Miracle-dz/UniFAR-FTUs huggingface dataset:
Mycobacterium tuberculosis Lineage Distribution Using Whole-Genome Sequencing and Bedaquiline, Clofazimine, and Linezolid Phenotypic Profiles among Rifampicin-Resistant Isolates from West Java, Indonesia

Tuberculosis (TB) is caused by Mycobacterium tuberculosis infection. Indonesia is ranked second in the world for TB cases. New anti-TB drugs from groups A and B, such as bedaquiline, clofazimine, and linezolid, have been shown to be effective in curing drug resistance in TB patients, and Indonesia is already using these drugs to treat patients. However, studies comparing the TB strain types with anti-TB resistance profiles are still relevant to understanding the prevalent strains in the country and their phenotypic characteristics. This study aimed to determine the association between the TB lineage distribution using whole-genome sequencing and bedaquiline, clofazimine, and linezolid phenotypic profile resistance among M. tuberculosisrifampicin-resistant isolates from West Java. M. tuberculosis isolates stock of the Department of Microbiology, Faculty of Medicine, Universitas Indonesia, was tested against bedaquiline, clofazimine, and linezolid using a mycobacteria growth indicator tube liquid culture. All isolates were tested for M. tuberculosis and rifampicin resistance using Xpert MTB/RIF. The DNA genome of M. tuberculosis was freshly extracted from a Löwenstein–Jensen medium culture and then sequenced. The isolates showed phenotypically resistance to bedaquiline, clofazimine, and linezolid at 5%, 0%, and 0%, respectively. We identified gene mutations on phenotypically bedaquiline-resistant strains (2/3), and other mutations also found in phenotypically drug-sensitive strains. Mykrobe analysis showed that most (88.33%) of the isolates could be classified as rifampicin-resistant TB. Using Mykrobe and TB-Profiler to determine the lineage distribution, the isolates were found to belong to lineage 4 (Euro-American; 48.33%), lineage 2 (East Asian/Beijing; 46.67%), and lineage 1 (Indo-Oceanic; 5%). This work underlines the requirement to increase the representation of genotype-phenotype TB data while also highlighting the importance and efficacy of WGS in predicting medication resistance and inferring disease transmission.
Texture Features Extraction Using Wavelet-Based CLBP for Surface Defects Retrieval of Hot Rolled Steel Strip

This paper addresses the effective content-based image retrieval (CBIR) system specifically designed for identifying surface defects of hot-rolled steel strips. This system allows the expert to separate serious defects from others automatically. The proposed CBIR system is based on extracting completed local binary patterns (CLBP) features from the discrete wavelet transform (DWT) coefficients. This DWCLBP descriptor extracts highly discriminative texture features at different scales and orientations. We select the optimal mother wavelet and wavelet decomposition levels by making extensive comparisons. The experimental results on NEU surface defects database demonstrate promising retrieval performance of the DWCLBP features.
A Proposed Technology Acceptance Model for Measuring Cloud Computing Usage in Education

Information and Communication Technology (ICT) has become essential in education, with e-learning and cloud services providing solutions to the education sector and enabling it to compete more effectively. The Technology Acceptance Model (TAM) and its various versions have been recognized worldwide for measuring technology acceptance in learning and teaching. However, deficiencies in measuring technology acceptance for cloud computing among teachers in the Arab world and Libya have been revealed in previous studies. This study aims to develop the TAM model by including external factors to measure teachers' acceptance of this technology. The researchers added essential factors to the model and tested it with experts in the same field. The resulting model was used to measure the acceptance of cloud computing applications among secondary school teachers in AL-Marj City. The study found that the model's external factors enhanced its ability to measure technology acceptance in an educational context. The study provides a solid foundation for future research. New extensions and amendments to the model can be proposed to include various factors influencing the decision to adopt, accept, or reject a specific technology in teaching and learning processes.
Exploration of the Polymorphism Distribution of Bovine HMGA2 Gene in Worldwide Breeds and Its Associations with Ovarian Traits

