bluuebunny/crossref_metadata_2025_split huggingface dataset:
Chinese Social Work Students’ Attitudes toward Online Social Work Services: A Q Methodology Study
Authors: Wang Qi , Li Jia , Zhou Xiaochen 
Published: March 2024

AbstractDuring the COVID-19 pandemic in China, the emergence of online social work services has garnered the attention of scholars, particularly as social work students are the future practitioners who will be responsible for delivering these services. This Q methodology study aimed to explore the perceptions and attitudes of 39 Master of Social Work (MSW) students (76.92% female, 23.08% male, Age(mean) = 22.14, SD = 0.48) from Shanghai, China, towards online social work service delivery. Participants were asked to respond to 73 Q statements. Three distinct viewpoints emerged from the factor analysis. Viewpoint One is optimistic about the prospect, believing that online delivery mode will expand the coverage of social services. Viewpoint Two is cautious due to practical constraints, recognizing the challenges that social workers and clients may encounter when participating in online social work services. Viewpoint Three is wary of privacy and ethical risks related to online social work services. The findings suggest that more education and training may be necessary to increase students’ confidence and promote online social work services, thus increasing accessibility to services for a wider population.
A New Modulator of Neuroinflammation in Diabetic Retinopathy: USP25
Authors: Hu Qiang , Zhang Xue , Peng Hongsong , Guan Jitian , Huang Zhangxin , Jiang Bo , Sun Dawei 
Published: March 2024

AbstractDiabetic retinopathy (DR) is a diabetes-associated complication that poses a threat to vision, distinguished by persistent and mild inflammation of the retinal microvasculature. The activation of microglia plays a crucial role in driving this pathological progression. Previous investigations have demonstrated that ubiquitin-specific peptidase 25 (USP25), a deubiquitinating enzyme, is involved in the regulation of immune cell activity. Nevertheless, the precise mechanisms through which USP25 contributes to the development of DR remain incompletely elucidated. Firstly, we have demonstrated the potential mechanism by which ROCKs can facilitate microglial activation and augment the synthesis of inflammatory mediators through the modulation of NF-κB signaling pathways in a high-glucose milieu. Furthermore, our study has provided novel insights by demonstrating that the regulatory role of USP25 in the secretion of proinflammatory factors is mediated through the involvement of ROCK in modulating the expression of NF-κB and facilitating the nuclear translocation of the phosphatase NF-κB. This regulatory mechanism plays a crucial role in modulating the activation of microglial cells within a high-glycemic environment. Hence, USP25 emerges as a pivotal determinant for the inflammatory activation of microglial cells, and its inhibition exhibits a dual effect of promoting retinal neuron survival while suppressing the inflammatory response in the retina. In conclusion, the promotion of diabetic retinopathy (DR) progression by USP25 is attributed to its facilitation of microglial activation induced by high glucose levels, a process mediated by the ROCK pathway. These findings highlight the importance of considering USP25 as a potential therapeutic target for the management of diabetic neuroinflammation.
Histological analysis of (antral) follicle density in ovarian cortex tissue attached to stripped endometriomas
Authors: de Koning Rozemarijn , Blikkendaal Mathijs D. , de Sousa Lopes Susana M. Chuva , van der Meeren Lotte E. , Cheng Hui , Jansen Frank Willem , Lashley Eileen E. L. O. 
Published: March 2024

Abstract
Purpose
When resecting endometriomas with the stripping technique, in the majority of cases, a thin line of adjacent ovarian cortex is attached to the endometrioma. In this study, we performed histological analysis to determine (antral) follicle density in the ovarian cortex tissue attached to stripped endometriomas and assessed patient- and surgical characteristics that could affect this.

Methods
Histological slides of previously removed endometriomas were assessed. Follicles in the attached ovarian tissue were classified according to maturation, and follicular density was determined. Immunofluorescent staining of antral follicles in a subset of endometriomas was also performed.

