Miracle-dz/UniFAR-FTUs huggingface dataset:
MediBioDeBERTa: Biomedical Language Model With Continuous Learning and Intermediate Fine-Tuning

The emergence of large language models (LLMs) has marked a significant milestone in the evolution of natural language processing. With the expanded use of LLMs in multiple fields, the development of domain-specific pre-trained language models (PLMs) has become a natural progression and requirement. Developing domain-specific PLMs requires careful design, considering not only differences in training methods but also various factors such as the type of training data and hyperparameters. This paper proposes MediBioDeBERTa, a specialized language model (LM) for biomedical applications. First, we present several practical analyses and methods for improving the performance of LMs in specialized domains. As the initial step, we developed SciDeBERTa v2, an LM specialized in the scientific domain. In the SciERC dataset evaluation, SciDeBERTa v2 achieves the state-of-the-art model performance in the named entity recognition (NER) task. We then provide an in-depth analysis of the datasets and training methods used in the biomedical field. Based on these analyses, MediBioDeBERTa, was continually trained on SciDeBERTa v2 to specialize in the biomedical domain. Utilizing the biomedical language understanding and reasoning benchmark (BLURB), we analyzed factors that degrade task performance and proposed additional improvement methods based on intermediate fine-tuning. The results demonstrate improved performance in three categories: named entity recognition (NER), semantic similarity (SS), and question-answering (QnA), as well as in the ChemProt relation extraction (RE) task on BLURB, compared with existing state-of-the-art LMs.
Radiotracers for Imaging of Inflammatory Biomarkers TSPO and COX-2 in the Brain and in the Periphery

Inflammation involves the activation of innate immune cells and is believed to play an important role in the development and progression of both infectious and non-infectious diseases such as neurodegeneration, autoimmune diseases, pulmonary and cancer. Inflammation in the brain is marked by the upregulation of translocator protein (TSPO) in microglia. High TSPO levels are also found, for example, in macrophages in cases of rheumatoid arthritis and in malignant tumor cells compared to their relatively low physiological expression. The same applies for cyclooxgenase-2 (COX-2), which is constitutively expressed in the kidney, brain, thymus and gastrointestinal tract, but induced in microglia, macrophages and synoviocytes during inflammation. This puts TSPO and COX-2 in the spotlight as important targets for the diagnosis of inflammation. Imaging modalities, such as positron emission tomography and single-photon emission tomography, can be used to localize inflammatory processes and to track their progression over time. They could also enable the monitoring of the efficacy of therapy and predict its outcome. This review focuses on the current development of PET and SPECT tracers, not only for the detection of neuroinflammation, but also for emerging diagnostic measures in infectious and other non-infectious diseases such as rheumatic arthritis, cancer, cardiac inflammation and in lung diseases.
Cooperation Between Teachers and Parents of Foreign Students

Recent years have contributed to the creation of many publications about the important role of parents in the education process and their cooperation with the school for fuller and more comprehensive development of the child. The role of parents, although not explicit, is increasingly appreciated by teachers and pedagogues in the process of adapting and building a satisfactory educational path for children and adolescents. Today, however, as a result of migratory movements of the population, the school is facing a new challenge: work in a culturally diverse environment. One of the issue is including foreign students and their parents in the school community. In the face of the constantly increasing number of foreign pupils in Polish schools, it is extremely important to know to what extent the Polish education system supports the dialogue and partnership between teachers and parents of foreign children. The essence of this paper is the presentation of the results of pilot studies conducted by the author in the Warsaw school environment. The aim of the research is to get to know the scope of cooperation and communication between teachers and parents of foreign students in Warsaw schools. The research was based on a cooperation model by Joyce L. Epstein (2010, 2019), referring to: parenting, communication, volunteering, learning at home, decision making and collaboration with the community. The presented research has the character of a diagnostic survey and it is an attempt to answer the following research questions: How does communication with parents of foreign students work? How teachers assess the parents' attitude in terms of: parenting, volunteering, learning at home, decision making, collaborating with the community?
Potential Bacteria Isolated from Contaminated Sites as Bio-degraders of Various Types of Plastic

