bluuebunny/crossref_metadata_2025 huggingface dataset:
Algorithm‐Driven Tele‐otoscope for Remote Care for Patients With Otitis Media
Authors: Fang Te‐Yung , Lin Tse‐Yu , Shen Chung‐Min , Hsu Su‐Yi , Lin Shing‐Huey , Kuo Yu‐Jung , Chen Ming‐Hsu , Yin Tan‐Kuei , Liu Chih‐Hsien , Lo Men‐Tzung , Wang Pa‐Chun
Published: March 2024

Objective

The COVID‐19 pandemic has spurred a growing demand for telemedicine. Artificial intelligence and image processing systems with wireless transmission functionalities can facilitate remote care for otitis media (OM). Accordingly, this study developed and validated an algorithm‐driven tele‐otoscope system equipped with Wi‐Fi transmission and a cloud‐based automatic OM diagnostic algorithm.

Study Design

Prospective, cross‐sectional, diagnostic study.

Setting

Tertiary Academic Medical Center.

Methods

We designed a tele‐otoscope (Otiscan, SyncVision Technology Corp) equipped with digital imaging and processing modules, Wi‐Fi transmission capabilities, and an automatic OM diagnostic algorithm. A total of 1137 otoscopic images, comprising 987 images of normal cases and 150 images of cases of acute OM and OM with effusion, were used as the dataset for image classification. Two convolutional neural network models, trained using our dataset, were used for raw image segmentation and OM classification.

Results

The tele‐otoscope delivered images with a resolution of 1280 × 720 pixels. Our tele‐otoscope effectively differentiated OM from normal images, achieving a classification accuracy rate of up to 94% (sensitivity, 80%; specificity, 96%).

Conclusion

Our study demonstrated that the developed tele‐otoscope has acceptable accuracy in diagnosing OM. This system can assist health care professionals in early detection and continuous remote monitoring, thus mitigating the consequences of OM.
Failure mode analysis and prediction model of additively manufactured continuous carbon fiber‐reinforced polylactic acid
Authors: Yang Lei , Zhou Lei , Lin Yudong , Hu Yong , Yan Chunze , Shi Yusheng
Published: March 2024

Carbon fiber‐reinforced composites are widely used in aerospace, rail transportation, and new energy vehicles due to their small specific gravity as well as good mechanical and chemical properties. Additive manufacturing of continuous carbon fiber‐reinforced polymer composites is an innovative composite manufacturing technique. In this paper, bending and shear specimens with different hatch spacing and layer thicknesses were prepared by fused filament fabrication (FFF) technique and subjected to three‐point bending experiments and interlayer shear experiments, respectively. The results showed that the maximum flexural strength and flexural modulus of the fabricated parts were 383.81 MPa and 41.23 GPa, respectively, and the maximum interlayer shear strength was 13.64 MPa. Finally, an optimized criterion for determining fiber kinking, fiber breakage, and matrix damage was proposed by considering in situ strength variations induced by process parameters. This new model was subsequently validated and could provide a method for fracture predicting of additive manufactured carbon fiber‐reinforced composites.

Highlights

CCFRC parts with different porosities were prepared by adjusting the layer thickness and hatch spacing.

The bending and interlaminar shear damage mechanisms of CCFRC fabrications are revealed, and the effects of layer thickness and hatch spacing on their mechanical properties are investigated.

Introduction of additive manufacturing factors to optimize failure models for CCFRC parts.

Introduction of additive manufacturing coefficients to accurately predict the interlaminar shear strength of CCFRC parts by AM.
Synthesis and characterization of monodispersed silica‐based shear thickening fluid for impact resistance applications
Authors: Kumar Nitin , Bishnoi Swati , Ghosh Anup K. , Majumdar Abhijit , Pattanayek Sudip K.
Published: March 2024

Shear thickening fluid (STF), a highly concentrated mixture of nanosized silica particles in polyethylene glycol (PEG) is characterized by its quick transition to a stiff, solid‐like form under high shear rates. In this study, the modified Stöber synthesis approach was used for synthesizing the monodispersed spherical 300 nm silica nanoparticles. The rheological properties of the STF formulated using different silica loading were characterized. The Takshak model was tested to assess the rheological properties. The effect of the STFs on the impact resistance and yarn pull‐out force of the Kevlar® 802 fabric was determined. The uniformity in size of the silica nanoparticles facilitated more efficient packing within the fluid matrix, resulting in the formation of networks or structures that enhance shear thickening behavior. The STF with 70% silica exhibited the best peak viscosity of 45.8 Pa.s. Upon impregnation of this STF onto the Kevlar, a significantly high energy absorption (478.4%) compared to neat Kevlar, was observed. Moreover, the yarn pull‐out force for this system was found to be very high (435.8%). The reasons for the enhancement of the properties are explained. The novelty of this work lies in the synthesis of silica particles, analysis of the rheological properties, and interrelating the rheological properties with the characteristic parameters to define the impact characteristics. The improved properties underscore the suitability of synthesized STF for impact resistance applications.
Effect of processing parameter changes on mechanical properties during injection molding: Amorphous versus semi‐crystalline materials
Authors: Cai Kaiyu , O'Leary Travis , Mulyana Rachmat , Castro Jose M.
Published: March 2024

