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A flexible drilling tool is a special drilling tool for ultrashort-radius radial horizontal wells. This tool is composed of many parts and has the characteristics of a multibody system. In this paper, a numerical method for the dynamic analysis of flexible drilling tools is proposed. The flexible drill tool is discretized into spatial beam elements, while the multilayer contact of the flexible drilling tool is represented by the multilayer dynamic gap element, and the dynamic model of the multibody system for the flexible drilling tool's multilayer contact is established, considering the interaction force between the drill bit and the rock. The nonlinear dynamic equation is solved using the Newmark method and Newton–Raphson method. An analysis of the dynamic behavior of a flexible drilling tool is conducted. The results indicate that the flexible drilling tool experiences vortex formation due to the interaction between the flexible drilling pipe and the guide pipe, leading to increased friction and wear. This situation hinders safe drilling operations with flexible drilling tools. The collision force of the flexible drilling tool near the bottom of the hole is more severe than that of the other tool types, which may lead to failure of the connection. [ABSTRACT FROM AUTHOR]

The enormous amount of data generated by sensors and other data sources in modern grid management systems requires new infrastructures, such as IoT (Internet of Things) and Big Data architectures. This, in combination with Data Mining techniques, allows the management and processing of all these heterogeneous massive data in order to discover new insights that can help to reduce the energy consumption of the building. In this paper, we describe a developed methodology for an Internet of Things (IoT) system based on a robust big data architecture. This innovative approach, combined with the power of Spark algorithms, has been proven to uncover rules representing hidden connections and patterns in the data extracted from a building in Bucharest. These uncovered patterns were essential for improving the building's energy efficiency. [ABSTRACT FROM AUTHOR]

Sponge City Public Private Partnership (PPP) project is a significant step to promote the construction of resilient city and sustainable development. Private companies take advantage of information asymmetry and regulatory loopholes to take opportunistic behavior, which affects the project delivery quality and public interests. In order to reveal the decision-making mechanism of the main stakeholders, this paper constructs an evolutionary game model of private companies, citizens and the government from a fresh perspective of perceived value. First, the traditional payoff matrix is modified by combining Prospect Theory and Mental Accounting. Next, this paper analyzes the strategic evolution law and stability conditions of game players by replicated dynamic equation. Finally, Nanganqu project is used for empirical simulation to verify the effectiveness of this model. Results indicate that, (1) due to the complexity of the project and the bounded rationality of the participants, there is no evolutionary stable strategy in this game system. (2) The behavioral decision of participants is affected by perceived incomes and perceived costs. (3) Government punishment and reputation loss can effectively curb the opportunistic behavior. All above studies are expected to improve the management of Sponge City PPP projects, providing theoretical guidance for the government to make scientific decisions. [ABSTRACT FROM AUTHOR]

The work addresses the topic of the thermal study of high-voltage power cables installed inside plastic pipes in the absence of filling. The presence of air inside the pipe creates an insulating layer that does not favor heat exchange and makes the calculation of the flow rate more complex, as it is necessary to take into account the thermal phenomena of natural convection and radiation between the surface of the cable and the internal surface of the tube. The numerical model based on the finite element calculation was compared with the experimental results obtained on a simulacrum in which the temperatures on the different layers of the cable were measured. After this validation, some typical installation configurations of single and double energy transport triads were analyzed. [ABSTRACT FROM AUTHOR]

The paper presents the case study of the recurrent slope movement in colluvium deposits at Doi Chang, Thailand. A thorough site investigation confirmed the slope movement rate corresponding to slow creep during dry season, while in the rainy season, its velocity remarkably increased. Despite frequent repair, the movement rate was sufficient to result in the recurrent damage of infrastructures like roads and buildings, causing economic loss and public concerns. Furthermore, surface mapping revealed that the hill's topography led to the concentration of flowing water in a particular area. This resulted in a high level of groundwater table, especially during the rainy season. The inclinometer installed in that area suggested an average movement rate of 20.5 mm/month in the wet season. In contrast, during the dry season, it was limited within 2 mm/month, indicating that the increase in the rate of slope movement in the colluvium deposit was primarily due to the rising groundwater table. Field and laboratory tests were conducted to determine the properties of the colluvium deposit. Landslide susceptibility assessment was performed using infinite slope model and later integrated with GIS to evaluate the factor of safety (FS) over a large area. The FS decreased below 1 when the groundwater level rose to 0.3 cm below the ground surface, and using GIS, based on infinite slope model, the potential risk zone were delineated. [ABSTRACT FROM AUTHOR]

This paper presents a new methodology for characterising the evolving behaviour of the time-varying causality between multivariate time series, from the perspective of change in the structure of the causality pattern. We propose that such evolutionary behaviour should be tracked by means of a complex network whose nodes are causality patterns and edges are transitions between those patterns of causality. In our new methodology each edge has a weight that includes the frequency of the given transition and two metrics relating to the gross and net structural change in causality pattern, which we call α and β . To characterise aspects of the behaviour within this network, five approaches are presented and motivated. To act as a demonstration of this methodology an application of sample data from the international oil market is presented. This example illustrates how our new methodology is able to extract information about evolving causality behaviour. For example, it reveals non-random time-varying behaviour that favours transitions resulting in predominantly similar causality patterns, and it discovers clustering of similar causality patterns and some transitional behaviour between these clusters. The example illustrates how our new methodology supports the inference that the evolution of causality in the system is related to the addition or removal of a few causality links, primarily keeping a similar causality pattern, and that the evolution is not related to some other measure such as the overall number of causality links. [ABSTRACT FROM AUTHOR]

Human–robot interaction technology has contributed to improving sociality for humanoid robots. At scales far from human scales, a microrobot can interact with an environment in a small world. Microsensors have been applied to measurement of forces by flying or walking insects. Meanwhile, most previous works focused on the measurement of the behavior of insects. Here, we propose microrobot-insect interactions by soft microfingers integrated with artificial muscle actuators and tactile sensors, which has been developed for a haptic teleoperation robot system. A soft pneumatic balloon actuator acts as the artificial muscle, and a flexible strain sensor using a liquid metal provides tactile sensing. Force interaction between a pill bug and the microfinger could be accomplished. The microfinger (12 mm × 3 mm × 490 μm) can move and touch an insect, and it can detect reaction force from an insect. The measured reaction force from the legs of a pill bug as a representative insect was less than 10 mN. This paper presents a microfinger as an end effector for the active sensing of reaction force from a small insect. We anticipate that our results will lead to further evaluation of small living things as well as technology development for human–environment interaction. [ABSTRACT FROM AUTHOR]

