bluuebunny/crossref_metadata_2025 huggingface dataset:
Anthropomorphic Robotic Hand Prosthesis Developed for Children
Authors: Medina-Coello Pablo , Salvador-Domínguez Blas , Badesa Francisco J. , Rodríguez Corral José María , Plastrotmann Henrik , Morgado-Estévez Arturo
Published: July 2024

The use of both hands is a common practice in everyday life. The capacity to interact with the environment is largely dependent on the ability to use both hands. A thorough review of the current state of the art reveals that commercially available prosthetic hands designed for children are very different in functionality from those developed for adults, primarily due to prosthetic hands for adults featuring a greater number of actuated joints. Many times, patients stop using their prosthetic device because they feel that it does not fit well in terms of shape and size. With the idea of solving these problems, the design of HandBot-Kid has been developed with the anthropomorphic qualities of a child between the ages of eight and twelve in mind. Fitting the features of this age range, the robotic hand has a length of 16 cm, width of 7 cm, thickness of 3.6 cm, and weight of 328 g. The prosthesis is equipped with a total of fifteen degrees of freedom (DOF), with three DOFs allocated to each finger. The concept of design for manufacturing and assembly (DFMA) has been integrated into the development process, enabling the number of parts to be optimized in order to reduce the production time and cost. The utilization of 3D printing technology in conjunction with aluminum machining enabled the manufacturing process of the robotic hand prototype to be streamlined. The flexion–extension movement of each finger exhibits a trajectory that is highly similar to that of a real human finger. The four-bar mechanism integrated into the finger design achieves a mechanical advantage (MA) of 40.33% and a fingertip pressure force of 10.23 N. Finally, HandBot-Kid was subjected to a series of studies and taxonomical tests, including Cutkosky (16 points) and Kapandji (4 points) score tests, and the functional results were compared with some commercial solutions for children mentioned in the state of the art.
Au24Cd Nanoenzyme Coating for Enhancing Electrochemical Sensing Performance of Metal Wire Microelectrodes
Authors: Chen Jia-Yi , Huang Shuang , Liu Shuang-Jie , Liu Zheng-Jie , Xu Xing-Yuan , He Meng-Yi , Yao Chuan-Jie , Zhang Tao , Yang Han-Qi , Huang Xin-Shuo , Liu Jing , Zhang Xiao-Dong , Xie Xi , Chen Hui-Jiuan
Published: July 2024

Dopamine (DA), ascorbic acid (AA), and uric acid (UA) are crucial neurochemicals, and their abnormal levels are involved in various neurological disorders. While electrodes for their detection have been developed, achieving the sensitivity required for in vivo applications remains a challenge. In this study, we proposed a synthetic Au24Cd nanoenzyme (ACNE) that significantly enhanced the electrochemical performance of metal electrodes. ACNE-modified electrodes demonstrated a remarkable 10-fold reduction in impedance compared to silver microelectrodes. Furthermore, we validated their excellent electrocatalytic activity and sensitivity using five electrochemical detection methods, including cyclic voltammetry, differential pulse voltammetry, square-wave pulse voltammetry, normal pulse voltammetry, and linear scanning voltammetry. Importantly, the stability of gold microelectrodes (Au MEs) modified with ACNEs was significantly improved, exhibiting a 30-fold enhancement compared to Au MEs. This improved performance suggests that ACNE functionalization holds great promise for developing micro-biosensors with enhanced sensitivity and stability for detecting small molecules.
Creatine Kinase and Respiratory Decline in Amyotrophic Lateral Sclerosis
Authors: Correia João Pedro , Gromicho Marta , Pronto-Laborinho Ana Catarina , Oliveira Santos Miguel , de Carvalho Mamede
Published: July 2024

Respiratory dysfunction is an important hallmark of amyotrophic lateral sclerosis (ALS). Elevation of creatine kinase (CK) has been reported in 23–75% of ALS patients, but the underlying mechanisms remain unknown. This work aims to enlighten the role of CK as a prognostic factor of respiratory dysfunction in ALS. A retrospective analysis of demographic and clinical variables, CK, functional decline per month (ΔFS), forced vital capacity (%FVC), and mean amplitude of the phrenic nerve compound motor action potential (pCMAP) in 319 ALS patients was conducted. These measurements were evaluated at study entry, and patients were followed from the moment of first observation until death or last follow-up visit. High CK values were defined as above the 90th percentile (CK ≥ P90) adjusted to sex. We analyzed survival and time to non-invasive ventilation (NIV) as proxies for respiratory impairment. Linear regression analysis revealed that high CK was associated with male sex (p < 0.001), spinal onset (p = 0.018), and FVC ≥ 80% (p = 0.038). CK was 23.4% higher in spinal-onset ALS patients (p < 0.001). High CK levels were not linked with an increased risk of death (p = 0.334) in Cox multivariate regression analysis. CK ≥ P90 (HR = 1.001, p = 0.038), shorter disease duration (HR = 0.937, p < 0.001), lower pCMAP (HR = 0.082, p < 0.001), and higher ΔFS (HR = 1.968, p < 0.001) were risk factors for respiratory failure. The association between high CK levels and poorer respiratory outcomes could derive from cellular metabolic stress or a specific phenotype associated with faster respiratory decline. Our study suggests that CK measurement at diagnosis should be more extensively investigated as a possible marker of poor respiratory outcome in future studies, including a larger population of patients.
Repetitive Transcranial Magnetic Stimulation for Action Naming in Aphasia Rehabilitation: A Systematic Review and Meta-Analysis
Authors: Spigarelli Manon , Lalancette Audrey , Massé-Alarie Hugo , Wilson Maximiliano A.
Published: July 2024

