bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of Chemical Fertilizer with Compound Microbial Fertilizer on Soil Physical Properties and Soybean Yield
Authors: Fu Chenye , Ma Weiran , Qiang Binbin , Jin Xijun , Zhang Yuxian , Wang Mengxue
Published: September 2023

Compound microbial fertilizer is a new type of environmentally friendly slow-release fertilizer that can effectively improve the physical and chemical properties of the soil, significantly improve the ecological environment, and promote the sustainable development of agriculture. In this study, we conducted a field experiment to evaluate the impact of different applications of chemical fertilizer combined with composite microbial fertilizer on soil physical properties and soybean yields at Heshan Farm, Heilongjiang Province, China, during 2021–2022. Soybean varieties “Jinyuan 55” and “Keshan 1” were treated with three treatments implemented as follows: T1 (conventional fertilization), T2 (50% N fertilizer + compound microbial fertilizer), and T3 (0 N fertilizer + compound microbial fertilizer). Compared to conventional fertilization (T1 treatment), the application of composite microbial fertilizers (T2 and T3) resulted in a decrease in soil bulk density and an increase in porosity. Notably, we observed that moderate application of the composite microbial fertilizer (T3) led to a decrease in the volume fraction of clay particles and an increase in the volume fraction of sand particles. Furthermore, all treatments exhibited high content of agglomerates larger than 5 mm at 0–20 cm. The application of composite microbial fertilizers (T2 and T3) promoted the formation of large soil agglomerates and reduced the presence of micro-agglomerates smaller than 0.25 mm. In 2021–2022, The soybean yield increased by 13.02% in the T2 treatment compared with the T1 treatment and decreased by 9.34% in the T3 treatment. We concluded that the appropriate application of compound microbial fertilizer can help protect black soil, enhance the self-repair capability of black soil, and improve soybean quality in abnormal precipitation years. These results provide an actionable basis for constructing and developing green fertilizer systems for the soybean industry.
Seasonal Dynamics and Physiological Age of Ixodid Ticks Collected from Dogs
Authors: Petrović Aleksandra , Stanić Ksenija , Popović Aleksandra , Ivanović Ivana , Supić Dejan , Marinković Dušan , Bursić Vojislava
Published: September 2023

In order to reproduce and complete life cycles, ticks have to feed on different hosts, thus participating as vectors and reservoirs in the maintenance and circulation of different pathogens. Since dogs can serve as suitable hosts for numerous tick species, the aims of this study were to determine tick species and their seasonal occurrence on pet dogs and to compare the accuracy of three indices frequently used to calculate engorged female physiological age. Ticks were collected from dogs brought to veterinary clinics. Three indices were analyzed: scutal index, alloscutal/scutal index ratio, and physiological age index. Four tick species were identified: Ixodes ricinus, Dermacentor marginatus, D. reticulatus, and Rhipicephalus sanguineus group, and the last was the most abundant. The highest number of collected ticks was in April, but two species were continuously active throughout the year. The statistical analyses distinguished the physiological age index as more precise because of lower variability. Dog owners usually ignore regular dog anti-tick treatments throughout the year, as they are not aware that ticks could be active during the winter months. Tick surveillance is unquestionably important in order to monitor and prevent the distribution of these vectors and also the diseases they transmit.
Opportunities for Regulatory Authorities to Assess Animal-Based Measures at the Slaughterhouse Using Sensor Technology and Artificial Intelligence: A Review
Authors: Voogt Annika M. , Schrijver Remco S. , Temürhan Mine , Bongers Johan H. , Sijm Dick T. H. M.
Published: September 2023

Animal-based measures (ABMs) are the preferred way to assess animal welfare. However, manual scoring of ABMs is very time-consuming during the meat inspection. Automatic scoring by using sensor technology and artificial intelligence (AI) may bring a solution. Based on review papers an overview was made of ABMs recorded at the slaughterhouse for poultry, pigs and cattle and applications of sensor technology to measure the identified ABMs. Also, relevant legislation and work instructions of the Dutch Regulatory Authority (RA) were scanned on applied ABMs. Applications of sensor technology in a research setting, on farm or at the slaughterhouse were reported for 10 of the 37 ABMs identified for poultry, 4 of 32 for cattle and 13 of 41 for pigs. Several applications are related to aspects of meat inspection. However, by European law meat inspection must be performed by an official veterinarian, although there are exceptions for the post mortem inspection of poultry. The examples in this study show that there are opportunities for using sensor technology by the RA to support the inspection and to give more insight into animal welfare risks. The lack of external validation for multiple commercially available systems is a point of attention.
Intravenous Injection of Sodium Hyaluronate Diminishes Basal Inflammatory Gene Expression in Equine Skeletal Muscle
Authors: Gregg Savannah R. , Barshick Madison R. , Johnson Sally E.
Published: September 2023