Results
In 90 out of 96 included endometriomas (93.7%), ovarian tissue attached to the cyst wall was observed. One thousand nine hundred forty-four follicles at different maturation stages were identified (3 follicles/mm3). Follicle density was negatively associated with age (p < 0.001). Antral follicles (< 7-mm diameter) were present in the ovarian tissue attached to 35 endometriomas (36.5%) derived from younger patients compared to endometriomas where none were detected (30 versus 35 years, p = 0.003). Antral follicle density was 1 follicle/mm3. Based on immunofluorescence, healthy antral follicles were identified in two out of four examined endometriomas.

Conclusions
Ovarian tissue attached to stripped endometriomas holds potential as a non-invasive source for antral follicles. In theory, application of IVM could be an interesting alternative FP option in young patients with endometriomas who undergo cystectomy in order to transform the surgical collateral damage to a potential oocyte source. Our results encourage future research with fresh tissue to further assess the quality and potential of these follicles.

Trial registration
Clinical Trials.gov Identifier: B21.055 (METC LDD), date of registration 12–08-2021, retrospectively registered.
Merits of photocatalytic activity of synthesized (ZnxCu(1−x)Fe2O4); x = (0–1) magnetic nanoparticles for wastewater treatment
Authors: Abuzeyad Osama H. , El-Khawaga Ahmed M. , Elsayed Mohamed A. , Gobara Mohamed , Tantawy Hesham 
Published: March 2024

AbstractSynthesis of crystalline zinc copper ferrite nanoparticles was achieved via a simple co-precipitation method. Scanning electron microscope (SEM) is utilized to give the morphological characterization of the prepared samples. A transmission electron microscope (TEM) was employed for further identification and confirmation of the particle size and morphology. Moreover, X-ray diffraction (XRD) and Fourier transformation infrared (FTIR) spectroscopy were utilized to examine crystalline structure and chemical structure, respectively. The photocatalytic performance of Zn0.5Cu0.5Fe2O4 nanoparticles under UV light was assessed by decolorization of methyl orange (MO) azo dye. The efficiency of photocatalytic degradation of 20 ppm of MO by Zn0.5Cu0.5Fe2O4 nanoparticles 15 mg was 96% after 135 min at an ambient temperature of 25 °C and pH value of 3. Further interpretation was carried out and a proposed mechanism for the MO photodegradation over Zn0.5Cu0.5Fe2O4 nanoparticles was suggested.
Electrical properties of PVC:BN nanocomposite as interfacial layer in metal-semiconductor structure
Authors: Badali Yosef 
Published: March 2024

AbstractIn this study, a comprehensive examination is assumed to investigate the influence of interfacial layers composed of polyvinyl chloride (PVC) and polyvinyl chloride-boron nitride (PVC: BN) on the electrical characteristics of the Au/n-Si structure. Two distinct structures, namely Au/PVC/n-Si (MPS1) and Au/PVC: BN/n-Si (MPS2), are fabricated for this purpose. The provided boron nitride (BN) nanostructures are analyzed using X-ray diffraction (XRD) patterns to determine their average crystalline size and surface morphology. Following the structural analysis, current-voltage (I–V) measurements are conducted over an extensive voltage range (± 3 V). Subsequently, the fundamental electrical properties of the developed Schottky structures are determined using various methods and compared. Experimental results indicate that the PVC: BN nanocomposite leads to an increase in the potential barrier height (BH), shunt resistance (Rsh), and rectifying rate (RR = IF/IR), while simultaneously decreasing the ideality factor (n), series resistance (Rs), and surface states density (Nss). It was discovered that the MS structure’s RR was 7 times lower than that of the MPS2 structure. Moreover, the energy-dependent Nss density is also derived using n(V) and ΦB0(V) functions. Based on the ln(IR)−VR0.5 profile at the reverse bias region, the Schottky-emission (SE) type conduction mechanism is effective for MS structures, whereas Poole-Frenkel-emission (PFE) is effective for MPS structures.
Quantum Machine-Based Decision Support System for the Detection of Schizophrenia from EEG Records
Authors: Aksoy Gamzepelin , Cattan Grégoire , Chakraborty Subrata , Karabatak Murat 
Published: March 2024

