bluuebunny/crossref_metadata_2025_split huggingface dataset:
Zero-shot Learning of Drug Response Prediction for Preclinical Drug Screening
Authors: Hu Wenbin , Li Kun , Liu Weiwei , Luo Yong , Cai Xiantao , Du Bo 
Published: October 2023

Abstract
Conventional deep learning methods typically employ supervised learning for drug response prediction (DRP). This entails dependence on labeled response data from drugs for model training. However, practical applications in the preclinical drug screening phase demand that DRP models predict responses for novel compounds, often with unknown drug responses. This presents a challenge, rendering supervised deep learning methods unsuitable for such scenarios. In this paper, we propose a zero-shot learning solution for the DRP task in preclinical drug screening. Specifically, we propose a Multi-branch Multi-Source Domain Adaptation Test Enhancement Plug-in, called MSDA. MSDA can be seamlessly integrated with conventional DRP methods, learning invariant features from the prior response data of similar drugs to enhance real-time predictions of unlabeled compounds. We conducted experiments using the GDSCv2 and CellMiner datasets. The results demonstrate that MSDA efficiently predicts drug responses for novel compounds, leading to a general performance improvement of 5-10\% in the preclinical drug screening phase. The significance of this solution resides in its potential to accelerate the drug discovery process, improve drug candidate assessment, and facilitate the success of drug discovery.
Lung Nodule Malignancy Classification with Associated Pulmonary Fibrosis using 3D Attention-gated Convolutional Network with CT scans
Authors: Liu Yucheng , Hsu Hao-Yun , Lin Tiffany , Peng Boyu , Saqi Anjali , Salvatore Mary M. , Jambawalikar Sachin R. 
Published: October 2023

Abstract

Background Chest Computed tomography (CT) scans detect lung nodules and assess pulmonary fibrosis. While pulmonary fibrosis indicates increased lung cancer risk, current clinical practice characterizes nodule risk of malignancy based on nodule size and smoking history; little consideration is given to the fibrotic microenvironment. Purpose To evaluate the effect of incorporating fibrotic microenvironment into classifying malignancy of lung nodules in chest CT images using deep learning techniques. Materials and Methods We developed a visualizable 3D classification model trained with in-house CT dataset for the nodule malignancy classification task. Three slightly-modified datasets were created: 1) nodule alone (microenvironment removed), 2) nodule with surrounding lung microenvironment, and 3) nodule in microenvironment with semantic fibrosis metadata. For each of the models, 10-fold cross-validation was performed. Results were evaluated using quantitative measures, such as accuracy, sensitivity, specificity, and area-under-curve (AUC), as well as qualitative assessments, such as attention maps and class activation maps (CAM). Results The classification model trained with nodule alone achieved 75.61% accuracy, 50.00% sensitivity, 88.46% specificity, and 0.78 AUC; the model trained with nodule and microenvironment achieved 79.03% accuracy, 65.46% sensitivity, 85.86% specificity, and 0.84 AUC. The model trained with additional semantic fibrosis metadata achieved 80.84% accuracy, 74.67% sensitivity, 84.95% specificity, and 0.89 AUC. Our visual evaluation of attention maps and CAM suggested that both the nodules and the microenvironment contributed to the task. Conclusion The nodule malignancy classification performance was found to be improving with microenvironment data. Further improvement was found when incorporating semantic fibrosis information.
Unsupervised physics-informed neural network in reaction-diffusion biology models (Ulcerative colitis and Crohn’s disease cases) A preliminary study
Authors: Rebai Ahmed , Boukhris Louay , Toujani Radhi , Gueddiche Ahmed , Banna Fayad Ali , Souissi Fares , Lasram Ahmed , Rayana Elyes Ben , Zaag Hatem 
Published: October 2023

Abstract
We propose to explore the potential of physics-informed neural networks (PINNs) in solving a class of partial differential equations (PDEs) used to model the propagation of chronic inflammatory bowel diseases, such as Crohn’s disease and ulcerative colitis. An unsupervised approach was privileged during the deep neural network training. Given the complexity of the underlying biological system, characterized by intricate feedback loops and limited availability of high-quality data, the aim of this study is to explore the potential of PINNs in solving PDEs. In addition to providing this exploratory assessment, we also aim to emphasize the principles of reproducibility and transparency in our approach, with a specific focus on ensuring the robustness and generalizability through the use of artificial intelligence. We will quantify the relevance of the PINN method with several linear and non-linear PDEs in relation to biology. However, it is important to note that the final solution is dependent on the initial conditions, chosen boundary conditions, and neural network architectures.
Do Genres in Extensive Reading Produce Dissimilar Results? –A Case of Chinese Junior High School Students
Authors: Zeng Ling , Luo Shaoqian 
Published: October 2023