Injection molding is the most common method to mass‐produce plastic parts. The high cost and long lead time of traditional injection molding steel molds make 3D‐printed plastic molds a potential substitute for limited production runs and prototype parts. However, results suggest that for some materials, utilizing plastic molds (compared to metal molds) could decrease the mechanical properties of parts, especially the ductility. In order to better understand the issues with utilizing plastic molds, in this work, we use a design of experiments to investigate how the processing parameter changes affect mechanical properties by comparing a semi‐crystalline polypropylene and an amorphous polystyrene material in a metal mold for better control of the controllable variables. Results show that ductility is the most sensitive property to processing conditions, especially for polypropylene. Our analysis shows that the controllable variable that affects ductility the most is mold temperature, then packing pressure, and injection time.

Highlights

3D‐printed plastic molds is a potential substitute for limited production runs.

Effects of processing parameters are analyzed through the design of experiments.

Ductility is the most sensitive property to processing conditions for the material studied.

Mold temperature is the most significant variable for ductility.
Virtual reality training versus conventional rehabilitation for chronic neck pain: A systematic review and meta‐analysis
Authors: Hao Jie , He Zhengting , Chen Ziyan , Remis Andréas
Published: March 2024

Objective

To identify, critically appraise, and quantitatively synthesize current randomized controlled trials to compare the effects of virtual reality and dose‐matched conventional exercises in patients with chronic neck pain.

Literature Search

PubMed, Embase, CINAHL, PsycINFO, and Scopus were searched for studies published prior to April 15, 2023. The search strategies combined controlled vocabularies and title/abstract keywords on search themes of virtual reality and neck pain.

Methods

A systematic review and meta‐analysis of randomized controlled trials was conducted. Two independent reviewers conducted study selection, data extraction, and quality assessment. Methodological quality was assessed using the Physiotherapy Evidence Database scale. Meta‐analyses were performed using random‐effects models.

Synthesis

Six randomized controlled trials including 243 participants with chronic neck pain met the inclusion criteria. Four studies were evaluated as good quality and two as fair. Pooled analysis revealed that virtual reality demonstrated significantly better improvements in the Neck Disability Index in both the short term (mean difference [MD] = −2.16; 95% confidence interval [CI]: −3.50 to −0.82) and long term (MD = −2.95; 95% CI: −4.93 to −0.97), and pain intensity in the short term (MD = −0.94, 95% CI: −1.31 to −0.58). No significant between‐group differences were found in pain in the long term and kinesiophobia.

Conclusions

Virtual reality is a promising intervention to address disability and pain in patients with chronic neck pain. This review supports the clinical significance of augmenting conventional exercise with virtual reality as part of conservative management of chronic neck pain.
Answering the Rehabilitation 2030 Call
Authors: Hillaker Emily , Bova Michael , Libby Jina , Tricarico Maria , Andrews Patrick , Scharf Rebecca
Published: March 2024

In 2017, the World Health Organization initiated a global effort to improve rehabilitative services by 2030, with the overall goal of helping individuals with disabilities achieve maximal independence and improved well‐being. Though more than 1 billion people worldwide live with a disability, a significant portion do not have access to appropriate rehabilitative services. In low‐income countries, such as Zambia, where rehabilitative services are greatly lacking, disability can further exacerbate economic disparities in the context of personal, cultural, and environmental factors that limit participation in society. Therefore, expansion of rehabilitative services in low‐income countries is a pressing global need, and such efforts must be tailored to the societal and cultural framework in which they are implemented. Community‐based rehabilitation programs are uniquely poised to provide services in similar low‐to‐middle‐income countries as they eliminate travel barriers to care, allow for regular follow‐up, and address the societal determinants of disability by encouraging greater community engagement and by decreasing cultural stigma around disability. Special Hope Network (SHN), a community‐based rehabilitation organization in Lusaka, Zambia that serves families caring for children with physical and cognitive disabilities, represents a cost‐effective, sustainable, and culturally practical model to provide rehabilitative care. We propose this organization's model as one that can be reproduced and expanded upon in other low‐to‐middle‐income countries to answer the World Health Organization's call to action.
Transcranial Doppler ultrasonography can predict inpatient rehabilitation functional outcome in patients with stroke
Authors: Navalkar Nina , Sandefer Kristen , Nanavati Hely , Lin Chen
Published: March 2024

Background

Despite advances in imaging techniques and treatment modalities, tools to predict recovery after stroke remain limited.

Objective

To determine if transcranial Doppler (TCD) mean flow velocities were predictive of functional recovery following ischemic stroke.

Methods

Data were collected from patients with stroke admitted to an academic tertiary care facility in the southeastern region of the United States between 2012 and 2019 who had a middle cerebral artery distribution ischemic stroke, TCD, and were discharged to our inpatient rehabilitation facility. Mean flow velocities were categorized as low (<40 cm/s), normal (40–80 cm/s), or high (>80 cm/s). Functional Independence Measure (FIM) scores were collected on admission to and discharge from inpatient rehabilitation. Multiple linear regression models were used to assess the differences in mean FIM score changes by categories of mean flow velocities.

