable investment in hardware. As such, there is a need for an autonomous low-cost system (~€500) that can be rapidly deployed in the field, while still producing the outcomes required for coastal monitoring. This research presents a sensitivity analysis of time-lapse intervals for two low-cost cameras located in a remote coastal area, overlooking a dissipative beach-dune system. The analysis shows that RMSD in the detected shoreline is similar to other studies for intervals ranging between 1 second and 30 seconds (i.e., RMSDmax for Camera 1 = 2.8 m and Camera 2 = 1.3 m). The increase of the sampling interval from 1 s to 30 s is shown to have no significant adverse effect on the precision of shoreline detection. The research found that the limitations of battery life and memory storage substantially decrease when sampling intervals increase without an effect on the data quality. This also has a positive effect for low-cost systems and removes the requirement for external battery and memory storage. On the systems used, the battery life increased from ~10 days to ~100 days when the sampling interval was increased from 1 to 5 s., As such, the current standard of producing Timex images from 1 s sampling intervals over 10 minutes can be changed depending on the application and requirements needed for analysis.

Cutaneous mycoses are common infections whose treatment has become more complex due to increasing antifungal resistance and the need for prolonged therapies, hindering patient adher-ence and increasing the incidence of adverse effects. Consequently, the use of physical therapies, especially photodynamic therapy (PDT), has increased for the treatment of onychomycosis due to its antimicrobial capacity mediated by the production of reactive oxygen species. This study investigates the in vitro effect of the combination of blue light (448 nm) and red light (645 nm) with terbinafine on the cell viability of human keratinocytes and the production of reactive ox-ygen species. The combination of terbinafine and blue light exhibits a synergistic effect on the production of reactive oxygen species and a significant increase in the expression of superoxide dismutase (SOD), an enzyme involved in the reduction of superoxide ions (O2-) and the genera-tion of hydrogen peroxide (H2O2). Such effect could be useful in clinical practice to improve the response of cutaneous mycoses to pharmacological treatment, reduce their toxicity, and shorten their duration.

This study evaluates and contrasts the changes in vegetation cover over three decades in two forest areas in northern Mexico with different management statuses: one with sustainable forest exploitation and the other under protection as a Flora and Fauna Protection Area (FFPA). The hypothesis proposed that both areas would maintain or increase their vegetation cover since 1995. Using QGIS 3.32 “Lima” software and supervised and unsupervised classification methods, satellite images from the periods 1995-2008, 2008-2014, 2014-2021, and 1995-2022 were analyzed. The results showed that the Ejido El Largo y Anexos significantly increased forest areas and reduced grasslands due to sustainable management practices, with notable expansion of pine-oak and pine forests. In contrast, the Tutuaca Flora and Fauna Protection Area (FFPA) showed a notable loss of oak and oak-pine forests, suggesting ineffectiveness in its conservation policies. However, a lesser loss of Douglas fir forest was observed, indicating some effective protection efforts. The comparison reveals opposing dynamics: while Ejido El Largo y Anexos demonstrates success in sustainable management, the Tutuaca FFPA faces conservation challenges. In conclusion, this study highlights the need for active management approaches to maintain ecosystem cover and functionality.

(1) Agricultural production is one of the most important, fundamental and resilient sectors. The excessive and incorrect use of agricultural pesticides has caused environmental pollution, with final destination in aquatic environments. Once in the aquatic environment, the decontamination process aimed at removing the pesticide is not always a simple task. There are expensive and low-efficiency procedures in the literature. In this sense, it is necessary to develop low-cost, sustainable procedures with high remediation capacity. Among the widely used agricultural pesticides, glyphosate stands out for weed control, which according to the World Health Organization (WHO) is potentially carcinogenic in humans. (2) In this context, a nanocellulose-based biopolymer was developed to recover glyphosate from aquatic environments. Different methodologies have been developed, the most interesting being membrane immersion in aquatic systems. The analytical technique for quantifying glyphosate was molecular spectrophotometry in the ultraviolet – visible range (UV-VIS); (3) Nanocellulose showed a value of 4.7 mg of Glyphosate per g of nanocellulose, and organomodified nanocellulose showed the removal of 6.1 mg of Glyphosate per g of nanocellulose, evaluated in pseudo-first order kinetic models; (4) The biomaterial has a sustainable and renewable origin and has potential for contaminant removal and can be applied to contaminated aquatic systems.

