This study explores the potential of natural compounds, including Daidzin, Luteolin, and Silibinin, as inhibitors of human monoamine oxidase B (MAO-B) for the treatment of Parkinson's disease. Docking simulations were performed using Autodock Vina with Pyrx program to evaluate the binding affinities of these compounds with MAO-B. Results indicate that Daidzin, Luteolin, and Silibinin exhibit promising binding affinities with MAO-B, with Daidzin demonstrating the highest affinity. Toxicity parameters were further predicted using the PkCSM Server, confirming the low toxicity of these compounds. Overall, the findings suggest that Daidzin, Luteolin, and Silibinin have the potential to be effective and safe treatments for Parkinson's disease through their inhibition of MAO-B. Further experimental validation is warranted to support their therapeutic efficacy in clinical settings.

“All diseases originate in the gut.” Hippocrates (400 BC) A healthy gut microbiome via the gut-brain-axis (GBA) elevates heart rate variability (HRV), a general measure of health and well-being. A dysbiotic gut microbiome, low in biodiversity and butyrate producers, alters tryptophan metabolism with release of proinflammatory cytokines, predominantly TNF-α, IL-6, and IL-1β. These also characterize chronic inflammation, oxidative stress, and a multitude of diseases, all exhibiting low HRV. Gut dysbiosis upregulates IFN-γ and with it IDO (indoleamine 2,3 dioxygenase). Tryptophan pivots from serotonin synthesis to that of IDO induced kynurenine, increasing the kynurenine to tryptophan ratio (KTR). An elevated KTR is positively linked to neurodegenerative and autoimmune diseases and negatively linked to HRV. Elevated IDO activity is not only enzymatic but also an intracellular signal transducer potentiated by TGF-β. This cytokine is the primary determinant of the TME. Also proposed is the gut-lung dysbiosis concept and consequent degradation of ACE2 (richest in lungs and gut). Leaky gut induced autoantibodies related to G-protein coupled receptors (GPCRs) in combination with increased Ang II further potentiate oxidative stress. Aldosterone and paroxysmal orthostatic tachycardia syndrome (POTS) paradoxes are highlighted in the context of GPCR and gut dysbiosis, and the role of Candida is explored. The triple play of a prebiotic (d-mannose), probiotic (bifidobacteria and lactobacilli), and postbiotic (butyrate) might improve intestinal barrier integrity, oppose entry of GPCR antigens, suppress the inflammatory cytokine triad, balance IFN-γ and TGF-β, suppress oxidative stress, depress KTR, elevate HRV, and extend lifespan and its quality.

With continued scaling of semiconductor devices , the value of predictive analysis through 1 accurate quantum transport modeling is exponentially increasing. Quantum transmitting Boundary 2 method (QTBM) has been a well-known method of choice to model quantum transport in simple 1-D 3 devices. Here, we present an extension of the QTBM to the 2-D domain and apply it for more realistic 4 devices for accurate performance analysis.

The necessity for effective intrusion detection systems (IDS) in big data environments has grown critical due to the rising prevalence of big data systems and the rising amount of security threats. Applying conventional intrusion detection methods to the enormous and intricate data produced by big data ecosystems presents difficulties. Deep learning, has proven to be exceptionally adept at deciphering complex, large-scale data. This study proposes a Deep Learning-based Intrusion Detection System (IDS) created specifically for the Big Data environment. Traditional intrusion detection systems struggle to efficiently identify and prevent cyber threats due to the ever-increasing volume and complexity of data in current networks. We suggest an IDS that makes use of Deep Learning (CNN, LSTM, GAN, etc.), to address this problem. These cutting-edge neural network topologies give the system the ability to process and analyze massive amounts of data for precise intrusion detection. Data collection, data preprocessing, feature engineering, DL model training, intrusion detection, warning generation, and reaction are some of the crucial parts of the suggested IDS. The data collection module mines the Big Data environment for network traffic, system logs, and security event information. To make sure the data is suitable for analysis, it is preprocessed. To improve the detection abilities of the DL models, important features are extracted from the data using feature engineering approaches.

There is a great need to develop research-based models for supporting collaboration between educational institutions. Collaboration models are needed, for example, to assist the transition from lower educational level to higher education or from higher education to work life. In this research, collaboration was conducted through a joint upper-secondary school and university course that addressed global challenges by using a project-based learning approach. There is a shortage of research exploring students’ perceptions of collaboration. Therefore, the main purpose of this qualitative case study is to explore the relevance of the joint course for students and university students. The research was guided by the following research question: What kind of relevance did the students experience in the joint project-based learning course? The data was gathered using questionnaires, interviews, and reflective study reports. The data was analyzed via theory-based content analysis where research-oriented relevance model was used as the analysis framework. The analysis framework enabled categorizing experienced relevance on individual, vocational and societal dimensions. Altogether, the analysis produced 7 relevance categories for upper-secondary students and 9 for university students. According to the analysis, upper-secondary school students felt that the course offered the most on an individual relevance dimension whereas university students experienced the vocational relevance dimension most diverse. As the main conclusion, this research produced new insights on the experienced relevance of upper-secondary level and higher education cooperation from the students’ point of view. The acquired knowledge can be useful for everyone developing new cross-institutional cooperation models.

This cross-sectional study investigates the impact of Virtual Private Networks (VPNs) on Nigerians during the 2021 Twitter ban, prompted by the Nigerian government's suspension of Twitter operations following the deletion of a tweet by the President. The study aims to analyze the frequency and awareness of VPN and Twitter usage among Nigerians during the ban, addressing specific objectives. Employing a survey research method, data was collected from 400 respondents through online and offline questionnaires. Descriptive statistical tools were used for data analysis, revealing significant findings. Results indicate a substantial decrease in Twitter usage during the ban, with IPVanish emerging as the preferred VPN brand. The study also highlights an increase in VPN awareness post-ban, emphasizing the need for educational initiatives. The demographic analysis reveals a dominant age group of 21 to 25 among social media users. Overall, the research underscores the complex interplay between social media dynamics, VPN adoption, and demographic factors, emphasizing the importance of nuanced regulatory approaches and ongoing user education in Nigeria's online landscape.

This study employs molecular docking experiments to investigate the binding interactions of Hypericin with key proteins implicated in Alzheimer's disease (AD). Hypericin demonstrated a significant binding energy of -10.1 kcal/mol with ABAD (3-hydroxyacyl-CoA dehydrogenase type II). The analysis revealed multiple binding interactions, including hydrogen bonds with arginine 6, serine 7, and glutamic acid 140, as well as hydrophobic bonds involving leucine 11, aspartic acid 142, and aspartic acid 86. These findings illuminate the intricate molecular interactions between Hypericin and ABAD, suggesting its potential as a lead compound for further therapeutic development in the context of Alzheimer's disease. Additionally, a parallel docking investigation was conducted for Beta-secretase 1 (BACE1), a protein pivotal in the generation of beta-amyloid peptides—a hallmark of Alzheimer's disease. Inhibiting BACE1 activity is considered a promising therapeutic strategy for AD. Computational analyses suggest that Hypericin may serve as a potential inhibitor of BACE1. Molecular Docking results reveal a robust binding affinity between Hypericin and BACE1, supported by a significant binding energy score of -10.3 kcal/mol. Notably, both ABAD and BACE1 exhibit high binding affinity with Hypericin. This theoretical exploration provides an initial understanding of the intricate molecular pathways involved in Alzheimer's disease and proposes Hypericin as a potential therapeutic compound for mitigating its progression.

This study aimed to overcome the difficulty of conducting the horizontal-well cavity leaching test in the field and to investigate the long-term stability of the horizontal-well salt-cavity natural gas storage. The simulation test design is combined with the similarity theory to study the cavity expansion characteristics and the influence law of cavity leaching parameters. Through the design of a rubber hose connection, an integrated closed test system for multi-stage horizontal-well cavity leaching and brine drainage was built. The test system also realises the repeatable backward movement of the injection well during the test. A similarity simulation of the test design was carried out, and the test platform was constructed to carry out multi-stage horizontal-well leaching tests with a nitrogen cushion. In the horizontal-well leaching tests with a nitrogen cushion, the influence laws of the well spacing, flow rate and liquid level position on cavity expansion were investigated. Based on the morphological characteristics of the horizontal-well cavity, a numerical model of the horizontal-well salt cavity was developed, which reflects the real cavity morphology leached in the test. The long-term stability of the horizontal-well salt-cavity natural gas storage under different internal pressures was investigated through numerical simulation.

Energy communities are key actors in the energy transition since they optimally interconnect renewable energy capacities with the consumers. Despite versatile objectives, they usually aim at improving the self-consumption of renewable electricity within low voltage grids to maximize revenues. In addition, energy communities are an excellent opportunity to supply renewable electricity to regional and national energy systems. However, effective price signals have to be designed to coordinate the needs of the energy infrastructure with the interests of these local stakeholders. The aim of this paper is to demonstrate the integration of energy communities at the national level with a bottom-up approach. District energy systems with a building scale resolution are modelled in a mixed integer linear programming problem. The Dantzig-Wolfe decomposition is applied to reduce the computational time. The methodology lies within the framework of renewable energy hub, characterized by a high share of photovoltaic capacities. Both investments into equipment and its operation are considered. The model is applied on a set of five typical districts and weather locations representative of the Swiss building stock. The extrapolation to the national scale revealed a heterogeneous photovoltaic potential throughout the country. Present electricity tariffs promote a maximal investment into photovoltaic panels in every region, reaching an installed capacity of 67.2 GW and generating 80 TWh per year. Since the national PV capacity needed is forecast at 15.4 GW peak, coordinated investments between local and national actors are needed to prevent dispensable expenses. An uncoordinated design is expected to increase the total costs for residential energy systems by 43.2% and curtails 48.2% of local renewable electricity.

Physical properties like shape, volume and size affect the dynamics of biological systems. Along these lines, we focus on the topological properties of biological fluids and their biochemical and physiological outcomes. We take as a paradigmatic example the salivary fluid and describe how its topological features may affect the physiopathology of the oral cavity. Topological approaches assess the general properties of saliva, ignoring small-scale physical details such as density, flow rate, stiffness, viscosity. Specifically, the mucin aggregates scattered in the salivary fluid can be tackled in terms of topological holes, i.e., vortical clusters that modify the direction, flow, impulse, local rate-of-change and velocity of saliva. While the current methodological approaches are inclined to remove the effects of impurities assessing systems as homogeneous structures, we argue that the occurrence of mucins breaks up the salivary fluid’s homogeneity, leading to unexpected biophysical modifications. We suggest that every collected salivary sample is not reliable for accurate clinical and experimental investigation, since it displays highly local as well as variable chemical, physical and biological features, not reflecting the current physiological state of the oral cavity. Therefore, the assessment of a single salivary sample is not fully reproducible and cannot provide information about the biophysical, enzymatic and microbiological content of the whole saliva. In sum, the very topological features of the saliva - such as volume, shape, antipodal cells, vortex area, whirling fluid mass, segmentation, discretization, triangulation, node numbering - produce unnoticed biological consequences and network connectivity features with intriguing operational implications.

A paddle wheel aerator is developed in this research, which includes a wireless sensor network for measuring the water quality in the aquaculture of marine shrimp ponds. It can also move to the desired position to fill oxygen and measure water quality. A basic requirement is good standard water quality to prevent shrimp from epidemics and improve production. The water quality paddle wheel aerator applies a microcontroller and sensors to measure eight parameters of water quality. These water quality parameters are observed on the web application via an IoT module. The movement system of the water-quality paddle wheel aerator consists of a LiDAR, GPS, and remote RF signal. Each item of data is recorded immediately on the cloud server while the water-quality paddle wheel moves in the marine shrimp farm. The controlled paddle wheel aerator is harnessed automatically to enhance precisely the spatial monitoring resolution of the measurement system installed, which is needless for a multiple measurement system with high cost of investment. Also, farmers can access real data through the Line application. Hence, they are able to plan and control a good environment for aquaculture, preventing the occurrence of various epidemics and decomposing organic matter in the pond.

The design of school environments plays a pivotal role in promoting student wellness, mindfulness, and socio-emotional learning (SEL). This article explores the integration of Environment Behaviour Studies (EBS) concepts into school design to enhance students' overall well-being and academic success. It highlights the importance of indoor environmental quality, ergonomic and flexible learning spaces, and biophilic design in fostering a healthy and engaging learning atmosphere. Additionally, the article delves into the creation of mindfulness spaces, sensory-friendly environments, and the use of colour and aesthetics to support emotional regulation and mental health. By examining case studies of successful implementations, the article underscores best practices for designing schools that promote positive social interactions, ensure safety, and reflect community values. Ultimately, this comprehensive approach to school design aims to nurture holistic development, support socio-emotional learning, and prepare students for lifelong success.

Abstract: This article aims to better understand the mechanisms that connect climate change perceptions and general willingness to engage in pro-environmental behavior using Spanish cross-sectional data (N = 403). To do this, we first developed and validated the General Willingness for Environmental Behavior Scale (GWEBS), which includes the classical approach of voluntarily doing new actions but also actions implying not doing things (degrowth) and actions forced by social constraints. The exploratory and confirmatory factor analysis showed a good fit for the one-factor structure, which had adequate validity based on their relationship with other variables. Additionally, the GWEBS distinguished between women and men, left- and right-oriented people, and people who belonged to pro-environmental groups and people who did not. In the second place, we tested the parallel mediator role of eco-anxiety and trust in science in the relationship between climate change perceptions and the GWEBS. The results showed that eco-anxiety, fully, and trust in science partially mediated such a relationship, making them crucial to mobilize the intention to act following the perception. This study contributes to our understanding of the psychological mechanisms that eventually drive pro-environmental behaviors and provides a clear direction for future research.

