bluuebunny/crossref_metadata_2025 huggingface dataset:
Automated System-Level Malware Detection Using Machine Learning: A Comprehensive Review
Authors: Gyamfi Nana Kwame , Goranin Nikolaj , Ceponis Dainius , Čenys Habil Antanas
Published: October 2023

Malware poses a significant threat to computer systems and networks. This necessitates the development of effective detection mechanisms. Detection mechanisms dependent on signatures for attack detection perform poorly due to high false negatives. This limitation is attributed to the inability to detect zero-day attacks, polymorphic malware, increasing signature base, and detection speed. To achieve rapid detection, automated system-level malware detection using machine learning approaches, leveraging the power of artificial intelligence to identify and mitigate malware attacks, has emerged as a promising solution. This comprehensive review aims to provides a detailed analysis of the status quo in malware detection by exploring the fundamentals of machine learning techniques for malware detection. The review is largely based on the PRISMA approach for article search methods and selection from four databases. Keywords were identified together with inclusion and exclusion criteria. The review seeks feature extraction and selection methods that enhance the accuracy and precision of detection algorithms. Evaluation metrics and common datasets were used to assess the performance of the system-level malware detection techniques. A comparative analysis of different machine learning approaches, emphasizing their strengths, weaknesses, and performance in detecting system-level malware is presented together with the limitations of the detection techniques. The paper concludes with future research opportunities, particularly in applying artificial intelligence, and provides a resource for researchers and cybersecurity professionals seeking to understand and advance automated system-level malware detection using machine learning.
Comparison of Forced Convective Heat-Transfer Enhancement of Conventional and Thin Plate-Fin Heat Sinks under Sinusoidal Vibration
Authors: Rasangika Ambagaha Hewage Dona Kalpani , Nasif Mohammad Shakir , Al-Waked Rafat
Published: October 2023

Applying sinusoidal vibration to heat sinks has proven to be a promising technique for improving heat transfer by disrupting the thermal boundary layer. However, applying sinusoidal vibration to the base of thin plate-fin heat sinks can cause a flapping motion within the fins, further enhancing heat transfer. Therefore, the current study numerically investigates and compares the effects of sinusoidal vibrations on the thermal performance of conventional and thin plate-fin heat sinks. The study concludes that increased vibrational amplitude and frequency (f ˃ 30 Hz) increases the vibration-assisted thermal performance. It was found that the thin plate-fin heat sink provides higher thermal performance compared to the conventional heat sink at every level of vibrational characteristics. The study found that the application of vibration enhances the Nusselt number up to a maximum of 20% and 15% in thin plate-fin and conventional heat sinks, respectively. Furthermore, the Reynolds number is reduced by 33.3% and 28% with thin plate-fin and conventional heat sinks compared with non-vibrating heat sinks, indicating a potential reduction of the size of the cooling system or fin size.
Comparative Study of Ultrasound Tissue Motion Tracking Techniques for Effective Breast Ultrasound Elastography
Authors: Caius Matthew , Samani Abbas
Published: October 2023

Breast cancer is the most common and deadly cancer in women, where early detection is of the utmost importance as survival rates decrease with the advancement of the disease. Most available methods of breast cancer screening and evaluation lack the ability to effectively differentiate between benign and malignant lesions without a biopsy. Ultrasound elastography (USE) is a cost-effective method that can potentially provide an initial malignancy assessment at the bedside. One of the challenges, however, is the uncertainty of tissue displacement data when performing USE due to out-of-plane movement of the tissue during mechanical stimulation, in addition to the computational efficiency necessary for real-time image reconstruction. This work presents a comparison of four different theoretically sound displacement estimators for their ability in tissue Young’s modulus reconstruction level with an emphasis on quality-to-runtime ratio to determine which estimators are most suitable for real-time USE systems. The methods are known in literature as AM2D, GLUE, OVERWIND, and SOUL methods. The effectiveness of each method was assessed as a stand-alone method or in combination with a strain field enhancement technique known as STREAL, which was recently developed using tissue mechanics-based regularization. The study was performed using radiofrequency US data pertaining to in silico and tissue mimicking phantoms in addition to clinical data. This data was used to generate tissue displacement fields employed to generate axial and lateral strain images before Young’s modulus images were reconstructed. The study indicates that the AM2D displacement estimator, which is an older and computationally less involved method, along with a tissue-mechanics-based image processing algorithm, performs very well, with high CNR, SNR, and preservation of tumor heterogeneity obtained at both strain and stiffness image levels, while its computation run-time is much lower compared to other estimation methods. As such, it can be recommended for incorporation in real-time USE systems.
MDCIM: MRAM-Based Digital Computing-in-Memory Macro for Floating-Point Computation with High Energy Efficiency and Low Area Overhead
Authors: Liu Liang , Tan Lehao , Gan Jie , Pan Biao , Zhou Jiahui , Li Zhengliang
Published: October 2023

