Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on an Anomaly Detection Method for Physical Condition Change of Elderly People in Care Facilities

Currently, the shortage of care workers for the elderly has become a big problem, and more streamlined care operations are needed. In care facilities, care workers are required to use their subjective experience to detect anomalies in physical condition of care receivers, including serious or insignificant deterioration or behavioral and psychological symptoms of dementia, which can decrease the work efficiency. Therefore, we aim to create a model using objective data for detecting anomalies in physical condition. In this study, data from 13 subjects in a care facility were collected, and isolation forest models were constructed for each subject. The subject ʼ s anomalies in physical condition were documented in a care record by a nurse and used as reference for model evaluation. Recall and specificity were used to evaluate the model, expressed as the per-centage of detection success for abnormal or normal conditions. Data collected for 1 to 60 days were used to train the isolation models, and the relationship between the amount of training data and model performance was simulated. Heart rate, respiratory rate, and time of getting out of bed were collected from a sensor placed on the subject ʼ s bed and used as the model features. In addition, dietary intake information was collected from the care record. Analysis of the evaluation results showed recall and specificity of 45.6 ± 46.7% and 83.88 ± 6.06%, re-spectively, for the model constructed using training data of 60 days. For future studies, we will continue to collect data and increase the number of participants to improve the robustness and accuracy of the proposed anomaly detection system.
Facile Fabrication of Quaternized Sisal Fiber by Electron Beam Radiation and its Effective Adsorption for Indigo Carmine from Aqueous Solution

The removal of Indigo carmine (IC) from the aquatic environment is necessary due to its high toxicity. In this study, methacryloxy ethyltrimethyl ammonium chloride (DMC) modified sisal fiber (SF-DMC) was prepared by a one-step process using radiation induced grafting polymerization. The adsorption performance of SF-DMC toward IC dye was investigated by batch adsorption experiments. The adsorption kinetic studies shows that adsorption equilibrium reached within 30 min, and it can be well described by pseudo-second-order model. The adsorption isotherms are well described by Langmuir model, and the theoretical maximum adsorption capacity are 709.22 to 892.86 mg/g at different temperature. The adsorption of IC onto SF-DMC is a spontaneous and exothermic reaction and low temperature is favorable for adsorption. Besides, SF-DMC has good selective adsorption for IC in the mixed anionic dyes and in high-salt solution. The dyes on SF-DMC can be desorbed by 2mol/L HCl solution. Therefore, the SF-DMC exhibits excellent adsorption performance, which is suitable for IC removal from high-salt wastewater.
Spall Fault Quantification Method for Flight Control Electromechanical Actuator

Flight control electro-mechanical actuators (EMAs) are among the primary onboard systems that significantly influence the reliability and safety of unmanned aerial vehicles. Recent reliability studies have shown that the ball-screw element of a flight control EMA is subject to oscillating operating conditions that may initiate rapid degradation, such as fatigue spall defects. Accordingly, detecting and quantifying such faults are crucial for developing efficient fault prognostic and remaining useful life estimation capabilities. In this study, a vibration-based fault quantification method is developed to quantify the fatigue faults of a ball-screw mechanism of an EMA. The method is based on identifying the ball passing instants through a localized surface defect on the vibrational jerk rather than the vibrational acceleration measurement. The jerk is numerically determined from conventional accelerometers using a Savitzky–Golay differentiator. This method was successfully tested for ball bearings and it is adjusted in this paper for ball-screw faults. The experimental validation is investigated on a set of fault-seeded samples on NASA’s Ames Research Center Flyable Electro-Mechanical Actuator test stand.
Nonnegative Latent Factor Analysis-Incorporated and Feature-Weighted Fuzzy Double $c$-Means Clustering for Incomplete Data

