Miracle-dz/UniFAR-FTUs huggingface dataset:
Improved Variational Mode Decomposition and CNN for Intelligent Rotating Machinery Fault Diagnosis

This paper proposes an intelligent diagnosis method for rotating machinery faults based on improved variational mode decomposition (IVMD) and CNN to process the rotating machinery non-stationary signal. Firstly, to solve the problem of time-domain feature extraction for fault diagnosis, this paper proposes an improved variational mode decomposition method with automatic optimization of the number of modes. This method overcomes the problems of the traditional VMD method, in that each parameter is set by experience and is greatly influenced by subjective experience. Secondly, the decomposed signal components are analyzed by correlation, and then high correlated components with the original signal are selected to reconstruct the original signal. The continuous wavelet transform (CWT) is employed to extract the two-dimensional time–frequency domain feature map of the fault signal. Finally, the deep learning method is used to construct a convolutional neural network. After feature extraction, the two-dimensional time-frequency image is applied to the neural network to identify fault features. Experiments verify that the proposed method can adapt to rotating machinery faults in complex environments and has a high recognition rate.
Multimodal Attention-Aware Convolutional Neural Networks for Classification of Hyperspectral and LiDAR Data

The attention mechanism is one of the most influential ideas in the deep learning community, which has shown excellent efficiency in various computer vision tasks. Thus, this article proposes the convolution neural network method with the attention mechanism to enhance the feature extraction of light detection and ranging (LiDAR) data. Meanwhile, our elaborately designed cascaded block contains a short path architecture beneficial for multistage information exchange. With the full exploitation of elevation information from LiDAR data and efficient utilization of the spatial-spectral information underlying hyperspectral data, our method provides a novel solution for multimodal feature fusion. Experiments are conducted on the LiDAR and hyperspectral dataset provided by the 2013 IEEE GRSS Data Fusion Contest and multisource Trento dataset to demonstrate the effectiveness of the proposed method. The experimental results have shown the superior results of the proposed method on both LiDAR and multimodality remote sensing data in comparison with several popular baselines.
The Small Heat Shock Protein, HSPB1, Interacts with and Modulates the Physical Structure of Membranes

Small heat shock proteins (sHSPs) have been demonstrated to interact with lipids and modulate the physical state of membranes across species. Through these interactions, sHSPs contribute to the maintenance of membrane integrity. HSPB1 is a major sHSP in mammals, but its lipid interaction profile has so far been unexplored. In this study, we characterized the interaction between HSPB1 and phospholipids. HSPB1 not only associated with membranes via membrane-forming lipids, but also showed a strong affinity towards highly fluid membranes. It participated in the modulation of the physical properties of the interacting membranes by altering rotational and lateral lipid mobility. In addition, the in vivo expression of HSPB1 greatly affected the phase behavior of the plasma membrane under membrane fluidizing stress conditions. In light of our current findings, we propose a new function for HSPB1 as a membrane chaperone.
Indoor Secondary Pollutants Cannot Be Ignored: Third-Hand Smoke

Smoking has been recognized by the World Health Organization (WHO) as the fifth highest threat to humanity. Smoking, a leading disease promoter, is a major risk factor for non-communicable diseases (NCDs) such as cancer, cardiovascular disease, diabetes, and chronic respiratory diseases. NCDs account for 63% of all deaths worldwide. Passive smoking is also a health risk. Globally, more than a third of all people are regularly exposed to harmful smoke. Air pollution is a common global problem in which pollutants emitted into the atmosphere undergo a series of physical or chemical reactions to produce various oxidation products, which are often referred to as secondary pollutants. Secondary pollutants include ozone (O3), sulfur trioxide (SO3), nitrogen dioxide (NO2), and respirable particulate matter (PM). It is worth mentioning that third-hand smoke (THS), formed by the reaction of nicotine with second-hand smoke (SHS) caused by indoor O3 or nitrous acid (HONO), is a major indoor secondary pollutant that cannot be ignored. As a form of indoor air pollution that is relatively difficult to avoid, THS exists in any corner of the environment where smokers live. In this paper, we summarize the important research progress on the main components, detection, and toxicity of THS and look forward to future research directions. Scientific understanding of THS and its hazards will facilitate smoking bans in indoor and public places and raise public concern for how to prevent and remove THS.
Shape Estimation of a 3D Printed Soft Sensor Using Multi-Hypothesis Extended Kalman Filter