Abstract

Extensive reading has been widely implemented and investigated in the learning of English as a foreign language, but the study of genre effects in extensive reading has been rarely touched. While fiction reading is associated with intrinsic motivation, nonfiction deserves inclusion as it is vital for learners’ success in higher education and career. In the present study, a pre- and post-test research design was exploited in a 16-week reading program with 63 junior high school students in Beijing, who were from two intact homogeneous classes reading informational texts (namely, newspapers & magazines, NM) and fictional graded readers (GR) respectively, and their gains in reading, writing ability, and reading attitude were compared. Results show that both groups had gains in reading, writing ability, and reading attitude from pre- to posttest, and Group NM had more gains in reading and writing ability, but only outperformed Group GR significantly in writing improvement. The results are explained by genre, experiment design, and reading style-related factors. Findings of this research suggest the necessity of including informational texts in an extensive reading program for EFL learners, and provide a deeper understanding of the relationship between different degrees of extensive reading and their effects.
Thermal image processing: A novel approach to predicting honey quality
Authors: Kibar Mustafa 
Published: October 2023

Abstract
This study aimed to estimate the proline and Brix content of honey based on the color properties. In the study, 20 honey samples from Türkiye were used, the proline and Brix content of which were determined using the IHC method and the refractometer. The color properties were determined using a spectrophotometer and the ImageJ program, which processed thermal images of honey. Brix and proline estimations were made using the classification and regression trees (CART) algorithm by taking parent node 6, child node 3 and cross validation 5. In the study, the mean Brix and proline values of honeys were 83.2 ± 0.79% and 678.83 ± 192.16 mg/kg, respectively. Analysis of the T-test revealed that there were statistical differences between high and low Brix honeys in terms of L and b values as measured by the spectrophotometer (p < 0.05). The dark and bluish honeys had a lower Brix value and therefore lower sugar content than light and yellowish honeys. In the CART, sensitivity, specificity, and accuracy were 100.00, 0.9091 and 0.9500 for proline and 100.00, 100.00 and 100.00 for Brix, respectively (p < 0.01). The L and b* values of high-proline honeys were higher and lower than 48.143 and 35.416, respectively. Low-Brix honeys had an L and a* value below 55.860 and 53.660 respectively and freshly harvested. As a result, high-proline honeys are whitish and bluish, and low-Brix honeys are more blackish and greenish. However, in order to determine the quality of honey based on color parameters, more extensive studies on honeys from different origins are required.
Photostability of indium phthalocyanines in organic solvents
Authors: Dyrda Gabriela 
Published: October 2023

Abstract
The effects of the macrocycle structure and the medium nature on photodecomposition under UV irradiation of different Indium phthalocyanines: the diindium tripledecker phthalocyanine, In2Pc3 (1), sandwich indium phthalocyanine, InPc2 (2) and iodoindium phthalocyanine, InPcI (3) in benzene, N,N-dimethylformamide (DMF), dimethyl sulfoxide (DMSO), dichloromethane (DCM) and 1-chloronaphtalene has been studied. The rate of decay of absorption is explained by a decomposition reaction which is of first-order kinetics with respect to the phthalocyanines concentration. In general, in the present of ligand I− in phthalocyanine InPcI enhance the rate of decomposition.
The effectiveness of glucocorticoid treatment in post-COVID- 19 pulmonary involvement
Authors: Mizera Jan , Genzor Samuel , Sova Milan , Stanke Ladislav , Burget Radim , Jakubec Petr , Vykopal Martin , Pobeha Pavol , Zapletalová Jana 
Published: October 2023

