bluuebunny/crossref_metadata_2025 huggingface dataset:
Mechanisms Associated with Cognitive and Behavioral Impairment Induced by Arsenic Exposure
Authors: Vázquez Cervantes Gustavo Ignacio , González Esquivel Dinora Fabiola , Ramírez Ortega Daniela , Blanco Ayala Tonali , Ramos Chávez Lucio Antonio , López-López Humberto Emanuel , Salazar Alelí , Flores Itamar , Pineda Benjamín , Gómez-Manzo Saúl , Pérez de la Cruz Verónica
Published: October 2023

Arsenic (As) is a metalloid naturally present in the environment, in food, water, soil, and air; however, its chronic exposure, even with low doses, represents a public health concern. For a long time, As was used as a pigment, pesticide, wood preservative, and for medical applications; its industrial use has recently decreased or has been discontinued due to its toxicity. Due to its versatile applications and distribution, there is a wide spectrum of human As exposure sources, mainly contaminated drinking water. The fact that As is present in drinking water implies chronic human exposure to this metalloid; it has become a worldwide health problem, since over 200 million people live where As levels exceed safe ranges. Many health problems have been associated with As chronic exposure including cancer, cardiovascular diseases, gastrointestinal disturbances, and brain dysfunctions. Because As can cross the blood–brain barrier (BBB), the brain represents a target organ where this metalloid can exert its long-term toxic effects. Many mechanisms of As neurotoxicity have been described: oxidative stress, inflammation, DNA damage, and mitochondrial dysfunction; all of them can converge, thus leading to impaired cellular functions, cell death, and in consequence, long-term detrimental effects. Here, we provide a current overview of As toxicity and integrated the global mechanisms involved in cognitive and behavioral impairment induced by As exposure show experimental strategies against its neurotoxicity.
JAK3 Inhibition Regulates Stemness and Thereby Controls Glioblastoma Pathogenesis
Authors: Smedley William , Patra Amiya
Published: October 2023

Glioblastoma multiforme (GBM) is the most deadly brain tumor, effective treatment options for which still remain elusive. The current treatment procedure of maximal resection followed by chemotherapy has proved to be grossly insufficient to prevent disease progression and death. Despite best efforts, the maximum survival post-diagnosis is a mere 1.5 years. Therefore, there is a huge unmet clinical need to find effective therapeutic procedures to prevent the pathogenesis and relapse of GBM. Small-molecule inhibitors of signaling pathways are an attractive option to prevent various types of tumors. However, no effective small-molecule inhibitors have been successful against GBM in clinical trials. Various signaling pathways are altered and an array of signaling molecules, transcription factors (TFs), and epigenetic modifying factors have been implicated in the pathogenesis of GBM. JAK-STAT pathway alteration is an important contributor to GBM pathogenesis and relapse. Many small-molecule inhibitors of JAKs, or STAT TFs, especially JAK2 and STAT3, have been assessed for their anti-tumor activity in GBM. However, no definitive success so far has been achieved. Herein, by using two small-molecule inhibitors of JAK3, we show that they are quite effective in inhibiting GBM cell proliferation and neurosphere formation, downregulating their stemness character, and inducing differentiation into neuronal origin cells. The effect of a single treatment with the drugs, both in a serum-containing differentiation medium and in a proliferation medium containing EGF and FGF, was really strong in limiting GBM cell growth, suggesting a potential therapeutic application for these JAK inhibitors in GBM therapy.
Impacts of Integrating Family-Centered Care and Developmental Care Principles on Neonatal Neurodevelopmental Outcomes among High-Risk Neonates
Authors: Alsadaan Nourah , Ramadan Osama Mohamed Elsayed , Alqahtani Mohammed , Shaban Mostafa , Elsharkawy Nadia Bassuoni , Abdelaziz Enas Mahrous , Ali Sayed Ibrahim
Published: October 2023

Background: Integrating family-centered care (FCC) and developmental care (DC) principles in neonatal care settings may improve neurodevelopmental outcomes for high-risk neonates. However, the combined impact of FCC and DC has been underexplored. This study aimed to investigate the effects of integrated FCC and DC on neurodevelopment and length of hospital stay in high-risk neonates. Methods: A quasi-experimental pre–post study was conducted among 200 high-risk neonates (<32 weeks gestation or <1500 g) admitted to neonatal intensive care units (NICU) in Saudi Arabia. The intervention group (n = 100) received integrated FCC and DC for 6 months. The control group (n = 100) received standard care. Neurodevelopment was assessed using the Bayley Scales of Infant Development-III. Length of stay and readmissions were extracted from medical records. Results: The intervention group showed significant improvements in cognitive, motor, and language scores compared to controls (p < 0.05). The intervention group had a 4.3-day reduction in the mean length of stay versus a 1.4-day reduction in controls (p = 0.02). Integrated care independently predicted higher cognitive scores (p = 0.001) and shorter stays (p = 0.006) in regression models. Conclusion: Integrating FCC and DC in neonatal care enhances neurodevelopmental outcomes and reduces hospitalization for high-risk neonates compared to standard care. Implementing relationship-based, developmentally supportive models is critical for optimizing outcomes in this vulnerable population.
An Integrated Approach Using HLAMatchmaker and Pirche II for Epitopic Matching in Pediatric Kidney Transplant—A Romanian Single-Center Study
Authors: Aldea Paul Luchian , Santionean Maria Diana , Elec Alina , Munteanu Adriana , Antal Oana , Loga Luminita , Moisoiu Tudor , Elec Florin Ioan , Delean Dan , Bulata Bogdan , Rachisan (Bot) Andreea Liana
Published: October 2023

