bluuebunny/crossref_metadata_2025 huggingface dataset:
Developing emotional intelligence in a static and interactive music learning environment
Authors: Liang Jitao
Published: February 2024

The concept of a static electronic learning environment implies the utilization of tools that do not necessitate any active participation on the part of the learner aside from familiarizing oneself with the provided materials. In contrast, an interactive electronic learning environment necessitates active engagement and interaction from the learner. The research purpose is to compare the impact of interactive and static learning environments on students’ emotional intelligence. Music education students (n = 216) took a theoretical course on emotional intelligence during one academic semester at the university. The students were randomly divided into two equal groups: Group A (n = 108) attended the course in a lecture format, using videos and additional reading materials. Group B participated in online forums, completed interactive exercises, and discussed individual personal diaries kept at home with the teacher. At the end of the semester, both groups completed the Mayer-Salovey-Caruso emotional intelligence test. The results suggest that the total score for emotional intelligence was higher in Group B. After another 6 months of training, students passed the same test again to assess the effectiveness of the long-term intervention strategy. The post-training results suggest that Group B has an advantage in training over Group A. At the same time, in the Managing Emotions subcategory, Group B was behind Group A, but after 6 months of training, Group B significantly improved the results (value of p = 0.01). The research summarizes the practical significance of the theoretical course on the development of emotional intelligence among music education students.
Adverse childhood experiences are associated with perceived cognitive difficulties among high school students in the United States
Authors: Iverson Ila A. , Cook Nathan E. , Iverson Grant L.
Published: February 2024

Objective

Adverse childhood experiences (ACEs) are associated with mental health and cognitive problems, and mental health problems are associated with perceived cognitive difficulties among adolescents. The unique contribution of ACEs to cognitive difficulties after adjusting for poor mental health is not well understood and represents the purpose of this study.

Methods

The Adolescent Behaviors and Experiences Survey was conducted in 2021 with high school students in the United States. Cognitive difficulty was assessed with: ‘Because of a physical, mental, or emotional problem, do you have serious difficulty concentrating, remembering, or making decisions?’ Four ACEs were examined: sexual violence (lifetime and past 12 months), parental emotional abuse, and parental physical abuse. Students were asked about feeling sad or hopeless (past year), considering suicide (past year), and having poor mental health (past month). Binary logistic regressions examined the association between ACEs and cognitive problems, adjusting for mental health.

Results

Participants were 6,945 students. Students reporting poor mental health were very likely to endorse difficulty concentrating, remembering, or making decisions (girls = 81% and boys = 67%). Cognitive difficulty was uncommon among students who denied poor mental health (girls = 17% and boys = 12%). For boys [p < 0.001; R2 = 0.22] and girls [p < 0.001; R2 = 0.31], after adjusting for mental health problems, independent predictors of cognitive difficulties included parental verbal abuse and physical abuse. For girls, lifetime forced sexual intercourse and sexual violence during the past year were also independently associated.

Conclusion

ACEs are associated with perceived cognitive difficulty in both adolescent girls and boys, even after adjusting for poor mental health.
Mandatory substance use treatment for justice-involved persons in Germany: a systematic review of reoffending, treatment and the recurrence of substance use outcomes
Authors: Tomlin Jack , Meise Esther , Wegner Juliane , Völlm Birgit
Published: February 2024

Many jurisdictions implement mandatory substance use treatment for justice-involved persons. Germany is one such country; however, debates about the appropriateness and effectiveness of this disposal abound. Very little attention has been paid in the international literature to patients receiving mandatory treatment in Germany. This systematic review synthesises research on patients receiving substance use treatment in forensic hospitals under §64 of the German Penal Code with regard to three primary outcomes: treatment completion, reoffending, and the recurrence of substance use. Forty-five publications reporting on 36 studies were reviewed; publication dates ranged from 1988 to 2023. On average, 47% of patients did not successfully complete treatment, compared to 45% who did. Average follow-up reconviction rates were higher than in mentally ill and general offender populations as reported elsewhere. Approximately half of all patients reused substances during treatment. Suggestions for future research, including a focus on strength- and recovery-based indicators, and harmonising routine outcomes measurements, are given.
Self-processing characteristics from first-person and third-person perspectives in individuals with social anxiety disorder: insights into negative bias
Authors: Wu Huating , Yue Caizhen , Cao Fasheng , Long Yihong , Wang Yan
Published: February 2024

Background

As one of the most common psychological problems, social anxiety disorder (SAD) has lots of negative effects on the physical and mental development of individuals, such as decreasing the quality of interpersonal relationships, and even causing depression, suicidal ideation, etc., as well as leads individuals to generate mental illness stigma. The mental illness stigma that individuals perceive affects not only how they perceive themselves (first-person perspective) but also how they perceive others’ appraisals of them (third-person perspective), which further exacerbates their anxiety symptoms.

Objective

The study aims to explore the self-processing characteristics of individuals with social anxiety disorder from the first-person perspective and the third-person perspective.