Anomia, characterized by difficulty in word retrieval, particularly action verbs, poses a significant challenge in post-stroke aphasia. Repetitive transcranial magnetic stimulation (rTMS) has gained attention for language processing investigations and interventions. This systematic review explores the potential of rTMS as a modality to address action-verb deficits in post-stroke aphasia. We searched MEDLINE via PubMed, CINAHL via Ebsco and Web of Science in February 2024 for English articles (1996–2024). Eligible studies involved post-stroke aphasia action naming rehabilitation with rTMS. In some of these studies, rTMS was combined with speech-language therapy. In total, 10 studies were included in this systematic review. These articles highlight the potential of rTMS in improving verb retrieval deficits. While significant improvements may not be evident, notable progress both before and after intervention is observed in this review. However, it also underscores the need for further research to enhance language recovery for individuals with post-stroke aphasia.
“I Can’t Get No Satisfaction”—Psychosocial Aspects and Awareness of Negative Impacts in Chemsex Users: Results from an Anonymous Online Survey
Authors: Gertzen Marcus , Karcher Sinan , Schwarz Johanna , Rosenberger Cornelia , Strasburger Moritz , Rabenstein Andrea , Strasser Anna-Martina , Palm Ulrich , Rüther Tobias
Published: July 2024

Chemsex is the interplay of substance use by men who have sex with men (MSM) in sexual contexts. The minority stress model and the identity process theory are explanatory models. In this study, we investigated whether (i) differences in certain psychosocial aspects (i.e., shame, aspects of queer identity, and sexual self-concepts) exist between chemsex users and non-users, and (ii) which factors influence an awareness of negative impacts in chemsex users. We conducted an anonymous, cross-sectional, online survey, including sociodemography, sexual history, history of substance use, validated scales for shame-proneness, aspects of queer identity, and sexual self-concepts. Our analysis comprised descriptive statistics, t-tests, Spearman’s correlations, and a multiple linear regression model. We recorded a total of 3257 datasets with 107 chemsex users. Chemsex users showed higher rates for risky sexual behavior. Values for shame proneness, more negative aspects of queer identity, and sexual self-concepts were elevated in chemsex users with an awareness of negative impacts. Sexual anxiety, intravenous substance use, and having had a difficult process coming out were significant predictors of feeling negative impacts. Aspects of shame, queer identity aspects, and sexual self-concepts play an important role in the field of chemsex. Different explanatory models seem to be relevant for different subgroups of chemsex users. Chemsex users with an awareness of a problem were particularly vulnerable and distressed but had the highest motivation for change. Prevention, counseling, and care might profit from the inclusion of these aspects. Further anti-stigma campaigns and a specialization of the healthcare system are needed. Registration: DRKS00022336, date: 29th of October, 2020.
A Prior-Guided Dual Branch Multi-Feature Fusion Network for Building Segmentation in Remote Sensing Images
Authors: Wu Yingbin , Zhao Peng , Wang Fubo , Zhou Mingquan , Geng Shengling , Zhang Dan
Published: July 2024

The domain of remote sensing image processing has witnessed remarkable advancements in recent years, with deep convolutional neural networks (CNNs) establishing themselves as a prominent approach for building segmentation. Despite the progress, traditional CNNs, which rely on convolution and pooling for feature extraction during the encoding phase, often fail to precisely delineate global pixel interactions, potentially leading to the loss of vital semantic details. Moreover, conventional CNN-based segmentation models frequently neglect the nuanced semantic differences between shallow and deep features during the decoding phase, which can result in subpar feature integration through rudimentary addition or concatenation techniques. Additionally, the unique boundary characteristics of buildings in remote sensing images, which offer a rich vein of prior information, have not been fully harnessed by traditional CNNs. This paper introduces an innovative approach to building segmentation in remote sensing images through a prior-guided dual branch multi-feature fusion network (PDBMFN). The network is composed of a prior-guided branch network (PBN) in the encoding process, a parallel dilated convolution module (PDCM) designed to incorporate prior information, and a multi-feature aggregation module (MAM) in the decoding process. The PBN leverages prior region and edge information derived from superpixels and edge maps to enhance edge detection accuracy during the encoding phase. The PDCM integrates features from both branches and applies dilated convolution across various scales to expand the receptive field and capture a more comprehensive semantic context. During the decoding phase, the MAM utilizes deep semantic information to direct the fusion of features, thereby optimizing segmentation efficacy. Through a sequence of aggregations, the MAM gradually merges deep and shallow semantic information, culminating in a more enriched and holistic feature representation. Extensive experiments are conducted across diverse datasets, such as WHU, Inria Aerial, and Massachusetts, revealing that PDBMFN outperforms other sophisticated methods in terms of segmentation accuracy. In the key segmentation metrics, including mIoU, precision, recall, and F1 score, PDBMFN shows a marked superiority over contemporary techniques. The ablation studies further substantiate the performance improvements conferred by the PBN’s prior information guidance and the efficacy of the PDCM and MAM modules.
CRISPR-Cas9 Knockout Screens Identify DNA Damage Response Pathways and BTK as Essential for Cisplatin Response in Diffuse Large B-Cell Lymphoma
Authors: Issa Issa Ismail , Due Hanne , Brøndum Rasmus Froberg , Veeravakaran Vidthdyan , Haraldsdóttir Hulda , Sylvester Cathrine , Brogaard Asta , Dhanjal Soniya , Schmierer Bernhard , Dybkær Karen
Published: July 2024