Quantitative information regarding the local behavior of interfaces in an inhomogeneous material during shock loading is limited due to challenges associated with time and spatial resolution. This paper reports the development of a novel method for in-situ measurement of the thermo-mechanical response of polymer bonded sugar composite where measurements are performed during propagagtion of shock wave in sucrose crystal through polydimethylsiloxane binder. The time-resolved measurements were performed with 5 ns resolution providing an estimation on local pressure, temperature, strain rate, and local shock viscosity. The experiments were performed at two different impact velocities to induce shock pressure of 4.26 GPa and 2.22 GPa and strain rate greater than 106/s. The results show the solid to the liquid phase transition of sucrose under shock compression. The results are discussed with the help of fractography analyses of sucrose crystal in order to obtain insights into the underlying heat generation mechanism. [ABSTRACT FROM AUTHOR]

The primary objective of this study is to investigate the microstructural, mechanical, and wear behaviour of AZ31/TiC surface composites fabricated through friction stir processing (FSP). TiC particles are reinforced onto the surface of AZ31 magnesium alloy to enhance its mechanical properties for demanding industrial applications. The FSP technique is employed to achieve a uniform dispersion of TiC particles and grain refinement in the surface composite. Microstructural characterization, mechanical testing (hardness and tensile strength), and wear behaviour evaluation under different operating conditions are performed. Response surface methodology (RSM) is utilized to optimize the wear rate by considering the effects of process parameters. The results reveal a significant improvement in hardness (41.3%) and tensile strength (39.1%) of the FSP-TiC composite compared to the base alloy, attributed to the refined grain structure (6–10 μm) and uniform distribution of TiC particles. The proposed regression model accurately predicts the wear rate, with a confirmation test validating an error percentage within ± 4%. Worn surface analysis elucidates the wear mechanisms, such as shallow grooves, delamination, and oxide layer formation, influenced by the applied load, sliding distance, and sliding velocity. The enhanced mechanical properties and wear resistance are attributed to the synergistic effects of grain refinement, particle-accelerated nucleation, the barrier effect of TiC particles, and improved interfacial bonding achieved through FSP. The optimized FSP-TiC composites exhibit potential for applications in industries demanding high strength, hardness, and wear resistance. [ABSTRACT FROM AUTHOR]

Self-injurious behavior (SIB) is a well-known phenomenon in patients with chronic tic disorders (CTD). To investigate prospectively symptomatology of SIB in adults with CTD, we developed and validated the self-injurious behavior scale for tic disorders (SIBS-T). Patients completed the SIBS-T and a variety of assessments for tics and comorbidities. We investigated SIB frequency, internal consistency of the SIBS-T, and carried out an exploratory factor analysis (EFA). We enrolled n = 123 adult patients with CTD. SIB was reported by n = 103 patients (83.7%). The most frequently reported SIB were beating/pushing/throwing and were found in 79.6% of cases. Patients with SIB had significantly higher tic severity measured with the Adult Tic Questionnaire (ATQ) (p = 0.002) as well as higher severity of psychiatric comorbidities such as obsessive–compulsive symptoms (OCS) (p < 0.001,), attention deficit/hyperactivity disorder (ADHD) (p < 0.001,), and anxiety (p = 0.001). In addition, patients with SIB had significantly lower quality of life (p = 0.002). Pearson correlations demonstrated significant associations between SIB and severity of tics (p < 0.001), depression (p = 0.005), ADHD (p = 0.008), and borderline personality traits (p = 0.014). Consequently, higher SIBS-T also correlated with greater impairment of quality of life (p < 0.001). The internal consistency of the SIBS-T was good (α = 0.88). The EFA confirmed a single factor underlying the SIBS-T. [ABSTRACT FROM AUTHOR]

The composite attachment loss during orthodontic clear aligner therapy is an adverse event that commonly happens in clinical practice and can affect the overall outcome and length of treatment. The aim of our research is to provide a basis for the further study of an innovative digital protocol and application method for orthodontic aligner attachments. Two 3D models were designed, one based on the proposed protocol and the other on the conventional method for aligner attachment application. Four attachment shapes were used to identify the maximum values for the von Mises equivalent stresses, the maximum displacements values and the areas in which these values were recorded through FEM analysis. The results of the mechanical simulation show lower values of von Mises stress recorded in the 3D printed attachments assemblies, independent of their shape, when simulated under the same boundary and load conditions. The trapezoidal prism shaped 3D printed model has a 3.7 times smaller displacement value (0.088 [mm]) compared to the adhesive resin model (0.326 [mm]). In conclusion, the proposed protocol for aligner attachments and the introduction of innovative materials is a promising method of solving conventional attachment problems in current orthodontic treatments. [ABSTRACT FROM AUTHOR]

Traffic cyclic loading is the key factor that leads to the deterioration of the long-term service behavior of subgrade. A series of cyclic triaxial tests was carried out by the large-scale dynamic and static triaxial apparatus (LSDSTA) to study the dynamic behaviors of coal gangue subgrade filler (CGSF) under multi-step cyclic loading using the morphological characteristics of hysteretic curves (MCHC). MCHC was quantitatively characterized by four parameters, i.e., the unclosed degree (εphl), inclination of long axis degree (khl), area (Shl) and fullness degree (αhl). With the increase of dynamic strain, εphl increases exponentially. khl of the coal gangue sample first decreases and then shows an increasing trend with the increasing dynamic strain. The values of Shl are close to each other, and the energy dissipation in the sample is small. However, with the increase of dynamic strain, the specimen failure degree is increased, Shl increases exponentially, and the damping ratio increases. With the increase of dynamic strain, αhl increases approximately linearly. Confining pressure has a certain effect on the four parameters. There parameters can be recommended and used for quantitative analysis the dynamic behaviors of subgrade filler under traffic cyclic loading. [ABSTRACT FROM AUTHOR]

Extracting knowledge from hybrid data, comprising both categorical and numerical data, poses significant challenges due to the inherent difficulty in preserving information and practical meanings during the conversion process. To address this challenge, hybrid data processing methods, combining complementary rough sets, have emerged as a promising approach for handling uncertainty. However, selecting an appropriate model and effectively utilizing it in data mining requires a thorough qualitative and quantitative comparison of existing hybrid data processing models. This research aims to contribute to the analysis of hybrid data processing models based on neighborhood rough sets by investigating the inherent relationships among these models. We propose a generic neighborhood rough set-based hybrid model specifically designed for processing hybrid data, thereby enhancing the efficacy of the data mining process without resorting to discretization and avoiding information loss or practical meaning degradation in datasets. The proposed scheme dynamically adapts the threshold value for the neighborhood approximation space according to the characteristics of the given datasets, ensuring optimal performance without sacrificing accuracy. To evaluate the effectiveness of the proposed scheme, we develop a testbed tailored for Parkinson's patients, a domain where hybrid data processing is particularly relevant. The experimental results demonstrate that the proposed scheme consistently outperforms existing schemes in adaptively handling both numerical and categorical data, achieving an impressive accuracy of 95% on the Parkinson's dataset. Overall, this research contributes to advancing hybrid data processing techniques by providing a robust and adaptive solution that addresses the challenges associated with handling hybrid data, particularly in the context of Parkinson's disease analysis. [ABSTRACT FROM AUTHOR]