Micro-Raman spectroscopy was carried out to evaluate the localized residual stresses in commercial Gallium Nitride-based devices, specifically AlGaN/GaN High Electron Mobility Transistors (HEMTs) in a novel packaging design provided by STMicroelectronics S.r.l. The packaging plays a key role in protecting the device core against the external environment, thus minimizing damages caused by mechanical shocks, exposure to light, and contact with chemicals, conjointly achieving an efficient heat dissipation rate. Even though the packaging is a required step for the proper functioning of ready-to-use electronic devices, its application typically may introduce mechanical stress to AlGaN/GaN HEMTs, which can result in various reliability issues. In this paper, we investigate the impact of packaging on residual stress by analyzing the frequency shift of the E2 Raman peak along GaN layers and at the GaN/Si interface. An extensive evaluation was conducted using both a packaged device and a wafer-level device. The correlation between Raman frequency shifts of the E2 mode was accurately quantified, revealing a stress mitigation of approximately 0.1 GPa. This reduction is ascribed to the compressive stress introduced by the packaging, which partially offsets the intrinsic tensile stress of the wafer-level device. The proposed methodology could, in principle, be implemented to improve the development of a packaging.

A positive fluid balance may evolve to fluid overload and associate with organ dysfunctions, weaning difficulties, and increased mortality in ICU patients. We explored whether individualized fluid management, assessing fluid-responsiveness via passive leg-raising maneuver (PLR) before spontaneous breathing trial (SBT) associated with less extubation failure in ventilated patients with high fluid balance, admitted to the ICU after liver transplantation (LT). We recruited 15 LT patients in 2023. Postoperative fluid balance was +4476 [3697,5722] mL. PLRs were conducted at ICU admission (T1) and pre-SBT (T2). Cardiac index (CI) changes were recorded before and after SBT (T3). Seven patients were fluid responsive at T1, and 12 at T2. No significant differences occurred in hemodynamic, respiratory, and perfusion parameters between fluid-responsive and fluid-unresponsive patients at any time. Fluid-responsive patients at T1 and T2 increased their CI during SBT from 3.1 [2.8,3.7] to 3.7 [3.4,4.1] mL/min/m2 (p= 0.045). All fluid-responsive patients at T2 were extubated after SBT and consolidated extubation. Two out of three of fluid-unresponsive patients experienced weaning difficulties. We concluded that fluid-responsive patients post-LT may start weaning earlier and achieve successful extubation despite high postoperative fluid balance. This highlights the profound impact of personalized assessment of cardiovascular state on critical surgical patients.

To analyze the combined response of ocular cyclotorsion and head tilt during body tilt and to interpret the physiologic role of those movements, each of the three subjects completed six different experiments of body tilt not fixating their head movements using a flight simulator, which consisted of combinations of three tilt angles (30, 45, and 60) and two visual conditions. Head tilt and ocular cyclotorsion of the right eye before, during, and after the tilt maneuver were recorded and analyzed by time sequence. In the active tilting phase, the right eye showed a stepladder pattern of multiple repeats of fast and slow cyclotorsion along with head tilt to obtain maximum visual information. During the stationary tilting phase, there occurred a small amount (mean, 2.3) of ocular cyclotorsion which was reciprocal to that of head tilt. The visual cue of body tilt through the central visual field induced a larger amount of head tilt but affected little ocular cyclotorsion. The maximum degree of ocular cyclotorsion during each experiment was 10.2 on average. In conclusion, the combined response of ocular cyclotorsion and head tilt develops during body tilt and it compromises the conflicting needs between binocular vision and gravitational orientation.

The reaction of berberine derivatives containing at O-9 position N,N-disubstituted acetamide fragments with sodium borohydride in methanol at 0 °C leads to a mild reduction of the "C" cycle with the formation of corresponding tetrahydroberberine derivatives with moderate to good yields.

Classroom resource allocation is a challenging problem in educational institutions. The use of cloud computing can aid in the optimization of this process by allowing resource providers to allocate resources to users in a timely and efficient manner. In this paper, we propose a modified Salp Swarm Algorithm (SSA) to optimize the allocation of classroom resources. The proposed approach involves generating a population of salps representing potential solutions to the resource allocation problem and updating the positions of the salps iteratively based on a fitness function and mathematical equations. We conducted simulations of the proposed algorithm on various numbers of tasks and sources to evaluate its performance. The results indicate that the modified SSA algorithm can efficiently allocate classroom resources, achieving lower completion time of tasks (makespan) with lower costs. This paper contributes to the literature by introducing an effective approach to solve the classroom resource allocation problem.

Soil microorganisms plays an important role on plant development and the homogenization of soil microbiome is agri-environmental harmful. It is essential that agricultural practices are carried out taking soil microbiome preservation in consideration. Agroforestry systems are one of the most environmentally friendly agrosystems and its plant diversity influence directly the soil microbiome diversity. In addition, many technologies have been developed and used by applying inoculants in agriculture. However, most of the inoculants are developed with only one or a little number of microbial species to supply a specific plant nutritional demand. In this study we tested the efficacy of the microbial consortium (MC) obtained from compost and the cyanobacteria Arthrospira platensis (AP) comparing with the application of the vermicompost tea (VT) and bokashi (BK) in arugula, lettuce, beetroot, and carrot in an agroforestry system in two seasons. Soil changes on chemical properties and β-glucosidase and arylsulfatase were measured over time. The vegetables yield was measured and for arugula and lettuce the nutritional traits and plant root system were also evaluated. Greater plant yield, nutritional values, and plant root development was observed in the CM treated plants, AP and BK had similar results. Our results show that both CM and AP have potential to become a sustainable product for agricultural production