The recurrence of diffuse large B-cell lymphoma (DLBCL) has been observed in 40% of cases. The standard of care for refractory/relapsed DLBCL (RR-DLBCL) is platinum-based treatment prior to autologous stem cell transplantation; however, the prognosis for RR-DLBCL patients remains poor. Thus, to identify genes affecting the cisplatin response in DLBCL, cisplatin-based whole-genome CRISPR-Cas9 knockout screens were performed in this study. We discovered DNA damage response (DDR) pathways as enriched among identified sensitizing CRISPR-mediated gene knockouts. In line, the knockout of the nucleotide excision repair genes XPA and ERCC6 sensitized DLBCL cells to platinum drugs irrespective of proliferation rate, thus documenting DDR as essential for cisplatin sensitivity in DLBCL. Functional analysis revealed that the loss of XPA and ERCC6 increased DNA damage levels and altered cell cycle distribution. Interestingly, we also identified BTK, which is involved in B-cell receptor signaling, to affect cisplatin response. The knockout of BTK increased cisplatin sensitivity in DLBCL cells, and combinatory drug screens revealed a synergistic effect of the BTK inhibitor, ibrutinib, with platinum drugs at low concentrations. Applying local and external DLBCL cohorts, we addressed the clinical relevance of the genes identified in the CRISPR screens. BTK was among the most frequently mutated genes with a frequency of 3–5%, and XPA and ERCC6 were also mutated, albeit at lower frequencies. Furthermore, 27–54% of diagnostic DLBCL samples had mutations in pathways that can sensitize cells to cisplatin. In conclusion, this study shows that XPA and ERCC6, in addition to BTK, are essential for the response to platinum-based drugs in DLBCL.
A Multi-Center Retrospective Observational Analysis of Three-Year Experience of Our Protocol for Prevention and Monitoring of Surgical Site Infections in Implant-Based Breast Reconstruction
Authors: Bottosso Stefano , Sidoti Giulia Benedetta , Vita Ludovica , Scian Alessandro , Bonat Guarini Luigi , Renzi Nadia , Ramella Vittorio , Papa Giovanni
Published: July 2024

Background: With the rise in the mastectomy rate, the number of patients who choose to undergo postmastectomy reconstruction has been increasing, and implant-based procedures are the most performed methods for postmastectomy breast reconstruction. Among the possible complications, the most feared is the loss of reconstruction. It can be related to several reasons, but one of the most common is infection of the implant, which can lead to prolonged antibiotic treatment, undesired additional surgical procedures, increased incidence of capsular contracture, and unsatisfactory aesthetics results, with a huge psychological impact on patients. Aims: The primary intent of this study is to analyze the status of infection rates at our institution and evaluate the effectiveness of our prevention protocol since its introduction. Secondly, we compared data of the surgical site infections (SSIs) after implant-based breast reconstruction at Trieste Hospital, where the protocol has been employed since 2020, and in another center, where plastic surgeons of our team are involved, with different prevention procedures. Methods and Results: We enrolled 396 female patients, who underwent implant-based breast reconstruction, using definitive mammary implants or breast tissue expanders, with or without ADM (acellular dermal matrix), both for breast cancer and risk-reducing surgery in BRCA1/2 patients. Patients treated at the Hospital of Trieste, with the use of the prevention protocol, were considered the experimental group (group 1), while patients treated in Gorizia by the same breast team with standardized best-practice rules, but without the use of the prevention protocol, were considered the control group (group 2). Infected patients were 5 in the first group (1.7%) and 8 in the second one (7.9%), with a global infection rate of 3.2%. Conclusion: After the introduction of our prevention protocol, we faced a lower incidence of infection after breast surgery with implants or tissue expanders.
Electrochemical Detection of Acetaminophen in Pharmaceuticals Using Rod-Shaped α-Bi2O3 Prepared via Reverse Co-Precipitation
Authors: Andjelković Ljubica , Đurđić Slađana , Stanković Dalibor , Kremenović Aleksandar , Pavlović Vladimir B. , Jeremić Dejan A. , Šuljagić Marija
Published: July 2024

This study employed a novel synthetic approach involving a modified reverse co-precipitation method utilizing glacial acetic acid to synthesize α-Bi2O3. X-ray powder diffraction and scanning and transmission electron microscopy analyses revealed the formation of a rod-like α-Bi2O3 microstructure. The prepared material was utilized to modify a glassy carbon paste (GCP) electrode for the development of an electrochemical sensor for acetaminophen (APAP) detection using differential pulse voltammetry (DPV). Cyclic voltammetry studies revealed that the GCP@Bi2O3 electrode exhibited enhanced electrochemical properties compared to the bare GCP. The designed GCP@Bi2O3 sensor detected APAP in the linear concentration range from 0.05 to 12.00 µM, with LOQ and LOD of 36 nM and 10 nM, respectively. Additionally, the developed sensor demonstrated sufficient precision, repeatability, and selectivity toward APAP detection. The recovery values between the declared and found APAP content in a pharmaceutical formulation (Caffetin®) displayed the advantageous accuracy, precision, and applicability of the GCP@Bi2O3 sensor and the developed DPV method for real-time APAP detection in pharmaceuticals, with minimal interference from the matrix effect.
Environmental Pollution Monitoring via Capillary Zone Electrophoresis and UHPLC Simultaneous Quantification of Some Antipsychotic Drug Residues in Industrial Wastewater Effluents
Authors: Alabbas Alhumaidi B. , Slimani Rachid , El Ouahabi Imane , Zarrouk Abdelkader , Lazar Said , Azzallou Rachid , Shalaby Noha F. , Abdel-Gawad Sherif A.
Published: July 2024

