Abstract: Cardiovascular Disease (CVD) is the most prevalent disease worldwide, which has been linked to work stress because of poor job design as explained by the Job Demand-Control (JDC) and the Effort-Reward Imbalance (ERI) models. In this paper we explore for the first time relative impact of a specific aspect of organisational climate, Psychosocial Safety Climate (PSC), on any CVD including angina, myocardial infarction, hypertension, and stroke. We used two waves of interview data from Australia, with an average lag of 5 years (excluding baseline CVD, final n = 1223). Logistic regression was conducted to estimate the prospective associations between PSC at baseline on incident CVD at follow-up. It was found that participants in low PSC environments were 59% more likely to develop new CVD than those in high PSC environments. Logistic regression showed that PSC at baseline predicts lower CVD risk at follow-up (OR = 0.98, 95% CI 0.96-1.00), and this risk remained unchanged even after joint adjustment for measures of ERI and JDC. These results suggest that PSC is an independent risk factor for CVD in Australia. Beyond job design this study implicates organisational climate and prevailing management values regarding worker psychological health as the genesis of CVD.

Syncope and presyncope occurring during work can affect safety and impair occupational performance. Few data are available regarding the prevalence of these events among workers. The possible role of sleep quality, mental stress and metabolic disorders in promoting syncope, presyncope and falls in workers is unknown. In the present study, 741 workers (male 35.4%; mean age 47±11 years), employed in different companies, underwent clinical evaluation and blood tests and completed questionnaires to assess sleep quality, occupational distress and mental disorders. The occurrence of syncope, presyncope and unexplained falls during their working life was assessed by an ad hoc interview. The prevalence of syncope, presyncope and falls of unknown origin was 13.9%, 27.0%, and 10.3%, respectively. The occurrence of syncope was associated with an increased risk of occupational distress (adjusted Odds Ratio aOR: 1.62, Confidence Intervals at 95%: 1.05-2.52), low sleep quality (aOR: 1.79 CI 95%: 1.16-2.77) and poor mental health (aOR: 2.43 CI 95%: 1.52-3.87). Presyncope was strongly associated with occupational distress (aOR: 1.77 CI 95%: 1.25-2.49), low sleep quality (aOR: 2.95 CI 95%: 2.08-4.18) and poor mental health (aOR: 2.61 CI 95%: 1.78-3.84), while no significant relationship was found between syncope or presyncope and metabolic syndrome. These results suggest that occupational health promotion interventions aimed at improving sleep quality, reducing stressors and increasing worker resilience might reduce syncope and presyncope events in the working population.

Background: Physical and mental health of corporate employees is equally important, especially in international salespeople in the in vitro diagnostic (IVD) medical device industry. The rapid growth of the IVD market is driven by the increasing prevalence of chronic and infectious diseases. This study aims to identify the association of socio-demographic, occupational, organizational, and psychosocial factors with mental health outcomes for depression, anxiety, and somatic symptoms in Chinese IVD international salespeople. Methods: The study was a cross-sectional survey of ISs in IVD companies officially registered in China. An online survey was designed to collect data through email contact with IVD companies and social media between August 2022 and March 2023. Measured factors included effort-reward imbalance (ERI), health-promoting leadership (HPL), health climate (HC), inner strength (IS), and perceived social support (PSS). Mental health outcomes assessed using the Core Symptom Index (CSI) were depression, anxiety, and somatic symptoms. Results: A total of 244 salespeople responded to the survey. CSI scores indicated that 18.4% (n = 45) and 10.2% (n = 25) of the respondents had symptoms of major depression and anxiety, respectively. ERI was positively correlated, while the IS and PSS were negatively correlated with major depression, anxiety, and somatic symptoms (p < .01). Health climate was negatively correlated with major depression (p < .05). Education background was associated with somatic symptoms (p < .05). ERI, IS, and gender were significant predictors of major depression, anxiety, and somatic symptoms (p < .05). Conclusion: The prevalence of depression and anxiety in China’s IVD international salespeople was considered low compared with prevalence in Chinese populations during COVID-19, but higher than those before the pandemic. Effort–reward imbalance, inner strength, and gender were significant factors in major depression, anxiety, and somatic symptoms among IVD international salespeople.

