bluuebunny/crossref_metadata_2025 huggingface dataset:
Genetic Biofortification of Winter Wheat with Selenium (Se)
Authors: Sunic Katarina , Spanic Valentina
Published: July 2024

Wheat is one of the three most important cereals in the world, along with rice and maize. It serves as the primary food and source of energy for about 30–40% of the world’s population. However, the low levels of micronutrients in wheat grains can lead to deficiencies of those micronutrients in people whose dietary habits are mostly based on cereals such as wheat. Apart from iron (Fe) and zinc (Zn), a lack of selenium (Se) is also one of the biggest problems in the world. The essentiality of Se has been confirmed for all animals and humans, and the lack of this micronutrient can cause serious health issues. Wheat dominates the world’s cereal production, so it is one of the best plants for biofortification. Due to the fact that agronomic biofortification is not an economical or environmentally acceptable approach, genetic improvement of cereals such as wheat for the enhanced content of micronutrients in the grain represents the most efficient biofortification approach.
Adsorption of Glyphosate in Water Using Iron-Based Water Treatment Residuals Derived from Drinking Water Treatment Plants
Authors: Qiu Fuguo , Li Chaoran , Wang Shunxi , Li Shuang
Published: July 2024

Glyphosate, a broad-spectrum herbicide, poses a potential threat to human health and the ecosystem due to its toxicity. In this study, iron-based water treatment residuals (Fe-WTRs) were employed for glyphosate removal. The adsorption kinetics, isotherms, and thermodynamics, as well as the effects of pH, Fe-WTR particle size, and temperature, were explored. The results show that Fe-WTRs are an effective adsorbent for glyphosate adsorption, and the maximum uptake capacity was recorded as 30.25 mg/g. The Fe-WTR surface was positively charged, and low-valent iron dominated under acidic conditions, favoring glyphosate adsorption. Furthermore, smaller Fe-WTR particles (<0.125 mm) showed a faster absorption rate and 20% higher adsorption capacity than larger particles (2–5 mm). The kinetic analysis indicated that the adsorption process exhibits a two-step profile, conforming to the pseudo-second-order model, and the thermodynamic analysis indicated that it is a spontaneous, endothermic, and entropy-driven reaction. Finally, the Fourier transform infrared spectral analysis revealed that this process is mainly associated with the formation of metal phosphate through the ligand exchange of the phosphate groups of glyphosates with the hydroxyl groups of iron present in Fe-WTRs. In this study, we demonstrated the potential of Fe-WTRs as a cost-effective and efficient adsorbent for glyphosate removal.
Pressure Transient and Production Analysis of Fractured Vertical Wells in Tight Sand Gas Reservoirs Considering Threshold Pressure Gradient, Phase-Change Phenomenon, and Stress Sensitivity
Authors: Tian Liqiang , Tan Zhongjian , Zhou Daoxi , Quan Hang , Zhao Hongxu , Zhao Hongtao , Li Chengyong
Published: July 2024

The productivity and pressure response of the tight sand gas wells are influenced by multiple flow mechanisms, such as threshold pressure gradient, phase-change phenomena, and stress sensitivity. Understanding the sensitivity of these factors is crucial for the effective development of tight sand gas reservoirs. This study aims to clarify the sensitivity of various factors affecting the productivity and pressure response of tight sand gas wells. Based on the percolation theory of tight sand gas reservoirs, we considered stress sensitivity, threshold pressure gradient, and phase-change phenomena to derive an unsteady mathematical model of a fractured well with an infinite boundary, and a point source solution was obtained. The proposed model was solved using series function properties, variable substitution, perturbation technique, Poisson superposition formula, Laplace transform, and numerical inversion. The influence of several important parameters on pressure response and productivity is discussed in detail. The results show that the threshold pressure gradient, stress sensitivity, and skin factor significantly impact gas well production and pressure response, while the wellbore storage effect and phase-change effect primarily affect the initial production and pressure response, having little effect on the cumulative gas production. The proposed model can estimate the influence of the threshold pressure gradient and stress sensitivity on productivity and pressure, providing a guide for the development of technical measures for fractured wells in tight sand gas reservoirs.
Optimization Operation of Power Systems with Thermal Units and Energy Storage Considering Lifetime Loss and Thermal Units Deep Peaking
Authors: Meng Yichao , Cui Zhengpai , Cao Zheng , Yao Dong , Chen Shijia , Li Na
Published: July 2024

Deep peak shaving achieved through the integration of energy storage and thermal power units is a primary approach to enhance the peak shaving capability of a system. However, current research often tends to be overly optimistic in estimating the operational lifespan of energy storage and lacks clear quantification of the cost changes associated with system peak shaving. This study proposes an optimized operation model for the joint operation of thermal power and energy storage while considering the lifespan degradation of energy storage and the deep peak shaving of thermal power. This model measures the cost changes due to the participation of energy storage in thermal power unit peaking. It is able to reflect the value of economic externalities of energy storage in the power system and has a positive reference effect on energy storage investment planning and energy storage subsidy pricing. First, an energy storage lifespan degradation model based on equivalent cycle counts is constructed, along with a thermal power unit peak shaving cost model based on output fluctuations. Second, an optimized joint operation model is developed. Finally, the impact of changes in energy storage capacity and renewable energy output on the system peak shaving costs and energy storage lifespan is recorded. Simulation experiments are conducted based on actual operational parameters, and the results demonstrate that the participation of energy storage in deep peak shaving can indeed effectively reduce system peak shaving costs. Additionally, the actual operational lifespan of energy storage is significantly lower than the floating lifespan.
On the Feasibility of Deep Geothermal Wells Using Numerical Reservoir Simulation
Authors: Nassereddine Ali , Zerpa Luis E.
Published: July 2024