The question of how behavior is represented in the mind lies at the core of psychology as the science of mind and behavior. While a long-standing research tradition has established two opposing fundamental views of perceptual representation, Structuralism and Gestalt psychology, we test both accounts with respect to action representation: Are multiple actions (characterizing human behavior in general) represented as the sum of their component actions (Structuralist view) or holistically (Gestalt view)? Using a single-/dual-response switch paradigm, we analyzed switches between dual ([A + B]) and single ([A], [B]) responses across different effector systems and revealed comparable performance in partial repetitions and full switches of behavioral requirements (e.g., in [A + B] → [A] vs. [B] → [A], or [A] → [A + B] vs. [B] → [A + B]), but only when the presence of dimensional overlap between responses allows for Gestalt formation. This evidence for a Gestalt view of behavior in our paradigm challenges some fundamental assumptions in current (tacitly Structuralist) action control theories (in particular the idea that all actions are represented compositionally with reference to their components), provides a novel explanatory angle for understanding complex, highly synchronized human behavior (e.g., dance), and delimitates the degree to which complex behavior can be analyzed in terms of its basic components. [ABSTRACT FROM AUTHOR]

Through extensive multisystem phenotyping, the central aim of Project PICMAN is to correlate metabolic flexibility to measures of cardiometabolic health, including myocardial diastolic dysfunction, coronary and cerebral atherosclerosis, body fat distribution and severity of non-alcoholic fatty liver disease. This cohort will form the basis of larger interventional trials targeting metabolic inflexibility in the prevention of cardiovascular disease. Participants aged 21–72 years with no prior manifest atherosclerotic cardiovascular disease (ASCVD) are being recruited from a preventive cardiology clinic and an existing cohort of non-alcoholic fatty liver disease (NAFLD) in an academic medical centre. A total of 120 patients will be recruited in the pilot phase of this study and followed up for 5 years. Those with 10-year ASCVD risk ≥ 5% as per the QRISK3 calculator are eligible. Those with established diabetes mellitus are excluded. Participants recruited undergo a detailed assessment of health behaviours and physical measurements. Participants also undergo a series of multimodality clinical phenotyping comprising cardiac tests, vascular assessments, metabolic tests, liver and neurovascular testing. Blood samples are also being collected and banked for plasma biomarkers, 'multi-omics analyses' and for generation of induced pluripotent stem cells (iPSC). Extensive evidence points to metabolic dysregulation as an early precursor of cardiovascular disease, particularly in Asia. We hypothesise that quantifiable metabolic inflexibility may be representative of an individual in his/her silent, but high-risk progression towards insulin resistance, diabetes and cardiovascular disease. The platform for interdisciplinary cardiovascular-metabolic-neurovascular diseases (PICMAN) is a pilot, prospective, multi-ethnic cohort study. [ABSTRACT FROM AUTHOR]

Behavioural indices are recognised as important criteria for assessing animal welfare. One of the basic animal behaviours included in ethograms is their activity. The assessment of fast-moving animals, performed by humans using the visual observation method, is difficult and not very objective. Therefore, the aim of the research was to develop a method of automated analysis of animal activity, particularly useful in the observation of quick and lively individuals, and to prove its suitability for assessing the behaviour of fast-moving animals. A method of automatically assessing animal activity was developed using digital image analysis, with the Python programming language and the OpenCV library being the foundational tools. The research model was Callimico goeldii monkeys housed in a zoological garden. This method has been proved to correlate well (Rs = 0.76) with the visual method of animal behaviour analysis. The developed automatic evaluation of animal behaviour is many times faster than visual analysis, and it enables precise assessment of the daily activity of fast-moving groups of animals. The use of this system makes it possible to obtain an activity index with sub-second resolution, which allows it to be used in online mode as a detector of abnormal animal activity, e.g. early detection of illnesses or sudden events that are manifested by increased or decreased activity in relation to the standard activity pattern. [ABSTRACT FROM AUTHOR]

Mosquitoes present a global health challenge due to their ability to transmit human and animal pathogens upon biting and blood feeding. The investigation of tastants detected by mosquitoes and their associated feeding behaviors is needed to answer physiological and ecological questions that could lead to novel control methods. A high-throughput system originally developed for research in fruit flies feeding behavior, the flyPAD, was adapted and tested for behaviors associated with the interaction or consumption of liquid diets offered to females of the mosquito Aedes aegypti Liverpool strain. Females were given water, sucrose solution and sheep blood in choice and non-choice assays. The volume ingested was evaluated with fluorescein. The placement of the system on a heated surface allowed blood consumption, and without females puncturing a membrane. The flyPAD system recorded nine feeding behavioral variables, of which the number of sips and number of activity bouts correlated with meal volume ingested for both sucrose solution and blood. The adaptation to mosquitoes of the flyPAD system differentiated feeding behavior variables between two feeding deterrents, capsaicin, and caffeine. The flyPAD has potential to quickly assess diverse tastants in both sucrose and blood and may contribute to characterizing more precisely their mode of action. [ABSTRACT FROM AUTHOR]

Mindfulness has become increasingly popular and the practice presents in many different forms. Research has been growing extensively with benefits shown across various outcomes. However, there is a lack of consensus over the efficacy of randomized controlled mindfulness interventions, both traditional and mind–body formats. This study aimed to investigate the structural brain changes in mindfulness-based interventions through a meta-analysis. Scopus, PubMed, Web of Science, and PsycINFO were searched up to April 2023. 11 studies (n = 581) assessing whole-brain voxel-based grey matter or cortical thickness changes after a mindfulness RCT were included. Anatomical likelihood estimation was used to carry out voxel-based meta-analysis with leave-one-out sensitivity analysis and behavioural analysis as follow-ups. One significant cluster (p < 0.001, Z = 4.76, cluster size = 632 mm3) emerged in the right insula and precentral gyrus region (MNI = 48, 10, 4) for structural volume increases in intervention group compared to controls. Behavioural analysis revealed that the cluster was associated with mental processes of attention and somesthesis (pain). Mindfulness interventions have the ability to affect neural plasticity in areas associated with better pain modulation and increased sustained attention. This further cements the long-term benefits and neuropsychological basis of mindfulness-based interventions. [ABSTRACT FROM AUTHOR]

The objectives of this study were to evaluate the stress distribution and risk of fracture of a non-vital immature maxillary central incisor subjected to various clinical procedures using finite element analysis (FEA). A three-dimensional model of an immature central incisor was developed, from which six main models were designed: untreated immature tooth (C), standard apical plug (AP), resin composite (RC), glass-fibre post (GFP), regeneration procedure (RET), and regeneration with induced root maturation (RRM). Mineral trioxide aggregate (MTA) or Biodentine® were used as an apical or coronal plug. All models simulated masticatory forces in a quasi–static approach with an oblique force of 240 Newton at a 120° to the longitudinal tooth axis. The maximum principal stress, maximum shear stress, risk of fracture, and the strengthening percentage were evaluated. The mean maximum principal stress values were highest in model C [90.3 MPa (SD = 4.4)] and lowest in the GFP models treated with either MTA and Biodentine®; 64.1 (SD = 1.7) and 64.0 (SD = 1.6) MPa, respectively. Regarding the shear stress values, the dentine tooth structure in model C [14.4 MPa (SD = 0.8)] and GFP models [15.4 MPa (SD = 1.1)] reported significantly higher maximum shear stress values compared to other tested models (p < 0.001), while no significant differences were reported between the other models (p > 0.05). No significant differences between MTA and Biodentine® regarding maximum principal stress and maximum shear stress values for each tested model (p > 0.05). A maximum strain value of 4.07E−03 and maximum displacement magnitude of 0.128 mm was recorded in model C. In terms of strengthening percentage, the GFP models were associated with the highest increase (22%). The use of a GFP improved the biomechanical performance and resulted in a lower risk of fracture of a non-vital immature maxillary central incisor in a FEA model. [ABSTRACT FROM AUTHOR]