Monitoring and measuring pharmaceutical pollutants in environmental samples is a vital and complex task due to their potential detrimental effects on human health, even at low levels. Using capillary zone electrophoresis (CZE) and ultra-high-performance liquid chromatography (UHPLC), it was possible to separate and measure three commonly used antipsychotic drugs, chlorpromazine (CPZ), haloperidol (HAL), and risperidone (RIS), in wastewater of the pharmaceutical industry. The technique of solid-phase extraction (SPE) was developed and implemented as a very effective method for preparing samples prior to analysis. The settings of the capillary electrophoretic and chromatographic techniques were adjusted to obtain the most efficient separation profile for the medications being studied. The concentration of all the medicines being investigated ranged from 0.5 to 50 µg/mL. SPE was used to treat real wastewater samples after a thorough validation process that followed the rules set by ICH-Q2B. The developed assays were then effectively employed to identify the tested antipsychotic substances in the real wastewater samples. The provided methodologies may be efficiently utilized to monitor the extent of environmental contamination caused by the investigated pharmaceuticals.
How to Crystallize Glass with a Femtosecond Laser
Authors: Que Ruyue , Lancry Matthieu , Cavillon Maxime , Poumellec Bertrand
Published: July 2024

The crystallization of glass through conventional thermal annealing in a furnace is a well-understood process. However, crystallization by femtosecond (fs) laser brings another dimension to this process. The pulsed nature of the irradiation necessitates a reevaluation of the parameters for optimal crystallization and an understanding of the particularities of using fs laser. This includes adjusting the laser pulse energy, the repetition rate, and the writing speed to either initiate nucleation or achieve substantial crystal growth. Therefore, a key challenge of this work is to establish reliable calculations for understanding the link between the size of the crystallized region and an ongoing transition (e.g., solid-to-solid, liquid-to-solid), while accounting for the aforementioned laser parameters. In this context, and based on previous work, a temperature distribution (in space and time) is simulated to model the thermal treatment at any point in the glass. By setting the condition that the temperatures are between the glass transition and melting temperature, the simulated crystallized region size can be compared with experimental observations. For that purpose, knowledge of the beam width at the focal point and of the absorbed beam energy fraction are critical inputs that were extracted from experiments found in the literature. After that, the management of the crystallization process and the width of the crystallization line can be achieved according to pulse energy, e.g., crystallite size, and also the effect of the scanning speed can be understood. Among the main conclusions to highlight, we disclose the laser conditions that determine the extent of the crystallized area and deduce that it is never of interest to increase the pulse energy too much as opposed to the repetition rate for the uniform crystallized line.
Growth Behaviors of Bubbles and Intermetallic Compounds in Solidifying Al-5 wt.% Mn Alloy
Authors: Huang Shudong , Lu Wenquan
Published: July 2024

The growth behaviors of hydrogen bubbles and intermetallic compounds (IMCs) during solidification of an Al-5 wt.% Mn alloy was investigated by synchrotron radiography. Results show that bubble collapse can increase hydrogen concentration in nearby Al melt, thus facilitating the formation and growth of new bubbles. Under the interference of Al6Mn IMCs, the growth method of an individual bubble is changed from a Gaussian distribution to a linear model. Al6Mn crystal growth can be divided into three stages: first an isotropic spherical crystal appears, then it evolves into primary branches, and eventually forms an irregular octahedron.
Risk Assessment and Optimization for Pregnancy in Patients with Rheumatic Diseases
Authors: Kwok Alyssa
Published: July 2024

Patients with rheumatic diseases frequently operate with incomplete or incorrect information while planning for and experiencing pregnancy, often due to variability in provider care and knowledge. Risk assessment at each stage of pregnancy—pre-conception, during pregnancy, and postpartum—is focused on reducing maternal and neonatal complications. This review aims to compile updated, evidence-based guidance on how to minimize risk factors contributing to adverse pregnancy outcomes (APOs). Mitigation of known causes of infertility, appropriate testing and monitoring, achieving low disease activity on pregnancy-safe disease-modifying antirheumatic drugs (DMARDs) prior to conception, controlling hypertension (a frequent comorbidity among patients with certain rheumatic diseases), and the use of appropriate adjunctive medications (such as low-dose aspirin when preeclampsia risk is high) can optimize fertility and prevent adverse maternal and neonatal outcomes.
IoT Privacy Risks Revealed
Authors: Chang Kai-Chih , Niu Haoran , Kim Brian , Barber Suzanne
Published: July 2024

