Miracle-dz/UniFAR-FTUs huggingface dataset:
Relationship between parental resilience and demographic characteristics

Resilience is the ability of an object to withstand tension or compression forces and ultimately resume its original shape. In the domain of social science related to human behavior resilience refers to the personal qualities that enable to thrive in the face of adversity. In the context of family, parental resilience is the ability to gainfully cope with and bounce back from all types of challenges. It is about creatively solving problems, building trusting relationships, maintaining a positive attitude, and seeking help when it is needed. The study was conducted in Jorhat district of Assam and 100 adolescents of 14-16 years having both the parents, thus a parents sample of 200 parents were selected as samples by following purposive sampling method under non probability sampling technique. The study aimed at assessing the extent of parental resilience and studying the relationship of parental resilience and demographic characteristics of the parents. Self constructed questionnaire was used to collect the data comprising demographic characteristics and self constructed interview schedule based on Connor-Davidson Resilience Scale (CD-RISC) was used to assess parental resilience. Results indicated that the majority of the parents (78%) possess average level of parental resilience while 10.5% and 11.5% possess high and low level of resilience respectively. It was also revealed that there is a significant association of the demographic variables -education, occupation and income with parental resilience. Therefore, parental resilience plays an important role in facing daily challenges, solving problems and bouncing back from certain adversities in the family.
Designing a data mining process for the financial services domain

ABSTRACT The implementation of data mining projects in complex organisations requires well-defined processes. Standard data mining processes, such as CRISP-DM, have gained broad adoption over the past two decades. However, numerous studies demonstrated that organisations often do not apply CRISP-DM and related processes as-is, but rather adapt them to address industry-specific requirements. Accordingly, a number of sector-specific adaptations of standard data mining processes have been proposed. So far, however, no such adaptation has been suggested for the financial services sector. This paper addresses the gap by designing and evaluating a Financial Industry Process for Data Mining (FIN-DM). FIN-DM adapts and extends CRISP-DM to address regulatory compliance, governance, and risk management requirements inherent in the financial sector, and to embed quality assurance as an integral part of the data mining project life-cycle. The framework has been iteratively designed and validated with data mining and IT experts in a financial services organisation.
Self-report Measures for Symptom Validity Assessment in Whiplash-associated Disorders

Whiplash-Associated Disorders (WAD) are one of the most complex conditions to evaluate because several of its symptoms are not observable with current diagnostic methods and cannot be quantified or evaluated correctly. No method is currently available to assess the risk of malingering in the aforementioned condition efficiently. Our aim is to study the capacity of several biopsychosocial psychometric self-report instruments, such as the Brief Pain Inventory (BPI), the Cervical Disability Index (NDI), the SF-36 Health Questionnaire, the Beck Anxiety and Depression Inventories (BDI-II and BAI), or the Brief Illness Perception Questionnaire (BIPQ), to discriminate between patients diagnosed with WAD following a vehicle accident and non-clinical participants with malingering instructions. Method: A simulation design was used with 630 participants: 200 non-clinical controls with honest responding condition, 201 instructed malingerers, and 229 WAD clinical outpatients. Results: Our results showed an AUC range of . 60 to . 90, with the highest value being that of the BPI (.90), followed by the NDI (.88), and the lowest value that of the BIPQ (.60), followed by the BAI (.71). Conclusions: Overall, the BPI, the NDI, and SF-36 can correctly discriminate between groups with a good specificity (> 90%), while the BAI, BDI, and BIPQ showed a lower capacity, with a high rate of false positives in the case of the BDI and of false negatives in the other two. Practical and research implications are discussed.
Antihemolytic and antioxidant activities of aerial parts extracts of Zygophyllum album L. and Globularia alypum L. from Algeria