Background: Autonomic balance measurement (ABM) is a valuable tool in clinical practice for assessing the functioning of the autonomic nervous system (ANS), which controls involuntary bodily functions. Here we summarize the current understanding of the utility of autonomic balance measurement in clinical practice. Methods: A narrative review of relevant literature was conducted, focusing on studies investigating the use of autonomic balance measures in various clinical settings. Results: ABM holds potential benefits in clinical practice, including aiding in diagnosing autonomic dysfunction, monitoring treatment efficacy, and predicting potential health complications. ABM can be crucial for diagnosing various conditions, including cardiovascular diseases (Heart failure, arrhythmias, and hypertension), neurological disorders (Parkinson's disease, Alzheimer's disease, and diabetic neuropathy), in sports medicine athletes can undergo ABM to optimize training regimens, enhance performance, assessing the impact of training stress, preventing overtraining, and promoting overall well-being and probably to assess potential health risks, in metabolic syndromes ABM can aid in the early detection of autonomic neuropathy, a diabetes-related complication, allowing for timely intervention and better management of the disease, and psychiatric disorders (Anxiety, depression, and post-traumatic stress disorder). In addition, ABM can be helpful in monitoring of treatment efficacy, by tracking changes in autonomic balance, clinicians can assess if treatments for conditions impacting the autonomic nervous system are effective. ABM can also be helpful in predicting outcomes by facilitating early recognition of future health complications in certain populations. However, limitations exist, including non-specificity, variability in measurements, and limited evidence for routine use in specific clinical settings. Conclusion: Incorporating autonomic balance measurement into routine clinical assessments provides a more comprehensive understanding of a patient's health. It complements traditional diagnostic methods, offering additional insights into the body's regulatory mechanisms. While autonomic balance measurement offers potential benefits, careful interpretation and consideration of its limitations are crucial for its effective use in clinical practice. ABM remains a valuable and versatile tool in clinical practice for a deeper understanding of the autonomic nervous system, enabling early detection, targeted interventions, and improved management of various medical conditions across different specialties.

In this paper, a method of charging lead acid battery with solar power by flyback converter is proposed. The basic system consists of a buffer circuit, auxiliary power circuit, control circuit, voltage feedback circuit and current feedback circuit. The system is capable of monitoring battery voltage and the current, charging the coupling inductor and automatic control of output duty cycle, overcharging and over-discharging protection. The experiment proves that the charging efficiency is improved by about 83% at full load.

The gut microbiota constitutes a complex ecosystem, comprising trillions of microbes that have co-evolved with their host over hundreds of millions of years. Over the past decade, a growing body of knowledge has underscored the intricate connections among diet, gut microbiota, and human health. Bioactive polysaccharides (BPs) from natural sources like medicinal plants, sea-weeds, and fungi have diverse biological functions, including antioxidant, immunoregulatory, and metabolic activities. Their effects are closely tied to the gut microbiota, which metabolizes BPs into health-influencing compounds. Understanding how BPs and gut microbiota interact is critical for harnessing their potential health benefits. This review provides an overview of the human gut microbiota, focusing on its role in metabolic diseases like obesity, type II diabetes mellitus (T2DM), non-alcoholic fatty liver disease (NAFLD), and cardiovascular diseases (CVD). It explores the basic characteristics of several BPs and their impact on gut microbiota. Given their significance for human health, we summarize the biological functions of these BPs, particularly in terms of im-munoregulatory activities, blood sugar, and hypolipidemic effect, providing a valuable reference for understanding the potential benefits of natural BPs in treating metabolic diseases. These properties make BPs promising agents for preventing and treating metabolic diseases. The comprehensive understanding of the mechanisms by which BPs exert their effects through gut microbiota opens new avenues for developing targeted therapies to improve metabolic health.

The comprehensibility of good predictive models learned from high-dimensional gene expression data is attractive because it can lead to biomarker discovery. Several good classifiers provide comparable predictive performance but differ in their abilities to summarize the observed data. We extend a Bayesian Rule Learning (BRL-GSS) algorithm, previously shown to be a significantly better predictor than other classical approaches in this domain. It searches a space of Bayesian networks using a decision tree representation of its parameters with global constraints, and infers a set of IF-THEN rules. The number of parameters and therefore the number of rules are combinatorial to the number of predictor variables in the model. We relax these global constraints to a more generalizable local structure (BRL-LSS). BRL-LSS entails more parsimonious set of rules because it does not have to generate all combinatorial rules. The search space of local structures is much richer than the space of global structures. We design the BRL-LSS with the same worst-case time-complexity as BRL-GSS while exploring a richer and more complex model space. We measure predictive performance using Area Under the ROC curve (AUC) and Accuracy. We measure model parsimony performance by noting the average number of rules and variables needed to describe the observed data. We evaluate the predictive and parsimony performance of BRL-GSS, BRL-LSS and the state-of-the-art C4.5 decision tree algorithm, across 10-fold cross-validation using ten microarray gene-expression diagnostic datasets. In these experiments, we observe that BRL-LSS is similar to BRL-GSS in terms of predictive performance, while generating a much more parsimonious set of rules to explain the same observed data. BRL-LSS also needs fewer variables than C4.5 to explain the data with similar predictive performance. We also conduct a feasibility study to demonstrate the general applicability of our BRL methods on the newer RNA sequencing gene-expression data.