Following strenuous exercise, skeletal muscle experiences an acute inflammatory state that initiates the repair process. Systemic hyaluronic acid (HA) is injected to horses routinely as a joint anti-inflammatory. To gain insight into the effects of HA on skeletal muscle, adult Thoroughbred geldings (n = 6) were injected with a commercial HA product weekly for 3 weeks prior to performing a submaximal exercise test. Gluteal muscle (GM) biopsies were obtained before and 1 h after exercise for gene expression analysis and HA localization. The results from RNA sequencing demonstrate differences in gene expression between non-injected controls (CON; n = 6) and HA horses. Prior to exercise, HA horses contained fewer (p < 0.05) transcripts associated with leukocyte activity and cytokine production than CON. The performance of exercise resulted in the upregulation (p < 0.05) of several cytokine genes and their signaling intermediates, indicating that HA does not suppress the normal inflammatory response to exercise. The transcript abundance for marker genes of neutrophils (NCF2) and macrophages (CD163) was greater (p < 0.05) post-exercise and was unaffected by HA injection. The anti-inflammatory effects of HA on muscle are indirect as no differences (p > 0.05) in the relative amount of the macromolecule was observed between the CON and HA fiber extracellular matrix (ECM). However, exercise tended (p = 0.10) to cause an increase in ECM size suggestive of muscle damage and remodeling. The finding was supported by the increased (p < 0.05) expression of CTGF, TGFβ1, MMP9, TIMP4 and Col4A1. Collectively, the results validate HA as an anti-inflammatory aid that does not disrupt the normal post-exercise muscle repair process.
Maternal Supraphysiological Hypercholesterolemia Is Accompanied by Shifts in the Composition and Anti-Atherogenic Functions of Maternal HDL along with Maternal Cardiovascular Risk Markers at Term of Pregnancy
Authors: Cantin Claudette , Morales Andrea , Serra Ramón , Illanes Sebastián E. , Leiva Andrea
Published: September 2023

Background: Maternal physiological hypercholesterolemia (MPH) occurs in pregnancy for a proper fetal development. When cholesterol increases over the physiological range, maternal supraphysiological hypercholesterolemia (MSPH) is described, a condition underdiagnosed by a lack of evidence showing its biological and clinical relevance. Aim: To determine if MSPH associates with maternal vascular dysfunction, along with changes in the composition and function of maternal HDL leading to increased cardiovascular risk. Methods: This study included 57 women at term of pregnancy in which a lipid profile was determined. Results: Maternal total cholesterol (TC) and LDL but not HDL were increased in MSPH women. The isolated HDL from a subgroup of MSPH women had a lower protein abundance and a reduced activity of the antioxidant enzyme PON1; however, an increased antioxidant capacity compared to MPH was observed, along with higher serum levels of α-tocopherol. Moreover, HDL from a subgroup of MSPH women had a lower capacity to induce NO synthesis in endothelial cells compared to MPH. In the circulation, we observed a reduced total antioxidant capacity and augmented levels of soluble VCAM, ApoB, ApoCII, ApoCIII, IL-10, and IL-12p70, as well as the cardiovascular risk ratio ApoB/ApoAI, compared to MPH women. Conclusion: MSPH women present dysfunctional HDL and increased atherogenic cardiovascular risk factors.
Antioxidants in Male Infertility—If We Want to Get This Right We Need to Take the Bull by the Horns: A Pilot Study
Authors: Punjabi Usha , Goovaerts Ilse , Peeters Kris , De Neubourg Diane
Published: September 2023

Antioxidant therapy should be reserved for infertile patients who actually exhibit signs of oxidative stress (OS). Nevertheless, there is no consensus regarding the measure of the primary endpoint and the assay that should be used. The formation of 8-hydroxy-2′-deoxyguanosine (8-OHdG), an early marker of sperm DNA oxidation (SDO), was analyzed using flow cytometry, in men at a University hospital setup for infertility treatment. Similar to conventional semen parameters, 8-OHdG assay was validated on fresh semen samples to reduce the variability of results. SDO was associated with semen volume, sperm concentration, leucocytes and round cells, but not with age, body mass index, sperm DNA fragmentation (SDF) or OS. Whether the semen samples were normal or subnormal according to the WHO criteria, the expression of 8-OHdG was not different. Receiver operating characteristic curve analysis could discriminate two independent populations. Both SDF and SDO were independently expressed. A high SDF did not reveal a high SDO and vice versa. The thresholds for SDO have been established, but vary with the techniques used. The methodology for SDO needs to be further validated and optimized on a larger clinically defined patient population before the outcome measure is fit to monitor antioxidant therapy in male infertility.
Energy Implications of Thermal Comfort in Buildings Considering Climate Change
Authors: Sánchez-García Daniel , Bienvenido-Huertas David
Published: September 2023

Extreme weather events and rising global temperatures are signs of the urgent threat that climate change poses to our planet [...]
Epicardial Adipose Tissue Changes during Statin Administration in Relation to the Body Mass Index: A Longitudinal Cardiac CT Study
Authors: Toia Patrizia , La Grutta Ludovico , Vitabile Salvatore , Punzo Bruna , Cavaliere Carlo , Militello Carmelo , Rundo Leonardo , Matranga Domenica , Filorizzo Clarissa , Maffei Erica , Galia Massimo , Midiri Massimo , Lagalla Roberto , Saba Luca , Bossone Eduardo , Cademartiri Filippo
Published: September 2023

