Miracle-dz/UniFAR-FTUs huggingface dataset:
SentiLARE: Linguistic Knowledge Enhanced Language Representation for Sentiment Analysis

Most of the existing pre-trained language representation models neglect to consider the linguistic knowledge of texts, which can promote language understanding in NLP tasks. To benefit the downstream tasks in sentiment analysis, we propose a novel language representation model called SentiLARE, which introduces word-level linguistic knowledge including part-of-speech tag and sentiment polarity (inferred from SentiWordNet) into pre-trained models. We first propose a context-aware sentiment attention mechanism to acquire the sentiment polarity of each word with its part-of-speech tag by querying SentiWordNet. Then, we devise a new pre-training task called label-aware masked language model to construct knowledge-aware language representation. Experiments show that SentiLARE obtains new state-of-the-art performance on a variety of sentiment analysis tasks.
Running head: FEATURE STRENGTHS FOR ASSOCIATIVE RECOGNITION 1 Associative recognition without hippocampal associations

Whereas both human and animal lesion and human neuroimaging studies have implicated the hippocampus in memory for associations, some studies find preserved associative memory following hippocampal damage. Starting with a classic summed similarity model of item recognition, we can account for associative recognition without assuming a specific hippocampally-mediated, associative process. We add one key assumption: that one item can influence activation of another item’s features. Feature-strength patterns, evaluated for each probe item individually, are then diagnostic of whether an item was paired with one item versus another. We suggest that feature-level inference, without explicit storage of associations, may play a critical role in associative recognition tasks.
Elastic Dynamically Focused Beam Migration in Anisotropic Media

The current research on elastic wave migration can be divided into two categories: One is the elastic wave wave equation finite difference method proposed by Sun and McMechan (1986); The elastic wave reverse-time migration has high calculation accuracy, but it requires a high computational cost, and the accurate velocity. The other is the elastic wave Kirchhoff migration imaging method proposed by Kuo and Dai (1984); Elastic wave Kirchhoff migration imaging method has the advantages in efficiency. However, Kirchhoff elastic wave migration has difficulty in imaging shadow area, caustics area. To resolve the problems in elastic wave reverse time migration and elastic wave Kirchhoff migration, Protasov (2015) studied the true amplitude elastic wave multi-component Gaussian beam migration imaging method, which improved the imaging accuracy. The above researches are all based on the isotropic assumption and cannot solve the complex anisotropic elastic wave imaging problem. Therefore, Xu (2020) proposed an elastic wave Gaussian beam migration imaging method for anisotropic media, which effectively solves the problem of anisotropic elastic wave imaging. However, the imaging quality is affected by the initial beam width of the Gaussian beam, which makes it difficult to balance the imaging quality of the shallow layer and the deep layer.
Advancing the Science of Well- Being A Dissenting View on Measurement Recommendations

We question use of the term “well- being” to encompass notably distinct phenomena (objective indicators of socioeconomic status and health, subjective indicators of psychological experience) and dispute characterization of the field of well- being as relatively new. We also call for greater interplay between government surveys and multi- use cohort studies, both of which increasingly focus on well- being. The Midlife in the United States (MIDUS) study is presented as an example of how to negotiate distinct disciplinary priorities in broad- based studies of well- being and health, including those that take context seriously. We conclude with explanations for why we do not endorse any of the measurement recommendations (single- item measures, 4- 6 item measures, multi- item assessments) put forth in the preceding chapter, arguing that the ultra- short assessments ig-nore extensive prior science documenting the complex, multi- faceted nature of well- being, while the proposed longer assessment (Comprehensive Inventory of Thriving, CTI) suffers from multiple problems including a questionable conceptual foundation, inadequate evidence of validity and reliability, and highly redundant items. We appreciate the opportunity to respond to the “Current Recommendations the Selection of Measures for Well- Being” 17) by many this It is worthwhile to engage in debate and discussion how to best growing in assessing human well- We have multiple the our Building intersections between inequality, health, and well- being and psychosocial pathways to mitigating the consequences of socioeconomic adversity. reflects integrative work that spans psychological and health sciences.
Modeling viscosity of (Mg,Fe)O at lowermost mantle conditions