Computing-in-Memory (CIM) is a novel computing architecture that enormously improves energy efficiency and reduces computing latency by avoiding frequent data movement between the computation and memory units. Currently, digital CIM is regarded as more suitable for high-precision operations represented in floating-point arithmetic, as it is not limited by the bit width of ADC/DAC in analog CIM. However, the development of DCIM still faces two problems: On the one hand, mainstream SRAM-based DCIM memory cells introduce large area overheads, which contain at least six transistors per cell. On the other hand, existing DCIM solutions can only support the computing precision up to FP32, failing to meet the demands of high-accuracy application scenarios. To overcome these problems, this work designs a novel SOT-MRAM-based digital CIM macro (MDCIM) with higher area/energy efficiency and achieves double-precision floating-point (FP64) computation with a modified fused multiply–accumulate (FMA) module. The proposed design is synthesized with a 55 nm CMOS technology node, achieving 0.62 mW power consumption, 26.9 GOPS/W, and 0.332 GOPS/mm2 energy efficiency at 150 MHz with 1.08 V supply. Circuit level simulation results show that the MDCIM can achieve higher area utilization compared to previous SRAM-based CIM designs.
Dual-Band Nested Circularly Polarized Antenna Array for 5G Automotive Satellite Communications
Authors: Tayyab Umais , Kumar Ashish , Petry Hans-Peter , Asghar Muhammad Ehtisham , Hein Matthias A.
Published: October 2023

Currently, 5G low-earth orbit satellite communications offer enhanced wireless coverage beyond the reach of 5G terrestrial networks, with important implications, particularly for automated and connected vehicles. Such wireless automotive mass-market applications demand well-designed compact user equipment antenna terminals offering non-terrestrial jointly with terrestrial communications. The antenna should be low-profile, conformal, and meet specific parameter values for gain and operational frequency bandwidth, tailored to the intended applications, in line with the aesthetic design requirements of passenger cars. This work presents an original concept for a dual-band nested circularly polarized automotive user terminal that operates at the S-band frequencies around 3.5 GHz and Ka-band frequencies around 28 GHz, namely within the 5G new-radio bands n78 and n257, respectively. The proposed terminal is designed to be integrated into the plastic components of a passenger vehicle. The arrays consist of 2 × 2 aperture-coupled corner-truncated microstrip slot patch antenna elements for the n78 band and of 4 × 4 single-layer edge-truncated microstrip circular slot patch antenna elements for the n257 band. The embedded arrays offer, across the two bands, respectively, 9.9 and 13.7 dBi measured realized gain and 3-dB axial ratio bandwidths of 100 and 1500 MHz for the n78 and n257 bands along the broadside direction. Detailed link budget calculations anticipate uplink data rates of 21 and 6 Mbit/s, respectively, deeming it suitable for various automotive mobility and Internet-of-Things applications.
Date Industry by-Product: Date Seeds (Phoenix dactylifera L.) as Potential Natural Sources of Bioactive and Antioxidant Compounds
Authors: Zarie Arwa Ali , Hassan Amro B. , Alshammari Ghedeir M. , Yahya Mohammed Abdo , Osman Magdi A.
Published: October 2023

The chemical composition, carotenoids, anthocyanins, total phenolic content, total flavonoid content, and antioxidant activity of three date seed cultivars, mainly Barhi, Ruthana, and Qatarah, were investigated. Date seed bioactive compounds were extracted by using different extraction solvents. The chemical analysis revealed that the Barhi cultivar has the highest moisture and fat content, while Ruthana has the highest carbohydrate content. There were no significant differences in protein and ash contents among the three date seeds. Ethanol (100%) showed the highest bioactive compound contents and antioxidant activity, whereas water showed the lowest content among the six solvents. Generally, all the date seed cultivars contain high amounts of phenolic, flavonoid, and antioxidant activity. The carotenoid content was highest in the Barhi (1.98 mg/g DW) followed by Qatarah (1.25 mg/g DW) and Ruthana (0.89 mg/g DW) seed, while the anthocyanin content was highest in the Ruthana cultivar (5.51 ± 0.71 cyanidin 3-glucoside/g DM.) and lowest in Barhi date seed (3.335 ± 0.23 cyanidin 3-glucoside/g DM.). Among the three date seeds, the Ruthana seed showed the highest phenolic (93.36 ± 0.30 mg GAE/g) and flavonoid compounds (59.9 ± 0.44 mg CE/g), DPPH activity (78.6 ± 0.92%), and total reducing power (60.3 ± 0.09%). The optimum solvent for the extraction of the antioxidants and their activity in each date seed was validated by using partial least squares regression (PLS). The results revealed a variation in the valid and optimum extracts for each seed; 100% ethanol extract for Barhi seed and mixture of methanol:ethanol:water (M 40:E40:W20) extract for Ruthana and Qatarah cultivars were the best solvent systems. The high natural antioxidant content of date seeds indicates that they can be considered functional ingredients for food and medicinal uses.
A Study on H∞-Fuzzy Controller for a Non-Linear Wind Turbine with Uncertainty
Authors: Jeon Taesu , Song Yuan , Paek Insu
Published: October 2023