Simple Summary Bovine breeding is an economically important endeavor in China. Ovarian traits play a significant role in the reproductive characteristics. This study aimed to underscore the discovery of a novel indel locus within the HMGA2 gene in Holstein cows. Our study found that a variant in the bovine HMGA2 gene has a significant connection with ovarian traits. These findings contribute to a more promising outlook for the bovine industry. Abstract The high-mobility group AT-hook 2(HMGA2) gene has been widely studied in the context of cancer and animal growth. However, recently, several studies have uncovered its critical role in cell proliferation. A genome-wide association study (GWAS) further suggests that the HMGA2 gene is a candidate gene in fertility, indicating its connection not only to growth traits but also to reproduction, specifically ovarian traits. Thus, this study aimed to analyze the distribution of the HMGA2 gene in 54 bovine breeds worldwide, identify important short fragment variants (indels), and investigate the relationship between HMGA2 and ovarian development. The dataset included genotypic information from a bovine population of 634 individuals (n = 634). After genotyping and analyzing four selected loci, we found that one out of four loci, rs133750033 (P4-D22-bp), was polymorphic. Our results also reveal that this indel of HMGA2 is significantly associated with certain ovarian traits (p < 0.05). Specifically, it has connection with ovarian length (p = 0.004) and ovarian height (p = 0.026) during diestrus. Additionally, we discovered a higher expression of the HMGA2 gene in Asian cattle breeds. In summary, this study suggests that HMGA2 has the potential to serve as an animal fertility testing marker gene. Moreover, these findings contribute to a more promising outlook for the bovine industry.
PERFORMANCE EVALUATION OF A MACHINE LEARNING-BASED ANOMALY DETECTION SYSTEM FOR WIRELESS COMMUNICATION NETWORK

Wireless communication networks have become a critical part of our daily lives, and the Internet of Things (IoT) has enabled the connection of various devices to these networks. However, this has also made these networks vulnerable to various types of attacks, leading to anomalies in the data generated by these networks. This research paper presents an investigation of machine learning algorithms for anomaly detection in wireless communication networks using IoT intrusion dataset. We present a comparative analysis of popular machine learning algorithms: Decision tree, Random Forest, CNN, and XGBoost, for anomaly detection in wireless communication networks. The research paper aims to compare and improve the accuracy of anomaly detection algorithms for wireless communication networks by utilizing feature engineering techniques. These techniques involve extracting relevant features from the dataset to enhance the performance of the algorithm. To achieve this objective, the study conducts an in-depth exploration of the impact of different hyperparameters on the performance of the algorithms. The study utilises feature engineering techniques to extract relevant features from the dataset and explores the impact of different hyperparameters on the performance of the algorithms To evaluate the performance of the proposed algorithms, the study uses cross-validation techniques and measures several performance metrics, including accuracy, precision and recall. These help to determine the effectiveness of the proposed algorithms in identifying anomalous events in wireless communication networks. Moreover, the research assesses the efficacy of the aforementioned algorithms by comparing their performance with other contemporary state-of-the-art algorithms. This comparative analysis helps to determine which algorithm is best suited for detecting anomalies in wireless communication networks, depending on the characteristics of the available dataset.
Customer Segmentation Analysis using K-means Algorithm with Elbow method and Dendrogram

In today’s competitive business environment, it is crucial to do marketing effectively based on the customer buying habits and requirements. By analyzing the buying habits of customers, companies can enhance customer’s shopping experiences. The analysis can be done with the help of a method called customer segmentation. It is the process of grouping customers into different clusters based on similar characteristics. In this paper, we have done customer segmentation using the k-means algorithm which is an unsupervised learning method and it focuses on grouping the data points into clusters where each point resides in a cluster with the nearest centroid. The accuracy for the optimal number of clusters is verified using a dendrogram where the number of clusters is equal to the number of points obtained by drawing a imaginary horizontal line bisecting through the most extended vertical line of the graph. This analysis gives insights based on customer buying habits which helps companies build marketing strategies for the targeted audience that will improve client retention and overall revenue of business.
Growth and Characterization of Hexagonal Lu-Fe-O Multiferroic Thin Films