Flowering in cassava is crucial for generation of botanical seed for breeding. However, most farmer preferred genotypes are poor at flowering, exhibit great disparity in time and amount of flowering or never flower. To elucidate the genetic basis of such a flowering behaviour, 293 diverse cassava accessions were evaluated for flowering traits under two locations and seasons in Uganda. Genotyping by the Diversity Array Technology Pty Ltd. (DArTseq) platform identified 24,040 single-nucleotide polymorphisms (SNPs) distributed on the 18 cassava chromosomes. Population structure analysis using principal components (PC) and kinships showed clustering, the first five PCs accounted for 49.2% of the observed genetic variation. Linkage disequilibrium (LD) estimation was averagely 0.32 at a distance of ~2850kb (kilo base pairs). Polymorphism information content (PIC) and minor allele frequency (MAF) were 0.25 and 0.23, respectively. Genome-wide association study (GWAS) analysis uncovered 53 significant marker-trait associations (MTA) with flowering traits involving 27 loci. Two loci, SNPs S5_29309724 and S15_11747301 were associated with all the flowering traits. Using five of the 27 SNPs with Phenotype_Variance_Explained (PVE) ≥ 5%, 37 candidate genes were identified in the peak SNP sites located within 50kb upstream or downstream, most were associated with branching traits. Eight of the genes, orthologous to Arabidopsis and other plant species, had known functional annotations related to flowering, e.g. eukaryotic translation initiation factor and myb family transcription factor. This study identified genomic regions associated with flowering in cassava, the identified SNPs could be useful in marker-assisted selection to overcome hybridization challenges like unsynchronized flowering, and candidate gene validation.

This work focuses on an inland area of North Sardinia (Italy), which is currently subject to depopulation and economic crisis because it is not affected by the summer tourism typical of the region. Despite this, the area shows an interesting architectural and natural heritage, as of today insufficiently known and valued. Therefore, the purpose of this paper is to illustrate the application of the Conjoint Analysis methodology on this case study aimed at supporting processes of valorisation, diversification of the tourist offer and promotion of the through the detection of the preferences of a sample of residents and visitors on a set of 9 cards (itinerary profiles) which also promote the peculiarities of small rural centres. Thus, by valorising the material and immaterial heritage and their intrinsic characteristics, it is shown that inland areas can generate an economy by offering new types of tourism, not just the typically invasive summer and maritime tourism. The research, therefore, seeks to estimate the economic value of the area from a public point of view through the WTP measured by a questionnaire of 600 interviews between inhabitants (300) and tourists (299).

The main objective of this review is to determine the main risks that agricultural workers are exposed to during pesticide application, which may have a harmful effect on their health and on public health. This systematic review was based on the PRISMA guidelines. A search for articles was conducted in the Medline/PubMed, ScienceDirect, and Web of Science databases. Fifteen articles were selected considering their assessment of agricultural workers' knowledge, perceptions, attitudes, practices, and behaviours, identifying the main risks and risk factors for disease associated with the unsafe handling of pesticides. The main risk factors identified were age, education, pesticide safety training, farming experience, and contact with other farmers/intermediaries resulting in pesticide access. The most frequent risk behaviours were: application of pesticides without personal protective equipment (PPE), incorrect disposal of empty packaging and waste, and undervaluation of label information, as well as other unsafe practices. A multidisciplinary and more effective training must be delivered in order to enhance pesticide safe usage. This will empower workers to adopt more conscious and safer behaviours while using pesticides.

Wash’Em is a process that supports humanitarians in assessing and designing rapid but context-specific hygiene programmes in crises or outbreaks. The process consists of training implementers, using tools to learn from populations, and entering findings into a software which generates contextualised activities. A process evaluation of Wash’Em use was conducted in a drought-affected area in Midland province, Zimbabwe. Data was collected during the programme design and following implementation, using a mix of qualitative methods. Findings were classified against the intended stages of Wash’Em, and the evaluation domains were defined by the UKRI Medical Research Council. The Wash’Em process was not fully implemented as intended. An abridged training was utilised, some of the tools for learning from populations were omitted, many of the recommended activities were not implemented, the delivery modalities were different from intended, the budget available was minimal, and the number of people exposed to activities were fewer than hoped. Despite these ‘on the ground’ challenges and adaptations, the Wash’Em process was considered feasible by implementers and was seen to be less top-down than most programme design approaches. The populations exposed to the intervention found the activities engaging, understood the content, and reportedly took action to improve handwashing behaviour.

This research paper examines the evolution of car purchasing behaviour among consumers in India from 2010 to the present. Through extensive literature review and questionnaire survey, it explores the reasons behind the changing preferences and decision-making processes of consumers in the Indian automobile market. The study draws upon various sources, including market research reports, industry publications, academic studies, and consumer surveys, to provide a comprehensive analysis of the factors influencing car purchasing behaviour in India over the last decade. The findings of this research paper can help automakers and marketers better understand consumer preferences and develop effective strategies to cater to the evolving needs of the Indian car market.

The genetic systems of Paspalum species have not been extensively studied. We analysed the ploidy, reproductive mode, mating system, and fertility of four Paspalum species - P. durifolium, P. ionan-thum, P. regnellii, and P. urvillei. An analysis of 378 individuals from 20 populations of north-eastern Argentina was conducted. All populations of the four Paspalum species were pure tetraploid and had a sexual and stable reproductive mode. However, some populations of P. durifolium and P. ionanthum showed low levels of apospory. Populations of P. durifolium and P. ionanthum had low seed sets under self-pollination but were fertile under open pollination, showing that self-incompatibility likely caused self-sterility. In contrast, populations of P. regnellii or P. urvillei showed no evidence of apospory and seed set in both self- and open pollination conditions were high, suggesting that they are self-compatible, due to the absence of pollen-pistil molecular in-compatibility mechanisms. The evolutionary origin of the four Paspalum species could explain these differences. This study supplies valuable insights into the genetic systems of Paspalum species, which could have implications for their conservation and management.

This study analysed through the perspective of networks the association between physical activity (PA), sedentary behaviour (SB), and cardiovascular risk factors in overweight low-income schoolchildren from the perspective of complex systems. Methods: The sample consisted of 41 overweight children between 6 and 10 years old (56% girls). PA and SB were analysed by accelerometer, and the measures of cardiovascular factor risk were: anthropometric and hemodynamic measurements, body fat, lipid profile and glucose, cardiorespiratory fitness (CRF), left ven-tricular mass (LVM), and Sokolov-Lyon. Network analysis with Boot-strap-1000 was performed to analyze the association between PA, SB and the cardiovascular risk factors. Results: Moderate to vigorous PA was positive related with Waist circumference (WC; 0.499), HDL-C (0.307), and CRF (0.276), and negatively associated with BMI (-0.251) and Fat (-0.341). For SB, positive associations were seen with WC (0.326), CRF (0.296), LVM (0.250) and Sokolov (0.215). Adicionalment, the centrality indicators highlighted WC as the most important variable in the network. Conclu-sion: Interventions that aim to mitigate the harmful effects of obesity on cardiovascular risk factors in overweight children should consider WC as an important variable in of system.

The marine red algae Asparagopsis armata is an invasive species which competitive advantage arises from the production and release of large amounts of toxic compounds to the surrounding invaded area, reducing the abundance of native species. The main objective of this study was to evaluate the effects of this invasive seaweed on marine invertebrates by exposing the common prawn Palaemon elegans and the marine snail Gibbula umbilicalis to the exudate of this macroalgae. The seaweed was collected and placed in tanks, for 12 hours, in the dark in a 1:10 ratio. Afterwards the media containing its secondary metabolites was collected for further testing. Lethal and sublethal effects of A. armata were investigated. Biochemical biomarkers responses associated with energy metabolism (lactate dehydrogenase, LDH; electron transport system activity, ETS; content in lipids, proteins and carbohydrates) were analysed. The biomarker responses showed invertebrates’ physiological status impairment after exposure to low concentrations of this algae exudate. Highest concentrations of exudate significantly increased lipid content in both organisms. In the shrimp, protein content, ETS, and LDH were also significantly increased. On the contrary, these parameters were significantly decreased in G. umbilicalis. A behavioural impairment was also observed in G. umbilicalis exposed to A. armata exudate, with reduction in feeding consumption. These results represent an important step in the research of natural toxic exudates released to the environment and prospective effects of this seaweed in invaded communities under increasing global change scenarios.

Obesity is one of the main causes of morbidity and mortality, and food addiction has been considered one of its phenotypes. The study aims to determine the effectiveness of physical activity (PA), exercise, and sedentary behaviour management in attenuating food addiction in obese and overweight healthy adults. A search strategy was undertaken using MEDLINE, CENTRAL, PsycINFO, and CINAHL until April 2019. A total of 295 studies were found from which seven studies, after duplicates were removed, were included. The acute effect of PA of moderate intensity had an effect on attentional bias, craving, and sweet taste perception, although no difference was observed between genders and body mass index groups. No effect was observed on the hedonic and reward value. The acute effects of PA of moderate intensity may be a useful tool to control the levels of food addiction. More research is needed to clarify if this effect also occurs during chronic application, at different doses and types of PA, and for all populations.

The reinforcement of concrete by using polyolefin fibres may be considered in structural design to meet the requirements of the applicable code rules. In order to achieve a reliable use of such a composite material, use of full-scale real structures is needed. The conversion of lab testing data into real practice properties is challenging and significantly influenced by various aspects, among which the size effect is a key one. Given that the available literature does not report coinciding conclusions about such an effect on quasi-brittle materials reinforced with fibres, further research is justified. Therefore, this work studies the behaviour of notched beams with three proportional sizes by using self-compacting polyolefin reinforced concrete with a fibre volume fraction of 1.1%. Flexural testing was carried out according to the standard EN-14651, with the results revealing the existence of the size effect. In addition, a reduction of the residual strength identified in the larger specimens was observed in fracture surfaces with equal fibre content.

Recent research has revealed surprisingly important connections between animals’ microbiome and social behaviour. Social interactions can affect the composition and function of the microbiome; conversely, the microbiome affects social communication by influencing the hosts’ central nervous system and peripheral chemical communication. These discoveries set the stage for novel research venues focusing on the evolution and physiology of animal social behaviour in relation to microbial transmission strategies. Here, we discuss the emerging roles of teleost fish model candidates and their key potential for advancing research fields linked to sociality and microbial regulation. We argue that fish models, such as the zebrafish, sticklebacks, guppies and cleaner-client dyads, will provide valuable insights into the roles of microbiome in shaping social behaviour and vice versa, while also being of direct relevance to the food and ornamental fish trades.

OBJETIVE: This study analyses the views of four groups of healthcare professionals who may play a role in the management of suicidal behaviour. The goal was to identify key factors for suicide prevention in different areas of the healthcare system. METHODOLOGY: Qualitative research was conducted using focus groups made up of different healthcare professionals who participated in the identification, management and prevention of suicidal behaviour. Professionals included were primary care physicians, psychologists, psychiatrists and emergency physicians. RESULTS: ‘Suicide’ was amongst the most relevant terms that came up in discussions most of the times it appeared associated with words such as ‘risk’, ‘danger’ or ‘harm’. In the analysis by categories, the four groups of professionals agreed that interventions in at-risk behaviours are first in importance. Prevention was the second main concern with greater significance among psychiatrists. DISCUSSION: Primary care professionals claim for more time to address patients at risk for suicide and an easier access to and communication with the mental health network. Emergency care professionals have a lack of awareness of their role in the detection of risk for suicide in patients who seek attention at emergency care facilities for reasons of general somatic issues. Mental health care professionals are in high demand in case of self-harm but they would like to receive specific training in dealing with g suicidal behaviour.

Since autism was first recognised, prevalence has increased rapidly. The growing economic as well as social cost to society can only be mitigated by effective interventions and supports. It is therefore not surprising that most governments have developed public policy documents to address the management of autism. Over the past 40-50 years, meaningful evidence has accrued showing that interventions based on the scientific discipline of Applied Behaviour Analysis (ABA) can help people with autism reach their potential. In view of this, nearly all of North America has laws to mandate that ABA-based interventions are available through the health care systems. In contrast, across Europe there are no such laws. In fact, the National Institute for Health and Care Excellence (NICE), the body guiding health and social policy in the UK, concluded that it could not find any evidence to support ABA, and therefore could not recommend it. This paper addresses the reasons for these diametrically opposed perspectives. In particular, it examines what happens when health and social care policy is misinformed about effective autism intervention.