Results

We enrolled 57 patients, mean age 60 years, 73.7% male. Compared to the normal velocity group, those with abnormally low velocities had a significantly smaller change in their FIM score (adjusted β = −8.42; p = .01). Compared to the normal velocity group, those with abnormally high velocities experienced a greater change in FIM score, but this association was not statistically significant (beta = 1.12; p = .77).

Conclusions

In this limited population, we found that low mean flow velocity as measured by TCD ultrasonography after a middle cerebral artery stroke is associated with poorer functional recovery following inpatient rehabilitation. Our results suggest that the value of TCD ultrasonography as a tool to predict motor recovery after stroke warrants further investigation.
ATS core curriculum 2023. Pediatric pulmonary medicine: Respiratory disorders in infants
Authors: Leon‐Astudillo Carmen , Dy Fei J. , McCown Michael Y. , Perez Iris A. , Chhabra Divya , Bansal Manvi , Maloney Melissa A. , Bedoya Mariana , Ezmigna Dima , Bush Douglas , Okorie Caroline U. A. , Gross Jane E.
Published: March 2024

The American Thoracic Society Core Curriculum updates clinicians annually in pediatric pulmonary disease. This is a summary of the Pediatric Pulmonary Medicine Core Curriculum presented at the 2023 American Thoracic Society International Conference. The respiratory disorders of infancy discussed in this year's review include: the care of the patient with bronchopulmonary dysplasia in the neonatal intensive care unit, clinical phenotypes and comorbidities; diffuse lung disease; pulmonary hypertension; central and obstructive sleep apnea. The care of infants with respiratory disorders often poses significant challenges to the general pediatric pulmonologist, sleep clinician, and neonatologist. This review aims to highlight the most clinically relevant aspects of the evaluation, management, and outcomes of infants with these key respiratory disorders, while emphasizing the importance of multidisciplinary care. Furthermore, this document summarizes essential aspects of genetic testing, novel imaging and treatment modalities, and includes multiple resources for clinical practice.
Clinical validation of circulating GDF15/MIC‐1 as a marker of response to docetaxel and survival in men with metastatic castration‐resistant prostate cancer
Authors: Mahon Kate L. , Sutherland Sarah IM , Lin Hui Ming , Stockler Martin R. , Gurney Howard , Mallesara Girish , Briscoe Karen , Marx Gavin , Higano Celestia S. , de Bono Johann S. , Chi Kim N. , Clark Georgina , Breit Samuel N. , Brown David A. , Horvath Lisa G.
Published: March 2024

Background

Elevated circulating growth differentiation factor (GDF15/MIC‐1), interleukin 4 (IL4), and IL6 levels were associated with resistance to docetaxel in an exploratory cohort of men with metastatic castration‐resistant prostate cancer (mCRPC). This study aimed to establish level 2 evidence of cytokine biomarker utility in mCRPC.

Methods

IntVal: Plasma samples at baseline (BL) and Day 21 docetaxel (n = 120). ExtVal: Serum samples at BL and Day 42 of docetaxel (n = 430). IL4, IL6, and GDF15 levels were measured by ELISA. Monocytes and dendritic cells were treated with 10% plasma from men with high or low GDF15 or recombinant GDF15.

Results

IntVal: Higher GDF15 levels at BL and Day 21 were associated with shorter overall survival (OS) (BL; p = 0.03 and Day 21; p = 0.004). IL4 and IL6 were not associated with outcomes. ExtVal: Higher GDF15 levels at BL and Day 42 predicted shorter OS (BL; p < 0.0001 and Day 42; p < 0.0001). Plasma from men with high GDF15 caused an increase in CD86 expression on monocytes (p = 0.03), but was not replicated by recombinant GDF15.

Conclusions

Elevated circulating GDF15 is associated with poor prognosis in men with mCRPC receiving docetaxel and may be a marker of changes in the innate immune system in response to docetaxel resistance. These findings provide a strong rationale to consider GDF15 as a biomarker to guide a therapeutic trial of drugs targeting the innate immune system in combination with docetaxel in mCRPC.
Comparisons of steady‐state optimal EWMA and DEWMA charts
Authors: Rigdon Steven E. , Champ Charles W. , Knoth Sven
Published: March 2024

The double EWMA (DEWMA) has been proposed as a more efficient control charting procedure for monitoring the mean of a process. Comparisons of the DEWMA and the EWMA charts, which often indicate the superiority of the DEWMA, are often flawed because the same smoothing constant is used in both charts. We take the approach of first selecting a shift that we would like to detect, and then compare the optimal DEWMA chart and the optimal EWMA chart for that particular shift. We consider the DEWMA chart whose smoothing constants are restricted to be the same and the general DEWMA. We find that there are situations where the optimal DEWMA outperforms, in the sense of a shorter out‐of‐control average run length (ARL) for a fixed in‐control ARL, but the improvement is slight. The optimal EWMA chart usually performs much better than the optimal DEWMA chart when the actual shift differs from the shift used to optimize the chart. The poor performance of the DEWMA chart away from the shift for which it was optimized, the nonmonotonicity of the DEWMA weights, and the additional computations required of the DEWMA chart indicate that the EWMA is a better overall choice than the DEWMA chart.
Log‐location‐scale increment degradation model: A Bayesian perspective
Authors: Yu I‐Tang , Wang Kuei‐Mao
Published: March 2024