In the quest for new types of information processing and storage, complex oxides stand out as one of the most promising material classes. The multiple functionalities of complex oxides naturally arise from the delicate energy balance between the various forms of order (structural, electronic, magnetic). In particular, multiferroic and magnetoelectric oxides which simultaneously exhibit more than one type of ferroic orders have many advantages over existing materials. Widespread practical applications will require a single-phase multiferroic material with a transition temperature that lies considerably above room temperature, large electric and magnetic polarizations, and strong coupling between ferroic orders. Recently, multiferroic LuFe2O4 has attracted great interest because it has relatively high transition temperatures, large polarization, high magnetic coercivity, and the strong magnetoelectric coupling. Compared to the large amount of effort to study bulk LuFe2O4, there are only a couple of reported attempts to grow LuFe2O4 thin films, presumably due to difficulties in the sample preparation. In this work, a comprehensive growth diagram of Lu-Fe-O compounds on MgO (111) substrates using pulsed laser deposition is constructed based on extensive growth experiments. The LuFe2O4 phase can only be grown in a small range of temperature and O2 pressure conditions. An understanding of the growth mechanism of Lu-Fe-O compound films is offered in terms of the thermochemistry at the surface. Superparamagnetism is observed in the LuFe2O4 film and is explained in terms of the effect of the impurity hexagonal LuFeO3 (h-LuFeO3) phase and structural defects. In addition to LuFe2O4, we also succeeded in growing hexagonal-LuFeO3 (h-LuFeO3) epitaxial films in single crystalline form on either insulating or metallic substrates using pulsed laser deposition (PLD). H-LuFeO3 thin films exhibit hysteresis in piezoresponse force microscopy (PFM) measurements indicative of ferroelectricity, and simultaneously show antiferromagnetic order, with both properties coexisting at room temperature.
An Improved Seeker Optimization Algorithm for Phase Sensitivity Enhancement of a Franckeite- and WS2-Based SPR Biosensor for Waterborne Bacteria Detection

For the purpose of detecting waterborne bacteria, a high-phase-sensitivity SPR sensor with an Ag–TiO2–Franckeite–WS2 hybrid structure is designed using an improved seeker optimization algorithm (ISOA). By optimizing each layer of sensor construction simultaneously, the ISOA guarantees a minimum reflectance of less than 0.01 by Ag (20.36 nm)–TiO2 (6.08 nm)–Franckeite (monolayer)–WS2 (bilayer) after 30 iterations for E. coli. And the optimal phase sensitivity is 2.378 × 106 deg/RIU. Sensor performance and computing efficiency have been greatly enhanced using the ISOA in comparison to the traditional layer-by-layer technique and the SOA method. This will enable sensors to detect a wider range of bacteria with more efficacy. As a result, the ISOA-based design idea could provide SPR biosensors with new applications in environmental monitoring.
Partial Grounding in Planning using Small Language Models

The aim of classical automated planning is to find a sequence of actions, a plan, that changes the state of the world from a given initial state to a state that satisfies the goal condition. Most research in the field focuses on heuristic search, which attempts to find a plan on a fully grounded model of the planning task. However, obtaining the full grounding is often in-feasible as its size can be exponentially larger than the original input. We follow up on previous work that introduced partial grounding for planning using a relevance prediction estimate obtained from classical machine learning models. These models are trained offline, on a per-domain basis, to estimate how likely it is for a plan to include a given action. In this article we leverage recent advances in the field of language models in natural language processing (NLP) to improve these estimates. We use small language models to create word embeddings for actions and facts directly from their textual representation. These models provide fixed-length representations for actions and facts reached along a delete-relaxed solution of a planning task, which can be obtained efficiently. We show that these feature vectors can be used to train predictors of action relevance, that consistently identify relevant actions on an established set of hard-to-ground planning benchmarks.
Bromopyrene Symphony: Synthesis and Characterisation of Isomeric Derivatives at Non-K Region and Nodal Positions for Diverse Functionalisation Strategies