Early childhood is important for future cognitive and educational outcomes. Programs overcoming barriers to engagement in early education for Indigenous children must address family cultural needs and target developmental delays. This systematic review identifies culturally adapted programs to improve cognitive, emotional and developmental delays among young children, in response to an identified priority of a remote Indigenous community. Five databases (the Cochrane Library, Embase, Medline, Scopus and CINAHL) were searched for English language papers in January 2018. Study quality was assessed and findings analysed thematically. Findings were presented to the community at an event with key stakeholders, to determine their inclusion and face validity. Seven relevant studies, published between 1997-2013, were identified by the researchers and each study was supported by the community for inclusion. Two studies focused on Native American children and five studies included children from non-Indigenous disadvantaged backgrounds. Findings were reported narratively across four themes: Storytelling to improve educational outcomes; Family involvement improved development; Culturally adapted Cognitive Behavioral Therapy to reduce trauma; Rewards-based teaching to improve child attention. Limited published research on culturally adapted and safe interventions for children with cognitive, emotional and developmental delay exists but these four themes from seven studies identify useful components.

Purpose: The purpose of this study is to determine the effects of post-purchase regret felt by consumers buying fashion products and their efforts to reverse their regrets, on dissatisfaction and their repurchase intention. Design/Methodology/Approach: The population of this research consists of the consumers in Gaziantep who buy fashion products and regret their purchase for any reason. Out Of non-probability sample methods, convenience sampling was used. Thinking that this can represent the population of the study, the sample number was determined as 441. In order to test the hypotheses, Smart PLS 3 (Partial Least Squares) statistics programme was used. Bootstrapping technique was used to test the hypotheses intended to be measured in the study. Findings: The tests show that regret positively affect dissatisfaction (ß=,544, p<0,001) and the effort to reverse the feeling of regret. In addition, regret negatively affect repurchase intentions. Another variable, dissatisfaction negatively affect re-purchasing intention and regret reversing efforts positively affect re-purchasing intentions. Research limitations: Because the study is restricted by time, cost, accessibility, control difficulties; the whole of the population was not reached. The study is conducted with the data obtained from 441 consumers in Gaziantep and evaluations made by consumers who prefer ready-made wear. Practical implications: The results show that regret experienced in the past negatively affect re-purchasing process. It has been determined that the consumers can diminish their regret when they try to reverse it and this situation strengthens their re-purchasing intentions. Hence, it is thought to be beneficial to ensure that consumers are aware of their regrets and to focus on strategies that help enterprises to reverse this regret. Originality/value: Even though there are studies that associate regret with dissatisfaction and repurchase intentions, there are very few studies that focus on regret reversing efforts. There is no such study in local literature. Therefore, this study is original in these aspects and it is thought that it will contribute to the body of literature.

Objective: This paper aims to build an Effort Estimation Model for design, coding and testing Web Applications Based Fuzzy and Practical Models, which will help in optimizing the efforts in software development. Methods/Analysis: Soft computing approach is adopted and applied in the effort estimation and then compared with practical efforts in the development process with interpreting the historical data available for the existing functionalities. Findings: The effort estimation model presented in this paper focuses on the first level estimates published by Project Managers and the second level estimates presented by Project Leaders or Developers for any new requirement or enhancement for a web application built on 3-tier architecture using Microsoft technologies. The model considers the classification of each task as either Low or Medium or High complexity. These tasks pertain to the lowest level parts in bottom-up estimation. Efforts are estimated for designing, coding and unit testing of these tasks and the efforts are summed up to get the effort estimation for the higher level which is a feature to be implemented. Novelty/Improvement: The paper also discusses about the application of the effort estimation model by taking a new requirement as a case study. The first level estimates calculated using the effort estimation model has a variance of about 25% when compared with the actual effort. This variance is very much acceptable considering the fact that the first level estimates can be tolerable up to 35%. The proposed effort estimation tool would help the project managers to efficiently control the project, manage the resources effectively, and improve the software development process and also trade off analyses among schedule, performance, quality and functionality. Fuzzy logic is used to verify the claims made in efforts estimation. It is proposed a new relation between the number of data and efforts value membership for actual data. And converts it into crisp value in the range [0…1] which helps to classify the complexity of the task and subtask in the design, coding and testing phases.