The viscosity of the lower mantle results from the rheological behavior of its two main constituent minerals, aluminous (Mg,Fe)SiO3 bridgmanite and (Mg,Fe)O ferropericlase. Understanding the transport properties of lower mantle aggregates is of primary importance in geophysics and it is a challenging task, due to the extreme time-varying conditions to which such aggregates are subjected. In particular, viscosity is a crucial transport property that can vary over several orders of magnitude. It thus has a first-order control on the structure and dynamics of the mantle. Here we focus on the creep behavior of (Mg,Fe)O at the bottom of the lower mantle, where the presence of thermo-chemical anomalies such as ultralow-velocity zones (ULVZ) may significantly alter the viscosity contrast characterizing this region. Two different iron concentrations of (Mg1–xFex)O are considered: one mirroring the average composition of ferropericlase throughout most of the lower mantle (x=0.20) and another representing a candidate magnesiowüstite component of ULVZs near the base of the mantle (x= 0.84). The investigated pressure-temperature conditions span from 120 GPa and 2800 K, corresponding to the average geotherm at this depth, to core-mantle boundary conditions of 135 GPa and 3800 K. In this study, dislocation creep of (Mg,Fe)O is investigated by dislocation dynamics (DD) simulations, a modeling tool which considers the collective motion and interactions of dislocations. To model their behavior, a 2.5 dimensional dislocation dynamics approach is employed. Within this method, both glide and climb mechanisms can be taken into account, and the interplay of these features results in a steady-state condition. This allows the retrieval of the creep strain rates at different temperatures, pressures, applied stresses and iron concentrations across the (Mg,Fe)O solid solution, providing information on the viscosity for these materials. A particularly low viscosity is obtained for magnesiowüstite with respect to ferropericlase, the difference being around 10 orders of magnitude. Thus, the final section of this work is devoted to the assessment of the dynamic implications of such a weak phase within ULVZs, in terms of the viscosity contrast with respect to the surrounding lowermost mantle.
Efficient Multilingual Text Classification for Indian Languages

India is one of the richest language hubs on the earth and is very diverse and multilingual. But apart from a few Indian languages, most of them are still considered to be resource poor. Since most of the NLP techniques either require linguistic knowledge that can only be developed by experts and native speakers of that language or they require a lot of labelled data which is again expensive to generate, the task of text classification becomes challenging for most of the Indian languages. The main objective of this paper is to see how one can benefit from the lexical similarity found in Indian languages in a multilingual scenario. Can a classification model trained on one Indian language be reused for other Indian languages? So, we performed zero-shot text classification via exploiting lexical similarity and we observed that our model performs best in those cases where the vocabulary overlap between the language datasets is maximum. Our experiments also confirm that a single multilingual model trained via exploiting language relatedness outperforms the baselines by significant margins.
Combinations of Linear Type Traits Affecting the Longevity in Hungarian Holstein-Friesian Cows

Simple Summary The selection for high-level milk production shortened the productive life of cows. In Hungary, the average number of lactations is only ca. 2.1. At the same time, the longevity, health status, milk production and reproduction were affected by the linear type traits, confirmed by several research studies. These studies, however, looked at the association of the linear type traits with longevity, using only one trait at a time. To take into account the connections between linear type traits, their combinations based on statistical analyses were considered. Identification of the risk ratio of various trait combinations could support corrective mating and bull selection. Abstract Several research studies confirm the association of the linear type traits with longevity, but only with one trait at a time. The aim of our study was to analyse the influence of combinations for linear type traits on longevity in the Hungarian Holstein-Friesian cows. Data were provided by four herds; the filtered dataset consisted of 17,717 cows. From the 14 available linear type traits, the most important combinations were identified based on principal components and cluster analysis. From the six identified combinations, only three (chest width-body depth, fore udder attachment-udder depth, angularity-rear udder height) proved to have a significant effect on longevity. A wide chest and deep body caused a high-risk ratio of culling. The lowest risk ratio was observed with cows having intermediate chest width and intermediate body depth. Very angular cows having low rear udder height were at the highest risk of culling. The lowest culling risk was found in cows with a lack of angularity and high rear udder height. Weak and loose fore udder along with deep udder had increased culling risk. Strong and tight fore udder subclasses were the most favourable as their risk ratios decreased towards the shallowing of udder depth.
Wise Information Technology of Med: Human Pose Recognition in Elderly Care