This work showed an application of computational tools to understand systematically the behavior of viscosity on CSAM systems relevant to industrial uses. Consequently in this study, the viscosity experimental data obtained from the literature were compared with the thermodynamic calculated results via the software FactSage v.7.3 for melts in CaO–SiO2–Al2O3–MgO slag system with the range of compositions slags cover 0–100 wt% CaO, 0–100 wt% SiO2, 0–100 wt% Al2O3 and 0–15 wt% MgO at temperature ranges of 1500–1700 °C. Using open-source software in Python, the results of viscosity, liquid, and solid fraction of the slag, as a function of composition and temperature, are represented by multiple color maps and by iso-viscosity contours. The results of the viscosity values indicated that the effect of all the oxides in the CSAM slag system follows the well-known behavior trend observed in the literature. Viscosities of the slag were found to increase with increasing SiO2 contents and decrease with increasing basicities (high CaO). The increase in Al2O3 content increases the viscosity values. An increase of 0–15% MgO depolymerized the slag melt and decreases the viscosity. However, above 5% MgO content occur a decrease in the liquid zone (single phase) and a liquid fraction (two-phase region) of the slag. For a constant MgO concentration, the increase in temperature generates an expansion of low-viscosity zones associated with an increase in the liquid phase of the slag. From the comparison between the calculated and experimental viscosities data keeps up within 30% average relative deviation (Δ), the predictions are considered acceptable for viscosity in the CSAM slag system at high temperatures. [ABSTRACT FROM AUTHOR]

Behavioural indices are recognised as important criteria for assessing animal welfare. One of the basic animal behaviours included in ethograms is their activity. The assessment of fast-moving animals, performed by humans using the visual observation method, is difficult and not very objective. Therefore, the aim of the research was to develop a method of automated analysis of animal activity, particularly useful in the observation of quick and lively individuals, and to prove its suitability for assessing the behaviour of fast-moving animals. A method of automatically assessing animal activity was developed using digital image analysis, with the Python programming language and the OpenCV library being the foundational tools. The research model was Callimico goeldii monkeys housed in a zoological garden. This method has been proved to correlate well (Rs = 0.76) with the visual method of animal behaviour analysis. The developed automatic evaluation of animal behaviour is many times faster than visual analysis, and it enables precise assessment of the daily activity of fast-moving groups of animals. The use of this system makes it possible to obtain an activity index with sub-second resolution, which allows it to be used in online mode as a detector of abnormal animal activity, e.g. early detection of illnesses or sudden events that are manifested by increased or decreased activity in relation to the standard activity pattern. [ABSTRACT FROM AUTHOR]

Object recognition tests are widely used in neuroscience to assess memory function in rodents. Despite the experimental simplicity of the task, the interpretation of behavioural features that are counted as object exploration can be complicated. Thus, object exploration is often analysed by manual scoring, which is time-consuming and variable across researchers. Current software using tracking points often lacks precision in capturing complex ethological behaviour. Switching or losing tracking points can bias outcome measures. To overcome these limitations we developed "EXPLORE", a simple, ready-to use and open source pipeline. EXPLORE consists of a convolutional neural network trained in a supervised manner, that extracts features from images and classifies behaviour of rodents near a presented object. EXPLORE achieves human-level accuracy in identifying and scoring exploration behaviour and outperforms commercial software with higher precision, higher versatility and lower time investment, in particular in complex situations. By labeling the respective training data set, users decide by themselves, which types of animal interactions on objects are in- or excluded, ensuring a precise analysis of exploration behaviour. A set of graphical user interfaces (GUIs) provides a beginning-to-end analysis of object recognition tests, accelerating a fast and reproducible data analysis without the need of expertise in programming or deep learning. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the factors that contribute to the propagation of COVID-19 vaccine misinformation on social media in Bangladesh. We attempted to identify the links between the propagation of misinformation and the factors associated with trust in sources based on personal ties among our respondents. In order to find our targeted outcomes, we used a cognitive method in our survey. A total of 202 replies were chosen for analysis, in which respondents were presented with falsified news and asked how they would react to it being shared or posted by someone with whom they have a personal connection. The survey also recorded a variety of other parameters. The Likert Chart Scale was our primary method of data collection, with Yes/No responses serving as a secondary option. The responses were analysed using statistical methods such as Chi-Square Tests, data visualizations and the Ordinal Logistic Regression Model. Our findings have shown that trust in the source can lead to hastily sharing news on social media platforms without proper verification. Other key factors, such as time spent on social media platforms and the type of content shared, also contribute to the propagation of fake news on social media platforms. Such findings may contribute to making Bangladesh more safe and secured in the cyberspace area. [ABSTRACT FROM AUTHOR]

Cynomolgus macaques may undergo surgical procedures for scientific and veterinary purposes. Recognition and assessment of pain using validated tools is a necessary first step for adequately managing pain in these primates. Grimace scales are one means of assessing the occurance of acute pain using action units such as facial expressions and posture. The aim of this study was to create and validate a Cynomolgus Macaque Grimace Scale (CMGS). Cynomolgus macaques (n = 43) were video recorded before and after a surgical procedure. Images were extracted from videos at timepoints at which breakthrough pain might be expected based on analgesic pharmacokinetics. Using the CMGS images were scored by 12 observers blinded to animal identification, times, and conditions. To validate the tool, detailed behavioral analyses emphasizing changes to baseline activity ethograms were compared to grimace scores. Four action units were identified related to potential pain including orbital tightening, brow lowering, cheek tightening, and hunched posture. The CMGS tool was found to have moderate inter- (ICCaverage action unit mean ± SD: 0.67 ± 0.28) and good intra- (ICCsingle mean ± SD: 0.79 ± 0.14) observer reliability. Grimace scores increased significantly (p < 0.0001) in the first four post-operative timepoints compared to baseline, correlating with behavioral findings (rho range = 0.22–0.35, p < 0.001). An analgesic intervention threshold was determined and should be considered when providing additional pain relief. The CMGS was shown to be a reliable and valid tool; however, more research is needed to confirm external validity. This tool will be highly valuable for refining analgesic protocols and acute peri-procedural care for cynomolgus macaques. [ABSTRACT FROM AUTHOR]