Fuzzy <inline-formula><tex-math notation="LaTeX">$c$</tex-math></inline-formula>-means (FCM) clustering is a promising method to handle uncertainties in data clustering. However, the traditional FCM and most of its variants cannot address incomplete inputs. To this aim, a novel fuzzy clustering framework is put forward to perform highly accurate clustering on incomplete data. It adopts twofold ideas: 1) Utilizing a nonnegative latent factor model to prefill the missing data in the inputs by rigidly extracting involved entities’ latent features, where the principle of a minibatch gradient descent algorithm is incorporated into a single latent factor-dependent, nonnegative and multiplicative update algorithm to accelerate the convergence rate; and 2) integrating the distribution of inputs and the weights of local features into the objective function through sparse self-representation and weighting allocation to focus on crucial features. In this way, a NLF analysis-incorporated and feature-weighted fuzzy double <inline-formula><tex-math notation="LaTeX">$c$</tex-math></inline-formula>-means clustering (NF <inline-formula><tex-math notation="LaTeX">$^2$</tex-math></inline-formula> D) method is achieved, where the data distribution and instance correlation are simultaneously considered with care. Experiments on 12 real-world datasets including both data and images with different missing rates show that the proposed NF<inline-formula><tex-math notation="LaTeX">$^2$</tex-math></inline-formula>D method has a significant superiority over state-of-the-art fuzzy clustering methods.
Advanced Processing and Machining of Tungsten and Its Alloys

Tungsten is a refractory metal with the highest melting temperature and density of all metals in this group. These properties, together with the high thermal conductivity and strength, make tungsten the ideal material for high-temperature structural use in fusion energy and other applications. It is widely agreed that the manufacture of components with complex geometries is crucial for scaling and optimizing power plant designs. However, there are challenges associated with the large-scale processing and manufacturing of parts made from tungsten and its alloys which limit the production of these complex geometries. These challenges stem from the high ductile-to-brittle transition temperature (DBTT), as well as the strength and hardness of these parts. Processing methods, such as powder metallurgy and additive manufacturing, can generate near-net-shaped components. However, subtractive post-processing techniques are required to complement these methods. This paper provides an in-depth exploration and discussion of different processing and manufacturing methods for tungsten and identifies the challenges and gaps associated with each approach. It includes conventional and unconventional machining processes, as well as research on improving the ductility of tungsten using various methods, such as alloying, thermomechanical treatment, and grain structure refinement.
Stable Isotope and Element Profiling for Determining the Agroclimatic Origin of Cow Milk within a Tropical Country

Information on the geographic origin of milk is important in determining quality attributes and for economic gain through building brand value associated with origin. Stable isotope signatures and trace element concentrations have been increasingly used in authentication of milk, though information on the power of such technology in verifying agroclimatic origin in small continents with diverse climatic, environmental conditions, and animal management practice is scarce. Therefore, the main objective of this study was to investigate the possibility of using a stable isotope composition of C, N, O, and H and element fingerprints to determine the agroclimatic origin of milk produced in different agroclimatic zones of Sri Lanka. Stable isotopes ratios of C, N, H, and O, and elemental fingerprints of milk samples were determined by IRMS and ICP-MS, respectively. Significant variations were observed in stable isotope ratios, especially δ18O and the mean content of Li, Al, Cr, Mn, and Sr in the bulk milk samples obtained from different agroclimatic zones. A linear discriminant analysis differentiated cow milk produced from four agroclimatic zones based on stable isotope ratios, and the inclusion of elemental ratios enhanced the discriminating ability.
The impact of COVID-19 on income and employment: policy responses and a subjective assessment by the Lithuanian population of the measures applied