Background: Vitamin B 12 deficiency has been implicated in endothelial dysfunction and cardiovascular disease via hyperhomocysteinemia. Coronary tortuosity (CorT) is a common coronary angiography finding. The etiology, clinical implication and long term prognosis are still not well clarified. This study was conducted with the aim to evaluate the relationship between CorT and vitamin B12. Subjects and Method: The medical records of consecutive patients, who underwent coronary angiography, were retrospectively reviewed. The study group consisted of 1624 patients. Taking into consideration the inclusion criteria, 212 patients with CorT and 210 patients with normal coronary angiographies (control group) were included in the study. Vitamin B12, other biochemical parameters, clinical and echocardiographic parameters, and CorT score were evaluated in all patients. CorT is defined as fixed 3 bends during both systole and diastole, with each bend ≥45 °. Results: Patients with CorT had higher prevalence of older, female gender, hypertension, current smoking. Vitamin B12 was significantly decreased in patient with CorT (134.7±47.8 vs 239.6±53.8 p<0.001). On multivariate analysis age, female gender, hypertension, diabetes mellitus and vitamin B12 were independent predictors for CorT (OR 1.56; 95% CI: 1.247–1.962; p < 0.001, OR 1.628; 95% CI: 1.376-2.048; p<0.001, OR 1.865; 95% CI: 1.387-2.695; p<0.001, OR 1.362; 95% CI: 1.184-1.726; p<0.001, OR 1.862; 95% CI: 1.486-2.674; p<0.001, respectively). Conclusion: In our study, we have founded a significant relationship between vitamin B12 deficiency and CorT.

In the context of the Lubumbashi Coal Production Basin (LCPB), the socio-economic repercussions of the COVID-19 pandemic have exacerbated pressures on populations dependent on forest resources for their subsistence. This study employs a comprehensive methodological approach, integrating advanced remote sensing techniques, including image classification, mapping, and detailed landscape analysis, to quantify alterations in forest cover within the LCPB during the pandemic period. Our findings reveal a consistent trend of declining forested area, characterized by processes of attrition and fragmentation observed throughout various study phases, spanning from May 2019 to November 2023. This reduction in forest cover, notably more pronounced in the vicinity of Lubumbashi city and the northern zone of the LCPB, proved to be less pronounced between November 2019 and September 2020, underscoring the influence of COVID-19 pandemic-induced confinement measures on forest management practices in the region. However, subsequent to this period of restriction, deforestation activity intensified, leading to significant landscape transformations within the LCPB, primarily attributable to expanded human activities, consequently resulting in a notable decrease in the proportion of land occupied by these natural ecosystems. Consequently, the size of the largest forest patch declined substantially, decreasing from 14.62% to 8.20% between May 2019 and November 2023, thereby fostering a heightened density of forest edges over time. Our findings provide a significant contribution to understanding the complex interactions between the COVID-19 pandemic and deforestation phenomena, emphasizing the urgent need to adopt adaptive management strategies and appropriate conservation measures in response to current economic challenges.

Biopolymers are of growing interest, but to improve some of their poor properties and performance, it is required the formulation of bio-based blends and/or adding of nanoparticles. For this purpose, in this work, two different metal oxides, such as zinc oxide (ZnO) and titanium dioxide (TiO2), at different concentrations (0.5, 1 and 2 %wt.) have been added in polylactic acid (PLA) and polylactic acid/polyamide 11 (PLA/PA11) blends to establish their effects on solid-state properties, morphology, melt behaviour, and photo-oxidation resistance. It seems that the addition of ZnO in PLA leads to a significant reduction of its rigidity probably due to an inefficient dispersion in the melt state, while the addition of TiO2 does not penalise PLA rigidity. Interestingly, the addition of both ZnO and TiO2 in PLA/PA11 blend has a positive effect on the rigidity because of blend morphology refinement and leads to a slight increase in film hydrophobicity. The photo-oxidation resistance of neat PLA and PLA/PA11 blend is significantly reduced due to the presence of both metal oxides, and this must be considered when designing the potential applications. The last results suggest that both metal oxides could be considered as photo-sensitive degradant agents for biopolymer and biopolymer blends.

