Correlation of personality with individual reproductive success in shrub-nesting birds depends on their life history style

Two questions in the research of animal personality—whether there is a correlation between a personality trait and individual reproductive success,and what is the genetic basis underlying a personality trait—remain unresolved.We addressed these two questions in three shrub-nesting birds,the Azure-winged Magpie(Cyanopica cyanus,AM),White-collared Blackbird(Turdus albocinctus,WB),and Brown-cheeked Laughingthrush(Trochalopteron henrici,BL).The personality type of an individual was first identified according to its response to a territorial intruder.Then,we compared the fleeing distance,breeding parameters,and differential expressed genes(DEGs) in the brain transcriptome between bold and shy breeders.In the three species,bold breeders exhibited more aggressiveness towards an intruder of their territory than did shy breeders.The reproductive success of bold breeders was significantly higher than that of shy breeders in AM but not in WB and BL.The three species shared one DEG,crabp1,which was up-regulated in bold relative to in shy individuals.By regulating the expression of corticotropin-releasing hormone,higher crabp1 gene expression can decrease cellular response to retinoic acid.Therefore,bold individuals are insensitive to external stresses and able to exhibit more aggressiveness to intruders than their shier counterparts.Aggressiveness is beneficial to bold individuals in AM but not in WB and BL because the former could evoke neighbors to make the same response of defending against intruders but the latter could not.Although a personality trait may have the same genetic basis across species,its correlation with reproductive success depends largely on the life history style of a species.

The Impact of Big Five Personality Traits on Older Europeans’ Physical Health

Investigating the role of Big Five personality traits in relation to various health outcomes has been extensively studied. The impact of “Big Five” on physical health is here explored for older Europeans with a focus on examining age groups differences. The study sample included 378,500 respondents derived from the seventh data wave of Survey of Health, Aging and Retirement in Europe (SHARE). The physical health status of older Europeans was estimated by constructing an index considering the combined effect of well-established health indicators such as the number of chronic diseases, mobility limitations, limitations with basic and instrumental activities of daily living, and self-perceived health. This index was used for an overall physical health assessment, for which the higher the score for an individual, the worst health level. Then, through a dichotomization process applied to the retrieved Principal Component Analysis scores, a two-group discrimination (good or bad health status) of SHARE participants was obtained as regards their physical health condition, allowing for further con-structing logistic regression models to assess the predictive significance of “Big Five” and their protective role for physical health. Results showed that neuroti-cism was the most significant predictor of physical health for all age groups un-der consideration, while extraversion, agreeableness and openness were not found to significantly affect the self-reported physical health levels of midlife adults aged 50 up to 64. Older adults aged 65 up to 79 were more prone to open-ness, whereas the oldest old individuals aged 80 up to 105 were mainly affected by openness and conscientiousness. .

Personal Thermal Management by Radiative Cooling and Heating

Maintaining thermal comfort within the human body is crucial for optimal health and overall well-being.By merely broadening the setpoint of indoor temperatures,we could significantly slash energy usage in building heating,ventilation,and air-conditioning systems.In recent years,there has been a surge in advancements in personal thermal management(PTM),aiming to regulate heat and moisture transfer within our immediate surroundings,clothing,and skin.The advent of PTM is driven by the rapid development in nano/micro-materials and energy science and engineering.An emerging research area in PTM is personal radiative thermal management(PRTM),which demonstrates immense potential with its high radiative heat transfer efficiency and ease of regulation.However,it is less taken into account in traditional textiles,and there currently lies a gap in our knowledge and understanding of PRTM.In this review,we aim to present a thorough analysis of advanced textile materials and technologies for PRTM.Specifically,we will introduce and discuss the underlying radiation heat transfer mechanisms,fabrication methods of textiles,and various indoor/outdoor applications in light of their different regulation functionalities,including radiative cooling,radiative heating,and dual-mode thermoregulation.Furthermore,we will shine a light on the current hurdles,propose potential strategies,and delve into future technology trends for PRTM with an emphasis on functionalities and applications.