Methods

This study adopted the self-referential paradigm to conduct the recognition memory test on individuals with social anxiety disorder (30 participants in experiment 1) and individuals without social anxiety disorder (31 participants in experiment 2) in the two experiments.

Results

In experiment 1, the recognition rate of individuals with social anxiety disorder under the self-appraisals condition was significantly higher than that under the condition of appraisals on mothers; in the three conditions of self-appraisals, appraisals on mothers and mothers’ reflected appraisals, the recognition rate of negative trait adjectives was significantly higher than that of positive trait adjectives. In experiment 2, there was no significant difference in recognition rate of individuals without social anxiety disorder under the three conditions, and the recognition rate of positive trait adjectives was significantly higher than that of negative trait adjectives under the three conditions.

Conclusion

Individuals with social anxiety disorder have a negative bias in self-processing and are more likely to focus on self-information, which is different from the self-positive bias of individuals without social anxiety disorder. This study can be beneficial to know the self-cognitive characteristics of individuals with social anxiety disorder, help them get rid of negative cognitive patterns, and remove the mental illness stigma.
Digital interventions targeting excessive substance use and substance use disorders: a comprehensive and systematic scoping review and bibliometric analysis
Authors: Johansson Magnus , Romero Danilo , Jakobson Miriam , Heinemans Nelleke , Lindner Philip
Published: February 2024

Addictive substances are prevalent world-wide, and their use presents a substantial and persistent public health problem. A wide range of digital interventions to decrease use and negative consequences thereof have been explored, differing in approach, theoretical grounding, use of specific technologies, and more. The current study was designed to comprehensively map the recent (2015-2022) extant literature in a systematic manner, and to identify neglected and emerging knowledge gaps. Four major databases (Medline, Web of Science Core Collection, and PsychInfo) were searched using database-specific search strategies, combining terms related to clinical presentation (alcohol, tobacco or other drug use), technology and aim. After deduplication, the remaining n=13,917 unique studies published were manually screened in two stages, leaving a final n=3,056 studies, the abstracts of which were subjected to a tailored coding scheme. Findings revealed an accelerating rate of publications in this field, with randomized trials being the most common study type. Several meta-analyses on the topic have now been published, revealing promising and robust effects. Digital interventions are being offered on numerous levels, from targeted prevention to specialized clinics. Detailed coding was at times made difficult by inconsistent use of specific terms, which has important implications for future meta-analyses. Moreover, we identify several gaps in the extant literature – few health economic assessments, unclear descriptions of interventions, weak meta-analytic support for some type of interventions, and limited research on many target groups, settings and new interventions like video calls, chatbots and artificial intelligence – that we argue are important to address in future research.
Diagnosing and tracking depression based on eye movement in response to virtual reality
Authors: Zheng Zhiguo , Liang Lijuan , Luo Xiong , Chen Jie , Lin Meirong , Wang Guanjun , Xue Chenyang
Published: February 2024

Introduction

Depression is a prevalent mental illness that is primarily diagnosed using psychological and behavioral assessments. However, these assessments lack objective and quantitative indices, making rapid and objective detection challenging. In this study, we propose a novel method for depression detection based on eye movement data captured in response to virtual reality (VR).

Methods

Eye movement data was collected and used to establish high-performance classification and prediction models. Four machine learning algorithms, namely eXtreme Gradient Boosting (XGBoost), multilayer perceptron (MLP), Support Vector Machine (SVM), and Random Forest, were employed. The models were evaluated using five-fold cross-validation, and performance metrics including accuracy, precision, recall, area under the curve (AUC), and F1-score were assessed. The predicted error for the Patient Health Questionnaire-9 (PHQ-9) score was also determined.

Results

The XGBoost model achieved a mean accuracy of 76%, precision of 94%, recall of 73%, and AUC of 82%, with an F1-score of 78%. The MLP model achieved a classification accuracy of 86%, precision of 96%, recall of 91%, and AUC of 86%, with an F1-score of 92%. The predicted error for the PHQ-9 score ranged from -0.6 to 0.6.To investigate the role of computerized cognitive behavioral therapy (CCBT) in treating depression, participants were divided into intervention and control groups. The intervention group received CCBT, while the control group received no treatment. After five CCBT sessions, significant changes were observed in the eye movement indices of fixation and saccade, as well as in the PHQ-9 scores. These two indices played significant roles in the predictive model, indicating their potential as biomarkers for detecting depression symptoms.

