bluuebunny/crossref_metadata_2025 huggingface dataset:
Wireless Traffic Prediction Based on a Gradient Similarity Federated Aggregation Algorithm
Authors: Li Luzhi , Zhao Yuhong , Wang Jingyu , Zhang Chuanting
Published: March 2023

Wireless traffic prediction is critical to the intelligent operation of cellular networks, such as load balancing, congestion control, value-added service promotion, etc. However, the BTS data in each region has certain differences and privacy, and centralized prediction needs to transmit a large amount of traffic data, which will not only cause bandwidth consumption, but may also cause privacy leakage. Federated learning is a kind of distributed learning method with multi-client joint training and no sharing between clients. Based on existing related research, this paper proposes a gradient similarity-based federated aggregation algorithm for wireless traffic prediction (Gradient Similarity-based Federated Aggregation for Wireless Traffic Prediction) (FedGSA). First of all, this method uses a global sharing enhanced data strategy to overcome the data heterogeneity challenge of multi-client collaborative training in federated learning. Secondly, the sliding window scheme is used to construct the dual channel training data to improve the feature learning ability of the model; In addition, to improve the generalization ability of the final global model, a two-layer aggregation scheme based on gradient similarity is proposed. The personalized model is generated by comparing the gradient similarity of each client model, and the central server aggregates the personalized model to finally generate the global model. Finally, the FedGSA algorithm is applied to wireless network traffic prediction. Experiments are conducted on two real traffic datasets. Compared with the mainstream Federated Averaging (FedAvg) algorithm, FedGSA performs better on both datasets and obtains better prediction results on the premise of ensuring the privacy of client traffic data.
Frequency-Limited Model Reduction for Linear Positive Systems: A Successive Optimization Method
Authors: Ren Yingying , Wang Qian
Published: March 2023

This paper studies frequency-limited model reduction for linear positive systems. Specifically, the objective is to develop a reduced-order model for a high-order positive system that preserves the positivity, while minimizing the approximation error within a given H∞ upper bound over a limited frequency interval. To characterize the finite-frequency H∞ specification and stability, we first present the analysis conditions in the form of bilinear matrix inequalities. By leveraging these conditions, we derive convex surrogate constraints by means of an inner-approximation strategy. Based on this, we construct a novel iterative algorithm for calculating and optimizing the reduced-order model. Finally, the effectiveness of the proposed model reduction method is illustrated with a numerical example.
Building XAI-Based Agents for IoT Systems
Authors: Dobrovolskis Algirdas , Kazanavičius Egidijus , Kižauskienė Laura
Published: March 2023

The technological maturity of AI solutions has been consistently increasing over the years, expanding its application scope and domains. Smart home systems have evolved to act as proactive assistants for their residents, autonomously detecting behavioral patterns, inferring needs, and making decisions pertaining to the management and control of various home subsystems. The implementation of explainable AI (XAI) solutions in this challenging domain can improve user experience and trust by providing clear and understandable explanations of the system’s behavior. The article discusses the increasing importance of explainable artificial intelligence (XAI) in smart home systems, which are becoming progressively smarter and more accessible to end-users, and presents an agent-based approach for developing explainable Internet of things (IoT) systems and an experiment conducted at the Centre of Real Time Computer Systems at the Kaunas University of Technology. The proposed method was adapted to build an explainable, rule-based smart home system for controlling light, heating, and ventilation. The results of this study serve as a demonstration of the feasibility and effectiveness of the proposed theoretical approach in real-world scenarios.
A Deep Learning Framework for Day Ahead Wind Power Short-Term Prediction
Authors: Xu Peihua , Zhang Maoyuan , Chen Zhenhong , Wang Biqiang , Cheng Chi , Liu Renfeng
Published: March 2023

Due to the increasing proportion of wind power connected to the grid, day-ahead wind power prediction plays a more and more important role in the operation of the power system. This paper proposes a day-ahead wind power short-term prediction model based on deep learning (DWT_AE_BiLSTM). Firstly, discrete wavelet transform (DWT) is used to denoise the data, then an autoencoder (AE) technology is used to extract the data features, and finally, bidirectional long short-term memory (BiLSTM) is used for prediction. To verify the effectiveness of the proposed DWT_AE_BiLSTM model, we studied three different power stations and compared their performance with the shallow neural network model. Experimental analysis shows that this model is more competitive in forecasting accuracy and stability. Compared with the BP model, the proposed model has increased by 3.86%, 3.22% and 3.42% in three wind farms, respectively.
Development of Infrared Reflective Textiles and Simulation of Their Effect in Cold-Protection Garments
Authors: Cherunova Irina , Kornev Nikolai , Jia Guobin , Richter Klaus , Plentz Jonathan
Published: March 2023

Two ways of to enhance the heat insulation of cold-protecting garments are studied using the mathematical model, which describes the coupled transport of temperature, humidity, and bound and condensed water. The model is developed in a one-dimensional formulation. The thermal radiation transport is explicitly considered by the subdivision of the heat flux into radiative and conduction parts. The model is utilized to study the improvement of heat-insulating properties of cold protective garments using aerogel materials and thin infrared reflective textile layers. Special attention is paid to the technological aspects of manufacturing such reflective textiles. The numerical investigations show that the use of infrared reflective textiles is the most effective of the two studied methods. Due to the reflection of the radiant heat flow coming from the human body, the skin temperature rises and the thermal insulation of clothing is significantly improved.
Integrated Analysis of Polycyclic Aromatic Hydrocarbons and Polychlorinated Biphenyls: A Comparison of the Effectiveness of Selected Methods on Dried Fruit Matrices
Authors: Ciemniak Artur , Witczak Agata , Pokorska-Niewiada Kamila
Published: March 2023

