Miracle-dz/UniFAR-FTUs huggingface dataset:
Biological sensitivity to context as a dyadic construct: An investigation of child–parent RSA synchrony among low-SES youth

Abstract Parenting behaviors are significantly linked to youths’ behavioral adjustment, an association that is moderated by youths’ and parents’ self-regulation. The biological sensitivity to context theory suggests that respiratory sinus arrhythmia (RSA) indexes youths’ varying susceptibility to rearing contexts. However, self-regulation in the family context is increasingly viewed as a process of “coregulation” that is biologically embedded and involves dynamic Parent×Child interactions. No research thus far has examined physiological synchrony as a dyadic biological context that may moderate associations between parenting behaviors and preadolescent adjustment. Using a two-wave sample of 101 low-socioeconomic status (SES) families (children and caretakers; mean age 10.28 years), we employed multilevel modeling to examine dyadic coregulation during a conflict task, indicated by RSA synchrony, as a moderator of the linkages between observed parenting behaviors and preadolescents’ internalizing and externalizing problems. Results showed that high dyadic RSA synchrony resulted in a multiplicative association between parenting and youth adjustment. High dyadic synchrony intensified the relations between parenting behaviors and youth behavior problems, such that in the context of high dyadic synchrony, positive and negative parenting behaviors were associated with decreased and increased behavioral problems, respectively. Parent–child dyadic RSA synchrony is discussed as a potential biomarker of biological sensitivity in youth.
A Novel Emotion-Aware Hybrid Music Recommendation Method Using Deep Neural Network

Emotion-aware music recommendations has gained increasing attention in recent years, as music comes with the ability to regulate human emotions. Exploiting emotional information has the potential to improve recommendation performances. However, conventional studies identified emotion as discrete representations, and could not predict users’ emotional states at time points when no user activity data exists, let alone the awareness of the influences posed by social events. In this study, we proposed an emotion-aware music recommendation method using deep neural networks (emoMR). We modeled a representation of music emotion using low-level audio features and music metadata, model the users’ emotion states using an artificial emotion generation model with endogenous factors exogenous factors capable of expressing the influences posed by events on emotions. The two models were trained using a designed deep neural network architecture (emoDNN) to predict the music emotions for the music and the music emotion preferences for the users in a continuous form. Based on the models, we proposed a hybrid approach of combining content-based and collaborative filtering for generating emotion-aware music recommendations. Experiment results show that emoMR performs better in the metrics of Precision, Recall, F1, and HitRate than the other baseline algorithms. We also tested the performance of emoMR on two major events (the death of Yuan Longping and the Coronavirus Disease 2019 (COVID-19) cases in Zhejiang). Results show that emoMR takes advantage of event information and outperforms other baseline algorithms.
Pemanfaatan Kulit Ubi Jalar Ungu Dengan Lama Perendaman Bahan Sebagai Indikator Asam Basa Alternatif Dan Variasi Pelarut Yang Berbeda

Acid-base indicator is an important tool in science learning practice of middle school. Ingredients from plants containing anthocyanin have the potential for the making of natural base acid indicators. Purple sweet potato rind higher anthocyanin content than the meat, so it can be used as a natural base acid indicator. This research aim to know purple sweet potato rind extract can be utilized as material of making natural acid acid indicator with solvent variations and long submersion of material. This study used a complete randomized design, with two treatment factors which is different solvent variations and long submersion of the material. Variations of solvent used 96% ethanol, 96% ethanol + vinegar and ethanol 96% + 3% citric acid and long submersion of the material for 23 hours, 24 hours and 25 hours. The parameters of this study include the color change of acid base indicator paper from purple sweet potato rind extract after submersion in acidic and alkaline solutions. The results showed that the acid base indicator paper from the purple sweet potato rind extract experienced a red brick change in acidic and green tea solution in the alkaline solution. The length submersion of the material did not give a significant effect on the color of the indicator paper.
Migrant Economic Behaviors: Causal Effects of Health Education on Saving Rates, Social Medical Insurance, and House Purchasing

