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The research aimed to assess how feeding conditions and the number of the dominant follicles (DF) influence oestrus synchronization in swamp buffaloes. A total of 170 swamp female buffaloes raised in semi-grazing and housekeeping were included in the study. The synchronization used CIDR method and the follicles on the day of CIDR (Controlled Internal Drug Releasing) insert and removal were tracked by sonography. The results indicated that the age of first mating, age at first calving, and caving interval showed no significant differences in the two feeding conditions. The number of follicles at CIDR insertion and removal decreased in semi-grazing, but increased in housekeeping buffaloes. The percentage of buffalo without DF, one DF, and two DFs at CIDR withdrawal did not differ statistically. The percentage of estrus was 100% in both groups. Pregnancy rates were 53.18% in semi- grazing and 52.63% in housekeeping. The onset of oestrus was similar, but the duration of oestrus was longer in the buffaloes without DF than those with one or two DFs. The percentage of pregnant buffaloes in the group without DF was significantly lower than that in the other two groups. In summary, the efficiency of oestrus synchronization did not differ between semi-grazing and housekeeping methods. Buffaloes without DF displayed longer oestrus periods and lower pregnancy rates compared to those with one or two DFs in the ovarian system.

Abstract Zinc metal anodes (ZMA) have high theoretical capacities (820 mAh g−1 and 5855 mAh cm−3) and redox potential (−0.76 V vs. standard hydrogen electrode), similar to the electrochemical voltage window of the hydrogen evolution reaction (HER) in a mild acidic electrolyte system, facilitating aqueous zinc batteries competitive in next‐generation energy storage devices. However, the HER and byproduct formation effectuated by water‐splitting deteriorate the electrochemical performance of ZMA, limiting their application. In this study, a key factor in promoting the HER in carbon‐based electrode materials (CEMs), which can provide a larger active surface area and guide uniform zinc metal deposition, was investigated using a series of three‐dimensional structured templating carbon electrodes (3D‐TCEs) with different local graphitic orderings, pore structures, and surface properties. The ultramicropores of CEMs are the determining critical factors in initiating HER and clogging active surfaces by Zn(OH)2 byproduct formation, through a systematic comparative study based on the 3D‐TCE series samples. When the 3D‐TCEs had a proper graphitic structure with few ultramicropores, they showed highly stable cycling performances over 2000 cycles with average Coulombic efficiencies of ≥99%. These results suggest that a well‐designed CEM can lead to high‐performance ZMA in aqueous zinc batteries.

Abstract Bifunctional hybrid anodes (BHAs), which are both a high‐performance active host material for lithium‐ion storage as well as a guiding agent for homogeneous lithium metal nucleation and growth, exhibit significant potential as anodes for next‐generation high‐energy‐density lithium‐ion batteries (LIBs). In this study, sulfur‐doped hard carbon nanosphere assemblies (S‐HCNAs) were prepared through a hydrothermal treatment of a liquid organic precursor, followed by high‐temperature thermal annealing with elemental sulfur for application as BHAs for LIBs. In a carbonate‐based electrolyte containing fluoroethylene carbonate additive, the S‐HCNAs showed high lithium‐ion storage capacities in sloping as well as plateau voltage sections, good rate capabilities, and stable cyclabilities. In addition, high average Coulombic efficiencies (CEs) of ~96.9% were achieved for dual lithium‐ion and lithium metal storage cycles. In the LIB full‐cell tests with typical NCM811 cathodes, the S‐HCNA‐based BHAs containing ~400 mA h g−1 of excess lithium led to high energy and power densities of ~500 W h kg−1 and ~1695 W kg−1, respectively, and a stable cycling performance with ~100% CEs was achieved.