Proton Exchange Membrane Fuel Cell (PEMFC) is a fast-developing battery technology, and the key to its reliability and lifespan improvement lies in the accurate assessment of durability. However, the degradation mechanism of PEMFC is hard to determine and its internal parameters are highly coupled. Thus, the development of the more accurate life prediction model that meets the actual scenarios is urgent to investigate. To solve this problem, a multi-feature fusion life prediction method based on Temporal Convolutional Network-Gated Recurrent Unit (TCN-GRU) is proposed. A TCN algorithm is used as the prediction base model, and two GRU modules are included to the model to strengthen the model expression ability and improve its predictive accuracy. Two widely recognized datasets and two operating conditions are utilized for model training and prediction, respectively. Comparisons are made with single-feature parameter models in terms of Root Mean Square Error (RMSE) and Determination Coefficient (R2). The results show that the prediction accuracy of the TCN-GRU multi-feature fusion model is higher than that of the single-feature models in terms of stability and anti-interference under both operating conditions. Furthermore, with the increase of input feature parameters, the TCN-GRU model is closer to the real value, which proves once again that the proposed model can meet the accuracy requirements of the life prediction of PEMFC.

Hemoglobinopathies are a group of disorders in which the hemoglobin molecule has abnormal production or structure. The hemoglobin molecules in red blood cells (RBC) are impacted by the blood disease known as sickle cell disease (SCD), and Thalassemia is one of the major monogenic disorders that reduces hemoglobin production( Kohne et al ., 2011). This disorder results in a large number of red blood cells being destroyed, leading to anemia. India bears a huge burden of hemoglobinopathies; thalassemia is the most prevalent (Mondal SK et al., 2016). A key component of thalassemia prevention is a successful screening procedure to identify Thalassemia carriers. Effective screening programs have numerous obstacles, especially in environments with limited resources. Machine learning (ML) has been used to solve technical and domain-specific problems in a variety of prognostic and diagnostic medical jobs. In this work, we aimed to identify and analyze the most common mutation of β--thalassemia and sickle cell disease from the north Indian population by employing Machine learning-based algorithms. To accurately predict the carrier state from a simple blood test, and to predict pathogenic hemoglobin variants in a group of individuals, these results demonstrate the application of integrated bioinformatics and machine learning approaches. This study contributes to the validation of the models based on data from several individuals and hemoglobinopathies.

Two decades after the antiretroviral therapy (ART) introduction, several challenges still prevail in maintaining people living with HIV (PLHIV), even with "Test and Treat" and/or "Rapid Start of ART" initiatives, as well as the scale-up of ART worldwide to promote access and adherence to treatment. This review examined articles on ART adherence in Africa between 2016 and 2023, published in English and indexed in PubMed. A total of 16 articles out of 2415 were eligible and included for analyses. Overall, ART adherence rates in SSA regions ranged from 43% to 84%. Rates in the centre of the SSA region ranged from 58% to 80%, in the north from 50% to 83%, in the south from 77% to 84%, in the west from 43% to 60% and in the east from 69% to 73%. Most African countries use the self-report to assess treatment adherence, although unreliable. The main factors with negative influence on ART adherence were comorbidities, lack of motivation, socioeconomic difficulties or side effects. Conclusion: Adherence to ART is a good indicator for controlling the spread of HIV. It is important to overcome the barriers that make it difficult to comply with ART and reinforce the factors that facilitate the accession of medication.

Dietary habits, including meal frequency, meal timing, and skipping meals, have been extensively studied due to their association with the development of non-communicable diseases (NCDs). This study describes dietary habits, meal timing, meal frequency, skipping meals, and late-night eating in Kuwaiti adults. The Kuwait National Nutrition Surveillance System data was utilized to reach the objectives of this study. The findings reveal that approximately 50% of the adults in Kuwait eat after 10 p.m., 29% skip breakfast, and 9.8% skip dinner. Furthermore, adults in Kuwait consume 4.4 meals per day on average. Women skip breakfast more often and have extended night fasting than men (p&lt;0.001). Married adults skip breakfast and dinner less than unmarried adults (p&lt;0.001). In conclusion, this descriptive study provides valuable insights into the dietary habits of Kuwaiti adults, emphasizing the importance of further investigating the association between meal timing, meal frequency, and the prevalence of NCDs in Kuwait.