(1) Background: Renal transplantation (KT) is the most efficient treatment for chronic kidney disease among pediatric patients. Antigenic matching and epitopic load should be the main criteria for choosing a renal graft in pediatric transplantation. Our study aims to compare the integration of new histocompatibility predictive algorithms with classical human leukocyte antigen (HLA) matching regarding different types of pediatric renal transplants. (2) Methods: We categorized our cohort of pediatric patients depending on their risk level, type of donor and type of transplantation, delving into discussions surrounding their mismatching values in relation to both the human leukocyte antigen Matchmaker software (versions 4.0. and 3.1.) and the most recent version of the predicted indirectly identifiable HLA epitopes (PIRCHE) II score. (3) Results: We determined that the higher the antigen mismatch, the higher the epitopic load for both algorithms. The HLAMatchmaker algorithm reveals a noticeable difference in eplet load between living and deceased donors, whereas PIRCHE II does not show the same distinction. Dialysis recipients have a higher count of eplet mismatches, which demonstrates a significant difference according to the transplantation type. Our results are similar to those of four similar studies available in the current literature. (4) Conclusions: We suggest that an integrated data approach employing PIRCHE II and HLAMatchmaker algorithms better predicts histocompatibility in KT than classical HLA matching.
Managing Dental Phobia in Children with the Use of Virtual Reality: A Systematic Review of the Current Literature
Authors: Rosa Alessio , Pujia Alberto Maria , Docimo Raffaella , Arcuri Claudio
Published: October 2023

Background: It is common today to encounter anxiety in patients facing dental treatment. Virtual reality (VR) is presented as a high-performing and innovative procedure because it can distract patients undergoing dental procedures or prepare them for such treatments. In addition, this meta-analysis has gathered evidence on VR and its ability to reduce dental anxiety in pediatric patients undergoing different treatments. Methods: The major Scopus, PubMed, EMBASE and Web of Science databases were searched for scientific articles published up to 2023. Studies in which VR was used for children and adults as a measure against anxiety during dental treatments were included. VR was defined as a three-dimensional place where patients experience a sense of immersion as they find themselves in attractive and interactive environments that detach them from reality. Anxiety and pain were examined and measured during dental treatments in which VR was used by comparing them with standard care situations. Results: Twenty-five studies were identified, of which eleven met the inclusion criteria. The effect of VR was studied mainly in the pediatric population as a distractive method. Only two studies (not significant) on an adult population were considered. Conclusions: this review shows that VR is an excellent distraction method that is effective in reducing anxiety before dental treatment; however, due to the few studies in this area, further research on VR as a tool to prepare patients for dental treatment is needed.
Tree-Regeneration Decline and Type-Conversion after High-Severity Fires Will Likely Cause Little Western USA Forest Loss from Climate Change
Authors: Baker William L.
Published: October 2023

Temperate conifer forests stressed by climate change could be lost through tree regeneration decline in the interior of high-severity fires, resulting in type conversion to non-forest vegetation from seed-dispersal limitation, competition, drought stress, and reburns. However, is fire triggering this global change syndrome at a high rate? To find out, I analyzed a worst-case scenario. I calculated fire rotations (FRs, expected period to burn once across an area) across ~56 million ha of forests (~80% of total forest area) in 11 western USA states from 2000 to 2020 for total high-severity fire area, interior area (>90 m inward), and reburned area. Unexpectedly, there was no trend in area burned at high severity from 2000 to 2020 across the four forest types studied. The vulnerable interior area averaged only 21.9% of total high-severity fire area, as 78.1% of burned area was within 90 m of live seed sources where successful tree regeneration is likely. FRs averaged 453 years overall, 2089 years in interiors, and 19,514 years in reburns. Creation of vulnerable interior area in a particular location is thus, on average, a 2000+ year event, like a very rare natural disaster, and reburns that may favor type conversion to non-forest have almost no effect. This means that, from 2021 to 2050 at most, only 3.0–4.2% of total forest area may become a vulnerable interior area, based on a likely high aridity-based climate projection of future fire and a higher scenario, where rates in the exceptional 2020 fire year have become the norm. These findings show that increased management to reduce high-severity fires is not currently needed, as the risk to forests from this global change syndrome is likely quite low up to 2050. Faster and larger disturbances (e.g., severe droughts) are more likely to cause most tree mortality or forest loss that occurs by 2050.
The Role of Translocal Practices in a Natural Climate Solution in Ghana
Authors: Narh John , Wehner Stefanie , Ungruhe Christian , Eberth Andreas
Published: October 2023