The epicardial adipose tissue (EAT) is the visceral fat located between the myocardium and the pericardium. We aimed to perform a longitudinal evaluation of the epicardial adipose tissue using an advanced computer-assisted approach in a population of patients undergoing Cardiac CT (CCT) during statin administration, in relation to their body mass index (BMI). We retrospectively enrolled 95 patients [mean age 62 ± 10 years; 68 males (72%) and 27 females (28%)] undergoing CCT for suspected coronary artery disease during statin administration. CCT was performed at two subsequent time points. At the second CCT, EAT showed a mean density increase (−75.59 ± 7.0 HU vs. −78.18 ± 5.3 HU, p < 0.001) and a volume decrease (130 ± 54.3 cm3 vs.142.79 ± 56.9 cm3, p < 0.001). Concerning coronary artery EAT thickness, a reduction was found at the origin of the right coronary artery (13.26 ± 5.2 mm vs. 14.94 ± 5.8, p = 0.001) and interventricular artery (8.22 ± 3.7 mm vs. 9.13 ± 3.9 mm, p = 0.001). The quartile (Q) attenuation percentage (%) distribution of EAT changed at the second CCT. The EAT % distribution changed by the BMI in Q1 (p = 0.015), Q3 (p = 0.001) and Q4 (p = 0.043) at the second CCT, but the normal-BMI and overweight/obese patients showed a similar response to statin therapy in terms of quartile distribution changes. In conclusion, statins may determine significant changes in EAT quantitative and qualitative characteristics detected by CCT; the BMI influences the EAT composition, but statins determine a similar response in quartile distribution’s variation, irrespective of the BMI.
Review on Surface Modification of SnO2 Electron Transport Layer for High-Efficiency Perovskite Solar Cells
Authors: Hoang Huy Vo Pham , Bark Chung-Wung
Published: September 2023

In the planar heterojunction perovskite solar cell (PSC) structure, among numerous contenders, tin oxide (SnO2) has been utilized, instead of TiO2, as the material for the electron transport layer (ETL) owing to its good band alignment, ultraviolet light resistance, strong charge extraction, and low photocatalytic activity. However, the morphology of the SnO2 ETL has proven to be unstable under low-temperature processing, leading to low electron extraction in PSCs. Therefore, the surface morphology must be modified to achieve high-performance PSCs. In this review, we provide an overview of the fundamental insights into how surface variations affect the ETL performance. The significance and the design rule of surface modification for an efficient SnO2 ETL, that is, the intentional alteration of the SnO2 interface, are discussed. Based on the evaluations, distinct surface engineering procedures and how they are implemented are presented. The effects of chemical and physical interactions on the properties of SnO2 are elucidated in detail; these have not been considered in previous studies. Finally, we provide an outlook on, highlight the key challenges in, and recommend future research directions for the design of the interfaces of highly efficient and stable PSCs.
Modeling of Traffic Information and Services for the Traffic Control Center in Autonomous Vehicle-Mixed Traffic Situations
Authors: Yang Dong-Hyuk , Choi Sung-Soo , Kang Yong-Shin
Published: September 2023

Achieving fully autonomous driving requires seamless collaboration between advanced autonomous driving and road infrastructure technologies. As the proportion of autonomous vehicles (AVs) increases, challenges may arise from their insufficient knowledge of the behavior of traffic objects and inability to effectively drive short distances. Therefore, traffic control centers that can proactively control these issues in real time are essential. In this study, first, the terminology is defined and the types of AV-mixed Traffic Information that a traffic control center needs to efficiently collect, store, and analyze to accommodate the coexistence of AVs and conventional vehicles are identified. Second, a generic notation for an AV-mixed Traffic Information model is defined and the results of modeling each AV-mixed Traffic Information type are presented. Third, an AV-mixed Traffic Information services model that included the names, operations, input/output messages, and relationships of all services is suggested. Finally, the importance of the service functionalities is evaluated through a survey. This study will serve as an initial guideline for the design, construction, and operation of traffic control centers and will help proactively address issues that may arise from the interaction between AVs and conventional vehicles on the road. Moreover, it contributes to identifying the types of traffic information and services that traffic control centers must provide in the era of AV-mixed traffic and suggests future directions for analysis and utilization of traffic information.
Aesthetic Experience and Popularity Ratings for Controversial and Non-Controversial Artworks Using Machine Learning Ranking
Authors: Vlachou Sofia , Panagopoulos Michail
Published: September 2023