Discussion

The results suggest that eye movement indices obtained using a VR eye tracker can serve as useful biomarkers for detecting depression symptoms. Specifically, the fixation and saccade indices showed promise in predicting depression. Furthermore, CCBT demonstrated effectiveness in treating depression, as evidenced by the observed changes in eye movement indices and PHQ-9 scores. In conclusion, this study presents a novel approach for depression detection using eye movement data captured in VR. The findings highlight the potential of eye movement indices as biomarkers and underscore the effectiveness of CCBT in treating depression.
Psychiatry, racism and crime: the case of Christopher Clunis reconsidered
Authors: Cummins Ian
Published: February 2024

In December 2022, the death of Christopher Clunis was made public. He had actually died in February 2021. Christopher Clunis was convicted of the manslaughter of a stranger, Jonathan Zito. He attacked Mr Zito at a train station. This paper will argue that this terrible event became a totemic symbol of the wider failings of the policy of community care. The image of Clunis being driven away from Court was repeatedly used in newspaper and other media reports as a reference point. The image reflects a number of long-standing traits in the representation of the “mentally ill.” These are combined with a racial stereotype of Black men. The paper examines historical representations of the mentally ill as a context for a discussion of the Clunis case. The paper uses the work of Stuart Hall as an analytical tool to examine the questions of race and representation, and the moral panic following failings of community care.
Parenting stress in parents with and without a mental illness and its relationship to psychopathology in children: a multimodal examination
Authors: Seipp Vanessa , Hagelweide Klara , Stark Rudolf , Weigelt Sarah , Christiansen Hanna , Kieser Meinhard , Otto Kathleen , Reck Corinna , Steinmayr Ricarda , Wirthwein Linda , Zietlow Anna–Lena , Schwenck Christina ,   the COMPARE-Family Research Group
Published: February 2024

Objective

Children of parents with a mental illness are at heightened risk to develop a mental illness themselves due to genetics and environmental factors. Although parenting stress (PS) is known to be associated with increased psychopathology in parents and children, there is no study investigating PS multimodally in a sample of parents with a mental illness. This study aims to compare PS of parents with and without a mental illness and further to examine the relationship between PS and psychopathology of children.

Methods

Participants were parents with a mental illness and parents without a mental illness and their children aged four to sixteen years. We assessed PS multimodally using a questionnaire, parents’ evaluation of children’s behavior (relational schemas) and psychophysiological arousal of parents during free speech task.

Results

Self-reported PS was increased, and evaluation of children’s behavior was more negative and less positive in parents with a mental illness compared to parents without a mental illness. Children’s psychopathology was associated with self-reported PS and relational schemas of parents. Regarding psychophysiological arousal, parents with a mental illness showed reduced reactivity in heart rate from baseline to free speech task in comparison to parents without a mental illness.

Conclusions

Our findings highlight the importance of implementing intervention programs to reduce PS for parents and children. In particular, parents with a mental illness might benefit from specific intervention programs in order to interrupt the transgenerational transmission of mental disorders.
Knowledge, attitude and practice towards tuberculosis among healthcare and non-healthcare students at a public university in Saudi Arabia
Authors: Kandasamy Geetha , Almaghaslah Dalia , Almanasef Mona
Published: February 2024

Background

Tuberculosis (TB) is a bacterial infection. It mostly affects the lungs (pulmonary TB), but it can also affect other organs. This cross-sectional study evaluated knowledge, attitudes, and practices (KAP) related to TB among King Khalid University (KKU) students between October and November 2023.

Objective

The objective of this study was to investigate current TB knowledge, attitudes, and practices of students at King Khalid University in Abha, Saudi Arabia.

Methods

A self-administered, cross-sectional, descriptive, web-based questionnaire was conducted from October to December 2023 among the students of King Khalid University. We used a 29-item questionnaire with five sections. Section 1 contained five questions about sociodemographic factors, there were 13 knowledge questions in Section 2, Section 3 contained 7 attitude questions, Section 4 contained 3 practice questions, and Section 5 contained 1 source of information question. A chi-squared test was used to assess differences in participants’ knowledge, attitude, and practices in relation to their demographic variables (p < 0.05).

Results

A total of 518 students completed the questionnaire. 53.66% were healthcare students and 46.33% non-healthcare students. The mean scores for healthcare and non-healthcare students, respectively, were as follows: knowledge 11.80 ± 4.81, 7.35 ± 4.96; attitude 6.94 ± 1.33, 5.05 ± 2.09; and practice 2.26 ± 0.85, 1.14 ± 0.87. The results of this study showed good knowledge (24.82 and 5.83% for healthcare and non-healthcare students, respectively) good attitude (67.62 and 46.25%) and good practice (45.32 and 9.58%). A total of 24.32% healthcare students and 28.18% non-healthcare students reported that most effective sources for obtaining information about TB were social networks, the internet and the radio.

Conclusion

The current study concludes that the knowledge, attitude, and practice about TB among healthcare faculty students is better than their non-healthcare counterparts. However, there are still areas of poor knowledge, attitude and practice toward some aspects of TB among the two categories, which shows the necessity of educational intervention that aims at improving student understanding about the disease and its impact on public health.
Evaluating the impact of a darts game intervention on cognitive function in older adults with and without mild cognitive impairment: a pilot study
Authors: Kawabata Nami , Iida Tadayuki , Kunishige Masafumi , Fukuda Hiroshi , Miyaguchi Hideki , Harada Toshihide
Published: February 2024

Introduction

The current study investigated the relationship between the characteristics of a darts game, including the throwing motion toward a target, and mild cognitive impairment (MCI). To this end, we examined the associations between cognitive function and mental health, and the shift in center of gravity while throwing darts. In a preliminary investigation, a 1-month dart game intervention was conducted among older individuals living in the community. The participants were divided into the non-MCI and MCI groups, and the relationship between center of gravity movement during throwing and the presence of dementia was examined.