Brain-stimulation reward, also known as intracranial self-stimulation (ICSS), is a commonly used procedure for studying brain reward function and drug reward. In electrical ICSS, an electrode is surgically implanted into the medial forebrain bundle in the lateral hypothalamus or the ventral tegmental area in the midbrain. Operant lever responding leads to the delivery of electrical pulse stimulation. The alteration in the stimulation frequency-lever response curve is used to evaluate the impact of pharmacological agents on brain reward function. If a test drug induces a leftward or upward shift in the ICSS response curve, it implies a reward-enhancing or abuse-like effect. Conversely, if a drug causes a rightward or downward shift in the functional response curve, it suggests a reward-attenuating or aversive effect. A significant drawback of electrical ICSS is the lack of cellular selectivity in understanding the neural substrates underlying drug reward versus aversion. Excitingly, recent advancements in optical ICSS (oICSS) have facilitated the development of at least three cell type-specific oICSS models – dopamine-, glutamate-, and GABA-dependent oICSS. In these new models, a comparable frequency-rate response curve has been established and employed to study the substrate-specific mechanisms underlying brain reward function and a drug's rewarding versus aversive effects. In this review article, we summarize recent progress in this exciting research area. The findings in these new behavioral models have not only increased our understanding of the neural mechanisms underlying drug reward and addiction but have also introduced a novel experimental approach in preclinical medication development for treating substance use disorders.

Machine learning offers advanced tools for efficient management of radio resources in modern wireless networks. In this study, we leverage a multi-agent deep reinforcement learning (DRL) approach, specifically the Parameterized Deep Q-Network (DQN), to address the challenging problem of power allocation and user association in massive multiple-input multiple-output (M-MIMO) communication networks. Our approach tackles a multi-objective optimization problem aiming to maximize network utility while meeting stringent quality of service requirements in M-MIMO networks. To address the non-convex and nonlinear nature of this problem, we introduce a novel multi-agent DQN framework. This framework defines a large action space, state space, and reward functions, enabling us to learn a near-optimal policy. Simulation results demonstrate the superiority of our Parameterized Deep DQN (PD-DQN) approach when compared to traditional DQN and RL methods. Specifically, we show that our approach outperforms traditional DQN methods in terms of convergence speed and final performance. Additionally, our approach shows 72.2 % and 108.5 % improvement over DQN methods and RL method respectively in handling large-scale multi-agent problems in M-MIMO networks.

Here we present a blockchain-backed token recognition system to reward the contributions that academics make to the scientific ecosystem. Recognition is important in science but current methods, systems and incentives are limited. Specifically, the traditional focus on narrow publication metrics means diverse contributions are not captured, while bias toward senior, established scientists is common. To tackle this challenge, we explore the potential of harnessing blockchain’s collaborative, decentralised and trust-brokering properties to develop a token reward system for use by research funders. Academics would be awarded tokens for undertaking common but vital tasks such as peer review, sitting on funding committees and submitting reports. These tokens would not be tradable or specifically monetisable but would serve as a validated record of scientific contribution. They would have value in professional recruitment and job placement, support grant and award applications, and inform performance appraisals and file reviews. Coordination and cooperation across multiple funding agencies in developing the platform would provide an opportunity to aggregate and standardise recognition, given academics often work with several funders. This system’s goals are to expand recognition metrics, promote efficiencies, improve the robustness of professional assessments and enable cross-funder collaboration, thereby optimising research processes and practices in a decentralised and democratised manner.

Background: Previous neuroimaging studies have identified brain regions related to respiratory motor control and perception. However, little is known about the resting-state functional connectivity (FC) associated with respiratory impairment. We aimed to determine the FC involved in mild respiratory impairment without changing the saturation of percutaneous oxygen. Methods: We obtained resting-state functional magnetic resonance imaging data from 36 healthy volunteers during normal respiration and mild respiratory impairment induced by resistive load (effort breathing). ROI-to-ROI and seed-to-voxel analyses were performed using Statistical Parametric Mapping 12 and the CONN toolbox. Results: Compared to normal respiration, effort breathing activated FCs within and between the sensory perceptive area of respiration (the postcentral gyrus, anterior insular cortex (AInsula), and anterior cingulate cortex) and visual cortex (the visual occipital, occipital pole (OP), and occipital fusiform gyrus). Graph theoretical analysis showed strong centrality in the visual cortex. A significant positive correlation was observed between the dyspnoea score (modified Borg scale) and FC between the left AInsula and right OP. Conclusions: These results suggested that the FCs within the respiratory sensory area via the network hub may be neural mechanisms underlying effort breathing and modified Borg scale scores.

