Miracle-dz/UniFAR-FTUs huggingface dataset:
A second-order adaptive temporal-causal network model for age and gender differences in evolving choice of emotion regulation strategies

ABSTRACT Emotion being an essential part of one’s life, its regulation is of utmost importance. The choice of strategies that one employs for regulating their emotions, varies at various stages of their lives and with contexts. Similarly, gender also has an influence on the choice of emotion regulation strategies. This paper presents a second-order adaptive network model for this phenomenon where the choice of strategies varies with age and gender in an adaptive manner. Simulation results for both the genders (male and female) have been provided where for both the genders, choice of emotion regulation strategies changes as age increases. The second-order adaptive network model presented here extends a non-adaptive network model previously introduced at ICCCI’19.
Assessing information sharing from plant clinics in China and Zambia through social network analysis

ABSTRACT Purpose: This paper explores the information sharing between farmers clustered around a formal plant health information source, using six case studies of plant clinics in China and Zambia. Design/methodology/approach: A survey was carried out with 327 farmers; six plant doctors were interviewed and plant clinic records reviewed. Data were analysed using social network analysis and descriptive statistics. Findings: Clinic attendees shared plant health information with an average of 4.6 other farmers in China and 3.8 farmers in Zambia. However, the effective secondary reach of plant clinics, i.e. clinic attendees sharing information with non-attendees, was considerably lower, especially in China, where most sharing took place among clinic attendees. The Zambian plant clinics, managed by public extension services, show a more open pattern where information is also shared with non-attendees. Practical implications: Plant doctors could play a more proactive role in bridging formal and informal networks to enhance the diffusion of plant health information within farming communities. Strategies to optimize the secondary reach of plant clinics should be informed by the agro-ecological and socio-economic context, as well as the type of organization operating the service. Theoretical implications: The type of production system (degree of market orientation) and clinic’s institutional setup (private vs. public sector) determine the characteristics of the social network around it. The closed, crop-specific networks in China result in high uptake of advice but limited secondary reach. The open, more crop-diverse networks in Zambia have higher secondary reach but lower uptake. Originality/value: This is the first study examining how information travels within social networks linked to plant clinics, and patterns of information sharing and use.
Differences in Complementary Feeding of 6 to 23 Month Olds in China, US and Mexico

sufficient to meet the nutritional needs of the infant [1]. The transition from exclusive breastfeeding to family foods, referred to as complementary feeding, typically covers the period from 6 to 18-24 months of age [1]. Since children under two years of age have high nutrient needs to support their rapid growth and development but consume relatively small amounts of food at a time, complementary foods need to be far more nutrient-dense than foods consumed by adults [2].
High Metabolic Age and Excessive Adipose Tissue as a Storage Location for Toxins, and their Influence on the Excretory Function of a Liver and Bile Ducts in Patients with a Transplanted Allogenic Kidney

Introduction: Metabolic age reflects person’s physical health, and is ca lated on a basis of the base metabolic rate (BMR). When person’s meta age is lower than their actual age, this implies their body is in a good he while a metabolic age higher than the actual age indicates that the sub may experience some health problems. Adipose tissue is a typical loca for storage of water-insoluble toxins in the body. It is a connective tissu which the intercellular substance consist of fat. According to the fat distribu in the body, we distinquish two types of obesity: android (abdominal) gynoidal (peripheral). Aim: An attempt was made to evaluate an influence of adipose tissue metabolic age on functions of a transplanted kidney and on an excretory f tion of a liver and bile ducts. Material andmethods: the study covered 152 patients with the functio kidney transplant after more than 3 months from the Ktx, 81 women an men. The average patient agewas 47.8 ± 11.6 years. Their body compos was assessed using the bioimpendance method (BIA) and anthropom measurements. Basic metabolic rate (BMR), muscle tissue weight, total b water content, and amount of the adipose tissue, all contributing to the m bolic age, were evaluated. The nutritional status and the obesity typewere termined with the Waist to Height Ratio (WHtR) and the Waist to Hip R (WHR). The excretory function of the transplanted kidney was evaluate calculating the estimated glomerular filtration rate (eGFR) using the MD formula. Functions of a liver and bile ductswere evaluated as total serum bilir levels, and alanine transaminase (ALT) and gamma-glutamyltransferase (GG levels. Haemolitic uremic syndrome (HUS) was excluded in the studied pers Results: 51% of patients were diagnosed with obesity. People with android body type had lower eGFR versus people with the gynoid b type (p < 0.001). The higher the percentage content of the adipose tissue the metabolic age, the lower was eGFR in the subjects (p < 0,001). Th creased ALT, GGTP levels were positively correlated with high content o ipose tissue and high metabolic age (p < 0.05). Conclusions: Excessive adipose tissue, particularly android obesity, be a predictor for renal, hepatic and bile ducts injury; therefore, correct and pharmacological management, together with physical activity ada to the physical fitness level of a patient are necessary.
Diagnostic Value of Adenosine Deaminase and its Isoenzymatic Activity in Nepalese Patients with Type 2 Diabetes Mellitus