The Relationship between Mental Disorders and Personality of Outpatients in a Psychiatric Clinic in Nanjing, China

Psychosis has increasingly become a social problem,emphasizing the need to understand the relationship between mental disorders and personality.This study aimed to investigate the relationship between mental disorders and personality among psychiatric outpatients based on real-world data.Symptom Checklist 90(SCL-90)and Eysenck Personality Questionnaire(EPQ)were used to evaluate the personality and psychopathological symptoms of patients(n=8409)in the Psychiatric Outpatient Department at Nanjing Drum Tower Hospital.t-test was used to compare scores between patients and national norms.Pearson’s correlation coefficient and path analysis were used to explore the relationship between mental health status and personality.The correlation coefficient between the neuroticism(N)score and each factor score of the SCL-90 test,as well as the correlation between psychoticism(P)and hostility and paranoia,exceeded 0.4.Path analysis revealed that the standardized path coefficients of N score and SCL-90 were all higher than 0.4.In addition,the standardized path coefficient of hostility and paranoia on P score were 0.313 and 0.280,respectively.Interpersonal sensitivity,depression and obsessive-compulsive symptoms were affected by extraversion(E)score,with standardized path coefficients of-0.149,-0.138,and-0.105,respectively.The path analysis also showed the direct and indirect effects of age,gender,education,and marital status on SCL-90.Patients characterized as melancholic had higher scores in all factors of SCL-90.In conclusion,mental health was related to personality traits of neuroticism,psychoticism and introversion.

Who Benefits More from Physical Exercise?On the Relations between Personality,Physical Exercise,and Well-Being

Although employers believe that encouraging and supporting physical exercise activities by purchasing fitness equipment and building sports venues can improve employees’well-being,the utilization rate is rather low.Since most of the evidence of the well-being promotion in the workplace concentrated on the perspectives of organizational factors and psychosocial factors and focused on the reduction of the negative affect of well-being,it is still an open question whether physical exercise has benefits on both negative and positive affect of well-being and who benefits more from physical exercise.Thus,the purpose of this study is to investigate the impact of physical exercise on occupational well-being(job burnout and work engagement)and examine whether effectiveness depends on personality traits.Online questionnaires were distributed.The sample included 671 participants from different enterprises in China.Results showed that the effectiveness of physical exercise was also applicable to well-being in the workplace.Physical exercise was negatively correlated with job burnout and positively correlated with work engagement.The effectiveness was different among employees with different personality traits.Contrary to our expectation,individuals with neuroticism were more likely to improve their work engagement through physical exercise.Extroversion and conscientiousness weakened the benefits of physical exercise.Therefore,differences of effectiveness among different personality traits emphasize the need for a more personalized strategy in physical exercise interventions.

On the Construction and Application Scenarios of——Analysis of Environmental Personality Interests Based on Human Rights

Environmental personality interests based on human rights reflect the multiple values of ecological order,ecological justice,and ecological freedom,and are closely linked to the protection of the right to life and the right to health.They are also related to human dignity and the personal freedom of civil subjects and conform to formal and essential standards of personality rights,which should be included in the scope of personality rights for protection.The construction and application of environmental personality rights faces bottlenecks such as the partiality of subjects,limitation of objects,and hysteresis of responsibilities in the protection of environmental personality rights.Environmental personality rights are supposed to reflect the needs of the development of modern human rights.We should expand the scope of its connotative power and function based on the Green Principle of the Civil Code,and follow a networked,typified,and systematic path of protection,so as to manifest the people-centered philosophy of the Civil Code and the Environmental Protection Law.

The moderating role of NTSR1 polymorphisms on personality and coping styles among breast cancer patients

Background:Some personality traits could be a predictor for coping styles.The objective of this investigation was to examine the correlation between personality traits and coping mechanisms in the context of gene regulation among breast cancer patients.Material and methods:This cross-sectional study was performed in 2021.A total of 200 breast cancer patients were included in this study.Data were collected using the Trait Coping Style Questionnaire(TCSQ)and the Eysenck Personality Questionnaire-Revised Short Scale for Chinese(EPQ-RSC).And individuals’blood was tested for genotype.Results:The findings indicated that there existed an inverse relationship between extraversion and negative coping style while also demonstrating a significant association between extraversion and positive coping style.Neuroticism was positively correlated with negative coping style but negatively with positive coping style.The SNP of NTSR1 only moderated the relationship between neuroticism and negative coping styles in breast cancer patients.Conclusion:The present investigation delves into the correlation between personality traits and coping mechanisms at the molecular level in breast cancer patients.

Personalized Perioperative Care for a Patient with a 10-Year-Old Postpartum Old Thrombus after Neoadjuvant Therapy for Breast Cancer

Breast cancer is one of the most common malignant tumors in women, and has become the main cause threatening women’s health. A case of breast cancer with neoadjuvant chemotherapy was discharged after active treatment and nursing.