Mankind's quest for a manned mission to Mars is placing increased emphasis on the development of innovative radio-protective countermeasures for long-term space travel. Hibernation confers radio-protective effects in hibernating animals, and this has led to the investigation of synthetic torpor to mitigate the deleterious effects of chronic low-dose-rate radiation exposure. Here we describe an induced torpor model we developed using the zebrafish. We explored the effects of radiation exposure on this model with a focus on the liver. Transcriptomic and behavioural analyses were performed. Radiation exposure resulted in transcriptomic perturbations in lipid metabolism and absorption, wound healing, immune response, and fibrogenic pathways. Induced torpor reduced metabolism and increased pro-survival, anti-apoptotic, and DNA repair pathways. Coupled with radiation exposure, induced torpor led to a stress response but also revealed maintenance of DNA repair mechanisms, pro-survival and anti-apoptotic signals. To further characterise our model of induced torpor, the zebrafish model was compared with hepatic transcriptomic data from hibernating grizzly bears (Ursus arctos horribilis) and active controls revealing conserved responses in gene expression associated with anti-apoptotic processes, DNA damage repair, cell survival, proliferation, and antioxidant response. Similarly, the radiation group was compared with space-flown mice revealing shared changes in lipid metabolism. [ABSTRACT FROM AUTHOR]

Based on the idea of discretization and the force balance analysis of each mass spring element, a spring-element analysis method for bolt is proposed. By analyzing the mechanical behavior of the bond interface of the fully grouted bolt, three coupling models of the bond interface, the slider model, the spring model and the spring-slider model, are proposed. Using the spring-element method, five load transfer models, namely the slider model, the spring model, the modified spring model, the spring-pulled slider model, and the spring-slider model, were deduced. And get the bolt displacement distribution function, axial force distribution function and shear stress distribution function under each model. The five proposed models are verified, analyzed and discussed by using the pull-out test of the smooth steel bolt and the threaded steel bolt. It is verified by experiments that this study is helpful to comprehensively understand the mechanical behavior of fully grouted bolts under axial load. The proposed spring element analysis method is simple and easy to understand and the results are reasonable. [ABSTRACT FROM AUTHOR]

An amendment to this paper has been published and can be accessed via a link at the top of the paper. [ABSTRACT FROM AUTHOR]

Attention deficit hyperactivity disorder (ADHD) is a common cognitive disorder affecting children. ADHD can interfere with educational, social, and emotional development, so early detection is essential for obtaining proper care. Standard ADHD diagnostic protocols rely heavily on subjective assessments of perceived behavior. An objective diagnostic measure would be a welcome development and potentially aid in accurately and efficiently diagnosing ADHD. Analysis of pupillary dynamics has been proposed as a promising alternative method of detecting affected individuals effectively. This study proposes a method based on the self-similarity of pupillary dynamics and assesses its strength as a potential diagnostic biomarker. Localized discriminatory features are developed in the wavelet domain and selected via a rolling window method to build classifiers. The application on a task-based pupil diameter time series dataset of children aged 10–12 years shows that the proposed method achieves greater than 78% accuracy in detecting ADHD. Comparing with a recent approach that constructs features in the original data domain, the proposed wavelet-based classifier achieves more accurate ADHD classification with fewer features. The findings suggest that the proposed diagnostic procedure involving interpretable wavelet-based self-similarity features of pupil diameter data can potentially aid in improving the efficacy of ADHD diagnosis. [ABSTRACT FROM AUTHOR]

The study aimed to evaluate trends in the prevalence and correlates of current tobacco use only (= CT), current heavy drinking only (= CHD), and current tobacco use and current heavy drinking (= CTHD) in people 15 years and older from 2009 to 2019 in Mongolia. Cross-sectional data were analyzed from 5,438 individuals (15–64 years) of the Mongolia STEPS 2009 survey, 6,013 (15–69 years) of the Mongolia STEPS 2013 survey, and 6,654 persons (15–69 years) of the Mongolia STEPS 2019 survey and responded to questions about substance use, other health risk behaviours and physical measurements. Trend analysis shows that the prevalence of CT increased from 14.4% in 2009 to 15.3% in 2019, and the prevalence of CHD significantly decreased from 13.3% in 2009 to 10.3% in 2019, and the prevalence of CTHD significantly decreased from 14.2% in 2009 to 9.4% in 2019. Middle and older age, male sex (13 times higher for CT, 3.4 times higher for CHD, and 28 times higher for CTHD) and high physical activity significantly increased the odds of CT, CHD and CTHD. Higher education decreased the odds of CT but increased the odds of CHD. Urban residence was positively associated with CT, and among women with CTHD. Underweight decreased the odds of CT, CHD, and CTHD, and obesity decreased the odds of CT and CTHD and increased the odds of CHD. Hypertension was positively associated with CHD and CTHD, while sedentary behaviour was positively associated with CT and CTHD. Being Khalkh by ethnicity increased the odds of CT and inadequate fruit and vegetable intake increased the odds of CHD. More than one in six persons 15 years and older engaged in CT and more than one in ten engaged in CHD and CTHD. Several sociodemographic factors, such as male sex and middle and/or older age, and health variables, such as obesity and hypertension for CHD, were identified associated with CT, CHD, and CTHD that can help in guiding public interventions. [ABSTRACT FROM AUTHOR]

Latent class analysis (LCA) is a type of modeling analysis approach that has been used to identify unobserved groups or subgroups within multivariate categorical data. LCA has been used for a wide array of psychological evaluations in humans, including the identification of depression subtypes or PTSD comorbidity patterns. However, it has never been used for the assessment of animal behavior. Our objective here is to identify behavioral profile-types of dogs using LCA. The LCA was performed on a C-BARQ behavioral questionnaire dataset from 57,454 participants representing over 350 pure breeds and mixed breed dogs. Two, three, and four class LCA models were developed using C-BARQ trait scores and environmental covariates. In our study, LCA is shown as an effective and flexible tool to classify behavioral assessments. By evaluating the traits that carry the strongest relevance, it was possible to define the basis of these grouping differences. Groupings can be ranked and used as levels for simplified comparisons of complex constructs, such as temperament, that could be further exploited in downstream applications such as genomic association analyses. We propose this approach will facilitate dissection of physiological and environmental factors associated with psychopathology in dogs, humans, and mammals in general. [ABSTRACT FROM AUTHOR]

Agroforestry systems, which are based on the integration of trees and animals, represent a useful practice for implementing the "One Welfare" concept. Geese could adapt well to these systems due to their kinetic and grazing abilities. However, the lack of specific ethograms and animal-based measures have not yet allowed a deep assessment of their welfare and behavior. The aim of this study was to develop and validate a protocol to evaluate the behavior of geese reared in two agroforestry systems (i.e., apple orchard and vineyard). Thus, a behavior observation form (BOF) including a specific ethogram was proposed, and its interobserver reliability, content, criterion and construct validity were determined. Moreover, the influence of the time of day and type of agroforestry system on geese's behavior was also investigated. Agreement and principal component analyses, as well as the comparison between data collected through direct observation by the BOF and indirect observation by a computerized system, supported the reliability and validity of the proposed protocol. While the BOF also highlighted differences in the behavior expressed by the geese according to the time of day and the environmental context, both the vineyard and apple orchard systems seem to meet their biological and behavioral needs. [ABSTRACT FROM AUTHOR]