Polycyclic aromatic hydrocarbons (PAHs) and polychlorinated biphenyls (PCBs) are groups of chemical substances commonly found in the environment. Because of large differences in the concentrations of PAHs and PCBs in the materials tested, separate analytical methods specific to each group of compounds are usually used. The aim of this study was to compare methods for the determination of PAHs and PCBs that permit the simultaneous determination of these compounds from one solvent extract. The analysis of the content of 15 PCB congeners and 16 PAHs was conducted using dried fruits. The analyses were performed with gas chromatography coupled with mass spectrometry. PAHs and PCBs were determined separately in each fruit sample using specific extraction and cleanup procedures for the respective groups of compounds. Analyses were also performed with two methods that permitted the simultaneous analysis of PAHs and PCBs in one solvent extract. The integrated methods did not provide adequate extract cleanup of interfering substances; consequently, the results of determinations of PAHs and PCBs using these methods were significantly different from the values obtained with proven determination methods for PAHs and PCBs.
Global Mechanical Response Sensing of Corrugated Compensators Based on Digital Twins
Authors: Zhou Run , Jiang Jingyan , Qin Jianhua , Du Ning , Shi Haoran , Wang Ying
Published: March 2023

The corrugated compensators are important components in the piping system, absorbing mechanical deformation flexibly. To reduce the risk of the piping system with corrugated compensators and improve the safety and stability of industrial equipment, condition monitoring and fault diagnosis of bellows is necessary. However, the stress monitoring method of corrugated compensators with limited localized sensors lack real-time and full-domain sensing. Therefore, this paper proposes a digital twin construction method for global mechanical response sensing of corrugated compensators, combining Gaussian process regression in machine learning and finite element analysis. The sensing data of three types of displacements are used as the associated information of a finite element model with 19,800 elements and its digital twin. The results show that the values of performance metrics correlation of determination R2 and standardized average leave-one-out cross-validation CVavg of the digital twin satisfy the recommended threshold, which indicates that the digital twin has excellent predictive performance. The single prediction time of the digital twin is 0.76% of the time spent on finite element analysis, and the prediction result has good consistency with the true response under dynamic input, indicating that the digital twin can achieve fast and accurate stress field prediction. The important state information hidden in the multi-source data obtained by limited sensors is effectively mined to achieve the real-time prediction of the stress field. This paper provides a new approach for intelligent sensing and feedback of corrugated compensators in the piping system.
Boundary–Inner Disentanglement Enhanced Learning for Point Cloud Semantic Segmentation
Authors: He Lixia , She Jiangfeng , Zhao Qiang , Wen Xiang , Guan Yuzheng
Published: March 2023

In a point cloud semantic segmentation task, misclassification usually appears on the semantic boundary. A few studies have taken the boundary into consideration, but they relied on complex modules for explicit boundary prediction, which greatly increased model complexity. It is challenging to improve the segmentation accuracy of points on the boundary without dependence on additional modules. For every boundary point, this paper divides its neighboring points into different collections, and then measures its entanglement with each collection. A comparison of the measurement results before and after utilizing boundary information in the semantic segmentation network showed that the boundary could enhance the disentanglement between the boundary point and its neighboring points in inner areas, thereby greatly improving the overall accuracy. Therefore, to improve the semantic segmentation accuracy of boundary points, a Boundary–Inner Disentanglement Enhanced Learning (BIDEL) framework with no need for additional modules and learning parameters is proposed, which can maximize feature distinction between the boundary point and its neighboring points in inner areas through a newly defined boundary loss function. Experiments with two classic baselines across three challenging datasets demonstrate the benefits of BIDEL for the semantic boundary. As a general framework, BIDEL can be easily adopted in many existing semantic segmentation networks.
The Effect of Abrupt Changes to Sources of PM10 and PM2.5 Concentrations in Three Major Agglomerations in Mexico
Authors: Méndez-Astudillo Jorge , Caetano Ernesto
Published: March 2023

In the three major urban agglomerations in Mexico (Mexico City, Monterrey, and Guadalajara), a significant change to anthropogenic sources of air pollution happened in March–May 2020, when policies implemented to stop the spread of the COVID-19 virus in Mexico caused the reduction of some anthropogenic sources of air pollution. We study the effect of these significant changes to air pollution sources using satellite-retrieved aerosol optical depth (AOD) and particulate matter (PM10 and PM2.5) concentrations from ground stations. The Chow test was applied to study trend changes in PM concentrations from 1 January to 30 May 2020. The Mann–Whitney non-parametric test was then used to compare average PM concentrations in April and May pre-lockdown, during lockdown in 2020, and post-lockdown in 2021. The assessment was further performed by evaluating the exceedance of national air quality standard maxima. The trend analysis showed that PM10 concentrations were reduced during lockdown in Mexico City and Monterrey, whereas no change was found for PM10 in Guadalajara and PM2.5 in the three cities. Further analysis showed that in Mexico City and Guadalajara, average PM10 and PM2.5 concentrations decreased by 12% in April and May 2020. However, in Monterrey, average PM10 and PM2.5 concentrations increased by 2.76% and 11.07%, respectively, in April 2021 due to a severe drought that caused dry soils and dust around the city. The results of this research can be used to implement policies for reducing anthropogenic sources to improve the air quality in urban areas.
Improvement of Maximum Air Temperature Forecasts Using a Stacking Ensemble Technique
Authors: Zhao Linna , Lu Shu , Qi Dan
Published: March 2023