In this study, an H∞-fuzzy controller is proposed for application in wind turbines with uncertainties and nonlinearities. The performance of the proposed controller was validated via dynamic simulations using a commercial aero-elastic code and wind tunnel experiments employing a scaled wind turbine. The simulation and the experimental results were then compared with those of the conventional PI and LQR control algorithms presented in our previous study. In the simulation, the perturbation and the sensor noise were applied to reflect uncertainty and nonlinearity effects. In addition, in the wind tunnel experiment, a control system using a commercial Bachmann PLC was established with an accelerometer to estimate the fatigue load exerted by the rotor thrust. It was confirmed through experiments that the robustness and adaptation of the control system improved in the situation of pitch system failure. As a result of the experiment, the proposed H∞ controller was able to reduce the rotor speed fluctuation by 39.9%, the power fluctuation by 32.0%, and the fatigue load by 2.4% compared with the LQR fuzzy controller, which had better performance than the conventional PI controller. In addition, it was confirmed through experiments that the robustness and adaptation of the control system were well maintained. This was even true in the situation of one-blade pitch system failure.
Application of Artificial Neural Networks for Identification of Lithofacies by Processing of Core Drilling Data
Authors: Yang Mingsheng , Hu Yuanbiao , Liu Baolin , Wang Lu , Zhou Zheng , Jia Mingrang
Published: October 2023

Identifying lithofacies types from core drilling data presents significant challenges, especially given the limited number of physical drilling characteristics available for analysis. Traditional machine learning methods often face issues with poor training and testing due to these limitations. Addressing this, we propose a new method for processing core drilling data to improve the accuracy of deep artificial neural networks (DANNs) in lithofacies recognition. Our approach transforms torque, weight on bit (WOB), and rotational speed data into three square matrices, creating a novel three-channel lithofacies image. This method allows for the application of DANNs by converting the complex lithofacies recognition task into a more standard image recognition problem. The developed method dramatically increases the input vector dimensions, enhancing the richness of the data input. The validation of results revealed that the DANN model trained for merely 3000 iterations successfully predicted lithofacies types of all eight testing samples in a mere 2.85 ms, showcasing superior accuracy. The innovative drilling data processing method proposed in this study enables DANNs to identify lithofacies with increased speed and accuracy. This offers a new direction for other DANNs utilizing drilling data.
Kinematic and Neuromuscular Ranges of External Loading in Professional Basketball Players during Competition
Authors: Ibáñez Sergio José , López-Sierra Pablo , Lorenzo Alberto , Feu Sebastián
Published: October 2023

Personalization of workloads is essential for optimizing training processes and minimizing the risk of injuries in sports. Precise knowledge of the external load demands borne by basketball players during competition is necessary for this purpose. The objective of this research was to determine the objective external load demands of five variables during a basketball competition, three kinematic (speed, accelerations, and decelerations) and two neuromuscular variables (impacts/min and Player Load/min), and subsequently establish workload ranges. Six official matches from preparatory tournaments involving professional basketball players from the Spanish first division, Liga ACB, were analyzed. Inertial devices and an UWB system were used for variable localization and recording within indoor spaces. Two methods, two-step and k-means clustering, were employed for workload range classification. The results revealed different workload thresholds clusters based on the data analysis technique used. The following speed ranges were identified in professional basketball players: Standing, <2.95 km/h; Walking, 2.96 to 7.58 km/h; Jogging, 7.59 to 12.71 km/h; Running, 12.72 to 17.50 km/h; and Sprinting, >17.51 km/h. The center of cluster 5 was found to determine the concept of a sprint (>19 km/h) as well as high-speed running (>17.50 km/h). Acceleration and deceleration ranges displayed few cases but with considerably high values, which must be considered when designing injury prevention tasks. The distribution of impacts showed a normal pattern, with identified periods during which players withstood significant G-forces (14%). Finally, the Player Load value at which an activity is considered to be very high, 1.95 au/min, was identified. Considering the obtained results, basketball is proposed as a sport with a high neuromuscular load. Coaches should choose the classification method that best suits their needs. These reference values are the first of their kind for this population of top-level professional players and should aid in adjusting training processes to match competition demands.
CL-TAD: A Contrastive-Learning-Based Method for Time Series Anomaly Detection
Authors: Ngu Huynh Cong Viet , Lee Keon Myung
Published: October 2023

Anomaly detection has gained increasing attention in recent years, but detecting anomalies in time series data remains challenging due to temporal dynamics, label scarcity, and data diversity in real-world applications. To address these challenges, we introduce a novel method for anomaly detection in time series data, called CL-TAD (Contrastive-Learning-based method for Times series Anomaly Detection), which employs a contrastive-learning-based representation learning technique. Inspired by the successes of reconstruction-based approaches and contrastive learning approaches, the proposed method seeks to leverage these approaches for time series anomaly detection. The CL-TAD method is comprised of two main components: positive sample generation and contrastive-learning-based representation learning. The former component generates positive samples by trying to reconstruct the original data from masked samples. These positive samples, in conjunction with the original data, serve as input for the contrastive-learning-based representation learning component. The representations of input original data and their masked data are used to detect anomalies later on. Experimental results have demonstrated that the CL-TAD method achieved the best performance on five datasets out of nine benchmark datasets over 10 other recent methods. By leveraging the reconstruction learning and contrastive learning techniques, our method offers a promising solution for effectively detecting anomalies in time series data by handling the issues raised by label scarcity and data diversity, delivering high performance.
Amazonian Indigenous Artists as Agents of Interface: Artworks, Networks, and Curation Strategies in the COVID-19 Crisis
Authors: Borea Giuliana
Published: October 2023