The growing problem of aging has led to a social concern on how to take care of the elderly living alone. Many traditional methods based on visual cameras have been used in elder monitoring. However, these methods are difficult to be applied in daily life, limited by high storage space with the camera, low-speed information processing, sensitivity to lighting, the blind area in vision, and the possibility of revealing privacy. Therefore, wise information technology of the Med System based on the micro-Doppler effect and Ultra Wide Band (UWB) radar for human pose recognition in the elderly living alone is proposed to effectively identify and classify the human poses in static and moving conditions. In recognition processing, an improved PCA-LSTM approach is proposed by combing with the Principal Component Analysis (PCA) and Long Short Term Memory (LSTM) to integrate the micro-Doppler features and time sequence of the human body to classify and recognize the human postures. Moreover, the classification accuracy with different kernel functions in the Support Vector Machine (SVM) is also studied. In the real experiment, there are two healthy men and one woman (22–26 years old) selected to imitate the movements of the elderly and slowly perform five postures (from sitting to standing, from standing to sitting, walking in place, falling and boxing). The experimental results show that the resolution of the entire system for the five actions reaches 99.1% in the case of using Gaussian kernel function, so the proposed method is effective and the Gaussian kernel function is suitable for human pose recognition.
ITS Sequence Analysis of Ophidascaris Baylisi from Burmese Pythons

Members of genus Ophidascaris are common parasitic roundworms in snakes that cause gastric granulomas, adenocarcinomas, intestinal obstruction, death, and serious economic losses in snakes and their products. To identify molecular marker of Ophidascaris baylisi from the Burmese python (Python molurus bivittatus), we amplified internal transcribed spacer (ITS) sequence from this roundworm and analyzed their homology and phylogeny. The amplified ITS sequence length was 1140 bp, comprising the complete ITS1, 5.8S, and ITS2 sequences and a partial 28S sequence. The ITS1+ sequence was homologous (85.8% homology) to the related species Ophidascaris robertsi. The phylogenetic tree revealed a close genetic distance between O. baylisi and O. robertsi, which formed a separate branch within family Ascaridae clade. The results indicated that the identified ITS sequence could be a good molecular marker for further study on the molecular classification and genetic variation of Ophidascaris species.
Review: Privacy-preservation in the context of Natural Language Processing

Data privacy is one of the highly discussed issues in recent years as we encounter data breaches and privacy scandals often. This raises a lot of concerns about the ways the data is acquired and the potential information leaks. There are opportunities where the privacy of the data could be violated when used in Artificial Intelligent (AI) models. A considerable portion of user-contributed data is in natural language, and in the past few years, many researchers have proposed NLP-based methods to address these data privacy challenges. To the best of our knowledge, this is the first interdisciplinary review discussing privacy preservation in the context of NLP. In this paper, we present a comprehensive review of previous research conducted to gather techniques and challenges of building and testing privacy-preserving systems in the context of Natural Language Processing (NLP). We group the different works under four categories: 1) Data privacy in the medical domain, 2) Privacy preservation in the technology domain, 3) Analysis of privacy policies, and 4) Privacy leaks detection in the text representation. This review compares the contributions and pitfalls of the various privacy violation detection and prevention works done using NLP techniques to help guide a path ahead.
Cardiometabolic and Anthropometric Outcomes of Intermittent Fasting among Overweight and Obese Civil Servants in Malaysia (CAIFA): Study Protocol for A Non-Randomized Controlled Trial (Preprint)