The growing demand for plastics and their improper disposal have resulted in a significant environmental pollution problem. While various management strategies have been employed to tackle this issue, the persistence of plastic pollutants in the environment is still a major concern. Therefore, exploring and developing sustainable and environmentally safe techniques, such as biodegradation using potential bacteria, can help mitigate plastic pollution and provide a viable solution. The purpose of this study was to isolate and identify potential bacteria for degrading plastics from six soil samples collected from five plastic-contaminated sites. The population of microorganisms in the soil ranged from 1.9 ×105 to 8.2 × 104 CFU/g. The screening of biodegradation abilities to degrade various types of plastics, including Polypropylene (PP), Polystyrene (PS), Polyethylene (PE), Polyethylene terephthalate (PET), and Polylactic acid (PLA) (Bioplastic), as measured by the diameters of the clear zones surrounding the colonies, revealed that out of 40 strains, only 8 strains could degrade various types of plastics. These bacteria were identified using 16S rRNA genes, which showed that NBI0106, NBI0108, NBI0109, and NBI0111 tend to be Streptomyces ardesiacus with similarity 99%, NBI0113 tend to be Pseudomonas plecoglossicida with similarity 99%, and NBI0305 tend to be Streptomyces cellulosae with similarity 100%. In addition, The Streptomyces ardesiaca strain NBI0111 demonstrated the highest degradation efficiency for PP plastic, with a clear zone diameter of 32.19  0.34 mm. This study shows the importance of identifying bacteria in plastic-contaminated soils and landfills, which may lead to the discovery of more effective bacteria strain with the capacity to degrade various types of plastic in real environmental conditions.
Improving a Deep Learning Model to Accurately Diagnose LVNC

Accurate diagnosis of Left Ventricular Noncompaction Cardiomyopathy (LVNC) is critical for proper patient treatment but remains challenging. This work improves LVNC detection by improving left ventricle segmentation in cardiac MR images. Trabeculated left ventricle indicates LVNC, but automatic segmentation is difficult. We present techniques to improve segmentation and evaluate their impact on LVNC diagnosis. Three main methods are introduced: (1) using full 800 × 800 MR images rather than 512 × 512; (2) a clustering algorithm to eliminate neural network hallucinations; (3) advanced network architectures including Attention U-Net, MSA-UNet, and U-Net++. Experiments utilize cardiac MR datasets from three different hospitals. U-Net++ achieves the best segmentation performance using 800 × 800 images, and it improves the mean segmentation Dice score by 0.02 over the baseline U-Net, the clustering algorithm improves the mean Dice score by 0.06 on the images it affected, and the U-Net++ provides an additional 0.02 mean Dice score over the baseline U-Net. For LVNC diagnosis, U-Net++ achieves 0.896 accuracy, 0.907 precision, and 0.912 F1-score outperforming the baseline U-Net. Proposed techniques enhance LVNC detection, but differences between hospitals reveal problems in improving generalization. This work provides validated methods for precise LVNC diagnosis.
The Impact of Short Videos in the Listening Skills of Young Adults with A1 Level from UCACUE

The use of short educational videos as a tool to enhance listening skills in adult learners has gained significant attention in recent years. This study aims to explore the effects of incorporating short everyday English videos into listening activities in university students from UCACUE, La Troncal extension. The research incorporates a comprehensive literature review to identify the theoretical foundations and justifications for using short videos in adult language education. The participants for this study are fifty undergraduate students from the Language Center at UCACUE, with a beginner English level (A1 course) divided into control and experimental. For gathering data, groups are evaluated through questionnaires and pre and post-tests, to obtain quantitative data. Similarly, to attain qualitative data, a survey is introduced to them for analyzing students’ perceptions regarding the implementation of Short Videos in Listening activities. The results of the study revealed a notable enhancement in listening performance, students’ motivation, and engagement for participants who were exposed to video materials compared to those who used traditional audio resources. Participants viewing videos scored higher in post-tests, signifying better comprehension. Consequently, the study concluded that integrating videos effectively enhances listening skills, marking multimedia as a potent tool for educational advancement.
Generation of a Zebrafish Knock-In Model Recapitulating Childhood ETV6::RUNX1-Positive B-Cell Precursor Acute Lymphoblastic Leukemia

Simple Summary Despite remarkable progress in the treatment of acute lymphoblastic leukemia (ALL) in recent years, it remains a significant contributor to pediatric cancer-related deaths. This highlights the urgent need for innovative therapeutic strategies that target the genetic alterations driving ALL. We built a novel zebrafish disease model for ETV6::RUNX1-positive ALL, which harbors secondary lesions in the two commonly mutated genes, pax5, and cdkn2a/b. The introduction of secondary mutations significantly augmented the incidence of disease. This model provides a valuable tool for investigating the etiological role of secondary mutations and facilitating the evaluation of drug sensitivities in the future. Abstract Approximately 25% of children with B-cell precursor acute lymphoblastic leukemia (pB-ALL) harbor the t(12;21)(p13;q22) translocation, leading to the ETV6::RUNX1 (E::R) fusion gene. This translocation occurs in utero, but the disease is much less common than the prevalence of the fusion in newborns, suggesting that secondary mutations are required for overt leukemia. The role of these secondary mutations remains unclear and may contribute to treatment resistance and disease recurrence. We developed a zebrafish model for E::R leukemia using CRISPR/Cas9 to introduce the human RUNX1 gene into zebrafish etv6 intron 5, resulting in E::R fusion gene expression controlled by the endogenous etv6 promoter. As seen by GFP fluorescence at a single-cell level, the model correctly expressed the fusion protein in the right places in zebrafish embryos. The E::R fusion expression induced an expansion of the progenitor cell pool and led to a low 2% frequency of leukemia. The introduction of targeted pax5 and cdkn2a/b gene mutations, mimicking secondary mutations, in the E::R line significantly increased the incidence in leukemia. Transcriptomics revealed that the E::R;pax5mut leukemias exclusively represented B-lineage disease. This novel E::R zebrafish model faithfully recapitulates human disease and offers a valuable tool for a more detailed analysis of disease biology in this subtype.
Risk Assessment of Listeria monocytogenes in Ready-to-eat Meat from Plants to Consumption

