bluuebunny/crossref_metadata_2025 huggingface dataset:
Enhanced Spatial Stream of Two-Stream Network Using Optical Flow for Human Action Recognition
Authors: Khan Shahbaz , Hassan Ali , Hussain Farhan , Perwaiz Aqib , Riaz Farhan , Alsabaan Maazen , Abdul Wadood
Published: July 2023

Introduction: Convolutional neural networks (CNNs) have maintained their dominance in deep learning methods for human action recognition (HAR) and other computer vision tasks. However, the need for a large amount of training data always restricts the performance of CNNs. Method: This paper is inspired by the two-stream network, where a CNN is deployed to train the network by using the spatial and temporal aspects of an activity, thus exploiting the strengths of both networks to achieve better accuracy. Contributions: Our contribution is twofold: first, we deploy an enhanced spatial stream, and it is demonstrated that models pre-trained on a larger dataset, when used in the spatial stream, yield good performance instead of training the entire model from scratch. Second, a dataset augmentation technique is presented to minimize overfitting of CNNs, where we increase the dataset size by performing various transformations on the images such as rotation and flipping, etc. Results: UCF101 is a standard benchmark dataset for action videos, and our architecture has been trained and validated on it. Compared with the other two-stream networks, our results outperformed them in terms of accuracy.
On a Novel Approach to Correcting Temperature Dependencies in Magnetic Observatory Data
Authors: Kudin Dmitry , Soloviev Anatoly , Matveev Mikhail , Shevaldysheva Olga
Published: July 2023

High-quality geomagnetic measurements are widely used in both fundamental research of the magnetic field and numerous industrial applications. However, vector data measured by fluxgate sensors show a dependency on temperature due to sensitive coil core material and components of the sensor electronics. Here, we propose a new method for detecting and eliminating temperature dependence in magnetic observatory data. The method is designed to correct temperature drifts in variation vector magnetometer measurements when preparing quasi-definitive data according to an INTERMAGNET standard. A special feature of the method is the semi-automatic adjustment of localization intervals for temperature correction, which prevents boundary jumps and discontinuities in the course of sequential data processing over long intervals. The conservative nature of the approach implies the minimization of the original data amount subjected to correction. The described method is successfully applied in the routine monthly preparation of quasi-definitive data of the Saint Petersburg Observatory (IAGA-code SPG) and can be efficiently introduced at other magnetic observatories worldwide.
FusionTrack: Multiple Object Tracking with Enhanced Information Utilization
Authors: Yang Yifan , He Ziqi , Wan Jiaxu , Yuan Ding , Liu Hanyang , Li Xuliang , Zhang Hong
Published: July 2023

Multi-object tracking (MOT) is one of the significant directions of computer vision. Though existing methods can solve simple tasks like pedestrian tracking well, some complex downstream tasks featuring uniform appearance and diverse motion remain difficult. Inspired by DETR, the tracking-by-attention (TBA) method uses transformers to accomplish multi-object tracking tasks. However, there are still issues with existing TBA methods within the TBA paradigm, such as difficulty detecting and tracking objects due to gradient conflict in shared parameters, and insufficient use of features to distinguish similar objects. We introduce FusionTrack to address these issues. It utilizes a joint track-detection decoder and a score-guided multi-level query fuser to enhance the usage of information within and between frames. With these improvements, FusionTrack achieves 11.1% higher by HOTA metric on the DanceTrack dataset compared with the baseline model MOTR.
Risk Propagation Mechanism and Prediction Model for the Highway Merging Area
Authors: Ye Qing , Li Yi , Niu Ben
Published: July 2023

The merging area is one of the most accident-prone areas on highways. After an accident occurs, the risk will propagate along the main road over a certain range and time. Therefore, the study of the propagation mechanism of accident risk will help to quantify the driving risk in this region. An effective risk prediction model is important for improving traffic control measures in this specific area. In this study, simulation experiments were conducted in SUMO (Simulation of Urban Mobility) to obtain the accident and risk propagation data in merging areas. Firstly, the Gaussian plume model was optimized for the merging area situation to determine and divide the impact range of the accidents. Then, different accident scenarios in the merging area and downstream were simulated with different input flow rates to study the time and speed of risk propagation in the three-level affected areas. Finally, LSTM (long short-term memory) and RNN (recurrent neural network) models were built to predict the accident risk in the merging area. The results showed that the LSTM model had higher accuracy. This study provides an innovative insight into the propagation process of merging area accidents. It is of benefit to the development of post-accident control measures.
A Gaussian Process Decoder with Spectral Mixtures and a Locally Estimated Manifold for Data Visualization
Authors: Watanabe Koshi , Maeda Keisuke , Ogawa Takahiro , Haseyama Miki
Published: July 2023

Dimensionality reduction plays an important role in interpreting and visualizing high-dimensional data. Previous methods for data visualization overestimate the local structure and lack the consideration of global preservation. In this study, we develop a Gaussian process latent variable model (GP-LVM) for data visualization. GP-LVMs are one of the frameworks of principal component analysis and preserve the global structure effectively. The drawbacks of GP-LVMs are the absence of local structure preservation and the use of low-expressive kernel functions. Therefore, we introduce regularization for local preservation and an expressive kernel function into GP-LVMs to overcome these limitations. As a result, we reflect the global and local structures in low-dimensional representations, improving the reliability and visibility of embeddings. We conduct qualitative and quantitative experiments comparing baselines and state-of-the-art methods on image and text datasets.
Biocompatibility of Membranes Based on a Mixture of Chitosan and Lythri herba Aqueous Extract
Authors: Iancu Irina Mihaela , Schröder Verginica , Apetroaei Manuela-Rossemary , Crețu Ruxandra Mihaela , Mireșan Horațiu , Honcea Adina , Iancu Valeriu , Bucur Laura Adriana , Mitea Gabriela , Atodiresei-Pavalache Georgiana
Published: July 2023