BACKGROUND Overweight and obesity among adults is a growing global public health threat and an essential risk factor for various non-communicable diseases. Although intermittent fasting is a generally new dietary approach to weight management that has been increasingly practised worldwide, the effectiveness of two-days per week dry fasting is still unclear. OBJECTIVE This study aimed to determine the cardiometabolic, anthropometric, dietary intake and quality of life changes among overweight and obese civil servants following combined Intermittent Fasting and Healthy Plate (IFHP) and Healthy Plate (HP), and to explore the participants’ experience. METHODS We designed a mixed-method quasi-experimental study that evaluates the effectiveness of IFHP and HP methods among overweight and obese adults. A total of 177 participants were recruited in this study, of which 91 were allocated in the IFHP group and 86 in the HP group. The intervention comprised two phases; supervised (12 weeks) and unsupervised (12 weeks). The data collection was conducted during baseline, after the supervised phase (at week 12), and after the unsupervised phase (at week 24). For each participant, serum and whole blood were collected for analysis. Data on socio-demographic, quality of life, physical activity and dietary intake were also obtained using questionnaires during data collection. RESULTS The majority of the participants were females (n=147, 83.7%) and Malays (n=141, 79.6%). The expected outcomes of this study are changes in body weight, body compositions, quality of life, physical activity, dietary intake and cardiometabolic parameters such as fasting blood glucose, 2-hour post prandial blood glucose, HbA1C, fasting insulin and lipid profile. CONCLUSIONS The CAIFA study is a mixed-method study to evaluate the effectiveness of intermittent fasting on cardiometabolic and anthropometric parameters and to explore participants’ experience throughout the study. CLINICALTRIAL ClinicalTrials.gov NCT05034653
Effects of Lower Temperature on Expression and Biochemical Characteristics of HCV NS3 Antigen Recombinant Protein

The nonstructural antigen protein 3 of the hepatitis C virus (HCV NS3), commonly-used for HCV ELISA diagnosis, possesses protease and helicase activities. To prevent auto-degradation, a truncated NS3 protein was designed by removing the protease domain. Firstly, it was overexpressed in E. coli by IPTG induction under two different temperatures (25 and 37 °C), and purified using affinity chromatography to attain homogeneity above 90%. The molecular mass of purified protein was determined to be approx. 55 kDa. While lowering the temperature from 37 to 25 °C, the yield of the soluble fraction of HCV NS3 was increased from 4.15 to 11.1 mgL−1 culture, which also improved the antigenic activity and specificity. The protein stability was investigated after long-term storage (for 6 months at −20 °C) revealed no loss of activity, specificity, or antigenic efficacy. A thermal stability study on both freshly produced and stored HCV NS3 fractions at both temperatures showed that the unfolding curve profile properly obey the three-state unfolding mechanism. In the first transition phase, the midpoints of the thermal denaturation of fresh NS3 produced at 37 °C and 25 °C, and that produced after long-term storage at 37 °C and 25 °C, were 59.7 °C, 59.1 °C, 55.5 °C, and 57.8 °C, respectively. Microplates coated with the fresh NS3 produced at 25 °C or at 37 °C that were used for the HCV ELISA test and the diagnosis outcome were compared with two commercial kits—Abbott HCV EIA 2.0 and Ortho HCV EIA 3.0. Results indicated that the specificity of the HCV NS3 produced fresh at 25 °C was higher than that of the fresh one at 37 °C, hence showing potential for application in HCV ELISA diagnosis.
A Hybrid Model to Alleviate Unemployment and Poverty in South Africa