Methods This is a hospital based case control study including 80 type 2 DM patients and same number of age and sex matched healthy controls aged between 30-70 years attending Manipal Teaching Hospital (MTH), Pokhara, Nepal. All the demographic and anthropometric data were collected using a preformed set of questionnaire and biochemical data were obtained from the laboratory analysis of the patients’ blood samples. Statistical analysis was done with SPSS version 20.
Principals’ Intentions to Promote Physical Education

The Principals’ Attitude toward Physical Education (PAPE) survey was used to assess public principals’ intention to promote physical education (PE). Principals (n = 106) from randomly selected middle and high school schools in California completed the PAPE. Results indicated favorable attitudes, perceived behavioral control, and normative beliefs were associated with promoting PE. Middle school principals are more likely to promote PE than high school principals, especially if they promoted PE in the past. Principals who reported higher perceived competence along with positive professional and personal experiences with PE indicated they would likely promote this subject-matter content in their school.
A Compact Ka-Band 4-bit Phase Shifter With Low Group Delay Deviation

This letter presents a compact <inline-formula> <tex-math notation="LaTeX">$Ka$ </tex-math></inline-formula>-band 4-bit switch-type phase shifter with low group delay deviation (GDD) using 28-nm CMOS technology. A magnetically coupled all-pass network (APN) configuration is employed to achieve both equal and flat group delay characteristics versus frequency at each phase state. The measured rms phase error is 1.2°, and the gain error is 1.1 dB at 33 GHz. The average measured insertion loss is 12.8 dB at 33 GHz, and the input and output return losses are both lower than −10 dB from 29 to 37 GHz. The fabricated phase shifter has a compact size of 0.08 mm<sup>2</sup> excluding pads, low GDD of ±4 ps, and rms group delay error of < 2.2 ps between 16 phase states from 29 to 37 GHz. The proposed <inline-formula> <tex-math notation="LaTeX">$Ka$ </tex-math></inline-formula>-band phase shifter has the lowest GDD per bandwidth (GDD/BW) compared with other reported passive phase shifters.
DeepLabStream: Closing the loop using deep learning-based markerless, real-time posture detection

In general, animal behavior can be described as the neuronal-driven sequence of reoccurring postures through time. Current technologies enable offline pose estimation with high spatio-temporal resolution, however to understand complex behaviors, it is necessary to correlate the behavior with neuronal activity in real-time. Here we present DeepLabStream, a highly versatile, closed-loop solution for freely moving mice that can autonomously conduct behavioral experiments ranging from behavior-based learning tasks to posture-dependent optogenetic stimulation. DeepLabStream has a temporal resolution in the millisecond range, can operate with multiple devices and can be easily tailored to a wide range of species and experimental designs. We employ DeepLabStream to autonomously run a second-order olfactory conditioning task for freely moving mice and to deliver optogenetic stimuli based on mouse head-direction.
Integrated spatial analysis for human–wildlife coexistence in the American West

Neil Carter ,MatthewAWilliamson , SophieGilbert, StacyALischka, Laura RPrugh, Joshua J Lawler, Alexander LMetcalf , Aerin L Jacob, Bray J Beltrán, Antonio JCastro, Abigail Sage andMorey Burnham 1 School for Environment and Sustainability, University ofMichigan, DanaBuilding, 440Church Street, AnnArbor,MI 48109,United States of America 2 Human-Environment Systems, Boise StateUniversity. 1910UniversityDr, Boise, ID 83725,United States of America 3 Department of Fish&Wildlife Sciences, University of Idaho, 875 PerimeterDrive,Moscow, ID 83844,United States of America 4 Department of Fish,Wildlife andConservation Biology, Colorado StateUniversity, 1474CampusDelivery, Fort Collins, CO80523, United States of America 5 School of Environmental and Forest Sciences, University ofWashington, Box 352100, Seattle,WA98195,United States of America 6 HumanDimensions Lab,WAFrankeCollege of Forestry andConservation, University ofMontana, 440CHCB, 32CampusDrive, Missoula,MT59812,United States of America 7 Yellowstone toYukonConservation Initiative, 200-1350RailwayAve. , Canmore, AB, T1W1P6, Canada 8 Heart of the Rockies Initiative, 120Hickory St.Missoula,MT59801,United States of America 9 Centro Andaluz para la Evaluación y Seguimiento del CambioGlobal (CAESCG), Departamento de Biología Vegetal y Ecología, Universidad deAlmería, La Cañada de SanUrbano, E-04120, Almería, Spain 10 Idaho StateUniversity, Department of Biological Sciences, 921 South 8thAvenue, Pocatello, ID 83209,United States of America 11 Department of Sociology, SocialWork, andCriminology, Idaho StateUniversity, 921 South 8thAvenue, Pocatello, ID 83209,United States of America 12 Author towhomany correspondence should be addressed.
Multi-View Multi-Label Learning With Sparse Feature Selection for Image Annotation