The main intrest of this study was to evaluate the antihemolytic and the antioxidant activities of the aqueous extracts of Globularia alypum and Zygophyllum album prepared by three different methods: decoction, infusion and maceration. Phytochemical tests, total phenolic, flavonoid and tannins contents of the different aqueous extracts were determined. DPPH radical scavenging assay and Ferric Reducing Antioxidant Power (FRAP) were employed for the evaluation of the antioxidant activity. Whereas, the antihemolytic activity was carried out by the evaluation of the protective effect of the various prepared extracts on red blood cells against the radical attack induced by 2,2′-azobis(2-amidinopropane) di-hydrochloride (AAPH). The aqueous extract of Globularia alypum prepared by decoction showed the highest level of total phenolic contents (196.52± 10.76 µg GAE/mg Extract). These findings confirmed the remarkably antioxidant properties of this plant with DPPH scavenging activity and FRAP test. A concentration of 160 µg/ml of this extract showed a protective effect against hemolysis induced by AAPH radical. Hence, Zygophyllum album extracts demonstrated lower level of total phenolic contents (30.41 ± 2.01 µg GAE/mg Extract) and lower antioxidant and antihemolytic activities. Globularia alypum extracts presented a powerful antioxidant and antihemolytic activities especially for the decoction extract whereas Zygophyllum album revealed a weaker protective effect except its maceration extract.
Altered Balance of Reelin Proteolytic Fragments in the Cerebrospinal Fluid of Alzheimer’s Disease Patients

Reelin binds to the apolipoprotein E receptor apoER2 to activate an intracellular signaling cascade. The proteolytic cleavage of reelin follows receptor binding but can also occur independently of its binding to receptors. This study assesses whether reelin proteolytic fragments are differentially affected in the cerebrospinal fluid (CSF) of Alzheimer’s disease (AD) subjects. CSF reelin species were analyzed by Western blotting, employing antibodies against the N- and C-terminal domains. In AD patients, we found a decrease in the 420 kDa full-length reelin compared with controls. In these patients, we also found an increase in the N-terminal 310 kDa fragment resulting from the cleavage at the so-called C-t site, whereas the 180 kDa fragment originated from the N-t site remained unchanged. Regarding the C-terminal proteolytic fragments, the 100 kDa fragment resulting from the cleavage at the C-t site also displayed increased levels, whilst the one resulting from the N-t site, the 250 kDa fragment, decreased. We also detected the presence of an aberrant reelin species with a molecular mass of around 500 kDa present in AD samples (34 of 43 cases), while it was absent in the 14 control cases analyzed. These 500 kDa species were only immunoreactive to N-terminal antibodies. We validated the occurrence of these aberrant reelin species in an Aβ42-treated reelin-overexpressing cell model. When we compared the AD samples from APOE genotype subgroups, we only found minor differences in the levels of reelin fragments associated to the APOE genotype, but interestingly, the levels of fragments of apoER2 were lower in APOE ε4 carriers with regards to APOE ε3/ε3. The altered proportion of reelin/apoER2 fragments and the occurrence of reelin aberrant species suggest a complex regulation of the reelin signaling pathway, which results impaired in AD subjects.
Global Trends in Natural Biopolymers in the 21st Century: A Scientometric Review

Since the 21st century, natural biopolymers have played an indispensable role in long-term global development strategies, and their research has shown a positive growth trend. However, these substantive scientific results are not conducive to our quick grasp of hotspots and insight into future directions and to understanding which local changes have occurred and which trend areas deserve more attention. Therefore, this study provides a new data-driven bibliometric analysis strategy and framework for mining the core content of massive bibliographic data, based on mathematical models VOS Viewer and CiteSpace software, aiming to understand the research prospects and opportunities of natural biopolymers. The United States is reported to be the most important contributor to research in this field, with numerous publications and active institutions; polymer science is the most popular subject category, but the further emphasis should be placed on interdisciplinary teamwork; mainstream research in this field is divided into five clusters of knowledge structures; since the explosion in the number of articles in 2018, researchers are mainly engaged in three fields: “medical field,” “biochemistry field,” and “food science fields. ” Through an in-depth analysis of natural biopolymer research, this article provides a better understanding of trends emerging in the field over the past 22 years and can also serve as a reference for future research.
Implementation of Artificial Intelligence Image Emotion Detection Mechanism Based on Python Architecture for Industry 4.0