Degradation modeling serves as a valuable tool for assessing the lifetime information of highly reliable products. One frequently employed approach for describing the degradation phenomenon involves the use of a degradation model that relies on stochastic processes. In a stochastic‐process‐based degradation model, it is assumed that the increments follow a distribution with the additivity property. This property makes the further inferences mathematically and statistically tractable. However, it limits the choices of the distributions. This paper aims to use those distributions without the additivity property to model the increments and explores distributions from the log‐location‐scale family. Under the frame of Bayesian analysis, Markov Chain Monte Carlo algorithms are developed for executing the necessary computations. Given that the proposed degradation models do not adhere to the additivity property, this paper tackles the challenges involved in predicting the lifetime of both on‐line and off‐line products. Two illustrative examples are subsequently analyzed to demonstrate the procedural steps outlined. The suitability of the proposed model is finally validated through a simulation study.
The finite mixture model for the tails of distribution: Monte Carlo experiment and empirical applications
Authors: Furno Marilena , Caracciolo Francesco
Published: March 2024

The finite mixture model estimates regression coefficients distinct in each of the different groups of the dataset endogenously determined by this estimator. In what follows the analysis is extended beyond the mean, estimating the model in the tails of the conditional distribution of the dependent variable within each group. While the clustering reduces the overall heterogeneity, since the model is estimated for groups of similar observations, the analysis in the tails uncovers within groups heterogeneity and/or skewness. By integrating the endogenously determined clustering with the quantile regression analysis within each group, enhances the finite mixture models and focuses on the tail behavior of the conditional distribution of the dependent variable. A Monte Carlo experiment and two empirical applications conclude the analysis. In the well‐known birthweight dataset, the finite mixture model identifies and computes the regression coefficients of different groups, each one with its own characteristics, both at the mean and in the tails. In the family expenditure data, the analysis of within and between groups heterogeneity provides interesting economic insights on price elasticities. The analysis in classes proves to be more efficient than the model estimated without clustering. By extending the finite mixture approach to the tails provides a more accurate investigation of the data, introducing a robust tool to unveil sources of within groups heterogeneity and asymmetry otherwise left undetected. It improves efficiency and explanatory power with respect to the standard OLS‐based FMM.
Wetlands contribution and linkage to support SDGs, its indicators and targets‐ A critical review
Authors: Mohanty Smrutisikha , Pandey Prem Chandra , Pandey Manish , Srivastava Prashant K. , Dwivedi Chandra Shekhar
Published: March 2024

This study marks one of the pioneering efforts to compile comprehensive information on Ramsar sites globally. It delves into the significance of wetlands and the designation of Ramsar sites across various countries, incorporating a concise exploration of the utilization of Unmanned Aerial Vehicles (UAVs) for wetland monitoring and assessment. Additionally, the study conducts a comparative evaluation of Ramsar sites, analyzing their percentage area and overall coverage worldwide. Incorporating a Scientometric analysis utilizing the Scopus database, the study features a co‐occurrence map, thematic map, thematic evolution trend, and country collaboration map. Emphasizing the interconnection between wetlands and Sustainable Development Goals (SDGs), particularly SDG6 (Clean Water & Sanitation), SDG12 (Responsible Consumption & Production), SDG13 (Climate‐Action), SDG14 (Life Below Water) and SDG15 (Life on Land), the study delves into associated targets and indicators. Targets such as 6.1, 6.2, 6.3, 6.4, 6.5, 6a, 6b of SDG‐6, 12.1, 12.2, 12.4 of SDG‐12, and 13.2, 13.3 of SDG‐13 align with wetland management and conservation. Moreover, it affirms the role of wetlands in supporting targets 14.1, 14.2, 14.3, 14.4, 14.5, 14.6, 14a‐c of SDG‐14, and 15.1, 15.5, 15.6, 15.7, 15.8, and 15.8 of SDG‐15. Policies, regulations and management plans of different countries relevant for supporting and establishing relationship with SDGs are discussed in details. The study offers a detailed exploration of these targets, elucidating indicator types associated with each SDG target. By doing so, it provides valuable insights for future researchers and policymakers, underlining the indispensable contribution of wetlands to the direct and indirect fulfillment of SDGs 6,12,13,14,15 and 17.
The effect of sputtering parameters and doping on the properties of CrN‐based coatings—A critical review
Authors: Tiwari Sunil Kumar , Rao Akula Umamaheswara , Kharb Archana Singh , Avasthi Devesh Kumar , Verma Piyush Chandra , Chawla Amit Kumar
Published: March 2024