Abstract Studies on three‐dimensional structured carbon templates have focused on how to guide homogeneous lithium metal nucleation and growth for lithium metal anodes (LMAs). However, there is still insufficient evidence for a key factor to achieve their high electrochemical performance. Here, the effects of nanopores and sulfur doping on carbon‐based nanoporous host (CNH) electrode materials for LMAs were investigated using natural polymer‐derived CNHs. Homogeneous pore‐filling behaviors of lithium metal in the nanopores of the CNH electrode materials were first observed by ex situ scanning electron microscopy analysis, where the protective lithium metal nucleation and growth process led to significantly high Coulombic efficiency (CE) of ~99.4% and stable 600 cycles. In addition, a comparison study of CNH and sulfur‐doped CNH (S‐CNH) electrodes, which differ only in the presence or absence of sulfur, revealed that sulfur doping can cause lower electrochemical series resistance, higher CE value, and better cycling stability in a wide range of current densities and number of cycles. Moreover, S‐CNH‐based LMAs showed high electrochemical performance in full‐cell Li–S battery tests using a sulfur copolymer cathode, where a high energy density of 1370 W h kgelectrode−1 and an excellent power density of 4120 W kgelectrode−1 were obtained.

Abstract Despite the development of multidimensional state‐of‐the‐art electrode materials for constructing better lithium metal anodes (LMAs), the key factors influencing the electrochemical performance of LMAs are still poorly understood. Herein, it is demonstrated that the local lithium ion concentration at the interface between the electrode and electrolyte exerts significant influence on the electrochemical performance of LMAs. The local ion concentration is multiplied by introducing pseudocapacitive nanocarbons (PNCs) containing numerous heteroatoms, because PNCs can store large numbers of lithium ions in a pseudocapacitive manner, and promote the formation of an electrochemical double layer. The high interfacial lithium ion concentration induces the formation of lithium‐rich inorganic solid–electrolyte–interface layers with high ionic conductivities, and facilitates sustainable and stable supplies of lithium ion charge carriers on the overall active surfaces of the PNCs. Accordingly, the PNC‐induced LMA exhibits high Coulombic efficiencies, high rate capabilities, and stable cycling performance.

In this work, we fabricated crumpled graphite oxides (CGOs) from discharged electrodes of waste batteries by the cathodic plasma electrolysis process and applied it for arsenic (As) removal from water solutions. Several factors that affect the removal efficiency of As(III) were investigated, including pH, initial concentrations, and contact time. After 120 min of experiment [10 mg of CGO in 40 ml of 1 mg/l As(III) solution], the removal efficiency reached to as high as 98.6%. From the Langmuir isotherm model, the calculated maximum adsorption capacity (qmax) was found to be 47.39 mg/g. The results from this study showed that CGOs could be an effective adsorbent for As(III) removal from the water environment and acts as a promising adsorbent for other heavy metals from contaminated water.

INTRODUCTION: Diagnosis of Attention Deficit/Hyperactivity Disorder (ADHD) is based on clinical evaluation of symptoms by a psychiatrist, referencing results of psychological tests. When diagnosing ADHD, the childs behavior and functionality in real-life situations are critical components. However, direct observation by a clinician is often not feasible in practice. Therefore, such information is typically gathered from primary caregivers or teachers, which can introduce subjective elements. To overcome these limitations, we developed AttnKare-D, an innovative digital diagnostic tool that could analyze childrens behavioral data in Virtual Reality using Artificial Intelligence. The purpose of this study was to explore the utility and safety of AttnKare-D for clinical application. METHOD: A total of 21 children aged between 6 and 12 years were recruited for this study. Among them, 15 were children diagnosed with ADHD, 5 were part of a normal control group, and 1 child was excluded due to withdrawal of consent. Psychological assessments, including K-WISC, Conners CPT, K-ARS, and K-CBCL, were conducted for participants and their primary caregivers. Diagnoses of ADHD were confirmed by child and adolescent psychiatrists based on comprehensive face-to-face evaluations and results of psychological assessments. Participants underwent VR diagnostic assessment by performing various cognitive and behavioral tasks in a VR environment. Collected data were analyzed using an AI model to assess ADHD diagnosis and the severity of symptoms. RESULTS: AttnKare-D demonstrated diagnostic performance with an AUC of 0.893 when compared to diagnoses made by child and adolescent psychiatrist, showing a sensitivity of 0.8 and a specificity of 1.0 at a cut-off score of 18.44. AttnKare-D scores showed a high correlation with K-ARS scores rated by parents and experts, although the correlation was relatively low for inattention scores. CONCLUSION: Results of this study suggest that AttnKare-D can be a useful tool for diagnosing ADHD in children. This approach has potential to overcome limitations of current diagnostic methods, enhancing the accuracy and objectivity of ADHD diagnoses. This study lays the groundwork for further improvement and research on diagnostic tools integrating VR and AI technologies. For future clinical applications, it is necessary to conduct clinical trials involving a sufficient number of participants to ensure reliable use.