This study develops a multi-hypothesis extended Kalman filter (MH-EKF) for the online estimation of the bending angle of a 3D printed soft sensor attached to soft actuators. Despite the advantage of compliance and low interference, the 3D printed soft sensor is susceptible to the hysteresis property and nonlinear effects. Improving measurement accuracy for sensors with hysteresis is a common challenge. Current studies mainly apply complex models and highly nonlinear functions to characterize the hysteresis, requiring a complicated parameter identification process and challenging real-time applications. This study enhances the model simplicity and the real-time performance for the hysteresis characterization. We identify the hysteresis by combining multiple polynomial functions and improving the sensor estimation with the proposed MH-EKF. We examine the performance of the filter in the real-time closed-loop control system. Compared with the baseline methods, the proposed approach shows improvements in the estimation accuracy with low computational complexity.
Karakteristik Mi Berbasis Ubi Jalar dengan Substitusi Pati Sagu atau Pati Ubi Banggai

Sweet potato is a local food that can be used to support food diversification programs. It can be used as a raw material to produce a diverse type of food products, for example noodles. The addition of sago starch and banggai starch to sweet potato noodle dough is to improve the quality of noodles because these two starches are more prone to retrograde. The purpose of this study was to determine the effect of starch type, extrusion temperature, and water addition on the sweet potato noodles’ quality. The types of starch added were sago starch and banggai starch, with extrusion temperature settings, which were 90 and 95°C, and the water additions were 40 and 35%. Analysis was carried out on the characterization of the flour and physical properties of sweet potato noodles. The best noodle processing conditions were with the addition of 15% sago starch, 95°C extrusion temperature, and 40% water added. This formula produced sweet potato noodles with low brightness, having redness and yellowish colour. It had a hardness value above 3000 g, with higher elasticity and elongation than the other formulas, and also had lower adhesiveness and cooking loss value.
Differentiation of beef, buffalo, pork, and wild boar meats using colorimetric and digital image analysis coupled with multivariate data analysis

Beef price is relatively expensive, which makes this commodity vulnerable to be counterfeited. The development of rapid, cheap and robust analytical methods for meats authentication has therefore become increasingly important. In this study, colorimetric and digital image analysis methods were used to characterize and classify four types of meat (beef, buffalo, pork, wild boar) and two muscle types from each sample (Semitendinosus and Vastus lateralis). Multivariate data analysis (PCA and OPLS-DA) was used to observe classification pattern among species using different color parameters data obtained from meat chromameter and digital image measurement. The results showed that PCA and OPLS-DA successfully classified meat from different species and different muscle type based on color, both in chromameter and in image analysis. It was shown that pork had the highest lightness level, and was the most different among the four types of meat tested. Beef was predominated by yellowish color, while buffalo meat had the highest reddish color level. Semitendinosus and Vastus lateralis muscles had different color intensity where Vastus lateralis exhibited darker color intensity. This study showed that meat color analysis using chromameter and imaging techniques can be used as cheap and quick tools to discriminate meats form different species and different muscles type.
Hematopoietic Stem and Progenitor Cells (HSPCs) and Hematopoietic Microenvironment: Molecular and Bioinformatic Studies of the Zebrafish Models