Methods

The intervention lasted for 1 month and was tested on healthy older individuals (aged ≥ 65 years) recruited from the community. The Japanese version of the Montreal Cognitive Assessment and the Trail Making Test was used to assess cognitive function. Mental health was evaluated using the Kessler Psychological Distress Scale and the Subjective Well-being Inventory. The center of pressure was analyzed to determine the center of gravity shift during dart throwing.

Results

The analysis of factors influencing the determination of the MCI score during the intervention revealed a tendency for the center of gravity shift to be associated as a protective factor in the non-MCI group, although this association did not reach statistical significance (odds ratio = 0.942, p = 0.084). In the MCI group, a significant effect of age was observed in the MCI score (odds ratio = 1.539, p = 0.007).

Conclusion

The current findings suggest that conducting center of gravity shift testing could potentially provide a helpful tool for predicting early decline in cognitive function.
Geothermal Heat Shapes the Antarctic Ice Sheet From Below
Authors: Stål Tobias , McCormack Felicity S. , Reading Anya M. , Askey-Doran Niam , Halpin Jacqueline A. , Lösing Mareen
Published: February 2024

Antarctica’s ice sheet is constantly on the move, flowing from the deep, frozen interior of the continent toward the ocean, where it melts. In fact, because the oceans are getting warmer, the Antarctic ice sheet melts faster, and therefore, the sea level is rising. However, predicting how the ice sheet will flow differently from place to place is complicated. The landscape beneath the ice sheet helps to control how fast the ice moves. For example, the ice can stick and deform, or slide smoothly across the land under the ice. Naturally occurring heat from inside the Earth can cause the base of the ice sheet to melt and soften so that it flows more easily, sliding on the meltwater formed. The amount of this geothermal heat varies across Antarctica and is difficult to measure. However, scientists with various expertise can collaborate to understand how much heat there is and how it shapes the ice sheet.
Virtual Reality Video Game Improves Memory in Older Adults
Authors: Arioli Melissa , Anguera-Singla Roger , Wais Peter E.
Published: February 2024

The ability to remember detailed information is called high-fidelity long-term memory. We use high-fidelity long-term memory to remember the details of our favorite stories and how to track which family member a green pair of socks belongs to. As we age, the ability to remember these details declines as the health of the brain changes. We created a virtual reality video game called Labyrinth-VR, with the aim to restore memory. When playing Labyrinth-VR, participants practice figuring out where they want to go using the shortest route to get there. In Labyrinth-VR, participants learned a virtual neighborhood and then had to find their way around to run errands. In our study, 49 older adults played either 12 h of Labyrinth-VR or 12 h of iPad games. The results of tests of high-fidelity long-term memory showed that playing Labyrinth-VR, but not iPad games, led to improvements in participants’ scores.
Design and Analysis of an MRI-Compatible Soft Needle Manipulator
Authors: Chen Jie , Zhang Jingyu , Jiang Tianyu , Dang Yu , Han Jianda
Published: February 2024

Needle manipulation with the guidance of magnetic resonance imaging (MRI) plays a key role in minimally invasive procedures such as biopsy and ablation. However, the confined bore and strong magnetic field of the MR environment pose great challenges in developing a robotic system that fulfills the needle manipulation function. This paper presents the design and analysis of a soft needle manipulator (SoNIM) that can achieve needle manipulation in the MR environment. This pneumatically actuated manipulator consists of two bending actuators and one elongation actuator that are completely made of non-magnetic materials. These soft pneumatic actuators can generate flexible movements while maintaining a compact design, ensuring that the SoNIM is accommodated within the MRI bore. The kinematic modeling and closed-loop control of the SoNIM are investigated to achieve the position control of the needle tip. Experiments showed that the SoNIM was capable of directing the needle tip to reach the targets with a satisfactory accuracy of 2.9 ± 0.98 mm. Furthermore, the functionality and MRI compatibility of the SoNIM were validated in the clinical setting, demonstrating the capability of the SoNIM to perform needle manipulation in the MRI bore with negligible degradation to the image quality. With excellent MRI compatibility, compact design, and flexible movements, the SoNIM provides a promising solution for manipulating surgical needles in MRI-guided minimally invasive surgeries.
Optimization Design Method for Non-Rectangular Constant Stress Accelerated Testing Considering Parameter Estimation Precision
Authors: Qian Ping , Feng Zheng , Chen Wenhua , Zhang Guotai , Zhang Jian
Published: February 2024