A user’s devices such as their phone and computer are constantly bombarded by IoT devices and associated applications seeking connection to the user’s devices. These IoT devices may or may not seek explicit user consent, thus leaving the users completely unaware the IoT device is collecting, using, and/or sharing their personal data or, only marginal informed, if the user consented to the connecting IoT device but did not read the associated privacy policies. Privacy policies are intended to inform users of what personally identifiable information (PII) data will be collected about them and the policies about how those PII data will be used and shared. This paper presents novel tools and the underlying algorithms employed by the Personal Privacy Assistant app (UTCID PPA) developed by the University of Texas at Austin Center for Identity to inform users of IoT devices seeking to connect to their devices and to notify those users of potential privacy risks posed by the respective IoT device. The assessment of these privacy risks must deal with the uncertainty associated with sharing the user’s personal data. If privacy risk (R) equals the consequences (C) of an incident (i.e., personal data exposure) multiplied by the probability (P) of those consequences occurring (C × P), then efforts to control risks must seek to reduce the possible consequences of an incident as well as reduce the uncertainty of the incident and its consequences occurring. This research classifies risk according to two parameters: expected value of the incident’s consequences and uncertainty (entropy) of those consequences. This research calculates the entropy of the privacy incident consequences by evaluating: (1) the data sharing policies governing the IoT resource and (2) the type of personal data exposed. The data sharing policies of an IoT resource are scored by the UTCID PrivacyCheck™, which uses machine learning to read and score the IoT resource privacy policies against metrics set forth by best practices and international regulations. The UTCID Identity Ecosystem uses empirical identity theft and fraud cases to assess the entropy of privacy incident consequences involving a specific type of personal data, such as name, address, Social Security number, fingerprint, and user location. By understanding the entropy of a privacy incident posed by a given IoT resource seeking to connect to a user’s device, UTCID PPA offers actionable recommendations enhancing the user’s control over IoT connections, interactions, their personal data, and, ultimately, user-centric privacy control.
Coherence-Enhanced Single-Qubit Thermometry out of Equilibrium
Authors: Frazão Gonçalo , Pezzutto Marco , Omar Yasser , Zambrini Cruzeiro Emmanuel , Gherardini Stefano
Published: July 2024

The metrological limits of thermometry operated in nonequilibrium dynamical regimes are analyzed. We consider a finite-dimensional quantum system, employed as a quantum thermometer, in contact with a thermal bath inducing Markovian thermalization dynamics. The quantum thermometer is initialized in a generic quantum state, possibly including quantum coherence with respect to the Hamiltonian basis. We prove that the precision of the thermometer, quantified by the Quantum Fisher Information, is enhanced by the quantum coherence in its initial state. We analytically show this in the specific case of qubit thermometers for which the maximization of the Quantum Fisher Information occurs at a finite time during the transient thermalization dynamics. Such a finite-time precision enhancement can be better than the precision that is achieved asymptotically.
Information Entropy Analysis of a PIV Image Based on Wavelet Decomposition and Reconstruction
Authors: Ke Zhiwu , Zheng Wei , Wang Xiaoyu , Lin Mei
Published: July 2024

In particle image velocimetry (PIV) experiments, background noise inevitably exists in the particle images when a particle image is being captured or transmitted, which blurs the particle image, reduces the information entropy of the image, and finally makes the obtained flow field inaccurate. Taking a low-quality original particle image as the research object in this research, a frequency domain processing method based on wavelet decomposition and reconstruction was applied to perform particle image pre-processing. Information entropy analysis was used to evaluate the effect of image processing. The results showed that useful high-frequency particle information representing particle image details in the original particle image was effectively extracted and enhanced, and the image background noise was significantly weakened. Then, information entropy analysis of the image revealed that compared with the unprocessed original particle image, the reconstructed particle image contained more effective details of the particles with higher information entropy. Based on reconstructed particle images, a more accurate flow field can be obtained within a lower error range.
A Review of Meta-Analyses of Correlation Coefficients on L2 Reading Comprehension
Authors: Jeon Eun-Hee , Yamashita Junko
Published: July 2024

Quantitative meta-analyses have gained popularity among L2 reading researchers in recent years. Meta-analyses, especially meta-analyses that investigate the relationships among variables (e.g., meta-analyses of correlation coefficients, meta-analytic structural equation modeling), are well-suited for L2 reading research due to their componential nature. The present study reviews 14 meta-analyses on L2 reading comprehension published between 2010 and 2023, with a focus on their key study features and findings. While all of the 14 meta-analyses examined the relationship between one or more reading-related variables and L2 reading comprehension and yielded substantial convergence in their findings, their research focus and scope also varied widely, leading to some level of diversity in their scope of literature search, methods of analysis, and findings. We review our findings on the convergence and divergence of the study features across the 14 meta-analyses, summarize their key findings, and provide suggestions for future research.
Spatial Reasoning Excellence: A Synergy of VanTassel-Baska’s Integrated Curriculum Model and Talent Development
Authors: Cotabish Alicia , Dailey Debbie , Trumble Jason , Miller Rachelle
Published: July 2024

This manuscript explores the integration of spatial reasoning into K-12 education through the lens of Joyce VanTassel-Baska’s Integrated Curriculum Model (ICM) and a talent development approach. It emphasizes the significance of nurturing spatial reasoning components—visualization, rotation, orientation, and perception—for academic success, problem-solving, and career prospects, especially for academically talented students. Through collaboration with talent development strategies, including mentorship and differentiated instruction, this approach provides a dynamic, real-world-focused learning experience. Inclusive and designed to engage the educational community, it aims to prepare students for complex global challenges, highlighting the transformative power of tailored education in developing versatile societal contributors.
Education Research in ‘Interesting Times’
Authors: Muijs Daniel
Published: July 2024