Since the beginning of the 21st century, with the development of information technology, researchers in various fields have gradually increased their research on human emotion and behavior. The current research mechanism used in emotion and behavior research is artificial intelligence technology. Through the literature survey and data analysis in related fields, it is found that the acquisition of human emotions and behaviors will be carried out through facial feature algorithm for point capture and combined with machine learning for output detection and analysis. Among them, the detection process requires machine learning of artificial intelligence first. This paper firstly analyzes and summarizes the advantages of Python programs at this stage and completes the preliminary work of system construction by setting and installing platform parameters. In the research process, this paper uses the existing algorithm to apply the σ E value algorithm to the samples and conducts preliminary tests. The overall detection values in the test data are relatively average, and there are still differences in the samples. At the same time, we compare the U E and T E detection algorithms according to the output Y value of the algorithm in the machine learning. The detection rate of some emoticons in the U E algorithm is high, but the detection rate of other emoticons is low. Finally, according to the limitation of the output method in the mathematical formula, a new algorithm σ x of taking the weighted sum and taking the logarithm and then taking the square root is proposed again. According to the statistical analysis, the overall average value of the final algorithm has been improved, and the overall detection rate is about 80%; compared with the T E and U E algorithms, the overall detection frequency fluctuates less. The σ x algorithm in the frequency fluctuation data table in the paper is also superior to the existing algorithms in machine learning, sample testing, and data in the frequency fluctuation. Our next direction will be to use the Python main program to perform AI automatic facial emotion detection work by combining the new algorithm σ x with the V value, DWT, and CNN algorithm in the facial recognition feature through machine learning.
Phylogenetic implications of the complete mitochondrial genome of Ogcogastersegmentator (Westwood, 1847) and first record of the genus Ogcogaster Westwood, 1847 from China (Neuroptera, Myrmeleontidae, Ascalaphinae)

Abstract Background The genus Ogcogaster Westwood, 1847, which is endemic to the Oriental Region and contains only five species, has been recorded in India and Pakistan, but not in China. The genus was not sampled in any previous study on the phylogeny of Neuroptera and its affinity within Ascalaphinae is unclear. New information The owlfly species Ogcogastersegmentator (Westwood, 1847) is firstly recorded from China, based on a female specimen collected from Yunnan Province, which represents the first record of the genus Ogcogaster from China. The complete mitochondrial genome of this species is first sequenced and described. The phylogenetic analysis, based on all 13 PCGs and two rRNA genes of the owlfly mitogenomes determined so far, assigned O.segmentator into a monophyletic group with Libelloidesmacaronius (Scopoli, 1763) and Ascalohybrissubjacens (Walker, 1853).
Explaining when older persons are perceived as a burden: A cross-national analysis of ageism

This study aims to shed further light on the emergence of ageist attitudes by introducing a theoretically grounded mechanism that helps explain why older persons appear as burdensome by segments of society. We introduce the concept of “marketized mentality” (MM), which depicts a strong personal commitment to the principal values associated with the market economy, to the research on ageism. The results of multilevel regression analyses with World Values Survey data (N = 70,456 individuals in 59 nations) reveal that MM yields the hypothesized, positive relationship with our burden-focused indicator of ageism. Moreover, we observe that countries with high levels of MM—which might be conceptualized as “marketized anomic cultures”—exhibit particularly high levels of this form of ageism.
A family life cycle perspective on deliberate self-harm among adolescents: an initial qualitative study