In addressing the design challenges for constant-stress accelerated life testing in non-rectangular experimental domains, we aim to optimize the precision in estimating parameters for the product reliability statistical model. Following the principles of regression orthogonal design theory to determine the combinations of stress levels, we constrain the maximum stress levels of each experimental stress along the boundary curve of the non-rectangular experimental domain. The remaining stress levels and the allocation ratios of specimens for each test serve as design variables in the optimization process. We establish a mathematical model for the optimal design of constant-stress accelerated life testing in non-rectangular experimental domains. The results of the optimized design for comprehensive stress accelerated life testing in non-rectangular experimental regions of aerospace electrical connectors indicate that, with the same sample size, the optimized testing scheme not only enhances the precision of model parameter estimation but also reduces the number of required tests. At an equivalent number of tests and testing duration, the optimization scheme proposed in this study demonstrates an improvement of over 63% in the precision of model parameter estimation compared to the EM-optimized testing scheme in non-rectangular experimental regions. Using the mean, standard deviation, and coefficient of variation of the determinant values of the information matrix as criteria for evaluating the precision and robustness of experimental designs, a simulated evaluation was conducted for the optimized experimental design, a conventional experimental design, and an EM experimental design. The results indicate that the optimal experimental design outperforms both the conventional experimental design and the EM experimental design in terms of precision and robustness.
The Communicative Behavior of Russian Cosmonauts: “Content” Space Experiment Result Generalization
Authors: Shved Dmitry , Supolkina Natalia , Yusupova Anna
Published: February 2024

The increasing complexity of the space flight program and the increase in the duration of missions require an improvement in psychological monitoring tools for astronauts in orbit. This article summarizes the experience of using quantitative content analysis of communication between the crews and the Mission Control Center (MCC). This method allows us to assess the dynamics of an astronaut’s psycho-emotional state, identify their communicative style, and detect the communication phenomena of board-MCC communication. The method is based on a combination of the coping strategies approach by Lazarus and Folkman as well as B.F. Lomov’s concept about the three functions of communication. We found the influence of workload on the structure and volume of communication, defined the main stable communication styles of crewmembers, and confirmed the presence of the emotional transfer phenomenon. We detected that astronauts successfully solve problems that arise in orbit using the capabilities of their communication style. An ineffective MCC communication style usually leads to psycho-emotional ill-being, manifesting in the emotional transfer phenomenon. The presence of the “third-quarter” phenomenon was not confirmed by materials from six-month space flights.
Effect of Long-Term Different Land Uses on Improving Stable Humic Compounds in Arenosol
Authors: Amaleviciute-Volunge Kristina , Tripolskaja Liudmila , Kazlauskaite-Jadzevice Asta , Slepetiene Alvyra , Baksiene Eugenija
Published: February 2024

There has not been enough research conducted on the effect of land use on the composition of humus in Arenosols. This long-term study (1995–2022) aimed to determine the differences in the formation of humic compounds in the natural and agricultural ecosystems of Arenosols. Soil samples were collected from six plots at two soil depths (0–15 and 15–25 cm), with four replicates. Conclusions were reached based on the results of the accumulation of humic substances (HSs) and their qualitative fractional composition, C/N ratio, humification degree (HD), and the optical properties of the humus substances. Afforestation, after 27 years, significantly increased (+6.7 g kg−1) the soil organic carbon (SOC) and influenced the qualitative composition of HS: HA + FA 79.3% of the SOC. Grassland cultivation showed faster (+3.8 g kg−1) SOC sequestration, a higher HA/FA ratio, and an increased HD. Arenosols may be used in crop rotation with approximately 40% leguminous plants to maintain a stable humus balance. Additionally, the effects of mineral fertilisers on the humification processes and humus quality of +2.59 g kg−1 SOC, +1.27 g kg−1 humin in crop rotation, +3.26 g kg−1 SOC, and 2.82 g kg−1 humin in a grass cultivation field were established. For SOC accumulation and a larger humus amount of a better quality, it is recommended that an Arenosol is used, as it is suitable for use in perennial cut grasslands, natural grasslands, and pine afforestation.
Renal Endocytic Regulation of Vitamin D Metabolism during Maturation and Aging in Laying Hens
Authors: Kuwata Nami , Mukohda Hatsune , Uchida Hiroto , Takamatsu Ryo , Binici Muhammet Mustafa , Yamada Takahisa , Sugiyama Toshie
Published: February 2024