Short-term behavioral alterations are associated with infection and aid the recovery from sickness. However, concerns have raised that sustained behavioral disturbances after acute neuroinflammation could relate to neurological diseases in the long run. We aimed to explore medium- and long-term behavioral disturbances after acute neuroinflammation in rats, using a model based on the intracerebroventricular administration of the enzyme neuraminidase (NA), which is part of some pathogenic bacteria and viruses. Neurological and behavioral assessments were performed 2 and 10 weeks after the injection of NA, and neuroinflammation was evaluated by gene expression and histology. No alterations were observed regarding basic neurological functions or locomotor capacity in NA-injected rats. However, they showed a reduction in unsupported rearing, and increased grooming and freezing behaviors, which indicate anxiety-like behavior. A principal component analysis including a larger set of parameters further supported such anxiety-like behavior. The anxiety profile was observed 2 weeks after NA-injection, but not after 10 weeks. Concomitantly, the amygdala presented increased number of microglial cells showing a morphologic bias towards an activated state. A similar but subtler tendency was observed in hypothalamic microglia located in the paraventricular nucleus. Also, in the hypothalamus the pattern recognition receptor toll-like receptor 4 (TLR4) was slightly overexpressed 2 weeks after NA injection. These results demonstrate that NA-induced neuroinflammation provokes anxiety-like behavior in the medium term, which disappears with time. Concurrent microgliosis in the amygdala could explain such behavior. Further experiments should aim to explore subtle but long-lasting alterations observed 10 weeks after NA injection, both in amygdala and hypothalamus, as well as mild behavioral changes. [ABSTRACT FROM AUTHOR]

We study the dynamical properties of the one-channel and two-channel spin-1/2 Kondo models after quenching in Hamiltonian variables. Eigen spectrum of the initial and final Hamiltonians is calculated by using the numerical renormalization group method implemented within the matrix product states formalism. We consider multiple quench protocols in the considered Kondo systems, also in the presence of external magnetic field of different intensities. The main emphasis is put on the analysis of the behavior of the Loschmidt echo L(t), which measures the ability of the system's revival to its initial state after a quench. We show that the decay of the Loschmidt echo strongly depends on the type of quench and the ground state of the system. For the one-channel Kondo model, we show that L(t) decays as, L (t) ∼ (t · T K) - 1.4 , where T K is the Kondo temperature, while for the two-channel Kondo model, we demonstrate that the decay is slower and given by L (t) ∼ (t · T K) - 0.7 . In addition, we also determine the dynamical behavior of the impurity's magnetization, which sheds light on identification of the relevant time scales in the system's dynamics. [ABSTRACT FROM AUTHOR]

Human activity recognition (HAR) using machine learning (ML) methods has been a continuously developed method for collecting and analyzing large amounts of human behavioral data using special wearable sensors in the past decade. Our main goal was to find a reliable method that could automatically detect various playful and daily routine activities in children. We defined 40 activities for ML recognition, and we collected activity motion data by means of wearable smartwatches with a special SensKid software. We analyzed the data of 34 children (19 girls, 15 boys; age range: 6.59–8.38; median age = 7.47). All children were typically developing first graders from three elementary schools. The activity recognition was a binary classification task which was evaluated with a Light Gradient Boosted Machine (LGBM) learning algorithm, a decision tree based method with a threefold cross validation. We used the sliding window technique during the signal processing, and we aimed at finding the best window size for the analysis of each behavior element to achieve the most effective settings. Seventeen activities out of 40 were successfully recognized with AUC values above 0.8. The window size had no significant effect. In summary, the LGBM is a very promising solution for HAR. In line with previous findings, our results provide a firm basis for a more precise and effective recognition system that can make human behavioral analysis faster and more objective. [ABSTRACT FROM AUTHOR]

Behavioural studies provide insights into normal and disrupted biological mechanisms. In many research areas, a growing spectrum of animal models—particularly small organisms—is used for high-throughput studies with infrared-based activity monitors, generating counts per time data. The freely available software to analyse such data, however, are primarily optimized for drosophila and circadian analysis. Researchers investigating other species or non-circadian behaviour would thus benefit from a more versatile software. Here we report the development of a free and open-source software—Rtivity—allowing customisation of species-specific parameters, and offering a versatile analysis of behavioural patterns, biological rhythms, stimulus responses, and survival. Rtivity is based on the R language and uses Shiny and the recently developed Rethomics package for a user-friendly graphical interface without requiring coding skills. Rtivity automatically assesses survival, computes various activity, sleep, and rhythmicity parameters, and performs fractal analysis of activity fluctuations. Rtivity generates multiple informative graphs, and exports structured data for efficient interoperability with common statistical software. In summary, Rtivity facilitates and enhances the versatility of the behavioural analysis of diverse animal species (e.g. drosophila, zebrafish, daphnia, ants). It is thus suitable for a broad range of researchers from multidisciplinary fields such as ecology, neurobiology, toxicology, and pharmacology. [ABSTRACT FROM AUTHOR]

There is a lack of clarity on whether pigs can emotionally respond to musical stimulation and whether that response is related to music structure. Qualitative Behavioral Assessment (QBA) was used to evaluate effects of 16 distinct musical pieces (in terms of harmonic structure) on emotional responses in nursery pigs (n = 30) during four periods: "habituation", "treatments", "breaks" and "final". Data were evaluated using Principal component analysis (PCA). Two principal components (PC) were considered in the analysis: PC1, characterized as a positive emotions index, included the emotional responses content, playful, sociable, and happy, whereas PC2, characterized as a negative emotions index, included fearful, inquisitive, and uneasy with positive loadings, and relaxed and calm with negative loadings. Musical stimulation (treatment) increased (P < 0.01) both emotional indices, compared to other periods and this response was influenced by harmonic characteristics of the music. We concluded that pigs have a wide variety of emotional responses, with different affective states related to the music structure used, providing evidence of its potential use as environmental enrichment for this species. [ABSTRACT FROM AUTHOR]

All mammalian mothers form some sort of caring bond with their infants that is crucial to the development of their offspring. The Pup Retrieval Test (PRT) is the leading procedure to assess pup-directed maternal care in laboratory rodents, used in a wide range of basic and preclinical research applications. Most PRT protocols require manual scoring, which is prone to bias and spatial and temporal inaccuracies. This study proposes a novel procedure using machine learning algorithms to enable reliable assessment of PRT performance. Automated tracking of a dam and one pup was established in DeepLabCut and was combined with automated behavioral classification of "maternal approach", "carrying" and "digging" in Simple Behavioral Analysis (SimBA). Our automated procedure estimated retrieval success with an accuracy of 86.7%, whereas accuracies of "approach", "carry" and "digging" were estimated at respectively 99.3%, 98.6% and 85.0%. We provide an open-source, step-by-step protocol for automated PRT assessment, which aims to increase reproducibility and reliability, and can be easily shared and distributed. [ABSTRACT FROM AUTHOR]