Currently, a substantial portion of images snapped at exhibitions and galleries on social media demonstrates that aesthetic experience is not restricted to the confines of cultural institutions. The primary objective of this paper is to examine whether the content or aspect of an artwork influences the aesthetic experience of the viewer and to measure the artwork’s social media popularity. To compare controversial works of art with those whose design, qualities, or intended message are non-controversial, we first sought out controversial works. A variety of artworks were revealed on Instagram; thus, the objective was to identify a non-controversial artwork published in the same year as each controversial artwork. We adhered to the complete procedure for cleansing, standardizing, and transforming the data to ensure comparability. Popularity was measured using a ranking algorithm and quantitative approaches for the recognition and statistical measurement of emotions. In addition, the exhaustive literature survey on models of aesthetic experience revealed no link between the experience of art and its social media popularity. Considering this, we have proposed, among other things, a new framework for interacting with art that integrates these parameters. According to the findings, controversial artworks elicited stronger emotions than non-controversial artworks. Furthermore, investigations have determined the three most popular works of art in each category. Under the scrutiny of social media, these results may inspire future research on the popularity of museum artworks and the design of aesthetic experiences.
Improving Behavior Monitoring of Free-Moving Dairy Cows Using Noninvasive Wireless EEG Approach and Digital Signal Processing Techniques
Authors: Silva Ana Carolina de Sousa , Arce Aldo Ivan Céspedes , Arteaga Hubert , Sarnighausen Valeria Cristina Rodrigues , Atzingen Gustavo Voltani von , Costa Ernane José Xavier
Published: September 2023

Electroencephalography (EEG) is the most common method to access brain information. Techniques to monitor and extract brain signal characteristics in farm animals are not as developed as those for humans and laboratory animals. The objective of this study was to develop a noninvasive method for monitoring brain signals in cattle, allowing the animals to move freely, and to characterize these signals. Brain signals from six Holstein heifers that could move freely in a paddock compartment were acquired. The control group consisted of the same number of bovines, contained in a climatic chamber (restrained group). In the second step, the signals were characterized by Power Spectral Density, Short-Time Fourier Transform, and Lempel–Ziv complexity. The preliminary results revealed an optimal electrode position, referred to as POS2, which is located at the center of the frontal region of the animal’s head. This positioning allowed for attaching the electrodes to the front of the bovine’s head, resulting in the acquisition of longer artifact-free signal sections. The signals showed typical EEG frequency bands, like the bands found in humans. The Lempel–Ziv complexity values indicated that the bovine brain signals contained random and chaotic components. As expected, the signals acquired from the retained bovine group displayed sections with a larger number of artifacts due to the hot 32 degree C temperature in the climatic chamber. We present a method that helps to monitor and extract brain signal features in unrestrained bovines. The method could be applied to investigate changes in brain electrical activity during animal farming, to monitor brain pathologies, and to other situations related to animal behavior.
Classification of Severe Maternal Morbidity from Electronic Health Records Written in Spanish Using Natural Language Processing
Authors: Torres-Silva Ever A. , Rúa Santiago , Giraldo-Forero Andrés F. , Durango Maria C. , Flórez-Arango José F. , Orozco-Duque Andrés
Published: September 2023

One stepping stone for reducing the maternal mortality is to identify severe maternal morbidity (SMM) using Electronic Health Records (EHRs). We aim to develop a pipeline to represent and classify the unstructured text of maternal progress notes in eight classes according to the silver labels defined by the ICD-10 codes associated with SMM. We preprocessed the text, removing protected health information (PHI) and reducing stop words. We built different pipelines to classify the SMM by the combination of six word-embeddings schemes, three different approaches for the representation of the documents (average, clustering, and principal component analysis), and five well-known machine learning classifiers. Additionally, we implemented an algorithm for typos and misspelling adjustment based on the Levenshtein distance to the Spanish Billion Word Corpus dictionary. We analyzed 43,529 documents constructed by an average of 4.15 progress notes from 22,937 patients. The pipeline with the best performance was the one that included Word2Vec, typos and spelling adjustment, document representation by PCA, and an SVM classifier. We found that it is possible to identify conditions such as miscarriage complication or hypertensive disorders from clinical notes written in Spanish, with a true positive rate higher than 0.85. This is the first approach to classify SMM from the unstructured text contained in the maternal EHRs, which can contribute to the solution of one of the most important public health problems in the world. Future works must test other representation and classification approaches to detect the risk of SMM.
Dual Parallel Branch Fusion Network for Road Segmentation in High-Resolution Optical Remote Sensing Imagery
Authors: Gao Lin , Chen Chen
Published: September 2023

Road segmentation from high-resolution (HR) remote sensing images plays a core role in a wide range of applications. Due to the complex background of HR images, most of the current methods struggle to extract a road network correctly and completely. Furthermore, they suffer from either the loss of context information or high redundancy of details information. To alleviate these problems, we employ a dual branch dilated pyramid network (DPBFN), which enables dual-branch feature passing between two parallel paths when it is merged to a typical road extraction structure. A DPBFN consists of three parts: a residual multi-scaled dilated convolutional network branch, a transformer branch, and a fusion module. Constructing pyramid features through parallel multi-scale dilated convolution operations with multi-head attention block can enhance road features while suppressing redundant information. Both branches after fusing can solve shadow or vision occlusions and maintain the continuity of the road network, especially on a complex background. Experiments were carried out on three datasets of HR images to showcase the stable performance of the proposed method, and the results are compared with those of other methods. The OA in the three data sets of Massachusetts, Deep Globe, and GF-2 can reach more than 98.26%, 95.25%, and 95.66%, respectively, which has a significant improvement compared with the traditional CNN network. The results and explanation analysis via Grad-CAMs showcase the effective performance in accurately extracting road segments from a complex scene.
Study on Mechanical Properties of Sulfate Saline Soil Improved by CLI-Type Polymer Active Agent
Authors: Zhu Xufen , Yang Zhuoqun , Zheng Jiaqiang , Liu Jin , Bu Fan , Dai Chengjiang , Lu Yipin
Published: September 2023