In the current context of concern for the improvement and protection of environmental conditions, emphasis is placed on the provision of non-toxic, eco-friendly, renewable biomaterials to replace established chemical substances. Lythri herba is the aerial part of the plant species Lythrum salicaria L., known in the scientific literature especially for its content of tannins and total polyphenols, which highlight its antioxidant, hemostatic, antibacterial and antidiarrheal properties. Chitosan is a biopolymer widely used in industry and medicine due to its abundance in nature, its biodegradability, lack of toxicity and the ease with which it can be transformed into several basic forms (hydrogel, membrane, sponge). The aqueous solutions and membranes obtained in this study by merging these two natural resources were biologically tested in terms of genotoxicity (SOS-Chromo assay), hemolytic activity, thrombin generation activity and bacterial adhesion to reveal outwardly the lack of these properties and their use for medical purposes. The results of the current study attest to the absence of mutagenic and slight hemolyzing properties, thus supporting the possibility of using this extract and membrane in medical and pharmaceutical therapeutic practice. The surface parameters of membranes were examined and important influences at thrombin activity were found. Also, bacterial adhesion results showed a correlation between Lythri herba and chitosan concentrations and membranes’ appearances (swelling, stability). The results show that the membranes could be a promising material for biomedical applications.
The Effect of Non-Newtonian Fluid Midsole Footwear on Lower Limb Biomechanics after 5 km of Running in High Temperature
Authors: Ye Jingyi , Gao Lidong , Shao Enze , Kovács Bálint , Li Jiao , Gu Yaodong
Published: July 2023

This study’s aim was to examine the effect of non-Newtonian fluid (NN) shoe and ethylene vinyl acetate (EVA) shoe on human lower limb biomechanics and muscle activation during running in hot temperatures. Thirty-five men utilizing a rearfoot strike ran 5 km at a self-selected tempo at an average summer temperature of 41.7 ± 1.0 °C and relative humidity of 80.7 ± 3.5%. The kinematics, kinetics, and muscle activation of the right leg were monitored from landing until the pedal was off the ground. A two-way repeated-measures ANOVA was conducted to investigate the main effects of the shoe condition, temperature, and interaction effect. Wearing NN at high temperature resulted in increased hip range of motion (ROM) (p = 0.001). The knee torque increased significantly when wearing EVA and NN shoes after the temperature increased (p = 0.006). When wearing EVA and NN, the ground reaction force (GRF) and loading rate (LR) increased significantly after the temperature increased (p = 0.001; p = 0.009). When wearing NN after running for 5 km at a high temperature, the displacement range of center of pressure (COP) was significantly reduced (p < 0.001), while the EVA was significantly increased (p < 0.001). Neither pair of shoes substantially altered muscle activity. After excluding the factor of fatigue, the increase in temperature not only changed the properties of the material inside the shoe, but also changed the parameters of the biomechanics of the human lower limbs. After the temperature increases, the shoes made of non-Newtonian fluid materials can quickly stabilize under the condition of increased shear stress and reduce the displacement of the human body. Thus, it indicated that non-Newtonian fluid shoes may lower the risk of injury when running in extremely hot conditions.
A New Method for Calculating Prediction Parameters of Surface Deformation in the Mining Area
Authors: Chi Shenshen , Wang Lei , Yu Xuexiang
Published: July 2023

The accurate calculation of mining-induced surface deformation has important guiding significance for efficient and safe production in mining areas. The probability integral method (PIM) is a main prediction method in China, and the selection of its parameters is directly related to the prediction accuracy of surface deformation in mining areas. To overcome shortcomings of PIM and other methods, this paper proposed a prediction model of the parameters of PIM combining a multiple regression model and an extreme learning machine. In this paper, the Huainan mining area was selected as the research object, the influence factors of PIM parameters were analyzed and the accuracy of the model was verified. The influence of the number of hidden layer nodes, the selection of activation function and the proportion of training set and test set in the model were analyzed. The conclusions suggest that the PIM parameters calculated in this paper could be used to predict mining subsidence and obtain surface movement and deformation data. The research results provide an effective method for the selection of surface deformation prediction parameters of new working faces or faces lacking measured data.
Engineering Hydroponic Systems for Sustainable Wastewater Treatment and Plant Growth
Authors: Clyde-Smith Dominic , Campos Luiza C.
Published: July 2023