Few young Japanese adults regularly consume a well-balanced diet composed of staples, course dishes, and sides. We hypothesised that adopting the recommended planetary health diet with regular breakfast consumption would promote well-balanced diets among young Japanese male undergraduates. This study aimed to examine the structural association between a planetary health diet with regular breakfast consumption and well-balanced diet intake. Participants were 142 male undergraduates who completed a 2022 online questionnaire via Google Forms in a cross-sectional study at a public university in Hyogo Prefecture. A planetary health diet comprises the consumption of the recommended eight items. A covariance structure analysis was performed in a hypothetical model with factors (regular breakfast consumption and eight items) potentially associated with the intake of a well-balanced diet at least twice daily. Acceptable goodness-of-fit was obtained by excluding chicken dishes and nuts from the eight recommended items of the planetary health diet. Frequent consumption of the remaining six recommended items (fish, eggs, soybeans/soybean products, dairy foods, vegetables, and fruits) was significantly positively correlated with regular breakfast consumption and a significant positive path to a well-balanced diet. Among male university students, regular breakfast consumption and a planetary health diet may lead to a well-balanced diet.

The delayed effects of radiation alone and combined with skin injury on the kidney are poorly understood. We aimed to unravel and compare the inflammatory, oxidative stress, and survival signaling pathways in the kidney cortex before mice manifested renal dysfunction after these two injuries. Mice were analyzed 30 days post irradiation (9.5 Gy for radiation alone, 9.0 Gy for radiation combined with a skin wound). Radiation alone did not significantly alter BUN, NGAL, or KIM-1 protein levels, indicating preserved kidney function. However, the combined injury had increased KIM-1 protein levels, indicating a nuanced effect on renal health. Radiation and combined injury activated distinct inflammatory pathways. Radiation increased STAT3-Y705 phosphorylation, while combined injury boosted STAT1-Y701 phosphorylation. Additionally, radiation increased mRNA abundance of IFNγR1, IFNγR2, heparanase and IL-10, while combined injury tended to increase heparanase mRNA levels and reduced IL-4 mRNA levels. Both injuries increased the abundance of HO-1 protein, indicating oxidative stress, but radiation alone also reduced MnSOD and catalase proteins. Both injuries promoted AKT1-S473 phosphorylation and diminished p53 protein levels, suggesting inhibition of apoptosis. In summary, despite the distinct activation of inflammatory and oxidative stress pathways, both radiation alone and combined injury activated protective mechanisms such as HO-1 and AKT1, offering insights into molecular events before manifesting renal dysfunction.

Objective: This prospective study aimed to compare the efficacy of caudal block (CB) and inguinal block (IB) for providing additional analgesia during unilateral orchidopexy. Methods: Seventy-two boys aged &lt;48 months, classified as ASA I/II, were assigned into CB (n=37) and IB (n=34) groups. Outcome measures included intra- and postoperative analgesic requirements, pain scores, and administration duration. Additional intraoperative analgesia was administered for a 10% increase in heart rate, while postoperative pain was assessed using the Children's and Infants Postoperative Pain Scale (CHIPPS), with scores &gt;4 prompting supplementary analgesia. Monitoring extended for 24 hours post-surgery. Results: CB significantly reduced the need for intraoperative (p&lt;0.001) and early postoperative (p=0.008) analgesia compared to IB. Although the CB group exhibited a slightly higher but non-significant analgesic requirement on the ward. No clinically relevant side effects were observed in either group. Conclusion: Both CB and IB are effective and safe methods for providing regional analgesia during orchidopexy. CB demonstrated superior efficacy intraoperatively and in the early postoperative period, while IB may offer advantages in the later recovery phase. However, additional analgesia is often required for orchidopexy, particularly in outpatient settings.

Solar energy has emerged as a promising alternative to traditional fossil fuels due to its abundant availability and sustainability. Solar cells, the fundamental units of solar energy conversion, have undergone significant advancements in fabrication techniques to enhance their efficiency, durability, and cost-effectiveness. This review aims to provide a comprehensive overview of various methods employed in the preparation of solar cells, including thin-film, crystalline silicon, organic, and perovskite-based technologies. By analyzing recent research developments, challenges, and future prospects, this article sheds light on the evolving landscape of solar cell fabrication, contributing to the ongoing efforts in achieving widespread adoption of solar energy.

Land cover segmentation, a fundamental task within the domain of remote sensing, boasts a broad spectrum of application potential. In this article, we focus on the land cover segmentation tasks and complete the following research work: Firstly, to address the issues of uneven distribution of foreground and background and significant differences in target scales in remote sensing images, we propose a decoder called MDCFD based on multi-dilation rate convolution fusion. The decoder utilizes dilated convolution to expand the receptive field, enhancing the model's ability to capture global features and thus improving the model's ability to distinguish between foreground and background. Meanwhile, we design a multi-dilation rate convolution fusion module (MDCFM), which fuses the outputs of different dilation rate convolution layers. Secondly, aiming at the problems of diverse scenes, significant differences between categories, and many background interferences in remote sensing images, we propose a hybrid attention module called LKSHAM based on large kernel convolution. This module combines spatial attention and channel attention mechanisms and combines the two attention modules in series. By introducing large kernel convolution, the model's ability to extract contextual information is improved. At the same time, we adopt a strategy of decomposing large kernel convolution into multiple depthwise convolutions to reduce computational complexity. The improved network models designed by this paper can achieve an improvement of over 1.1% in the mIoU metric on segmentation tasks on the Potsdam and Vaihingen datasets.