In this article, I analyse how the COVID-19 crisis crystalised and fuelled the vigorous role of Amazonian indigenous artists as, what I call, “agents of interface”, enabling connectivity, translation, networking and bridging information, ontologies, claims, and aesthetics. With the pandemic’s spatial restrictions and the reduction of global activity in the arts with a return to focusing on the local, I argue that it is important to look at interfaces as arenas from which to understand further reconfigurations, actions, and values in the arts. Based on the project and exhibition Ite!/Neno!/Here!: Responses to COVID-19 co-curated by the indigenous artist Rember Yahuarcani and me, and on other various initiatives, this paper explores how Amazonian indigenous artists became crucial agents of the interface in four main arenas providing first-hand, real-time information of the impact of COVID-19 at Amazonian urban and rural settings, channelling networks of aid and curation, connecting different agents and worlds, and engaging in curatorial collaborations. I argue that by acting at the interface, artists have reinforced their voices, while pushing for redefinitions of and positions in the art system and suggest that the COVID-19 crisis has introduced a new moment in the configuration of Peru’s art scene.
Soil-Derived Dust PM10 and PM2.5 Fractions in Southern Xinjiang, China, Using an Artificial Neural Network Model
Authors: Gao Shuang , Liu Yaxin , Zhang Jieqiong , Yu Jie , Chen Li , Sun Yanling , Mao Jian , Zhang Hui , Ma Zhenxing , Yang Wen , Hong Ningning , Azzi Merched , Zhao Hong , Wang Hui , Bai Zhipeng
Published: October 2023

Soil-derived dust emissions have been widely associated with health and environmental problems and should therefore be accurately and reliably estimated and assessed. Of these emissions, the inhalable PM10 and PM2.5 are difficult to estimate. Consequently, to calculate PM10 and PM2.5 emissions from soil erosion, an approach based on an artificial neural network (ANN) model which provides a multilayered, fully connected framework that relates input parameters and outcomes was proposed in this study. Owing to the difficulty in obtaining the actual emissions of soil-derived PM10 and PM2.5 over a broad area, the PM10 and PM2.5 simulated results of the ANN model were compared with the published results simulated by the widely used wind erosion prediction system (WEPS) model. The PM10 and PM2.5 emission results, based on the WEPS, agreed well with the field data, with R2 values of 0.93 and 0.97, respectively, indicating the potential for using the WEPS results as a reference for training the ANN model. The calculated r, RMSE and MAE for the results simulated by the WEPS and ANN were 0.78, 3.37 and 2.31 for PM10 and 0.79, 1.40 and 0.91 for PM2.5, respectively, throughout Southern Xinjiang. The uncertainty of the soil-derived PM10 and PM2.5 emissions at a 95% CI was (−66–106%) and (−75–108%), respectively, in 2016. The results indicated that by using parameters that affect soil erodibility, including the soil pH, soil cation exchange capacity, soil organic content, soil calcium carbonate, wind speed, precipitation and elevation as input factors, the ANN model could simulate soil-derived particle emissions in Southern Xinjiang. The results showed that when the study domain was reduced from the entire Southern Xinjiang region to its five administrative divisions, the performance of the ANN improved, producing average correlation coefficients of 0.88 and 0.87, respectively, for PM10 and PM2.5. The performances of the ANN differed by study period, with the best result obtained during the sand period (March to May) followed by the nonheating (June to October) and heating periods (November to February). Wind speed, precipitation and soil calcium carbonate were the predominant input factors affecting particle emissions from wind erosion sources. The results of this study can be used as a reference for the wind erosion prevention and soil conservation plans in Southern Xinjiang.
Gold-Nanorod-Assisted Live Cell Nuclear Imaging Based on Near-Infrared II Dark-Field Microscopy
Authors: Shi Yifeng , Peng Shiyi , Huang Zhongyu , Feng Zhe , Liu Wen , Qian Jun , Zhou Weidong
Published: October 2023

Dark-field microscopy offers several advantages, including high image contrast, minimal cell damage, and the absence of photobleaching of nanoprobes, which make it highly advantageous for cell imaging. The NIR-II window has emerged as a prominent research focus in optical imaging in recent years, with its low autofluorescence background in biological samples and high imaging SBR. In this study, we initially compared dark-field imaging results of colorectal cancer cells in both visible and NIR-II wavelengths, confirming the superior performance of NIR-II imaging. Subsequently, we synthesized gold nanorods with localized surface plasmon resonance (LSPR) absorption peaks in the NIR-II window. After bio-compatible modification, we non-specifically labeled colorectal cancer cells for NIR-II dark-field scattering imaging. The imaging results revealed a sixfold increase in SBR, especially in the 1425–1475 nm wavelength range. Finally, we applied this imaging system to perform dark-field imaging of cell nuclei in the NIR-II region and used GNRs for specific nuclear labeling in colorectal cancer cells. The resulting images exhibited higher SBR than non-specifically-labeled cell imaging, and the probe’s labeling was precise, confirming the potential application of this system in photothermal therapy and drug delivery for cancer cells.
Decoding the Behavior of a Queenless Colony Using Sound Signals
Authors: Kanelis Dimitrios , Liolios Vasilios , Papadopoulou Fotini , Rodopoulou Maria-Anna , Kampelopoulos Dimitrios , Siozios Kostas , Tananaki Chrysoula
Published: October 2023