This study aimed to optimize hydroponic systems for simultaneous wastewater treatment/nutrient recovery and plant growth. Various hydroponic systems (geyser pump, full flow, ebb and flow, nutrient film techniques, aeroponics, misting) were constructed using 160 mm PVC waste pipes supported on a 200 L reservoir. Secondary wastewater was used to cultivate rice (Oryza sativa), ivy (Hedera helix), tomatoes (Solanum lycopersicum), and wheatgrass (Triticum aestivum). Parameters such as plant height, biomass, retention time, temperature, conductivity, pH, dissolved oxygen, ammonia, nitrite, nitrate, total phosphorus, COD, BOD, TDS, TSS, and TS were monitored. Results indicated minor variations in pH, EC, and TDS over time in systems with and without plants, with no significant differences. Turbidity decreased significantly (p ≤ 0.001) in all systems, while TOC levels reduced significantly (p ≤ 0.05) only in the presence of plants. BOD and COD levels exhibited similar reductions with and without plants. Ammonium levels decreased in plant systems, while nitrite levels remained unchanged. Nitrate levels increased significantly in plant systems, and phosphate levels showed no significant difference. Additionally, significant (p ≤ 0.001) plant length (12.84–46.75%) and biomass (31.90–57.86%) increases were observed in all hydroponic systems, accompanied by higher levels of dissolved oxygen (36.26–53.65%), compared to the control (4.59%). The hydroponic system that created a moist atmosphere, either through misting or aeroponics, thus allowing maximum access to oxygen, showed the greatest growth. This study confirmed the importance of oxygen availability to the rhizosphere for plant growth and wastewater treatment. It also identified limitations and investigated the impact of dissolved oxygen concentration on plant–microorganism interactions. Optimal oxygen availability was achieved when plant roots were exposed to a moist atmosphere created by the hydroponic system through aeroponics or misting. The findings have practical implications for hydroponic system design in urban vertical farms, benefiting wastewater treatment, mitigating eutrophication, and reducing food miles.
Maximum Power Point Tracking Algorithm of Photo-Voltaic Array through Determination of Boost Converter Conduction Mode
Authors: Noman Abdullah M. , Sheikh Haseeb Shakeel , Murtaza Ali Faisal , Almutairi Sulaiman Z. , Alqahtani Mohammed H. , Aljumah Ali S.
Published: July 2023

In this paper, we present a new maximum power point tracking (MPPT) algorithm that can identify whether a boost converter is operating in continuous conduction mode (CCM) or discontinuous conduction mode (DCM). The conventional MPPT algorithm assumes that the converter is always in CCM mode, even though this is not always the case. The converter can enter DCM mode due to factors such as the inductor size, irradiance and temperature conditions, voltage step size of the algorithm, and operating point of the PV array. In the proposed work, the conduction mode of a boost converter is evaluated under different conditions. The region of the I–V curve where the converter is likely to operate in DCM mode is identified and a mathematical expression developed in this work is then used to detect the conduction mode of the converter. The proposed algorithm incorporates this expression into a modified perturb and observe (P&O) algorithm. In each iteration, the algorithm first detects the conduction mode of the converter. If the converter is in DCM mode, the algorithm takes a large voltage step to force the converter back into CCM mode, i.e., into the constant current region. The proposed MPPT algorithm was tested using simulation experiments, and the results show that the proposed algorithm can significantly improve the efficiency of the MPPT process.
Linear Optics Calibration in a Storage Ring Based on Machine Learning
Authors: Li Ruichun , Jiang Bocheng , Zhang Qinglei , Zhao Zhentang , Li Changliang , Wang Kun
Published: July 2023

Inevitably, various errors occur in an actual storage ring, such as magnetic field errors, magnet misalignments, and ground settlement deformation, which cause closed orbit distortion and tuning shift. Therefore, linear optics calibration is an essential procedure for storage rings. In this paper, we introduce a new method using machine learning to calibrate linear optics. This method is different from the traditional linear optics from closed orbit (LOCO) method, which is based on singular value decomposition (SVD). The machine learning model does not need to be computed by SVD. Our study shows that the machine-learning-based method can significantly reduce the difference between the model response matrix and the measurement response matrix by adjusting the strength of the quadrupoles.
Implementing and Improving CBMZ-MAM3 Chemistry and Aerosol Modules in the Regional Climate Model WRF-CAM5: An Evaluation over the Western US and Eastern North Pacific
Authors: Wu Xiaokang , Feng Yan , He Cenlin , Kumar Rajesh , Ge Cui , Painemal David , Xu Yangyang
Published: July 2023

The representation of aerosols in climate–chemistry models is important for air quality and climate change research, but it can require significant computational resources. The objective of this study was to improve the representation of aerosols in climate–chemistry models, specifically in the carbon bond mechanism, version Z (CBMZ), and modal aerosol modules with three lognormal modes (MAM3) in the WRF-CAM5 model. The study aimed to enhance the model’s chemistry capabilities by incorporating biomass burning emissions, establishing a conversion mechanism between volatile organic compounds (VOCs) and secondary organic carbons (SOCs), and evaluating its performance against observational benchmarks. The results of the study demonstrated the effectiveness of the enhanced chemistry capabilities in the WRF-CAM5 model. Six simulations were conducted over the western U.S. and northeastern Pacific region, comparing the model’s performance with observational benchmarks such as reanalysis, ground-based, and satellite data. The findings revealed a significant reduction in root-mean-square errors (RMSE) for surface concentrations of black carbon (BC) and organic carbon (OC). Specifically, the model exhibited a 31% reduction in RMSE for BC concentrations and a 58% reduction in RMSE for OC concentrations. These outcomes underscored the importance of accurate aerosol representation in climate–chemistry models and emphasized the potential for improving simulation accuracy and reducing errors through the incorporation of enhanced chemistry modules in such models.
Long-Term Trends of Extreme Climate Indexes in the Southern Part of Siberia in Comparison with Those of Surrounding Regions
Authors: Watanabe Takanori , Matsuyama Hiroshi , Kuzhevskaia Irina , Nechepurenko Olga , Chursin Vladislav , Zemtsov Valerii
Published: July 2023