Silica on Silicon is a major optical integration platform, while the emergent class of integrated Laser written circuits' platform offers additionally high customizability, and flexibility for rapid prototyping. However, the inherent waveguides' low core/cladding refractive index contrast characteristic compared to other photonic platforms in silicon or silicon nitride, sets serious limitations for on-chip efficient coupling with single photon emitters, like semiconductor nanowires with quantum dots limiting the applications in quantum computing. A new light coupling scheme proposed here overcomes this limitation providing means for light coupling >50%. The scheme is based on the incorporation of an optical microsphere between the nanowire and the waveguide, properly optimized and arranged in terms of: size, refractive index, distance of microsphere between nanowire and waveguide. Upon suitable design of the optical arrangement, the photonic nanojet emitted by the illuminated microsphere excites efficiently the guided eigenmodes of the input channel waveguide, thus launching light with high coupling efficiency. The method is tolerant in displacements, misalignments, and imperfections and is fabricationally feasible by current state of the art techniques. The proposed method enables the on-chip multiple single photon emitters' integration thus allowing the development of highly customizable and scalable quantum photonic integrated circuits for quantum computing.

We present a comprehensive database of near-shore wind observations that were carried out during the experimental campaign of the RUNE project. RUNE aims at reducing the uncertainty of the near-shore wind resource estimates from model outputs by using lidar, ocean, and satellite observations. Here we concentrate in describing the lidar measurements. The campaign was conducted from November 2015 to February 2016 at the west coast of Denmark and comprises measurements from eight lidars, an ocean buoy and three types of satellites. The wind speed was estimated based on measurements from a scanning lidar performing PPIs, two scanning lidars performing dual synchronized scans, and five vertical profiling lidars, of which one was operating offshore on a floating platform. The availability of measurements is highest for the profiling lidars, followed by the lidar performing PPIs, those peforming the dual setup, and the lidar buoy. Analysis of the lidar measurements reveals good agreement between the estimated 10-m wind speeds, although the instruments used different scanning strategies and measured different volumes in the atmosphere. The campaign is characterized by strong westerlies with occasional storms.

Georgia is ranked fifth highest among states for rates of HIV diagnosis. About 4% of persons living with HIV infection in the United States reside in Georgia, and almost 19% of these people do not know their HIV status. The present study examined the trends and associated factors of HIV testing among adults in Georgia between 2010 and 2014 by analyzing data of the Behavioral Risk Factor Surveillance System (BRFSS). A total of 30,791 persons aged ≥18 years were identified who responded to the question “Have you ever been tested for HIV?” Overall, there were 11,543 respondents who had been tested for HIV, with a decrease in percentage from 49.4% in 2010 to 43.7% in 2014 (p<0.001). Factors associated with HIV testing were being black (p<0.001), being younger than 55 years (p<0.001), single (p=0.02), attaining education level above high school (P<0.001), engaging in HIV high-risk behaviors (p<0.001), and not having healthcare coverage (p=0.03). Overall in Georgia, there has been a decline in the temporal trend of HIV testing, and more than half of adults have never been tested for HIV. For reducing HIV transmission in Georgia, enhancing access and utilization of HIV testing should be a public health priority.

Recent advancements in mass spectrometry have significantly enhanced our understanding of complex lipid profiles, opening new avenues for oncological diagnostics. This review highlights the importance of lipidomics in the comprehension of certain metabolic pathways and its potential for the detection and characterization of various cancers, in particular melanoma. Through detailed case studies, we demonstrate how lipidomic analysis has led to significant breakthroughs in the identification and understanding of cancer types and its potential for detecting unique biomarkers that are instrumental in its diagnosis. Additionally, the review addresses the technical challenges and future perspectives of these methodologies, including their potential expansion and refinement for clinical applications. The discussion underscores the critical role of lipidomic profiling in advancing cancer diagnostics, proposing a new paradigm in how we approach this devastating disease, with particular emphasis on its application in comparative oncology.

In an era characterized by technological disruption and unprecedented challenges posed by the COVID-19 pandemic, this scholarly investigation explores the role of Artificial Intelligence (AI) in shaping Leadership Dynamics in Higher Education Institutions (LDHE) within the specific socio-cultural and regulatory environment of China. Utilizing Structural Equation Modeling (SEM) as operationalized through the SMART_PLS software, this research harnessed data from a robust sample of 381 key stakeholders in China higher education. The study's empirical findings indicate a noteworthy impact of AI-informed decision-making processes on LDHE, which was further mediated by the variable of AI Literacy among leadership. Moreover, the consequences of the ongoing pandemic served as a moderating factor in this relationship. These nuanced outcomes not only contribute to the theoretical discourse surrounding educational leadership and technological integration but also provide actionable insights for policy formulation and institutional strategies in an increasingly complex educational landscape.