Due to the influence of complex factors such as atmospheric dynamic processes, physical processes and local topography and geomorphology, the prediction of near-surface meteorological elements in the numerical weather model often has deviation. The deep learning neural networks are more flexible but with high variance. Here, we proposed a stacking ensemble model named FLT, which consists of a fully connected neural network with embedded layers (ED-FCNN), a long short-term memory (LSTM) network and a temporal convolutional network (TCN) to overcome the high variance of a single neural network and to improve prediction of maximum air temperature. The case study of daily maximum temperature forecast evaluated with observation of almost 2400 weather stations shows substantial improvement over that of single neural network model, ECMWF-IFS and statistical post-processing model. The FLT model can more effectively improve the forecast bias of the ECMWF-IFS model than that of any of the above single neural network model, with the RMSE reduced by 52.36% and the accuracy of temperature forecast increased by 43.12% compared with the ECMWF-IFS model. The average RMSEs of the FLT model decreases by 8.39%, 1.50%, 2.96% and 16.03%, respectively, compared with ED-FCNN, LSTM, TCN and the decaying average method.
Existence and Stability of a Nonlinear Distributed Delayed Periodic AG-Ecosystem with Competition on Time Scales
Authors: Zhao Kaihong
Published: March 2023

The Ayala-Gilpin (AG) kinetics system is one of the famous mathematical models of ecosystem. This model has been widely concerned and studied since it was proposed. This paper stresses on a nonlinear distributed delayed periodic AG-ecosystem with competition on time scales. In the sense of time scale, our model unifies and generalizes the discrete and continuous cases. Firstly, with the aid of the auxiliary function having only two zeros in the real number field, we apply inequality technique and coincidence degree theory to obtain some sufficient criteria which ensure that this model has periodic solutions on time scales. Meanwhile, the global asymptotic stability of the periodic solution is founded by employing stability theory in the sense of Lyapunov. Eventually, we provide an illustrative example and conduct numerical simulation by means of MATLAB tools.
Pulsed Current Constructs 3DM Cu/ZnO Current Collector Composite Anode for Free-Dendritic Lithium Metal Batteries
Authors: Zhou Zhenkai , Chen Qiang , Wang Yang , Hou Guangya , Zhang Jianli , Tang Yiping
Published: March 2023

Although lithium metal is an ideal anode material for achieving high-energy-density lithium-based batteries, the uneven deposition/exfoliation process of lithium during cycling easily triggers the formation of lithium dendrites and dead lithium, which leads to a low Coulombic efficiency and safety issues. In this paper, a lithiophilic 3D copper mesh current collector is designed by using lithiophilic ZnO and pulsed current plating and is applied to a lithium metal battery composite anode. Under the action of the pulsed current field, the novel lithium metal composite anode battery achieved the homogeneous deposition of lithium ions. The lithium-to-copper half cells assembled with the 3DM Cu/ZnO current collector from the pulsed current deposition presented a Coulombic efficiency as high as 97.8% after 1 min of activation at 3 mA cm−2 follow by 10 cycles at a stripping current of 0.5 mA cm−2. Moreover, the symmetric cell could be stable for 1500 h at 1 mA cm−2 with a limited capacity of 1 mAh cm−2, and the assembled full cell (LiFePO4 as the cathode) maintained a Coulombic efficiency of about 90% for the 30th cycle at 1 C. This novel mechanism is an advanced strategy to improve cyclic stability and is crucial for designing stable lithium metal batteries.
Investigation of the Electrochemical Behaviour of Al Current Collector Material Polarised Highly Anodically and Located in Butyltrimethylammonium Bis(trifluoromethylsulfonyl)imide Room-Temperature Ionic Liquid
Authors: Kruusma Jaanus , Käämbre Tanel , Tõnisoo Arvo , Kisand Vambola , Lust Karmen , Lust Enn
Published: March 2023