Large amounts of soluble salts in a soil enhance the soil sensitivity to changes in its properties induced by changes in environmental conditions, such as easy dissolution in water and easy occurrences of salt heaving in low-temperature environments, which make the soil volume swell rapidly, leading to a series of engineering disasters. Moreover, the growth and development of surface vegetation will be inhibited due to excessive salinity, resulting in a gradual decline in the ecological functionality of the area. A polymer active agent (CLI) was selected for the ecological improvement of sulfuric acid saline soils. Triaxial compression tests and a test on the soluble salt content of the treated soil were carried out to investigate the effects of polymer active agent content and maintenance time on the mechanical properties and soluble salt content of sulfate saline soils. The results showed that the addition of CLI can improve the soil strength by increasing the cohesion of the specimen, and the improvement increases significantly with the content of CLI and the curing age. Meanwhile, the calcium ions in CLI can react with sulfate ions in sulfate-salted soils to produce calcium sulfate precipitation to alleviate soil salinization. The scanning electron microscopy (SEM) images indicated that an appropriate content of CLI (about 8%) can strengthen the soil structure through an excellent chelating ability, enhancing the strength of the soil.
Special Issue on “Research on Circadian Rhythms in Health and Disease”
Authors: Gubin Denis , Cornelissen Germaine , Stefani Oliver , Weinert Dietmar
Published: September 2023

Despite rigorous investigation of circadian rhythms in humans and animal models in the past, basic chronobiologic principles have not yet entered clinical practice [...]
Machine Learning and Deep Learning Based Model for the Detection of Rootkits Using Memory Analysis
Authors: Noor Basirah , Qadir Sana
Published: September 2023

Rootkits are malicious programs designed to conceal their activities on compromised systems, making them challenging to detect using conventional methods. As the threat landscape continually evolves, rootkits pose a serious threat by stealthily concealing malicious activities, making their early detection crucial to prevent data breaches and system compromise. A promising strategy for monitoring system activities involves analyzing volatile memory. This study proposes a rootkit detection model that combines memory analysis with Machine Learning (ML) and Deep Learning (DL) techniques. The model aims to identify suspicious patterns and behaviors associated with rootkits by analyzing the contents of a system’s volatile memory. To train the model, a diverse dataset of known rootkit samples is employed, and ML and deep learning algorithms are utilized. Through extensive experimentation and evaluation using SVM, RF, DT, k-NN, and LSTM algorithms, it is determined that SVM achieves the highest accuracy rate of 96.2%, whereas Execution Time (ET) shows that k-NN depicts the best performance, and LSTM (a DL model) shows the worst performance among the tested algorithms. This research contributes to the development of advanced defense mechanisms and enhances system security against the constantly evolving threat of rootkit attacks.
Simulation Analysis of Acoustic Radiation from Force Excitation of Foam-Filled Stiffened Sandwich Panels
Authors: Li Bin , Wang Ning , Ding Haoyang , Zheng Zilai , Kuang Wenjian , Wei Langlang
Published: September 2023

To tackle the influence of foam filling on the sound radiation performance of reinforced sandwich panels, this study employs a combined approach of experiments and simulations to investigate the factors that impact the sound radiation performance in the 1–2000 Hz mid–low frequency range. The aim is to determine how the parameters of foam impact the sound radiation performance of foam-filled reinforced sandwich panels. The results indicate that changes in the acoustic parameters of the foam have a weak effect on the frequency corresponding to the peak sound radiation power and the non-peak frequency range sound radiation performance of the sandwich panel, while significantly impacting the peak sound radiation power. Among them, porosity has the least influence on sound radiation performance, whereas static flow resistivity and tortuosity factors have a greater influence on peak sound radiation performance. The reduction in thermal characteristic length and the increase in static flow resistivity can both enhance the sound radiation performance of the panel, while the impact of tortuosity factor and viscous characteristic length on panel sound radiation performance depends on the frequency range.
Vehicle State and Road Adhesion Coefficient Joint Estimation Based on High-Order Cubature Kalman Algorithm
Authors: Quan Lingxiao , Chang Ronglei , Guo Changhong
Published: September 2023