In 2003, the Food and Drug Administration (FDA) and the USDA Food Safety and Inspection Service (FSIS) developed a quantitative assessment of the relative risk of L. monocytogenes in 23 ready-to-eat (RTE) foods to public health. Deli meats ranked as the riskiest food category, riskier than any other food categories. This study reassess the risk using newer concentrations data from a multi-state study and divides the deli meats category into four subcategories: prepackaged with growth inhibitor (GI), prepackaged without GI, retail-sliced with GI, and retail-sliced without GI. The relative risk based on the estimated deaths per annum and deaths per serving for each of the now 26 food category was ranked and compared with the previous risk ranking completed by FDA-FSIS (2003). The weighted median deaths per serving of the combined four deli meats was 74% of the median deaths per serving of the deli meats of original results, while those of non-deli meats foods increased by 191% to 537% because of the calibrated nature of the FDA-FSIS model. The median deaths per annum of deli meats decreased from 312 to 232 deaths per annum, while the median and mean deaths per annum for other food categories slightly increased with the use of new deli meats data but the relative ranking among non-deli meats food didn’t changed. Deli meats still had the highest deaths per annum of any food category, but their rank for deaths per serving dropped for 1 to 3, below unreheated frankfurters and pate. Retail-sliced deli meats without growth inhibitors have the highest risk of L. monocytogenes based on both death per serving and death per annum, while other three deli meat categories pose much lower risk. The work illustrates the improvements that the deli meats processing industry has made and highlights the need for a more current and comprehensive risk ranking.
Identifying common errors in polynomials of eighth grade students

This research aims to study and classify errors in polynomials made by secondary school students. The data for error identification was collected from exercise books of 72 eighth grade students. Three types of errors were examined: careless, computational, and conceptual errors. The errors were considered according to four topics in polynomials: similar terms of monomials; addition of polynomials; subtraction of polynomials; and multiplication of polynomials. It is found that students made the highest computational errors in identifying monomials’ similarity, which accounts for 17.86%. They have the highest percentage of making computational errors in the addition and subtraction of polynomials, which account for 10.88% and 12.04%, respectively. Lastly, they have the highest percentage of making careless errors in the multiplication of polynomials, which accounts for 14.44%. Furthermore, it can be seen that the source of errors is learners’ carelessness when writing the question and its answer. In addition, the basic knowledge of computing addition, subtraction, and multiplication of integers is the most crucial factor that leads to incorrect answers. Nevertheless, most students understand the principle of polynomials, but frequently make errors on other issues.
Linking Frontline Employee Self-Efficacy to Customers Service Performance in Healthcare Industry: A Dynamic Capability Perspective

Purpose In the complex and rapidly changing healthcare environment, the dynamic capabilities of frontline employees (FLEs) to integrate resources and adapt to environmental changes are crucial. This study aims to investigate the relationship between FLEs’ self-efficacy, dynamic capabilities (including sensing capability and reconfiguring capability), and their impact on service performance. Methods Data were collected from a matched sample of 123 doctors and 762 corresponding consumers from two medical aesthetic hospitals in China. SPSS and SmartPLS are used to test the proposed model. Results The findings indicate that FLEs’ self-efficacy positively influences their service performance through the mediation of dynamic capabilities. Moreover, while the direct impact of FLEs’ sensing capabilities on service performance was found to be insignificant, it was observed that these capabilities indirectly affect service performance through reconfiguring capabilities. Conclusion This study presents theories and arguments on the role of self-efficacy and dynamic capabilities in improving service performance. These findings contribute to a deeper understanding of how FLEs cultivate the dynamic capability of resource integration, offering valuable insights for the attainment of sustainable competitive advantages.
AN EXPERIMENTAL ANALYSIS ON STABILIZATION OF EXPANSIVE SOIL WITH STEEL SLAG AND FLY ASH