Egg-laying hens undergo a specific and dramatic calcium metabolism to lay eggs with eggshells composed of calcium carbonate. Calcium metabolism is mainly regulated by vitamin D3. Although vitamin D3 metabolism is closely related to the deterioration of eggshell quality associated with aging and heat stress, the details of the mechanisms regulating vitamin D3 metabolism are not clear. In mammals, the vitamin D3 metabolite (25(OH)D3) produced in the liver binds to the vitamin binding protein (DBP), is subsequently taken up by renal proximal tubular cells via the endocytic receptors megalin (Meg) and cubilin (CUB), and is metabolized to 1,25-dihydroxyvitamin D3 (1,25(OH)2D3). Therefore, the present study aimed to examine the expression and localization of Meg and CUB in the kidneys of immature chicks and mature and aged laying hens to prevent eggshell quality deterioration. As a result, we showed that as circulating 1,25(OH)2D3 concentrations increased from 156.0 ± 13.5 pg/mL to 815.5 ± 61.4 pg/mL with maturation in immature chicks, relative expression levels (arbitrary units; AU) of Meg and CUB mRNA in the kidneys of mature hens significantly increased 1.92- and 2.75-fold, respectively, compared to those in immature chicks. On the other hand, the Meg mRNA expression levels of mature hens did not change with age, while CUB mRNA expression levels (1.03 ± 0.11 AU) were significantly decreased compared to mature hens (2.75 ± 0.24 AU). Immunohistochemical observations showed that Meg and CUB proteins were localized to the apical membrane of renal proximal tubular epithelial cells in immature chicks, mature hens, and aged hens, and that DBP protein was observed as granular endosomes in the cytoplasm of proximal tubular cells from the apical membrane to the cell nucleus. Especially in mature hens, the endosomes were larger and more numerous than those in immature chicks. In contrast, in aged hens, DBP-containing endosomes were smaller and limited to the apical cytoplasm. These results indicate that with maturation, the expression of Meg and CUB is promoted in the renal proximal tubules of laying hens, facilitating the uptake of the 25(OH)D3-DBP complex and its conversion to 1,25(OH)2D3, and regulating calcium metabolism in eggshell formation. On the other hand, it is suggested that the age-related decrease in CUB expression suppresses the uptake of the 25(OH)D3-DBP complex in the kidney, resulting in a deterioration of eggshell quality.
A Novel Antibiotic, Rhodomyrtone: Pharmacokinetic Studies in a Murine Model and Optimization and Validation of High-Performance Liquid Chromatographic Method for Plasma Analysis
Authors: Suwandecha Tan , Yingyongnarongkul Boon-Ek , Towtawin Kanokkan , Voravuthikunchai Supayang Piyawan , Sriwiriyajan Somchai
Published: February 2024

Rhodomyrtone has indisputable and undeniable potential as a new antibiotic for antibiotic-resistant Gram-positive bacteria. Therefore, the main objective of this study was to determine the pharmacokinetics profiles of orally administered rhodomyrtone in rats. A reverse-phase HPLC-UV method was developed, optimized and validated for the analysis of rhodomyrtone concentrations in rat plasma. The retention time of papaverine and rhodomyrtone was 3.928 and 5.937 min, with no interference with the excipients used. The lower limit of quantification (LLOQ) of rhodomyrtone in the plasma sample was 0.04 μg/mL, the accuracy of rhodomyrtone at the LLOQ level ranged from 93.64 to 106.36%, precision was 6.59%, 80–120% for accuracy and <20% CV for precision. The calibration curve was linear at concentrations ranging from 0.04 to 128 µg/mL with a correlation coefficient (r) value of equal to or greater than 0.999. Sprague Dawley rats received a single dose of rhodomyrtone at 50 and 100 mg/kg. Blood samples were collected from tail veins. The peak plasma concentration was observed at 2 h, and the area under the curve of rhodomyrtone at 50 mg/kg and 100 mg/kg was 3.41 ± 1.04 and 7.82 ± 1.53 μg·h/mL, respectively. The results demonstrated linear pharmacokinetics characteristics at the studied dosage range. The plasma concentration of rhodomyrtone was above the minimal inhibition concentrations of several common pathogenic bacteria of medical importance. The proposed HPLC-UV method is fast, cost-effective, reliable and reproducible, and it is proposed for the routine analysis of rhodomyrtone.
Oxidative Damage and Antioxidants as Markers for the Selection of Emersion Hardening Treatments in GreenshellTM Mussel Juveniles (Perna canaliculus)
Authors: Delorme Natalí J. , Burritt David J. , Zamora Leonardo N. , Welford Mena R. V. , South Paul M.
Published: February 2024

Transport out of the water is one of the most challenging events for juvenile Perna canaliculus and can be a highly inefficient process, with many juveniles subsequently being lost following extended periods of emersion. Hardening techniques offer a possible method for reducing transport-related stress. In this study, different hardening treatments (short, long and intermittent sub-lethal emersion) were used to prepare ~1.2 mm P.canaliculus for transport (20 h) and subsequent reoxygenation stress during re-immersion (i.e., recovery). The oxidative stress responses, resettlement behaviour, respiration rates and survival of the mussels after transport and during recovery were all assessed. Short emersion (1 h) as a hardening treatment prior to transport did not cause major stress to the mussels, which maintained respiration at control levels, showed significantly stimulated antioxidant defences during recovery, showed greater resettlement behaviour and remained viable after 24 h of recovery. In comparison, the long and intermittent emersion treatments negatively impacted oxidative stress responses and affected the viability of the mussels after 24 h of recovery. This study showed that exposing juvenile P.canaliculus to a mild stress prior to transport may stimulate protective mechanisms, therefore eliciting a hardening response, but care must be taken to avoid overstressing the mussels. Improving the management of stress during the transport of juvenile mussels may be key to minimising mussel losses and increasing harvest production, and biomarkers associated with oxidative stress/antioxidant metabolism could be valuable tools to ensure emersion hardening does not overstress the mussels and reduce survival.
Redox Biomarkers and Matrix Remodeling Molecules in Ovarian Cancer
Authors: Supruniuk Elżbieta , Baczewska Marta , Żebrowska Ewa , Maciejczyk Mateusz , Lauko Kamil Klaudiusz , Dajnowicz-Brzezik Patrycja , Milewska Patrycja , Knapp Paweł , Zalewska Anna , Chabowski Adrian
Published: February 2024