People-centred reforestation is one of the ways to achieve natural climate solutions. Ghana has established a people-centred reforestation programme known as the Modified Taunya System (MTS) where local people are assigned degraded forest reserves to practice agroforestry. Given that the MTS is a people-centred initiative, socioeconomic factors are likely to have impact on the reforestation drive. This study aims to understand the role of translocal practices of remittances and visits by migrants on the MTS. Using multi-sited, sequential explanatory mixed methods and the lens of socioecological systems, the study shows that social capital and socioeconomic obligations of cash remittances from, as well as visits by migrants to their communities of origin play positive roles on reforestation under the MTS. Specifically, translocal households have access to, and use remittances to engage relatively better in the MTS than households that do not receive remittances. This shows that translocal practices can have a positive impact on the environment at the area of origin of migrants where there are people-centred environmental policies in place.
Cross-Cultural Adaptation, Reliability, and Validity of the Polish Version of the Neck Outcome Score
Authors: Dyrek Nicola , Pulik Łukasz , Piwowarczyk Aleksandra , Skała Wiktoria , Grabowska-Mycko Nina , Łęgosz Paweł
Published: October 2023

This study aimed to translate and psychometrically validate the Neck Outcome Score (NOOS) in the Polish population according to the recommendations of the American Academy of Orthopedic Surgeons Participants completed online version of the NOOS, Neck Disability Index (NDI), and Visual Analogue Scale (VAS) for pain assessment (23 November 2021–9 April 2022). The questionnaires were completed by 57 women and 32 men with cervical spine ailments. A retest was performed after 48 h. The analysis confirmed the high internal consistency (Cronbach’s alpha of 0.95) of the Polish NOOS. No floor/ceiling effects were observed. The Polish NOOS showed a significant Spearman’s coefficient correlation with NDI (0.87; p < 0.001) and VAS (0.79; p < 0.001). The intraclass correlation coefficient (ICC) for the test–retest was found to be high (0.97). The Polish NOOS can be used for clinical and research purposes as an equivalent to the original version.
Behaviors of Bubbles Trapped in Film Coating during Spray Gun Coating and Its Influences on Coating Defects
Authors: Noguchi Ryo , Yano Ayako , Amagai Kenji
Published: October 2023

In this paper, we investigated the behaviors of bubbles entrained in a film coating during spray coating. Air bubbles that remain in a film coating after diluent evaporation cause coating defects called bubbling defects, including fish-eye and crater defects. In this study, the visualization of a film coating revealed that smaller bubbles in the film shrank slowly and disappeared, while larger bubbles remained. These remaining bubbles grew during the heating process for the drying of the film coating. The shrinking phenomenon was explained using bubble dynamics based on the Young–Laplace equation of a bubble’s inner pressure and Henry’s law for bubble gas dissolution into the film coating. This shrinking model is often used in studies on microbubble dynamics. The results suggested the importance of avoiding the entrainment of large bubbles during the spraying process and enhancing the release of air bubbles from the film coating’s surface through the appropriate usage of defoaming agents.
Detecting Breast Tumors in Tomosynthesis Images Utilizing Deep Learning-Based Dynamic Ensemble Approach
Authors: Hassan Loay , Saleh Adel , Singh Vivek Kumar , Puig Domenec , Abdel-Nasser Mohamed
Published: October 2023

Digital breast tomosynthesis (DBT) stands out as a highly robust screening technique capable of enhancing the rate at which breast cancer is detected. It also addresses certain limitations that are inherent to mammography. Nonetheless, the process of manually examining numerous DBT slices per case is notably time-intensive. To address this, computer-aided detection (CAD) systems based on deep learning have emerged, aiming to automatically identify breast tumors within DBT images. However, the current CAD systems are hindered by a variety of challenges. These challenges encompass the diversity observed in breast density, as well as the varied shapes, sizes, and locations of breast lesions. To counteract these limitations, we propose a novel method for detecting breast tumors within DBT images. This method relies on a potent dynamic ensemble technique, along with robust individual breast tumor detectors (IBTDs). The proposed dynamic ensemble technique utilizes a deep neural network to select the optimal IBTD for detecting breast tumors, based on the characteristics of the input DBT image. The developed individual breast tumor detectors hinge on resilient deep-learning architectures and inventive data augmentation methods. This study introduces two data augmentation strategies, namely channel replication and channel concatenation. These data augmentation methods are employed to surmount the scarcity of available data and to replicate diverse scenarios encompassing variations in breast density, as well as the shapes, sizes, and locations of breast lesions. This enhances the detection capabilities of each IBTD. The effectiveness of the proposed method is evaluated against two state-of-the-art ensemble techniques, namely non-maximum suppression (NMS) and weighted boxes fusion (WBF), finding that the proposed ensemble method achieves the best results with an F1-score of 84.96% when tested on a publicly accessible DBT dataset. When evaluated across different modalities such as breast mammography, the proposed method consistently attains superior tumor detection outcomes.
Rapid Remote Online Evaluation in Endoscopic Diagnostics: An Analysis of Biopsy-Proven Respiratory Cytopathology
Authors: Elmas Hatice , Önal Binnur , Steurer Stefan , Hantzsch-Kuhn Birgit , Claussen Martin , Mehdi Elnur , Ince Ümit , Rabe Klaus F. , Sauter Guido , Welker Lutz
Published: October 2023