Abstract
Schizophrenia is a serious chronic mental disorder that significantly affects daily life. Electroencephalography (EEG), a method used to measure mental activities in the brain, is among the techniques employed in the diagnosis of schizophrenia. The symptoms of the disease typically begin in childhood and become more pronounced as one grows older. However, it can be managed with specific treatments. Computer-aided methods can be used to achieve an early diagnosis of this illness. In this study, various machine learning algorithms and the emerging technology of quantum-based machine learning algorithm were used to detect schizophrenia using EEG signals. The principal component analysis (PCA) method was applied to process the obtained data in quantum systems. The data, which were reduced in dimensionality, were transformed into qubit form using various feature maps and provided as input to the Quantum Support Vector Machine (QSVM) algorithm. Thus, the QSVM algorithm was applied using different qubit numbers and different circuits in addition to classical machine learning algorithms. All analyses were conducted in the simulator environment of the IBM Quantum Platform. In the classification of this EEG dataset, it is evident that the QSVM algorithm demonstrated superior performance with a 100% success rate when using Pauli X and Pauli Z feature maps. This study serves as proof that quantum machine learning algorithms can be effectively utilized in the field of healthcare.
Diverging or converging technology capabilities in the European Union?
Authors: Grafström Jonas , Alm Carl 
Published: March 2024

AbstractThe ongoing debate among economists regarding the presence of economic convergence or divergence has been reignited. This paper aims to dissect the extent of technological divergence or convergence among European Union member states, evaluating the effectiveness of the EU’s pronounced goals for convergence. Defining a countries technological level is not straightforward, this study examines six key indicators: (a) scientific journal publications, (b) total patents, (c) high tech exports, (d) Gross domestic expenditure on R&D, (e) government budget on R&D, and (f) human resources in science and technology as a share of the active population. Employing both time-series and longitudinal methodologies, the analysis spans from 2000 to 2019. The findings reveal a gradual catching-up trend in the inventive capabilities across the EU. This modest pace of convergence necessitates a critical reassessment by policymakers of the current EU convergence strategies to ensure they effectively foster technological parity among member states.
Non-Uniformly Weighted Multisource Domain Adaptation Network For Fault Diagnosis Under Varying Working Conditions
Authors: Zhang Hongliang , Zhang Yuteng , Wang Rui , Pan Haiyang , Chen Bin 
Published: March 2024

AbstractMost transfer learning-based fault diagnosis methods learn diagnostic information from the source domain to enhance performance in the target domain. However, in practical applications, usually there are multiple available source domains, and relying on diagnostic information from only a single source domain limits the transfer performance. To this end, a non-uniformly weighted multisource domain adaptation network is proposed to address the above challenge. In the proposed method, an intra-domain distribution alignment strategy is designed to eliminate multi-domain shifts and align each pair of source and target domains. Furthermore, a non-uniform weighting scheme is proposed for measuring the importance of different sources based on the similarity between the source and target domains. On this basis, a weighted multisource domain adversarial framework is designed to enhance multisource domain adaptation performance. Numerous experimental results on three datasets validate the effectiveness and superiority of the proposed method.
The Optimization of Hydrodynamic Cavitation as an Advanced Oxidation Option for the Removal of Persistent Contaminants in Wastewater
Authors: Kakama Natacha Kabata , Petrik Leslie Felicia , Ojumu Tunde Victor 
Published: March 2024

