bluuebunny/crossref_metadata_2025_split huggingface dataset:
Assessment and Data-Based Decisions in Contemporary Classrooms
Authors: Rao Dr. Shaila M. 
Published: August 2023

AbstractIn the United States, the No Child Left Behind Act (NCLB) in 2001 and Individuals with Disabilities Education Act (IDEA) in 2004 have together made it possible for students with diverse educational needs to be educated in general education classrooms. To be able to address students’ needs efficiently and effectively, teachers need to collect data on students’ current level of performance, design instruction using evidence-based strategies, implement instruction, and make data-based decisions to evaluate effectiveness of their instruction by continuously monitoring student achievement. Using four hypothetical cases, this paper illustrates use of curriculum-based measurement (CBM), a research validated approach, to assess and progress monitor students’ performance in reading and mathematics, and also illustrates with examples how the process can help teachers make required data-based decisions during the progress monitoring phase.
The Social Networking Sites (SNS) Facebook and OpenStudy as Student Learning Forum
Authors: Chia Janet 
Published: August 2023

AbstractEven though the popularity of Social Networking Sites has proliferated over the years, however, its educational affiliation has gone largely unexplored. Therefore, this paper primarily examined how information was communicated on the Social Networking Sites (SNS), Facebook and OpenStudy, as part of Liverpool John Moores University Summer Semester 2012 Mass Communication students’ learning experience. It studied the effect of students’ educational usage of Social Networking Sites, the way in which students’ learning resources were shared and exchanged online in a Facebook closed group named “LJMU Mass Comm Union’12”. The appeal and motivational strategies adopted by Social Networking Sites through elements of edutainment which ’repackaged’ online learning as a fun and leisure activity was also considered.
Teaching the Structures of Academic Writing through Peer Review: A Study on the Beginners of English Language Courses at BRAC University
Authors: Chowdhury Md. Aftab Uddin , Akteruzzaman Mohammad 
Published: August 2023

AbstractSubstantial peer feedback of the students through peer review in the context of EFL or ESL can help them become skilled at different structures and strategies of academic writing in English rather than receiving feedback from teachers in the classroom. However, most of the students at English language classes in Bangladesh do not appreciate the significance of following the structures of academic writing from the lectures of the respective teachers immediately. On the other hand, most of the English language instructors in their classes are not used to encouraging their students to provide peer feedback through peer review. Therefore, this paper will be focusing on the issues regarding how peer review can be utilized for the beginners of English language courses in terms of making them aware of the structures of academic writing. Moreover, this paper will make an attempt to find out whether peer review makes them a better writer, a more rational thinker or a more critical appreciator of peers’ writings. At last, this paper will present some recommendations on how peer review can develop the students’ creativity while producing thought provoking and critical comments on their peers’ writing.
Prevalence of Hepatitis D Virus among Hepatitis B Positive Blood Donors in Port Harcourt, Nigeria
Authors: Nwika Goodnews Nkabari , Awortu Jeremiah Zaccheus , Mgbeoma Eze Evelyn 
Published: August 2023