This paper deals with the design and kinematic analysis of a novel mechanism for the elbow joint of an upper-limb exoskeleton, with the aim of helping operators, in terms of effort and physical resistance, in carrying out heavy operations. In particular, the proposed eight-bar el-bow joint exoskeleton mechanism consists of a motorized Watt I six-bar linkage and a suitable RP dyad, which connects mechanically the external parts of the human arm with the corre-sponding forearm by hook and loop velcro and thus, helping their closing relative motion for lifting objects during repetitive and heavy operations. This relative motion is not a pure rotation and thus, the upper part of the exoskeleton is fastened to the arm, while the lower part is not rigidly connected to the forearm, but through a prismatic pair which allows both rotation and sliding along the forearm axis. Instead, the human arm is sketched by means of a crossed four-bar linkage, which coupler link is considered as attached to the glyph of the prismatic pair, that is fastened to the forearm. Therefore, the kinematic analysis of the whole ten-bar mecha-nism, which is obtained by joining the Watt I six-bar linkage and the RP dyad to the crossed four-bar linkage, is formulated to investigate the main kinematic performance and for design purposes. The proposed algorithm has given several numerical and graphical results. Finally, a double-parallelogram linkage, as particular case of the Watt I six-bar linkage, was considered in combination with the RP dyad and the crossed four-bar linkage, by giving a first mechanical de-sign and a 3D printed prototype.

Traditional urban design often overlooks the synchronisation of human and ecological connectivities, typically favouring corridors for ecological continuity. Our study challenges this convention by introducing a computational design approach, Meta-Connectivity, leveraging the deep generative models performing cross-domain translation to integrate human-wildlife landscape connectivity in urban morphology amidst the planetary urbanisation. Utilising chained Pix2Pix models, our research illustrates a novel meta-connectivity design reasoning framework, combining landscape connectivity modelling with conditional reasoning based on deep generative models. This framework enables the adjustment of both human and wildlife landscape connectivities based on their correlative patterns in one single design process, guiding the re-materialisation of urban landscapes without the need for explicit prior ecological or urban data. Our empirical study in East London demonstrated the framework's efficacy in suggesting wildlife connectivity adjustments based on human connectivity metrics. The results demonstrate the feasibility of creating an innovative urban form in which the land cover guided by the connectivity gradients replaces the corridors based on simple geometries. This research thus presents a methodology shift in urban design, proposing a symbiotic approach to integrating disparate yet interrelated landscape connectivities within urban contexts.

HIGHLIGHTS Special relativity has been successfully used to describe the behaviour of particles (Rossi & Hall, 1941), but there is no observation of special relativity in our world. On the contrary, there are at least two paradoxes based on special relativity: the twin paradox (Langevin, 1911) and Ehrenfest's paradox (1909). This paper is presenting a first experiment, based on Ehrenfest's paradox, where an effect of special relativity was expected but not observed. The validity of special relativity in our macro world will be questioned and an alternative will be offered. ABSTRACT After presenting the history of special relativity, the non-simultaneity of special relativity is questionned in our macro world. In addition, some incompatibilities between light clocks and the application of Lorentz transformation are presented. All this indicates some issues with special relativity which appears to be correct only for particles and would be invalid in our macro world. A new theory is presented based on an adaptation of special relativity; this new theory solves the anomalies and could be a solution to the twin paradox. This paper also presents a new experiment and its observation. The preliminary result shows that special relativity has no effect in our macro world and therefore supports the new theory. A lack of special relativistic effects has been observed in the universe (Davis et al., 2004); that is another observation where special relativity doesn't work. That second observation is also explained with the new theory.

This article examines the integration of artificial intelligence (AI) and robotic process automation (RPA) in financial accounting and management, underscoring their role in driving the digital transformation of corporate finance. It discusses the shortcomings of traditional financial processes and highlights the potential of AI and RPA technologies to enhance efficiency, accuracy, and cost-effectiveness. The paper also explores the limitations of RPA, such as its challenges in processing unstructured data and handling complex decision-making scenarios. Looking forward, it considers the future trends in AI and RPA, emphasizing the benefits of cloud technology in scaling automated systems and addressing associated challenges.

The periodontal ligament (PDL) is a complex connective tissue that connects the tooth root to the dental alveolar bone and plays crucial mechanical roles. PDL also exhibits regenerative roles and regulatory functions to maintain per-iodontium integrity and homeostasis. While PDL exposure to oral microbial pathogens is common, virtually nothing is known regarding viral infections of PDL. In particular, human herpes simplex virus type 1 (HSV-1) persistently infects the oral cavity through infections of the oral epithelium, connective tis-sue and neurons. While the oral spread of HSV-1 is generally asymptomatic, this virus has also been implicated in various oral pathologies. In this study, using a primary cell model derived from PDL (PDL-cells), and whole surgical fragments of PDL, we provide evidence supporting the efficient infection of PDL by HSV-1 and the promotions of cytopathic effects. Infection of PDL by HSV-1 was also associated with an acute innate inflammatory response, as il-lustrated by the production of the antiviral interferons and pro-inflammatory cytokines. Furthermore, this inflammatory response to HSV-1 was exacerbated in the presence of bacterial-derived products, such as peptidoglycans. This work therefore highlights the ability of HSV-1 to infect mesenchymal cells from PDL, suggesting that PDL may serve as a viral reservoir for the perio-dontal spread of HSV-1. Moreover, this raises questions about HSV-1 oral pathogenesis, as HSV-1-associated cytopathic and inflammatory effects may contribute to profound alterations of PDL integrity and functioning.

Epithelial barrier damage plays a central role in the development and maintenance of allergic inflammation. The rise in airways epithelial barrier permeability alters the tissue homeostasis and allows the allergen and other external agents penetration. Different factors contribute to barrier impairment, such as eosinophilic infiltrate and allergens proteases action: the eosinophilic cationic proteins and the allergens' proteolytic activity have a central role in contributing to epithelial damage. In the airways, the allergens proteases degrade the epithelial junctional proteins allowing the allergen penetration and the uptake by dendritic cells. The increase in allergen-immune system interactions induce the release of the alarmins and the activation of type 2 inflammatory pathways causing, or worsening, the main symptoms at skin, bowel and respiratory levels. We aim to highlight the molecular mechanisms underlying allergenic proteases-induced epithelial barrier damage and the role of immune response in allergic asthma onset, maintenance and progression. We further will explore clinical and radiological potential biomarkers of airways remodeling in allergic asthma patients.

Avian influenza viruses (AIVs) are highly contagious respiratory viruses of birds, lead-ing to significant morbidity and mortality globally and causing substantial economic losses to the poultry industry. Since their first isolation in 2013, the Asian-origin H5N1 highly pathogenic avian influenza viruses (HPAI) of clade 2.3.4.4b have undergone unprecedented evolution and re-assortment of internal gene segments and have spread to Asia, Europe, Africa, and America, caus-ing outbreaks in all the poultry categories. Novel epidemiological and pathobiological character-istics, distinct from other clades, are specific of clade 2.3.4.4b viruses. Wild waterfowl, the natu-ral reservoir of AIVs, are frequently found infected with clade 2.3.4.4b viruses, which can also cause high morbidity and mortality in these birds. The sustained clade 2.3.4.4b virus circulation in waterfowl has also led to virus infection in other wild bird species, with implications for the conservation of endangered species. Furthermore, clade 2.3.4.4b viruses have been isolated in var-ious wild and domestic mammals worldwide, and critical mutations related to virus adaptation to mammalian species have been identified, raising concerns about virus spillover to humans. The main clinical signs, and anatomopathological findings associated to clade 2.3.4.4b virus infection in birds and non-human mammals are hereby summarized.

: Microplastics and nanoplastics (MNPs) are becoming an increasingly severe global problem due to their widespread distribution and complex impact on living organisms. Apart from their environmental impact, the effects of MNPs on living organisms have also continued to attract attention. The harmful impact of MNPs has been extensively documented in marine invertebrates and larger marine vertebrates like fish. However, the research on the toxicity of these particles on mammals is still limited, and their possible effects on humans are poorly understood. Considering that MNPs are commonly found in food or food packaging, humans are primarily exposed to them through ingestion. It would be valuable to investigate the potential harmful effects of these particles on gut health. This review focuses on recent research exploring the toxicological impacts of micro- and nanoplastics on the gut, as observed in human cell lines and mammalian models. Available data from various studies indicate that the accumulation of MNPs in mammalian models and human cells may result in adverse consequences, in terms of epithelial toxicity, immune toxicity, and disruption of gut microbiota. The paper also discusses the current research limitations and prospects in this field, aiming to provide a scientific basis and reference for further studies on the toxic mechanisms of micro- and nanoplastics.

This paper is dedicated to examining dynamic dark energy models in the context of observational constraints and their implications for the universe's future. By integrating theoretical models with various observational data, we aim to provide a comprehensive view of how dynamic dark energy influences cosmic evolution and the universe's fate. This study tests these models against the latest observational evidence, including the Cosmic Microwave Background, supernovae, and large-scale structure surveys, to refine our understanding of the universe's accelerating expansion and the mysterious nature of dark energy.

In this preliminary investigation, a concise molecular docking study using the Pyrx program screened thousands of compounds against the active site of HIV-1 reverse transcriptase. The Virtual Screening library was employed to assess binding energetics scores, focusing on identifying candidates with high Vina Scores. Eight compounds, including Tetrophan, Imatinib, Amentoflavone, Alprazolam, Bilobetin, Bafetinib, Nilotinib, and Ginketin, emerged as promising candidates with significant binding energies.Recognizing compounds that strongly bind to HIV-1 reverse transcriptase holds potential for antiretroviral drug development in the fight against HIV infection. Subsequently, the study evaluated the toxicity properties of these candidates using pKCSM. Amentoflavone, a natural biflavonoid found in Ginkgo biloba and Nilotinib, a tyrosine kinase inhibitor, demonstrated lower overall toxicity profiles compared to other candidates. Further toxicity analysis using Pro-Tox-II revealed Amentoflavone's higher predictive LD50, lower toxicity class, and reduced probabilities of hepatotoxicity, carcinogenicity, mutagenicity, and moderate immunotoxicity compared to Nilotinib. While Nilotinib, a pharmaceutical drug, exhibited higher probabilities of adverse effects in these categories. In summary, Amentoflavone and Nilotinib present as promising candidates with lower toxicity concerns. Amentoflavone, as a natural substance, showcases a more favorable toxicity profile than Nilotinib, offering valuable insights for potential therapeutic applications.

A typical halogen-free flame-retardant (HFFR) formulation for electric cables may contain polymers, various additives, and fire-retardant fillers. In this study, composites are prepared by mixing natural magnesium hydroxide (n-MDH) with linear low-density polyethylene (LLDPE) and a few types of ethylene-octene copolymers (C₈-POE). Depending on the content of LLDPE and C₈-POE, we obtained composites with different crystallinity that affected the final mechanical properties. The nucleation effect of the n-MDH and the variations in crystallinity caused by the blending of C₈-POE/LLDPE/n-MDH were investigated. In the C₈-POE/LLDPE blend, we found a decrease in the crystallization temperature of LLPDE compared to pure LLDPE and an increase in the crystallization temperature of C₈-POE compared to pure C₈-POE. On the contrary, the addition of n-MDH led to an increase in the crystallization temperature of LLDPE. As expected, the increase in the crystallinity of the polyolefin matrix of composites led to higher elastic modulus, higher tensile strength, and lower elongation at break. Overall, these results show how to obtain the required mechanical features for halogen-free flame-retardant compounds for electric cable applications depending on the quantities of the two miscible components in the final blend.

The purpose of this paper is to assess the differential impacts of transformational and transactional leadership styles on employee performance during change initiatives within commercial banks in Sierra Leone. The research study utilised a cross-sectional survey design, and data was collected from 903 participants employed in the banking industry. The study used the structural equation model as the investigative instrument to examine the hypotheses. The findings reveal that transformational and transactional leadership styles demonstrate a strong bearing on employee performance, with the latter having a bigger influence. Organisational citizenship behaviour has a mediating effect between leadership styles and employee performance, while employee commitment does not act as a mediator between transformational leadership and employee performance, but it acts as a mediator between transactional leadership and employee performance. Commercial banks need to devise training programmes that will advance both leadership styles to arouse, energise, or inspire followers to display favourable behaviour and commitment to attain organisational. The paper makes an insightful contribution to the existing leadership literature by ascertaining the significance of leadership styles on performance and the role of commitment and organisational citizenship behaviour as mediators of the nexus between leadership styles and performance in the Sierra Leone banking industry.

The awareness of ciliate importance in freshwater has changed dramatically in the last decades, reflecting methodological attempts. We analysed two decades (1994-2018) of data on the surface (0-3 m) ciliate assemblage in the Slapy reservoir (Vltava River, Czech Republic) during two different nutrient-load defined periods. We identified, quantified, and evaluated the biomass of ciliates in the quantitative protargol-stained preparations. We used water age, nutrients, bacteria, heterotrophic nanoflagellates and rhodomonads as the main explanatory background variables. The sampling median and interquartile range data analysis and a non-metric multidimensional scaling were applied. Ciliates were grouped according to their feeding behaviour. The picoplankton filtering species dominated the assemblages in an annual mean (halteriids and minute strobilidiids followed by peritrichs). Algae hunters Balanion planctonicum, urotrichs and nanoplankton filtering tintinnids were important before the spring phytoplankton peak when a maximum of ciliate biomass reflected mixotrophic nanoplankton filtering pelagostrombidiids. Only there, ciliate biomass tightly followed their quantified prey. Heterotrophic and mixotrophic Askenasia and Lagynophrya were typical raptorial/flagellate hunters; only Mesodinium spp. peaked during autumn. The oligotrophication increased the ciliate assemblage biomass in the surface layer during the stratification in concordance with the PEG model.