Ovarian cancer (OC) has emerged as the leading cause of death due to gynecological malignancies among women. Oxidative stress and metalloproteinases (MMPs) have been shown to influence signaling pathways and afflict the progression of carcinogenesis. Therefore, the assessment of matrix-remodeling and oxidative stress intensity can determine the degree of cellular injury and often the severity of redox-mediated chemoresistance. The study group comprised 27 patients with serous OC of which 18% were classified as Federation of Gynecology and Obstetrics (FIGO) stages I/II, while the rest were diagnosed grades III/IV. The control group comprised of 15 ovarian tissue samples. The results were compared with genetic data from The Cancer Genome Atlas. Nitro-oxidative stress, inflammation and apoptosis biomarkers were measured colorimetrically/fluorometrically or via real-time PCR in the primary ovarian tumor and healthy tissue. Stratification of patients according to FIGO stages revealed that high-grade carcinoma exhibited substantial alterations in redox balance, including the accumulation of protein glycoxidation and lipid peroxidation products. TCGA data demonstrated only limited prognostic usefulness of the studied genes. In conclusion, high-grade serous OC is associated with enhanced tissue oxidative/nitrosative stress and macromolecule damage that could not be overridden by the simultaneously augmented measures of antioxidant defense. Therefore, it can be assumed that tumor cells acquire adaptive mechanisms that enable them to withstand the potential toxic effects of elevated reactive oxygen species.
Parameter and Topology Optimization of Structures in the Frequency Domain under Nevanlinna–Pick Interpolation Constraints
Authors: Kara Aliyye , Eksin Ibrahim , Mugan Ata
Published: February 2024

The design optimization of structures can be conducted in either the time domain or the frequency domain. The frequency domain approach is advantageous compared to its time domain counterpart, especially if the degree of freedom is large, the objectives and/or constraints are formulated in the frequency domain, or the structure is subject to random loading. In this paper, an attempt is undertaken to obtain feasible optimal solutions by implementing the Nevanlinna–Pick (NP) interpolation theory across multi-objective structural optimization problems in the frequency domain. The NP equations introduce a trade-off that originates from the interpolation theory for complex variables. According to the NP theory, a complex function cannot have an independent amplitude from its derivative at a certain frequency. Consequently, the frequency response of a physical system cannot be shaped arbitrarily at discrete frequencies. Our objectives within this paper include calculating the weight, natural frequency, fatigue life, frequency domain response, and its derivative. To illustrate our claims, sample parameter and topology optimization problems were formulated and solved, both with and without the NP constraints. It was found that the inclusion of NP constraints induced a considerable improvement in the optimal solutions, while also causing the convergence to the optimal solution to become smoother.
A Machine Learning Approach to Simulation of Mallard Movements
Authors: Einarson Daniel , Frisk Fredrik , Klonowska Kamilla , Sennersten Charlotte
Published: February 2024

Machine learning (ML) is increasingly used in diverse fields, including animal behavior research. However, its application to ambiguous data requires careful consideration to avoid uncritical interpretations. This paper extends prior research on ringed mallards where sensors revealed their movements in southern Sweden, particularly in areas with small lakes. The primary focus is to distinguish the movement patterns of wild and farmed mallards. While well-known statistical methods can capture such differences, ML also provides opportunities to simulate behaviors outside of the core study span. Building on this, this study applies ML techniques to simulate these movements, using the previously collected data. It is crucial to note that unrefined application of ML can lead to incomplete or misleading outcomes. Challenges in the data include disparities in swimming and flying records, farmed mallards’ biased data due to feeding points, and extended intervals between data points. This research highlights these data challenges, while identifying discernible patterns, as well as proposing approaches to meet such challenges. The key contribution lies in separating incompatible data and, through different ML models, handle these separately to enhance the reliability of the simulation models. This approach ensures a more credible and nuanced understanding of mallard movements, demonstrating the importance of critical analysis in ML applications in wildlife studies.
Predicting Team Well-Being through Face Video Analysis with AI
Authors: Müller Moritz , Dupuis Ambre , Zeulner Tobias , Vazquez Ignacio , Hagerer Johann , Gloor Peter A.
Published: February 2024