BackgroundsHealth China as the essentials policy with advancing Global Health, contributing to decline the inequality between rural and urban health education, and recovering the domestic markets after Coronavirus. The goal of this study is to evaluate the economic returns on health educations in a developing country. MethodsWe combine life cycle mechanisms and safety beliefs to evaluate continuous values of health education from 720,900 migrants’ economic behaviors through the ERM model, average treatment effects, and heterogeneous treatment effects robust empirically approach.ResultsWe find that health education positively affects participation in social medical insurance and house purchasing. In contrast, the relationship between health education and saving rates is an inverted ‘U’ shape. Heterogeneous treatment effect empirically robust account for heterogeneity in the previous generation and young generation; urban citizenship and rural citizenship continuous effects of health education. ConclusionThe finding suggests that health education stimulates immigrant consumption behaviors; however, extra health education is not a wise policy. Rural-urban citizenship acquisition bias is a significant factor of health education effects differential.JEL CLASSIFICATIONI15; D14; R23
Increased PINK1 Confers a Neuroprotective Role After Glutamate Excitotoxicity in Neuronal Cells

Background: Ischemic insults often leads to mitochondrial dysfunction and neuronal injury. The neuronal damage induced by ischemia can be partly attributed to glutamate excitotoxicity. Previous studies have indicated that PINK1 plays a neuroprotective role against ischemic brain injury via regulating mitochondrial integrity and function. However, there are few reports elucidating the expression changes and effect of PINK1 on neuronal survival in glutamate excitotoxicity model.Methods: We utilized HT22 cells and primary cortical neurons to establish glutamate excitotoxicity neuronal model. Cell Counting Kit-8 was used to investigate the effects of different concentrations of glutamate on neuronal activity; RT-PCR assay was used to investigate PINK1 transcription level following glutamate excitotoxicity; Western-blot and immunofluorescence assays were used to evaluate PINK1 translation level after glutamate injury. Moreover, we established HT22 cell stable transformants by lentiviral transfection to determine the role of PINK1 on neuronal damages in glutamate excitotoxicity.Results: Different concentrations of glutamate inhibited the cell viability of HT22 line and primary cortical neurons. Following glutamate treatment at different times, the mRNA level, protein level and cellular fluorescence intensity of PINK1 firstly increased and then decreased. In addition, cells with low PINK1 expression could reinforce the inhibitory effect of glutamate on neuronal activity compared with normal cells, while high PINK1 expression showed a protective effect on neurons.Conclusion: PINK1 may play a neuroprotective role in glutamate induced neuronal excitotoxicity.
Antioxidant and Antimicrobial Effects of Lemongrass (Cymbopogon citrates) Oil on the Quality Characteristics of Camel Burger “Camburger” under Refrigerated Storage

Lipid oxidation and growth of undesirable microorganisms in food products result in the development of spoilage, rancidity and deterioration, rendering such products unacceptable for human consumption (Bozin et al., 2007). In an effort to retard this process, several synthetic food additives have been widely used in the meat industry. However, the application of synthetic antioxidants has been recently restricted due to the toxicological effects of synthetic antioxidants and there is suspicion that they are carcinogenic. Consumers have shown preference for the use of natural antioxidants (Byrd, 2001; Johnston et al., 2005). Natural plants can inhibit oxidative rancidity and delay the development of off-flavor in some products.
Toward Data-Model-Agnostic Autonomous Machine-Generated Data Labeling and Annotation Platform: COVID-19 Autoannotation Use Case