With regard to the rear-drive in-wheel motor vehicle, this paper studies the joint estimation method for the vehicle state and road adhesion coefficient. A nonlinear seven degrees of freedom vehicle estimation model and a tire estimation model are established. A vehicle driving state estimator and a road adhesion coefficient estimator based on the generalized high-order cubature Kalman filter (GHCKF) algorithm are designed. The vehicle state estimator combines the vehicle model and the tire model to calculate the vehicle state parameters, provides the state parameters for the road adhesion coefficient estimator, and realizes the real-time estimation of the road adhesion coefficient. The exponential fading memory adaptive algorithm is used to update the measurement noise variance, and we upgrade the GHCKF to the adaptive generalized high-order cubature Kalman filter (AGHCKF), which estimates the vehicle state and road adhesion coefficient. The typical working conditions using the double GHCKF/AGHCKF estimation algorithm were simulated and analyzed. Then, high-and low-speed driving experiments based on typical working conditions were carried out. An integrated navigation system (INS), global positioning system (GPS), and real-time kinematic positioning (RTK) were used to collect the real-time data of the vehicle, and compare them with the estimated values of the joint estimator, to verify the feasibility of the vehicle-state–road-adhesion-coefficient joint estimator. We compared a high-order GHCKF algorithm, high-order improved AGHCKF algorithm, and a cubature Kalman filter (CKF) algorithm, and the simulation and experimental results show that the joint estimator using the CKF, GHCKF, and AGHCKF algorithms can realize the real-time estimation of the vehicle state and the road adhesion coefficient. The AGHCKF algorithm shows the best effectiveness and robustness of the three algorithms.
Forensic Operations for Recognizing SQLite Content (FORC): An Automated Forensic Tool for Efficient SQLite Evidence Extraction on Android Devices
Authors: Daraghmi Eman , Qaroush Zaer , Hamdi Monia , Cheikhrouhou Omar
Published: September 2023

Mobile forensics is crucial in reconstructing various everyday activities accomplished through mobile applications during an investigation. Manual analysis can be tedious, time-consuming, and error-prone. This study introduces an automated tool called Forensic Operations for Recognizing SQLite Content (FORC), specifically designed for Android, to extract Simple Query Language Table Database Lightweight (SQLite) evidence. SQLite is a library that serves as a container for mobile application data, employing a zero-configuration, serverless, self-contained, and transactional SQL database engine. While some SQLite files possess extensions such as .db, .db3, .sqlite, and .sqlit3, others have none. The lack of file extensions may result in missing evidence that could unveil the truth. The proposed tool utilizes both the file extensions and headers of the SQLite data to recognize and identify SQLite data generated or modified by a mobile application. The FORC tool’s capability was evaluated using the Chrome application as a case study, and a comparison between FORC and other tools was conducted. The results suggest that FORC significantly simplifies mobile forensic analysis.
Spectral and Energy Efficiency Trade-Off in UAV-Based Olive Irrigation Systems
Authors: Massaoudi Ayman , Berguiga Abdelwahed , Harchay Ahlem , Ben Ayed Mossaad , Belmabrouk Hafedh
Published: September 2023

Precision agriculture, also referred to as smart farming, is one of the main pillars of modern society to achieve the Sustainable Development Goals (SDGs). Precision agriculture aims to improve the quality and quantity of production while conserving scarce natural resources. Smart farming has grown in recent years thanks to the adoption of modern technologies, including artificial intelligence (AI) and the Internet of Things (IoT). In this work, we consider an irrigation system for olive orchards based on unmanned aerial vehicles (UAVs). Specifically, UAVs ensure remote sensing (RS), which offers the advantage of collecting vital information on a large temporal and spatial scale (which cannot be achieved with traditional technologies). However, UAV-based irrigation systems face tremendous challenges due to the various requirements of a powerful computing ability, battery capacity, energy efficiency, and spectral efficiency for different connected devices. This paper addresses the energy efficiency and spectral efficiency trade-off problem of UAV-based irrigation systems. We propose to adopt massive multiple input, multiple output (M-MIMO) technology to ensure wireless communication. In fact, this technology plays a significant role in future sixth-generation (6G) wireless mobile networks and has the potential to enhance the energy efficiency as well as the spectral efficiency. We design a network model with a three-layered architecture and analytically compute the achievable spectral efficiency and the energy efficiency of the studied system. Then, we numerically determine the optimal number of ground base station antennas as well as the optimal number of IoT devices that should be used to ensure the maximum energy efficiency while guaranteeing a high spectral efficiency. The numerical results prove that the proposed UAV-based irrigation system outperforms conventional systems and demonstrate that the best spectral and energy efficiency trade-off is obtained by using the M-MMSE combiner.
Structural Assessment of Historical Stone Bridges with the Finite Element Method under Dynamic Effects of Arch Shape: The Antik Iscehisar Bridge
Authors: Karalar Memduh , Çufalı Gülşah
Published: September 2023

In this study, the effect of the variation of the arch form in thickness and height on the bridge was investigated as a numerical analysis. For this purpose, the historic Antik Iscehisar Bridge located in the Iscehisar district of Afyonkarahisar in the Aegean Region was elected as a numerical application. The bridge was subjected to its own weight and moving load as a static analysis. For dynamic analysis, the effect of 10 different fault movements with historical character obtained from The Pacific Earthquake Engineering Research Center (PEER) on the bridge was investigated. The areas of principal stress and deformation resulting from the applied analyses were determined. Contour diagrams, tables, and charts were given in a comparative manner based on the results of the analysis applied to the bridge. At the end of the analysis, it was observed that the displacements decreased as the arch thickness increased under its own weight in the bridge. In addition, under the influence of live loads and earthquakes, it was observed that the displacements decrease as the arch thickness increases. A seismic reliability assessment was made using the performance criteria provided in this study. If the security level is below what it should be, reinforcement applications can be designed. Accordingly, future maintenance and monitoring planning can be made.
Free Vibration Analysis of Elastically Restrained Tapered Beams with Concentrated Mass and Axial Force
Authors: Lee Jung Woo
Published: September 2023