In image analysis, image samples are always represented by multiple view features and associated with multiple class labels for better interpretation. However, multiple view data may include noisy, irrelevant and redundant features, while multiple class labels can be noisy and incomplete. Due to the special data characteristic, it is hard to perform feature selection on multi-view multi-label data. To address these challenges, in this paper, we propose a novel multi-view multi-label sparse feature selection (MSFS) method, which exploits both view relations and label correlations to select discriminative features for further learning. Specifically, the multi-labeled information is decomposed into a reduced latent label representation to capture higher level concepts and correlations among multiple labels. Multiple local geometric structures are constructed to exploit visual similarities and relations for different views. By taking full advantage of the latent label representation and multiple local geometric structures, the sparse regression model with an <inline-formula><tex-math notation="LaTeX">$l_{2,1}$</tex-math></inline-formula>-norm and an Frobenius norm (<inline-formula><tex-math notation="LaTeX">$F$</tex-math></inline-formula>-norm) penalty terms is utilized to perform hierarchical feature selection, where the <inline-formula><tex-math notation="LaTeX">$F$</tex-math></inline-formula>-norm penalty performs high-level (i.e., view-wise) feature selection to preserve the informative views and the <inline-formula><tex-math notation="LaTeX">$l_{2,1}$</tex-math></inline-formula>-norm penalty conducts low-level (i.e., row-wise) feature selection to remove noisy features. To solve the proposed formulation, we also devise a simple yet efficient iterative algorithm. Experiments and comparisons on real-world image datasets demonstrate the effectiveness and potential of MSFS.
International study abroad programmes: Exploring global south student perspectives, reciprocity and sustainability

ABSTRACT This paper explores student experience, sustainability and the nature of reciprocity in the context of international student mobility programs. There is a considerable body of literature on various aspects of these programs such as educational outcomes, curriculum development, standards for practice and ethical issues. Much of the literature tends to focus on the experiences of the students and staff from the Global North and not on the experiences of those from the Global South. Some authors have highlighted the importance of maximizing the mutual benefits of international programs for all participants and to encourage some level of reciprocity as part of program-planning and delivery. To explore an example of one attempt to increase reciprocity, this small-scale qualitative study focused on the experiences of two international students from India on a short-term program to an Australian regional university. Using semi-structured interviews and thematic analysis to explore their experiences, we reflect on what educators can learn from the lived experience of these students and how we can further increase the level of reciprocity of these programs, thereby enhancing mutual benefit and ethical standards of international engagement.
“Help, I’ve Been Hacked!”: Insights from a Corpus of User-Reported Cyber Victimization Cases on Twitter

Understanding users is critical to develop secure IT systems and effective cybersecurity solutions. Unfortunately, research that analyzes user cybersecurity behaviors and experiences is limited. Motivated by work in public health that relies on Twitter user-reported health conditions, we explore using Twitter to understand user victimization experiences. Observing that users often self-report victimization (Help, I’ve been hacked! ), we construct a corpus of 2,910 Tweets representing user reports of victimization experiences. We label these reports with information about the affected device or account and the associated consequences, as expressed by the users themselves. We begin to uncover trends in compromise in addition to startling attitudes and behaviors that security practitioners must contend with when developing cybersecurity solutions. To the best of our knowledge, this is one of the first papers to construct and analyze a dataset of cyber victimization user reports.
Tuning antiviral CD8 T-cell response via proline-altered peptide ligand vaccination

Viral escape from CD8+ cytotoxic T lymphocyte responses correlates with disease progression and represents a significant challenge for vaccination. Here, we demonstrate that CD8+ T cell recognition of the naturally occurring MHC-I-restricted LCMV-associated immune escape variant Y4F is restored following vaccination with a proline-altered peptide ligand (APL). The APL increases MHC/peptide (pMHC) complex stability, rigidifies the peptide and facilitates T cell receptor (TCR) recognition through reduced entropy costs. Structural analyses of pMHC complexes before and after TCR binding, combined with biophysical analyses, revealed that although the TCR binds similarly to all complexes, the p3P modification alters the conformations of a very limited amount of specific MHC and peptide residues, facilitating efficient TCR recognition. This approach can be easily introduced in peptides restricted to other MHC alleles, and can be combined with currently available and future vaccination protocols in order to prevent viral immune escape. Author Summary Viral escape mutagenesis correlates often with disease progression and represents a major hurdle for vaccination-based therapies. Here, we have designed and developed a novel generation of altered epitopes that re-establish and enhance significantly CD8+ T cell recognition of a naturally occurring viral immune escape variant. Biophysical and structural analyses provide a clear understanding of the molecular mechanisms underlying this reestablished recognition. We believe that this approach can be implemented to currently available or novel vaccination approaches to efficiently restore T cell recognition of virus escape variants to control disease progression.
Hunting and Nesting Phenology Influence Gobbling of Wild Turkeys