Quick, early, and precise detection is important for diagnosis to control the spread of COVID-19 infection. Artificial Intelligence (AI) technology could certainly be used as a modulating tool to ease the detection, and help with the preventive steps further. Convolutional neural networks (CNNs) have achieved state-of-the-art performance in many visual recognition tasks. Nevertheless, most of these state-of-the-art networks highly rely on the availability of a high amount of labeled data, being an essential step in supervised machine learning tasks. Conventionally, this manual, mundane, and time-consuming process of annotating images is done by humans. Learning to localize or detect COVID-19 infection masks in our specific case study typically requires the collection of CT scan data that has been labeled with bounding boxes or similar annotations, which generally is limited. A technique that could perform such learning with much less annotations, and transfer the learned proposals that are algorithm-driven to generate more synthetic annotated samples would be helpful & quite valuable. We present such a technique inspired by weakly trained mask region based convolutional neural networks (R-CNN) architecture for localization, in which the number of images with their pixel-level masks can be a small proportion of the total dataset, and then further improvise CNNs by inversely generating dense annotations on-the-go using an algorithmic-based computational approach. We focus on alleviating the bottleneck associated with deep learning models needing annotated data for training in an intuitive reverse engineering fashion through this work. Our proposed solution can certainly provide the prospect of automated labeling on-the-fly, thereby reducing much of the manual work. As a result, one can quickly train a precise COVID-19 infection detector with the leverage of autonomous frame-by-frame machine generated annotations. The model achieved mean precision accuracy (%) of 0.99, 0.931, and 0.8 for train, validation, and test set, respectively. The results demonstrate that the proposed method can be adopted in a clinical setting for assisting radiologists, and also our fully autonomous approach can be generalized to any detection/recognition tasks at ease.
p-Chloroacetophenone: A study of enolization kinetics

ABSTRACT The reaction rate of enolization of p-chloroacetophenone has been studied in the presence of amino acids, namely, β-alanine, DL-alanine, L-alanine, and glycine. Maximum reaction rate was observed in the case of β-alanine at 22M concentration. The effects of parameters such as effect of ketone concentration, effect of dielectric constant, effect of catalysts, etc., have been found to exert a significant effect on the reaction rate. The effect of temperature was studied in the range of 313–328 K, and several thermodynamic parameters such as entropy (ΔS≠), enthalpy (ΔH≠), energy of activation (ΔEa), and Gibbs free energy (ΔF≠) were found to be −10.32 e.u., 17.87 cal mol−1, 19.24 kcal mol−1, and 21.20 cal mol−1, respectively. The reaction rate increased from 1.9 to 5.8 min−1 on increasing the percentage of dimethylformamide from 10 to 50% (v/v).
‘Better than watching daytime TV': sickness presenteeism in UK academics

ABSTRACT Sickness presenteeism refers to the practice of continuing to work during illness. Although not always damaging, working while sick can impair employees' wellbeing and professional functioning. As the causes of presenteeism are multi-faceted, insight into the experiences of different occupational groups is needed. This study examines the prevalence of sickness presenteeism among academic employees, the factors that encourage such behaviour and the implications for wellbeing and performance. Qualitative data obtained from 5209 academics working in UK universities were subjected to thematic content analysis. Most respondents (90%) reported working while sick at least sometimes, with more than half (52%) doing so often or always. Seven interlinked themes were identified: workload pressure; non-negotiable deadlines; lack of cover; culture and working conditions; being professional, working strategically and personal choice. Although presenteeism among academics can be therapeutic and functional, the findings suggest it has serious implications for their wellbeing and performance.
Antimicrobial Agents for Textiles: Types, Mechanisms and Analysis Standards

The large surface area, and ability to retain moisture of textile structures enable microorganisms’ growth, which causes a range of undesirable effects, not only on the textile itself, but also on the user. Moreover, textiles used in health care environments are required to possess antimicrobial property to minimize spread of pathogenic infection. Anti-microbial property can be imparted via chemical finishing with an antimicrobial agent. Currently the use of antimicrobial agents includes metal compounds (notably copper and silver particle), chitosan, halogenated phenols “triclosan”, quaternary ammonium compounds, antibiotics (a class of antimicrobials produced from microorganisms that act against one another), and N-halamines. The possibility of bacterial resistance limits antibiotic use to specific medical applications, and triclosan is known for being dangerous to the environment and is currently under scrutiny for possible endocrine disrupting to human being. Although quaternary ammonium compounds are stable and easily manufactured, microbial resistance is also a concern. Quaternary ammonium compounds (QACs), Polyhexamethylene Biguanide (PHMB), chitosan and N-halamines are listed under bound or non-leaching type antimicrobials. The bulk of current chapter focuses on the different family of antimicrobial agents used for textiles and their mechanisms.
Unveiling Island Tourism in Cape Verde through Online Reviews