ABSTRACT Deliberate Self-Harm (DSH) among adolescents is a frequent reason for Emergency Department admissions. Many studies that have considered the risk factors for DSH, mainly from a psychiatric standpoint. However, looking at it from a family life cycle perspective is also important. This study discusses the contribution of systemic themes such as differentiation of self to events leading up to DSH. Of the 24 adolescents presenting with first time DSH without any psychiatric disorder in a 12-month period, 16 were triggered by conflicts with parents and 8 due to conflicts with romantic partners. A struggle with differentiation of self was the major systemic theme. Brief intervention strategies that consider these systemic issues and help both the adolescent and the family are likely to be of benefit.
Research on Chengdu Ma Goat Recognition Based on Computer Vison

Simple Summary Accurate and efficient automatic individual recognition of livestock such as goats is one of the key tasks to achieve smart farming. However, this task is challenging due to factors such as the dense distribution of livestock in a barn. To accurately recognize Chengdu ma goats, a high-quality sheep breed with local characteristics, we construct a Chengdu ma goat dataset containing nearly one thousand images with manual annotation information and propose a method for the automatic individual recognition of Chengdu ma goats using a computer. Experiments demonstrate the usability of our method to accurately recognize Chengdu ma goats under extreme conditions such as dense target distribution and drastic differences in scale. It is worth noting that the method is scalable, which enhances the network’s representation ability for data by learning the structural information of goats’ head area. The location and category information obtained by our automatic individual recognition method is the basis for realizing a series of subsequent intelligent breeding tasks, such as precision feeding based on age and sex. Our method provides a new idea for automatic livestock recognition and can be extended to be applied to additional types of livestock. Abstract The Chengdu ma goat is an excellent local breed in China. As one of the breeds listed in the National List of Livestock and Poultry Genetic Resources Protection, the protection of its germplasm resources is particularly important. However, the existing breeding and protection methods for them are relatively simple, due to the weak technical force and lack of intelligent means to assist. Most livestock farmers still conduct small-scale breeding in primitive ways, which is not conducive to the breeding and protection of Chengdu ma goats. In this paper, an automatic individual recognition method for Chengdu ma goats is proposed, which saves labor costs and does not depend on large-scale mechanized facilities. The main contributions of our work are as follows: (1) a new Chengdu ma goat dataset is built, which forms the basis for object detection and classification tasks; (2) an improved detection algorithm for Chengdu ma goats based on TPH-YOLOv5 is proposed, which is able to accurately localize goats in high-density scenes with severe scale variance of targets; (3) a classifier incorporating a self-supervised learning module is implemented to improve the classification performance without increasing the labeled data and inference computation overhead. Experiments show that our method is able to accurately recognize Chengdu ma goats in the actual indoor barn breeding environment, which lays the foundation for precision feeding based on sex and age.
Monotony, Fatigue and Microsleeps - Train driver' daily routine: a Simulator study.

The train drivers’ profession has undergone significant changes in the last years. Information-processing and controlling functions have increased substantially while physical demand has decreased. However, because of the shift work, physical and mental strain is still high. Fatigue and monotony seem to be issues related to normal operation conditions. Also, train drivers’ ability to react to unpredictable events deteriorates when exposed to highly predictable and uneventful driving tasks. A driving simulator study was conducted in order to evaluate the impact of monotony to the train drivers’ driving performance. Eleven male train drivers took part at the experimental study in the RailSET train simulation environment - a realistic replica of a real train drivers’ cabin and its surrounding. While driving under a normal and monotonous condition, driving tasks were given to the participants in order to measure reaction times and driving performance. Participants were divided into two groups: morning and afternoon. The results of the study show a significant difference in reaction times between the normal and the monotonous condition, with higher reaction times in the monotonous condition. The self-rated sleepiness on basis of the Karolinska Sleepiness Scale shows a considerable increase in the course of the test drive. Five from eleven participants were experiencing microsleep episodes. Six out of eleven test persons showed signals passed at danger (SPADs), i.e. they slipped past a signal showing a red aspect (stop). Almost all train drivers participating in the simulator study pointed out the importance of the monotony and fatigue study, based on their own experience of occurrence and probability of microsleep in the daily routine of the train drivers’ work.
Study of the compression properties of welded seams formed using hot wedge, hot air, ultrasonic, and high-frequency welding techniques