Siberia, which experienced disastrous heat waves in 2010 and 2012, is one of the regions in which extreme climate events have occurred recently. To compare the long-term trends of extreme climate events in the southern part of Siberia with those of surrounding regions, we calculated 11 extreme climate indexes from observational data for 1950–2019 and analyzed the trends in Siberia and other parts of Russia using statistical techniques, i.e., Welch’s t-test, the Mann–Kendall test, Sen’s slope estimator, and a cluster analysis. We clarified that high-temperature events in March are more frequent in Siberia than in the surrounding areas. However, the increasing trends of high temperatures in Siberia were lower than those in northwestern China and Central Asia. The intensity of heavy precipitation is increasing in Siberia, as it is in the surrounding areas. Compared to the surrounding areas analyzed in previous studies, the trend of heavy precipitation in Siberia has not increased much. In particular, Siberia shows a more remarkable decreasing trend in heavy precipitation during the summer than other regions. The dry trends in the summer, however, do not occur in Siberia as a whole, and the opposite trend of summer precipitation was observed in some areas of Siberia.
Role of Gas Pressure in Quasi-Phase Matching in High Harmonics Driven by Two-Color Laser Field
Authors: Stremoukhov Sergey
Published: July 2023

The results of a study on the effect of pressure in a medium consisting of a set of gas jets separated by vacuum gaps, interacting with two-color laser fields formed by the fundamental and the second harmonics of a laser, are presented herein. It has been demonstrated that a decrease in pressure leads to a shift in the region of harmonics where quasi-phase matching (QPM) occurs towards shorter wavelength radiation, accompanied by an increase in the efficiency of amplification of these harmonics. A feature of this process is the identical power-law character of the shift in the region and the increase in the efficiency of harmonic QPM amplification. Additionally, the study presents the results of the effect of inaccurately setting the width of the gas jets on the shape of the spectrum of harmonic QPM amplification.
On Modified Interpolative Almost E−Type Contraction in Partial Modular b−Metric Spaces
Authors: Kesik Dilek , Büyükkaya Abdurrahman , Öztürk Mahpeyker
Published: July 2023

The current study attempts to identify a new generalized metric space structure, referred to as partial modular b−metric, that extends both partial modular metric space via b−metric space and explains the topological aspects of the new space implementing examples. In addition, a new contraction mapping referred to as modified interpolative almost E−type contraction is determined, which is an interpretation of interpolative contraction bestowed with almost contraction and E−contraction as well as a simulation function and a fixed point theorem that encompass such mappings in the context of partial modular b−metric space is demonstrated. In conclusion, an example and an application that endorse the main theorem’s outcomes are offered.
Robust Optimality Conditions for a Class of Fractional Optimization Problems
Authors: Saeed Tareq
Published: July 2023

In this paper, by considering the parametric technique, we study a class of fractional optimization problems involving data uncertainty in the objective functional. We formulate and prove the robust Karush-Kuhn-Tucker necessary optimality conditions and provide their sufficiency by considering the convexity and/or concavity assumptions of the involved functionals. In addition, to complete the study, an illustrative example is presented.
A Unified Approach for Extremal General Exponential Multiplicative Zagreb Indices
Authors: Ismail Rashad , Azeem Muhammad , Shang Yilun , Imran Muhammad , Ahmad Ali
Published: July 2023

The study of the maximum and minimal characteristics of graphs is the focus of the significant field of mathematics known as extreme graph theory. Finding the biggest or smallest graphs that meet specified criteria is the main goal of this discipline. There are several applications of extremal graph theory in various fields, including computer science, physics, and chemistry. Some of the important applications include: Computer networking, social networking, chemistry and physics as well. Recently, in 2021 exponential multiplicative Zagreb indices were introduced. In generalization, we introduce the generalized form of exponential multiplicative Zagreb indices for α∈R+\{1}. Furthermore, to see the behaviour of generalized first and second exponential Zagreb indices for α∈R+\{1}, we used a transformation method. In term of the two newly developed generalized exponential multiplicative Zagreb indices, we will investigate the extremal bicyclic, uni-cyclic and trees graphs. Four graph transformations are used and some bounds are presented in terms of generalized exponential multiplicative Zagreb indices.
OralNet: Fused Optimal Deep Features Framework for Oral Squamous Cell Carcinoma Detection
Authors: Mohan Ramya , Rama Arunmozhi , Raja Ramalingam Karthik , Shaik Mohammed Rafi , Khan Mujeeb , Shaik Baji , Rajinikanth Venkatesan
Published: July 2023