Introduction: The Prevalence of Hepatitis D Virus among Blood Donors in Port Harcourt, Nigeria is a maiden epidemiological study of Hepatitis D or delta hepatitis among the donors’ population in Port Harcourt, Rivers State. Hepatitis D (Hepatitis Delta) is a disease caused by the hepatitis D virus (HDV). It is considered to be a sub viral satellite because it can propagate only in the presence of the hepatitis B virus. The prevalence of HDV in Port Harcourt has not been reported; hence this study, bridge that knowledge gap.
Methods: Using a qualitative cross sectional study design, a general serological screening test was performed on a total of 300 blood donors recruited; 222(74.00%) males and 78 (26.00%) females, all within 20-59years. Of this number, 86(28.70%) were positive for HBV while 214(71.30%) Hepatitis B negative served as control. Samples collected were analysed at blood bank unit of the Haematology Department of the Rivers State University Teaching Hospital, Port Harcourt (RSUTH). Hepatitis B surface antigen (HBsAg), and anti-hepatitis D antibodies (anti-HDV) for the presence of HBV and HDV infections were detected by one step Hepatitis B surface antigen (HBsAg) in serum, and enzyme linked immunosorbent assay for the detection of HDV as described by the www.elabScience.com (16).
Results: Of the 300 subjects, 86(28.6%) were positive for Hepatitis B surface antigen (HBsAg). Of these HBV positive subject, 9(10.4%) were positive for Hepatitis D virus (HDV). Age and gender of the study participants were not found to be risk factors for its prevalence (p > 0.05). There was no statistically significant difference in the PCV of those infected when compared with the non infected group. Using Pearson correlation analysis, HDV was not found to associate significantly with PCV (r = 0.2849, p > 0.05). This study recorded HDV prevalence rate of 10.4% among the HBsAg positive blood donors.
Conclusion and Implications for Translation: There is a 10.4% prevalence of HDV among the HBsAg positive blood donors. To increase the safety level of blood products, the screening process should therefore be extended to the HDV.
Magneto‐Optical Properties of Electron Gas in a Chain of Planar Quantum Rings: Effect of Screening on the Signature of Quantum Phase Interference
Authors: Harutyunyan Armen , Mughnetsyan Vram , Kirakosyan Albert , Gudmundsson Vidar 
Published: January 2025

AbstractThe equilibrium properties and interminiband transitions for Hartree‐interacting 2D electron gas in a 1D chain of planar quantum rings subjected to a transverse homogeneous magnetic field are examined. The proposed analytical models for the modulation potential and the basis wave‐function reflect the symmetry and the topology of the system allowing to get high accuracy results. The calculated dependencies of the electronic band structure versus magnetic field show two detached minibands in the region of low energies, while higher minibands manifest crossings and anticrossings. The existence of highly degenerate energy levels (miniband nodes) for certain values of magnetic field is revealed. The miniband nodes are preserved when taking into account the Coulomb interaction of the electrons. The interaction causes both an upward shift and broadening of minibands, while also shifting the nodes to higher magnetic fields. The miniband nodes have their signature in the magnetization of the electron gas and in the interminiband transitions. The number of electrons per a unite cell of the system has a strong impact on the current density distribution, magnetization and the oscillator strength. The obtained results open new opportunities for a flexible manipulation of magneto‐optical properties of future devices operating in far‐infrared and THz regimes.
Optimization of Culture Medium Ingredients and Culture Conditions for Bacteriocin Production in Lactococcus lactis NCU036019
Authors: Wei Ziqi , Fan Pengrong , Li Bo , Madjirebaye Philippe , Peng Zhen , Xiong Tao 
Published: January 2025

ABSTRACTBacteriocin lactococcin036019 was identified and characterized from Lactococcus lactis NCU036019, which displayed significant antibacterial activity toward foodborne pathogenic bacteria Staphylococcus aureus under various conditions. However, the in situ low‐level expression of lactococcin036019 severely limited its wide application in food industry. In this study, we optimized the medium ingredients and culture conditions of L. lactis NCU036019 for maximum production of lactococcin036019. The effects of different carbon sources, nitrogen sources, inorganic salts, growth factors, surfactants, and buffer salts on the production of bacteriocin were studied using antibacterial titer and diameter of inhibitory zone as evaluation indexes. Through single‐factor experiments, Plackett‐Burman (PB) experiment, steepest ascent experiment and response surface methodology, yeast extract, zinc sulfate, sodium acetate, mannitol, Tween‐80, and dipotassium hydrogen phosphate were identified to display significant influence on the production of bacteriocin. By optimizing Man Rogosa and Sharpe (MRS) culture medium ingredients, the antibacterial activity of lactococcin036019 in the cell‐free supernatant raised from 46.19 to 300.14 Au/mL, namely, 6.5 times increased. Furthermore, the culture conditions, such as inoculation amount, culture time, and culture temperature, were optimized, and this further increased the antibacterial activity to 409 Au/mL, namely, 8.8 times increased. This study investigated the effects of culture media and conditions on the production of lactococcin036019, and they were optimized for a maximum harvest of bacteriocin, and the significant increase of bacteriocin production in L. lactis NCU036019 facilitates the application of the antibacterial substance in future work.
An efficient and industrially feasible process for purification and immobilization of orange‐peel‐based lipase for biocatalytic applications
Authors: Ghutake Sahil , Gharge Varunraj , Pawar Hitesh 
Published: January 2025