The electrochemical behaviour of Al, used as a current collector in supercapacitors and in Li-ion and Na-ion electrochemical power sources, was investigated for the first time using the in situ soft X-ray photoelectron spectroscopy (XPS) method, collecting the information directly at the electrolyte-covered Al current collector polarised electrochemically at high anodic potentials. Cyclic voltammetry, electrochemical impedance spectroscopy, and synchrotron in situ soft XPS methods were applied to collect physical and electrochemical information characterising the electrochemically polarised Al-current-collector RTIL interface soaked into the butyltrimethylammonium bis(trifluoromethylsulfonyl)imide (N4111(TFSI)) room-temperature ionic liquid. The obtained data show the start of intensive oxidation processes, including aluminium oxidation and the formation of an insoluble Al(TFSI)3 surface layer in N4111(TFSI) at E ≥ 3.0 V (vs. Ag-QRE). Very intensive electro-oxidation of TFSI− anions at E ≥ 6.5 V (vs. Ag-QRE) has been observed. CV data indicate that the electrochemical oxidation of once-activated Al is possible in N4111(TFSI) at 1.1 V < E < 1.6 V (vs. Ag-QRE). Therefore, the oxidation of Al starts at E ≥ 2.05 V (vs. Ag-QRE) if the Al surface is modified with electro-oxidation products of TFSI− anions.
Grafting of Cyclodextrin to Theranostic Nanoparticles Improves Blood-Brain Barrier Model Crossing
Authors: Puglisi Antonino , Bognanni Noemi , Vecchio Graziella , Bayir Ece , van Oostrum Peter , Shepherd Dawn , Platt Frances , Reimhult Erik
Published: March 2023

Core–shell superparamagnetic iron oxide nanoparticles hold great promise as a theranostic platform in biological systems. Herein, we report the biological effect of multifunctional cyclodextrin-appended SPIONs (CySPION) in mutant Npc1-deficient CHO cells compared to their wild type counterparts. CySPIONs show negligible cytotoxicity while they are strongly endocytosed and localized in the lysosomal compartment. Through their bespoke pH-sensitive chemistry, these nanoparticles release appended monomeric cyclodextrins to mobilize over-accumulated cholesterol and eject it outside the cells. CySPIONs show a high rate of transport across blood–brain barrier models, indicating their promise as a therapeutic approach for cholesterol-impaired diseases affecting the brain.
Heme Scavenging and Delivery: The Role of Human Serum Albumin
Authors: De Simone Giovanna , Varricchio Romualdo , Ruberto Tommaso Francesco , di Masi Alessandra , Ascenzi Paolo
Published: March 2023

Heme is the reactive center of several metal-based proteins that are involved in multiple biological processes. However, free heme, defined as the labile heme pool, has toxic properties that are derived from its hydrophobic nature and the Fe-atom. Therefore, the heme concentration must be tightly controlled to maintain cellular homeostasis and to avoid pathological conditions. Therefore, different systems have been developed to scavenge either Hb (i.e., haptoglobin (Hp)) or the free heme (i.e., high-density lipoproteins (HDL), low-density lipoproteins (LDL), hemopexin (Hx), and human serum albumin (HSA)). In the first seconds after heme appearance in the plasma, more than 80% of the heme binds to HDL and LDL, and only the remaining 20% binds to Hx and HSA. Then, HSA slowly removes most of the heme from HDL and LDL, and finally, heme transits to Hx, which releases it into hepatic parenchymal cells. The Hx:heme or HSA:heme complexes are internalized via endocytosis mediated by the CD91 and CD71 receptors, respectively. As heme constitutes a major iron source for pathogens, bacteria have evolved hemophores that can extract and uptake heme from host proteins, including HSA:heme. Here, the molecular mechanisms underlying heme scavenging and delivery from HSA are reviewed. Moreover, the relevance of HSA in disease states associated with increased heme plasma concentrations are discussed.
Purification and Biological Properties of Raniseptins-3 and -6, Two Antimicrobial Peptides from Boana raniceps (Cope, 1862) Skin Secretion
Authors: Freitas Gabriel Gonçalves de , Barbosa João Martins , Santana Carlos José Correia de , Magalhães Ana Carolina Martins , Macedo Keven Wender Rodrigues , Souza Jéssica Oliveira de , Castro Jessica Schneider de , Vasconcelos Isadora Alves de , Souza Amanda Araújo , Freitas Sonia Maria de , Báo Sônia Nair , Costa Samuel Ribeiro , Brand Guilherme Dotto , Chaves Ian de Meira , Costa Vivian Vasconcelos , Fontes Wagner , Pires Júnior Osmindo Rodrigues , Castro Mariana S.
Published: March 2023

The number of multidrug-resistant pathogenic microorganisms has been growing in recent years, most of which is due to the inappropriate use of the commercial antibiotics that are currently available. The dissemination of antimicrobial resistance represents a serious global public health problem. Thus, it is necessary to search for and develop new drugs that can act as antimicrobial agents. Antimicrobial peptides are a promising alternative for the development of new therapeutic drugs. Anurans’ skin glands are a rich source of broad-spectrum antimicrobial compounds and hylids, a large and diverse family of tree frogs, are known as an important source of antimicrobial peptides. In the present study, two novel antimicrobial peptides, named Raniseptins-3 and -6, were isolated from Boana raniceps skin secretion and their structural and biological properties were evaluated. Raniseptins-3 and -6 are cationic, rich in hydrophobic residues, and adopt an α-helix conformation in the presence of SDS (35 mM). Both peptides are active against Gram-negative bacteria and Gram-positive pathogens, with low hemolytic activity at therapeutic concentrations. No activity was observed for yeasts, but the peptides are highly cytotoxic against B16F10 murine melanoma cells and NIH3T3 mouse fibroblast cells. None of the tested compounds showed improvement trends in the MTT and LDH parameters of MHV-3 infected cells at the concentrations tested.
PPARα Inhibits Astrocyte Inflammation Activation by Restoring Autophagic Flux after Transient Brain Ischemia
Authors: Luo Doudou , Ye Wenxuan , Chen Ling , Yuan Xiaoqian , Zhang Yali , Chen Caixia , Jin Xin , Zhou Yu
Published: March 2023