Humankind is witnessing a gradual increase in cancer incidence, emphasizing the importance of early diagnosis and treatment, and follow-up clinical protocols. Oral or mouth cancer, categorized under head and neck cancers, requires effective screening for timely detection. This study proposes a framework, OralNet, for oral cancer detection using histopathology images. The research encompasses four stages: (i) Image collection and preprocessing, gathering and preparing histopathology images for analysis; (ii) feature extraction using deep and handcrafted scheme, extracting relevant features from images using deep learning techniques and traditional methods; (iii) feature reduction artificial hummingbird algorithm (AHA) and concatenation: Reducing feature dimensionality using AHA and concatenating them serially and (iv) binary classification and performance validation with three-fold cross-validation: Classifying images as healthy or oral squamous cell carcinoma and evaluating the framework’s performance using three-fold cross-validation. The current study examined whole slide biopsy images at 100× and 400× magnifications. To establish OralNet’s validity, 3000 cropped and resized images were reviewed, comprising 1500 healthy and 1500 oral squamous cell carcinoma images. Experimental results using OralNet achieved an oral cancer detection accuracy exceeding 99.5%. These findings confirm the clinical significance of the proposed technique in detecting oral cancer presence in histology slides.
Active Estrogen–Succinate Metabolism Promotes Heme Accumulation and Increases the Proliferative and Invasive Potential of Endometrial Cancer Cells
Authors: Lu Jia-Jing , Zhang Xing , Abudukeyoumu Ayitila , Lai Zhen-Zhen , Hou Ding-Yu , Wu Jiang-Nan , Tao Xiang , Li Ming-Qing , Zhu Xiao-Yong , Xie Feng
Published: July 2023

Uterine endometrial cancer (UEC) is an estrogen-related tumor. Succinate and heme metabolism play important roles in the progression of multiple tumors. However, the relationship between estrogen, succinate, and heme metabolism and related regulatory mechanisms remain largely unknown. In this study, we observed that the expression of aminolevulinate delta synthase 1 (ALAS1) and solute carrier family member 38 (SLC25A38) in UEC tissues is significantly higher than that in normal tissues. Further analysis showed that estrogen and succinate increased the expression of ALAS1 and SLC25A38 in uterine endometrial cancer cells (UECC), and the administration of succinate upregulated the level of the estrogen receptor (ER). Silencing nuclear receptor coactivator 1 (NCOA1) reversed the effects of estrogen and succinate via downregulation of ALAS1 expression. Additionally, exposure of UECC to heme increased cell viability and invasiveness, while silencing the NCOA1 gene weakened this effect. These findings revealed that estrogen and succinate can synergistically increase the expression of ALAS1 and SLC25A38 via the ERβ/NCOA1 axis, promoting heme accumulation and increasing the proliferative and invasive potential of UECC.
The Microbiological Burden of Short-Term Catheter Reuse in Individuals with Spinal Cord Injury: A Prospective Study
Authors: Miller Tiev , Lange Dirk , Kizhakkedathu Jayachandran N. , Yu Kai , Felix Demian , Samejima Soshi , Shackleton Claire , Malik Raza N. , Sachdeva Rahul , Walter Matthias , Krassioukov Andrei V.
Published: July 2023

Despite the risk of developing catheter-associated urinary tract infections (CAUTI), catheter reuse is common among people with spinal cord injury (SCI). This study examined the microbiological burden and catheter surface changes associated with short-term reuse. Ten individuals with chronic SCI reused their catheters over 3 days. Urine and catheter swab cultures were collected daily for analysis. Scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS) analyses were used to assess catheter surface changes. Catheter swab cultures showed no growth after 48 h (47.8%), skin flora (28.9%), mixed flora (17.8%), or bacterial growth (5.5%). Asymptomatic bacteriuria was found for most participants at baseline (n = 9) and all at follow-up (n = 10). Urine samples contained Escherichia coli (58%), Klebsiella pneumoniae (30%), Enterococcus faecalis (26%), Acinetobacter calcoaceticus–baumannii (10%), Pseudomonas aeruginosa (6%) or Proteus vulgaris (2%). Most urine cultures showed resistance to one or more antibiotics (62%). SEM images demonstrated structural damage, biofilm and/or bacteria on all reused catheter surfaces. XPS analyses also confirmed the deposition of bacterial biofilm on reused catheters. Catheter surface changes and the presence of antibiotic-resistant bacteria were evident following short-term reuse, which may increase susceptibility to CAUTI in individuals with SCI despite asymptomatic bacteriuria.
Systematic Screening of Associations between Medication Use and Risk of Neurodegenerative Diseases Using a Mendelian Randomization Approach
Authors: Wang Wenjing , Zhang Linjing , Cao Wen , Xia Kailin , Huo Junyan , Huang Tao , Fan Dongsheng
Published: July 2023