The Enlightenment of Cai Yuanpei’s Aesthetic Education to Personality Education

With the development of human society and the progress of science and technology,people’s cultural cognition has constantly strengthened.With people’s research and thinking,all kinds of cultural education came into being,aesthetic education,moral education,and sports,all play a significant role in people’s physical and mental development,among which the aesthetic education thought advocated by Cai Yuanpei has a great value as guidelines for the significance of personality education.It is of great importance to people’s physical and mental development.

Socio-Spatial Dynamics of Land in Southwest Niger: The Case of the Commune of Gothèye

In south-west Niger, ecosystems are losing several hectares of their surface area every year due to internally displaced persons and refugees. The commune of Gothèye is not immune to this situation. The aim of this research is to assess the impact of displaced persons and refugees on socio-spatio-temporal dynamics of ecosystems using Landsat images. To achieve this, Landsat TM, Landsat ETM+ and OLI 8 satellite images from September and March were used (2010 to 2024). Operations on Envi 5.3, field validation output and finally mapping on ArcGIS were the steps involved. Discrimination is significant, with kappa coefficients of 0.97, 0.96, 0.86 and 0.85. The results obtained indicate a degradation of natural ecosystems, reflected in a change in landscape structure, with a marked reduction in the quantity and quality of ecosystem goods. Analysis of the evolution of land use showed that 31% of the land remained in its initial state (unchanged), 69% underwent modifications, and 11% was converted to cropland. Over these fourteen years, the study area has undergone changes in land use patterns, which have resulted in a modification of landscape structure, with a marked decline in the quantity and quality of ecosystem services.

COVID-19 and the Vascular Elderly Subject: Illustration of Therapeutic Management with Corticosteroids in an Elderly Diabetic Patient with COVID-19

Introduction: The severity of Sars-Cov-2 infection is associated with the development of acute respiratory distress syndrome (ARDS). The progression to ARDS appears to be driven by a major inflammatory mechanism potentially sensitive to corticosteroids. Observation: This article describes the case of an elderly patient was admitted to emergency departments for intense asthenia, accompanied by motor diarrhoea, dyspnoea with desaturation in ambient air, in a context of strong suspicion of infection linked to COVID-19. The article also reviews the existing literature on the diagnosis and treatment of this severe form of the disease. Conclusion: Corticosteroids, and in particular dexamethasone, have been shown to be effective in the management of patients with COVID-19, an oxygen-releasing disease.

The Development of Human Rights Protection in Cross-border Personality Rights and Tort Conflict Laws

Personality rights are basic rights related to human dignity in the concept of human rights protection,and respect for personality rights is the basic prerequisite for safeguarding other human rights.Human rights protection exerts a profound impact on the value of legislation and enforcement practices of private international laws in the field of cross-border personality rights infringement in various countries,which is mainly manifested in the integration of substantive justice and the humanistic care concept of protecting the rights of vulnerable groups into formal justice,and expands the development space of human rights protection ideas in cross-border personality rights and tort conflict laws.the diversity of human rights protection values determines that cross-border personality rights infringement may lead to conflicts between personality rights and other basic rights,such as freedom of speech.to reconcile such conflicts,a workable method is to prioritize personality rights protection in accordance with the hierarchy of rights theory in the value judgment of public order reservation or to clarify the limits of the right holder’s tolerance obligation through the limited application of the principle of proportionality.China’s current cross-border personality rights and tort conflict law can optimize the protection of the rights of vulnerable groups by diversifying the options of available legal methods,and establish a balancing mechanism between personality rights and freedom of speech,so as to improve China’s legal protection system for human rights in the field of foreign-related civil and commercial affairs.

Enhancing Unsupervised Domain Adaptation for Person Re-Identification with the Minimal Transfer Cost Framework