This work focused on Diplectanum aequans, a gill parasite of Dicentrarchus labrax. Analyzes allowed us to detect factors regulating parasites distribution on Corsican fish-farms, and to highlight the ecological structure of D. aequans communities on gills of fish. The study of parasite distribution showed that bigger fish appear more parasitized and that the infection dynamics of D. aequans can be explained by several factors such as biotic factors or farm environment conditions. The study of gill repartition of D. aequans showed that parasites tend to have a homogeneous distribution with no statistically significant difference in infection between two sides on each fish. However, the distribution of the number of parasites on gill arches varies according to the total number of parasites. Results differ depending on infection degree and host weight. When parasites are numerous, the individuals are distributed on the gill arches according to an antero-posterior gradient, while with low rates of infection, the parasites are randomly distributed on the 4 arches. The spatial distribution of D. aequans appears to be determined by the differential action of water flow through gill arch and the size of anterior arches. We also proposed a tool in order to reduce the sampling effort and allow optimal exploitation for fish farmers.

Animal-focused research has been crucial for scientific advancement however, in this matter, rodents are still taking a starring role. Coming out from merely being supportive of evidence found in rodents, the use of fish models has slowly taken a more central role and expanded its overall contributions in areas such as social sciences, evolution, physiology, and recently in translational medical research. In neurosciences, zebrafish has been widely adopted, contributing to our understanding of the genetic control of brain processes, and the effects of pharmacological manipulations. However, discussion continues regarding the paradox of function versus structure, when fish and mammals are compared, and on the potentially evolutionarily conserved nature of behaviour across fish species. From the behavioural stand point we explored aversive/stress and social behaviour in selected fish models, and refer to the extensive contributions of stress and monoaminergic systems. We suggest that, in spite of marked neuroanatomical differences between fish and mammals, stress and sociality are conserved at the behavioural and molecular levels. We also suggest that stress and sociality are mediated by monoamines in predictable and non-trivial ways, and that monoamines could “bridge” the relationship between stress and social behaviour. To reconcile the level of divergence with the level of similarity, we need neuroanatomical, pharmacological, behavioural, and ecological studies conducted in the laboratory and in nature. These areas need to add to each other to enhance our understanding of fish behaviour and ultimately how this all may translate to better model systems for translational studies.

Social interaction is essential for life and is impaired in many psychiatric disorders like schizophrenia, au-tism, depression and major anxiety disorder. Monoamine transmission plays a key role in social behavior and both genetic and epigenetic modifications of dopamine and noradrenaline neurotransmission-related genes can affect the levels of social interaction. Since heterozygous individuals for a specific genetic trait possess only one mutant allele of that trait, in order to better evaluate the role of the interaction between genetics and epigenetics in unmasking latent genetically-determined predispositions, our interest has focused on studying the interplay between genetics and epigenetics influences on social behavior in male rats obtained by two different breeding schemes: a first group by breeding of knock-out (KO) male rats with wild-type (WT) female dams (homogeneous heterozygous offspring, termed MAT-HET), and a second group of heterozygous DAT male offspring by breeding of KO male and DAT-heterozygous female subjects (to obtain comparable control pups, termed MIX-HET). Their social behavior was then assessed by partner preference, social preference and elicited preference tests. In the first test MIX-HET and MAT-HET male mice had choice between two WT females one in estrous and the other not in estrous. In the second test they met either a MIX-HET or a WT male rodent. Also, the expression of the noradrenaline transporter (NET) was assessed in the prefrontal cortex, hippocampus and hypothalamus of MAT, MIX and WTs by immunofluorescence in order to estimate its involvement in the expression of social behavior. Our results show that MIX-HET focal rodents tend to have an asocial behavior when in contact with a female in estrous, and their behavior is similar to when the stimulus is a MIX-HET male. MAT-HET male rodents, instead, tend to be very attracted by the female in estrous, but they ignore the MIX-HET stimulus. MIX-HET progeny showed a lower expression of noradrenaline transporter in both hypothalamus and hippocampus with respect to MAT-HET rats, whereas MAT-HET rats displayed increased noradrenaline transporter immunofluorescence in the hypothalamus and in the hippocampus with respect to WT rats, while no difference was observed in the prefrontal cortex. Therefore we can hypothesize that the differences observed between the two heterozygous groups may be attributable to an epigenetic factor: the different maternal care received. These data can open new perspectives towards increased the preclinical knowledge about autism and bipolar disorder.