AbstractLipase is an important enzyme with wide industrial applications in various sectors. The present study focuses on the development of an efficient and industrially feasible process for the purification and immobilization of orange‐peel‐based lipase. The integration of ultrafiltration (UF), adsorptive chromatography, and immobilization on synthetic resins offers an efficient method for producing purified, immobilized lipases. Ultrafiltration membranes with varying molecular weight cutoffs were evaluated for concentrating crude lipase. Among the membranes tested, the 5 kDa UF membrane demonstrated over 94% enzyme activity retention. Various microporous adsorbents (hydrophilic, hydrophobic and ion exchange) were tested for removing color impurities from concentrated crude lipase. The hydrophobic adsorbent achieved over 90% removal of color components. Overall, the integration of UF membranes and adsorptive chromatography showed a 2.29‐fold increase in production efficiency. Different microporous adsorbents were tested for the immobilization of purified lipase to produce an immobilized lipase biocatalyst. The use of hydrophobic adsorbents with lower porosity and a larger surface provides maximum binding efficiency (95%). The characterization study of purified lipase was conducted by using Fourier transform infrared (FTIR) spectroscopy and sodium dodecyl sulfate‐polyacrylamide gel electrophoresis (SDS‐PAGE). The purification process yielded a lipase enzyme concentration of 0.28 mg mL−1 with a specific activity of 250.54 U mL−1, achieving an approximately 2.29‐fold increase in purity. This study presents an efficient and industrially viable method for the purification and immobilization of lipases, enabling their use in biocatalytic applications.
Research Advances on Lithium‐Ion Batteries Calendar Life Prognostic Models
Authors: Pan Tao , Li Yujie , Yao Ziqing , Liu Shuangke , Zhu Yuhao , Wang Xuanjun , Wang Jian , Zheng Chunman , Sun Weiwei 
Published: January 2025

ABSTRACTIn military reserve power supplies, there is an urgent need for superior secondary batteries to replace conventional primary batteries, and lithium‐ion batteries (LIBs) emerge as one of the best choices due to their exceptional performance. The life of LIBs includes cycle life and calendar life, with calendar life spanning from years to decades. Accurate prediction of calendar life is crucial for optimizing the deployment and maintenance of LIBs in military applications. Model‐based prognostics are usually established to estimate calendar life using accelerated aging methods under various storage conditions. This review firstly outlines the general prognostic workflow for calendar life of LIBs, analyzes degradation mechanisms, and summarizes influencing factors; then, we introduce calendar life prognostic models, evolving from simplistic empirical models (EMs) to nonempirical mechanistic models (MMs) based on LIB calendar aging knowledge and then to traditional hybrid empirical‐mechanistic models (trad‐EMMs). Finally, the data‐driven models (DDMs) based on machine learning (ML) are discussed due to the limitation of the traditional methods, evolving from pure data‐driven to knowledge‐integrated models and establishing a comprehensive framework for calendar life assessment. To the best of our knowledge, this paper presents the first comprehensive review in this field, summarizing calendar life prognostic models of LIBs and offering some insights into future model development directions. Model‐based prognostics can facilitate researchers in calendar aging analysis and calendar life prolongation, thereby better serving the application of LIBs in national economic life.
Effect of Occlusal Scheme and Bone‐Level Implant Number and Position on Stress Distribution in Kennedy Class II Implant‐Assisted Removable Partial Dentures: A 3D Finite Element Analysis
Authors: Barati Solmaz , Ghodsi Safoura , Zeighami Somayeh 
Published: January 2025