In Unsupervised Domain Adaptation(UDA)for person re-identification(re-ID),the primary challenge is reducing the distribution discrepancy between the source and target domains.This can be achieved by implicitly or explicitly constructing an appropriate intermediate domain to enhance recognition capability on the target domain.Implicit construction is difficult due to the absence of intermediate state supervision,making smooth knowledge transfer from the source to the target domain a challenge.To explicitly construct the most suitable intermediate domain for the model to gradually adapt to the feature distribution changes from the source to the target domain,we propose the Minimal Transfer Cost Framework(MTCF).MTCF considers all scenarios of the intermediate domain during the transfer process,ensuring smoother and more efficient domain alignment.Our framework mainly includes threemodules:Intermediate Domain Generator(IDG),Cross-domain Feature Constraint Module(CFCM),and Residual Channel Space Module(RCSM).First,the IDG Module is introduced to generate all possible intermediate domains,ensuring a smooth transition of knowledge fromthe source to the target domain.To reduce the cross-domain feature distribution discrepancy,we propose the CFCM Module,which quantifies the difficulty of knowledge transfer and ensures the diversity of intermediate domain features and their semantic relevance,achieving alignment between the source and target domains by incorporating mutual information and maximum mean discrepancy.We also design the RCSM,which utilizes attention mechanism to enhance the model’s focus on personnel features in low-resolution images,improving the accuracy and efficiency of person re-ID.Our proposed method outperforms existing technologies in all common UDA re-ID tasks and improves the Mean Average Precision(mAP)by 2.3%in the Market to Duke task compared to the state-of-the-art(SOTA)methods.

Personality Trait Detection via Transfer Learning

Personality recognition plays a pivotal role when developing user-centric solutions such as recommender systems or decision support systems across various domains,including education,e-commerce,or human resources.Tra-ditional machine learning techniques have been broadly employed for personality trait identification;nevertheless,the development of new technologies based on deep learning has led to new opportunities to improve their performance.This study focuses on the capabilities of pre-trained language models such as BERT,RoBERTa,ALBERT,ELECTRA,ERNIE,or XLNet,to deal with the task of personality recognition.These models are able to capture structural features from textual content and comprehend a multitude of language facets and complex features such as hierarchical relationships or long-term dependencies.This makes them suitable to classify multi-label personality traits from reviews while mitigating computational costs.The focus of this approach centers on developing an architecture based on different layers able to capture the semantic context and structural features from texts.Moreover,it is able to fine-tune the previous models using the MyPersonality dataset,which comprises 9,917 status updates contributed by 250 Facebook users.These status updates are categorized according to the well-known Big Five personality model,setting the stage for a comprehensive exploration of personality traits.To test the proposal,a set of experiments have been performed using different metrics such as the exact match ratio,hamming loss,zero-one-loss,precision,recall,F1-score,and weighted averages.The results reveal ERNIE is the top-performing model,achieving an exact match ratio of 72.32%,an accuracy rate of 87.17%,and 84.41%of F1-score.The findings demonstrate that the tested models substantially outperform other state-of-the-art studies,enhancing the accuracy by at least 3%and confirming them as powerful tools for personality recognition.These findings represent substantial advancements in personality recognition,making them appropriate for the development of user-centric applications.

Harnessing the Power of Artificial Intelligence in Neuromuscular Disease Rehabilitation: A Comprehensive Review and Algorithmic Approach

Neuromuscular diseases present profound challenges to individuals and healthcare systems worldwide, profoundly impacting motor functions. This research provides a comprehensive exploration of how artificial intelligence (AI) technology is revolutionizing rehabilitation for individuals with neuromuscular disorders. Through an extensive review, this paper elucidates a wide array of AI-driven interventions spanning robotic-assisted therapy, virtual reality rehabilitation, and intricately tailored machine learning algorithms. The aim is to delve into the nuanced applications of AI, unlocking its transformative potential in optimizing personalized treatment plans for those grappling with the complexities of neuromuscular diseases. By examining the multifaceted intersection of AI and rehabilitation, this paper not only contributes to our understanding of cutting-edge advancements but also envisions a future where technological innovations play a pivotal role in alleviating the challenges posed by neuromuscular diseases. From employing neural-fuzzy adaptive controllers for precise trajectory tracking amidst uncertainties to utilizing machine learning algorithms for recognizing patient motor intentions and adapting training accordingly, this research encompasses a holistic approach towards harnessing AI for enhanced rehabilitation outcomes. By embracing the synergy between AI and rehabilitation, we pave the way for a future where individuals with neuromuscular disorders can access tailored, effective, and technologically-driven interventions to improve their quality of life and functional independence.

Nano-revolution in hepatocellular carcinoma:A multidisciplinary odyssey-Are we there yet?