AbstractWastewater is increasingly becoming the primary source of potable water in many cities, thanks to the development of recycling facilities. Persistent contaminants such as dyes and perfluorinated compounds from textile industries as well as other contaminants necessitate the design of removal technologies to treat wastewater to reduce these chemicals before discharge or being used as feed to a potable water plant. Several chemical treatment techniques have been reported but the most utilized advanced chemical treatments lead to high costs and further environmental concerns. This study investigated an alternative approach to wastewater treatment using a hydrodynamic cavitation pilot plant combined with a venturi as a way to remove recalcitrant compounds. The optimization of the removal process was explored by testing the effect of orifices with size 2, 3, 4, 5, or 6 mm on the decoloration of orange II dye. The impact of the catalyst: iron(II); oxidizing agent: hydrogen peroxide; and contact time was evaluated to find the ideal conditions under which the removal of perfluorooctanoic acid (PFOA) could be achieved. The decoloration of 20 ppm of orange II dye in simulated industrial textile wastewater was achieved at 90% efficiency when the pressure at the inlet was maintained at 300 kPa, the temperature at 34 °C, the pH at 2, and the orifice size at 2 mm of diameter. The kinetic study proved the decoloration reaction was pseudo first order and the rate of decolourisation of orange II was 0.23/min.Ten parts per million of PFOA could not be degraded by free radical attack using advanced oxidation processes when the inlet pressure was maintained at 300 kPa, the temperature at 34 °C, the pH of 2, and the orifice diameter of 2 mm. This resistance to removal is due to the structure of PFOA which is made up of a fluorine ion which stabilizes the compounds by inductive effects while dye is made up of nitrogen ion and is compatible with the above removal methods. The study demonstrated that the combination of venturi and orifice requires the throat size of the venturi to be similar or equal to that of the orifice for better efficiency.
Characterizing the sprint threshold (25.2 km/h): a case study analysis on how soccer players reach sprint speeds and what relative intensity the threshold represents
Authors: Silva Hugo , Nakamura Fábio Yuzo , Mendez-Villanueva Alberto , Gomez-Diaz Antonio , Menezes Pedro , Marcelino Rui 
Published: March 2024

Abstract
Purpose
This study investigated how soccer players reach sprint speeds (> 25.2 km⋅h−1) and what that fixed threshold represents to each player regarding their individual match peak speeds registered during competition.

Methods
Twenty professional players (n = 20) from a team competing in the Brazilian first division were monitored with a global navigation satellite system during six matches. All efforts with final speeds > 25.2 km⋅h−1 were analyzed according to starting speed, and accelerations’ duration and magnitude. Peak speeds for each player were also retrieved and compared to the sprint threshold.

Results
Most efforts > 25.2 km⋅h−1 (> 91%) start with very short accelerations (< 0.5 s). Efforts started predominately from high starting speeds (20–25 and > 25 km⋅h−1) than low starting speeds (< 5 and 5–10 km⋅h−1) with huge effect sizes (p < 0.001). Most accelerations had magnitudes between 1 and 3 m⋅s−2 (p < 0.05). The 25.2 km⋅h−1 threshold represented an intensity of 71–91% of players’ match peak speed.

Conclusion
The inclusion of accelerations and peak speeds associated to the sprinting events that occur > 25.2 km⋅h−1 was shown to be useful for further characterization of soccer sprinting performance. In addition, the fixed threshold fails to individualize players’ capabilities and performances, misleading load demands performed by players.
Cu nanoparticles grafting on the surface of ZnO nanostructures to boost the porosity and surface area for effective removal of manganese ions from aqueous solutions
Authors: Geioushy Ramadan A. , Ali Eman S. , Djellabi Ridha , Abdel-Khalek Mohamed A. , Fouad Osama A. 
Published: March 2024

AbstractDesigning highly adsorptive materials for wastewater treatment via facile approaches is still challenging. To boost the recovery of heavy metals from wastewater, surface and structure modification are considered a successful route. Herein, we report the design of ZnO nanoparticles by a simple thermal decomposition method followed by grafting Cu nanoparticles (Cu NPs) over the ZnO surface. Cu/ZnO was prepared with different Cu ratios, 0.01 and 1%. It was found that incorporating Cu into ZnO improved the porosity and surface area of ZnO. The adsorption ability of Cu/ZnO compared with bare ZnO was studied towards removing manganese ions from wastewater. The effects of several parameters, such as pH, temperature, contact time, and initial ion concentrations, were studied. The maximum removal of manganese was found at pH 2, 20 °C after 60 min in the presence of 1 g/L adsorbent. The role of Cu grafted on the surface of ZnO was discussed. The rates of adsorption were found to follow the pseudo-second-order model. The results showed better fitting to Freundlich isotherm. The thermodynamic study revealed that the sorption process is spontaneous, exothermic, and favorable at low temperatures. The free energy (ΔG°), enthalpy (ΔH°), and entropy (ΔS°) changes were calculated to predict the nature of adsorption.
Graphical Abstract
CheekAge: a next-generation buccal epigenetic aging clock associated with lifestyle and health
Authors: Shokhirev Maxim N. , Torosin Nicole S. , Kramer Daniel J. , Johnson Adiv A. , Cuellar Trinna L. 
Published: March 2024