ABSTRACTObjectivesTo assess the effect of occlusion and implant number/position on stress distribution in Kennedy Class II implant‐assisted removable partial denture (IARPD).Materials and MethodsIARPDs were designed in six models: with one implant (bone level with a platform of 4 mm and length of 10 mm) at the site of (I) canine, (II) between first and second premolars, (III) first molar, (IV) second molar, or two implants at the sites of (V) canine‐first molar, and (VI) canine‐second molar. A conventional RPD served as control. Loads were applied according to the group function (GF) (500N load was applied to the left canine/premolar/molar teeth in the ratio of 1:1:2) or canine guidance (CG) (125N load was to the canine tooth) occlusions. Maximum displacement and Von Mises Stress in different components were analyzed by finite element analysis (FEA).ResultsThe control model showed the highest displacement followed by the IARPD with a canine implant in both occlusal schemes. In GF, the maximum and minimum jaw stress were recorded in IARPDs with canine implants (16.45 MPa) and canine‐first molar implants (13.47 MPa), respectively. In CG, the maximum and minimum jaw stress was recorded in IARPD with first/second premolar implant (15.91 MPa) and canine‐first molar implants (12.38 MPa), respectively. The highest stress in resin, framework, and implant(s) was noted in IARPD with canine implant in both schemes. The lowest stress in the implant(s) was recorded in IARPD with canine‐second molar implants in GP and IARPD with canine‐first molar implants in CG.ConclusionDental implants reduced the total displacement of IARPDs, increased stress in mechanical components, and did not affect stress distribution in biological components. Insertion of two implants decreased implant stress. The GP scheme caused greater stress on mechanical components.
Left ventricular function improvement during angiotensin receptor–neprilysin inhibitor treatment in a cohort of HFrEF/HFmrEF patients
Authors: Appenzeller Florian , Harm Tobias , Sigle Manuel , Aidery Parwez , Kreisselmeier Klaus‐Peter , Baas Livia , Goldschmied Andreas , Gawaz Meinrad Paul , Müller Karin Anne Lydia 
Published: January 2025

AbstractAimsHeart failure (HF) patients may lack improvement of left ventricular (LV) ejection fraction (LVEF) despite optimal HF medication comprising an angiotensin receptor–neprilysin inhibitor (ARNI). Therefore, we aimed to identify key predictors for LV functional enhancement and prognostic reverse cardiac remodelling in HF patients on ARNI treatment.MethodsWe retrospectively analysed 294 consecutive patients with HF with reduced (HFrEF) or mildly reduced (HFmrEF) ejection fraction in our ‘EnTruth’ patient registry. LVEF was determined by echocardiography at initiation of ARNI and at 12 months of follow‐up. We assessed the predictive value of clinically relevant patient‐, HF‐ and treatment‐related parameters in regard to changes in LVEF and all‐cause mortality using medoid clustering and the XGBoost machine learning algorithm.ResultsCluster analysis integrating clinically relevant patient characteristics unveiled four characteristic sub‐phenotypes of patients with HFrEF and HFmrEF, respectively. Distinct clusters exhibit a strong (P < 0.05) therapeutic response to ARNI treatment and enhanced LV function. Key patient criteria, such as duration and aetiology of HF, renal function and de novo ARNI treatment, were significantly (P < 0.05) associated with change of LVEF and independently predicted cardiac remodelling. By training various machine learning models on relevant clinical parameters, stratification of LVEF improvement by XGBoost resulted in a high prediction accuracy. The stratification of patients with HFrEF [area under the receiver operating characteristic curve (AUC) = 0.77] and HFmrEF (AUC = 0.70) led to an increased diagnostic accuracy of LVEF improvement in the validation cohort. Using machine learning, the likelihood of cardiac remodelling following ARNI treatment, as indicated by our newly established EnTruth score, was directly associated with absolute LVEF improvement in both HFrEF (r = 0.51, P < 0.0001) and HFmrEF (r = 0.42, P = 0.001). Ultimately, patients with HFrEF and a high EnTruth score have a lower risk of all‐cause mortality (P < 0.05 in survival analysis).ConclusionsRecognition of essential clinical factors by integrating machine learning and cluster analyses may help to identify HF patients benefiting from improvement of LVEF following ARNI treatment. Early identification of those patients with a high response to ARNI treatment may allow a more refined selection of patients benefiting from an early escalation of HF treatment or interventional therapy.
Predicting survival in patients with severe heart failure: Risk score validation in the HELP‐HF cohort
Authors: Chiarito Mauro , Stolfo Davide , Villaschi Alessandro , Sartori Samantha , Baldetti Luca , Lombardi Carlo Mario , Adamo Marianna , Loiacono Ferdinando , Sammartino Antonio Maria , Riccardi Mauro , Tomasoni Daniela , Inciardi Riccardo Maria , Maccallini Marta , Gasparini Gaia , Grossi Benedetta , Contessi Stefano , Cocianni Daniele , Perotto Maria , Barone Giuseppe , Merlo Marco , Cappelletti Alberto Maria , Sinagra Gianfranco , Pini Daniela , Metra Marco , Pagnesi Matteo 
Published: January 2025