It is no secret to any of us that the world we live in is going through a great deal of turbulence, with the impact of COVID-19 lingering and social and political change occurring across continents [...]
Fluid-Solid-Thermal Coupled Freezing Modeling Test of Soil under the Low-Temperature Condition of LNG Storage Tank
Authors: Jin Guolong , Xie Xiongyao , Li Pan , Li Hongqiao , Zhao Mingrui , Zou Meitao
Published: July 2024

Due to the extensive utilization of liquid nature gas (abbreviated as LNG) resources and a multitude of considerations, LNG storage tanks are gradually transitioning towards smaller footprints and heightened safety standards. Consequently, underground LNG storage tanks are being designed and constructed. However, underground LNG storage tanks release a considerable quantity of cold into the ground under both accidental and normal conditions. The influence of cold results in the ground freezing, which further compromises the safety of the structure. Existing research has neglected to consider the effects of this. This oversight could potentially lead to serious safety accidents. In this work, a complete set of experiments using a novel LNG underground storage tank fluid-solid-thermal coupled cryogenic leakage scale model were conducted for the first time to simulate the effect of the tank on the soil temperature field, stress field, and displacement field and to analyze the development of the three fields and the results of the effect. This research helps the related personnel to better design, construct, and evaluate the LNG underground storage tanks to avoid the catastrophic engineering risks associated with cryogenic leakage and helps to improve the design process of LNG underground storage tanks.
Active Thermal Management Method for Improving Current Capability of Power Devices under Influence of Random Convection
Authors: He Weichao , Zhu Yiming , Liu Zijian , Ying Zhanfeng , Zu Wei
Published: July 2024

The active thermal management (ATM) method can improve the current capability of power devices safely by utilizing the thermal limit of the device. However, the existing methods are not suitable for power devices affected by random convection. This is because the randomness of convection will lead to the uncertainty of increased current capability, which is unacceptable in most engineering applications. To overcome the shortcomings of existing ATM methods, this paper proposed a novel ATM method for power devices under the influence of random convection. In the proposed method, the short-time current capability of the power device is maximized according to the thermal inertia of the device and maximum load current. The continuous current capability of the power device is determined by a maximum continuous current that satisfies the over-temperature risk constraint of the device. To accurately estimate the maximum continuous current, an uncertainty model is presented for the convective thermal resistance of the power device based on wavelet packet transform and Markov chain. A series of experimental studies are carried out by taking a power MOSFET as an example. The experimental results show that the proposed method can safely improve the output performance of the power device without causing random fluctuations in the current capability.
Performance Analysis of Interconnection and Differential Power Processing Techniques under Partial Shading Conditions
Authors: Gouvêa Evaldo Chagas , Castro Thais Santos , de Souza Teófilo Miguel
Published: July 2024

Partial shading conditions can cause low output power, hotspots, and a reduced lifespan in photovoltaic arrays. Interconnection (IC) and differential power processing (DPP) can be used to mitigate these effects. When individually applied to an array, these techniques can significantly increase the generated power. A few authors studied the combined use of these schemes under specific conditions such as large-scale arrays or a complex combination of several techniques, making it difficult to identify the individual contribution of each technique. Here, we aimed to determine whether the combined use of a switching-inductor DPP circuit and a total-cross-tied interconnection scheme presents better performance than each standalone technique, using a small-scale photovoltaic array. An array was tested using IC, DPP, and a combination of both techniques, and the array was subjected to 13 shading patterns and two irradiance levels. The performance in each case was assessed using maximum output power, performance ratio, mismatch power loss, and power enhancement indicators. The results showed that a standalone differential power processing circuit presents better performance than when it is combined with an interconnection. The DPP showed performance ratio values of up to 97%, mismatch power losses lower than 36.9%, and a power enhancement of up to 95.9%. The standalone interconnection shows the worst performance among the three techniques.
Magnetic Resonance Imaging-Compatible Electromagnetic Actuator: Design and Tests
Authors: Chauvière Simon , Belguerras Lamia , Lubin Thierry , Mezani Smail , Leclerc Sébastien , Guendouz Laoues
Published: July 2024

This paper presents the detailed design, construction and tests of a protype iron-free MRI-compatible electromagnetic actuator. The originality of this proposal lies in the use of the homogeneous static magnetic field B0, present in the MRI bore, to ensure the electromechanical energy conversion. The armature is composed of three rectangular coils in a three-phase arrangement, which makes the actuator very light-weight and compact. The operating principle is that of an AC synchronous motor with a rotating armature. In order to design the actuator, a 3D analytical electromagnetic model is developed to predict the magnetic field produced by the armature winding. Then, a 3D finite element (FE) computation is performed to validate the analytically calculated magnetic field. The developed analytical model is then inserted into an optimization routine based on Genetic Algorithms (GAs) to obtain the prototype dimensions to be realized. Finally, the prototype is constructed and tested inside an MRI research scanner. The results indicate that the reduction in the Signal-to-Noise Ratio (SNR) and the geometrical distortion are less than 5% when the actuator is powered with a current of 10 times the rated one and when it is located very close to the subject to be imaged.
Effects of Stand Density on Tree Growth, Diversity of Understory Vegetation, and Soil Properties in a Pinus koraiensis Plantation
Authors: Iddrisu Abdul-Qadir , Hao Yuanqin , Issifu Hamza , Getnet Ambachew , Sakib Nazmus , Yang Xiubo , Abdallah Mutaz Mohammed , Zhang Peng
Published: July 2024