Abstract
Rationale: Persistent respiratory symptoms following Coronavirus Disease 2019 (COVID-19) are associated with residual radiological changes in lung parenchyma, with a risk of development into lung fibrosis; and with impaired pulmonary function. Previous studies hinted the possible efficacy of corticosteroids (CS) in facilitating the resolution of post-COVID residual changes in the lungs, but the available data is limited.
Aim: To evaluate the effects of CS treatment in post-COVID respiratory syndrome patients.
Patients and methods: Post-COVID patients were recruited into a prospective single-center observational study and scheduled for an initial (V1) and follow-up visit (V2) at the Department of Respiratory Medicine and Tuberculosis, University Hospital Olomouc, comprising of pulmonary function testing, chest x-ray, and complex clinical examination. The decision to administer CS or maintain watchful waiting (WW) was in line with Czech national guidelines.
Results: The study involved 2729 COVID-19 survivors (45.7% male; mean age: 54.6). From 2090 patients with complete data, the largest proportion of patients with persistent lung abnormalities on imaging studies was seen in moderate (14.5%) and severe (31.4%) COVID-19 groups. The patients selected for CS therapy showed significantly worse radiological and functional impairment at V1. At V2, the rates of subjective and radiological improvement, and dynamic lung volumes, were similar in CS and WW groups. However, static lung volumes and lung diffusion capacity for carbon monoxide (DLCO) improved significantly more in the CS group, with the vital capacity (VC) increasing by a mean of 493.72 ml (13.01 %predicted) and DLCO by a mean of 9.19 %predicted (p <0.0001).
Conclusion: While the rates of subjective and radiological improvement were similar between the study groups, the CS group saw significantly better rates of improvements of static lung volumes and DLCO. Our findings suggest that glucocorticoid therapy could benefit selected patients with persistent dyspnea, significant radiological changes, and decreased DLCO.
Comparing sleep measures in cancer survivors: Self-reported sleep diary versus objective wearable sleep tracker
Authors: Li Xiaotong , Mao Jun J. , Garland Sheila N. , Root James , Li Susan Q. , Ahles Tim , Liou Kevin T. 
Published: October 2023

Abstract

Purpose
Cancer survivors are increasingly using wearable fitness trackers, but it's unclear if they match traditional self-reported sleep diaries. We aimed to compare sleep data from Fitbit and the Consensus Sleep Diary (CSD) in this group.
Methods
We analyzed data from two randomized clinical trials, using both CSD and Fitbit to collect sleep outcomes: total sleep time (TST), wake time after sleep onset (WASO), number of awakenings (NWAK), time in bed (TIB) and sleep efficiency (SE). Insomnia severity was measured by Insomnia Severity Index (ISI). We used the Wilcoxon Singed Ranks Test, Spearman’s rank correlation coefficients, and the Mann-Whitney Test to compare sleep outcomes and assess their ability to distinguish insomnia severity levels between CSD and Fitbit data.
Results
Among 62 participants, compared to CSD, Fitbit recorded longer TST by an average of 14.6 (SD = 84.9) minutes, longer WASO by an average of 28.7 (SD = 40.5) minutes, more NWAK by an average of 16.7 (SD = 6.6) times per night, and higher SE by an average of 7.1% (SD = 14.4); but shorter TIB by an average of 24.4 (SD = 71.5) minutes. All the differences were statistically significant (all p < 0.05), except for TST (p = 0.38). Moderate correlations were found for TST (r = 0.41, p = 0.001) and TIB (r = 0.44, p < 0.001). Compared to no/mild insomnia group, participants with clinical insomnia reported more NWAK (p = 0.009) and lower SE (p = 0.029) as measured by CSD, but Fitbit outcomes didn’t.
Conclusions
TST was the only similar outcome between Fitbit and CSD. Our study highlights the advantages, disadvantages, and clinical utilization of sleep trackers in oncology.
Implementing I-CBT (Moodgym) for African Students with Symptoms of Low Mood During the Covid-19 Pandemic: A Qualitative Feasibilty Study
Authors: Ncheka Joyce Msumba , Menon J. Anitha , Davies E Bethan , Paul Ravi , Mwaba Sidney O C , Mudenda John , Wharrad Heather , Tak Harsa , Glazebrook Cris 
Published: October 2023