Environmental responsibility and economic benefits have promoted the development of closed-loop supply chain (CLSC), and shortages and channels are considered to be two important issues in CLSC. This paper explores ordering and channel decisions in CLSC with new and differentiated remanufactured products, and considers the price and sales effort-dependent demands, as well as the proportion of emergency orders determined by emergency order costs and backorder losses, and establishes an integrated and decentralized CLSC game models. We introduce a stochastic sales effort, which affects two types of products. Numerical results show that sales effort and the order quantity of new and remanufactured products exhibit concave and convex functions, respectively. Wherein, the upper limit of sales effort has a greater impact on supply chain decisions. High sales efforts can serve as a means of coordinating dispersed supply chains. Moreover, in different cases, decisions of integrated channel are better than those of decentralized channel. Finally, whether the supply chain adopts an emergency order strategy depends on the relative cost of emergency orders and out of stock costs. According to the research in this article, some management insights are also provided.

Purpose: School-age children with autism spectrum conditions (ASC) often experience difficulties in speech-in-noise (SiN) perception, leading to increased listening effort that impacts their well-being and academic performance. This study aimed to investigate the SiN processing challenges faced by Mandarin-speaking children with ASC and its impact on their listening effort. Methods: Participants completed sentence recognition tests in both quiet and noisy conditions, with a steady-state noise masker presented at 0 dB signal-to-noise ratio in the noisy condition. We compared recognition accuracy and task-evoked pupil responses from 23 Mandarin-speaking children with ASC to 19 age-matched neurotypical (NT) counterparts to gauge their behavioral performance and listening effort during these auditory tasks. Results: The ASC group demonstrated notably decreased accuracy in noise compared to their NT peers, suggesting poorer SiN perception. Pupillometric data further revealed significantly larger peak dilations in the ASC group than in the NT group under comparable conditions. Importantly, the ASC group's peak dilation in quiet mirrored the NT group's in noise. However, the ASC group exhibited shorter peak latencies and reduced mean dilations than the NT group in similar conditions. Such patterns indicate the ASC group might initially experience a heightened cognitive load but utilize fewer cognitive resources as the task continued, indicating an atypical allocation of cognitive resources and a potential tendency towards relatively superficial and automated auditory processing. Conclusion: Our findings highlight the unique SiN processing challenges children with ASC face, underscoring the importance of a nuanced, individual-centric approach for interventions and support.

Humans’ performance varies due to the mental resources that are available to successfully pursue a task. To monitor users’ current cognitive resources in naturalistic scenarios, it is essential to not only measure demands induced by the task itself but also consider situational and environmental influences. We conducted a multimodal study with 18 participants (nine female, M = 25.9 with SD = 3.8 years). In this study, we recorded, respiratory, ocular, cardiac, and brain activity using functional near-infrared spectroscopy (fNIRS) while participants performed an adapted version of the warship commander task with concurrent emotional speech distraction. We tested the feasibility of decoding the experienced mental effort with a multimodal machine learning architecture. The architecture comprised feature engineering, model optimisation, and model selection to combine multimodal measurements in a cross-subject classification. Our approach reduces possible overfitting and reliably distinguishes two different levels of mental effort. These findings contribute to the prediction of different states of mental effort and pave the way toward generalised state monitoring across individuals in realistic applications.

The metaphor of being touched by music is widespread and almost universal. The tactile experience, moreover, has received growing interest in recent years. There is, however, a need to go beyond a mere metaphorical use of the term, by positioning the tactile experience within the broader frame of embodied cognition and the experiential turn in cognitive science. This article explores the possible contribution of a science of touch by defining music as a vibrational art that impinges upon the body and the senses. It takes as a starting point the clinical findings on the psychological and physiological value of tender touch with a special focus on the method of kangaroo mother care, which is a method for holding the baby against the chest of the mother, skin-to-skin. It is seen as one of the most basic affiliative bonding with stimuli that elicit reward. Via an extensive review of the research literature, it is questioned to what extent this rationale can be translated to the realm of music. There are, in fact, many analogies, but a comprehensive theoretical framework is still lacking. This article aims at providing at least some preparatory groundwork to fuel more theorizing about listening and its relation to the sense of touch.