Honeybees are reported to be the most vital pollinators of agricultural and horticultural crops. However, their widespread decline has raised great attention to the need to monitor their activity in order to identify the causes and implement countermeasures. The recording and analysis of signals used by honeybees for their communication in their hive can be a very helpful tool to the beekeepers for the remote control of the hives. Thus, in the present study, we used a set of sound recording data taken inside the hives to automatically detect the sounds of the bees over a certain period, to distinguish between queenright and queenless states, and to find the gradual changes in the queenless state. Unlike what was commonly believed, noticeable changes in the sound signals of all experimental colonies were observed just one hour after the queens’ removal from the hive, while the sound signals were intensified over a period of 5 h, after which the transmitted signal stabilized to the equivalent of a queenless state. The colonies seemed to return to their normal sounds 9–10 days after the reintroduction of the queens in the hives. Our study concluded that timely intervention of the queen’s absence combined with the immediate intervention of the beekeeper may be a determining factor in mitigating the adverse effects that occur from the queen’s loss.
Anthocyanins: Molecular Aspects on Their Neuroprotective Activity
Authors: Zaa César A. , Marcelo Álvaro J. , An Zhiqiang , Medina-Franco José L. , Velasco-Velázquez Marco A.
Published: October 2023

Anthocyanins are a type of flavonoids that give plants and fruits their vibrant colors. They are known for their potent antioxidant properties and have been linked to various health benefits. Upon consumption, anthocyanins are quickly absorbed and can penetrate the blood–brain barrier (BBB). Research based on population studies suggests that including anthocyanin-rich sources in the diet lower the risk of neurodegenerative diseases. Anthocyanins exhibit neuroprotective effects that could potentially alleviate symptoms associated with such diseases. In this review, we compiled and discussed a large body of evidence supporting the neuroprotective role of anthocyanins. Our examination encompasses human studies, animal models, and cell cultures. We delve into the connection between anthocyanin bioactivities and the mechanisms underlying neurodegeneration. Our findings highlight how anthocyanins’ antioxidant, anti-inflammatory, and anti-apoptotic properties contribute to their neuroprotective effects. These effects are particularly relevant to key signaling pathways implicated in the development of Alzheimer’s and Parkinson’s diseases. In conclusion, the outcome of this review suggests that integrating anthocyanin-rich foods into human diets could potentially serve as a therapeutic approach for neurological conditions, and we identify promising avenues for further exploration in this area.
Anti-Aging Activity and Modes of Action of Compounds from Natural Food Sources
Authors: Song Lili , Zhang Shicui
Published: October 2023

Aging is a natural and inescapable phenomenon characterized by a progressive deterioration of physiological functions, leading to increased vulnerability to chronic diseases and death. With economic and medical development, the elderly population is gradually increasing, which poses a great burden to society, the economy and the medical field. Thus, healthy aging has now become a common aspiration among people over the world. Accumulating evidence indicates that substances that can mediate the deteriorated physiological processes are highly likely to have the potential to prolong lifespan and improve aging-associated diseases. Foods from natural sources are full of bioactive compounds, such as polysaccharides, polyphenols, carotenoids, sterols, terpenoids and vitamins. These bioactive compounds and their derivatives have been shown to be able to delay aging and/or improve aging-associated diseases, thereby prolonging lifespan, via regulation of various physiological processes. Here, we summarize the current understanding of the anti-aging activities of the compounds, polysaccharides, polyphenols, carotenoids, sterols, terpenoids and vitamins from natural food sources, and their modes of action in delaying aging and improving aging-associated diseases. This will certainly provide a reference for further research on the anti-aging effects of bioactive compounds from natural food sources.
Biomarkers Associated with Drugs for the Treatment of Lupus Nephritis
Authors: Nie Huiyu , Chang Siyuan , Li Yuanyuan , Li Fen
Published: October 2023

The constant updating of lupus drug treatment guidelines has led to a question. How can the efficacy of treatment be more effectively monitored? Systemic lupus erythematosus (SLE) is a complex autoimmune disease that often presents clinically with multi-organ involvement, and approximately 30% of patients with SLE develop lupus nephritis (LN). Therefore, it is important to better track disease progression and drug efficacy. Now, kidney biopsy is still the gold standard for diagnosing and guiding the treatment of LN, but it is invasive and expensive. If simple, non-invasive and effective biomarkers can be found, drug intervention and prognosis can be better monitored and targeted. In this review, we focus on LN and explore biomarkers related to LN therapeutics, providing clinicians with more possibilities to track the therapeutic effect of drugs, improve treatment options and assess patient outcomes.
Whole-Body Cryotherapy Improves Asprosin Secretion and Insulin Sensitivity in Postmenopausal Women–Perspectives in the Management of Type 2 Diabetes
Authors: Wiecek Magdalena , Szymura Jadwiga , Kusmierczyk Justyna , Lipowska Maria , Szygula Zbigniew
Published: October 2023