Pyrene, a renowned aromatic hydrocarbon, continues to captivate researchers due to its versatile properties and potential applications across various scientific domains. Among its derivatives, bromopyrenes stand out for their significance in synthetic chemistry, materials science, and environmental studies. The strategic functionalisation of pyrene at non-K region and nodal positions is crucial for expanding its utility, allowing for diverse functionalisation strategies. Bromo-substituted precursors serve as vital intermediates in synthetic routes; however, the substitution pattern of bromoderivatives significantly impacts their subsequent functionalisation and properties, posing challenges in synthesis and purification. Understanding the distinct electronic structure of pyrene is pivotal, dictating the preferential electrophilic aromatic substitution reactions at specific positions. Despite the wealth of literature, contradictions and complexities persist in synthesising suitably substituted bromopyrenes due to the unpredictable nature of substitution reactions. Building upon historical precedents, this study provides a comprehensive overview of bromine introduction in pyrene derivatives, offering optimised synthesis conditions based on laboratory research. Specifically, the synthesis of mono-, di-, tri-, and tetrabromopyrene isomers at non-K positions (1-, 3-, 6-, 8-) and nodal positions (2-, 7-) is systematically explored. By elucidating efficient synthetic methodologies and reaction conditions, this research contributes to advancing the synthesis and functionalisation strategies of pyrene derivatives, unlocking new possibilities for their utilisation in various fields.
Hsa_circ_0001615 downregulation inhibits esophageal cancer development through miR-142-5p/β-catenin

Background Recent studies have found that circular RNAs (circRNAs) play important roles in tumorigenesis. This study aimed to determine the function and potential mechanisms of hsa_circ_0001615 in esophageal cancer. Methods Quantitative real-time reverse transcription polymerase chain reaction (qRT-PCR) was used to validate the expression of hsa_circ_0001615 and miR-142-5p. Subsequently, 3-(4,5-dimethylthiazol-2-yl)-5-(3-carboxymethoxyphenyl)-2-(4-sulfophenyl)-2H-tetrazolium salt, flow cytometry, clone formation, and transwell assays were used to assess the function of hsa_circ_0001615. Furthermore, qRT-PCR and Western blot analysis were used to verify cyclin D1, Bcl-2 associated X, B-cell lymphoma/leukemia gene-2, and β-catenin levels. Circular RNA Interactome was used to estimate the binding site between hsa_circ_0001615 and miR-142-5p. Additionally, dual-luciferase reporter assays were used to determine whether miR-142-5p was a direct target of hsa_circ_0001615. Pearson correlation analysis was used to explore the relationship between miR-142-5p and hsa_circ_0001615. Results In esophageal cancer, the expressions of hsa_circ_0001615 and miR-142-5p were increased and decreased, respectively. Hsa_circ_0001615 inhibition significantly reduced the proliferation, migration, and invasion but increased the apoptosis of esophageal cancer cells. Additionally, hsa_circ_0001615 knockdown increased miR-142-5p expression but decreased β-catenin expression. MiR-142-5p was a direct target of hsa_circ_0001615. Conclusion Hsa_circ_0001615 knockdown could mediate antitumor effects through the miR-142-5p/β-catenin pathway.
Telehealth Consultation for Malaysian Citizens’ Willingness to Pay Assessed by the Double-Bounded Dichotomous Choice Method