This research investigates the fatigue behaviour and fracture mechanics of high-performance concrete (HPC), including various compositions such as HPC with basalt aggregates (HPC-B), HPC with gravel (HPC-G), and high-strength coarse mortar (CM) static and cyclic tensile loading within the special priority program SPP 2020. The study aims to integrate fracture mechanics into structural analysis to enhance design guidelines for slender cross-sections and safety-related high-performance structural components. The experimental investigations reveal HPC-B's re-markable superiority, displaying higher compressive strength, modulus of elasticity, and tensile strength compared to HPC-G and CM. A modified disk-shaped compact tension (MDCT) based on ASTM standards, aided by digital image correlation (DIC) unveils fracture behaviour, empha-sizing fracture energy as a crucial parameter. HPC-B exhibits improved crack resistance and notch sensitivity reduction attributed to crushed basalt aggregates and enhanced interfacial transition zone (ITZ). The research scrutinizes factors like material characterization, aggregate morphology, stress levels, and displacement rate on crack formation. High-cycle fatigue tests show HPC-B's superior performance, and post-fatigue analysis reveals enhanced residual fracture toughness attributed to nano-level structural changes, stress redistribution and aggregate-matrix interac-tion. 3D image analysis via Computed Tomography (CT) scans captures mesostructural crack propagation and provide quantitative insights. This study advances the understanding of HPC fatigue behaviour, emphasizing the interplay of aggregate types, morphologies, and their dy-namic response to cyclic loading, offering valuable insights for optimizing design guidelines and fostering innovation in structural engineering.

Large-scale crowd phenomena are complex to model because the behaviour of pedestrians needs to be described at both strategic, tactical, and operational levels and is impacted by the density of the crowd. Microscopic models manage to mimic the dynamics at low densities, whereas mesoscopic models achieve better performances in dense situations. This paper proposes and evaluates a novel agent-based architecture to enable agents to dynamically change their operational model based on local density. The ability to combine microscopic and mesoscopic models for multi-scale simulation is studied through a use case of pedestrians at the Festival of Lights, Lyon, France. Pedestrian outflow data is extracted from video recordings of exiting crowds at the festival. The hybrid model is calibrated and validated using a genetic algorithm that optimizes the match between simulated and observed outflow data. Additionally, a local sensitivity analysis is then conducted to identify the most sensitive parameters in the model. Finally, the performance of the hybrid model is compared to different models in terms of density map and computation time. The results demonstrate that the hybrid model has the capacity to effectively simulate pedestrians across varied density scenarios while optimizing computational performance compared to other models.

Context and aim: Environmental awareness is the first step to climate change risk perceptions and environmental behaviour. However, this pathway is not always possible within different population segments and trust contexts. This study explores the conditional effect of trust on environmental behaviour in the Zed Generation in Albania. The consideration of the Zed generation due to two opposing traits, such as social courage and anti-social, make them an interesting topic to understand, especially for their importance in online communities. Method: The youth engagement environmental programme and the climate change risk perceptions framework are adopted in an input-output design. Environmental awareness (input) is the initiating factor, and climate change risk perception and community engagement as mediators of environmental behaviour(output). Individual and institutional trust is the moderating factor that inhibits/enhances engagement and environmental behaviour. Results: The moderation-mediation show that climate change risk perceptions did not mediate environmental behaviour. Environmental awareness directly affects it. However, low institutional trust inhibits the general trust that, in turn, lowers the impact of awareness in climate change perceptions and community engagement toward environmental protection. Practical recommendation: The application of the input-output model shows that the pathway that directly affects environmental behaviour among Zed Generation in Albania is not Climate change risk perception. In low-trust contexts, positive environmental behaviour can be generated through community engagement. Policymakers and educational programmes in low-middle-income countries might consider community engagement to mitigate trust issues and effectively deal with environmental problems with a global segment such as the Zed generation.

Animal welfare assessment protocols are important for identifying welfare problems in conservation programs. This study aimed to develop a baseline welfare protocol for the assessment of welfare in huemul (Hippocamelus bisulcus) in conservation centers. This protocol is based on the Welfare Quality® (WQ) framework for cattle, considering the available literature on the behaviours, ecology, conservation plans, captive management of this species, and welfare assessment protocols for other ungulate species. As a result, the protocol was specifically developed for huemuls and included four principles, 12 criteria, and 23 animal- and resource-based indicators. The 12 criteria of the WQ protocol were reduced to nine, and three new criteria were added because they were both feasible and essential for welfare assessment in captive huemuls. This protocol is mainly intended to identify welfare problems in endangered species in the context of conservation centers (reproduction, rescue, rehabilitation, or treatment centers). Thus, aggregation of different measures to obtain a global score has not been proposed. However, a scoring system that assigns a value on a 0-2 scale (0= No welfare concern; 1= welfare concern; 2= urgent welfare concern) is proposed for each category. Although further research is still needed to fully validate the protocol, this is the first development of a completed protocol for huemul welfare assessment.

The chondrichthyan lineage diverged from the osteichthyan line around 440 million years ago, resulting in a vast evolutionary gulf between modern elasmobranchs and other vertebrates. Though this has supported the assumption that sharks are ancient, dangerous, and binary-minded, intelligent actions including social interactions have been noted in the field, while laboratory studies have confirmed a variety of cognitive capacities. Yet, due to fear of sharks and the difficulties of observing them in their aquatic environments, few ethological studies have been done, so their natural behaviour remains little known. On noting that Carcharhinus melanopterus displayed complex actions during incidental meetings, a long-term ethological study of the species was carried out on the north shore of Mo’orea Island, French Polynesia. During the 6.5 years of the study, new behaviours continued to present. The 35 context-specific actions identified as comprising the behavioural repertoire of C. melanopterus are described.

High-resolution GPS/GSM dataloggers provide spatial information of the highest quality, which outperform previous tracking methods, such as Argos telemetry or conventional VHF ground-tracking. As a result, this has improved our knowledge of home-range behavior and spatial ecology of many species, including large raptors. In this paper, we use high-resolution GPS/GSM dataloggers to assess the home-range size and the role of sex, season (breeding or non-breeding season), and breeding status (reproductive or non-reproductive individuals) on the space use of Bonelli’s eagle (Aquila fasciata). To this end, 51 territorial individuals (25 females and 26 males) were equipped with GPS/GSM transmitters and were tracked over 7 years (2015–2021) in eastern Spain. Overall, we recorded 4,791,080 fixes that were analyzed through kernel density methods (50%, 75%, and 95% fixed kernels). The average individual home-range size according to the 95%, 75%, and 50% kernels was 54.84 ± 20.78 km², 24.30 ± 10.18 km², and 11.17 ± 4.90 km², respectively. Overall, the home-range size of individuals occupying the same territory was similar, mainly due to the cooperative hunting behavior exhibited by the species. We did not find interannual differences in the home-range size (95% fixed kernel) of the majority of individuals, showing a strong territorial fidelity of the breeding pairs. In general, females’ home-range size was slightly smaller than males’ size due to the decrease in activity in the breeding season as a result of laying, incubation, and chick attendance at nests. No seasonal variation in the 95% kernel was found, but it was found in the 75% and 50% kernels. In regard to the breeding status, higher home-range size was recorded in the non-reproductive individuals. Moreover, we found a low neighbor overlap among the territories (4.18% ± 3.06%), which evidences a high level of intraspecific competition in the Bonelli’s eagle. Finally, this study highlights the advantages of the use of accurate telemetry information to improve our understanding of the spatial ecology of the endangered Bonelli’s eagle, which ultimately will serve to better inform management actions for its conservation.

Previous studies implied the different behavioral intention formation of a specific object for individuals in different age groups, but few research to Chinese consumers’ sustainable fast fashion behaviour were found considering the enormous amount of consumption and waste of fast fashion products in China. Meanwhile, as a fast developing country, it might be insufficient to conduct research ignoring the consequences of different education level and growing environment among different generations. Thus, to generate in-depth and heuristic Chinese consumers information, this study developed proposed theoretical framework (TORA) based on research by Fishbein and Ajzen (1975), while the validity among Chinese consumers was tested as well. Following the TORA model, this study aims to investigate if consumers’ age will moderate the relationship between attitude and intention, and the relationship between subjective norms to behavioral intention. Through structural equation modelling in AMOS, it was found that the model has a well fit to large sample of Chinese consumers, while the moderation effect of age was not significant in the whole sample. Further hierarchical regression analysis conducted in SPSS and Process was able to locate the moderation effect of if divide the consumers into groups by age. Which is, age is significantly and positively moderating the path subjective norms to intention in younger generation (18-25), but significantly positive moderating attitude to intention in consumers aged 26-39. Implications in marketing and to policy makers are discussed at the end of this research.

Introduction: Neuroinflammation following lipopolysaccharide (LPS) administration induces locomotor deficit and anxiety-like behavior. In this study, minocycline was compared to memantine, the NMDA receptor antagonist, for its effects on LPS-induced locomotor deficit and anxiety-like behavior in rats. Methodology: Adult male Sprague Dawley rats were administered either two different doses of minocycline (25 or 50 mg/kg/day, i.p.) or 10 mg/kg/day of memantine (i.p.) for 14 days four days prior to LPS (5 mg/kg, i.p.) injection. The locomotor activity and anxiety-like behavior were assessed using the open field test (OFT). The phosphorylated tau protein level was measured using ELISA while the expression and density of brain-derived neurotrophic factor (BDNF) and cAMP response element-binding protein (CREB) protein in the medial prefrontal cortex (mPFC) were measured using immunohistochemistry and western blot, respectively. Results: In the mPFC, minocycline treatment reduced the locomotor deficit and anxiety-like behavior, reduced phosphorylated tau protein level, and upregulated BDNF/CREB protein expression comparable to memantine, with the higher dose of minocycline having better benefits. Conclusion: Minocycline treatment attenuated LPS-induced locomotor deficit and anxiety-like behavior in rats, possibly via a decrease in phosphorylated tau protein levels and an increase in the expression of the BDNF/CREB proteins.

Breaking up prolonged sitting by short bouts of light physical activities including standing and walking has been shown to be beneficial for people with type 2 diabetes (T2D). This paper presents the development of an android mobile app to deliver a just-in-time adaptive intervention (JITAI) to reduce sedentary time in people with T2D. A total of six design workshops were conducted with seven experts to identify design requirements, a behavioural framework, and required contextual adaptations for the development of a bespoke mobile app (iMOVE). Moreover, a focus group was conducted among people with T2D as potential end-users (N=10) to ascertain their perceptions of the app. Feedback from the focus group was used in subsequent iterations of the iMOVE app. Data were analysed using an inductive qualitative thematic analysis. Based on workshops, key features of iMOVE were developed, including simplicity (e.g., navigation, login), colours and font sizes, push notifications, messaging algorithms and a triggering system for breaking up sitting time and moving more. Based on the user testing results, a goal setting tab was added, font sizes were made larger, the brightness of colours was reduced, and a colour indicator was used to indicate device connectivity with an activity tracker. A user-centric app was developed to support people with T2D to transition from sedentary to active lifestyles.

Background: Using the COM-B model as a framework, an EU-wide survey aimed to ascertain multidisciplinary healthcare workers’ (HCWs) knowledge, attitudes and behaviours on antibiotics, antibiotic use and antibiotic resistance. The UK findings are presented. Methods: A 43-item questionnaire was developed through a two-round modified Delphi consensus process. The UK target quota was 1,315 respondents. Results: 2,404 participants responded. The highest proportion were nursing and midwifery professionals (42%), pharmacists (23%) and medical doctors (18%). HCWs correctly answered that antibiotics are not effective against viruses (97%), they have associated side effects (97%), unnecessary use makes antibiotics ineffective (97%) and healthy people can carry antibiotic resistant bacteria (90%). However, fewer than 80% correctly answered that using antibiotics increases a patient’s risk of antimicrobial resistant infection or that resistant bacteria can spread from person to person. Whilst the majority of HCWs (81%) agreed there is a connection between their antibiotic prescribing behaviour and the spread of antibiotic resistant bacteria, only 64% felt that they have a key role in controlling antibiotic resistance. The top three barriers to providing advice or resources were lack of resources (19%), insufficient time (11%) and the patient being uninterested in the information (7%). Approximately 35% of UK respondents who were prescribers prescribed an antibiotic at least once in the last week due to fear of patient deterioration or complications. Conclusion: These findings highlight that a multifaceted approach to tackling the barriers to prudent antibiotic use in the UK is required and provides evidence for guiding targeted policy, intervention development and future research. Education and training should focus on patient communication, information on spreading resistant bacteria and increased risk for individuals.

Children with Fetal Alcohol Spectrum Disorders (FASD) and Autism Spectrum Disorders (ASD) experience significantly higher rates of sleep disturbances than their typically developing peers. Pre-sleep anxiety and waking emotional content is known to affect the content and frequency of nightmares, which can be distressing to children and caregivers. This is the first study to analyse nightmare frequency and content in FASD, and to assess its association with psychometric outcomes. We assessed reports from 277 caregivers of children with ASD (n=61), FASD (n=112), and TD children (n=104) using the Children’s Sleep Habits Questionnaire (CSHQ), the Child Behavior Checklist (CBCL), the Spence Children’s Anxiety Scale (SCAS) and the Behavior Rating Inventory for Executive Functioning (BRIEF). Within the ASD group, 40.3% of caregivers reported their children had nightmares. Within the FASD group, 73.62% of caregivers reported their children had nightmares and within the TD group, 21.36% of caregivers reported their children had nightmares. Correlation analysis revealed significant associations between anxiety and nightmares, maladaptive behaviour and nightmares, and executive functioning and nightmares in the TD and FASD groups, but not ASD group. This paper adds to the emerging body of work supporting the need for sleep interventions as part of clinical practice with regard to children with ASD and FASD. As a relatively niche but important area of study this warrants much needed further research.