Type 2 diabetes (T2DM) is a global problem. The effect of whole-body cryotherapy (WBC) on metabolism in humans is postulated. The aim of this study was to determine the effect of WBC on asprosin concentrations, glucose homeostasis and insulin resistance in postmenopausal women with T2DM. Changes in fasting blood glucose (FBG), glycated haemoglobin (HbA1c), insulin, asprosin, insulin-resistance indices (HOMA-IR, Quicki), the triglyceride–glucose index (TyG) and C-reactive protein (CRP) were determined. Determination was carried out after 30 WBCs (3 min, −120 °C), applied in six series of five treatments, with 2-day breaks in postmenopausal women with T2DM and the results were compared to changes in postmenopausal women without T2DM (CON). Blood was collected before 1 WBC (T0), after 30 WBCs (T1) and 2 weeks after their completion (T2). In the T2DM group, there was a significant decrease in FBG and HbA1c in T1 and T2, as well as a significant decrease in insulin, HOMA-IR and CRP, and an increase in the Quicki index in T2. In the CON group, the concentration of asprosin at T2 was significantly lower than at T0. There was a significantly positive correlation between asprosin and FBG and HOMA-IR, and a trend towards a decrease of asprosin concentration in T2 in postmenopausal women with T2DM.
Bio-Inspired Sutures: Simulating the Role of Suture Placement in the Mechanical Response of Interlocking Structures
Authors: Gibbons Melissa M. , Chen Diana A.
Published: October 2023

The hardest anatomical components of many animals are connected at thin seams known as sutures, which allow for growth and compliance required for respiration and movement and serve as a defense mechanism by absorbing energy during impacts. We take a bio-inspired approach and parameterize suture geometries to utilize geometric connections, rather than new engineering materials, to absorb high-impact loads. This study builds upon our work that investigated the effects of the dovetail suture contact angle, tangent length, and tab radius on the stiffness and toughness of an archway structure using finite element analysis. We explore how increasing the archway segmentation affects the mechanical response of the overall structure and investigate the effects of displacement when induced between sutures. First, when keeping displacement along a suture but increasing the number of archway pieces from two to four, we observed that stiffness and toughness were reduced substantially, although the overall trends stayed the same. Second, when the displacement was induced along an archway edge rather than upon a suture (in a three-piece archway), we observed that archway stiffness and toughness were much less sensitive to the changes in the suture parameters, but unlike the archway indented along the suture line, they tended to lose stiffness and toughness as the tangent length increased. This study is a step forward in the development of bio-inspired impact-resistant helmets.
Physical Virology in Spain
Authors: Reguera David , de Pablo Pedro J. , Abrescia Nicola G. A. , Mateu Mauricio G. , Hernández-Rojas Javier , Castón José R. , San Martín Carmen
Published: October 2023

Virus particles consist of a protein coat that protects their genetic material and delivers it to the host cell for self-replication. Understanding the interplay between virus structure and function is a requirement for understanding critical processes in the infectious cycle such as entry, uncoating, genome metabolism, capsid assembly, maturation, and propagation. Together with well-established techniques in cell and molecular biology, physical virology has emerged as a rapidly developing field, providing detailed, novel information on the basic principles of virus assembly, disassembly, and dynamics. The Spanish research community contains a good number of groups that apply their knowledge on biology, physics, or chemistry to the study of viruses. Some of these groups got together in 2010 under the umbrella of the Spanish Interdisciplinary Network on Virus Biophysics (BioFiViNet). Thirteen years later, the network remains a fertile ground for interdisciplinary collaborations geared to reveal new aspects on the physical properties of virus particles, their role in regulating the infectious cycle, and their exploitation for the development of virus-based nanotechnology tools. Here, we highlight some achievements of Spanish groups in the field of physical virology.
Explainable Machine Learning with Pairwise Interactions for Predicting Conversion from Mild Cognitive Impairment to Alzheimer’s Disease Utilizing Multi-Modalities Data
Authors: Cai Jiaxin , Hu Weiwei , Ma Jiaojiao , Si Aima , Chen Shiyu , Gong Lingmin , Zhang Yong , Yan Hong , Chen Fangyao ,   for the Alzheimer’s Disease Neuroimaging Initiative
Published: October 2023