AbstractAimsAccurate selection of patients with severe heart failure (HF) who might benefit from advanced therapies is crucial. The present study investigates the performance of the available risk scores aimed at predicting the risk of mortality in patients with severe HF.Methods and resultsThe risk of 1‐year mortality was estimated in patients with severe HF enrolled in the HELP‐HF cohort according to the MAGGIC, 3‐CHF, ADHF/NT‐proBNP, and GWTG‐HF risk scores, the number of criteria of the 2018 HFA‐ESC definition of advanced HF, I NEED HELP markers, domains fulfilled of the 2019 HFA‐ESC definition of frailty, the frailty index, and the INTERMACS profile. In addition, we tested the performance of different machine learning (ML)‐based models to predict 1‐year mortality. At 1‐year follow‐up, 265 patients (23.1%) died. The prognostic accuracy, tested in the subgroup of patients with completeness of all data regarding the variables included in the scores (497/1149 patients), resulted moderate for MAGGIC, GWTG‐HF, and ADHF/NT‐proBNP scores (area under the curve [AUC] ≥0.70) and only poor for the other tools. All the scores lost accuracy in estimating the rate of 1‐year mortality in patients at the highest risk. Support vector machine‐based model had the best AUC among ML‐based models, slightly outperforming most of the tested risk scores.ConclusionMost of the scores used to predict the risk of mortality in HF performed poorly in real‐world patients with severe HF and provided inaccurate estimate of the risk of 1‐year mortality in patients at the highest risk. ML‐based models did not significantly outperform the currently available risk scores and their use must be validated in large cohort of patients.
Microbial Characterization of a Zambian Honey Vinegar
Authors: Cambray Garth Anton , Kalinski Jarmo‐Charles Julian 
Published: January 2025

ABSTRACTForest Fruits Organic Honey Vinegar (FFOHV) is a spontaneously fermented (yeast) and acetified (Acetic Acid Bacteria—AAB) Miombo Woodland honey vinegar developed in Zambia. Live vinegars containing live microbial cultures are marketed for their probiotic health benefits. The correlation between a well‐developed gut microbiome and human health is well studied and fermented products such as live vinegar containing AAB contribute to a healthy gut microbiome. This study details a metagenomic analysis of stable, bottled FFOHV (Zambia) alongside two commercially available live vinegar products: Bragg Organic Apple Cider Vinegar (BOACV) and Nature's Source Apple Cider Vinegar (NSACV). FFOHV contained representatives of five bacterial and nine fungal genera, compared to BOACV with two bacterial and five fungal, and NSACV containing no bacterial and six fungal genera. FFOHV and BOACV showed a dominance of Komagataeibacter bacterial species. The dominant yeast was Vanrija humicola present in all three vinegar samples. FFOHV contained greater diversity of genera, with the notable species Monascus purpureus—a microbe that produces several health‐enhancing compounds. The analysis showed that FFOHV is a microbially diverse product containing several potentially health‐enhancing microbes. Graphical Abstract Text: This study presents a metagenomic analysis of Forest Fruits Organic Honey Vinegar (FFOHV) from Zambia, compared with two commercial live cider vinegars: Bragg Organic Apple Cider Vinegar (BOACV) and Nature's Source Apple Cider Vinegar (NSACV). FFOHV exhibited a richer microbial diversity, containing five bacterial and nine fungal genera, including the health‐promoting species Monascus purpureus. Both FFOHV and BOACV were dominated by Komagataeibacter species, with Vanrija humicola as the prevalent yeast across all samples. This confirmed FFOHV's unique potential probiotic benefits.