Wild turkeys (Meleagris gallopavo) use a polygynous mating system whereby males engage in multiple courtship behaviors, including vocalizations (gobbling) to attract females and compete with other males for breeding opportunities. Males must balance the risk of courtship behaviors with the reproductive potential of each courtship behavior. Male turkeys are primarily hunted during the reproductive period, so the associated risk of courtship behaviors is increased. Many state agencies attempt to set hunting season frameworks that maximize hunter satisfaction by allowing hunting when gobbling activity is greatest and most females are theoretically incubating nests, but the relationship between gobbling activity and nesting phenology is unclear. We used autonomous recording units and global positioning system transmitters to monitor gobbling activity by male turkeys and reproductive behaviors of female turkeys in the Piedmont region of Georgia, USA. We used 13,177 gobbles, behavioral data from 82 females during the reproductive season, and daily estimates of harvest of males by hunters to examine relationships between daily gobbling activity, cumulative removal of males, and reproductive behaviors (laying, incubating) of females during 2017–2018. We observed a weak negative relationship between daily gobbling activity and gobbling activity the following day. As the reproductive season progressed, gobbling activity decreased. As the proportion of females engaged in laying or incubating behaviors increased, expected daily gobbling activity increased. Conversely, we observed that hunting and removal of males had a negative effect on daily gobbling activity, and this effect was disproportionately greater than the positive effect of female reproductive behaviors. Our findings suggest that hunting and removal of males are important determinants of gobbling activity, and that corresponding reductions in gobbling activity may have mediating effects on the mating system of wild turkeys. © 2019 The Wildlife Society.
Surface recognition of machine parts based on the results of optical scanning

To predict the quality parameters of products (in particular, the assembly parameters) mathematical models were implemented in the form of computer models. To ensure the adequacy of calculations, it is necessary to have information about the actual geometry of the parts, which can be obtained using noncontact measurements of parts of the assembly. As a result of measuring parts and components using optical or laser scanner, a large dimension array of measured points is formed. After standard processing (e.g. noise removal, combining the scans, smoothing, creating triangulation mesh), the recognition of individual surfaces of parts becomes necessary. This paper presents a neural network model that allows the recognition of elements based on an array of measured points obtained by scanning.
A paradox or a culture of acceptance? The idiosyncratic workforce delivering health education in lower secondary government schools in Western Australia

ABSTRACT Internationally, research has repeatedly highlighted the marginal and apparently precarious position of Health and Physical Education (HPE) in schools. It has also consistently identified staffing as a key concern in relation to prospects for quality teaching and learning. This paper reports on mixed-methods research that has specifically addressed these concerns in exploring current staffing for health education (HE) in Western Australia (WA). The research sample for the study comprised 75 teachers. The data presented raises serious questions about the capacity of schools and teachers to deliver on national policy intentions to provide all Australian children with an education that effectively supports their current and future health and well-being. Discussion of data addresses professional standards for teachers, teacher preparation in HPE and professional learning for teachers. Developments in all of these areas are identified as necessary to position HE as a key site for meaningful and valuable health learning.
Traffic Impact Area Detection and Spatiotemporal Influence Assessment for Disaster Reduction Based on Social Media: A Case Study of the 2018 Beijing Rainstorm

The abnormal change in the global climate has increased the chance of urban rainstorm disasters, which greatly threatens people’s daily lives, especially public travel. Timely and effective disaster data sources and analysis methods are essential for disaster reduction. With the popularity of mobile devices and the development of network facilities, social media has attracted widespread attention as a new source of disaster data. The characteristics of rich disaster information, near real-time transmission channels, and low-cost data production have been favored by many researchers. These researchers have used different methods to study disaster reduction based on the different dimensions of information contained in social media, including time, location and content. However, current research is not sufficient and rarely combines specific road condition information with public emotional information to detect traffic impact areas and assess the spatiotemporal influence of these areas. Thus, in this paper, we used various methods, including natural language processing and deep learning, to extract the fine-grained road condition information and public emotional information contained in social media text to comprehensively detect and analyze traffic impact areas during a rainstorm disaster. Furthermore, we proposed a model to evaluate the spatiotemporal influence of these detected traffic impact areas. The heavy rainstorm event in Beijing, China, in 2018 was selected as a case study to verify the validity of the disaster reduction method proposed in this paper.