Background: Predicting cognition decline in patients with mild cognitive impairment (MCI) is crucial for identifying high-risk individuals and implementing effective management. To improve predicting MCI-to-AD conversion, it is necessary to consider various factors using explainable machine learning (XAI) models which provide interpretability while maintaining predictive accuracy. This study used the Explainable Boosting Machine (EBM) model with multimodal features to predict the conversion of MCI to AD during different follow-up periods while providing interpretability. Methods: This retrospective case-control study is conducted with data obtained from the ADNI database, with records of 1042 MCI patients from 2006 to 2022 included. The exposures included in this study were MRI biomarkers, cognitive scores, demographics, and clinical features. The main outcome was AD conversion from aMCI during follow-up. The EBM model was utilized to predict aMCI converting to AD based on three feature combinations, obtaining interpretability while ensuring accuracy. Meanwhile, the interaction effect was considered in the model. The three feature combinations were compared in different follow-up periods with accuracy, sensitivity, specificity, and AUC-ROC. The global and local explanations are displayed by importance ranking and feature interpretability plots. Results: The five-years prediction accuracy reached 85% (AUC = 0.92) using both cognitive scores and MRI markers. Apart from accuracies, we obtained features’ importance in different follow-up periods. In early stage of AD, the MRI markers play a major role, while for middle-term, the cognitive scores are more important. Feature risk scoring plots demonstrated insightful nonlinear interactive associations between selected factors and outcome. In one-year prediction, lower right inferior temporal volume (<9000) is significantly associated with AD conversion. For two-year prediction, low left inferior temporal thickness (<2) is most critical. For three-year prediction, higher FAQ scores (>4) is the most important. During four-year prediction, APOE4 is the most critical. For five-year prediction, lower right entorhinal volume (<1000) is the most critical feature. Conclusions: The established glass-box model EBMs with multimodal features demonstrated a superior ability with detailed interpretability in predicting AD conversion from MCI. Multi features with significant importance were identified. Further study may be of significance to determine whether the established prediction tool would improve clinical management for AD patients.
Persisting Verbal Memory Encoding and Recall Deficiency after mGluR5 Autoantibody-Mediated Encephalitis
Authors: Hansen Niels , Rentzsch Kristin , Hirschel Sina , Wiltfang Jens , Schott Björn , Malchow Berend , Bartels Claudia
Published: October 2023

Background: Metabotropic glutamate receptors type 5 (mGluR5) play a central role in persistent forms of synaptic plasticity and memory formation. Antibodies to mGluR5 have been reported to be clinically associated with memory impairment. Here, we report on a patient with persistent amnestic cognitive impairment in a single cognitive domain after resolution of mGluR5-associated encephalitis. Methods: We report on the clinical data of a patient in our Department of Psychiatry and Psychotherapy who underwent several diagnostic investigations including a detailed neuropsychological examination, magnetic resonance imaging, and cerebrospinal fluid analysis involving the determination of neural autoantibodies. Results: A 54-year-old woman presented to our memory clinic with pleocytosis 4 months after remission of probable anti-mGluR5-mediated encephalitis, revealing initial pleocytosis and serum proof of anti-mGluR5 autoantibodies (1:32). A neuropsychological examination revealed mild cognitive impairment in verbal memory encoding and recall. The patient received immunotherapy with corticosteroids, and a subsequent cerebrospinal fluid analysis 1.5 months after the onset of encephalitis confirmed no further signs of inflammation. Conclusions: Our results suggest that although immunotherapy resulted in the remission of anti-mGluR5 encephalitis, a verbal memory encoding and recall dysfunction persisted. It remains unclear whether the reason for the persistent verbal memory impairment is attributable to insufficiently long immunotherapy or initially ineffective immunotherapy. Because mGluR5 plays an essential role in persistent synaptic plasticity in the hippocampus, it is tempting to speculate that the mGluR5 antibody–antigen complex could lead to persistent cognitive dysfunction, still present after the acute CNS inflammation stage of encephalitis.
Neuropsychological Assessment of the Relationship of Working Memory with K-BIT Matrices and Vocabulary in Normal Development and ADHD Children and Adolescents
Authors: Rodriguez-Martínez Elena I. , Muñoz-Pradas Raquel , Arjona Antonio , Angulo-Ruiz Brenda Y. , Muñoz Vanesa , Gómez Carlos M.
Published: October 2023

Background: The present report tries to understand the possible relationship between working memory (WM) and intelligence measurements, using the direct scores of the Working Memory Test Battery for Children (WMTBC) and Kaufman’s Brief Intelligence Test (K-BIT), in normal development (ND) and diagnosed attention deficit hyperactivity disorder (ADHD) children and adolescents. Results: Partial correlations, discounting the effect of age, showed a significant correlation in ND subjects between the central executive (CE) component of WM and the WM visuospatial sketchpad (VSS) component and the WM phonological loop (PL); also, significant correlations were obtained for the WM VSS with the K-BIT Matrices scores, the WM PL with the K-BIT Vocabulary, and the K-BIT Matrices scores with the K-BIT Vocabulary. For ADHD subjects, there were significant correlations between WM VSS and WM CE, and WM VSS and K-BIT Matrices. We tested the robustness of these correlations by selecting a small number of subjects through permutations; a robust correlation between WM CE and WM PL in ND, and between WM VSS and WM CE and WM VSS and K-BIT Matrices scores was obtained. These results were also supported by mediation analysis. Conclusions: There is a relationship during development between WM as measured with WMTBC and general intelligence as measured with K-BIT in ND and ADHD subjects. The dysexecutive character of ADHD has been shown, given that by controlling for intelligence, the differences in WM performance between ND and ADHD disappear, except for WM CE. The results suggest that in ADHD subjects, the WM VSS component presents a more pivotal role during cognitive processing compared to ND subjects.
Detecting Central Auditory Processing Disorders in Awake Mice
Authors: Dejean Camille , Dupont Typhaine , Verpy Elisabeth , Gonçalves Noémi , Coqueran Sabrina , Michalski Nicolas , Pucheu Sylvie , Bourgeron Thomas , Gourévitch Boris
Published: October 2023