Background: The study assessed men’s role in the preparedness against emerging pandemic of Ebola Virus Disease in Ogun State, Nigeria. It examined the changes in men’s hygiene practices as response to the news of the outbreak of Ebola Virus Disease. Methods: The data were extracted from a 2015 Cross-Sectional Survey on wellness, knowledge, attitude and practices towards the control and prevention of Ebola Virus Disease. The respondents (466 male) in the main survey were selected using simple random sampling technique within two enumeration areas (EAs). Results: The results revealed high level of knowledge of EVD but over 70% were not aware of centre for EVD treatment, 60.2% believed they are not susceptible to EVD. The practice of handshaking reduced, eating of hunted animals decreased only marginally by 6.9% and washing with soap increased by 4%. Conclusion: The study provides helpful information for public health policy especially in terms of behavioral risk factors that are prone to Ebola virus infections or other communicable diseases. It emphasises regular hand washing with soap and sanitizing agents and recommended that availability of treatment centres and vaccines that can enhance effective response in curtailing further health emergencies.

Climate change is one of the biggest challenges of our times. Its impact on human populations is not yet completely understood. Many studies have focused on single aspects with contradictory observations. However, climate change is a complex phoenomenon that cannot be adequately addressed from a single discipline's perspective. Hence, we propose a comprehensive conceptual framework on the relationships between climate change and human responses. This framework includes biological, psychological and behavioural aspects, and provides a multidisciplinary overview and critical information for focused interventions. The role of tipping points and regime shifts is explored, and a historical perspective is presented to describe the relationship between climate evolution and socio-cultural crisis. Vulnerability, resilience and adaptation are analyzed from an individual and a community point of view. Finally, emergent behaviours and mass effect phenomena are examined that account for mental maladjustment and conflicts.

.Most of the accident cases at work are caused by unsafe behaviour. Scholars have thus extensively researched factors of safe behavior.Safety leadership is stated as the most effective factor in safety behaviour. Besides, safety knowledge and safety attitudes are also found to influence safety behaviour. The purpose of this paper is to investigate the nature of the relationship between safety leadership, safety knowledge, safety attitude, and safety behavior, which has been found to be limited or rare in previous research.A self-administered questionnaire was applied and was distributed randomly to 140 SME manufacturing workers and they were analysed using the structural equation modelling partial least squares (PLS-SEM). The results prove that safety leadership has a significant effect on safety knowledge, safety attitude, and safety behaviour, with safety knowledge and safety attitude mediating the safety leadership-safety behaviour relationship. Consequently, the results provide a more in-depth view of the relationship between safety leadership and safety knowledge-attitude-behaviour via adapting social-cognitive theory and social learning theory in solving safety issues in SME. This study also provides a starting point for researchers to better understand how effective safety leadership is provided by supervisors in terms of improving worker safety and safety knowledge-attitude-behaviour.

The functioning of the parents’ emotional sphere is very important to a child’s mental and physical health. This study focused on investigating the association between mothers’ emotional intelligence (EI) and paediatric type I diabetes (T1DM) disease management in their children. We hypothesized that mothers’ EI is associated with T1DM outcomes. Mothers of children with T1DM aged 6-12 years were surveyed. One hundred and thirty-four mothers, the main caregivers of their diabetic children, provided measures of EI and completed a demographic questionnaire. The primary indicator of diabetes management was haemoglobin A1c (HbA1c; the main form of glycosylated haemoglobin). EI scales and subscales were associated with glycaemic management indices. Logistic regression analysis was applied for the assessment of the association between parents’ EI and their paediatric with T1DM disease management. The analysis demonstrated a statistically significant correlation between T1DM management and mothers’ ability to understand and control own emotions, to transform their own negative emotions into positive and to control own negative emotions. Mothers’ EI scales and subscales of understanding and regulating their own emotions, subscales of transforming their own negative emotions into positive ones and controlling their own negative emotions were statistically reliable predictors of glycaemic control in children with T1DM.

A characteristic feature of lightweight constructions is their low thermal mass which causes high internal temperature fluctuations that require high heating and cooling demand throughout the year. Phase Change Materials (PCMs) is effective in providing thermal inertia to low thermal mass buildings. The aim of this paper is to analyse the thermal behaviour of two proposed lightweight buildings designed for homeless people and to investigate the potential benefit achievable through the use of different types of PCM in the temperate climatic conditions of Christchurch, New Zealand. For this purpose, over 300 numerical simulations have been conducted using the simulation software DesignBuilder®. The bulk of the simulations were carried out under the assumption that the whole opaque building envelope is equipped with PCM. The results showed significant energy saving and comfort enhancement through the application of PCMs. Thereby, annual energy saving of over 50 % was reached for some of the PCMs considered. Additionally, the effectiveness of single, PCM-equipped structure components was investigated and substantial benefits between 19 and 27 % annual energy saving were achieved. However, occupant behaviour in terms of ventilation habits, occupancy of zones etc. remains one of the biggest challenges in any simulation work due to insufficient data.

Analgesic products for piglet castration are critically needed. This requires extensive animal experimentation such as to meet regulatory-required proof of efficacy. At present, there are no validated methods of assessing pain in neonatal piglets. This poses challenges for investigators to optimize trial design and to meet ethical obligations to minimize the number of animals needed. Pain in neonatal piglets may be subtle, transient and / or variably expressed and, in the absence of validated methods, investigators must rely on using a range of biochemical, physiological and behavioural variables, many of which appear to have very low (or unknown) sensitivity or specificity for documenting pain, or pain-relieving effects. A previous systematic review of this subject was hampered by the high degree of variability in the literature base both in terms of methods used to assess pain and pain mitigation, as well as in outcomes reported. In this setting we provide a narrative review, to assist in determining the optimal methods currently available to detect piglet pain during castration and methods to mitigate castration-induced pain. In overview, the optimal outcome variables identified are nociceptive motor and vocal response scores during castration, and quantitative sensory-threshold response testing and pain-associated behaviour scores following castration.

Purpose: To explore the influence of education and other factors on an athlete’s decision to return to sport post-concussion injury, and whether general risk-taking tendencies are related to return to sport post-concussion decisions in these athletes. Participants and Methods: A self-administered electronic survey was designed to examine their decision-making process when faced with scenario-based questions regarding returning to sport post-concussion injury. Students from the Health Sciences and Medicine Faculty at Bond University were invited to participate. Participants were allocated to a concussion education or non-education group prior to commencement of questionnaire via the random generator on Qualtrics software function. The risk propensity scale was used to assess the risk aversion of each participant. Results: Sixteen respondents were randomized evenly to education and non-education groups. Seven (43.8%) had previously received concussion education training prior to completing the questionnaire, with one (14%) choosing to return to sport in the scenario-based questions. The education group reported two (25%) respondents return to sport, while three (75%) respondents out of four returned to sport with no education or previous concussion training. Influential factors that impacted the decision whether to return to sport or not included: game importance, concussion severity and symptoms, and various internal and external factors. Finally, there was a divergence in results from the risk propensity scale when deciding to return to sport and general risk-taking propensities. Conclusion: This study identified several influential factors including game importance, concussion severity and symptoms which play a significant role in the return to sport decisions post-concussion injury.

Integrated information theory (IIT) was initially proposed to describe human consciousness in terms of intrinsic-causal brain network structures. This theory could potentially be used for conceptualising complex living systems. In a previous study, we analysed collective behaviour in {\it Plecoglossus altivelis}. We found that IIT 3.0 exhibits qualitative discontinuity between three and four schools of fish in terms of $\Phi$ values (i.e., group integrity). Other measures, such as mutual information, did not show such characteristics. In this study, we follow up on our previous findings and introduce two new factors. First, we define the global parameter settings to determine a different kind of group integrity. Second, we set several timescales (from $\Delta t =5/120$ s to $\Delta t =120/120$ s). The results showed that we succeeded in classifying fish school according to their group size in terms of the degree of group integrity, despite the small group size. The concrete classification includes the followership for a two-fish school, fission--fusion for a three-fish school, emergence of leadership for a four-fish school, and emergence of Boid-like behaviour for a five-fish school. These minute classifications have never been revealed before. Finally, we discuss one of the longstanding paradoxes in collective behaviour, known as the heap paradox, for which two tentative answers could be provided through our IIT analysis.

Dispersal represents a key life-history trait with several implications for the fitness of organisms, population dynamics and resilience, local adaptation, meta-population dynamics, range shifting and biological invasions. Plastic and evolutionary changes of dispersal traits have been intensively studied over the past decades in entomology, in particular in wing-dimorphic insects for which literature reviews are available. Importantly, dispersal polymorphism also exists in wing-monomorphic and wingless insects, and except for butterflies, fewer syntheses are available. In this perspective, by integrating the very last research in the fast moving field of insect dispersal ecology, this review article provides an overview of our current knowledge of dispersal polymorphism in insects. After having provided a definition of the main terms characterising insects’ movements, some of the most often used experimental methodologies for the separation of dispersers and residents in wing-monomorphic and wingless insects are presented. The existing knowledge on the morphological and life-history trait differences between resident and disperser phenotypes is then synthetized. The fourth part examines the effects of range expansion on dispersal traits and performance, in particular for insects from range edges and invasion fronts. Finally, some research perspectives are proposed in the last part of the review.

The aim of this study was to identify gender differences in technical-tactical behaviour in football. To this end 68 matches of the first division of the Spanish men’s and women´s league, corresponding to 2016/17 season were analyzed. A comparison of medians was carried out using the Mann-Whitney U-test were conducted as post hoc test and a grouping of the variables through the clustering bootstrapping technique in both groups. We have detected statistically significant differences regarding all accurate passes, in favour of men, as well as a greater number of yellow cards. In female football, a greater number of picking up free balls, interceptions, lost balls, recoveries, challenges and attacks, both positional and counterattacks, are produced. The clustering analysis also allowed that in male football, the circumstance of receiving a red card is closely related to the number of goals conceded and most of the shots on goal are achieved by positional attacks. In women's football, ball possession on own half is closely related to the number of losses. These results could be useful for gender-specific training information for optimal preparation. However, more research is warranted to establish the main gender differences and characterize women's football.

Integrated information theory (IIT) was initially proposed to describe human consciousness in terms of intrinsic, causal brain-network structures. This theory has the potential to be useful for conceptualising complex living systems. In a previous study, we analysed collective behaviour in Plecoglossus altivelis and found that IIT 3.0 exhibits qualitative discontinuity between three and four fish. Other measures like mutual information did not have such characteristics. In this study, we followed up on our previous findings and examined timescale effects on integrated information of collective behaviour. We found that a long timescale (1 s) causes Boid-like local interactions to dominate over interactions with the whole, but only when the group size is five at a given time scale (i.e. around 0.2 s). Interestingly, the most suitable time scale is roughly equal to fish reaction time. We used these data to propose a new classification for fish schools, with each size group being a unique and autonomous system, despite small group sizes.

This article addresses the role the Word-Acaid Philosophy plays in directing or guiding human behaviour in all situations and circumstances. It discusses the origin of the philosophy when I asked myself the following question: “Why do I do what I do when I do what I do?” This question led me to carefully self-examine to discover the reason for my behaviours. Once the philosophy was crafted, I observed that all other human beings seem to go through the same process. The philosophy did not originate as a formal study. However, in this article I did a systematic study on the concepts to verify the initial propositions. In order to achieve my goal a formal study was done using a descriptive approach to explicate the modus operandi of the philosophy with a view of understanding its nature and the role each of the essential elements plays. A conceptual analysis method was used focusing on the definition of key concepts. It was conclusively found that each concept played a significant role in driving human behaviour in every situation. The findings’ implications are very significant to trainers, coaches, educators and all whose goal is to affect human beings towards particular exit outcomes. The findings made it very simple also for me to deductively conclude that the philosophy is a system and is valid.

Polyolefin fibre reinforced concrete (PFRC) has become an attractive alternative to steel for the reinforcement of concrete elements mainly due to its chemical stability and the residual strengths that can be reached with lower weights. The use of polyolefin fibres can meet the requirements in the standards, although the main constitutive relations are based on the experience with steel fibres. Therefore, the structural contributions of the fibres should be assessed by inverse analysis. In this study, the fibre dosage has been fixed at 6kg/m³ and both self-compacting concrete and conventional concrete have been used to compare the influence of the positioning of the fibres. An idealized homogeneous distribution of the fibres with such fibres crossing from side to side of the specimen has been added to self-compacting concrete. The experimental results of three-point bending tests on notched specimens have been reproduced by using the cohesive crack approach. Hence, the constitutive relations were found. The significance of this research relies on the verification of the formulations found to build the constitutive relations. Moreover, with these results it is possible to establish the higher threshold of the performance of PFRC and the difficulties of limiting the first unloading branch typical of fracture tests of PFRC.