This paper is focused on research addressing a large quantity of data extracted from online reviews written by tourists visiting islands. These were extracted from TripAdvisor regarding island tourist destinations since there is a gap in the scientific literature using this approach on island tourism. The Islands of the Sun, Boa Vista and Sal, of Cape Verde, a Small Island Developing State (SIDS), were the targets of this investigation. After applying text mining to a large dataset, results are discussed, including from the perspectives of hotels, restaurants, and tourist attractions. For example, the beach is the main tourist attraction in both islands, but whereas in Boa Vista, tours on quad bikes constitute a major tourist activity, its equivalent in Sal is actually diving. The location of hotels near the beach is a big plus for tourists who also emphasize their human interaction with staff members in both hotels and restaurants.
Evolution of New Guar Variety “BR-21” With High Yield Potential through Pure-Line Selection

Guar is a drought tolerant, summer annual legume, well adapted to arid and semi-arid regions of Pakistan. Guar gum is important product which is obtained from guar seed and has worldwide uses in different industries. Therefore, there is a dire need of evolution of new high yielding, short duration and early maturing varieties of guar. Keeping in view the above facts, Agricultural Research Station, Bahawalpur is conducting research to develop new varieties. The present newly developed variety BR-21 (strain name S-5823) is high yielding, short duration, non-hairy with a wider range of adaptability. Yield data (grain yield) were collected from the guar varietal performance trials conducted over eight consecutive years (2011-2020). This strain performed better when evaluated/tested in 7 different yield performance trails including commercial variety as a check from year 2013-2018. The BR-21 also performed excellent in the agronomic trials (Sowing date, fertilizer requirement, row spacing, and irrigation levels) compared to check variety in different years of study. Finally, it is concluded that BR-21 is a non-hairy and very easy to harvest than previous guar varieties. It contains high gum contents (34.9%) than check variety. It is high yielder, early maturing and requires very low inputs. It is comparatively resistant to insect pests and diseases. It is short duration variety, therefore, wheat, raya, chickpea and other Rabi crops can be sown well in time.
Sağlık Okuryazarlığının Diyet Kalitesine Etkisi

Amaç: Bu kesitsel araştırma, üniversite öğrencilerinin sağlık okuryazarlığı düzeyinin diyet kalitesine etkisini belirlemek amacıyla yürütülmüştür. Bireyler ve yöntem: Çalışmaya Erciyes Üniversitesi Sağlık Bilimleri Fakültesi Beslenme ve Diyetetik Bölümü (BD), Turizm Fakültesi (TF) ve Spor Bilimleri Fakültesindeki (SB) 580 gönüllü öğrenci dâhil edilmiştir. Sağlık okuryazarlığı “En Yeni Yaşamsal Bulgu Testiyle (NVS)”, diyet kalitesi “Sağlıklı Yeme İndeksi-2015 (SYİ-2105)”le saptanmıştır. Veriler yüz yüze görüşme yöntemiyle toplanmış, antropometrik ölçümler yapılmıştır. p<0.05 değeri istatistiksel olarak anlamlı kabul edilmiştir. Bulgular: Yeterli sağlık okuryazarlığı olanların oranı sırasıyla en yüksek BD (%99.2), daha sonra SB (%53.2), en az TF (%31.2) öğrencilerinindir (p<0.001). Sağlık okuryazarlığı düzeyinin TF (2.59±1.97) ve SB (3.48±1.87) öğrencilerinin sınırlı, BD öğrencilerinin (5.55±0.68) yeterli olduğu saptanmıştır. Sağlık okuryazarlığı düzeyi yeterli olan öğrencilerin SYİ-2015 puanı (56.30±9.73), sınırlı (54.26±9.61) ve yüksek olasılıklı sınırlı (53.77±9.52) olanlardan anlamlı olarak daha yüksektir (p=0.037) Sağlık okuryazarlığı düzeyi ile diyet kalitesi arasında pozitif yönlü zayıf anlamlı korelasyon saptanmıştır (rho=0.123, p=0.003). Bireylerin bel çevresi ve bel/kalça oranıyla NVS puanı, bel/kalça oranıyla SYİ-2015 puanı arasında negatif yönlü zayıf korelasyon bulunmuştur (p<0.05). Sonuç: Sağlık okuryazarlığı düzeyindeki artış diyetin kalitesini olumlu yönde etkilemekte, daha sağlıklı beslenme alışkanlığına sahip olunduğunu göstermektedir. BD öğrencilerinin sağlık okuryazarlığı düzeyinin ve diyet kalitelerinin SB ve TF öğrencilerine göre yüksek olması beklenen bir sonuçtur. Ancak BD öğrencileri için de SYİ-2015 puanı beklenenin altındadır ve diyetlerinin kalitelilerinin iyileştirilmesi gerekmektedir. Beslenmeyle yakından ilişkili olan TF ve SB fakültelerinin eğitim müfredatlarındaki beslenme ile ilgili derslerin sayısı ve saatlerinin artırılması önerilir.
Mineralized-tissue histology reveals protracted life history in the Pliocene three-toed horse from Langebaanweg (South Africa)