Chromium‐based coatings have been of interest to researchers for the last two decades because of their extraordinary properties like high hardness, high wear, and corrosion resistance properties. However, it is in practice and research to increase the properties of Cr‐based coatings for high‐temperature applications. Numerous dopants like silicon (Si), titanium (Ti), vanadium (V), aluminum (Al), and zirconium (Zr) have been used together with Cr to achieve enhanced properties. The plasma‐based sputtering process is one of the popular and reliable techniques to deposit thin film coatings. The substrate material, processed gas and pressure, substrate temperature, film thickness, and so on also play a significant role in varying the properties and microstructure of the deposited film. Several researchers have deposited Cr/CrN‐based thin films via the chemical vapor deposition technique (CVD) and physical vapor deposition technique (PVD) to study their properties and behavior at room temperature as well as for high‐temperature applications. This work reflects the review of work done to deposit Cr/CrN‐based coatings deposited via PVD: more specifically sputtering technique. The effect of doping in the CrN matrix and variation in sputtering parameters on the properties of CrN‐based coatings have also been studied.
How could a pooled testing policy have performed in managing the early stages of the COVID‐19 pandemic? Results from a simulation study
Authors: Heath Bethany , Villar Sofía S. , Robertson David S.
Published: March 2024

A coordinated testing policy is an essential tool for responding to emerging epidemics, as was seen with COVID‐19. However, it is very difficult to agree on the best policy when there are multiple conflicting objectives. A key objective is minimizing cost, which is why pooled testing (a method that involves pooling samples taken from multiple individuals and analyzing this with a single diagnostic test) has been suggested. In this article, we present results from an extensive and realistic simulation study comparing testing policies based on individually testing subjects with symptoms (a policy resembling the UK strategy at the start of the COVID‐19 pandemic), individually testing subjects at random or pools of subjects randomly combined and tested. To compare these testing methods, a dynamic model compromised of a relationship network and an extended SEIR model is used. In contrast to most existing literature, testing capacity is considered as fixed and limited rather than unbounded. This article then explores the impact of the proportion of symptomatic infections on the expected performance of testing policies. Symptomatic testing performs better than pooled testing unless a low proportion of infections are symptomatic. Additionally, we include the novel feature for testing of non‐compliance and perform a sensitivity analysis for different compliance assumptions. Our results suggest for the pooled testing scheme to be superior to testing symptomatic people individually, only a small proportion of the population () needs to not comply with the testing procedure.
A nonparametric relative treatment effect for direct comparisons of censored paired survival outcomes
Authors: Dobler Dennis , Möllenhoff Kathrin
Published: March 2024

A frequently addressed issue in clinical trials is the comparison of censored paired survival outcomes, for example, when individuals were matched based on their characteristics prior to the analysis. In this regard, a proper incorporation of the dependence structure of the paired censored outcomes is required and, up to now, appropriate methods are only rarely available in the literature. Moreover, existing methods are not motivated by the strive for insights by means of an easy‐to‐interpret parameter. Hence, we seek to develop a new estimand‐driven method to compare the effectiveness of two treatments in the context of right‐censored survival data with matched pairs. With the help of competing risks techniques, the so‐called relative treatment effect is estimated. This estimand describes the probability that individuals under Treatment 1 have a longer lifetime than comparable individuals under Treatment 2. We derive hypothesis tests and confidence intervals based on a studentized version of the estimator, where resampling‐based inference is established by means of a randomization method. In a simulation study, we demonstrate for numerous sample sizes and different amounts of censoring that the developed test exhibits a good power. Finally, we apply the methodology to a well‐known benchmark data set from a trial with patients suffering from diabetic retinopathy.
Getting heard? How employees learn to gain senior management attention in inclusive strategy processes
Authors: Splitter Violetta , Seidl David , Whittington Richard
Published: March 2024

Research Summary

Recent trends toward inclusive strategy processes raise the issue of how employees acquire the discursive competence necessary to gain senior management attention. Building on the emergent dynamic attention‐based view's (DABV) emphasis on communicative interaction, we ethnographically track an inclusive strategy process in a large insurance company. We find that employees typically failed to gain CEO attention because they lacked the discursive competence to integrate their operational knowledge with the CEO's corporate themes. Employees acquired this competence by both experiential and vicarious learning. The CEO promoted employee learning more effectively by specific coaching than by generic coaching. We contribute primarily to the DABV by showing how interactions are sites for learning as well as communications and that communication channels can be both expandable and transparent.

Managerial Summary

The benefits of increased employee inclusion in strategy processes depend upon participants being truly heard. This study of an inclusive strategy process in a large insurance company shows that top management attention to employee contributions cannot be assumed. Employees often fail to pitch ideas in a manner that top managers can work with. Employees learn to pitch ideas effectively both by receiving direct feedback from top management and by observing feedback on other employees' contributions. Top managers must also learn how to coach effectively, engaging with the specifics of employees' contributions rather than offering general advice. Designs for new inclusive strategy processes should include opportunities for top managers to improve their coaching and for employees to learn from both direct feedback and indirect observation.
Engineering Nitrogen‐Doped Carbon Quantum Dots: Tailoring Optical and Chemical Properties through Selection of Nitrogen Precursors
Authors: Nguyen Kiem G. , Huš Matej , Baragau Ioan‐Alexandru , Bowen James , Heil Tobias , Nicolaev Adela , Abramiuc Laura Elena , Sapelkin Andrei , Sajjad Muhammad Tariq , Kellici Suela
Published: March 2024