Hematopoietic stem cells (HSCs) reside in a specialized microenvironment in a peculiar anatomic location which regulates the maintenance of stem cells and controls its functions. Recent scientific progress in experimental technologies have enabled the specific detection of epigenetic factors responsible for the maintenance and quiescence of the hematopoietic niche, which has improved our knowledge of regulatory mechanisms. The aberrant role of RNA-binding proteins and their impact on the disruption of stem cell biology have been reported by a number of recent studies. Despite recent modernization in hematopoietic microenvironment research avenues, our comprehension of the signaling mechanisms and interactive pathways responsible for integration of the hematopoietic niche is still limited. In the past few decades, zebrafish usage with regards to exploratory studies of the hematopoietic niche has expanded our knowledge for deeper understanding of novel cellular interactions. This review provides an update on the functional roles of different genetic and epigenetic factors and molecular signaling events at different sections of the hematopoietic microenvironment. The explorations of different molecular approaches and interventions of latest web-based tools being used are also outlined. This will help us to get more mechanistic insights and develop therapeutic options for the malignancies.
Character association and identification of trait specific introgression in restorer lines of sunflower (Helianthus annuus L.)

The study was carried out involving 40 MAGIC crosses of sunflower restorer lines along with 10 parental checks during rabi, 2020 grown in augmented block design with four blocks at MARS, UAS Raichur with an objective of assessing variation and character association for yield attributing traits. The highest estimates of GCV, PCV, heritability and genetic advance as per cent of mean were recorded for seed yield per plant followed by 100-seed weight. Seed yield per plant recorded a highly significant positive association with plant height and head diameter. Path analysis studies indicated plant height had the highest positive direct effect on seed yield per plant followed by oil content. Trait specific introgression studies revealed that R-127-1 × R Ⅱ , CSFI-99 × R Ⅲ and No-30 × R Ⅳ showed the highest percentage (87.5%) of introgression with the expression of seven out of eight traits.
ONE ON ONE.COM: A STRATEGY IN ENHANCING THE COMPUTER LITERACY OF EMPOWERMENT TECHNOLOGY STUDENTS

This action research study is conducted to determine the effect of one-on-one Tutorials with performance task sheets as an intervention for the low performance of students in Isabela School of Arts and Trades Senior High School taking up Empowerment Technology Subject. Thirty-seven students consented to participate in the study. It was found out that the intervention has a medium positive effect in improving the students' computer skills. Thus, the intervention is encouraging to be utilized in the teaching and learning process. The method and procedure of the research used is descriptive comparative design in this study wherein the data were generated from the pre and post-test results of the respondents in their Empowerment of Technology subject for the first semester 2019 – 2020, specifically in learning Competency Advanced Spreadsheet skills.
The relationship between intellectual capital and financial performance: a case study of Kurdistan Region of Iraq

Intellectual capital is primarily based on knowledge and useful information. Intellectual capital plays a vital role in creating value through a combination of tangible and intangible assets to improve organizational performance. This study provides further insight into the role of IC in organizational performance, especially financial performance through a descriptive analysis of the questionnaire that have distributed among employees of Halabja Co. in Kurdistan Region of Iraq (KRG)/ Sulaimani city. Findings from this study indicate that the relationships between intellectual capital and financial performance is significant for achieving the company’s competitive advantages and maximizing profits. The findings suggest that the performance of a company’s intellectual capital can explain profitability and productivity.
Impact of Morus alba L. on the expression of drug-metabolizing enzymes and transporters in Caco-2 cells