AbstractEpigenetic aging clocks are computational models that predict age using DNA methylation information. Initially, first-generation clocks were developed to make predictions using CpGs that change with age. Over time, next-generation clocks were created using CpGs that relate to both age and health. Since existing next-generation clocks were constructed in blood, we sought to develop a next-generation clock optimized for prediction in cheek swabs, which are non-invasive and easy to collect. To do this, we collected MethylationEPIC data as well as lifestyle and health information from 8045 diverse adults. Using a novel simulated annealing approach that allowed us to incorporate lifestyle and health factors into training as well as a combination of CpG filtering, CpG clustering, and clock ensembling, we constructed CheekAge, an epigenetic aging clock that has a strong correlation with age, displays high test–retest reproducibility across replicates, and significantly associates with a plethora of lifestyle and health factors, such as BMI, smoking status, and alcohol intake. We validated CheekAge in an internal dataset and multiple publicly available datasets, including samples from patients with progeria or meningioma. In addition to exploring the underlying biology of the data and clock, we provide a free online tool that allows users to mine our methylomic data and predict epigenetic age.
Investigating the design, participation and experience of teaching and learning facilitated by user-generated microgames on an open educational platform
Authors: Rahmadi Imam Fitri , Lavicza Zsolt , Arkün Kocadere Selay , Houghton Tony , Spector Jonathan Michael 
Published: March 2024

AbstractAlthough user-generated microgames, defined as very simple games made by non-professionals on open platforms, are popular and appear to have considerable advantages in facilitating learning, further exploration is needed to establish their potential in instructional practices. The present study investigates the design, participation and experience of teaching and learning facilitated by user-generated microgames on an open educational platform. Through an exploratory experiment research method, four elementary school teachers designed and implemented microgame-based learning utilising these very small games on GeoGebra Classroom attended by 129 students. Data were gathered from lesson plans, classroom activity records and self-reflection questionnaires. This study revealed that teachers designed learning with various user-generated microgames and debriefing methods respecting learning content, but they shared comparatively similar scenarios by inserting microgame-based learning into the middle of the main session. The completion rate for the debriefing activity is minimum although the total joining times overshoot the number of students. Teachers found that user-generated microgames are acceptable to orchestrate short serious gaming sessions even though they are limited to one player with basic interfaces. Notwithstanding several disadvantages of these microgames recognised by students, such as missing learning instructions and inadequate interfaces, they so far enjoy learning by playing the games. The most critical implication of this study is to provide sufficient instructions and additional time for microgaming sessions in elementary schools to ensure sustainable completion of the briefing, playing and debriefing activities.
Improving supply chain planning for perishable food: data-driven implications for waste prevention
Authors: Birkmaier Alexandra , Imeri Adhurim , Reiner Gerald 
Published: March 2024

AbstractWaste in the perishable food supply chain is a challenge that data-driven forecasting methods can tackle. However, integrating such methods in supply chain planning requires development efforts. In this regard, understanding user expectations is the first development step. This study scrutinizes the expectations of a data-driven forecasting method for perishable food. The intended development is a joint initiative of a consortium containing three perishable grocery handling firms. Besides planning expectations, the study identifies and ranks demand-sensing factors that can enable data-driven forecasting for food waste prevention. As the participating firms compete in the same region, horizontal collaboration implications are additionally explored in this context. Accordingly, the study extracts relevant performance measures parallelized to food waste. A two-round Delphi study is used to collect the expectations from a data-driven forecasting method. Individual semi-structured interviews with experts from the initiative firms are conducted in the first Delphi round. Based on the extracted propositions in each interview, industrial experts jointly readdressed and ranked the extracted propositions in the second Delphi round, i.e., focus group workshop. The results reveal that the perishability characteristic emerges as a common expectation in linking supply chain planning with data-driven forecasting. This empirical study contributes to the research on supply chain forecasting and addresses the pertinent aspects of developing data-driven approaches to prevent food waste.