Background: Systematically assessing the causal associations between medications and neurodegenerative diseases is significant in identifying disease etiology and novel therapies. Here, we investigated the putative causal associations between 23 existing medication categories and major neurodegenerative diseases (NDs), including Alzheimer’s disease (AD), Parkinson’s disease (PD), and amyotrophic lateral sclerosis (ALS). Methods: A two-sample mendelian randomization (MR) approach was conducted. Estimates were calculated using the inverse-variance weighted (IVW) method as the main model. A sensitivity analysis and a pleiotropy analysis were performed to identify potential violations. Results: Genetically predisposition to antihypertensives (OR = 0.809, 95% CI = 0.668–0.981, p = 0.031), thyroid preparations (OR = 0.948, 95% CI = 0.909–0.988, p = 0.011), and immunosuppressants (OR = 0.879, 95% CI = 0.789–0.979, p = 0.018) was associated with a decreased risk of AD. Genetic proxies for thyroid preparations (OR = 0.934, 95% CI = 0.884–0.988, p = 0.017), immunosuppressants (OR = 0.825, 95% CI = 0.699–0.973, p = 0.022), and glucocorticoids (OR = 0.862, 95% CI = 0.756–0.983, p = 0.027) were causally associated with a decreased risk of PD. Genetically determined antithrombotic agents (OR = 1.234, 95% CI = 1.042–1.461, p = 0.015), HMG CoA reductase inhibitors (OR = 1.085, 95% CI = 1.025–1.148, p = 0.005), and salicylic acid and derivatives (OR = 1.294, 95% CI = 1.078–1.553, p = 0.006) were associated with an increased risk of ALS. Conclusions: We presented a systematic view concerning the causal associations between medications and NDs, which will promote the etiology discovery, drug repositioning and patient management for NDs.
Biomechanics of Chondrocytes and Chondrons in Healthy Conditions and Osteoarthritis: A Review of the Mechanical Characterisations at the Microscale
Authors: Pettenuzzo Sofia , Arduino Alessandro , Belluzzi Elisa , Pozzuoli Assunta , Fontanella Chiara Giulia , Ruggieri Pietro , Salomoni Valentina , Majorana Carmelo , Berardo Alice
Published: July 2023

Biomechanical studies are expanding across a variety of fields, from biomedicine to biomedical engineering. From the molecular to the system level, mechanical stimuli are crucial regulators of the development of organs and tissues, their growth and related processes such as remodelling, regeneration or disease. When dealing with cell mechanics, various experimental techniques have been developed to analyse the passive response of cells; however, cell variability and the extraction process, complex experimental procedures and different models and assumptions may affect the resulting mechanical properties. For these purposes, this review was aimed at collecting the available literature focused on experimental chondrocyte and chondron biomechanics with direct connection to their biochemical functions and activities, in order to point out important information regarding the planning of an experimental test or a comparison with the available results. In particular, this review highlighted (i) the most common experimental techniques used, (ii) the results and models adopted by different authors, (iii) a critical perspective on features that could affect the results and finally (iv) the quantification of structural and mechanical changes due to a degenerative pathology such as osteoarthritis.
Progress and Perspectives of Mid-Infrared Photoacoustic Spectroscopy for Non-Invasive Glucose Detection
Authors: Kaysir Md Rejvi , Song Jiaqi , Rassel Shazzad , Aloraynan Abdulrahman , Ban Dayan
Published: July 2023

The prevalence of diabetes is rapidly increasing worldwide and can lead to a range of severe health complications that have the potential to be life-threatening. Patients need to monitor and control blood glucose levels as it has no cure. The development of non-invasive techniques for the measurement of blood glucose based on photoacoustic spectroscopy (PAS) has advanced tremendously in the last couple of years. Among them, PAS in the mid-infrared (MIR) region shows great promise as it shows the distinct fingerprint region for glucose. However, two problems are generally encountered when it is applied to monitor real samples for in vivo measurements in this MIR spectral range: (i) low penetration depth of MIR light into the human skin, and (ii) the effect of other interfering components in blood, which affects the selectivity of the detection system. This review paper systematically describes the basics of PAS in the MIR region, along with recent developments, technical challenges, and data analysis strategies, and proposes improvements for the detection sensitivity of glucose concentration in human bodies. It also highlights the recent trends of incorporating machine learning (ML) to enhance the detection sensitivity of the overall system. With further optimization of the experimental setup and incorporation of ML, this PAS in the MIR spectral region could be a viable solution for the non-invasive measurement of blood glucose in the near future.
A Comparative Study on Cyanine Dyestuffs as Sensor Candidates for Macromolecular Crowding In Vitro and In Vivo
Authors: Koch Leon , Pollak Roland , Ebbinghaus Simon , Huber Klaus
Published: July 2023

Pseudo isocyanine chloride (PIC) has been identified in a preceding work as a sensor suited to probe macromolecular crowding both in test tubes with solutions of synthetic crowding agents and in HeLa cells as a representative of living systems. The sensing is based on a delicate response of the self-assembly pattern of PIC towards a variation in macromolecular crowding. Based on a suitable selection of criteria established in the present study, four additional cyanine dyestuffs (TDBC, S071, S2275, and PCYN) were scrutinized for their ability to act as such a sensor, and the results were compared with the corresponding performance of PIC. UV-VIS and fluorescence spectroscopy were applied to investigate the photo-physical properties of the four candidates and, if possible, light scattering was used to characterize the self-assembly of the dyestuffs in solution. Finally, HeLa cells were exposed to solutions of the most promising candidates in order to analyze their ability to infiltrate the cells and to self-assemble therein. None of the dyestuff candidates turned out to be as similarly promising in probing crowding effects in cells as PIC turned out to be. S0271 and S2275 are at least stable enough and meet the photophysical requirements necessary to act as sensors responding to changes in macromolecular crowding.
The Effect of Cued-Speech (CS) Perception on Auditory Processing in Typically Hearing (TH) Individuals Who Are Either Naïve or Experienced CS Producers
Authors: Caron Cora Jirschik , Vilain Coriandre , Schwartz Jean-Luc , Bayard Clémence , Calcus Axelle , Leybaert Jacqueline , Colin Cécile
Published: July 2023