Morus alba ( MA) L. (mulberry) fruit has been consumed for a long time as a food and a source of vitamin C, anthocyanins, flavonoids, and alkaloids. The effects of MA fruit extract on drug-metabolizing genes and drug transporters were investigated in human colorectal adenocarcinoma cells. Cells treated with MA or its major bioactive constituents, rutin, and cyanidin-3-O-glucoside (C3G), were assessed for cell viability, production of reactive oxygen species (ROS), and alanine aminotransferase (ALT) and aspartate transaminase (AST) levels. The mRNA expression of target metabolic genes was determined using real-time polymerase chain reaction. Cell viability remained higher than 80%, and ROS levels were unchanged by all treatments. MA, C3G, and rutin did not alter the ALT and AST levels or expression of CYP2D6 and sulfotransferase 1A1 ( SULT1A1 ). However, MA, C3G, and rutin down-regulated the expression of CYP2C19 , CYP3A4 , uridine diphosphate-glucuronosyltransferase 1A6 ( UGT1A6 ), N -acetyltransferase 1, and organic anion transporting polypeptide 1B1 ( OATP1B1 ), and MA elevated the expression of CYP1A2 . In addition, MA induced CYP1A2 and CYP2C19 expression in combination with aspirin, caffeine, and simvastatin and upregulated expression of UGT1A6 and SULT1A1 in combination with paracetamol. Therefore, consumption of MA fruit or its supplements poses a risk for drug interactions via its modulation of cytochrome P450 and conjugation enzyme-associated metabolism and OATP1B1 -mediated drug transport.
Nature-Based Solutions (NBSs) to Mitigate Urban Heat Island (UHI) Effects in Canadian Cities

Canada is warming at double the rate of the global average caused in part to a fast-growing population and large land transformations, where urban surfaces contribute significantly to the urban heat island (UHI) phenomenon. The federal government released the strengthened climate plan in 2020, which emphasizes using nature-based solutions (NBSs) to combat the effects of UHI phenomenon. Here, the effects of two NBSs techniques are reviewed and analysed: increasing surface greenery/vegetation (ISG) and increasing surface reflectivity (ISR). Policymakers have the challenge of selecting appropriate NBSs to meet a wide range of objectives within the urban environment and Canadian-specific knowledge of how NBSs can perform at various scales is lacking. As such, this state-of-the-art review intends to provide a snapshot of the current understanding of the benefits and risks associated with the implantation of NBSs in urban spaces as well as a review of the current techniques used to model, and evaluate the potential effectiveness of UHI under evolving climate conditions. Thus, if NBSs are to be adopted to mitigate UHI effects and extreme summertime temperatures in Canadian municipalities, an integrated, comprehensive analysis of their contributions is needed. As such, developing methods to quantify and evaluate NBSs’ performance and tools for the effective implementation of NBSs are required.
MONEY SUPPLY, INFLATION AND ECONOMIC GROWTH IN BOSNIA AND HERZEGOVINA: AN EMPIRICAL ANALYSIS

The analysis of monetary variables and their impact on the economic growth rate has always been in the focus of economic research. In the broadest sense, economic theory distinguishes two basic views defined by the views of monetarists and Keynesians. Although the basic difference is reflected in the determination of price rigidity and money neutrality, specifics of modern economic systems shift the focus towards the positive influence of monetary on real variables. The aim of our research is to identify and quantify the impact of monetary variables on economic growth in Bosnia and Herzegovina. The research was conducted using data from the period 2000-2020. The paper starts with the hypothesis that money supply and inflation ultimately have a positive impact on the real economic growth in BiH. The money supply M2 and the annual inflation rate are taken as explanatory (monetary) variables in the research, while real growth is a dependent variable. The long-term relationship between monetary variables and real growth rates was tested, taking into account the specificity of the BiH monetary arrangement established in the form of a currency board. In order to prove the hypothesis, we applied econometric techniques such as VEC model, cointegration analysis, innovation analysis based on the impulse-responsive function, decomposition variance as well as a causality test. The research results showed the connection between the money supply and the inflation rate with the economic growth in BiH, the relation being positive and statistically significant in the long run. With this, we confirmed the initial hypothesis of the work.
Effects of dance on upper extremity activities in underserved adults