The process of N‐doping is frequently employed to enhance the properties of carbon quantum dots. However, the precise requirements for nitrogen precursors in producing high‐quality N‐doped carbon quantum dots (NCQDs) remain undefined. This research systematically examines the influence of various nitrogen dopants on the morphology, optical features, and band structure of NCQDs. The dots are synthesized using an efficient, eco‐ friendly, and rapid continuous hydrothermal flow technique. This method offers unparalleled control over synthesis and doping, while also eliminating convention‐related issues. Citric acid is used as the carbon source, and urea, trizma base, beta‐alanine, L‐arginine, and EDTA are used as nitrogen sources. Notably, urea and trizma produced NCQDs with excitation‐independent fluorescence, high quantum yields (up to 40%), and uniform dots with narrow particle size distributions. Density functional theory (DFT) and time‐dependent DFT modelling established that defects and substituents within the graphitic structure have a more significant impact on the NCQDs’ electronic structure than nitrogen‐containing functional groups. Importantly, for the first time, this work demonstrates that the conventional approach of modelling single‐layer structures is insufficient, but two layers suffice for replicating experimental data. This study, therefore, provides essential guidance on the selection of nitrogen precursors for NCQD customization for diverse applications.
Balancing Flexible Side Chains on 2D Conjugated Acceptors Enables High‐Performance Organic Solar Cell
Authors: Bi Xingqi , Li Shitong , He Tengfei , Chen Hongbin , Li Yu , Jia Xinyuan , Cao Xiangjian , Guo Yaxiao , Yang Yang , Ma Wei , Yao Zhaoyang , Kan Bin , Li Chenxi , Wan Xiangjian , Chen Yongsheng
Published: March 2024

Balancing the rigid backbones and flexible side chains of light‐harvesting materials is crucially important to reach optimized intermolecular packing, micromorphology, and thus photovoltaic performance of organic solar cells (OSCs). Herein, based on a distinctive CH‐series acceptor platform with 2D conjugation extended backbones, a series of nonfullerene acceptors (CH‐6F‐Cn) are synthesized by delicately tuning the lengths of flexible side chains from n‐octyl to n‐amyl. A systemic investigation has revealed that the variation of the side chain's length can not only modulate intermolecular packing modes and crystallinity but also dramatically improve the micromorphology of the active layer and eventual photovoltaic parameters of OSCs. Consequently, the highest PCE of 18.73% can be achieved by OSCs employing D18:PM6:CH‐6F‐C8 as light‐harvesting materials.
Pinpointing the Cl Coordination Effect on Mn‐N3‐Cl Moiety Toward Boosting Reaction Kinetics and Suppressing Shuttle Effect in Li–S Batteries
Authors: Yan Yurong , Fu Ning , Shao Wei , Wang Tiantian , Liu Ying , Niu Yongsheng , Zhang Yanwei , Peng Mao , Yang Zhenglong
Published: March 2024

Single atom catalysts (SACs) are highly favored in Li–S batteries due to their excellent performance in promoting the conversion of lithium polysulfides (LiPSs) and inhibiting their shuttling. However, the intricate and interrelated microstructures pose a challenge in deciphering the correlation between the chemical environment surrounding the active site and its catalytic activity. Here, a novel SAC featuring a distinctive Mn‐N3‐Cl moiety anchored on B, N co‐doped carbon nanotubes (MnN3Cl@BNC) is synthesized. Subsequently, the selective removal of the Cl ligands while inheriting other microstructures is performed to elucidate the effect of Cl coordination on catalytic activity. The Cl coordination effectively enhances the electron cloud density of the Mn‐N3‐Cl moiety, reducing the band gap and increasing the adsorption capacity and redox kinetics of LiPSs. As a modified separator for Li–S batteries, MnN3Cl@BNC exhibits high capacities of 1384.1 and 743 mAh g−1 at 0.1 and 3C, with a decay rate of only 0.06% per cycle over 700 cycles at 1 C, which is much better than that of MnN3OH@BNC. This study reveals that Cl coordination positively contributes to improving the catalytic activity of the Mn‐N3‐Cl moiety, providing a fresh perspective for the design of high‐performance SACs.
Acidity‐Aided Surface Modification Strategy to Enhance In Situ MnO2 Deposition for High Performance Zn‐MnO2 Battery Prototypes
Authors: Panda Manas Ranjan , El Meragawi Sally , Mirshekarloo Meysam Sharifzadeh , Chen Wanqing , Shaibani Mahdokht , Majumder Mainak
Published: March 2024

Zn–MnO2 batteries offer cost‐effective, eco‐friendly, and efficient solutions for large‐scale energy storage applications. However, challenges, like irreversible cathode reactions, prolonged cyclability, and electrolyte stability during high‐voltage operations limit their broader application. This study provides insight into the charge–discharge process through in situ deposition of active β‐MnO2 nanoflakes on a carbon‐based current collector. The study elucidates the effect of pH and electrolyte concentration on chemical conversion reactions with Zn, in particular focus on their impact on the two‐electron MnO2/Mn2+ reaction crucial for high voltage operation. The electrolyte, characterized by being relatively lean in Mn2+ and with a targeted low pH, enables extended cycling. This research achieves greater cycling durability by integrating a carbon‐based cathode current collector with high density of structural defects in combination with cell architectures suitable for large‐scale energy storage. A flooded stack‐type Zn–MnO2 battery prototype employing the optimized electrolyte demonstrates a high discharge voltage (≈2 V) at a substantial discharge current rate of 10 mA cm−2. The battery exhibits an impressive areal capacity of ≈2 mAh cm−2, maintaining ≈100% capacity retention over 400 cycles. This research establishes a promising practical, and cost‐effective cathode‐free design for Zn–MnO2 batteries, that minimizes additional processing and assembly costs.
Accelerating the Development of Thin Film Photovoltaic Technologies: An Artificial Intelligence Assisted Methodology Using Spectroscopic and Optoelectronic Techniques
Authors: Grau‐Luque Enric , Becerril‐Romero Ignacio , Atlan Fabien , Huber Daniel , Harnisch Martina , Zimmermann Andreas , Pérez‐Rodríguez Alejandro , Guc Maxim , Izquierdo‐Roca Victor
Published: March 2024