All the countries in the world, to a greater or smaller extent, experienced the negative impact of the COVID-19 pandemic on their economies in 2020–21. Due to the pandemic, Lithuania, like other countries’ welfare states, have faced new challenges in managing the impact caused by the health crisis. A tremendous burden was imposed upon the healthcare system, and a number of economic activities were also affected by operational restrictions and lockdown restrictions. The need for social protection is greatly enhanced in the context of various social crises. We are witnessing growing public support for increased funding for social protection to a wider range of beneficiaries. In addition, national governments are expected to provide protection in the event of unemployment, illness, provide an effective response to the challenges posed by various social crises, and to offer the population an adequate package of measures. Even though the COVID 19 pandemic is not over, an assessment of the impact and measures applied is crucial for the sustainability and effectiveness of the welfare state. This article aims to study policies targeted to mitigate the negative impact of the COVID-19 pandemic on income and employment and their subjective assessment by the Lithuanian population. The research also seeks to understand the perceptions of the population about universal social policies, which, in the context of Lithuania, are considered as a more radical policy alternative. There is a growing body of literature examining the changes in social policies in response to the challenges of the pandemic in various regions and countries around the world – in Europe (Cook and Grimshaw 2020), the Nordic countries (Greve et al. 2020), the United States (Barry et al. 2020), and central and eastern European countries (Aidukaite et al. 2021). Researchers observe that the negative effects of the pandemic are more severe in countries which use the Western
Adaptive event‐triggered robust H∞ control for Takagi–Sugeno fuzzy networked Markov jump systems with time‐varying delay

This paper considers an adaptive event‐triggered robust H∞ control for the Takagi–Sugeno (T‐S) fuzzy under the networked Markov jump systems (NMJSs) with time‐varying delay. First, a new adaptive event‐triggered scheme is developed to guarantee the T‐S fuzzy NMJSs, and as a result, communication energy consumption reduced while device efficiency is maintained. Besides, an asynchronous operation method is adopted to deal with the mismatched premise variables between the fuzzy system and the fuzzy controller. One of the main objectives of this article is to construct the fuzzy state‐feedback controller (mode‐dependent) in a closed‐loop form for stochastic stability for all admissible parameter uncertainties with an H∞ performance index. Different from the conventional triggering mechanism, in this paper, the parameters of the triggering function are based on a new adaptive law that is obtained online rather than a predefined constant. To achieve the less conservative control design, a new type of stochastic Lyapunov–Krasovskii functional is designed by decomposing method, in which the delay interval transforms into various equidistant subintervals in terms of linear matrix inequalities. An example of a truck‐trailer application is used to demonstrate the effectively of the proposed algorithms.
Scalable recommendation systems based on finding similar items and sequences

The rapid growth in the airline industry, which started in 2009, continued until the COVID‐19 era, with the annual number of passengers almost doubling in 10 years. This situation has led to increased competition between airline companies, whose profitability has decreased considerably. They aimed to increase their profitability by making services like seat selection, excess baggage, Wi‐Fi access optional under the name of ancillary services. To the best of our knowledge, there is no recommendation system for recommending ancillary services for airline companies. Also, to the best of our knowledge, there is no testing framework to compare recommendation algorithms considering their scalabilities and running times. In this paper, we propose a framework based on Lambda architecture for recommendation systems that run on a big data processing platform. The proposed method utilizes association rule and sequential pattern mining algorithms that are designed for big data processing platforms. To facilitate testing of the proposed method, we implement a prototype application. We conduct an experimental study on the prototype to investigate the performance of the proposed methodology using accuracy, scalability, and latency related performance metrics. The results indicate that the proposed method proves to be useful and has negligible processing overheads.
Morphology Characterization, Molecular Identification, and Pathogenicity of Fungal Pathogen Causing Kaffir Lime Leaf Blight in Northern Thailand

Thailand is known to be the largest producer of kaffir lime leaf products in the global market. In 2021, leaf blight was found on kaffir lime plants (Citrus hystrix DC.) in Lamphun Province of northern Thailand. This disease has been associated with significant economic losses. However, there have been no prior reports of leaf blight on kaffir lime plants in Thailand or anywhere else in the world. In this study, causal fungi were isolated from lesions of kaffir lime plants and a total of three fungal isolates were obtained. All causal fungi were identified as Lasiodiplodia chinensis based on morphological characteristics and the phylogenetic analysis of combined sequences of the internal transcribed spacer (ITS) of ribosomal DNA, the translation elongation factor 1-alpha (tef-1), β-tubulin (tub), and RNA polymerase II subunit (rbp2) genes. Pathogenicity tests were conducted and the results revealed that all isolated fungi caused symptoms of leaf blight on inoculated leaves. This outcome was similar to symptoms that naturally occur and have been observed in the field. This is the first report on kaffir lime leaf blight caused by L. chinensis. Our study will provide information of high value for the development of effective strategies for the monitoring and prevention of this disease.
Synergistic oxygen vacancy-rich CuO/visible light activation of peroxymonosulfate for degradation of rhodamine B: fast catalyst synthesis and degradation mechanism