Background: This prospective study assesses the use of rapid remote online cytological evaluation for diagnosing endoscopical achieved biopsies. It focuses on its effectiveness in identifying benign and malignant conditions using digital image processing. Methods: The study was conducted between April 2021 and September 2022 and involved analyses of 314 Rapid Remote Online Cytological Evaluations in total (154 imprint cytologies, 143 fine needle aspirations and 17 brush cytologies) performed on 239 patients at the LungenClinic Grosshansdorf. During on-site evaluation via telecytology, the time requirement was recorded and the findings were compared with the cyto-/histological and final diagnoses. Results: By means of rapid remote online evaluation, findings of 86 cytological benign, 190 malignant and 38 unclear diagnoses were recorded (Ø assessment time, 100 s; range, 11–370 s). In 27 of the 37 specimens with unclear diagnoses, the final findings were malignant tumours and only 6 were benign changes. The diagnosis of another 4 of these 37 findings remained unclear. Excluding these 37 specimens, rapid remote online evaluation achieved a sensitivity of 90.5% with a specificity of 98.5% and a correct classification rate of 92.4% with regard to the final diagnosis of all cases. As expected, an increase in the sensitivity rate for the cytological detection of malignant tumours (76.1% vs. 92.5%) was found especially in fine-needle aspirations. Conclusions: Rapid remote online analysis allows the fast quantitative and qualitative evaluation of clinically obtained cytological specimens. With a correct classification rate of more than 93%, sampling deficiencies can be corrected promptly and diagnostic and therapeutic approaches can be derived.
Applications of Shaped-Charge Learning
Authors: Galitsky Boris
Published: October 2023

It is well known that deep learning (DNN) has strong limitations due to a lack of explainability and weak defense against possible adversarial attacks. These attacks would be a concern for autonomous teams producing a state of high entropy for the team’s structure. In our first article for this Special Issue, we propose a meta-learning/DNN → kNN architecture that overcomes these limitations by integrating deep learning with explainable nearest neighbor learning (kNN). This architecture is named “shaped charge”. The focus of the current article is the empirical validation of “shaped charge”. We evaluate the proposed architecture for summarization, question answering, and content creation tasks and observe a significant improvement in performance along with enhanced usability by team members. We observe a substantial improvement in question answering accuracy and also the truthfulness of the generated content due to the application of the shaped-charge learning approach.
District Office Leadership Supporting Site-Level Teacher Collaborative Teams
Authors: Voelkel Robert H. , Johnson Christie W. , Nadeem Fiaz
Published: October 2023

Previous researchers examining professional learning communities (PLCs) claim that effective building-level PLCs improve teacher collaboration and student achievement. However, the role of district office leadership in supporting the success of site-level PLC teams is presently underexplored. Using an online survey, we investigated the claim that district office support enhances the success of site-level PLCs. Quantitative data were collected from 596 participants employed at 21 schools within 16 school districts in the north Texas region. Findings derived from correlation and structural equation modeling analyses revealed a significant direct effect of district office leadership support on successful PLC team implementation, suggesting that district leaders play an active role in the districtwide implementation of PLCs.
A Hybrid Quasi-Single-Stage AC-DC Converter with Low Twice-Line-Frequency Output Voltage Ripple
Authors: Yan Tiesheng , Wang Chu , Zhou Shuhan , Wen Hao , Zhou Guohua
Published: October 2023

Power factor correction (PFC) converters have been frequently employed in various switching power supply devices to reduce input current harmonics. However, the PFC converter suffers from an obvious twice-line-frequency output voltage ripple due to the instantaneous power imbalance between constant output power and variable input power. Suppression of twice-line-frequency ripple usually can be realized by the post-stage DC-DC converter of the two-stage cascade PFC converter; however, the two-stage cascade PFC structure is challenging to realize high efficiency since the energy is transferred twice. To achieve high power factor, high efficiency, and low twice-line-frequency ripple, a hybrid quasi-single-stage (QSS) AC-DC converter is presented in this paper, which consists of a dual output hybrid Boost/Flyback PFC converter and a Buck ripple compensation circuit (RCC). The fundamental principles of the proposed converter and the critical conditions of operation mode transition are discussed in the paper. To confirm that the twice-line-frequency ripple is effectively suppressed, the small signal model of Buck RCC is built and analyzed. Moreover, the main characteristics, including operation mode transition angle, input current, power factor, and switching frequency of the proposed hybrid QSS AC-DC converter, are analyzed. By building a 120 W experimental prototype to validate the feasibility of the proposed hybrid QSS AC-DC converter, the experimental results show that the proposed converter can realize PFC function with high efficiency and extremely low twice-line-frequency output voltage ripple.
An Optimal Strategy for Submodule Capacitance Sizing of Cascaded H-Bridge-Based Active Power Filter
Authors: Wang Hengyi , Gao Fei
Published: October 2023