Thin film photovoltaic (TFPV) materials and devices present a high complexity with multiscale, multilayer, and multielement structures and with complex fabrication procedures. To deal with this complexity, the evaluation of their physicochemical properties is critical for generating a model that proposes strategies for their development and optimization. However, this process is time‐consuming and requires high expertise. In this context, the adoption of combinatorial analysis (CA) and artificial intelligence (AI) strategies represents a powerful asset for accelerating the development of these complex materials and devices. This work introduces a methodology to facilitate the adoption of AI and CA for the development of TFPV technologies. The methodology covers all the necessary steps from the synthesis of samples for CA to data acquisition, AI‐assisted data analysis, and the extraction of relevant information for research acceleration. Each step provides details on the necessary concepts, requirements, and procedures and are illustrated with examples from the literature. Then, the application of the methodology to a complex set of samples from a TFPV production line highlights its ability to rapidly glean significant insights even in intricate scenarios. The proposed methodology can be applied to other types of materials and devices beyond PV and using different characterization techniques.
Study on the Cleanliness of SWRS82B Hard Wire Steel Refined by Fluorine‐Free Slag with Medium and High Basicity
Authors: Zhao Yudong , Deng Siqi , Wang Linzhu , Xia Chaokai , Li Shen
Published: March 2024

In order to apply and develop fluorine‐free slag in steelmaking, it is of great significance to study the effect of composition for fluorine‐free refining slag on the cleanliness of molten steel which affects its performance directly. The effect of composition of fluorine‐free refining slag with medium and high basicity on the contents of impurity elements for sulfur and oxygen, and characteristics of inclusions in SWRS82B hard wire steel, are investigated systematically. Sulfide capacity of refining slag is estimated based on the Royal Swedish Institute of Technology model. Dissolved oxygen content in molten steel equilibrated by refining slag is calculated based on Factsage software and classical thermodynamics. The calculated results are in good agreement with experimental results. The plasticity of inclusions at high temperature and low temperature is analyzed by phase diagram and Young's modulus calculation. The best cleanliness and inclusions of SWRS82B steel are obtained with slag composition of 53%CaO–19%SiO2–19%Al2O3–7%MgO, which has good melting characteristics. The impurity elements sulfur and oxygen in steel can be controlled for 26 and 19 ppm, respectively, and the average size of inclusions is 2.84 μm.
Study on the Coil Position Adaptive Adjustment Control Scheme of Wireless Power Transfer System
Authors: Gao Pengfei , Wang Peiyi , Tian Xiaoying , Huang Xiaoyan
Published: March 2024

Wireless power transfer (WPT) technology can completely isolate the equipment from the power supply, and has been widely used. However, the transmission efficiency of WPT system is optimal only as the transmitting coil was completely aligned with the receiving coil. But in practical applications, the mobile devices are all dynamic system, and perfectly alignment of the coils is a very demanding condition. In order to solve this problem, the paper proposed a coil position adaptive adjustment control scheme of WPT system with lateral misalignment or angular misalignment. Firstly, the relationship between transmission efficiency and lateral misalignment and angular misalignment was analyzed. And the research results show that if there is a lateral misalignment between the coils, the transmission efficiency can be optimized by adjusting the angular misalignment. Secondly, based on the hill climbing algorithm, a coil position adaptive adjustment control method was proposed. Finally, a coil position adaptive adjustment WPT system experimental platform was built, and the experimental researches are carried on. The results of the experiment show that as the transfer distance is 0.10 m and the lateral misalignment is 0.12 m, the transfer efficiency can be increased from 38.38% to 55.61% through the proposed control scheme. And the results verify the feasibility and effectiveness of control scheme proposed in the paper. © 2024 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.
“Are you Gonna Help us with Writing?” Empowering Writers though Dialogue Journaling
Authors: Bryars Leah , Pletcher Bethanie
Published: March 2024

Before ever entering a formal educational setting, children use writing to make themselves known. Yet by the time students reach the fourth grade, only a small minority of students demonstrate writing skills considered competent by national standards. By this time in their school career, many have begun to internalize that they are poor writers and have become apprehensive toward writing tasks and tests. Using an approach that applies the well‐established literacy practice of dialogue journaling, Leah, a teacher, facilitated an after‐school book club for fourth‐grade students who experienced writing apprehension. The outcomes of the book club were that students began to build confidence and develop more positive attitudes toward writing.
Basic Properties of Plasma in Fluid Model
Authors: Takabe Hideaki
Published: March 2024

If the spatial variation of plasma is longer than the particle mean free path and the time variation is sufficiently longer than the plasma Coulomb collision time, the plasma can be approximated as being in local thermal equilibrium (LTE) at any point (t, r). Then the velocity distribution functions of the particles become Maxwellian. In addition, assuming Maxwellian is also a good assumption in many cases even for collisionless plasmas such as high-temperature fusion plasmas. In the fluid model of plasmas, The plasmas can be described in terms of five variables characterizing local Maxwellian: the density n(t, r), flow velocity vector u(t,r), and temperature T(t, r). So, the mathematics used in fluid physics is widely applicable to studying plasma phenomena.