The use of pain relief during castration and dehorning of calves on commercial beef operations can be limited by constraints associated with the delivery of analgesic agents. As topical anaesthetic (TA) and buccal meloxicam (MEL) are now available in Australia, offering practical analgesic treatments for concurrent castration and dehorning of beef calves, a study was conducted to determine their efficacy in providing pain relief when applied alone or in combination. Weaner calves were randomly allocated to; (1) no castration and dehorning / positive control (CONP); (2) castration and dehorning / negative control (CONN); (3) castration and dehorning with buccal meloxicam (BM); (4) castration and dehorning with topical anaesthetic (TA); and (5) castration and dehorning with buccal meloxicam and topical anaesthetic (BMTA). Weight gain, paddock utilisation, lying activity and behaviour following treatment were measured. CONP and BMTA calves had significantly greater weight gain than CONN calves (P < 0.001). CONN calves spent less time lying compared to BMTA calves on all days (P < 0.001). All dehorned and castrated calves spent more time walking (P = 0.024) and less time eating (P < 0.001) compared to CONP calves. There was a trend for CONP calves to spend the most time standing and CONN calves to spend the least time standing (P = 0.059). There were also trends for the frequency of head turns to be lowest in CONP and BMTA calves (P = 0.098) and tail flicks to be highest in CONN and BM calves (P = 0.061). The findings of this study suggest that TA and MEL can improve welfare and production of calves following surgical castration and amputation dehorning.

AI is often looked at as a logical rational way to develop a games agent that methodically looks at options and delivers rational solutions. This paper is based on developing an AI agent that plays a game with a similar emotive content like a human. The purpose of the study was to see if the incorporation of this emotive content would influence the outcomes within the game Love Letter. In order to do this an AI agent with an emotive layer was developed to paly the game over a million times. A lower win/loss ratio demonstrates that to some extent this methodology was vindicated and a 100 per cent win for the AI agent did not happen. Machine learning techniques were modelled purposely so as to match extreme models of behavioural change. The results demonstrated a win/loss ration of 0.67 for the AI agent and in many ways reflectd the frustration that a normal player would exhibit during game play. As was hypothesised the final agent investment value was, on average, lower after matchplay than its initial value.

This paper discusses the application of artificial intelligence in imaging omics, especially in cancer research. Imaging omics enables detailed analysis of spatial and temporal heterogeneity of tumours through high-throughput extraction of quantitative features from medical images such as MRI, PET, and CT. This paper focuses on applying PARKS systems to automate the recognition, segmentation, and extraction of image features, significantly enhancing the capabilities of clinical decision support systems (CDSS). The future direction is to establish a robust network infrastructure for radiology Medication-led Health care (RLHC) to facilitate the development and application of personalised treatment protocols, and to improve diagnostic accuracy, prognosis assessment, and treatment recommendations by uploading quantitative image features to a shared database and comparing them with historical images.

The analysis of aggregate data has received increasing attention in the statistical discipline over the past 20 years. Much of this attention has been focused on estimating the cells frequencies of a 2×2 contingency table given only the marginal totals; the analyses proposed have been received with missed reviews. More recently, the focus has shifted toward analysing the overall association structure rather than on the estimation of the cell frequencies. This article provides some insight int how informative the aggregate data of a single 2×2 contingency table is for assessing the association. The information contained in the margins of the table is quantified using the squared deviation of the expected cell frequencies over the possible range of values, where the row and column totals are known and fixed. The new measure we discuss to quantify this association is referred to as the aggregate informative index (AII) and is shown to be the standardized area under the squared deviation curve.

Complexity science studies physical phenomena that cannot be explained by the mere analysis of the single units of a system but requires to account for their interactions. A feature of complexity in connected systems is the emergence of mesoscale patterns in a geometric space, such as groupings in bird flocks. These patterns are formed by groups of points that tend to separate from each other, creating mesoscale structures. When multidimensional data or complex networks are embedded in a geometric space, some mesoscale patterns can appear respectively as clusters or communities, and their geometric separability is a feature according to which the performance of an algorithm for network embedding can be evaluated. Here, we introduce a framework for the definition and measure of the geometric separability (linear and nonlinear) of mesoscale patterns by solving the travelling salesman problem (TSP), and we offer experimental evidence on embedding and visualization of multidimensional data or complex networks, which are generated artificially or are derived from real complex systems. For the first time in literature the TSP’s solution is used to define a criterion of nonlinear separability of points in a geometric space, hence redefining the separability problem in terms of the travelling salesman problem is an innovation which impacts both computer science and complexity theory.

Instagram is a popular social media platform among youth, with over a billion active users worldwide. The platform allows users to share photos, videos, and stories and connect with friends and followers. Instagram has become a significant part of youth culture, with many young people spending a considerable amount of time on the app. According to Enterprise (2012:02), Instagram is a community shared among one member with other members from all over the world. This study examines the impact of Instagram on the physical and mental well-being of Indian youth. With the rapid proliferation of social media platforms in India, Instagram has emerged as a prominent influence on the lives and perceptions of young individuals. Studies have shown that using Instagram among youth can have positive and negative effects. On the positive side, Instagram can be a way for young people to express themselves, connect with others, and discover new interests. However, excessive use of the platform can also lead to negative outcomes, such as social comparison, anxiety, and low self-esteem. Instagram addiction among youth is a growing concern. Some young people may feel compelled to check their accounts frequently and may experience negative emotions if they are unable to do so. In extreme cases, excessive use of the platform can interfere with daily activities and relationships, leading to a negative impact on mental health. Parents and educators can play a role in helping young people manage their Instagram use. This can include setting limits on screen time, encouraging healthy online habits, and promoting offline activities and social interaction. Additionally, mental health professionals can offer support to young people who are struggling with addiction or other negative effects of Instagram use. This study explores the prevalence of Instagram dependency among Indian youth.

Product attribute extraction is an growing field in e- commerce business, with several applications including product ranking, product recommendation, future assortment planning and improving online shopping customer experiences. Under- standing the customer needs is critical part of online business, specifically fashion products. Retailers uses assortment planning to determine the mix of products to offer in each store and channel, stay responsive to market dynamics and to manage inventory and catalogs. The goal is to offer the right styles, in the right sizes and colors, through the right channels. When shoppers find products that meet their needs and desires, they are more likely to return for future purchases, fostering customer loyalty. Product attributes are a key factor in assortment planning. In this paper we present PAE, a product attribute extraction algorithm for future trend reports consisting text and images in PDF format. Most existing methods focus on attribute extraction from titles or product descriptions or utilize visual information from existing product images. Compared to the prior works, our work focuses on attribute extraction from PDF files where upcoming fashion trends are explained. This work proposes a more comprehensive framework that fully utilizes the different modalities for attribute extraction and help retailers to plan the assortment in advance. Our contributions are three-fold: (a) We develop PAE, an efficient framework to extract attributes from unstructured data (text and images); (b) We provide catalog matching methodology based on BERT representations to discover the existing attributes using upcoming attribute values; (c) We conduct extensive experiments with several baselines and show that PAE is an effective, flexible and on par or superior (avg 92.5% F1-Score) framework to existing state-of-the-art for attribute value extraction task.

Strong-aroma Baijiu is a traditional Chinese spirit distilled from grains that undergo solid-state fermentation. At the end of each fermentation cycle, a significant quantity of Huangshui accumulates at the bottom of the fermentation pit, constituting one of the primary by-products in the brewing process of strong-flavor liquor. In this report, the chemical component analysis of Huangshui obtained from a strong-flavor liquor factory revealed a diverse array of organic acids, alcohols, esters, starch, reducing sugars, amino acids, and other compounds present in Huangshui. Additionally, two specialized solid-state fermentation models were developed to investigate the formation process of Huangshui. Our findings demonstrate a positive correlation between the yield of Huangshui and the initial moisture content of fermented grains. It is concluded that Huangshui is the percolate produced during the solid-state brewing process of strong-flavor liquor, with its water content originating from the initial moisture of fermented grains.

Background/Objectives: Although the role of F-18 FDG PET/CT imaging is well established in oncology, its diagnostic value in routine monitoring for recurrent colorectal cancer (CRC) is still controversial. The aim was to evaluate the diagnostic value of FDG PET/CT in detecting recurrent CRC in correlation with CEA, CA 19-9 levels, and conventional imaging modalities (CIM). Methods: Between 2009 and 2023, we retrospectively studied 134 CRC patients referred for FDG PET/CT imaging on the suspicion of recurrence based on elevated CEA and/or CA 19-9, and/or equivocal radiological findings. According to the Institutional Tumor Board CRC protocol, after initial treatment which was dependent on TNM stage (neoadjuvant therapy, primary resection or adjuvant treatment), patients underwent a standard 5-year surveillance including CEA and CA 19-9 measurements, CIM, and colonoscopy every 6 months. The statistics including univariate and multivariable analyses were conducted using the IBM SPSS 20.0 statistical software. P-values <0.05 were considered statistically significant. Results: Recurrent CRC was confirmed in 54/134 (40.3%) patients with elevated tumor markers. FDG PET/CT shows high diagnostic performance in detecting recurrent CRC with sensitivity, specificity, PPV, NPV, and accuracy of 94.4%, 82.5%, 78.5%, 95.7%, and 87.3%, respectively. The CEA shows a high sensitivity of 98.1%, but both low specificity and accuracy of 15% and 48.5%, respectively. The sensitivity, specificity, and accuracy, for CA 19-9 and CIM for the correct diagnosis in CRC patients were: 44.4%, 67.5%, 58.2%, and 51.9%, 98.8%, 79.9%, respectively. The AUC for FDG PET/CT, elevated CEA levels, CIM, and elevated CA 19-9 levels was 0.885 (95% CI: 0.824-0.946; p<0.001), 0.844 (95% CI: 0.772-0.916; p<0.001), 0.753 (95% CI: 0.612-0.844; p<0.001); and 0.547 (95% CI: 0.442-0.652; p=0.358). Univariate analysis shows that both FDG PET/CT- and CIM-positive results were highly associated with CRC recurrence (p<0.001 and p<0.001, respectively), while gender, mucinous tumor type, presence of initial lymph node metastasis (N+), and presence of initial distant metastasis (M+) have no significance (p=0.211, p=0.158, p=0.583, and p=0.201, respectively). Our multivariate analysis shows that independent predictors for CRC recurrence are: positive FDG PET/CT scans (p<0.001), positive CIM results (p=0.001) and elevated CA19-9 levels (p=0.023). Although CA 19-9 was not detected as a statistically significant predictor in the univariate analysis (p=0.358), in a multivariate analysis it was recognized as a significant predicting factor in detecting CRC recurrence (p=0.023). Conclusions: FDG PET/CT shows a high diagnostic efficacy in CRC recurrence detection, in correlation with CEA levels, CA 19-9 levels, and CIM. This imaging modality should be routinely integrated into the postoperative follow-op in patients with elevated tumor markers.

A recent study revealed a persistent presence of the PP-Spike recombinant protein in 50% of individuals who received ModRNA injections, contrasting with unvaccinated controls, whether SARSCoV-2 infected or not, up to 187 days post-injection. The implications of these findings are discussed in the context of PP-Spike recombinant protein-induced hyperimmune/inflammatory reactions and thrombotic vasculitis as mechanisms to elucidate the serious side effects, long-term organ complications, and excess deaths observed after administering Covid ModRNA products. These results underscore the urgent need for a comprehensive reassessment of the risk-benefit profile of ModRNA injections, including an immediate halt in their use for any person, and a renewed emphasis on understanding and addressing their long-term effects on human health

Aim: the main aim of this study is to compare the onset of effectiveness of mental nerve block with lingual infiltration and inferior alveolar nerve block on patients visiting dental hospital for extraction of mandibular anterior teeth. Materials and methods: The study was set in a clinical setting. This was a randomized controlled double-blind cross study, where 25 subjects received two treatments at an interval of at least 1 week in a within a dental hospital.Inferior alveolar nerve block and lingual nerve block injection is given with 2mL lignocaine 2% with 1:2,00,000 epinephrine was administered for the right side. Mental nerve block along with lingual infiltration of the corresponding tooth was given with 2mL lignocaine 2% with 1:2,00,000 epinephrine was administered on the left side.Visual analogue scale (VAS) was used in this study, which consists of a scale with range of 0-10 pain severity on which 0 indicated absence of pain and 10 the worst pain possible. The patients were asked to give scores corresponding to his/her pain, after IANB, mental nerve block and lingual infiltration and these scores were recorde.Results: From the results we can see that patients gave scores between 3-4, stating that they had moderate pain during extraction after administration of IANB (54%) (graph 2) and VAS scores of 0-1 were given by patients, which is suggestive of no pain during extraction after administration of Mental nerve block and lingual nerve infiltration (62%)Conclusion: Within the limits of the study we can conclude that mental nerve block along with lingual infiltration is an effective way to completely and quickly anaesthetise the central incisor to the 1st premolar region.

Flavin-dependent monooxygenases (FMOs) have made substantial influence as catalysts for monooxygenation reactions, impacting diverse field such as drug metabolism, environmental studies, and natural product synthesis. Their application in biocatalysis boasts several advantages over conventional chemical catalysis, such as heightened selectivity, safety, sustainability, and eco-friendliness. In the realm of biomedicine, FMOs are pivotal in antibiotic research, modulating natural products, antimicrobial agents, and pathways involved in drug synthesis. They're also underscored as potential pharmaceutical targets, pivotal in disease progression and viable for therapeutic intervention. Additionally, FMOs play a substantial role in environmental science, especially in pesticide processing and plant vitality. Their involvement in biosynthesizing compounds like polyethers, tropolones, and ω-hydroxy fatty acids, with remarkable regio- and stereoselectivity, renders them indispensable in drug discovery and development. As our comprehension of FMOs' catalytic mechanisms and structures advances, coupled with cutting-edge biotechnologies like computational design and directed evolution, FMOs are poised to occupy an increasingly significant role in both scientific exploration and industrial applications.