Speech detection and discrimination ability are important measures of hearing ability that may inform crucial audiological intervention decisions for individuals with a hearing impairment. However, behavioral assessment of speech discrimination can be difficult and inaccurate in infants, prompting the need for an objective measure of speech detection and discrimination ability. In this study, the authors used functional near-infrared spectroscopy (fNIRS) as the objective measure. Twenty-three infants, 2 to 10 months of age participated, all of whom had passed newborn hearing screening or diagnostic audiology testing. They were presented with speech tokens at a comfortable listening level in a natural sleep state using a habituation/dishabituation paradigm. The authors hypothesized that fNIRS responses to speech token detection as well as speech token contrast discrimination could be measured in individual infants. The authors found significant fNIRS responses to speech detection in 87% of tested infants (false positive rate 0%), as well as to speech discrimination in 35% of tested infants (false positive rate 9%). The results show initial promise for the use of fNIRS as an objective clinical tool for measuring infant speech detection and discrimination ability; the authors highlight the further optimizations of test procedures and analysis techniques that would be required to improve accuracy and reliability to levels needed for clinical decision-making. [ABSTRACT FROM AUTHOR]

Society suffers from biases and discrimination, a longstanding dilemma that stems from ungrounded, subjective judgments. Especially unequal opportunities in labor remain a persistent challenge, despite the recent inauguration of top-down diplomatic measures. Here we propose a solution by using an objective approach to the measurement of nonverbal behaviors of job candidates that trained for a job assessment. First, we implemented and developed artificial intelligence, computer vision, and unbiased machine learning software to automatically detect facial muscle activity and emotional expressions to predict the candidates' self-reported motivation levels. The motivation judgments by our model outperformed recruiters' unreliable, invalid, and sometimes biased judgments. These findings mark the necessity and usefulness of novel, bias-free, and scientific approaches to candidate and employee screening and selection procedures in recruitment and human resources. [ABSTRACT FROM AUTHOR]

Misokinesia––or the 'hatred of movements'––is a psychological phenomenon that is defined by a strong negative affective or emotional response to the sight of someone else's small and repetitive movements, such as seeing someone fidget with a hand or foot. Among those who regularly experience misokinesia sensitivity, there is a growing grass-roots recognition of the challenges that it presents as evidenced by on-line support groups. Yet surprisingly, scientific research on the topic is lacking. This article is novel in systematically examining whether misokinesia sensitivity actually exists in the general population, and if so, whether there is individual variability in the intensity or extent of what sensitivities are reported. Across three studies that included 4100 participants, we confirmed the existence of misokinesia sensitivity in both student and non-student populations, with approximately one-third of our participants self-reporting some degree of sensitivity to seeing the repetitive, fidgeting behaviors of others as encountered in their daily lives. Moreover, individual variability in the range and intensity of sensitivities reported suggest that the negative social-affective impacts associated with misokinesia sensitivities may grow with age. Our findings thus confirm that a large segment of the general population may have a visual-social sensitivity that has received little formal recognition. [ABSTRACT FROM AUTHOR]

In everyday life, people sometimes find themselves making decisions on behalf of others, taking risks on another's behalf, accepting the responsibility for these choices and possibly suffering regret for what they could have done differently. Previous research has extensively studied how people deal with risk when making decisions for others or when being observed by others. Here, we asked whether making decisions for present others is affected by regret avoidance. We studied value-based decision making under uncertainty, manipulating both whether decisions benefited the participant or a partner (beneficiary effect) and whether the partner watched the participant's choices (audience effect) and their factual and counterfactual outcomes. Computational behavioural analysis revealed that participants were less mindful of regret (and more strongly driven by bigger risks) when choosing for others vs for themselves. Conversely, they chose more conservatively (regarding both regret and risk) when being watched vs alone. The effects of beneficiary and audience on anticipated regret counteracted each other, suggesting that participants' financial and reputational interests impacted the feeling of regret independently. [ABSTRACT FROM AUTHOR]

How strategies are formulated during a performance is an important aspect of motor control. Knowledge of the strategy employed in a task may help subjects achieve better performances, as it would help to evidence other possible strategies that could be used as well as help perfect a certain strategy. We sought to investigate how much of a performance is conditioned by the initial state and whether behavior throughout the performance is modified within a short timescale. In other words, we focus on the process of execution and not on the outcome. To this scope we used a repeated continuous circle tracing task. Performances were decomposed into different components (i.e., execution variables) whose combination is able to numerically determine movement outcome. By identifying execution variables of speed and duration, we created an execution space and a solution manifold (i.e., combinations of execution variables yielding zero discrepancy from the desired outcome) and divided the subjects according to their initial performance in that space into speed preference, duration preference, and no-preference groups. We demonstrated that specific strategies may be identified in a continuous task, and strategies remain relatively stable throughout the performance. Moreover, as performances remained stable, the initial location in the execution space can be used to determine the subject's strategy. Finally, contrary to other studies, we demonstrated that, in a continuous task, performances were associated with reduced exploration of the execution space. [ABSTRACT FROM AUTHOR]

The intergenerational sustainability dilemma (ISD) is a situation of whether or not a person sacrifices herself for future sustainability. To examine the individual behaviors, one-person ISD game (ISDG) is instituted with strategy method where a queue of individuals is organized as a generational sequence. In ISDG, each individual chooses unsustainable (or sustainable) option with her payoff of X ( X - D ) and an irreversible cost of D (zero cost) to future generations in 36 situations. Future ahead and back (FAB) mechanism is suggested as resolution for ISD by taking the perspective of future generation whereby each individual is first asked to take the next generation's standpoint and request what she wants the current generation to choose, and, second, to make the actual decision from the original position. Results show that individuals choose unsustainable option as previous generations do so or X D is low (i.e., sustainability is endangered). However, FAB prevents individuals from choosing unsustainable option in such endangered situations. Overall, the results suggest that some new institutions, such as FAB mechanisms, which induce people to take the perspective of future generations, may be necessary to avoid intergenerational unsustainability, especially when intergenerational sustainability is highly endangered. [ABSTRACT FROM AUTHOR]