Purpose:This secondary analysis examined the immediate and maintaining effects of a 12‐week line‐dancing intervention on upper and lower extremity activities in underserved adults who receive care from a nurse‐managed clinic (NMC). Data sources:This one‐group, repeated measures, feasibility study consisted of 40 participants recruited from an urban apartment complex that housed a NMC. Of the 40 participants, 21 participants completed the 12‐week line‐dancing intervention. Physical function of the upper and lower extremities was measured with the Late Life Function and Disability Instrument at baseline, 12, and 18 weeks to determine the maintaining effects. Conclusions:Age ranged from 45 to 87 years (M = 63; SD = 7.8), body mass index (BMI) was 33.4 (SD = 7.8), 92% were female, and 75% were African American. At baseline, participants showed limitations in all aspects of physical function. Significant improvements in upper and lower extremity activities were noted at 12 weeks and maintained at 18 weeks. Implications for practice:Although line‐dancing mainly involves the lower body, there were significant improvements in upper extremity activities at 12 weeks, which were maintained at 18 weeks. The maintaining effects support line‐dancing as an intervention to improve upper and lower extremity activities needed for independent living. NMCs are important settings for health promotion interventions in underserved adults.
FINDING SYNONYMS IN A SYNTACTICALLY CONSTRAINED VECTOR SPACE MODEL

Distributional semantics in a vector space model plays an important role in natural language engineering. Apart from the word co-occurrences in plain context, the role of syntactic dependencies in deriving distributional semantics has not yet been fully investigated. We systematically investigate the salience of syntactic dependencies in accounting for distributional similarity. We first categorize the syntactic dependencies of words into four raw co-occurrence matrices that are respectively transformed into the second-order compressed matrices, then we systematically evaluate them in the TOEFL synonym test. Our results show that the semantic features of nouns mostly consist of their modifiers and their head nouns, whereas the semantic features of verbs are mostly explained by verb-modifiers and verb-objects. The syntactically conditioned contexts can interpret lexical semantics better than the unconditioned one.
The unwrapping of various understandings of statelessness in Latvian media discourse

There is a substantial literature in the tradition of constructivism and sociological new institutionalism that suggests the existence of shared EU norms. Yet, the issue of how EU norms are adopted and/or contested in EU member states remains underexamined. In the paper, we therefore study the public discourse on citizenship in Latvia and examine how the discourse relates to EU norms on citizenship, minority rights and in the broader sense human rights. The analysis takes its empirical starting point in the period after the Russian annexation of Crimea in 2014 and focuses on how the issue of statelessness was discussed in the Latvian online media. Looking at how the contested term (‘statelessness’) achieves different meanings in the Latvian discourse, and how the domestic actors try to reformulate the EU norms in question, we aim at a better understanding of the diffusion of norms within the context of a regional organization. The conclusion indicates that apart from the EU human rights norm, there are several different articulations of statelessness (i.e. othering, security and instrumental) that are present in the discourse. This has enabled Latvian governments to stress their commitment to human rights promotion, while simultaneously facing criticism regarding the country’s stateless inhabitants.
Roles of Fatty Acids in Microglial Polarization: Evidence from In Vitro and In Vivo Studies on Neurodegenerative Diseases

Microglial polarization to the M1 phenotype (classically activated) or the M2 phenotype (alternatively activated) is critical in determining the fate of immune responses in neurodegenerative diseases (NDs). M1 macrophages contribute to neurotoxicity, neuronal and synaptic damage, and oxidative stress and are the first line of defense, and M2 macrophages elicit an anti-inflammatory response to regulate neuroinflammation, clear cell debris, and promote neuroregeneration. Various studies have focused on the ability of natural compounds to promote microglial polarization from the M1 phenotype to the M2 phenotype in several diseases, including NDs. However, studies on the roles of fatty acids in microglial polarization and their implications in NDs are a rare find. Most of the studies support the role of polyunsaturated fatty acids (PUFAs) in microglial polarization using cell and animal models. Thus, we aimed to collect data and provide a narrative account of microglial types, markers, and studies pertaining to fatty acids, particularly PUFAs, on microglial polarization and their neuroprotective effects. The involvement of only PUFAs in the chosen topic necessitates more in-depth research into the role of unexplored fatty acids in microglial polarization and their mechanistic implications. The review also highlights limitations and future challenges.