IntroductionAttention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder where hyperactivity often manifests as fidgeting, a non-goal-directed motoric action. Many studies demonstrate fidgeting varies under different conditions as a self-regulating mechanism for attention and alertness during cognitively demanding tasks. Fidgeting has also been associated with reaction time variability. However, a lack of standard variables to define and quantify fidgeting can lead to discrepancies in data and interpretability issues across studies. Furthermore, little is known about fidgeting in adults with ADHD compared to youth. This study aims to design a framework to quantify meaningful fidgeting variables and to apply them to test the relation between fidgeting and performance on a cognitive task, the Flanker, in adults with ADHD.MethodOur study included 70 adult participants diagnosed with ADHD, aged 18-50 years (30.5 ± 7.2 years). Screening included a structured clinical interview, childhood, current self and current observer ratings of ADHD symptoms. Actigraphy devices were attached to the left wrist and right ankle during completion of a cognitive control, attention task (the Flanker). Laboratory testing was subsequently completed on a single day. The relation between task performance, reaction time variability and fidgeting was examined.Results and discussionOur analysis revealed increased fidgeting during correct trials as defined by our new variables, consistent with previous observations. Furthermore, differences in fidgeting were observed between early and later trials while the percentage of correct trials were not significantly different. This suggests a relation between the role of fidgeting and sustaining attention. Participants with low reaction time variability, that is, those with more consistent reaction times, fidgeted more during later trials. This observation supports the theory that fidgeting aids arousal and improves sustained attention. Finally, a correlation analysis using ADHD-symptom rating scales validated the relevance of the fidget variables in relation to ADHD symptom severity. These findings suggest fidgeting may be a compensatory mechanism that aids in sustained attention for those with ADHD, although alternative explanations exist.ConclusionOur study suggests that fidgeting may aid in sustained attention during the attention-demanding, cognitive control processes for adults with ADHD, with more fidgeting observed during correct trials and among participants with lower reaction time variability. Furthermore, the newly defined fidget variables were validated through a significant correlation with ADHD rating scales. By sharing our implementation of fidget variables, we hope to standardize and encourage further quantitative research into the role of fidgeting in ADHD.

In this study, we introduce a framework designed to help educators assess the effectiveness of popular generative artificial intelligence (AI) tools in solving authentic assessments. We employed Bloom's taxonomy as a guiding principle to create authentic assessments that evaluate the capabilities of generative AI tools. We applied this framework to assess the abilities of ChatGPT-4, ChatGPT-3.5, Google Bard and Microsoft Bing in solving authentic assessments in economics. We found that generative AI tools perform very well at the lower levels of Bloom's taxonomy while still maintaining a decent level of performance at the higher levels, with "create" being the weakest level of performance. Interestingly, these tools are better able to address numeric-based questions than text-based ones. Moreover, all the generative AI tools exhibit weaknesses in building arguments based on theoretical frameworks, maintaining the coherence of different arguments and providing appropriate references. Our study provides educators with a framework to assess the capabilities of generative AI tools, enabling them to make more informed decisions regarding assessments and learning activities. Our findings demand a strategic reimagining of educational goals and assessments, emphasising higher cognitive skills and calling for a concerted effort to enhance the capabilities of educators in preparing students for a rapidly transforming professional environment.