This paper presents capacitor dimensioning to increase a system’s power density while the converter performance for the delta-connected cascaded H-bridge (CHB) active power filter (APF) is not impaired. After comparing aluminum electrolytic capacitors with film capacitors, this paper proposes capacitance design requirements for film capacitors. With the help of trigonometric transformation for periodic time-varying variables, including capacitor voltages and branch voltages, the capacitance design requirements can be represented as positive univariate polynomials, the coefficients of which are with regard to the capacitance value. The optimization solver SeDuMi is then applied to determine whether a capacitance value is feasible by checking the positiveness of the polynomials. This research has very appealing theoretical and practical properties: the time-domain analysis capability for periodic variables is improved, therefore, enabling a fast computation and a broad application. Both the simulations and experimental results validate the proposed strategy. Compared with the previous work, the proposed method can result in a lower capacitance value without degrading the performance, which is beneficial for a low-cost and low-volume system.
Self-Supervised Non-Uniform Low-Light Image Enhancement Combining Image Inversion and Exposure Fusion
Authors: Huang Wei , Li Kaili , Xu Mengfan , Huang Rui
Published: October 2023

Low-light image enhancement is a challenging task in non-uniform low-light conditions, often resulting in local overexposure, noise amplification, and color distortion. To obtain satisfactory enhancement results, most models must resort to carefully selected paired or multi-exposure data sets. In this paper, we propose a self-supervised framework for non-uniform low-light image enhancement to address these issues, only requiring low-light images on their own for training. We first design a robust Retinex model-based image exposure enhancement network (EENet) to obtain global brightness enhancement and noise removal of images by carefully designing the loss function of each decomposition map. Then, to correct overexposed areas in the enhanced image, we incorporate the inverse image of the low-light image for enhancement using EENet. Furthermore, a three-branch asymmetric exposure fusion network (TAFNet) is designed. The two enhanced images and the original image are used as the TAFNet inputs to obtain a globally well-exposed and detail-rich image. Experimental results demonstrate that our framework outperforms some state-of-the-art methods in visual and quantitative comparisons.
Detecting Persuasion Attempts on Social Networks: Unearthing the Potential of Loss Functions and Text Pre-Processing in Imbalanced Data Settings
Authors: Teimas Rúben , Saias José
Published: October 2023

The rise of social networks and the increasing amount of time people spend on them have created a perfect place for the dissemination of false narratives, propaganda, and manipulated content. In order to prevent the spread of disinformation, content moderation is needed. However, manual moderation is unfeasible due to the large amount of daily posts. This paper studies the impact of using different loss functions on a multi-label classification problem with an imbalanced dataset, consisting of 20 persuasion techniques and only 950 samples, provided by SemEval’s 2021 Task 6. We used machine learning models, such as Naive Bayes and Decision Trees, and a custom deep learning architecture, based on DistilBERT and Convolutional Layers. Overall, the machine learning models achieved far worse results than the deep learning model, using Binary Cross Entropy, which we considered our baseline deep learning model. To address the class imbalance problem, we trained our model using different loss functions, such as Focal Loss and Asymmetric Loss. The latter providing the best results, particularly for the least represented classes.
FSTT: Flow-Guided Spatial Temporal Transformer for Deep Video Inpainting
Authors: Liu Ruixin , Zhu Yuesheng
Published: October 2023

Video inpainting aims to complete the missing regions with content that is consistent both spatially and temporally. How to effectively utilize the spatio-temporal information in videos is critical for video inpainting. Recent advances in video inpainting methods combine both optical flow and transformers to capture spatio-temporal information. However, these methods fail to fully explore the potential of optical flow within the transformer. Furthermore, the designed transformer block cannot effectively integrate spatio-temporal information across frames. To address the above problems, we propose a novel video inpainting model, named Flow-Guided Spatial Temporal Transformer (FSTT), which effectively establishes correspondences between missing regions and valid regions in both spatial and temporal dimensions under the guidance of completed optical flow. Specifically, a Flow-Guided Fusion Feed-Forward module is developed to enhance features with the assistance of optical flow, mitigating the inaccuracies caused by hole pixels when performing MHSA. Additionally, a decomposed spatio-temporal MHSA module is proposed to effectively capture spatio-temporal dependencies in videos. To improve the efficiency of the model, a Global–Local Temporal MHSA module is further designed based on the window partition strategy. Extensive quantitative and qualitative experiments on the DAVIS and YouTube-VOS datasets demonstrate the superiority of our proposed method.
A Capacity Enhancement Method for Frequency-Hopping Anti-Jamming Communication Systems
Authors: Yu Ziting , Hao Zhisong , Yao Wang , Jia Min
Published: October 2023

In this paper, we study the enhancement of channel transmission information by expanding the transmission channel in the frequency-hopping rate dimension in a communication system. This is achieved using the frequency-hopping spread spectrum (FHSS) without increasing communication resources, such as power and bandwidth. The anti-jamming capability of the original information is maintained during this process. The spectral characteristics of the extended signal for frequency-hopping (FH) transmission are investigated, a demodulation method based on carrier reconstruction is proposed, the bit error rate performance is simulated, and the capacity enhancement and anti-jamming ability of the extended signal for FH transmission are analyzed.
FLRAM: Robust Aggregation Technique for Defense against Byzantine Poisoning Attacks in Federated Learning
Authors: Chen Haitian , Chen Xuebin , Peng Lulu , Ma Ruikui
Published: October 2023