Well-being is one of the pillars of positive psychology, which is known to have positive effects not only on the personal and professional lives of individuals but also on teams and organizations. Understanding and promoting individual well-being is essential for staff health and long-term success, but current tools for assessing subjective well-being rely on time-consuming surveys and questionnaires, which limit the possibility of providing the real-time feedback needed to raise awareness and change individual behavior. This paper proposes a framework for understanding the process of non-verbal communication in teamwork, using video data to identify significant predictors of individual well-being in teamwork. It relies on video acquisition technologies and state-of-the-art artificial intelligence tools to extract individual, relative, and environmental characteristics from panoramic video. Statistical analysis is applied to each time series, leading to the generation of a dataset of 125 features, which are then linked to PERMA (Positive Emotion, Engagement, Relationships, Meaning, and Accomplishments) surveys developed in the context of positive psychology. Each pillar of the PERMA model is evaluated as a regression or classification problem using machine learning algorithms. Our approach was applied to a case study, where 80 students collaborated in 20 teams for a week on a team task in a face-to-face setting. This enabled us to formulate several hypotheses identifying factors influencing individual well-being in teamwork. These promising results point to interesting avenues for research, for instance fusing different media for the analysis of individual well-being in teamwork.
Towards Client Selection in Satellite Federated Learning
Authors: Wu Changhao , He Siyang , Yin Zengshan , Guo Chongbin
Published: February 2024

Large-scale low Earth orbit (LEO) remote satellite constellations have become a brand new, massive source of space data. Federated learning (FL) is considered a promising distributed machine learning technology that can communicate optimally using these data. However, when applying FL in satellite networks, it is necessary to consider the unique challenges brought by satellite networks, which include satellite communication, computational ability, and the interaction relationship between clients and servers. This study focuses on the siting of parameter servers (PSs), whether terrestrial or extraterrestrial, and explores the challenges of implementing a satellite federated learning (SFL) algorithm equipped with client selection (CS). We proposed an index called “client affinity” to measure the contribution of the client to the global model, and a CS algorithm was designed in this way. A series of experiments have indicated the advantage of our SFL paradigm—that satellites function as the PS—and the availability of our CS algorithm. Our method can halve the convergence time of both FedSat and FedSpace, and improve the precision of the models by up to 80%.
A Population-Based Search Approach to Solve Continuous Distributed Constraint Optimization Problems
Authors: Liao Xin , Hoang Khoi D.
Published: February 2024

Distributed Constraint Optimization Problems (DCOPs) are an efficient framework widely used in multi-agent collaborative modeling. The traditional DCOP framework assumes that variables are discrete and constraint utilities are represented in tabular forms. However, the variables are continuous and constraint utilities are in functional forms in many practical applications. To overcome this limitation, researchers have proposed Continuous DCOPs (C-DCOPs), which can model DCOPs with continuous variables. However, most of the existing C-DCOP algorithms rely on gradient information for optimization, which means that they are unable to solve the situation where the utility function is a non-differentiable function. Although the Particle Swarm-Based C-DCOP (PCD) and Particle Swarm with Local Decision-Based C-DCOP (PCD-LD) algorithms can solve the situation with non-differentiable utility functions, they need to implement Breadth First Search (BFS) pseudo-trees for message passing. Unfortunately, employing the BFS pseudo-tree results in expensive computational overheads and agent privacy leakage, as messages are aggregated to the root node of the BFS pseudo-tree. Therefore, this paper aims to propose a fully distributed C-DCOP algorithm to solve the utility function form problem and avoid the disadvantages caused by the BFS pseudo-tree. Inspired by the population-based algorithms, we propose a fully decentralized local search algorithm, named Population-based Local Search Algorithm (PLSA), for solving C-DCOPs with three-fold advantages: (i) PLSA adopts a heuristic method to guide the local search to achieve a fast search for high-quality solutions; (ii) in contrast to the conventional C-DCOP algorithm, PLSA can solve utility functions of any form; and (iii) compared to PCD and PCD-LD, PLSA avoids complex message passing to achieve efficient computation and agent privacy protection. In addition, we implement an extended version of PLSA, named Population-based Global Search Algorithm (PGSA), and empirically show that our algorithms outperform the state-of-the-art C-DCOP algorithms on three types of benchmark problems.
Research on the Remaining Life Prediction Method of Rolling Bearings Based on Multi-Feature Fusion
Authors: Zhang Guanwen , Jiang Dongnian
Published: February 2024

Rolling bearings are one of the most important and indispensable components of a mechanical system, and an accurate prediction of their remaining life is essential to ensuring the reliable operation of a mechanical system. In order to effectively utilize the large amount of data collected simultaneously by multiple sensors during equipment monitoring and to solve the problem that global feature information cannot be fully extracted during the feature extraction process, this research presents a technique for forecasting the remaining lifespan of rolling bearings by integrating many features. Firstly, a parallel multi-branch feature learning network is constructed using TCN, LSTM, and Transformer, and a parallel multi-scale attention mechanism is designed to capture both local and global dependencies, enabling adaptive weighted fusing of output features from the three feature extractors. Secondly, the shallow features obtained by the parallel feature extractor are residually connected with the deep features through the attention mechanism to improve the efficiency of utilizing the information of the front and back features. Ultimately, the combined characteristics produce the forecasted findings for the RUL of the bearing using the fully connected layer, and RUL prediction studies were performed with the PHM 2012 bearing dataset and the XJTU-SY bearing accelerated life test dataset, and the experimental results demonstrate that the suggested method can effectively forecast the RUL of various types of bearings with reduced prediction errors.