Semi-continuous data are very common in the social science and economics. In this paper, a Bayesian variable selection procedure is developed to assess the influence of exogenous factors including observed and unobserved on the semi-continuous data. Our formulation is based on the two-part latent variable model with polytomous response. We consider two schemes for the penalties of regression coefficients and factor loadings: the Bayesian spike and slab bimodal prior and the Bayesian lasso prior. Within the Bayesian framework, we implement Markov Chains Monte Carlo sampling method to conduct posterior inference. To facilitate posterior sampling, we recast the logistic model in part one as the norm-like mixture model. Gibbs sampler is designed to draw observations from the posterior. Our empirical results show that with suitable hyper-parameters, the spike and slab bimodal method slightly outperforms the Bayesian lasso in the current analysis. Finally, a real example related to the China household finance survey is analyzed to illustrate the application of the methodology.. .

This paper proposes two max-pooling engines, named the RTB-MAXP engine and the CMB-MAXP engine, with a scalable window size parameter for FPGA-based convolutional neural network (CNN) implementation. The max-pooling operation for the CNN can be decomposed into two stages, i.e., a horizontal axis max-pooling operation and a vertical axis max-pooling operation. These two one-dimensional max-pooling operations are performed by tracking the rank of the values within the window in the RTB-MAXP engine and cascading the maximum operations of the values in CMB-MAXP engine. Both the RBM-MAXP engine and the CMB-MAXP engine were implemented using VHSIC Hardware Description Language (VHDL) and verified by simulations. They have been employed for and tested in our CNN accelerator targeting at the CNN model YOLOv4-CSP-S-Leaky for object detection.

Depressive disorder in childhood and adolescence is a highly prevalent mood disorder that tends to recur throughout life. Untreated mood disorders can adversely impact a patient's quality of life and cause socioeconomic loss. Thus, an accurate diagnosis and appropriate treatment is crucial. However, until now, diagnoses and treatments are conducted according to clinical symptoms. Objective and biological validation are lacking. This may result in a poor outcome for patients with depressive disorder. Research has been conducted to identify the biomarkers that are related to depressive disorder. Cumulative evidence has revealed that certain immunologic biomarkers in-cluding brain-derived neurotrophic factor (BDNF) and cytokines, gastrointestinal biomarkers, hormones, oxidative stress, and certain hypothalamus-pituitary axis biomarkers are associated with depressive disorder. This article reviews the biomarkers related to the diagnosis and treatment of pediatric depressive disorders. To date, clinical biomarker tests are not yet available for diagnosis or for the prediction of treatment prognosis. However, cytokines such as Interleukin-2, interfer-on-gamma, tumor necrosis factor-alpha, and BDNF have shown significant results in previous studies of pediatric depressive disorder. These biomarkers have the potential to be used for diagnosis, prognostic assessment, and group screening for those at high risk.

Pesticides are chemical compounds or mixtures of hazardous substances that are used by humans to increase and protect crops from pests and control disease-carrying insects. Because of its wide use, it may be poisonous to helpful and non-targeting plants and animals. Spraying or spreading pesticides over whole fields of crops can cause runoff to transfer the chemicals into aquatic ecosystems, and wind can carry the chemicals to nearby grazing regions, farms, and populated areas, where they can endanger other animals. This review summarises recent studies on pesticide combination toxicity to aquatic biota and approaches used to anticipate toxic effects. When toxicants harm economically significant organisms that humans consume, the negative effects become more severe and can cause stress conditions, vital organ damage, biochemical damage, or even the death of living things in both terrestrial and aquatic environments. Pesticides are highly toxic to aquatic organisms such as snails, fish, etc. Neurological dysfunction in freshwater organisms is also caused by pesticides. By producing excessive ROS, pesticides can cause severe biochemical and histological changes in freshwater organisms. So, it is therefore easy to understand the attention of the public on these substances. Because aquatic organisms play a major part in the food chain. However, through the biomagnification process, the quantity of pesticides increases in the higher organisms through the food chain. Which results play a terrific role in the higher organism’s body. So, It's essential to comprehend the way that insecticides work on aquatic organisms. In this review article, we are focusing on the way that pesticides work, which will help in the system of biomonitoring.

Generating executable code from natural language instructions using Large Language Models (LLMs) presents challenges such as semantic understanding and handling ambiguous input. This study focuses on the SantaCoder model and explores the impact of in-context learning on code generation using the MBPP and HumanEval datasets for evaluation. Our results demonstrate significant improvements in three key metrics (defined in the paper): correctness@k, similarity@k and pass@k. To address the problem of selecting optimal demonstrations to maximize correctness and pass rates, we investigate two methods: latent concept selection and random selection in this paper. These findings highlight the effectiveness of in-context learning and the critical role of demonstration selection in enhancing the accuracy, efficiency, and versatility of the SantaCoder model in code generation.