The regulation of stand density has been studied in specific aspects of plantations with different age categories. A clearer understanding is still required of the extent to which stand density impacts multiple plantation attributes such as tree growth, understory vegetation diversity, and soil properties in Korean pine (Pinus koraeinsis Sieb. et Zucc) plantations. This study utilized a 43-year-old middle-aged Korean pine plantation in Qingping Forest Farm in northeast China to answer the research question posed. Three stand density levels, low stand density (LSD, 716 trees/ha), medium stand density (MSD, 850 trees/ha), and high stand density (HSD, 916 trees/ha) were studied for their effects on plantation attributes enumerated above. The results revealed a significant (p < 0.05) effect of stand density on mean stand volume (m3). Medium stand density had the highest mean stand volume of 26.16 (±0.27) m3 while the lowest stand volume was recorded for the low stand density at 14.90 (±1.72) m3. Also, significant differences in total nitrogen, total potassium, available nitrogen, available potassium, and percentage soil moisture content were observed among stand density levels. Additionally, stand density was found to have significant effects on species richness, Shannon–Wiener, and Simpson’s diversity indexes for the shrub and herb layers of the plantation. This study shows that a medium stand density is the most optimal for promoting tree growth and understory biodiversity, as well as enhancing the status of certain soil nutrients. Thus, medium density achieves a balance between growth, nutrient availability, and biodiversity in middle-aged Korean pine plantations after a short period of thinning. These findings provide valuable knowledge for forest management, emphasizing the significance of continuous, long-term, and site-specific research.
A Packet Content-Oriented Remote Code Execution Attack Payload Detection Model
Authors: Sun Enbo , Han Jiaxuan , Li Yiquan , Huang Cheng
Published: July 2024

In recent years, various Remote Code Execution vulnerabilities on the Internet have been exposed frequently; thus, more and more security researchers have begun to pay attention to the detection of Remote Code Execution attacks. In this paper, we focus on three kinds of common Remote Code Execution attacks: XML External Entity, Expression Language Injection, and Insecure Deserialization. We propose a packet content-oriented Remote Code Execution attack payload detection model. For the XML External Entity attack, we propose an algorithm to construct the use-definition chain of XML entities, and implement detection based on the integrity of the chain and the behavior of the chain’s tail node. For the Expression Language Injection and Insecure Deserialization attack, we extract 34 features to represent the string operation and the use of sensitive classes/methods in the code, and then train a machine learning model to implement detection. At the same time, we build a dataset to evaluate the effect of the proposed model. The evaluation results show that the model performs well in detecting XML External Entity attacks, achieving a precision of 0.85 and a recall of 0.94. Similarly, the model performs well in detecting Expression Language Injection and Insecure Deserialization attacks, achieving a precision of 0.99 and a recall of 0.88.
Effect of Sol–Gel Silica Matrices on the Chemical Properties of Adsorbed/Entrapped Compounds
Authors: Burg Ariela , Yadav Krishna K. , Meyerstein Dan , Kornweitz Haya , Shamir Dror , Albo Yael
Published: July 2024

The sol–gel process enables the preparation of silica-based matrices with tailored composition and properties that can be used in a variety of applications, including catalysis, controlled release, sensors, separation, etc. Commonly, it is assumed that silica matrices prepared via the sol–gel synthesis route are “inert” and, therefore, do not affect the properties of the substrate or the catalyst. This short review points out that porous silica affects the properties of adsorbed/entrapped species and, in some cases, takes an active part in the reactions. The charged matrix affects the diffusion of ions, thus affecting catalytic and adsorption processes. Furthermore, recent results point out that ≡Si-O. radicals are long-lived and participate in redox processes. Thus, clearly, porous silica is not an inert matrix as commonly considered.
Design and Experimental Study of a Traction Double-Row Automatic Transplanter for Solanum Lycopersicum Seedlings
Authors: Ji Dong , Liu Limin , Zeng Fandi , Zhang Guangteng , Liu Yinzeng , Diao Hongwei , Tian Subo , Zhao Zhihuan
Published: July 2024

The most important part of fruit cultivation is transplanting, which can be completed efficiently by an automatic transplanter. In this study, an automatic solanum lycopersicum transplanter was developed. It is primarily composed of the following devices: a seedling tray fixator, a mechanical transplanting arm, double horizontal driving modules, double vertical driving cylinders, a seedling separation device, double-crank five-bar planting devices, a power distribution system, and a PLC control system. An experimental test on an automatic transplanter was carried out on dry land. The experimental results showed that when the planting frequency was 80 plants/(min·row), the transplanting success rate was 93.89%, the missed planting rate was 1.58%, the replanting rate was 0.65%, the lodging rate was 1.94%, and the exposed seedling rate was 1.94%. Each device of the automatic transplanter was coordinated to complete the transplanting process. The automatic transplanter met the operation requirements, and it not only transplanted in dry land but also provided a theoretical basis for fruit cultivation in solar greenhouses in the future.
KLF4 Suppresses the Progression of Hepatocellular Carcinoma by Reducing Tumor ATP Synthesis through Targeting the Mir-206/RICTOR Axis
Authors: Wang Yongjin , Zuo Dinglan , Huang Zhenkun , Qiu Yuxiong , Wu Zongfeng , Liu Shaoru , Zeng Yi , Qiu Zhiyu , He Wei , Li Binkui , Yuan Yunfei , Niu Yi , Qiu Jiliang
Published: July 2024