Astrocyte inflammation activation is an important cause that hinders the recovery of motor function after cerebral ischemia. However, its molecular mechanism has not yet been clearly clarified. The peroxisome proliferator-activated receptor α (PPARα) is a ligand-activated nuclear transcriptional factor. This study aims to further clarify the role of PPARα in astrocyte inflammation activation after cerebral ischemia and to explore the underlying mechanism. Astrocyte activation was induced in an in vivo model by transient middle cerebral artery occlusion (tMCAO) in mice. The in vitro model was induced by an oxygen-glucose deprivation/reoxygenation (OGD/R) in a primary culture of mouse astrocyte. PPARα-deficient mice were used to observe the effects of PPARα on astrocyte activation and autophagic flux. Our results showed that PPARα was mainly expressed in activated astrocytes during the chronic phase of brain ischemia and PPARα dysfunction promoted astrocyte inflammatory activation. After cerebral ischemia, the expressions of LC3-II/I and p62 both increased. Autophagic vesicle accumulation was observed by electron microscopy in astrocytes, and the block of autophagic flux was indicated by an mRFP-GFP-LC3 adenovirus infection assay. A PPARα deficit aggravated the autophagic flux block, while PPARα activation preserved the lysosome function and restored autophagic flux in astrocytes after OGD/R. The autophagic flux blocker bafilomycin A1 and chloroquine antagonized the effect of the PPARα agonist on astrocyte activation inhibition. This study identifies a potentially novel function of PPARα in astrocyte autophagic flux and suggests a therapeutic target for the prevention and treatment of chronic brain ischemic injury.
Thyroid Hormone and Heart Failure: Charting Known Pathways for Cardiac Repair/Regeneration
Authors: Mantzouratou Polyxeni , Malaxianaki Eleftheria , Cerullo Domenico , Lavecchia Angelo Michele , Pantos Constantinos , Xinaris Christodoulos , Mourouzis Iordanis
Published: March 2023

Heart failure affects more than 64 million people worldwide, having a serious impact on their survival and quality of life. Exploring its pathophysiology and molecular bases is an urgent need in order to develop new therapeutic approaches. Thyroid hormone signaling, evolutionarily conserved, controls fundamental biological processes and has a crucial role in development and metabolism. Its active form is L-triiodothyronine, which not only regulates important gene expression by binding to its nuclear receptors, but also has nongenomic actions, controlling crucial intracellular signalings. Stressful stimuli, such as acute myocardial infarction, lead to changes in thyroid hormone signaling, and especially in the relation of the thyroid hormone and its nuclear receptor, which are associated with the reactivation of fetal development programmes, with structural remodeling and phenotypical changes in the cardiomyocytes. The recapitulation of fetal-like features of the signaling may be partially an incomplete effort of the myocardium to recapitulate its developmental program and enable cardiomyocytes to proliferate and finally to regenerate. In this review, we will discuss the experimental and clinical evidence about the role of the thyroid hormone in the recovery of the myocardium in the setting of heart failure with reduced and preserved ejection fraction and its future therapeutic implications.
Chronic Kidney Disease—How Does It Go, and What Can We Do and Expect?
Authors: Chang Li-Yun , Chang Jer-Ming
Published: March 2023

Chronic kidney disease (CKD), as a worldwide threat to public health, is a key determinant of poor health outcomes, but the severity of the problem is probably not fully appreciated [...]
A 3D-Printed Soft Haptic Device with Built-in Force Sensing Delivering Bio-Mimicked Feedback
Authors: Mutlu Rahim , Singh Dilpreet , Tawk Charbel , Sariyildiz Emre
Published: March 2023

Haptics plays a significant role not only in the rehabilitation of neurological disorders, such as stroke, by substituting necessary cognitive information but also in human–computer interfaces (HCIs), which are now an integral part of the recently launched metaverse. This study proposes a unique, soft, monolithic haptic feedback device (SoHapS) that was directly manufactured using a low-cost and open-source fused deposition modeling (FDM) 3D printer by employing a combination of soft conductive and nonconductive thermoplastic polyurethane (TPU) materials (NinjaTek, USA). SoHapS consists of a soft bellow actuator and a soft resistive force sensor, which are optimized using finite element modeling (FEM). SoHapS was characterized both mechanically and electrically to assess its performance, and a dynamic model was developed to predict its force output with given pressure inputs. We demonstrated the efficacy of SoHapS in substituting biofeedback with tactile feedback, such as gripping force, and proprioceptive feedback, such as finger flexion–extension positions, in the context of teleoperation. With its intrinsic properties, SoHapS can be integrated into rehabilitation robots and robotic prostheses, as well as augmented, virtual, and mixed reality (AR/VR/MR) systems, to induce various types of bio-mimicked feedback.
Gold Nanoparticle-Based Plasmonic Biosensors
Authors: Ferrari Enrico
Published: March 2023