Cued Speech (CS) is a communication system that uses manual gestures to facilitate lipreading. In this study, we investigated how CS information interacts with natural speech using Event-Related Potential (ERP) analyses in French-speaking, typically hearing adults (TH) who were either naïve or experienced CS producers. The audiovisual (AV) presentation of lipreading information elicited an amplitude attenuation of the entire N1 and P2 complex in both groups, accompanied by N1 latency facilitation in the group of CS producers. Adding CS gestures to lipread information increased the magnitude of effects observed at the N1 time window, but did not enhance P2 amplitude attenuation. Interestingly, presenting CS gestures without lipreading information yielded distinct response patterns depending on participants’ experience with the system. In the group of CS producers, AV perception of CS gestures facilitated the early stage of speech processing, while in the group of naïve participants, it elicited a latency delay at the P2 time window. These results suggest that, for experienced CS users, the perception of gestures facilitates early stages of speech processing, but when people are not familiar with the system, the perception of gestures impacts the efficiency of phonological decoding.
Association between PDE4D rs966221 and the Risk of Ischemic Stroke in Regional Chinese Populations
Authors: Wang Chunyang , Zhang Fenghe , Zhang Xiaojing , Zhang Chao , Li He
Published: July 2023

In published research that includes genome-wide association studies and meta-analyses, the phosphodiesterase 4D (PDE4D) rs966221 variant has been identified as a risk factor in ischemic stroke (IS) in the Caucasian population. Several studies have investigated the relationship between rs966221 and IS susceptibility in Chinese populations over the years but have not provided consistently conclusive results. Therefore, our team performed a new meta-analysis of 5973 IS patients and 6204 controls from qualified studies. We observed no significant link between the PDE4D rs966221 variant and IS in any of the regional Chinese populations. Thus, we performed a subgroup analysis by the geographical distribution of China. Notably, significant associations were observed between rs96622 and the susceptibility of IS in the Northeast Chinese populations (p = 1.00 × 10−4, odds ratio = 1.28, and 95% confidence interval = 1.13–1.44, I2 = 0%). However, rs966221 was not found to be correlated with IS risk in the populations of North, Central, South, and East China. Our meta-analysis demonstrated that the PDE4D rs966221 variant is significantly associated with IS risk in some regional Chinese populations.
Resuspension of Seeded Particles Containing Live Influenza A Virus in a Full-Scale Laboratory
Authors: Rawat Mahender Singh , Roberts Alan D. , Brown Deborah M. , Ferro Andrea R.
Published: July 2023

Many respiratory viruses, including influenza and SARS-CoV-2, are transmitted via the emission and inhalation of infectious respiratory aerosols in indoor environments. Resuspended particles from indoor surfaces and clothing can be a major source of airborne microbiological contaminants in indoor environments; however, it is unknown whether resuspended viruses contribute substantially to disease transmission. In this study, we investigated the resuspension via human walking activity of influenza A virus H3N2 laboratory strain, which was generated through a nebulizer into a sealed, unventilated biosafety level 2 (BSL-2) laboratory. The mean airborne viral concentrations following the resuspension events (3.7×103 viral RNA copies m−3) were two orders of magnitude lower than those following direct emission via the nebulizer (1.1×105 viral RNA copies m−3). The calculated resuspension emission factor (normalized ratio of the airborne mass to mass available for resuspension on the surface) of 10−3 was similar to reported values for 1–2 μm particles. Thus, depending on the infectious dose and viability of the virus, resuspension of settled respiratory viruses could lead to transmission, but the risk appears to be much lower than for direct respiratory emissions. To our knowledge, this is the first full-scale experimental study designed to quantify virus resuspension.
Experimental and Numerical Flexural–Torsional Performance of Thin-Walled Open-Ended Steel Vertical Pile Foundations Subjected to Lateral Loads
Authors: Pérez José Antonio , Reyes-Rodríguez Antonio Manuel , Sánchez-González Estíbaliz , Ríos José D.
Published: July 2023

This research investigates the effects of torsional moments on the mechanical behavior of thin-walled open-ended vertical pile foundations subjected to lateral wind loads. The aim of this research is to determine and quantify the errors using traditional design methods and provide more effective alternatives. The warping and torsion effect generated over the piles due to the resultant lateral load impact outside the shear center is analyzed in field tests. Complementarily, a two-dimensional finite element model based on the simple bending stress–strain state, as well as a three-dimensional finite element model considering torsional effects, were implemented and their results analyzed. Finally, a comparative analysis between the in-field lateral loading tests and the finite element model approaches was established by comparing load–displacement curves and using a non-linear Wrinkle model of the soil. Additionally, correlations between the experimental and finite element model errors for the cross-sections pile with a different torsional constant and torsional susceptibility index are shown. From the results, it has been ascertained that the slender thin-walled open-ended pile foundations are particularly sensitive to small load deviations from their center of gravity; this leads to the fact that the slenderer the load and the greater its eccentricity, the more it affects the torsion and warping of the pile. Calculation methodologies usually consider a simple in-plane bending behavior, which leads to errors between 44 and 58% in comparison with the experimental results obtained.
Biochar for Soil Carbon Sequestration: Current Knowledge, Mechanisms, and Future Perspectives
Authors: Li Simeng , Tasnady Desarae
Published: July 2023