This paper deals about the stabilization of expansive soil on experimental basis. The stabilization of expansive soil is required because their volume can be change due to the variation in moisture content on it, which leads to either shrink or swell while the soil is in dry or wet condition respectively. The stabilization of expansive soil is assessed by the presence of different percentage of steel slag and fly ash on the expensive soil and the performance of modified expansive soil is evaluated using index properties test, permeability test, compaction test and unconfined compressive strength test. Based on this performance tests, optimum amount of steel slag and fly ash on expensive soil is also determined.
Present scenario of cattle hides price at some selected areas in Bangladesh

The study was carried out to investigate the present market price of cattle hide and socio-economic status of slaughterer at three selected areas of Bangladesh. Data was gathered from one hundred and fifty randomly selected respondents from three areas where twenty household from each area who slaughtered cattle during Eid-al-Adha, twenty slaughterers from each area and thirty tannery from Hemayetpur, Savar through a structured questionnaire, from December, 2022 to April, 2023. During survey the considered parameters were the current cattle hide price at different level, respondent gender, age, literacy, family size, housing, source of income, monthly income and working experience. Result from the study revealed that all slaughterers were male and the average aged in Savar, Dhaka South City Corporation & Mymensingh City Corporation were 50.00, 37.16 & 43.61 respectively. For literacy rate of slaughterers it was found that about 36.11% had primary level education, 59.33% had secondary level education, 4.56% had higher secondary level education and no graduate were found. Their average family size were 5.75 and about 75.39% slaughterer lived on rent house and 24.61% on own house. About 94.40% slaughterer solely depend on meat processing but along with meat processing 5.60% were engaged with business. Average income of selected slaughterers were 40468.75 TK/month. Maximum slaughterer (42.00%) have been involved in this profession for 8-16 years. Major sources of hides were household (who slaughtered animal during Eid-al-Adha and for ceremonial purposes) slaughterhouse, meat processing industries etc. In household, slaughterer and tannery small size hides selling price were 245.00 and 295.00 Tk/piece respectively, for medium size 518.00 and 561.00 TK/piece respectively. In case of large size hide market price was 744.00 and 885.00 TK/piece respectively. In tannery, buying price of small, medium and large size hides were 443.00, 758.00 and 1515.00 TK/piece and 28.00, 32.00, 43.00 TK/sq. ft. respectively. The main reason for the rapid decline in the price of hide was low demand of hide and also flay defect.
Viral–Bacterial Interactions That Impact Viral Thermostability and Transmission

Enteric viruses are significant human pathogens that commonly cause foodborne illnesses worldwide. These viruses initiate infection in the gastrointestinal tract, home to a diverse population of intestinal bacteria. In a novel paradigm, data indicate that enteric viruses utilize intestinal bacteria to promote viral replication and pathogenesis. While mechanisms underlying these observations are not fully understood, data suggest that some enteric viruses bind directly to bacteria, stabilizing the virion to retain infectivity. Here, we discuss the current knowledge of these viral–bacterial interactions and examine the impact of these interactions on viral transmission.
Magnetotelluric imaging of a fossil paleozoic intraoceanic subduction zone in western Junggar, NW China

The fate of subducted oceanic slabs can provide important clues to plate reconstruction through Earth history. Since oceanic slabs in continental collision zones are typically not well preserved, ancient subduction zones have rarely been imaged by geophysical techniques. Here we present an exception from the Darbut belt in the Junggar accretionary collage in the southern Altaids of Asia. We deployed a 182 km long magnetotelluric (MT) profile including 60 broadband sounding sites across the belt. Quality off‐diagonal impedances were inverted by a three‐dimensional scheme to image resistivities beneath the profile. The resistivity model along with MT impedance phase ellipses and induction vectors were tested and interpreted in detail. Combining geological and geophysical observations, mineral physical experiment, and geodynamic modeling results, the MT transect suggests a fossil intraoceanic subduction zone during the Late Paleozoic in the western Junggar that has been well preserved due to lack of significant subsequent tecto‐thermal events.
Center-Triplet Loss for Railway Defective Fastener Detection

Sample imbalance is the main factor affecting detection performance of defective fasteners. Most of the existing methods focus on leveraging image generation and unsupervised idea to overcome sample imbalance and realize detection of defective fasteners, while learning discriminative features with deep metric learning for imbalanced fastener detection is neglected. Thus, we study the variants of deep metric learning losses and propose a novel loss named center-triplet loss for defective fastener detection in the case of imbalanced samples. Specially, the proposed center-triplet loss can learn a center for each fastener state and this center is closer to the same fastener state than to different fastener states. In this way, the learned features are more robust and discriminative and it is beneficial to realize accurate detection of defective fasteners when samples are uneven. Extensive experiments are conducted on the constructed fastener dataset, and the results demonstrate the effectiveness and superiority of our proposed loss for the detection of imbalanced fasteners.