This study proposes a new numerical method for the free vibration analysis of elastically restrained tapered Rayleigh beams with concentrated mass and axial force. The beam model had elastic support, concentrated mass at both ends, and axial force at the right end. The elastic supports were modeled as translational and rotational springs. The shear force and bending moment were determined under the assumption that the sum of the forces at arbitrary positions and the joint between the beam and elastic supports always becomes zero. Therefore, a frequency determinant is established considering the free-free end condition at both ends, but various boundary conditions were constructed by adjusting the values of the elastic springs in the frequency equation. This assumption simplified the deduction procedure, and the method’s efficiency was demonstrated through various comparisons. In particular, the value of compressive loading at which the first natural frequency vanished was investigated by considering the taper ratio based on the relationship between the elastic support and compressive loading. The analyzed results can be adopted as benchmark solutions for other approaches. The frequency determinant employs the transfer matrix method; however, numerical methods can easily be utilized in other approaches.
Service Recommendation of Industrial Software Components Based on Explicit and Implicit Higher-Order Feature Interactions and Attentional Factorization Machines
Authors: Xu Ke , Wang Tao , Cheng Lianglun
Published: September 2023

In the context of the rapid advancement of the Industrial Internet and Urban Internet, a crucial trend is emerging in the realization of unified, service-oriented, and componentized encapsulation of IT and OT heterogeneous entities underpinned by a service-oriented architecture. This is pivotal for achieving componentized construction and development of extensive industrial software systems. In addressing the diverse demands of application tasks, the efficient and precise recommendation of service components has emerged as a pivotal concern. Existing recommendation models either focus solely on low-order interactions or emphasize high-order interactions, disregarding the distinction between implicit and explicit aspects within high-order interactions as well as the integration of high-order and low-order interactions. This oversight leads to subpar accuracy in recommendations. Real-world data exhibit intricate structures and nonlinearity. In practical applications, different interaction components exhibit varying predictive capabilities. Therefore, in this paper we propose an EIAFM model that fuses explicit and implicit higher-order feature interactions and introduce an attention mechanism to identify which low-level feature interactions contribute more significantly to the prediction results. This approach leads to increased interpretability, combining both generalization and memory capabilities. Through comprehensive experiments on authentic datasets that align with the characteristics of the Service Recommendation of Industrial Software Components problem, we demonstrate that the EIAFM model excels compared to other cutting-edge models in terms of recommendation effectiveness, with the evaluation metrics for the AUC and log-loss reaching values of 0.9281 and 0.3476, respectively.
Impact of Economic and Environmental Factors on O3 Concentrations in the Yangtze River Delta Region of China
Authors: Hong Lei , Hou Xuewei , Liu Dong , Zou Changxin
Published: September 2023

The concentration of atmospheric ozone (O3) pollution is showing a rapid growing tendency, and O3 pollution has become one of the bottleneck issues that restrict the continuous improvement of air quality in China. In this study, we first identified the primary factors based on the source apportionment of O3, then used factor analysis to divide these selected factors into economic and environmental categories. The geographical detector model was used to analyze the impact of factors and their interactions on O3 concentration in 41 cities in the Yangtze River Delta (YRD) region in 2020. The results showed that forest coverage ranked first among all the detected factors, suggesting a strong relationship between the regional O3 concentration and forest coverage. The driving factors of economic activity were ranked as follows: actual utilization of foreign capital (0.400) > gross domestic product (GDP) per capita (0.387) > proportion of tertiary industry (0.360) > urbanization rate (0.327) > per capita consumption expenditure (0.194) > research and development (R&D) of full-time equivalents of industrial enterprises above designated size (0.182) > number of industrial enterprises (0.126). The interaction between any two factors enhanced their influence on O3 concentration more than any single factor, indicating that the variability of regional O3 concentration was an outcome of a combination of multiple factors. This study could provide recommendations for the prevention and control of O3 pollution and the development of ecological integration in the YRD region.
Assessing the Cooling Potential of Tailing Piles for Urban Heat Mitigation in Germany’s Ruhr Metropolitan Area—A Case Study of the Rungenberg in Gelsenkrichen
Authors: Glocke Patricia , Scholz Tobias , Grudzielanek A. Martina
Published: September 2023

Elevated air temperatures in cities with potential negative effects on, e.g., residents are a major challenge for urban planning. Open green spaces on hills where at night air can cool and drain into residential areas are of great importance to ameliorate the heat load in urban areas. In the Ruhr Metropolitan Region in Germany, tailing piles from the former coal mining industry offer a previously neglected potential for cooling neighbourhoods. The genesis and drainage of cold air on tailing piles have not been extensively investigated so far. Tailing piles are often located in or nearby residential areas and are exposed as open spaces, where cold air can build up and drain into the surrounding neighbourhoods due to their slopes. In the present study, the genesis of cold air and the cold air drainage are empirically investigated using thermal infrared imagery and air temperature measurements during one night in 2019 at the Rungenberg tailing pile in Gelsenkirchen. Furthermore, the cooling effect on the adjacent residential area, Schüngelberg, was studied. The results indicate that cold air builds up at Rungenberg and drains into Schüngelberg. However, the cold air flow into the residential area was blocked by a brick wall located at the foot of the Rungenberg tailing pile. More awareness should be given to the cooling potential of tailing piles, and urban planners should improve this cooling potential by keeping tailing piles open and removing barriers located in the drainage pathways in order to alleviate urban heat.
The Characteristics of the Abnormal Day-to-Day TEC Variation above East Asian Region
Authors: Su Fanfan , Yang Jian , Hu Liangchen , Zhu Fuying
Published: September 2023