Biochar, a sustainable solid material derived from biomass pyrolysis enriched in carbon, has emerged as a promising solution for soil carbon sequestration. This comprehensive review analyzes the current knowledge on biochar’s application in this context. It begins by examining biochar properties and production methods, highlighting its recalcitrant nature as a potential stable carbon sink. The influence of various feedstocks and pyrolysis conditions on various physicochemical properties of biochar and its soil carbon sequestration potential is explored. Mechanisms through which biochar enhances soil carbon sequestration are discussed, including its role as a physical barrier against carbon loss and its ability to promote stable soil aggregates and influence soil microorganisms. Challenges and limitations, such as variations in biochar properties and optimal application rates, are addressed, along with strategies for maximizing biochar effectiveness through amendments. The review concludes by emphasizing the importance of long-term field studies, standardized protocols, and economic assessments to support the widespread adoption of biochar for soil carbon sequestration and its potential in climate change mitigation.
Distal Humeral Replacement in Patients with Primary Bone Sarcoma: The Functional Outcome and Return to Sports
Authors: Schneider Kristian Nikolaus , Ellerbrock Moritz , Gosheger Georg , Westphal Lucia Maria , Deventer Niklas , Klingebiel Sebastian , Rickert Carolin , Theil Christoph
Published: July 2023

Distal humeral replacement (DHR) is a limb-salvage option for the endoprosthetic reconstruction of bone defects following the resection of a primary bone sarcoma. As primary bone sarcomas are only occasionally located around the distal humerus, there is a paucity of information regarding postoperative function, and patients’ resumption of sporting activities. With advances in diagnostics and in surgical and oncological treatment leading to an increased patient life expectancy and higher quality of life, patients’ functional outcome and return to sports activities are of increasing interest. Between 1997 and 2021, a total of 24 patients underwent DHR with a single-design modular implant at a tertiary sarcoma center. A total of 14 patients who died of their disease were excluded, leaving a study cohort of 10 patients, with a median age of 30 years on the day of surgery (IQR 20–37). At the last follow-up, after a median of 230 months (IQR 165–262), the median MSTS was 19 (IQR 13–24), the median TESS was 79 (IQR 66–87), the median SEV was 38% (IQR 24–53), the median TS was 6 (IQR 4–7), and the median WAS was 3 (IQR 1–8). Among the variables of gender, surgery on the dominant extremity, intraoperative nerve resection, extra-articular tumor resection, chemotherapy, radiotherapy, and revision surgeries, none were associated with a better/lower functional outcome score or return to sports activities. However, a higher level of sports performance prior to diagnosis (WAS > 10) was associated with a higher level of sports performance postoperatively (p = 0.044).
Detection of Cancer Recurrence Using Systemic Inflammatory Markers and Machine Learning after Concurrent Chemoradiotherapy for Head and Neck Cancers
Authors: So Yoon Kyoung , Kim Zero , Cheong Taek Yoon , Chung Myung Jin , Baek Chung-Hwan , Son Young-Ik , Seok Jungirl , Jung Yuh-Seog , Ahn Myung-Ju , Ahn Yong Chan , Oh Dongryul , Cho Baek Hwan , Chung Man Ki
Published: July 2023

Pretreatment values of the neutrophil-to-lymphocyte ratio (NLR) and the platelet-to-lymphocyte ratio (PLR) are well-established prognosticators in various cancers, including head and neck cancers. However, there are no studies on whether temporal changes in the NLR and PLR values after treatment are related to the development of recurrence. Therefore, in this study, we aimed to develop a deep neural network (DNN) model to discern cancer recurrence from temporal NLR and PLR values during follow-up after concurrent chemoradiotherapy (CCRT) and to evaluate the model’s performance compared with conventional machine learning (ML) models. Along with conventional ML models such as logistic regression (LR), random forest (RF), and gradient boosting (GB), the DNN model to discern recurrences was trained using a dataset of 778 consecutive patients with primary head and neck cancers who received CCRT. There were 16 input features used, including 12 laboratory values related to the NLR and the PLR. Along with the original training dataset (N = 778), data were augmented to split the training dataset (N = 900). The model performance was measured using ROC-AUC and PR-AUC values. External validation was performed using a dataset of 173 patients from an unrelated external institution. The ROC-AUC and PR-AUC values of the DNN model were 0.828 ± 0.032 and 0.663 ± 0.069, respectively, in the original training dataset, which were higher than the ROC-AUC and PR-AUC values of the LR, RF, and GB models in the original training dataset. With the recursive feature elimination (RFE) algorithm, five input features were selected. The ROC-AUC and PR-AUC values of the DNN-RFE model were higher than those of the original DNN model (0.883 ± 0.027 and 0.778 ± 0.042, respectively). The ROC-AUC and PR-AUC values of the DNN-RFE model trained with a split dataset were 0.889 ± 0.032 and 0.771 ± 0.044, respectively. In the external validation, the ROC-AUC values of the DNN-RFE model trained with the original dataset and the same model trained with the split dataset were 0.710 and 0.784, respectively. The DNN model with feature selection using the RFE algorithm showed the best performance among the ML models to discern a recurrence after CCRT in patients with head and neck cancers. Data augmentation by splitting training data was helpful for model performance. The performance of the DNN-RFE model was also validated with an external dataset.