Mice are increasingly used as models of human-acquired neurological or neurodevelopmental conditions, such as autism, schizophrenia, and Alzheimer’s disease. All these conditions involve central auditory processing disorders, which have been little investigated despite their potential for providing interesting insights into the mechanisms behind such disorders. Alterations of the auditory steady-state response to 40 Hz click trains are associated with an imbalance between neuronal excitation and inhibition, a mechanism thought to be common to many neurological disorders. Here, we demonstrate the value of presenting click trains at various rates to mice with chronically implanted pins above the inferior colliculus and the auditory cortex for obtaining easy, reliable, and long-lasting access to subcortical and cortical complex auditory processing in awake mice. Using this protocol on a mutant mouse model of autism with a defect of the Shank3 gene, we show that the neural response is impaired at high click rates (above 60 Hz) and that this impairment is visible subcortically—two results that cannot be obtained with classical protocols for cortical EEG recordings in response to stimulation at 40 Hz. These results demonstrate the value and necessity of a more complete investigation of central auditory processing disorders in mouse models of neurological or neurodevelopmental disorders.
Robot-Assisted Manufacturing Technology for 3D Non-Metallic Reinforcement Structures in the Construction Applications
Authors: Friese Danny , Hahn Lars , Le Xuan Hung , Mersch Johannes , Neef Tobias , Mechtcherine Viktor , Cherif Chokri
Published: October 2023

Of all industrial sectors, the construction industry accounts for about 37% of carbon dioxide (CO2) emissions. This encompasses the complete life cycle of buildings, from the construction phase to service life to component disposal. The main source of emissions of climate-damaging greenhouse gases such as CO2, with a share of 9% of global emissions, is the production of ordinary cement as the main binder of concrete. The use of innovative approaches such as impregnated carbon yarns as non-corrosive reinforcement embedded in concrete has the potential to dramatically reduce the amount of concrete required in construction, since no excessive concrete cover is needed to protect against corrosion, as is the case with steel reinforcement. At the same time, architectural design options are expanded via this approach. This is achieved above all using novel robotic manufacturing technologies to enable no-cut direct fiber placement. This innovative technological approach to fabricating 2D and 3D biologically inspired textiles, including non-metallic structures for textile-reinforced concrete (TRC) components, will promote an automatable construction method that reduces greenhouse gas emissions. Furthermore, the impregnated yarn which is fabricated enables the production of load-adapted and gradual non-metallic reinforcement components. Novel and improved design strategies with innovative reinforcement patterns allow the full mechanical potential of TRC to be realized. The development of a robotic fabrication technology has gone beyond the state of the art to implement spatially branched, biologically inspired 3D non-metallic reinforcement structures. A combined robotic fabrication technology, based on the developed flexible 3D yarn-guiding and impregnation module and a 3D yarn fixation module, is required to implement this sophisticated approach to fabricate freely formed 3D non-metallic reinforcement structures. This paper presents an overview of the development process of the innovative technological concept.
Experimental and Computational Research on the Shear Performance of Partially Filled Narrow-Width Steel Box-UHPC-Combined Girders under Negative Moment Action
Authors: Liu Shuai , Wang Bohan , Zheng Yan , Mo Shixu , Zhang Qiyu , Zhou Peixuan
Published: October 2023

To examine the vertical shear behavior of narrow-width steel box-UHPC (Ultra-High Performance Concrete) composite beams with partial filling under negative bending moments, a total of six test beams were created and constructed in this study. The variables considered during the design and fabrication process included the flange thickness of UHPC, the amount of steel fibers in UHPC, and the height of the concrete filling. Reverse static concentration loading was applied to the beams. Compared to the C40 concrete flange, the cracking load of the 1/2 plate thickness UHPC flange and pure UHPC flange increased by 55.6% and 66.7%, respectively. The yield load witnessed a rise of 17.3% and 22.7%, while the ultimate load experienced an increase of 7% and 13.1%. This suggests that incorporating steel fibers can regulate the formation of cracks, enhance the flexibility of the flanges, and improve the overall shear capacity of the composite beams. When steel fibers were used in the amount of 2% of the concrete volume, the cracking resistance of the flange plate was increased by 16.7%. Partially filled and fully filled composite beams exhibited a 7.7% and 30.8% augmentation in cracking load, a 35.3% and 49.9% increase in yield load, and a 41% and 83.2% elevation in ultimate load when contrasted with composite beams devoid of concrete infusion within the steel box. The above observation implies that the incorporation of concrete within the steel box significantly improves the yield strength and ultimate shear capacity of the composite beams. The shear strength of the narrow-width steel box-UHPC composite beams, which are partially filled, shows a significant relationship with the experimental results when applying the principle of component superposition.