One of the emerging technologies in molecular diagnostics of the last two decades is the use of gold nanoparticles (AuNPs) for biosensors. AuNPs can be functionalized with various biomolecules, such as nucleic acids or antibodies, to recognize and bind to specific targets. AuNPs present unique optical properties, such as their distinctive plasmonic band, which confers a bright-red color to AuNP solutions, and their extremely high extinction coefficient, which makes AuNPs detectable by the naked eye even at low concentrations. Ingenious molecular mechanisms triggered by the presence of a target analyte can change the colloidal status of AuNPs from dispersed to aggregated, with a subsequent visible change in color of the solution due to the loss of the characteristic plasmonic band. This review describes how the optical properties of AuNPs have been exploited for the design of plasmonic biosensors that only require the simple mixing of reagents combined with a visual readout and focuses on the molecular mechanisms involved. This review illustrates selected examples of AuNP-based plasmonic biosensors and promising approaches for the point-of-care testing of various analytes, spanning from the viral RNA of SARS-CoV-2 to the molecules that give distinctive flavor and color to aged whisky.
Does Music Therapy Improve Gait after Traumatic Brain Injury and Spinal Cord Injury? A Mini Systematic Review and Meta-Analysis
Authors: Ghai Shashank
Published: March 2023

There is a growing body of research examining the potential benefits of music therapy-based auditory stimulation (MT) for individuals with movement disorders in improving gait performance. However, there is limited knowledge about the effects of MT on gait outcomes in individuals with traumatic brain injury (TBI) or spinal cord injury (SCI). A previous review of MT’s impact on gait in TBI had limitations, and there are no studies on its effects on gait in SCI. In this study, we conducted a meta-analysis to more thoroughly evaluate the impact of MT on gait outcomes in individuals with TBI and SCI. We systematically searched through eight databases and found six studies on MT in TBI and four on SCI. Our meta-analysis showed that MT has positive medium effect improvements on spatiotemporal aspects of gait in individuals with TBI (Hedge’s g: 0.52) and SCI (0.53). These findings suggest that MT could be a practical intervention for enhancing different aspects of gait in these populations, although the limited number and “fair” quality of the studies included in the meta-analysis may affect the generalizability of the outcomes. Further research is needed to fully understand the mechanisms by which MT may influence gait and determine the optimal parameters for its use.
Antidepressant Activities of Synthesized Benzodiazepine Analogues in Mice
Authors: Haq Faizan Ul , Shoaib Mohammad , Ali Shah Syed Wadood , Hussain Haya , Zahoor Muhammad , Ullah Riaz , Bari Ahmed , Alotaibi Amal , Hayat Muhammad Faisal
Published: March 2023

Depression is a serious psychological disorder which negatively affects human feelings and actions. The use of antidepressants is the therapy of choice while treating depression. However, such drugs are associated with severe side effects. There is a need for efficient and harmless drugs. In this connection, the present study was designed to synthesize several substituted benzodiazepine derivatives and explore their antidepressant potentials in an animal model. The chalcone backbone was initially synthesized, which was then converted into several substituted benzodiazepine derivatives designated as 1–6. The synthesized compounds were identified using spectroscopic techniques. The experimental animals (mice) after acclimatation were subjected to forced swim test (FST) and tail suspension test (TST) after oral administration of the synthesized compounds to evaluate their antidepressant potentials. At the completion of the mentioned test, the animals were sacrificed to determine GABA level in their brain hippocampus. The chloro-substituent compound (2) significantly reduced the immobility time (80.81 ± 1.14 s; p < 0.001 at 1.25 mg/kg body weight and 75.68 ± 3.73 s with p < 0.001 at 2.5 mg/kg body weight dose), whereas nitro-substituent compound (5) reduced the immobility time to 118.95 ± 1.31 and 106.69 ± 3.62 s (p < 0.001), respectively, at the tested doses (FST). For control groups, the recorded immobility time recorded was 177.24 ± 1.82 s. The standard drug diazepam significantly reduced immobility time to 70.13 ± 4.12 s while imipramine reduced it to 65.45 ± 2.81 s (p < 0.001). Similarly, in the TST, the compound 2 reduced immobility time to 74.93 ± 1.14 s (p < 0.001) and 70.38 ± 1.43 s (p < 0.001), while compound 5 reduced it to 88.23 ± 1.89 s (p < 0.001) and 91.31 ± 1.73 s (p < 0.001) at the tested doses, respectively, as compared to the control group immobility time (166.13 ± 2.18 s). The compounds 1, 3, 4, and 6 showed weak antidepressant responses as compared to compounds 2 and 5. The compounds 2 and 5 also significantly enhanced the GABA level in the brain’s hippocampus of experimental animals, indicating the possible involvement of GABAergic mechanism in alleviating the depression which is evident from the significant increase in mRNA levels for the α subunit of the GABAA receptors in the prefrontal cortex of mice as well. From the results, it can be concluded that compound 2 and 5 could be used as alternative drugs of depression. However, further exploration in this connection is needed in other animal models in order to confirm the observed results in this study.
Somatic Cell Reprogramming for Nervous System Diseases: Techniques, Mechanisms, Potential Applications, and Challenges
Authors: Chen Jiafeng , Huang Lijuan , Yang Yue , Xu Wei , Qin Qingchun , Qin Rongxing , Liang Xiaojun , Lai Xinyu , Huang Xiaoying , Xie Minshan , Chen Li
Published: March 2023