To address the increased energy demand, tumor cells undergo metabolic reprogramming, including oxidative phosphorylation (OXPHOS) and aerobic glycolysis. This study investigates the role of Kruppel-like factor 4 (KLF4), a transcription factor, as a tumor suppressor in hepatocellular carcinoma (HCC) by regulating ATP synthesis. Immunohistochemistry was performed to assess KLF4 expression in HCC tissues. Functional assays, such as CCK-8, EdU, and colony formation, as well as in vivo assays, including subcutaneous tumor formation and liver orthotopic xenograft mouse models, were conducted to determine the impact of KLF4 on HCC proliferation. Luciferase reporter assay and chromatin immunoprecipitation assay were utilized to evaluate the interaction between KLF4, miR-206, and RICTOR. The findings reveal low KLF4 expression in HCC, which is associated with poor prognosis. Both in vitro and in vivo functional assays demonstrate that KLF4 inhibits HCC cell proliferation. Mechanistically, it was demonstrated that KLF4 reduces ATP synthesis in HCC by suppressing the expression of RICTOR, a core component of mTORC2. This suppression promotes glutaminolysis to replenish the TCA cycle and increase ATP levels, facilitated by the promotion of miR-206 transcription. In conclusion, this study enhances the understanding of KLF4’s role in HCC ATP synthesis and suggests that targeting the KLF4/miR-206/RICTOR axis could be a promising therapeutic approach for anti-HCC therapeutics.
SARS-CoV-2 Nucleocapsid Protein Induces Tau Pathological Changes That Can Be Counteracted by SUMO2
Authors: Orsini Franca , Bosica Marco , Martucci Annacarla , De Paola Massimiliano , Comolli Davide , Pascente Rosaria , Forloni Gianluigi , Fraser Paul E. , Arancio Ottavio , Fioriti Luana
Published: July 2024

Neurologic manifestations are an immediate consequence of SARS-CoV-2 infection, the etiologic agent of COVID-19, which, however, may also trigger long-term neurological effects. Notably, COVID-19 patients with neurological symptoms show elevated levels of biomarkers associated with brain injury, including Tau proteins linked to Alzheimer’s pathology. Studies in brain organoids revealed that SARS-CoV-2 alters the phosphorylation and distribution of Tau in infected neurons, but the mechanisms are currently unknown. We hypothesize that these pathological changes are due to the recruitment of Tau into stress granules (SGs) operated by the nucleocapsid protein (NCAP) of SARS-CoV-2. To test this hypothesis, we investigated whether NCAP interacts with Tau and localizes to SGs in hippocampal neurons in vitro and in vivo. Mechanistically, we tested whether SUMOylation, a posttranslational modification of NCAP and Tau, modulates their distribution in SGs and their pathological interaction. We found that NCAP and Tau colocalize and physically interact. We also found that NCAP induces hyperphosphorylation of Tau and causes cognitive impairment in mice infected with NCAP in their hippocampus. Finally, we found that SUMOylation modulates NCAP SG formation in vitro and cognitive performance in infected mice. Our data demonstrate that NCAP induces Tau pathological changes both in vitro and in vivo. Moreover, we demonstrate that SUMO2 ameliorates NCAP-induced Tau pathology, highlighting the importance of the SUMOylation pathway as a target of intervention against neurotoxic insults, such as Tau oligomers and viral infection.
Overview and Evolution of Insect Fibroin Heavy Chain (FibH)
Authors: Zhang Tong , Ma Sanyuan , Zhang Ziyang , Guo Yongkang , Yang Daiying , Lu Wei
Published: July 2024

The FibH gene, crucial for silk spinning in insects, encodes a protein that significantly influences silk fiber mechanics. Due to its large size and repetitive sequences, limited known sequences of insect FibH impede comprehensive understanding. Here, we analyzed 114 complete FibH gene sequences from Lepidoptera (71 moths, 24 butterflies) and 13 Trichoptera, revealing single-copy FibH in most species, with 2–3 copies in Hesperinae and Heteropterinae (subfamily of skippers). All FibH genes are structured with two exons and one intron (39–45 bp), with the second exon being notably longer. Moths exhibit higher GC content in FibH compared to butterflies and Trichoptera. The FibH composition varies among species, with moths and butterflies favoring Ala, Gly, Ser, Pro, Gln, and Asn, while Trichoptera FibH is enriched in Gly, Ser, and Arg, and has less Ala. Unique to Trichoptera FibH are Tyr, Val, Arg, and Trp, whereas Lepidoptera FibH is marked by polyAla (polyalanine), polySer (polyserine), and the hexapeptide GAGSGA. A phylogenetic analysis suggests that Lepidoptera FibH evolved from Trichoptera, with skipper FibH evolving from Papilionoidea. This study substantially expands the FibH repertoire, providing a foundation for the development of artificial silk.