The compression properties of welded seams depending on welding parameters using the hot wedge and hot air welding technique, ultrasonic welding technique, and high-frequency welding technique were studied. The compression properties, expressed by parameters such as compressional energy WC, compressional resilience RC, linearity LC, and compressibility C, are important information about the welded seam quality in terms of touch, voluminosity, stiffness, and flexibility of the welded seam. KES-FB and FAST measurement systems were used to test the compression properties of the welded seams. Based on the analysis of the results obtained, the influence of the welding parameters on the compression properties of the welded seam was determined. The results of the investigation showed that improperly selected welding parameters, such as the supply or introduction of too much heat into the material to be welded or too long exposure of the material in the weld zone to heat, result in welded seams with expressive extrusion edges, which affects the quality of the welded seams. These welded seams have very low values of compressional resilience RC and very high values of compressional energy WC and compressibility C.
Genome-Wide Analysis of the Rice Gibberellin Dioxygenases Family Genes

Gibberellins (GAs), a pivotal plant hormone, play fundamental roles in plant development, growth, and stress response. In rice, gibberellin-dioxygenases (GAoxes) are involved in the biosynthesis and deactivation of gibberellins. However, a comprehensive genome-wide analysis of GA oxidases in rice was not uncovered. Here, a total of 80 candidate OsGAox genes were identified and 19 OsGAox genes were further analyzed. Studies on those 19 OsGAox genes, including phylogenetic tree construction, analysis of gene structure, exploration of conserved motifs and expression patterns, were conducted. Results showed that the GAox genes in Arabidopsis and rice were divided into four subgroups and shared some common features. Analysis of gene structure and conserved motifs revealed that splicing phase and motifs were well conserved during the evolution of GAox genes in Arabidopsis and rice, but some special conserved motifs possessed unknown functions need to be further studied. Exploration of expression profiles from RNA-seq data indicated that each GAox gene had tissue-specific expression patterns, although they varied greatly. The expression patterns of these genes under GA3 treatment revealed that some genes, such as OsGA2ox1, OsGA2ox3, OsGA2ox4, OsGA2ox7, OsGA20ox1, and OsGA20ox4, may play a major role in regulating the level of bioactive GA. Taken together, our study provides a comprehensive analysis of the GAox gene family and will facilitate further studies on their roles in rice growth and development so that these genes can be better exploited.
Thermal and hydraulic performance of solid-porous compound wavy micro-channel heat sinks

In this numerical study, seven distinct three-dimensional unique models of micro-channel heat sinks have been investigated. A solid-porous compound wavy channel with optimum thickness of porous fins has been newly adapted to improve the thermal and hydraulic performance of the forthcoming micro-electronic devices. The finite volume method is used to solve the hydraulic and thermal performance of micro-channel heat sinks, and Darcy–Forchheimer flow models are applied for fluid flow through porous fins. Water is employed as a working fluid. Solid wall and porous fins are made of copper material; during analysis, Reynolds numbers vary from 50 to 300, and the effective thermal conductivity has been considered for porous fins as well as solid-porous compound fins. The effect of solid fins, porous fins, and compound fins are comprehensively determined. The result shows that as the thickness of porous fins increases in compound wavy channel, the heat transfer performance significantly increases up to 63.6% and pressure drop penalty decreases up to 55.32% as compared to the regular straight channel (solid fins) heat sinks. This is due to reduction of viscous shear stress at the place of fluid-porous interface and slip effect of fluids in the porous zone. Hence, the ability of the solid-porous compound wavy micro-channel heat sinks can effectively enhance the cooling performance of high-power electronic devices.