Background Re-envisioning healthcare in technology tools includes robust utilisation of telehealth, improvement in access, quality, care efficiencies and cost-effectiveness of healthcare services. In reality, the technology’s potential to transform healthcare may be limited by the ability to pay for it. This study aims to estimate Malaysian citizens’ willingness to pay (WTP) for telehealth consultations and determine the factors contributing to it. This is vital to inform decision-making about expansion, preferences and deployment of a pricing strategy for telehealth services. Methods A random sample of 220 adult Malaysians was surveyed using social network services (SNS). Three different WTP bid arrays were identified and each respondent received a randomly drawn bid price. The WTP fee for using the telehealth consultation for 30 min was measured and estimated using a Double-Bounded Dichotomous Choice (DBDC) and the Random Utility Logit Model. Result The median WTP was estimated to be RM58 (JPY2,198), RM78 (JPY2,956) for 132 respondents’ willingness to use telehealth consultation and RM26 (JPY985) for 51 respondents who were unwilling. Further analysis found that WTP is correlated with the perception and willingness of the respondents to use it. Conclusion Despite most respondents being willing to pay for telehealth consultations, sociodemographic characteristics and affordability influenced the process of making decisions about WTP for telehealth consultation. This finding suggests that the private sector can play a crucial role in the deployment of telehealth. However, there may be a need to consider affordability and how to increase access and use of telehealth services.
NBER WORKING PAPER SERIES MISALLOCATION, SELECTION AND PRODUCTIVITY: A QUANTITATIVE ANALYSIS WITH PANEL DATA FROM CHINA

We are grateful to Chaoran Chen for providing excellent research assistance. We also thank for useful comments Carlos Urrutia, Daniel Xu, and seminar participants at Toronto, McGill, Ottawa, REDg Barcelona, NBER China workshop, IMF conference on inequality, Cornell, Michigan, UBC, Xiamen U. , ASU, Tsinghua-USCD China conference, HKUST macroeconomics conference, Western conference on misallocation, Tsinghua workshop on macroeconomics, EEA Geneva, Banco de Mexico, Montreal, Ohio State, and Universitat de Barcelona. Restuccia gratefully acknowledges the support from the Canada Research Chairs program. Brandt thanks the support from the Noranda Chair for International Trade and Economics. Adamopoulos, Brandt, and Restuccia gratefully acknowledge the support from the Social Sciences and Humanities Research Council of Canada. The views expressed herein are those of the authors and do not necessarily reflect the views of the National Bureau of Economic Research.
Correlation of Serum Prolactin and Thyroid Stimulating Hormone Concentration in Infertile Women: A Systematic Review and Meta-Analysis

Infertility affects millions of people of reproductive age worldwide. Thyroid hormones and prolactin (PRL) affect reproduction and pregnancy; therefore, these two hormones influence fertility. This systematic review and meta-analysis aimed to summarise the strength of the correlation between serum PRL and thyroid stimulating hormone (TSH) in infertile women and to explore selected factors influencing the correlation. We conducted a systematic search of online databases (PubMed, Scopus, ScienceDirect, SAGE and Google Scholar) from inception until March 2021 and a manual search of the bibliographies of the included studies to identify relevant publications. The original research paper describing the correlation between PRL and TSH in reproductive-age women with infertility (primary and secondary) was included. The risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Analytical Cross-Sectional Studies. A random effect model was used to estimate the pooled correlations of PRL and TSH, followed by an assessment of heterogeneity and a sensitivity analysis. From a total of 822 relevant articles identified, 11 were eligible and included in this systematic review and meta-analysis. The random effect pooled correlation estimates between PRL and TSH was 0.431 (95% CI: 0.251, 0.582), with substantial heterogeneity between the included studies (I2 = 80%, τ2 = 0.067, P < 0.001). No significant publication bias was observed. Study region, types of infertility, sample size and year of the study did not influence the correlation estimates. Our results highlighted a significant positive moderate correlation between serum PRL and serum TSH in infertile women.
APPLICATION OF ILLUSTRATIVE MATERIALS IN FOREIGN LANGUAGE TEACHING FOR ENGINEERING SPECIALTIES

In the process of learning a foreign language for specific purposes, the most suitable, adequate, and innovative approaches are constantly being sought, concerning how and which/what additional (supplementary) materials contribute to more effective 1) subject and 2) language content learning, as well as concerning easy knowledge transfer - from the native to the foreign language. The following paper examines the importance of various content components and illustrative materials as supporting engineering students’ foreign language teaching and learning. By means of an exploratory survey (survey card), the opinion of the students was collected and analyzed, which is indicative of the materials suitable for application in a working environment in their relation with the conceptual apparatus in the studied material in the native and foreign languages.