We studied the bone and dental histology of the tri-dactyl equid Eurygnathohippus hooijeri, one of the most iconic mammals found at the world-renowned Pliocene site of Langebaanweg, South Africa, to reconstruct important features of its life history. Our results show that key life-history events, such as weaning, skeletal maturity and reproductive maturity, occurred later in this African hipparionine compared with European three-toed equids and several extant Equus. Its late life-history schedule agrees with an ecological context of low adult extrinsic mortality and low juvenile survival rates. We also observed high rates of bone growth in Eu. hooijeri that were probably achieved through a high-quality diet and plentiful available water. Our research highlights the significance of combining bone and dental histology in the same taxon to obtain refined palaeobiological information about extinct vertebrates.
Finding Needles in a Haystack: Recognizing Emotions Just From Your Heart

Emotion plays an important role in human cognition and behavior. How to recognize emotions based on physiological signals has attracted increasing research interests worldwide up to date. Both traditional eastern medicine and modern western medicine have confirmed the existence of relationship between human emotionality and heart activity. However, in practice, emotion recognition only using Electrocardiogram (ECG) signals seems quite challenging, not only due to the severe noise interferences and the serious data variations, but also because of the ambiguous relationship between emotional states and ECG data. Such difficulty can even be compared to finding needles in a haystack. As an innovative endeavor to deal with the issue of only-ECG-based emotion recognition, this paper has proposed a novel solution from the perspective of weak signal classification. The proposed solution extracts the static-dynamic representation under the principle of Yin-Yang balance from the heartbeat data, and then utilizes the set-based collaborative measurement upon the thought of data coopetition to classify these features for recognizing emotions. Experimental results have demonstrated the effectiveness, efficiency and adaptiveness of the solution for uncovering the potential relationship between emotions and ECG. Thus, this proposal has also illuminated a promising research direction for the general problem of weak signal classification.
Ability of weakly supervised learning to detect acute ischemic stroke and hemorrhagic infarction lesions with diffusion-weighted imaging.

Background Gradient-recalled echo (GRE) sequence is time-consuming and not routinely performed. Herein, we aimed to investigate the ability of weakly supervised learning to identify acute ischemic stroke (AIS) and concurrent hemorrhagic infarction based on diffusion-weighted imaging (DWI). Methods First, we proposed spatially locating small stroke lesions in different positions and hemorrhagic infarction lesions by residual neural and visual geometry group networks using weakly supervised learning. Next, we compared the sensitivity and specificity for identifying automatically concurrent hemorrhagic infarction in stroke patients with the sensitivity and specificity of human readings of diffusion and b0 images to evaluate the performance of the weakly supervised methods. Also, the labeling time of the weakly supervised approach was compared with that of the fully supervised approach. Results Data from a total of 1,027 patients were analyzed. The residual neural network displayed a higher sensitivity than did the visual geometry group network in spatially locating the small stroke and hemorrhagic infarction lesions. The residual neural network had significantly greater patient-level sensitivity than did the human readers (98.4% versus 86.2%, P=0.008) in identifying concurrent hemorrhagic infarction with GRE as the reference standard; however, their specificities were comparable (95.4% versus 96.9%, P>0.99). Weak labeling of lesions required significantly less time than did full labeling of lesions (2.667 versus 10.115 minutes, P<0.001). Conclusions Weakly supervised learning was able to spatially locate small stroke lesions in different positions and showed more sensitivity than did human reading in identifying concurrent hemorrhagic infarction based on DWI. The proposed approach can reduce the labeling workload.