Abstract
Background
Online therapies have been shown to be effective in improving students’ mental health. They are cost-effective and therefore have particular advantages in low-income countries like Zambia where mental health resources are limited. This study aimed to explore the perceived impact of the COVID-19 pandemic and the feasibility of implementing an iCBT intervention (‘moodgym’) to improve resilience in vulnerable Zambian students.
Methods The study was a qualitative interview study. Participants identifying as having symptoms of low mood and completing a baseline, online survey (n=620) had the option to volunteer for a semi-structured interview to explore views about their experience of the pandemic and the acceptability and perceived benefits and limitations of using moodgym.
Results A total of 50 students (n= 24 female, n=26 male) participated in the study. One theme with 4 sub-themes, captured the severe emotional and social impact of the COVID-19 pandemic. A second, very strong theme, with 5 sub-themes, reflected the considerable negative effects of the pandemic on the students’ educational experience. This included the challenges of online learning. The third theme, with three subthemes, captured the benefits and acceptability of moodgym, particularly in terms of understanding the relationship between thoughts and feelings and improving academic performance.
The fourth theme described the technical difficulties experienced by students in attempting to use moodgym.
Conclusion COVID-19 caused fear and impacted wellbeing in vulnerable students and severely impaired the quality of students’ educational experience. The findings suggest that moodgym might be a valuable support to students in a low income country.
Multimodality Imaging of Medical Resins: a Comprehensive Research Catalog
Authors: Fu Weibo , Way Ashley , Hernandez Mauricio , Meyer Travis 
Published: October 2023

Abstract
Background:
Additive manufacturing describes the process of creating and printing three-dimensional products. In medicine, stereolithography remains one of the most commonly used additive manufacturing techniques. At present, few studies have sought to quantify the imaging properties of stereolithography resins, which would allow for standardization and streamlining of medical research in additive manufacturing. The aim of this study is to quantify and catalog imaging properties of commercially available FormLabs stereolithography resins via computer tomography, magnetic resonance imaging, and ultrasound.
Methods:
Fourteen unique stereolithography resins offered by Formlabs (Somerset, MA) were selected based on their clinical utility. Each resin was subject to a tri-modality investigation through computer tomography, magnetic resonance imaging, and ultrasound imaging. Image analysis was performed by two separate board-certified radiologists using the picture archiving and communication system. Results of this analysis were aggregated and organized onto data tables.
Results:
Of the fourteen resins evaluated by computed tomography, twelve were found to have radiological properties that were within one standard deviation (σ) of a known type of body tissue, in Hounsfield Units. When the same fourteen resins were evaluated by magnetic resonance imaging, little variability was observed between each resin in image intensity. Of the fourteen resins evaluated through ultrasound, imaging revealed little variability with no significant points of comparison with human tissue.
Conclusion:
Our investigation confirms that computed tomography is an ideal method for comparing imaging properties of stereolithography resins with those of human tissue. A comprehensive catalog of imaging properties for stereolithography resins allows clinical investigators to standardize future research studies, decreasing inter-observer variability and improving research outcomes for new devices and phantom models in medicine.
Up to 200% underestimation of cumulative methane emission from individual landfills uncovers tens of Tg of overlooked annual emission worldwide
Authors: Wang Yao , Yin Ke , Fang Mingliang , Guo Yuliang , Pi Xiaoqing , Wang Yijie , He Hongping , Lou Ziyang , Fei Xunchang 
Published: October 2023

Abstract
Landfill methane (CH4) emissions account for ~ 10% of all anthropogenic CH4 emissions globally, amounting to ~ 50 Tg/year. Contrasted by “top-down” atmospheric inversion results, the mainstream “bottom-up” emission inventories, which use the Intergovernmental Panel on Climate Change’s (IPCC) model, exhibit significant bias due to inaccurate a priori decay constant (k) estimations. We improved the k estimation method by incorporating composition- and environment-specific corrections, which are readily integrated into the IPCC’s model. We demonstrate that the accuracies of CH4 emission predictions are significantly improved by using the corrected k values, which are benchmarked against the atmospheric inversion results. We extend the emission estimations to landfills worldwide and reveal up to 209% underestimation in individual landfills and several tens of Tg/year of potentially overlooked CH4 emission globally. Our findings highlight the importance of prioritizing landfill CH4 emission monitoring and reduction as one of the most cost-effective mitigation options to achieve current climate goals.
Response of two aquatic plant species to metallic nanoparticles and their potential for phytoremediation
Authors: Ebrahimbabaie Parisa , Smith Anthony , Zahran Elsayed M. , Jones James , Pichtel John 
Published: October 2023