Autism spectrum disorder (ASD) is a heterogeneous neuropsychiatric problem with a few core symptoms: weaknesses in social behavior, verbal impairments, repetitive behavior and restricted interests. Beyond the core symptoms, autism has strong association with other disorders such as intellectual disability, epilepsy, schizophrenia among many others. This paper outlines a theory of ASD with capacity to connect heterogeneous ‘core’ symptoms, medical and psychiatric comorbidities as well as other etiological theories of autism in a unifying cognitive framework rooted in neuroscience and genetics. Cognition is embedded into an ever-developing structure modified by experiences, including the outcomes of environment influencing behaviors. We introduce the hypothesis that autism is caused by deficits in component-based cognition and the internal learning reinforcing machinery. Specifically, we outline our Cartesian Factor forming autoencoder like model that supports cognition by breaking combinatorial explosion and discuss the cognitive and neural processes behind our model. The high dimensionality of sensory information poses serious problems, since the brain can handle only 7±2 relevant variables at a time making processes, such as the extraction and encoding of the relevant variables and their efficient manipulation critical. These processes are influenced by previous experiences and the internal reward system. In addition, large delays of distributed information processing should be counteracted by learned predictive models to synchronize sensory, proprioceptive, and cognitive signals and have timely and accurate model-based actions. Impairments in any of these aspects may disrupt learning and execution. Combinations of small impairments may allow the solving of low complexity tasks but may become visible if learned variables and the related metric are improper and imprecise, respectively, especially if their number is large. We claim that social interactions are amongst the most challenging cognitive tasks in terms of the number of variables involved. In turn, they are highly susceptible to combinations of small impairments. We consider impairments as the basic colors of autism, whereas the combinations of diverse impairments make the palette of autism. In turn, social processes can be spoiled in many ways and can lead to diverse comorbidities.

Software project estimating (SPE) is a powerful but necessary step in the production of projects for software. Software project estimating includes several components, estimating software time, software resources, software costs, and software effort estimation (SEE). SEE seeks to estimate the number of "hours-person" and "months-person" of work required for developing or managing a software program. During the initial phase of the development of software, future efforts are impossible to predict. To estimate effort, many deep learning (DL) and machine learning (ML) models were previously created. For estimate, single-model techniques and ensemble methods were investigated in this research. Ensemble methods involve a combination of multiple separate models. Bagging, boosting, and voting were the ensemble methods looked into for estimation. Datasets considered for estimation were COCOMO81, COCOMONasa I, COCOMONasa II, Albrecht, Maxwell, China, Desharnais, Desharnais_1_1, Kitchenham, Boehm, and Belady. The evaluation criteria used MAE, RAE, RMSE, RRSE, and CC. The result from previous studies is that the total size of the set of data utilized is small in predicting the effort, as the largest size of the set of data used is the China dataset containing only 499 projects. So, in this study, the dataset has been merged to increase the total size of the set of data and increase the accuracy of prediction. The results indicated that the suggested merged dataset increased effort estimation accuracy.

Changes in food preferences after bariatric surgery may alter its effectiveness as a treatment for obesity. We aimed to compare food reward for a comprehensive variety of food categories between patients who received a sleeve gastrectomy (SG) or a Roux-en-Y gastric bypass (RYGB) and to explore whether food reward differs according to weight loss. In this cross-sectional exploratory study, food reward was assessed using the Leeds Food Preference Questionnaire (LFPQ). We assessed liking and wanting of eleven food categories. Comparisons were done regarding type of surgery and Total Weight Loss (TWL; based on tercile distribution). Fifty-six patients (30 SG and 26 RYGB) were included (women: 70%; age: 44.0 (11.1) y). Regarding the type of surgery, scores were not significantly different between SG and RYGB, except for ‘non-dairy products – without color’ explicit liking (p = 0.04). Regarding TWL outcomes, explicit liking, explicit wanting and implicit wanting, scores were significantly higher for Good responders than Low responders for ‘No meat – High fat’ (post-hoc corrected p-value: 0.04, 0.03 and 0.04, respectively). Together, our results failed to identify major differences in liking and wanting regarding the type of surgery and tended to indicate that higher weight loss might be related to a higher reward for high protein-content food. Rather to focus only on palatable foods, future studies should also consider a broader range of food items, including protein reward.