This work outlines the synthesis of copper oxide nanoparticles (CuO-SC) loaded with a number of oxygen vacancies by a fast sodium citrate assisted precipitation method with no need of calcination. X-ray diffraction, scanning electron microscopy, UV-Vis diffuse reflectance spectroscopy, time-resolved fluorescence lifetime and electrochemical impedance spectra were used to characterize the as-synthesized nanocomposites. The results indicated that the CuO-SC nanoparticles had regular fusiform shape with high surface area, wide light harvesting window, fast charge transport and high carrier concentration. As a result, the catalytic activity of the CuO-SC/peroxymonosulfate (PMS)/visible light (Vis) system for the degradation of rhodamine B (RhB) was much higher than that of as-prepared CuO nano powder in the absence of sodium citrate. Almost 98.0% of the initial RhB dyes was decomposed in 20 min with 0.12 g L−1 PMS and 0.3 g L−1 catalyst. Meantime, it exhibited high catalytic stability with little deactivation after four runs and a wide application range of pH. Moreover, RhB can be readily degraded with backgrounds of Cl−, NO3−, SO42−, HCO3− and low concentration of humic acid in a CuO-SC/PMS/Vis system. Combined with the results of electron spin resonance paramagnetic spectroscopy, X-ray photoelectron spectroscopy and radical quenching experiments, holes, superoxide radicals and a small amount of sulfate radicals, hydroxyl radicals and singlet oxygen were involved in the CuO-SC/PMS/Vis system. Furthermore, a possible degradation mechanism based on the synergistic effect of radical reaction and non-radical reaction was proposed based on the above results.
Analysis of the power demand side management based on ISM

Aiming at the complexity of the power demand side management,interpretative structural modeling is introduced to analyse the relationship of the various factors.This paper takes an area as an example to explain the method.Based on the factors of the area,the ISM is erected after gaining the reach matrix.According to the ISM,the hierarchical relationship is established to find out surface,shallow,intermediate and deep factors which can provide reference to formulate the measures.
PHENOLIC CONTENT AND ANTIOXIDANT ACTIVITY OF CRATAEGUS MONOGYNA JACQ. AND CRATAEGUS MACROCARPA HEGETSCHW. LEAVES AND FRUITS EXTRACTS

UDK: 547.56:582.711. 714 582.711. 714:581.45/. 47 Phenolic contents of methanolic extracts prepared from leaves and fruits of Crataegus monogyna Jacq. and Crataegus macrocarpa Hegetschw. were determined. The antioxidant capacity was assessed by DPPH, ABTS and FRAP assay. The results showed that leaves were richer in the content of phenols (59.23 - 91.91 GAE g-1), flavonoids (2.38 - 4.08 mg QE g-1 and 5.24 - 8.9 mg RE g-1) , phenolic acids (33.40 - 68.98 CAE g-1) and proanthocyanidins (26.15 - 48.60 CE g-1) while in fruits anthocyanins dominateted (0.43 - 0.80 CG g-1). Leaves also had higher antioxidant capacity than fruits for both species. Generelly, C. monogyna fruits had higher content of anthocyanins. Total phenols, phenolic acids and proanthocyanidins were highly corelated with DPPH (r2 = 0.8703 - 0.9618), ABTS (r2 = 0.7833 - 0.9443) and FRAP (r2 = 0.903 - 0.9695) assay. The results suggests that these compounds were the major contributors to the antioxidant capacity in leaves and fruits extracts of both species. Higher contents of bioactive compounds and higher antioxidant capacity were determined for C. x macrocarpa samples. Therefore, C. x macrocarpa leaves and fruits are valuble source of antioxidant polyphenols with high potential for use in preparation of different natural health products.
Maxwell fish eye for polarized light