Abstract

Certain plants have been identified with the capability to take up metallic and metal oxide nanoparticles (ENPs), thus suggesting their potential role in phytoremediation. The reported study evaluated the response of two aquatic plants, sedge (Carex rostrata) and cattail (Typha latifolia), on their exposure to Ag, ZnO, TiO2, BiVO4/Pd, and Cu2O/Pd nanoparticles over 15 weeks. Plant physiological responses (chlorophyll content, carbonic anhydrase (CA) activity, leaf area, production of new shoots, and root length) varied according to the plant species and ENP type. By week 15, sedge treated with BiVO4/Pd ENP had a high chlorophyll content and increased CA activity and leaf area compared to the control. In contrast, cattail had reduced chlorophyll levels and number of new shoots when exposed to exogenously applied BiVO4/Pd. Highest sedge chlorophyll content at week 15 was measured in the mixed-ENPs, Cu2O, and Ag (53.2, 35.8, and 32.7%, respectively, greater than the control). The ZnO ENPs were beneficial for sedge chlorophyll content, cattail shoot production and root length. The mixed-ENPs treatment imparted positive effects to several sedge properties (CA and new shoots) and cattail (chlorophyll, leaf area, and root length). Additional research is needed to assess the capabilities of different aquatic plant species to tolerate metal-based ENPs for remediation purposes.
The implication of Brexit on the financial market of the European Union and its regulation – legal and institutional aspects
Authors: Wicha Agnieszka 
Published: October 2023

The Article tackled with the topic of the impact of Brexit on the EU financial market. The most important changes were identified and defined. Among different types of implications the Author chose those which were important for the shape of the EU financial market. The Article identified all crucial changes in the EU law regulating financial market. In the Article there was the analysis of the single passport rule in the context of Brexit and the sability of equivalency mechanism in this context. The changes in BMR and EMIR implied by Brexit were analysed.
Migration Policy is Heading Down a Beaten Track. Comment on the Judgment of the European Court of Human Rights in the R.R. and others v. Hungary Case of 5 July 2021
Authors: Kun-Buczko Magdalena 
Published: October 2023

In July 2021, the Grand Chamber of the European Court of Human Rights (ECHR) delivered a judgment in the R.R. v. Hungary case which perpetuates previous case law on obligations in providing migrants with international protection. The judgment is also of critical importance in view of the Common European Asylum System.
The ECHR has confirmed that Hungary had failed to full its obligations in providing migrants with international protection especially when it comes to the length of time applicants were deprived of their liberty and the extent of the protection afforded to the pregnant applicant and her minors.
Социальная активность студентов в университете: ее проявления, значение и взаимосвязь с коммуникативными навыками и установками
Authors: Вашумирская Дарья В. 
Published: October 2023

Введение. Социальная активность в рамках университетской жизни включает в себя совокупность отношений студентов, задействованных в образовательном процессе, научной деятельности, внеучебных мероприятиях, самоуправлении и межличностном общении. Актуальность изучения социальной активности обусловлена современными реалиями: общество справляется с последствиями пандемии, а университеты перешли из дистанционного в очный формат обучения. Изучение роли социальной активности в учебной деятельности позволит ответить на вопрос: «Нужно ли мотивировать студентов на общение и активную социальную жизнь?». Цель исследования – определить влияние социальной активности студентов на их успешность в ученой деятельности. Методы. В исследовании приняли участие 75 студентов в возрасте от 17 до 24 лет. Нами было использовано авторское анкетирование, направленное на определение сходства и различия между социально активными и менее социально активными студентами. Для изучения различий между ними были выбраны следующие методики: «Диагностика типа коммуникативной установки» и «Коммуникативные и организаторские склонности (КОС)». Обработка эмпирических данных проводилась с помощью математической статистика (количественный анализ, корреляционный анализ по Спирмену). Результаты. Были выявлено, что общение с другими студентами влияет на чувство принадлежности к университету, и на учебную успеваемость. Степень общения оказалась отрицательно связана с общим уровнем негативных установок и положительно с уровнем коммуникативных навыков. Обсуждение результатов. В ходе анализа исследований установлено, что социальная активность студентов положительно влияет на их успеваемость в учебе, а также на их чувство принадлежности к университету. Можно сделать вывод, что необходимо способствовать студенческой социальной активности в рамках университетской жизни с помощью улучшения коммуникативных навыков студентов.