We investigate the abnormal day-to-day variability of total electron content (TEC) over 60 Global Navigation Satellite System (GNSS) stations above the East Asian region from 2012 to 2018 and find that the positive anomalies occur more frequently at the middle latitude at about LT 14–20 and occur frequently around 28° N at about LT 22–00. The negative anomalies occur more frequently at the middle latitude at LT 10–02, and they obviously occur less frequently at about 15° N~30° N and LT 08–12, and occur less frequently near about 22° N~30° N and LT 14–18. The quantities of positive anomalies and negative anomalies are comparable. The direction of moving anomalies is from east to west in a zonal direction in all conditions. The moving speeds of anomalies are around 15~19 degrees per hour in the zonal direction and seem to grow as the latitude increases. TEC anomalies occur in 22.1% of temporal bins before large earthquakes within seven days and occur in 24% of temporal bins in the interval, which is within one day before and three days later than the main phase of geomagnetic storms. Further work is necessary to determine the sources of these anomalies.
Insights into COVID-19: Perspectives on Drug Remedies and Host Cell Responses
Authors: Awad Ahmed M. , Hansen Kamryn , Del Rio Diana , Flores Derek , Barghash Reham F. , Kakkola Laura , Julkunen Ilkka , Awad Kareem
Published: September 2023

In light of the COVID-19 global pandemic caused by SARS-CoV-2, ongoing research has centered on minimizing viral spread either by stopping viral entry or inhibiting viral replication. Repurposing antiviral drugs, typically nucleoside analogs, has proven successful at inhibiting virus replication. This review summarizes current information regarding coronavirus classification and characterization and presents the broad clinical consequences of SARS-CoV-2 activation of the angiotensin-converting enzyme 2 (ACE2) receptor expressed in different human cell types. It provides publicly available knowledge on the chemical nature of proposed therapeutics and their target biomolecules to assist in the identification of potentially new drugs for the treatment of SARS-CoV-2 infection.
Autophagy and Inflammation: Regulatory Roles in Viral Infections
Authors: Chen Li , Yang Limin , Li Yingyu , Liu Tianrun , Yang Bolun , Liu Lei , Wu Rui
Published: September 2023

Autophagy is a highly conserved intracellular degradation pathway in eukaryotic organisms, playing an adaptive role in various pathophysiological processes throughout evolution. Inflammation is the immune system’s response to external stimuli and tissue damage. However, persistent inflammatory reactions can lead to a range of inflammatory diseases and cancers. The interaction between autophagy and inflammation is particularly evident during viral infections. As a crucial regulator of inflammation, autophagy can either promote or inhibit the occurrence of inflammatory responses. In turn, inflammation can establish negative feedback loops by modulating autophagy to suppress excessive inflammatory reactions. This interaction is pivotal in the pathogenesis of viral diseases. Therefore, elucidating the regulatory roles of autophagy and inflammation in viral infections will significantly enhance our understanding of the mechanisms underlying related diseases. Furthermore, it will provide new insights and theoretical foundations for disease prevention, treatment, and drug development.
In Vitro and In Vivo Chaperone Effect of (R)-2-amino-6-(1R, 2S)-1,2-dihydroxypropyl)-5,6,7,8-tetrahydropterin-4(3H)-one on the C1473G Mutant Tryptophan Hydroxylase 2
Authors: Arefieva Alla B. , Komleva Polina D. , Naumenko Vladimir S. , Khotskin Nikita V. , Kulikov Alexander V.
Published: September 2023

Tryptophan hydroxylase 2 (TPH2) is the key and rate-limiting enzyme of serotonin (5-HT) synthesis in the mammalian brain. The 1473G mutation in the Tph2 gene decreases TPH2 activity in the mouse brain by twofold. (R)-2-amino-6-(1R, 2S)-1,2-dihydroxypropyl)-5,6,7,8-tetrahydropterin-4(3H)-one (BH4) is a pharmacological chaperone for aromatic amino acid hydroxylases. In the present study, chaperone effects of BH4 on the mutant C1473G TPH2 were investigated in vitro and in vivo. In vitro BH4 increased the thermal stability (T50 value) of mutant and wild-type TPH2 molecules. At the same time, neither chronic (twice per day for 7 days) intraperitoneal injection of 48.3 mg/kg of BH4 nor a single intraventricular administration of 60 μg of the drug altered the mutant TPH2 activity in the brain of Balb/c mice. This result indicates that although BH4 shows a chaperone effect in vitro, it is unable to increase the activity of mutant TPH2 in vivo.