Nervous system diseases present significant challenges to the neuroscience community due to ethical and practical constraints that limit access to appropriate research materials. Somatic cell reprogramming has been proposed as a novel way to obtain neurons. Various emerging techniques have been used to reprogram mature and differentiated cells into neurons. This review provides an overview of somatic cell reprogramming for neurological research and therapy, focusing on neural reprogramming and generating different neural cell types. We examine the mechanisms involved in reprogramming and the challenges that arise. We herein summarize cell reprogramming strategies to generate neurons, including transcription factors, small molecules, and microRNAs, with a focus on different types of cells.. While reprogramming somatic cells into neurons holds the potential for understanding neurological diseases and developing therapeutic applications, its limitations and risks must be carefully considered. Here, we highlight the potential benefits of somatic cell reprogramming for neurological disease research and therapy. This review contributes to the field by providing a comprehensive overview of the various techniques used to generate neurons by cellular reprogramming and discussing their potential applications.
Research on the Factors Affecting the Adoption of Smart Aged-Care Products by the Aged in China: Extension Based on UTAUT Model
Authors: Wang Xiang , Lee Chang-Franw , Jiang Jiabei , Zhang Genlei , Wei Zhong
Published: March 2023

With the rapid development of network technology and smart technology, smart aged-care products are becoming increasingly valued for their ability to help the aged actively cope with the challenges of aging. However, seniors face challenges in using smart aged-care products for many reasons, which reduces their willingness to adopt them. As a result, the sustainable development of smart aged-care products is constrained. This study combined the unified theory of technology acceptance and use, perceived risk theory and perceived cost theory, and reconstructed a research model that investigated the adoption of smart aged-care products by the elderly in China. Questionnaires were given to older Chinese adults in this study, and 386 valuable responses were received. The findings of the structural equation model (SEM) analysis are as follows: (1) performance expectancy, effort expectancy, and social influence were positively related to the behavioral intention of seniors to use smart aged-care products; (2) perceived cost and perceived risk were negatively related to the behavioral intention of seniors to use smart aged-care products; (3) perceived risk indirectly affected use behavior through behavioral intentions; (4) facilitating conditions did not have a significant impact on the use behavior of seniors in adopting smart aged-care products. Based on the empirical results, this study sought to improve the use behavior of the aged in relation to the adoption of smart aged-care products, and provided suggestions to improve the overall service quality and sustainability of those products.
The Importance of the 5Cs of Positive Youth Development to Depressive Symptoms: A Cross-Sectional Study with University Students from Peru and Spain
Authors: Manrique-Millones Denisse , Gómez-Baya Diego , Wiium Nora
Published: March 2023

Background: Prior research has documented the protective role of the 5Cs of Positive Youth Development (PYD) on adjustment problems, such as depressive symptoms. Nonetheless, more research is needed, especially in non-US contexts. The main objective of the present study was to assess associations between the 5Cs and depressive symptoms in Peru and Spain, considering gender differences across contexts. Methods: Cross-sectional data was collected from undergraduate students from Peru [n = 250] and Spain [n = 1044]. Results: The results revealed significant negative associations of Competence, Confidence, Character and Connection with depressive symptoms, while Caring was positively and significantly related to depressive symptoms in both samples. Regarding gender differences, female undergraduates in both samples reported high levels of Caring, while Competence was predominant among males compared to females in both countries. Likewise, higher scores in Competence and Confidence were registered among Peruvian male undergraduates compared to Spanish students, while Caring and Character were more prevalent in Spanish female undergraduates compared to Peruvian students. Conclusions: These findings confirm the importance of targeting the 5Cs of PYD alongside the role of gender and country context in intervention programs, put together to address the mental health of students in Peru and Spain.
Sharing Is Saving? Building Costs Simulation of Collaborative and Mainstream Housing Designs
Authors: Brysch Sara , Gruis Vincent , Czischke Darinka
Published: March 2023

Building costs play a significant role in determining the affordability of a housing project, and these depend to a large extent on design choices. This paper is based on the premise that collaborative design processes, or co-design, used in collaborative housing (CH) in Europe reduce building costs and consequently increase the affordability of these housing projects. However, research remains scarce on the extent to which CH is an affordable solution from a design perspective compared to affordable mainstream housing (MH), in which no co-design is used. Therefore, this paper aims to fill this knowledge gap by assessing the impact of design choices on building costs in CH and MH. To this end, we developed a simulation model to compare the building costs of CH with MH based on their design choices. Findings indicate that CH represents a more affordable and space-efficient solution when compared to MH, if we look at the building costs per unit. This is because CH provides less expensive units while it includes larger common spaces and extra quality. These results help to refute existing claims about the unaffordability of CH design solutions.
Investigation of Corrosion Effects on Collapse of Truss Structures
Authors: Fırat Alemdar Zeynep , Alemdar Fatih
Published: March 2023