Scientists observe, discover, justify and eventually share their findings with the scientific community. Dissemination is an integral aspect of scientific discovery since discoveries which go unnoticed have no or little impact on science. Today, peer-review is part of this process of scientific dissemination as it contributes proactively to the quality of a scientific article. As the numbers of scientific journals and scientific articles published therein are increasing steady, processes such as the single-blind or double-blind peer review are facing a near collapse situation. In fact, these traditional forms of reviewing have reached their limits and, because of this, are also increasingly considered as unfair, sloppy, superficial and even biased. In this manuscript we propose forms of Post Publication Public Peer Review (P4R) as valuable alternatives to the traditional blind peer review system. We describe how the journal Sci has explored such an approach and provide first empirical evidence of the benefits and also challenges such a P4R approach is facing.

When “hijacked” by compulsive behaviors that affect the reward and stress centers of the brain, functional changes in dopamine circuitry occur as the consequence of pathological brain adaptation. As a brain explanans for mental health, with a central functional role in behavioral regulation from healthy reward seeking to pathological adaptation to stress in response to adversity, we may use dopamine regulation in interaction with other brain mechanisms, as discussed herein, to gather a deeper insight into environmentally triggered mental health changes to understand, for example, specific behavioral changes observed during and after the COVID-19 pandemic. Pandemic-related adversities, the stresses they engendered, and the long lockdown periods where people had to rely on digital tools to get feed-back rewards via the internet can be seen as the major triggers of changes in motivation and reward seeking behavior worldwide. The pathological adaptation of dopamine-mediated reward circuitry in the brain offers a highly plausible explanation why, when pushed by fate and circumstance into a physiological brain state of anti-reward, human behavior and mental health changes almost inevitably depending on individual vulnerability to stress. A unified conceptual account that places dopamine function at the centre of the current global mental health context is proposed.

There is clinical concern about the combined use of alcohol and opiates. Several lines of evidence support an interaction between alcohol and the endogenous opioid system. Thus, we hypothesized that ethanol by causing the release of opioid peptides may sensitize the system to the action of exogenous opioids such as morphine. In this study, using the place conditioning paradigm as an animal model of reward, we determined whether a morphine challenge would alter the pre-established preference induced by ethanol conditioning in mice, and whether this response was mediated by the mu opioid receptor (MOP). Given that ethanol exposure stimulates the release of opioid peptides, we also assessed the role of beta-endorphin (β-END) and enkephalins (ENKs) in this response. Mice lacking MOP, β-END and/ or ENKs as well as their respective wild-type controls were tested for baseline place preference on day 1, conditioned with ethanol (2 g/kg) versus saline on days 2 to 4 and then tested under a drug-free state for postconditioning place preference on day 5. On day 8, mice received a single injection of morphine (5 mg/kg) and were tested for place preference. On each test day, mice were placed in the central neutral chamber and allowed to freely explore the conditioning chambers. The amount of time that mice spent in each chamber was recorded. We found that a challenge dose of morphine given on day 8 enhanced the CPP response in mice previously conditioned with ethanol. This response was abolished in MOP null mice, confirming the role of MOP in this response. Although this enhanced response was not altered in mice lacking either β-end or ENKs compared to their wild-type littermates/controls, it was completely blunted in mice lacking both β-end and enkephalins. Together, these results suggest that these opioid peptides jointly mediate the crosstalk between the rewarding actions of morphine and ethanol.

Recent times have witnessed an increasing number of countries and private firms pledging carbon neutrality by mid-century. Whilst representing a significant improvement in intentions to tackle climate change, such pledges lack substance and structure. For instance, individual pledges lack coordination and aggregation among peers, while strategies and measures to achieve ambitious targets are largely absent. Moreover, current disagreements obstructing progress in international climate change negotiations further undermine the reliability of carbon neutrality objectives. Effective international policies are needed to foster aggregate mitigation ambitions and the creation of adequate supporting mechanisms. This theoretical paper describes a governance innovation aimed at overcoming such shortfalls and disagreements through a unifying yet customizable pathway towards carbon neutrality. It does so by first outlining a political governance framework based on a climate club interpretation of Article 6 of the Paris Agreement. Secondly, it proposes carbon emission mitigation effort sharing on a per capita basis to ensure efficiency, equity and political feasibility. Thirdly, this paper describes how the supply of certified mitigations of carbon emissions required to satisfy effort sharing-based demand can be assetized as carbon credits by operationalizing Article 6 as a joint certification mechanism. The resulting governance architecture for managing demand and supply of mitigations shifts efforts to tackle climate change from a ‘problem-driven’ cost approach to ‘opportunity-driven’ value creation pathways towards carbon neutrality.