This research explored the potential of artificial intelligence (AI)-assisted learning using ChatGPT in an engineering course at a university in South-east Asia. The study investigated the benefits and challenges that students may encounter when utilising ChatGPT-3.5 as a learning tool. This research developed an AI-assisted learning flow that empowers learners and lecturers to integrate ChatGPT into their teaching and learning processes. The flow was subsequently used to validate and assess a variety of exercises, tutorial tasks and assessment-like questions for the course under study. Introducing a self-rating system allowed the study to facilitate users in assessing the generative responses. The findings indicate that ChatGPT has significant potential to assist students; however, there is a necessity for training and offering guidance to students on effective interactions with ChatGPT. The study contributes to the evidence of the potential of AI-assisted learning and identifies areas for future research in refining the use of AI tools to better support students' educational journey.

Objectives: This study aimed to identify the prevalence, risk factors, and impact of long COVID in a community-based representative sample of patients with COVID-19 aged 19–64 years. Methods: A total of 975 participants completed online or telephone surveys at 1 and 3 months post-diagnosis, covering persistent symptoms, daily activity limitations, vaccination status, and underlying diseases. Results: Long COVID, as defined by the WHO criteria, had a prevalence of 19.7–24.9% in females and 12.7% in males. Logistic regression revealed that the odds of having long COVID symptoms were higher among females compared to males (OR, 2.43; 95% CI, 1.53–3.87), and higher in those aged ≥ 30 years compared to those aged 19–29 years: 30–39 years (OR, 2.91; 95% CI, 1.59–5.33), 40–49 years (OR, 2.72; 95% CI, 1.51–4.89), and 50–64 years (OR, 1.96; 95% CI, 1.10–3.49). Additionally, patients with underlying diseases had higher odds of long COVID symptoms compared to those without underlying diseases (OR, 1.81; 95% CI, 1.24–2.64). Among those with long COVID, 54.2% experienced daily activity limitations, and 40.6% received treatment. Furthermore, lower income groups faced greater daily activity limitations but had similar treatment rates to higher income groups. Conclusions: These findings emphasize the need for interest in and the development of programs to support these low-income populations. [ABSTRACT FROM AUTHOR]

Symptoms of inattention (IA), hyperactivity, and impulsivity present in school‐aged children are important indications of developmental problems. The assessment of these symptoms largely relies on questionnaires completed by parents, teachers, and the children themselves. However, inherent perceptual biases may lead to inaccuracies in these evaluations. This study investigates the biases among different respondents for 41 elementary‐aged students (19 male and 22 female) by analyzing their responses on the attention‐deficit/hyperactivity disorder‐rating scale (ADHD‐RS) through a novel virtual reality‐based objective measure (AttnKare‐D). Correlation analysis reveals higher agreement between parents and students compared to other informant pairs. Nevertheless, when compared with the objective measure, parents and students do not exhibit distinct separation between high and low‐scoring samples, whereas teachers demonstrate significant separation on various objective measure factors. This discrepancy suggests that teachers may possess a more accurate baseline for peer‐related measurements, leading to a more objective evaluation of ADHD symptoms. However, it is essential to acknowledge that teachers are not entirely exempt from biases. Gender‐specific comparisons reveal notable differences, with male children showing the largest separation in distractibility and female children in movement. In conclusion, this study emphasizes the significance of recognizing and addressing potential biases when interpreting questionnaires assessing symptoms of IA, hyperactivity, and impulsivity in children. Practitioner points: Recognize bias in assessing ADHD symptoms in children through parent, teacher, and self‐reports.Teachers provide more objective evaluation of ADHD symptoms when compared with objective measure.Distractibility is the primary factor for males, and movement is the main factor for females in ADHD assessment by teachers. [ABSTRACT FROM AUTHOR]