Corrosion damage is a serious problem in steel structures. The cross-sectional loss in the structural members due to corrosion reduces the load-carrying capacity of the members and the stability of their structures. In this study, the main reasons for the collapse of three steel sports infrastructure facilities after moderate snowfall were investigated by conducting field observations and detailed numerical analyses. Finite element models of the structures were developed by considering the effects of different rafter systems and corrosion damage at their columns’ support regions. The load-carrying capacity ratios and stress distributions of the structural members were determined under the effect of the snow load at the time of the collapse. The analysis results were consistent with the damage modes observed during site inspections. The snowfall was not the primary cause of the collapse; however, the section and joint losses due to excessive corrosion, improper erections, and discrepancies between the design project and the as-built project were the main reasons for the collapse.
Dynamic Response Modeling of Mountain Transmission Tower-Line Coupling System under Wind–Ice Load
Authors: Song Haoran , Li Yingna
Published: March 2023

Transmission lines have the characteristics of being tall tower structures with a large span distribution of transmission lines that are sensitive to external loads such as wind and ice, and belong to strong, nonlinear, complex, rigid-flexible coupling systems. The force process of the tower-line structure is a combination of instantaneous and continuously stressed, so it is not accurate to judge the safety of the transmission line based only on the operation status of the transmission tower or the conductor. In this paper, a finite element model of three towers and two lines with large span and large elevation differences is established by taking into account the tower-line coupling system. From the static point of view, the static axial force of a single tower and the contribution rate of wind and ice load are analyzed, and the ultimate bearing capacity of a tension-type electric tower is obtained by considering the bending effect and critical initial defects. From the perspective of transient dynamic response, the displacement of the tower-line coupling system under wind–ice load is calculated, and the force characteristics and force transmission process of the straight tower under wind–ice load are observed. Multiple comparison models are set up to compare and analyze the sway and tension under large span and large elevation differences, and the maximum icing thickness of each group model is obtained by repeated trials. The experimental results show that under the tower-line coupling system, the contribution of wind load to the axial force of the main material is 72.92%, and the contribution of wind–ice load to the axial force of main material is 27.6%. The maximum increase tension under transient ice-off effect is 59.58%, the ultimate force of the tension tower is 545.5 kN, and the maximum icing thickness of the transmission line under large span and large elevation differences is 28.7 cm, which is slightly larger than the design icing thickness. In conclusion, this paper can provide reference for the construction of mountain transmission towers, power safety inspection, and line health status assessment.
A French Residential Retrofit toward Achieving Net-Zero Energy Target in a Mediterranean Climate
Authors: Kutty Najeeba , Barakat Dua , Khoukhi Maatouk
Published: March 2023

Cities are paying more attention to building energy use and carbon footprint for attaining sustainability. Within this building sector, there is a growing attention toward development and adoption of energy efficient retrofit strategies. Plagued by the lack of efforts in achieving comprehensive energy efficient retrofit solution sets (passive, active, and renewable energy systems), the authors acknowledge the concept of NZEB toward achieving energy efficiency by 2050. Toward this end, a numerical energy simulation modeling is carried out to retrofit an existing French “Puccini house” using ‘passive, energy efficient building systems and renewable energy’ strategies toward an NZEB target in the Mediterranean climate of Nice. Using Design builder 7.0, the simulated baseline energy model (Case A) is retrofitted through variations in the proposed energy efficient retrofit measures using two case scenarios (Case B: passive retrofit; Case C: energy-efficient building) to achieve NZEB (Case D). Assessing the performance of energy efficient retrofits using % energy reduction, the implementation of a high-performance building envelope is achieved using a thermally insulated external wall (46.82%), upgraded airtightness (20.39%), thermally insulated pitched roof component (33.03%), and high-performance window type—a glazing system (3.35%) with maximized window-to-wall ratio (5.53%). The maximum energy-saving retrofit solutions provide an ambitious reduction in energy consumption by approximately 90% from the baseline. A deep retrofitting of the French house meets the NZEB targets, as it reduces the baseline energy consumption from 194.37 kWh/m2/year to 23.98 kWh/m2/year using both passive and active strategies. The remaining energy demand is met by the integration of on-site PV panels (EUI= −27.71 kWh/m2/year), which achieve an increase in energy production by 15.5%, while returning energy back to the grid (−3.73 kWh/m2/year). Findings of this study serve as a guideline for retrofitting traditional French single-family residences, while contributing toward the NZEB goal.
Immune Checkpoint Inhibitors and the Kidney: A Focus on Diagnosis and Management for Personalised Medicine
Authors: Longhitano Elisa , Muscolino Paola , Lo Re Claudia , Ferrara Serena Ausilia , Cernaro Valeria , Gembillo Guido , Tessitore Dalila , Speranza Desirèe , Figura Francesco , Santarpia Mariacarmela , Silvestris Nicola , Santoro Domenico , Franchina Tindara
Published: March 2023

Immunity plays a crucial role in fighting cancer, but tumours can evade the immune system and proliferate and metastasize. Enhancing immune responses is a new challenge in anticancer therapies. In this context, efficacy data are accumulating on immune checkpoint inhibitors and adjuvant therapies for various types of advanced-stage solid tumours. Unfortunately, immune-related adverse events are common. Although infrequent, renal toxicity may occur via several mechanisms and may require temporary or permanent drug suspension, renal biopsy, and/or immunosuppressive treatment. This short review aims to provide a practical approach to the multidisciplinary management of cancer patients with renal toxicity during treatment with immune checkpoint inhibitors.