In this editorial we comment on the review by Zhou et al reviewing the landscape of nanomedicine in the treatment of hepatocellular carcinoma(HCC).We focus on the immense potential of nanotechnology,particularly ligand-receptor mediated nanotherapy,in revolutionizing the treatment landscape of HCC.Despite advan-cements in multidisciplinary treatment,HCC remains a significant global health challenge.Ligand-mediated nanotherapy offers the opportunity for precise drug delivery to tumor sites,targeting specific receptors overexpressed in HCC cells,thereby enhancing efficacy and minimizing side effects.Overcoming drug resistance and aggressive tumor biology is facilitated by nanomedicine,bypassing traditional hurdles encountered in chemotherapy.Examples include targeting glypican-3,asialoglycoprotein,transferrin receptor or folic acid receptors,capitalizing on their over-expression in tumor cells.The ability for multi-receptor targeting through dual-ligand nanoparticle modification holds the prospect of further enhancement in specificity and efficacy of directed therapy.However,challenges including immune responses,reproducibility in nanoparticle synthesis,and production scalability remain.Future directions involve refining targeting strategies,improving drug release mechanisms,and streamlining production processes to enable personalized and multifunctional nanotherapies.Overall,the integration of nanotherapy in HCC treatment holds immense promise,but continued partnership and effort are needed in offering hope for more effective,precise,and accessible clinical care in the management of HCC.

Perspectives and Experiences of Education Stakeholders: A Quantitative Study on the Adoption of Artificial Intelligence in Executive Training Using Structural Equation Modeling

The recent increase in the use of artificial intelligence has led to fundamental changes in the development of training and teaching methods for executive education. However, the success of artificial intelligence in regional centers for teaching and training professions will depend on the acceptance of this technology by young executive trainees. This article discusses the potential benefits of adopting AI in executive training institutions in Morocco, specifically focusing on CRMEF Casablanca Settat. Based on the Unified Theory of Acceptance and Use of Technology (UTAUT) (Venkatesh et al., 2003), this study proposes a model to identify the factors influencing the acceptance of artificial intelligence in regional centers for teaching professions and training in Morocco. To achieve this, a structural equation modeling approach was used to quantitatively describe the impact of each factor on AI adoption, utilizing data collected from 173 young executive trainees. The results indicate that perceived ease of use, perceived usefulness, trainer influence, and personal innovativeness influence the intention to use artificial intelligence. Our research provides managers of CRMEFs with a set of practical recommendations to enhance the implementation conditions of an artificial intelligence system. It aims to understand which factors should be considered in designing an artificial intelligence system within regional centers for teaching professions and training (CRMEFs).

Attitudes Toward People Who Stutter in the Chinese Context: An Exploratory Study on the Impact of Knowledge Sources

The public’s attitudes can affect the experience of stuttering of people who stutter.This study investigated the attitudes held by the public about people who stutter in China.A web-based written survey with closed and open-ended questions was implemented to develop a rich understanding.One hundred and two respondents in 26 provinces and 3 municipalities provided comments on people who stutter in their life aspects such as personality,speech,social life,work,life participation,education,dating and marriage,capability,and communication skills.The predominantly negative attitudes towards the overall domains were identified.Attitudes to people who stutter varied according to the different sources of knowledge.Familiarity with people who stutter might reduce stereotypes.However,knowledge from the media might aggravate stereotypes.Implications and future research orientation were also discussed.

Modulatory role of plant-derived metabolites on host-microbiota interactions:personalized therapeutics outlook

A diverse array of microbes in and on the human body constitute the microbiota.These micro-residents continuously interact with the human host through the language of metabolites to dictate the host’s physiology in health and illnesses.Any biotic and abiotic component ensuring a balanced host-microbiota interaction are potential microbiome therapeutic agents to overcome human diseases.Plant metabolites are continually being used to treat various illnesses.These metabolites target the host’s metabolic machinery and host-gut microbiota interactions to overcome human diseases.Despite the paramount therapeutic significance of the factors affecting host-microbiota interactions,a comprehensive overview of the modulatory role of plant-derived metabolites in host-microbiota interactions is lacking.The current review puts an effort into comprehending the role of medicinal plants in gut microbiota modulation to mitigate various human illnesses.It would develop a holistic understanding of hostmicrobiota interactions and the role of effectors in health and diseases.

Exploring the Intersection of Spirituality and Religion:Transcendence,Secularism,and Personal Beliefs in Contemporary Society

This paper explores the intersection of spirituality and religion,focusing on how transcendence,secularism,and personal beliefs shape contemporary spiritual practices.It examines the philosophical foundations of transcendence,the rise of existentialism,and the distinction between spirituality and religion.Secularism's role in fostering personal spirituality and reducing religious authority is discussed,alongside the psychological and societal impacts of spiritual transcendence.The paper also critiques the limitations of spirituality,emphasizing the need for a balanced approach that integrates cognitive development and mental health perspectives.