We investigated the cognitive and behavioral profile of three distinct groups of epilepsies with a genetic background for intergroup differences: (1) idiopathic/genetic generalized epilepsies (IGE/GGE group); (2) idiopathic focal epilepsies (IFE group); and (3) epilepsies with proven or strongly suggested monogenic or structural/numeric chromosomal etiology (genetic epilepsies, GE group). Cognitive (total IQ and subcategories) and behavioral parameters (CBCL) were assessed at the tertiary epilepsy center of the University of Munich (Germany). We used ANOVA with post-hoc Bonferroni-correction to explore significant mean differences and Fisher's exact test for significant proportional differences of intelligence impairment and behavioral problems. 126 (56 IGE/GGE, 26 IFE, 44 GE) patients were available. Total IQ was 89.0 ± 15.9 (95% CI 84.5–93.4) for IGE/GGE, 94.8 ± 18.1 (95% CI 87.3–102.3) for IFE and 76.4 ± 22.4 (95% CI 67.6–85.3) for GE (p = 0.001). The same trend was significant for all but one IQ subcategory. The rate of patients with an intelligence impairment (total IQ < 70) was higher for GE (40%) than for IGE/GGE (14%) and for IFE (7%) patients (p = 0.033). There were no significant differences between groups for behavior scores and behavioral problems. This study shows that the current ILAE classification of epilepsies with genetic etiology creates a heterogeneous group of patients with respect to cognitive performance but not behavior. These findings may help in further delineating epilepsies as regards cognitive performance, notwithstanding their closely related etiological classification. [ABSTRACT FROM AUTHOR]

Despite its prolific growth, neurolinguistic research on phonemic sequencing has largely neglected the study of individuals with highly developed skills in this domain. To bridge this gap, we report multidimensional signatures of two experts in backward speech, that is, the capacity to produce utterances by reversing the order of phonemes while retaining their identity. Our approach included behavioral assessments of backward and forward speech alongside neuroimaging measures of voxel-based morphometry, diffusion tensor imaging, and resting-state functional connectivity. Relative to controls, both backward speakers exhibited behavioral advantages for reversing words and sentences of varying complexity, irrespective of working memory skills. These patterns were accompanied by increased grey matter volume, higher mean diffusivity, and enhanced functional connectivity along dorsal and ventral stream regions mediating phonological and other linguistic operations, with complementary support of areas subserving associative-visual and domain-general processes. Still, the specific loci of these neural patterns differed between both subjects, suggesting individual variability in the correlates of expert backward speech. Taken together, our results offer new vistas on the domain of phonemic sequencing, while illuminating neuroplastic patterns underlying extraordinary language abilities. [ABSTRACT FROM AUTHOR]

Shared attention experiments examine the potential differences in function or behavior when stimuli are experienced alone or in the presence of others, and when simultaneous attention of the participants to the same stimulus or set is involved. Previous work has found enhanced reactions to emotional stimuli in social situations, yet these changes might represent enhanced communicative or motivational purposes. This study examines whether viewing emotional stimuli in the presence of another person influences attention to or memory for the stimulus. Participants passively viewed emotionally-valenced stimuli while completing another task (counting flowers). Each participant performed this task both alone and in a shared attention condition (simultaneously with another person in the same room) while EEG signals were measured. Recognition of the emotional pictures was later measured. A significant shared attention behavioral effect was found in the attention task but not in the recognition task. Compared to event-related potential responses for neutral pictures, we found higher P3b response for task relevant stimuli (flowers), and higher Late Positive Potential (LPP) responses for emotional stimuli. However, no main effect was found for shared attention between presence conditions. To conclude, shared attention may therefore have a more limited effect on cognitive processes than previously suggested. [ABSTRACT FROM AUTHOR]

We examined whether the co-occurrence of four behavioural risk factors (alcohol consumption, smoking, physical inactivity and obesity) is associated with disability-free and chronic disease-free life expectancy similarly in two longitudinal studies of ageing in England and the United States. Data were from 17,351 individuals aged 50+ from the US Health and Retirement Study (HRS) and, 10,388 from the English Longitudinal Study of Ageing (ELSA), from 2002 to 2013. Disability-free life expectancy was estimated using repeat measures of limitations with instrumental activities and activities of daily living and, chronic disease-free life expectancy was based on chronic health conditions. Multistate life table models were used to estimate sex-specific health expectancy at the ages of 50, 60 and 70. In both countries and at all ages, there was a clear gradient towards shorter health expectancy with increasing number of behavioural risk factors. Compared to people with 2+ behavioural risk factors, in both countries, those with no behavioural risk factors could expect to live up to 11 years longer without disability and, up to 12 years longer without chronic conditions. Individual and co-occurring behavioural risk factors were strongly associated with shorter healthy life expectancy in both countries, attesting to the robustness of the contribution of lifestyle factors on health expectancy. [ABSTRACT FROM AUTHOR]

Quantification and parametrisation of movement are widely used in animal behavioural paradigms. In particular, free movement in controlled conditions (e.g., open field paradigm) is used as a "proxy for indices of baseline and drug-induced behavioural changes. However, the analysis of this is often time- and labour-intensive and existing algorithms do not always classify the behaviour correctly. Here, we propose a new approach to quantify behaviour in an unconstrained environment: searching for frequent patterns (k-motifs) in the time series representing the position of the subject over time. Validation of this method was performed using subchronic quinpirole-induced changes in open field experiment behaviours in rodents. Analysis of this data was performed using k-motifs as features to better classify subjects into experimental groups on the basis of behaviour in the open field. Our classifier using k-motifs gives as high as 94% accuracy in classifying repetitive behaviour versus controls which is a substantial improvement compared to currently available methods including using standard feature definitions (depending on the choice of feature set and classification strategy, accuracy up to 88%). Furthermore, visualisation of the movement/time patterns is highly predictive of these behaviours. By using machine learning, this can be applied to behavioural analysis across experimental paradigms. [ABSTRACT FROM AUTHOR]

How the evolution of complex behavioral traits is associated with the emergence of novel brain pathways is largely unknown. Songbirds, like humans, learn vocalizations via tutor imitation and possess a specialized brain circuitry to support this behavior. In a comprehensive in situ hybridization effort, we show that the zebra finch vocal robust nucleus of the arcopallium (RA) shares numerous markers (e.g. SNCA, PVALB) with the adjacent dorsal intermediate arcopallium (AId), an avian analog of mammalian deep cortical layers with involvement in motor function. We also identify markers truly unique to RA and thus likely linked to modulation of vocal motor function (e.g. KCNC1, GABRE), including a subset of the known shared markers between RA and human laryngeal motor cortex (e.g. SLIT1, RTN4R, LINGO1, PLXNC1). The data provide novel insights into molecular features unique to vocal learning circuits, and lend support for the motor theory for vocal learning origin. [ABSTRACT FROM AUTHOR]

We introduce an ensemble learning scheme for community detection in complex networks. The scheme uses a Machine Learning algorithmic paradigm we call Extremal Ensemble Learning. It uses iterative extremal updating of an ensemble of network partitions, which can be found by a conventional base algorithm, to find a node partition that maximizes modularity. At each iteration, core groups of nodes that are in the same community in every ensemble partition are identified and used to form a reduced network. Partitions of the reduced network are then found and used to update the ensemble. The smaller size of the reduced network makes the scheme efficient. We use the scheme to analyze the community structure in a set of commonly studied benchmark networks and find that it outperforms all other known methods for finding the partition with maximum modularity. [ABSTRACT FROM AUTHOR]