Hund's rule of maximum multiplicity is a powerful empirical tool for determining the electron population of electronic shells. It was recently discovered that it is also the rule of minimum Shannon entropy. This study extends these findings to the Aufbau rule and discusses them from the perspective of emergent dimensionality, providing a monotonically increasing entropy function. We observed that some elements that violate the Aufbau rule have the same entropies in the actual and Aufbau electron configurations. On the other hand, lower entropies of all actual elements' configurations are associated with higher or equal numbers of unpaired electrons in these configurations compared to the Aufbau configurations. The only exception to this rule is palladium.

The visual span refers to the number of letters readers can identify in a single fixation without using linguistic skills. Proponents of the visual span hypothesis postulate an influence of early visual processing on reading speed. Given the slowness of reading Arabic texts, the present work aims to study the development of the visual span and its effects on reading speed in the Arabic-speaking context. Thirty-four subjects participated in the study. The trigram task and the rapid serial visual presentation (RSVP) paradigm were used to estimate visual span size and reading speed. In line with our initial assumptions, the results showed a significant effect of grade level on reading speed (F(2,31) = 30.93, p<0.001), visual span size (F(2,31) = 20.57, p<0.001). In good alignment with previous work, our results show that visual span size could explain around 40% of the reading speed variability. Interestingly, our analyses revealed a narrowing of visual span size in our Arabic sample. The results of study 2, suggest that the poor performance in the trigram task is due to poor visual attention capacities in our Arabic readers

Although working memory (WM) is crucial for intellectual abilities, not much is known about its brain underpinnings, especially the structural connectivity. We used diffusion tensor imaging (DTI) to look across the whole brain for the white matter integrity correlates of the individual differences in the reading span (verbal WM capacity during reading) in healthy adults. Right-handed healthy native Russian speakers (N = 67) underwent DTI on a 3T Philips Ingenia scanner. Verbal WM was assessed with the Daneman-Carpenter reading span test (Russian version). Fractional anisotropy maps from each participant were entered into the group tract-based spatial statistics analysis with the reading span as a covariate; the results were TFCE-corrected. After taking into account effects of age, sex, education and handedness, reading span positively correlated with the white matter integrity in multiple sites: the body, the genu and the splenium of corpus callosum; bilateral corona radiata (anterior, posterior, and superior); bilateral superior longitudinal fasciculus; several tracts in the right hemisphere only, including the internal and external capsule; bilateral superior parietal and frontal white matter. Although the left hemisphere is central for verbal processing, we revealed the important role of the right hemisphere white matter for the verbal WM capacity. Our finding indicates that larger verbal working memory span may originate from additional processing resources of the right hemisphere.

Introduction:Lumbar radiculopathy, frequently triggered by disc herniation, affects around one in 50 young adults (30-55 ages), leading to significant impacts on quality of life. When conservative treatments fail to alleviate symptoms, surgical intervention such as discectomy is often pursued. Technological advancements have led to various minimally invasive techniques, promising improved outcomes. Our aim was to compare clinical outcomes of different techniques.Methods:We conducted a systematic search in PubMed using "lumbar disc hernia" and the meta-analysis filter. Inclusion criteria comprised meta-analyses focusing on lumbar disc herniation treatments, published in English. A rigorous selection process adhering to PRISMA guidelines ensured high-quality evidence extraction.Results:From 28,171 initial records, 31 meta-analyses involving 87,852 patients were included. Heterogeneity across the literature presented challenges, notably in study populations, surgical techniques, and research designs. Among the techniques evaluated, full-endoscopic lumbar discectomy (FELD) emerged as superior in various perioperative parameters, including Visual Analog Scale (VAS) scores, Oswestry Disability Index (ODI), operation time, and complications. Conversely, automated percutaneous discectomy (AUTD) consistently exhibited poorer outcomes, suggesting limited effectiveness compared to other techniques. Conclusion:Despite advancements, the heterogeneity observed in the literature underscores the need for standardized approaches in minimally invasive spinal surgery research. FELD stands out as a preferred technique, offering favorable outcomes across multiple parameters. Conversely, techniques like AUTD raise concerns regarding efficacy. Future research should aim for uniformity in methodologies to facilitate accurate comparisons and guide clinical decision-making.

The integration of deep learning models into financial risk prediction and analysis has significantly transformed traditional approaches. While conventional quantitative methods often rely on simplistic metrics like maximum drawdown, the advent of deep learning necessitates a more nuanced evaluation, emphasizing the model's generalization ability, especially during market crises such as stock market crashes. This paper explores the critical aspects of evaluating deep learning models' risk control capabilities in finance, underscoring the importance of understanding both statistical metrics and generalization abilities, particularly in adverse market conditions. By examining deep learning models' performance in scenarios like stock market crashes and highlighting the significance of cross-validation techniques, this study aims to offer practitioners insights into constructing robust risk management systems. It advocates for a comprehensive approach integrating quantitative analysis with macroeconomic factors to enhance financial risk prediction and analysis in volatile markets. The experimentation reveals that different deep generative models excel in various aspects of financial time series analysis, with generative adversarial networks (GANs) demonstrating superior performance in predicting Value at Risk (VaR) and variational autoencoders (VAEs) excelling in return rate prediction. Moreover, integrating multiple models further enhances predictive performance, leveraging the strengths of each model to compensate for individual weaknesses. Overall, this paper underscores the potential and significance of deep generative models in financial time series analysis, offering a roadmap for improved risk management and decision-making in financial markets.

The profile of secondary metabolites occurring in apple cuticular layer is not only characteristic for particular apple cultivar, but also dynamically reflects various external factors in growing environment. In this study, the possibility to authenticate apple samples based on analysis of their cuticular layer extracts was investigated. Ultra-high-performance liquid chromatography coupled to high resolution tandem mass spectrometry (UHPLC-HRMS/MS) was employed for obtaining metabolomic fingerprints. In total, 274 authentic apple samples, four cultivars harvested within the seasons 2020 to 2022 in the Czech Republic and Poland were analysed. The generated complex data processed by univariate and multivariate statistical methods enabled to build classification models for discrimination of apple cultivars as well as their geographical origin. The models showed very good performance in differentiation of Czech and Polish samples for three of four cultivars: ‘Gala’, ‘Golden Delicious’ and ‘Idared’, moreover, the validity of the models was verified over harvest seasons. The diagnostic markers, besides metabolites of triterpene biosynthetic pathway, mainly represented wax esters. ‘Jonagold’, which is known to be susceptible to mutations, was the only cultivar for which the unambiguous classification of geographical origin was not possible.

Suppose for n∈ ℕ, set A⊆ℝⁿ and function f∶A→ℝⁿ. If set A, using the Hausdorff outer measure, is measurable in the sense of Carathèodory; we want to find an extension of the expected value, w.r.t the Hausdorff measure, that's unique, finite and "natural" (defined on §2.3 & §2.4) for all f in a prevalent subset of ℝᴬ. The issue is current extensions of the expected value are finite for all functions in only a shy subset of ℝᴬ. The reason this issue wasn't resolved is mathematicians have not thought of the problem, focusing on application rather than generalization. Despite the lack of potential use, we'll attempt to solve the problem by defining a choice function---this shall choose a unique set of equivalent sequences of sets (Fₖ***) , where the set-theoretic limit of Fₖ*** is the graph of f; the measure Hʰ is the ℎ-Hausdorff measure, such for each k∈ℕ, 0 < Hʰ(Fₖ***) < +∞; and (fₖ*) is a sequence of functions where {(x,fₖ*(x))∶x∈ dom(Fₖ***)}=Fₖ***. Thus, the extended expected value of or E**[f,Fₖ***] is: ∀(ε>0)∃(N∈ℕ)∀(k∈N)(k≥N⇒1/Hʰ(dom(Fₖ***))∫dom(Fₖ*** )fₖ* dHʰ - E**[f,Fₖ***]<ε ) which should be unique, finite, and "natural" (defined on §2.3 & §2.4) for all f in a prevalent subset of ℝᴬ. Note we guessed the choice function using computer programming but we don’t use mathematical proofs due to the lack of expertise in the subject matter. Despite this, the biggest use of this research is the extension of the expected value is finite for "almost all" functions: this is easier to use in application when finding the "average" of functions covering an infinite expanse of space.

Cucurbitacin phytonematicides consistently suppress population densities of plant nematodes, but have no effect against bacteria, fungi and insects. This study investigates the mechanism through which cucurbitacin phytonematicides consistently exert nematicidal properties on nematodes. Post 72-h exposure of second-stage juveniles (J2) of Meloidogyne enterolobii to geometric concentration of Nemafric-BL phytonematicide, J2 total proteins were measured using TruspecCHNS Macro. Total proteins versus phytonematicide exhibited a negative quadratic relation (R² = 0.97), with the minimum total proteins achieved at x = 4.9% phytonematicide. Beyond the minimum, total proteins increased gradually, depicting the existence of both isoprenylation (breakdown) and farnesylation (biosynthesis) of total proteins. In conclusion, cucurbitacins and nematode cuticles are both chemically structured, which provides the mechanism through which the test chemicals consistently decrease population densities of plant nematodes.

The objectives of this paper are to investigate the tradeoffs between a physically constrained neural network and a deep, convolutional neural network and to design a combined ML approach ("VarioCNN"). Our solution is provided in the framework of a cyberinfrastructure that includes a newly designed ML software, GEOCLASS-image, modern high-resolution satellite image data sets (Maxar WorldView data) and instructions/descriptions that may facilitate solving similar spatial classification problems. Combining the advantages of the physically-driven connectionist-geostatistical classification method with those of an efficient CNN, VarioCNN provides a means for rapid and efficient extraction of complex geophysical information from submeter resolution satellite imagery. A retraining loop overcomes the difficulties of creating a labeled training data set. Computational analyses and developments are centered on a specific, but generalizable, geophysical problem: The classification of crevasse types that form during the surge of a glacier system. A surge is a glacial catastrophe, an acceleration of a glacier to typically 100-200 times its normal velocity. GEOCLASS-image is applied to study the current (2016-2024) surge in the Negribreen Glacier System, Svalbard. The geophysical result is a description of the structural evolution and expansion of the surge, based on crevasse types that capture ice deformation in six simplified classes.

Space exploration is an arduous journey, with future explorations extending in duration, increasing the risk for common space-related health issues such as bone density loss due to microgravity, impaired gut microbiota, cardiovascular ailments, and exposure to cosmic radiation. These ailments can be addressed using medicinal plants. Enhancing their efficacy entails employing gene editing to target specific secondary metabolite pathways associated with therapeutic properties. Moreover, gene editing can combine multiple medicinal properties from various plants, culminating in a singular 'superplant' with enhanced therapeutic benefits. This review discusses the current usage of medicinal plants in promoting human health during space travel, the application of gene editing technology in modifying medicinal plants and presents a vision for the utilization of gene-edited medicinal plants in space to mitigate the risk of various space-related health issues.

The purpose of this study is to analyze how global research cooperation patterns in the secondary battery industry have changed over recent years and to identify the evolution in the focus of research. To this end, network analysis was performed using the nationality information of the authors of a 10-year multinational joint research paper related to lithium-ion batteries. Furthermore, keyword analysis and topic modeling were performed using the abstract data from the study. The results of this study confirm that some countries that are not well-known in the field, such as Australia, Spain, and France, showed high centrality, compared with the level of cooperation scale. Additionally, six research topics were identified. According to a comparison over the first half of the decade, no difference was observed in the appearance of keywords indicating high energy density and conductivity with lithium, a key mineral. Keyword distribution was high for topics like battery charging and discharging in the first half of the decade, and for next-generation battery materials, such as solid electrolytes, lithium metal anodes, and lithium-sulfur batteries in the second. These results provide insights into the establishment of R&D cooperation strategies by countries and pre-planning by companies in the battery industry.

Stroke is a global leading cause of death and disability. Knowledge of related guidelines is crucial for Emergency Department (ED) staff, influencing early diagnosis and timely treatment. We investigated Greek-Cypriot ED healthcare professionals' (nurses and physicians) knowledge in recognizing and managing stroke. A descriptive cross-sectional study spanned November 2019 to April 2020, encompassing four private and seven public EDs in the Republic of Cyprus. The data were collected through a self-reported questionnaire developed by the research team, consisting of 37 questions. Eight questions focused on sociodemographic and employment characteristics, 28 assessed knowledge in stroke recognition and management (each item was equally weighted without deliberate prioritization), and one question addressed self-assessment of knowledge in stroke care. 255 nurses [Response Rate (RR): 74.1%] and 26 physicians (RR: 47.3%) completed the questionnaire. The average correct response rate was 12.9 out of 28 statements (SD: 4.2), with nurses and physicians scoring 12.6 (SD: 4.1) and 15.7 (SD: 4), respectively. Work experience significantly influenced stroke knowledge, with all groups demonstrating superiority over those with less than one year of experience. Participants with previous training scored an average of 1.45 additional correct answers while educational attainment did not significantly influence stroke knowledge. Investigating stroke knowledge among Emergency Department nurses and physicians in the Republic of Cyprus revealed significant deficits. The study stresses targeted interventions, including, education, yearly examinations, workshops with hands-on training, and repeated training, to address these gaps and enhance the overall stroke care capabilities of the healthcare professionals.