In response to the susceptibility of federated learning, which is based on a distributed training structure, to byzantine poisoning attacks from malicious clients, resulting in issues such as slowed or disrupted model convergence and reduced model accuracy, we propose a robust aggregation technique for defending against byzantine poisoning attacks in federated learning, known as FLRAM. First, we employ isolation forest and an improved density-based clustering algorithm to detect anomalies in the amplitudes and symbols of client local gradients, effectively filtering out gradients with large magnitude and angular deviation variations. Subsequently, we construct a credibility matrix based on the filtered subset of gradients to evaluate the trustworthiness of each local gradient. Using this credibility score, we further select gradients with higher trustworthiness. Finally, we aggregate the filtered gradients to obtain the global gradient, which is then used to update the global model. The experimental findings show that our proposed approach achieves strong defense performance without compromising FedAvg accuracy. Furthermore, it exhibits superior robustness compared to existing solutions.
Analysis on Fairness and Efficiency of the 3-PLP LDM System Using a Normalized Channel Capacity
Authors: Kim Ho Jae , Kwon Soon-Young , Bae JaeHwui , Hur Namho , Kim Hyoung-Nam
Published: October 2023

This article presents a novel approach to investigate efficient resource allocation in the layered division multiplexing (LDM) system, a key technology in next-generation broadcasting systems. The LDM system provides diverse services, resulting in different channel capacities for each service, unlike the conventional non-orthogonal multiple access scheme that aims for equal channel capacity among users. To achieve efficient resource allocation among services, we proposed a new method that normalizes the channel capacities allocated to different services while maintaining high fairness. Our proposed method involves normalizing the channel capacities of each service and finding the point where the sum of normalized channel capacities is maximized. This point can be obtained using the Lagrange multiplier method, ensuring a high normalized fairness index. Through simulations, we confirmed that the proposed approach maintains high fairness in the LDM system and achieves the highest normalized channel capacities compared to other transmission techniques. These findings provide valuable insights into resource allocation strategies for the LDM system, enabling a fair comparison of efficiency and performance within a multi-service environment.
Basic Mechanisms of Single-Event Occurrence in Silicon Carbide Semiconductor under Terrestrial Atmospheric Neutron Irradiation
Authors: Munteanu Daniela , Autran Jean-Luc
Published: October 2023

This numerical simulation work investigates the basic physical mechanisms of single events induced in a target layer composed of silicon carbide exposed to natural radiation with atmospheric neutrons at the terrestrial level. Using direct calculations and extensive Geant4 simulations, this study provides an accurate investigation in terms of nuclear processes, recoil products, secondary ion production and fragment energy distributions. In addition, the thorough analysis includes a comparison between the responses to neutron irradiation of silicon carbide, carbon (diamond) and silicon targets. Finally, the consequences of these interactions in terms of the generation of electron–hole pairs, which is a fundamental mechanism underlying single-event transient effects at the device or circuit level, are discussed in detail.
Radio Map-Based Trajectory Design for UAV-Assisted Wireless Energy Transmission Communication Network by Deep Reinforcement Learning
Authors: Chen Changhe , Wu Fahui
Published: October 2023

In this paper, we consider a wireless energy-carrying communication network of a UAV. In this communication network, the internet of things (IoT) devices maintain their work via the power supply of batteries. The energy of batteries is slowly consumed over time. The UAV adopts the full-duplex working mode and the flight hover protocol, that is, they can power the target device in the hover position and collect base station data at the same time. Unlike traditional methods, which seek to achieve wireless energy transmission, this paper adopts deep reinforcement learning. On the one hand, the deep reinforcement learning algorithm seeks to solve the dynamic programming problem without a model. The traditional method often requires a prior channel model, to form a formula about variables for convex optimization, while reinforcement learning only requires the interaction between agents and the environment. Then, the strategy is optimized according to the reward function feedback. On the other hand, traditional optimization methods generally solve static programming problems. Since IoT devices constantly collect information from the surrounding physical environment, and their requirements for power supply change dynamically, traditional methods are relatively complex and require huge computational overhead, while deep reinforcement learning performs well in complex problems. The purpose of our work is that with the assistance of the radio map, a UAV can find the best hover position, maximize the energy supplied by the UAV, maximize the data throughput collected, and minimize the energy consumption. The simulation results show that the proposed algorithm can well find the best hovering position of the UAVs and significantly improve the performance of the UAV-assisted wireless energy transmission communication network.
Experimental Study and Numerical Simulation of Gas Dryer Structure Improvement
Authors: Yang Tianqi , Wang Yukui , Xu Changkai , Zhu Yi , Min Chunhua
Published: October 2023