Poverty and unemployment are considered social threats in South Africa as the rate keeps on escalating while few measures are implemented to alleviate the trend. This study devised a hybrid model to reduce the rate of poverty and unemployment in South Africa. The Human Capital Theory formed the theoretical base of this study, which explained the need for the government to invest in education to improve the chances of gaining employment to reduce poverty. The study adopted a quantitative approach and data were collected from only secondary sources. Major findings disclosed that the poverty rate in South Africa is at 49.2% while 64.2% of South African blacks remain poor. The study revealed that the unemployment rate is at 30.1% in the first quarter of 2020 while provinces such as Eastern Cape (40.5%) and the Free State (38.4%) have the highest share of unemployment in the country. The meta-analysis conducted revealed that improvement is needed in areas such as legislation and labour laws, entrepreneurial development, youth development policies, common vision and leadership, sectoral development, business climate, acquisition of skills and education, engagement management, and strategic management. This is in an endeavour to reduce poverty and unemployment rate in South Africa.
Applying Self-Determination Theory to Education: Regulations Types, Psychological Needs, and Autonomy Supporting Behaviors

The self-determination theory (SDT) has been used to understand students’ motivation at school in general as well as in various school subjects. This literature review conducted on a number of SDT studies showed that (1) autonomous types of extrinsic motivation as well as intrinsic motivation leads to positive consequences for students; (2) the types of goals and the regulation behind them are also important to predict school outcomes; (3) when the psychological needs for competence, autonomy and relatedness are satisfied this leads to autonomous motivation or autonomous goals endorsement; (4) autonomy supportive practices by parents and teachers are important catalyzers of needs’ fulfillment; (5) intervention programs designed for teachers or parents focusing on these psychological needs usually lead to greater autonomous extrinsic motivation and intrinsic motivation and better adjustment outcomes. The implication of this theory for school psychologists is underscored as well as its implications for the practice of teaching.
Magnetic Coupler Optimization for Inductive Power Transfer System of Unmanned Aerial Vehicles

Unmanned aerial vehicles (UAVs) have been widely used in military and civilian applications. However, the insufficient cruising range restricts the development of UAVs due to the limitation of their battery. Inductive power transfer (IPT) is an effective way to charge the battery and solve this problem. Magnetic coupler is a key component of the IPT system, which greatly affects the power transfer and efficiency of the IPT. This paper proposes a new magnetic coupler with vertical spiral coils and ferrite PQI cores for the IPT system of UAVs, which can enhance the magnetic coupling and improve the performance of the IPT system. Finite element simulations are used to investigate the magnetic field distribution and coupling capability of the proposed magnetic coupler. In addition, an experimental platform is built to prove the validity of the IPT system using the proposed magnetic coupler. The results show that the coupling coefficient can reach 0.98, and the system transfer efficiency is 89.27% with an output power of 93 W. The IPT system also has a perfect misalignment tolerance and can achieve a stable output power.
Non-specific effects of a CINNAMATE-4-HYDROXYLASE inhibitor on auxin homeostasis

Chemical inhibitors are often implemented for the functional characterization of genes to overcome the limitations associated with genetic approaches. Although being a powerful tool, off-target effects of these inhibitors are easily overlooked in a complex biological setting. Here we illustrate the implications of such secondary effects by focusing on piperonylic acid (PA), an inhibitor of CINNAMATE-4-HYDROXYLASE (C4H) that is often used to investigate the involvement of lignin during plant growth and development. When supplied to plants, we found that PA is recognized as a substrate by GRETCHEN HAGEN 3.6 (GH3.6), an amido synthetase involved in the formation of the auxin catabolite indole-3-acetic acid (IAA)-Asp. By competing for the same enzyme, PA interferes with auxin conjugation, resulting in an increase in cellular auxin concentrations. These increased auxin levels likely further contribute to an increase in adventitious rooting previously observed upon PA-treatment. Despite the focus on GH3.6 in this report, PA is conjugated by an array of enzymes and their subsequent reduced activity on native substrates could potentially affect a whole set of physiological processes in the plant. We conclude that surrogate occupation of the endogenous conjugation machinery in the plant by exogenous compounds is likely a more general phenomenon that is rarely considered in pharmacological studies. Our results hereby provide an important basis for future reference in studies using chemical inhibitors.