Astronauts in space are subject to a continuous bombardment of ionizing radiation. The Earth's magnetic field and the ISS shield some biologically damaging particles traveling through. Still, travel beyond low-Earth orbit and extravehicular activities are exceedingly more dangerous and there is a concern for the acute and late-occurring adverse health effects befalling astronauts. So, it is vital to consider the current tools and models used to describe and study the organic consequences of ionizing radiation exposure. It is equally important to see where these models may improve. This article reviews the historical development and current state of knowledge of radiation effects impacting astronauts in orbit. We explain the space radiation environment, cellular microenvironment, and how these may be incorporated in radiobiological models to aid in our understanding of the influence space travel may have on astronaut health. The topics discussed in this paper include a review of DNA damage and repair mechanisms and the numerical models that aim to explain the biological effects resulting from ionizing radiation damage. Historically, radiobiological models focused on how radiation damages nuclear DNA, built upon the hypotheses of Crowther and Lea in the 1940s and 1960s, and neglected other sub-cellular targets outside of nuclear DNA.

Abstract: This review addresses the complexities of type 1 diabetes (T1D)and its associated complications, with a par-ticular focus on diabetic retinopathy (DR). This review outlines the progression from non-proliferative to proliferative diabetic retinopathy and diabetic macular edema, highlighting the role of dysglycemia in the pathogenesis of these conditions. A significant portion of the review is devoted to technological advances in diabetes management, particu-larly the use of Hybrid Closed Loop systems (HCLS) and to the potential of open-source HCLS systems, which could be easily adapted to different patiens’needs using big data analytics and machine learning. Personalized HCLS algorithms that integrate factors such as patient lifestyle, dietary habits, and hormonal variations are highlighted as critical to reducing the incidence of diabetes-related complications and improving patient outcomes.

The new slide roller burnishing (SRB) method has been developed to produce mirror-like surfaces. Unlike conventional roller burnishing (RB), SRB is implemented through a unique device that allows the axes of the deforming roller and the rotary workpiece to cross resulting in a relative sliding velocity that can be controlled (in magnitude and direction) by varying the crossing angle. In the present work, the effect of SRB on the fatigue behavior of AISI 316 steel fatigue specimens was investigated by comparing with a conventional RB using the basic correlation in surface engineering: finishing–surface integrity (SI)–operating behavior. To obtain a more representative picture of the comparison, we implemented each method (RB and SRB) with two combinations of governing factors: (A) a radius of the roller toroidal surface of 3 mm, a burnishing force of 250 N and feed rate of 0.05 mm/rev (RB-A and SRB-A) and (B) a radius of the roller toroidal surface of 4 mm, a burnishing force of 550 N and feed rate of 0.11 mm/rev (RB-B and SRB- B). Both SRB-A (crossing angle of –45°) and SRB-B (crossing angle of –30°) achieved mirror-finish surfaces. SRB-B lead to the greatest fatigue strength and, thus, the longest fatigue life among all tested processes. SRB-B created the deepest zone (&gt;0.5 mm) with residual compressive macro-stresses and a clearly defined modified surface layer, whose thickness of more than 20 m is about twice that created by the other three processes.

In this paper, we present a three-step sixth-order iterative schemes to estimate the solutions of a nonlinear systems of equations, for predicting the shear strength of a reinforced concrete beam. This procedure is designed by means of a weight function technique. The values for the parameters of this system were randomly selected inside the prescribed ranges by technical standards for structural concrete; moreover, some of this parameters were fixed taking into consideration the solvability region of the adopted steel constitutive model. The efficiency of the new class is compared with other current schemes, with very good results.

The concept of collecting data of people using a domestic space is not novel. However, the methods and processes used to decipher this raw data and transform it into useful and appropriate information (i.e., sequence, duration, and timing derived from domestic activities) have been challenging and the focus of many research groups. But how are the results of the decoded transposition received, interpreted and used by the various professionals (e.g., occupational therapists and architects) who consume the information? This paper describes the inclusive evaluation process undertaken, which involved architects, engineers and end-users (not the occupant, but the care team managing the occupant). Finally, our study evidence the importance of making accessible to a multidisciplinary audience spatial, temporal and sequential aspects derived from people's domestic routines. Shedding light on how a systematic approach to collecting, processing and mapping low-level sensor data into higher forms and representations can be a valuable source of knowledge for improving the domestic living experience.

In this age of mass media and, in particular, social media-driven perception of reality, coupling disease and prophylactic opinion dynamics models can provide better insights into disease evolution than using a disease model alone. We develop in this work two disease-opinion dynamics models based on the epidemiology of the new coronavirus disease (COVID-19) and the availability or not of imperfect vaccines. We assume that susceptibility to infection decreases with the level of prophylactic attitude (personal hygiene, social distancing), and changes in prophylactic attitudes of susceptible individuals occur in response to perceived disease prevalence and vaccination coverage and efficacy in the population. We derive and discuss the disease-free equilibriums and reproduction numbers in the introduced models. We further assess the impacts of the distribution of opinions at disease introduction, the ability to detect presymptomatic, asymptomatic and symptomatic positive COVID-19 cases, the behavioural responses to the outbreak and the introduction of vaccination, and the effects of distortions of disease prevalence by public policy and mass media on disease dynamics. The insights highlighted from the proposed models are expected to make informative contributions to public policy in a context of opinion fluxes in response to perceived disease prevalence.

Lifestyle physical activity (PA) and nutrition are known to be effective interventions in preventing and managing obesity related comorbidities is adult populations, but less so in children and adolescents. We examined the effectiveness of lifestyle interventions in children from minority ethnic populations in western high-income countries. Our systematic review included 53 studies involving 26045 children from minority ethnic populations within western countries, who followed lifestyle intervention programs lasting between 8 weeks and 5 years with an aim to prevent and/or manage childhood obesity and associated comorbidities, including adiposity and cardiometabolic risks. Studies were heterogenous in terms of lifestyle intervention components (nutrition, PA, behavioural counselling) and settings (community vs. schools and after schools). Our meta-analysis included 31 eligible studies and showed no significant effects of lifestyle interventions when they focused on body weight and body mass index (BMI) outcomes [pooled BMI mean change = -0.09 (95% CI -0.19, 0.01), p=0.09]. This was irrespective of the intervention program duration (< 6 months vs. ≥ 6 months), type (PA vs nutrition/combined intervention) and weight status (overweight or obese vs no normal weight), all showed no significant effects in the sensitivity analysis. Nonetheless, 19 of the 53 studies reported reduction in BMI, BMI z scores and body fat percentage. However, majority of lifestyle interventions adopting a quasi-design with a combined primary and secondary obesity measures (11 out of 15 studies), were effective in reducing obesity comorbidities of cardiometabolic risks including metabolic syndrome, insulin sensitivity, and blood pressure in children with overweight and obesity. Preventing childhood obesity and associated comorbidities in children from high-risk ethnic minority groups is best achieved using a combined PA and nutrition intervention approach, which jointly target preventing obesity and cardiometabolic disease primary and secondary outcomes, especially measures of diabetes, hypertension, and cardiovascular disease.

This study uses the social impact theory to analyse consumer behaviour amidst Covid-19. Fear of scarcity has changed consumer buying behaviour in crisis times such as the now abating global health crisis – i.e., Covid-19. The study asserts that the existing five-stage model of consumer purchasing decisions does not fit neatly in turbulent times. It proposes a shortened four-stage process of need recognition, purchase, ownership and satisfaction as a better and more adaptable fit. Cutting out information search and evaluation of alternatives in the old model, and replacing these with ownership, is where the main contribution of the study lies. The study has implications for managing the marketing mix as we know it. It asserts that not all the 4Ps of the marketing mix are important in crisis times.

Deep learning dominates automated animal activity recognition (AAR) tasks due to the high performance on large-scale datasets. However, constructing centralised data across diverse farms raises data privacy issues. Federated learning (FL) provides a distributed learning solution to train a shared model by coordinating multiple farms (clients) without sharing their private data. Whereas directly applying FL to AAR tasks often faces two challenges: client-drift during local training and gradient conflicts during global aggregation. In this study, we develop a novel FL framework called FedAAR to achieve AAR with sensor data. Specifically, we devise a prototype-guided local update module to alleviate the client-drift issue, which introduces global prototypes as shared knowledge to force clients to learn consistent features. To reduce gradient conflicts between clients, we design a gradient refinement-based aggregation module to eliminate conflicting components between client gradients during global aggregation, thereby improving the agreement between clients. Experiments are conducted on a public dataset to verify FedAAR’s effectiveness, which consists of 87,621 2-s motion data. The results demonstrate that FedAAR outperforms state-of-the-arts, with precision (75.23%), recall (75.17%), F1-score (74.70%), and accuracy (88.88%), respectively. The ablation experiments also show FedAAR’s robustness against various factors (i.e., different data sizes, communication frequency, and client numbers).

The world's growing population is highly dependent on animal agriculture. Animal products provide nutrient-packed meals that help to sustain individuals of all ages in communities across the globe. As the human demand for animal proteins grows, the agricultural industry must continue to advance its efficiency and quality of production. One of the most commonly farmed livestock is poultry and their significance is felt on a global scale. Current poultry farming practices result in the premature death and rejection of billions of chickens on an annual basis before they are processed for meat. This loss of life is concerning regarding animal welfare, agricultural efficiency, and economic impacts. The best way to prevent these losses is through the individualistic and/or group level assessment of animal on a continuous basis. On large-scale farms, such attention to detail was generally considered to be inaccurate and inefficient, but with the integration of Artificial Intelligence (AI) assisted technology individualized and per-herd assessments of livestock are possible and accurate. Various studies have shown cameras linked with specialized systems of AI can properly analyze flocks for health concerns, thus improving the survival rate and product quality of farmed poultry. Building on the recent advancements, this review explores the aspects of AI in the detection, counting and tracking of the poultry in commercial and research-based applications.

The outbreak of SARS-COV-2 disease 2019 (COVID-19) abruptly changed the patterns in electricity consumption, challenging the system operations of forecasting and balancing supply and demand. This is due to the mitigation measures that include lockdown and Work from Home (WFH), which decreased the aggregated demand and remarkably altered its profile. Here, we characterise these changes with various quantitative markers and compare it with pre-COVID-19 business-as-usual data using Great Britain (GB) as a case study. The ripple effects on the generation portfolio, system frequency, forecasting accuracy and imbalance pricing are also analysed. An energy data extraction and pre-processing pipeline that can be used in a variety of similar studies is also presented. Analysis of the GB demand data during the March 2020 lockdown indicates that a shift to WFH will result to a net benefit for flexible stakeholders, such as consumer on variable tariffs. Furthermore, the analysis illustrates a need for faster and more frequent balancing actions, as a result of the increased share of renewable energy in the generation mix. This new equilibrium of energy demand and supply will require a redesign of the existing balancing mechanisms as well as the longer-term power system planning strategies.

Social, cultural, environmental and economic factors closely regulate the selection, allocation and consumption of maternal diets. We developed a nutrition behaviour change intervention to promote a balanced diet in pregnancy through practical demonstration in rural Bangladesh and tested the impact with a cluster randomised controlled trial. This paper presents the findings of the process evaluation and describes the strategies that worked for intervention compliance. We conducted in-depth interviews with pregnant women, women who birthed recently, and their husbands; focus groups with mothers and mothers-in-law; key-informant interviews with community health workers, and observation of home visits. We identified six key areas within the intervention strategy that played a crucial role in achieving the desired adherence. These included practical demonstration of portion sizes; addressing local food perceptions; demystifying animal-source foods; engaging husbands and mothers-in-law; leveraging women’s social networks; and harnessing community health workers’ social role. Practical demonstration, opportunity to participate and convenience of making of the plate with the food available in their kitchen or neighbours’ kitchen were the most commonly mentioned reasons for acceptance of the intervention by the women and their families. The balanced plate intervention helped women through practical demonstration to learn about a balanced meal by highlighting appropriate portion sizes and food diversity. The women needed active involvement of community health workers in mobilising social support to create an enabling environment essential to bring changes in dietary behaviours. Programs to promote a nutritious maternal diet should focus on encouraging the use of healthy foods through practical demonstration of portion sizes and engagement of the women and family instead of replicating the traditional information-based counselling.

This paper attempts to alter a prevailing assumption that buildings use energy to an understanding that in fact, people use energy. Therefore, to successfully accelerate the transition to a low-carbon society and economy more emphasis should be on motivating people and increasing their awareness by making them energy conscious building users and therefore active players in the energy transition process. In this context, this paper provides insights from the Horizon 2020 MOBISTYLE project. It demonstrates research and development approaches, highlights the main project objectives, and presents findings of an ethnographic (qualitative) study of users’ habits, practices, and needs. The aim of the project is to motivate behavioural change by raising consumer awareness through the provision of attractive personalized information on user’s energy use, indoor environment and health, all enabled by an integrated information and communication technology (ICT) service. In this context, the anthropological people-centred approach is integrated into the MOBISTYLE approach putting users at the centre of the ICT tools development process. The main quantitative objective of the project is a reduction of energy use for at least 16 % prompted by the provision of combined information and feedback systems on energy, indoor environmental quality (IEQ) and health. The most relevant motivational factors and key performance indicators (KPIs) for encouraging a more energy conscious and healthy lifestyle were defined by means of a people-centred approach, adopting anthropological inquiries in different settings. Information about users’ lifestyles and their needs was collected in focus groups with potential users in five case studies, located in different European Union (EU) countries. Behaviour change is achieved through awareness campaigns, which encourage users to be pro-active about their energy consumption and to simultaneously improve health and well-being.