We consider the propagation of polarized light in the medium with Maxwell ﬁsh eye refraction index proﬁle. We show that polarization violates the additional symmetries of the medium so that ray trajectories no longer remain closed. Then we suggest a modiﬁed, polarization-dependent Maxwell ﬁsh eye refraction index which restores all symmetries of the initial proﬁle and yields closed trajectories of polarized light. Explicit expressions for the polarization-dependent integrals of motion and the solutions of corresponding ray trajectories are presented.
Regional Trends and Socioeconomic Predictors of Adolescent Pregnancy in Nigeria: A Nationwide Study

Adolescent pregnancy is a major health concern which has lifelong consequences. The aim of this study is to examine the regional trends and socioeconomic predictors of adolescent pregnancy in Nigeria. This study used pooled data from the 2008, 2013 and 2018 Nigeria Demographic and Health Survey (NDHS). A total of 22,761 women aged 15–19 years were selected across the three surveys. Multilevel logistic regression analysis that adjusted for cluster and survey weights was used to identify predictors of adolescent pregnancy in Nigeria, across the six geopolitical zones of Nigeria. Adolescent pregnancy remained constant between 2008 (22.9%; 95% CI = 22.14, 24.66), and 2013 (22.5%; 95% CI = 20.58, 24.50), but a significant decline was reported in 2018 (18.7%; 95% CI = 17.12, 20.46). Trends show a decrease in adolescent pregnancy across all six geopolitical zones, except for the South-East zone which reported a slight increase (0.6%). Multivariable analysis revealed that the main socioeconomic predictors across all six geopolitical zones were: poor households, increasing age, and low education. Exposure to media (watching television and reading newspapers) was reported as predictor in all regions except the North-East geopolitical zone, while all northern zones reported high levels of adolescent pregnancy in male-led households. To address adolescent pregnancy in Nigeria, there is need to promote girls’ education especially among poor households, and for the dissemination of reproductive health messages to adolescents through various forms of mass media campaign, as well as the adoption of social marketing interventions to improve sexual and reproductive health literacy.
Measuring and Controlling System of Single-Axis Stable Platform Based on LabWindows/CVI

A project of LabWindows/CVI multithreading technique is introduced,which researches the key technique and method that how to achieve highspeed data transmission between threads to solve the problem of data barrage in communication.The measuring and control software for single-axis stable platform is designed and this software achieves the functions of data acquisition,processing,storing,transmission,display and report generation.The application indicates that the system has a great efficiency in processing and can meet clients' need.
Fostering Multilingual Academic Writing Knowledge in Interdisciplinary EMI Degree Programs

This contribution presents a course curriculum as well as conclusions drawn from a quasi-interventional study on the development of advanced English writing skills in an interdisciplinary English-medium instruction (EMI) management degree program at the master’s level, offered at a Midwestern German university. Two English for specific purposes (ESP) writing instructors and seven discipline-specific lecturers in the life and social sciences contributed to a writing-intensive course design in team-teaching partnerships (Lasagabaster, 2018) formed during the implementation of a 14-week core module in the interdisciplinary degree program. The student group in the present project (n=20) provides an illustrative example of today’s superdiverse student populations in higher education (Donahue, 2018). In order to document developments in the students’ EFL writing skills, EFL sourcebased academic writing assignments were collected from the students prior to and after the module. Also prior to and after the module, students completed extensive writing-focused surveys, documenting the students’ declarative writing skills and the students’ attitudes towards different types of advanced EFL writing.
RESEARCH ON QUALITY FAULT DIAGNOSIS IN MECHANICAL MACHINING PROCESS BASED ON GENETIC ALGORITHM

The probabilistic causal model, based on the parsimonious covering theory, is a universal fault diagnosis model and its shortcomings and some improvements are firstly described. And then a new improved model based on a genetic algorithm is put forward to solve the quality fault diagnosis problem in mechanical machining process, in which some steps are introduced in detail,and an individual fitness evaluation function is developed by analyzing the relationship between the machining error and error resource and using fault tree analysis. Finally, some implementation techniques are described and the feasibility of the method is demonstrated by means of CASE.