For many years, the programmable positioners have been widely applied in structures of modern electro-pneumatic final control elements. The positioner consists of an electro-pneumatic transducer, embedded controller and measuring instrumentation. Electro-pneumatic transducers that are used in positioners are characterized by a relatively short mean time-to-failure. The practical and economical method of a reasonable prolongation of this time is proposed in this paper. It is principally based on assessment and minimizing the effort of the embedded controller. For this purpose, were introduced: the control value variability, mean-time and the cumulative controller's effort. The diminishing of controller effort has significant practical repercussions, because it reduces the intensity of mechanical wear of the final control element components. On the other hand, the reduction of the cumulative effort is important in the context of process economy due to limitation of the consumption of energy of compressed air supplying the final control element. Therefore, the minimization of introduced effort factors has an impact on increasing the functional safety and economics of the controlled process. As a result of the performed simulations, the recommendations regarding the selection of the structure and tuning of positioner controller were elaborated. The simulations were performed in the Matlab-Simulink environment with the use of the liquid level control system in which a phenomenological model of a final control element was deployed. It has been proven that under appropriate conditions, it is possible to extend significantly the lifetime of the final control element and simultaneously enhance the control quality factors.

Wind power is one of the most important sources of renewable energy available today. A large part of the wind energy cost is due to the cost of maintaining wind power equipment. When a wind turbine component fails to function, it might need to be replaced under the less than ideal circumstances. This is known as corrective maintenance. To minimize unnecessary costs, a more active maintenance policy based on the life expectancy of the key components is preferred. Optimal scheduling of preventive maintenance activities requires advanced mathematical modeling. In this paper, an optimal preventive maintenance algorithm is designed using the renewal-reward theorem. In the multi-component setting, our approach involves a new idea of virtual maintenance which allows us to treat each replacement event as a renewal event even if some components are not replaced by new ones. The proposed optimization algorithm is applied to a four-component model of a wind turbine and the optimal maintenance plans are computed for various initial conditions. The modeling results showed clearly the benefit of PM planning compared to pure CM strategy (about 30% lower maintenance cost).

Directed movement towards a target requires spatial working memory, including processing of sensory inputs and motivational drive. In a stimulus-driven, operant conditioning paradigm designed to train zebrafish, we present a pulse of light via LED’s and/or sounds via an underwater transducer. A webcam placed below a glass tank records fish swimming behavior. During operant conditioning, a fish must interrupt an infrared beam at one location to obtain a small food reward at the same or different location. A timing-gated interrupt activates robotic-arm and feeder stepper motors via custom software controlling a microprocessor (Arduino). “Ardulink”, a JAVA facility, implements Arduino-computer communication protocols. In this way, full automation of stimulus-conditioned directional swimming is achieved. Precise multi­day scheduling of training, including timing, location and intensity of stimulus parameters, and feeder control is accomplished via a user-friendly interface. Our training paradigm permits tracking of learning by monitoring, turning, location, response times and directional swimming of individual fish. This facilitates comparison of performance within and across a cohort of animals. We demonstrate the ability to train and test zebrafish using visual and auditory stimuli. Current methods used for associative conditioning often involve human intervention, which is labor intensive, stressful to animals, and introduces noise in the data. Our relatively simple yet flexible paradigm requires a simple apparatus and minimal human intervention. Our scheduling and control software and apparatus (NemoTrainer) can be used to screen neurologic drugs and test the effects of CRISPR­-based and optogenetic modification of neural circuits on sensation, locomotion, learning and memory.

Deep reinforcement learning (DRL) has achieved significant results in many Machine Learning (ML) benchmarks. In this short survey we provide an overview of DRL applied to trading on financial markets, including a short meta-analysis using Google Scholar, with an emphasis on using hierarchy for dividing the problem space as well as using model-based RL to learn a world model of the trading environment which can be used for prediction. In addition, multiple risk measures are defined and discussed, which not only provide a way of quantifying the performance of various algorithms, but they can also act as (dense) reward-shaping mechanisms for the agent. We discuss in detail the various state representations used for financial markets, which we consider critical for the success and efficiency of such DRL agents. The market in focus for this survey is the cryptocurrency market.