The dryer is an important part of the paper drying process, and the uniformity of the dryer wall temperature distribution has an important influence on paper production quality and efficiency. In this paper, improving the temperature uniformity of the traditional gas dryer wall is taken as the research goal, and the distribution trend and uniformity of the traditional gas dryer wall temperature are studied and analyzed, and the structural improvement plan is put forward. On the basis of this, in order to further improve the uniformity of the wall temperature of the improved gas dryer, the optimization scheme of applying endothermic coating in the low-temperature area of the inner wall of the dryer is proposed. The numerical simulation and experimental research methods are used to compare and analyze the temperature uniformity of the wall of the improved gas dryer. The results show that the axial uniformity of the wall temperature of the modified gas dryer is significantly improved. Compared with the traditional gas dryer, the temperature difference of the cylinder wall is reduced from 40 °C to 13 °C, the maximum axial temperature difference of the cylinder wall is reduced by 57%, and the temperature uniformity is increased from 66.7% to 89.6%. Compared with the improved gas dryer, after the endothermic coating is applied to the low-temperature area of the inner wall of the dryer, the temperature difference of the cylinder wall is reduced from 13 °C to 7 °C, the maximum axial temperature difference of the cylinder wall is further reduced by 46%, and the temperature uniformity is increased from 89.6% to 94.4%.
Advances in Tea Chemistry
Authors: Cao Qing-Qing , Gao Ying , Xu Yong-Quan
Published: October 2023

The origins of tea, a traditional beverage in China, can be traced back to the Shennong period, about 2737 years before the birth of Christ [...]
Determination and Analysis of Composition, Structure, and Properties of Teff Protein Fractions
Authors: Quan Zhenyang , Zhang Lili , Chang Wenping , Ding Xiangli , Qian Jianya , Tang Jianhua
Published: October 2023

To develop teff-based food products with acceptable quality, the composition, structure, and properties of teff protein fractions should be better understood. In this study, teff proteins were extracted, and their protein composition, structure, and properties were calculated, analyzed, and compared with those of wheat gliadin and glutenin. Results showed that teff flour contained 9.07% protein, with prolamin as its main protein fraction. The isoelectric points of albumin, globulin, prolamin, and glutelin were at pH 3.6, 3.0, 4.4, and 3.4, respectively. Teff prolamin and glutelin showed a significant difference in amino acids and free energy of hydration compared to wheat gliadins and glutenins. The protein chain length of teff prolamins was smaller than that of wheat gliadins, and teff glutelins lacked high molecular weight glutelin subunits. Teff prolamin had the highest α-helices content (27.08%), whereas no random coils were determined, which is different from wheat gliadin. Teff glutelin had a lower content of β-turn than wheat glutenin, and no α-helices were determined in it. Teff prolamin and glutelin had lower disulfide bond content and surface hydrophobicity. Teff prolamin had significantly higher thermal stability than wheat gliadin, whereas the thermal stability of teff glutelin was significantly lower than that of wheat glutenin.
Total Triterpenes, Polyphenols, Flavonoids, and Antioxidant Activity of Bioactive Phytochemicals of Centella asiatica by Different Extraction Techniques
Authors: Sabaragamuwa Rasangani , Perera Conrad O.
Published: October 2023

Obtaining phytochemical-rich plant extracts from natural products where the active ingredients are present in comparatively low levels in the tissue matrix is the critical initial step of any chemical analysis or bioactivity testing. The plant C. asiatica is rich in various phytochemicals, the major constituents being triterpenes and flavonoids, as well as other polyphenols, leading to a number of bioactivities. In this study, an attempt was made to achieve several green technology principles, while optimizing the extraction method for the efficient extraction of bioactive compounds from C. asiatica. Soxhlet extraction (SE), ultrasound-assisted extraction (UAE) with low-frequency sonication, microwave-assisted extraction (MAE) using a closed-vessel microwave digestion system, and subcritical water extraction (SWE) in a high-pressure reactor were employed to extract the bioactive compounds. The solvent system, extraction time, and solid-to-solvent ratio were varied to optimize the extraction. UAE gave the best extraction yield, while MAE gave similar results, with a solid-to-liquid ratio of 1:25, a binary solvent system of 9:1 methanol to water (v/v), and a 20 min extraction time for the extraction of triterpenes, including madecassoside, asiaticoside, madicassic acid, and asiatic acid. Investigation of different solvent systems based on water and methanol also revealed information on the extraction behavior of total triterpene content (TTC), total polyphenolic content (TPC), total flavonoid content (TFC), and the variations in the antioxidant capacity of the extracts. In this study, it was evident that UAE and MAE offer more efficient and effective extraction of bioactive compounds in terms of extraction yield, time, and minimal solvent and energy use. Furthermore, the results showed that the different solvent ratios in the extraction mixture will affect the extraction of bioactive compounds, and a binary solvent system with a combination of methanol and water was the most efficient for the studied compounds in Centella asiatica.
Reviewing the Palaeontological and Palaeoenvironmental Heritage of the Monti Pisani Massif (Italy): A Compelling History of Animals, Plants and Climates through Three Geological Eras
Authors: Collareta Alberto , Sorbini Chiara , Farina Simone , Granata Valerio , Marchetti Lorenzo , Frassi Chiara , Angeli Lucia , Bianucci Giovanni
Published: October 2023