Although conventional fluids are neutral, plasma fluids of electrons and ions couple with electromagnetic fields. It is, therefore, necessary to solve Maxwell’s equations simultaneously. It is also possible to approximate electrons and ions as two different fluids or as a single fluid in case-by-case. This requires an insight into what kind of physics is important in our problem.

After reviewing the basic equation of fluids, several fluid models for plasmas are shown. Especially, a variety of waves appears because of charged particle fluids are derived to know why waves are fundamental to knowing the plasma dynamics. The mathematical method to obtain the wave solutions as an initial value problem is explained as well as the meaning of the resultant dispersion relations.

Magneto-hydrodynamic equations (MHD) are derived to explain the effects of the Biermann battery, magnetic dynamo, etc. The relationship of magnetic field and vortex flow is studied. Resistive MHD is derived including the Nernst effect, which becomes important for the magnetic field in strong electron heat flux.

Finally, electromagnetic (EM) waves in magnetized plasmas are derived to see how to use for diagnostics in the laboratory and observation of wide range of electromagnetic waves from the Universe.
Shock Waves and Ablation Dynamics
Authors: Takabe Hideaki
Published: March 2024

When an intense laser is irradiated on a solid target, the laser energy is absorbed on the surface so that the material becomes plasma to expand into the vacuum region. Through the laser-plasma interaction, the laser energy heats the expanding region spreading by its sound velocity. As the result the expanding region has the temperature ~ 1 keV and the pressure reaches 100 Mbar (10TPa). Since the laser is absorbed near relatively high density (~cut-off density), the plasma can be assumed to be in LTE and hydrodynamic description is acceptable.

The surface pressure called ablation pressure drives strong shock waves in the solid material as if the solid is almost gas. The shock wave physics is briefly reviewed to use the Rankin-Hugoniot (RH) relation, although detail studied is needed for the equation of state of the compressed matter. By use of the ablation pressure, it is possible to accelerate a thin material to higher velocity like a rocket propulsion.

One dimensional hydrodynamics is reviewed for steady state and time dependent dynamics within the ideal fluid assumption. Deflagration and detonation waves are also explained as jump condition with energy deposition. The laser implosion dynamics is compered between stationary solutions, computational results, and the experimental data. The importance of validation of simulation codes is discussed.
The Impact of Workforce Agile Behavior on Organizational Innovation Performance for Manufacturing Enterprises
Authors: Mohamad Amal Abdulrahim
Published: March 2024

Purpose - This paper intends to study the relationship between workforce agile behavior and organizational innovation in manufacturing enterprises. The research focuses on the impact of three characteristics of workforce agility (proactivity, flexibility, and resilience) on organizational innovation performance using the planned behavior theory (PBT), with a particular emphasis on product and process innovation.

Methodology - The research of this paper uses the theoretical background for the selected topic to propose a conceptual research framework to improve manufacturing enterprises’ innovation performance by understating the significance of workforce agility.

Findings - The expected outcome of the paper is to understand the relationship between agility in the workforce and innovation performance in manufacturing organizations. It can show the positive impact of a proactive, flexible, and resilient workforce in manufacturing enterprises to guarantee continuous growth in the rapid market landscape.

Implications - This study can support leadership and employees in the manufacturing sector to understand the importance of providing agile capabilities in the work environment to improve innovative organizational performance, sustain competitive market advantage, and respond to internal and external changes.

Originality/value - The paper addresses the literature gap on how organizational innovation can be influenced by workforce agility behavior in the manufacturing sector and helps understand the significance of agility practices in sustaining competitive advantages.
The Impact of the Zone of Proximal Development Concept (Scaffolding) on the Students Problem Solving Skills and Learning Outcomes
Authors: Raslan Gilan
Published: March 2024

Schools regularly use the zone of proximal development (ZPD), also known as scaffolding, to help students learn new skills. Students who do not receive enough scaffolding may not be able to acquire the skills at all, while students who receive too much scaffolding may suffer when it is taken away. Additionally, this will have an impact on their capacity for problem-solving and learning outcomes. This systematic literature review's goal is to examine how ZPD and scaffolding effect students’ learning outcomes and the growth of their problem-solving abilities.

Through a selection of pertinent publications that have undergone extensive analysis, the study addresses three main research topics.

The study's findings revealed that in order to achieve a high level of learning independence for the students and the ability to adapt to new situations leading to more advanced skills, a re-definition of certain concepts along with modifications and amendments on how to apply these new redefined ones, using more advanced teaching methodologies with incorporating technology to help students in exploring new ideas using critical thinking techniques and providing constructive feedback, are needed.