The Monti Pisani massif (Tuscany, central Italy) is an isolated mountain relief known for its rich geodiversity, including a remarkable palaeontological heritage from the Palaeozoic, Mesozoic and Cenozoic eras. The Palaeozoic record consists of exquisitely preserved plant remains and rarer invertebrates of Permo-Carboniferous age, which testify to extensive rainforests and large swamps that thrived in an alluvial system under a humid, (sub)tropical climate. In addition to invertebrate shells, invertebrate trace fossils and microbial structures, the Mesozoic record features a diverse Middle Triassic tetrapod ichnoassemblage consisting of tracks of lepidosauromorphs, archosaurs (among which are the earliest dinosauromorph fossils of Italy) and nonmammalian therapsids. These vertebrates lived in a subsiding costal setting that stretched across an expanding rift valley under a subarid climate. The Cenozoic record features abundant fossils of terrestrial vertebrates (including spectacular members of the mammalian megafauna) from karst deposits, testifying to the manifold inhabitants of the massif during the glacial and interglacial phases of the Late Pleistocene. Overall, this long-lasting fossil record remarkably demonstrates how much the Earth’s environments have been changing through the Phanerozoic. The outstanding palaeontological heritage of the Monti Pisani area is in need of specific efforts of conservation and valorisation, especially with respect to the many palaeontological sites that punctuate the massif.
Falls and Sleep Disorders in Spanish Alzheimer’s Disease in Nursing Homes: An Observational Study
Authors: Cámara-Calmaestra Rubén , Martínez-Amat Antonio , Aibar-Almazán Agustín , Hita-Contreras Fidel , De Miguel-Hernando Nerea , Rodríguez-Almagro Daniel , Fábrega-Cuadros Raquel , Achalandabaso-Ochoa Alexander
Published: October 2023

Objective: The main objective of this study was to establish a relationship between the number of falls and sleep problems experienced by patients with Alzheimer’s disease. Materials and Methods: This was a cross-sectional study. A total of 114 Spanish aged people with Alzheimer’s disease institutionalized in nursing homes and 80 independent Spanish aged people without neurodegenerative diseases living at home were enrolled in this study and completed in-person interviews and digital questionnaires. Results: The mean age was 78.98 ± 8.59 years. Sleep disorders were related to continuous stress (p = 0.001; OR = 4.729) and a high frequency of falls (p = 0.001; OR = 2.145), while predictor variables associated with falls in patients with Alzheimer’s disease were continuous medical visits (β = 0.319, p < 0.001), family history of dementia (β = 0.212; p = 0.014), and sleep disorders (β = 0.235; p = 0.007). Second, the analysis showed that moderate physical activity (p = 0.001; OR = 0.147), continuous medical visits (p < 0.001; OR = 0.621), and high level of study (p = 0.011; OR = 0.334) were protective factors against Alzheimer’s, while older age (p = 0.035; OR = 1.087), type II Diabetes Mellitus (p = 0.042; OR = 3.973), number of falls (p = 0.021; OR = 1.409), and daily drug intake (p = 0.001; OR = 1.437) were risk factors for Alzheimer’s. Conclusions: Sleep disturbances are related to stress and falls in a sample of 114 Spanish AD aged people institutionalized in nursing homes, and the falls they experience are related to ongoing medical visits, a history of dementia, and sleep disturbances. Therefore, a bidirectional relationship was established between falls and sleep disorders in these patients. Moreover, this study showed that a greater frequency of falls and high daily drug intake could constitute novel risk factors for Alzheimer’s disease, in addition to already known factors, such as age and type II Diabetes Mellitus, while being physically active and a high level of studies are protective factors against Alzheimer’s disease.
Double Disparity of Sexual Minority Status and Rurality in Cardiometabolic Hospitalization Risk: A Secondary Analysis Using Linked Population-Based Data
Authors: Gupta Neeru , Cookson Samuel R.
Published: October 2023

Studies have shown separately that sexual minority populations generally experience poorer chronic health outcomes compared with those who identify as heterosexual, as do rural populations compared with urban dwellers. This Canadian national observational study explored healthcare patterns at the little-understood intersections of lesbian, gay, or bisexual (LGB) identity with residence in rural and remote communities, beyond chronic disease status. The secondary analysis applied logistic regressions on multiple linked datasets from representative health surveys, administrative hospital records, and a geocoded index of community remoteness to examine differences in the risk of potentially avoidable cardiometabolic-related hospitalization among adults of working age. Among those with an underlying cardiometabolic condition and residing in more rural and remote communities, a significantly higher hospitalization risk was found for LGB-identified persons compared with their heterosexual peers (odds ratio: 4.2; 95% confidence interval: 1.5–11.7), adjusting for sociodemographic characteristics, behavioral risk factors, and primary healthcare access. In models stratified by sex, the association remained significant among gay and bisexual men (5.6; CI: 1.3–24.4) but not among lesbian and bisexual women (3.5; CI: 0.9–13.6). More research is needed leveraging linkable datasets to better understand the complex and multiplicative influences of sexual minority status and rurality on cardiometabolic health to inform equity-enhancing preventive healthcare interventions.