This study examines the geothermal energy extraction potential from the basement rock within the Denver–Julesburg Basin, focusing on the flow performance and heat extraction efficiency of different geothermal well configurations. It specifically compares U-shaped, V-shaped, inclined V-shaped, and pipe-in-pipe configurations against enhanced geothermal system setups. Through numerical modeling, we evaluated the thermal behavior of these systems under various operational scenarios and fracture conditions. The results suggest that while closed-loop systems offer moderate temperature increases, Enhanced geothermal system configurations show substantial potential for high-temperature extraction. This underscores the importance of evaluating well configurations in complex geological settings. The insights from this study aid in strategic geothermal energy planning and development, marking significant advancements in geothermal technology and setting a foundation for future explorations and optimizations.
Recent Progress in Poly (Lactic-co-Glycolic Acid)-Based Biodegradable Drug Delivery Carriers for Pain Management
Authors: Liang Tao , Gao Jingjing , Feng Ruiquan , Zheng Yu , Tian Kewei , Chen Jianer , Xu Xiaoling
Published: July 2024

Pain, a prevalent clinical symptom, significantly demands attention in the current public health system due to its profound impact on patients’ quality of life, daily activities, and economic circumstances. Despite being a pervasive issue, many forms of pain remain ineffectively addressed, hence posing an enormous burden on patients. Pharmaceutical treatments, the first-line approach for various forms of pain, continue to face considerable challenges due to their limited efficacy, lack of long-lasting effects, and adverse side effects. In recent years, the rapid advancements in science and technology, especially the incorporation of micro and nano technologies across various domains, have accelerated the development of novel therapeutics. This review underscores the merits and drawbacks of different pharmacological strategies for pain management. It focuses on the research progress and applications of poly (lactic-co-glycolic acid)(PLGA) as drug delivery carriers, elucidating their potential therapeutic influence over pain management. The review concludes with a thorough summary of current research outcomes and limitations, a discussion of potential clinical transformations, and projections for future pain management research and effective care strategies.
The Evolving Technological Framework and Emerging Trends in Electrical Intelligence within Nuclear Power Facilities
Authors: Sun Yao , Wang Zhijian , Huang Yao , Zhao Jie , Wang Bo , Dong Xuzhu , Wang Chenhao
Published: July 2024

This paper thoroughly explores the feasibility of integrating a variety of intelligent electrical equipment and smart maintenance technologies within nuclear power plants to enhance the currently limited level of intelligence of these systems and better support operational and maintenance tasks. Initially, this paper outlines the demands and challenges of intelligent electrical systems in nuclear power plants, highlighting the current state of development of intelligent electrical systems, including new applications of artificial intelligence and big data technologies in power grid companies, such as intelligent defect recognition through image recognition, intelligence-assisted inspections, and intelligent production commands. This paper then provides a detailed introduction to the architecture of intelligent electrical equipment, encompassing the smart electrical equipment layer, the smart control system layer, and the cloud platform layer. It discusses the intelligentization of medium- and low-voltage electrical equipment, such as smart circuit breakers, smart switchgear, and low-voltage distribution systems, emphasizing the importance of intelligentization in improving the safety, reliability, and maintenance efficiency of medium- and low-voltage distribution equipment in nuclear power plants. Furthermore, this paper addresses issues in the intelligentization of nuclear power plant electrical systems, such as information silos, the inefficiency of traditional manual inspection processes, and the lack of comprehensive intelligent design and evaluation standards, proposing corresponding solutions. Additionally, this paper presents the trends in intelligent operation and maintenance technology and applications, including primary and secondary fusion technology, intelligent patrol system architecture, intelligent inspection based on non-destructive testing, and a comprehensive solution based on inspection robots. The application of these technologies aids in achieving automated inspection, real-time monitoring, and the intelligent diagnosis of electrical equipment in nuclear power plants. Finally, this paper proposes basic principles for the development of intelligent electrical systems in nuclear power plants, including intelligent architecture, the evolutionary path, and phased goals and key technologies. It emphasizes the gradual transition from automation to digitization and then to intelligentization and presents a specific implementation plan for the intelligentization of the electrical systems in nuclear power plants. This paper concludes with a summary of short-term and long-term goals for improving the performance of nuclear power plant electrical systems through intelligent technologies and prospects for the application of intelligent technologies in the operation and maintenance of nuclear power plants in the future.
Recent Advances on Jamming and Spoofing Detection in GNSS
Authors: Radoš Katarina , Brkić Marta , Begušić Dinko
Published: July 2024

Increased interest in the development and integration of navigation and positioning services into a wide range of receivers makes them susceptible to a variety of security attacks such as Global Navigation Satellite Systems (GNSS) jamming and spoofing attacks. The availability of low-cost devices including software-defined radios (SDRs) provides a wide accessibility of affordable platforms that can be used to perform these attacks. Early detection of jamming and spoofing interferences is essential for mitigation and avoidance of service degradation. For these reasons, the development of efficient detection methods has become an important research topic and a number of effective methods has been reported in the literature. This survey offers the reader a comprehensive and systematic review of methods for detection of GNSS jamming and spoofing interferences. The categorization and classification of selected methods according to specific parameters and features is provided with a focus on recent advances in the field. Although many different detection methods have been reported, significant research efforts toward developing new and more efficient methods remain ongoing. These efforts are driven by the rapid development and increased number of attacks that pose high-security risks. The presented review of GNSS jamming and spoofing detection methods may be used for the selection of the most appropriate solution for specific purposes and constraints and also to provide a reference for future research.
Enhancing Monitoring Performance: A Microservices Approach to Monitoring with Spyware Techniques and Prediction Models
Authors: Rossetto Anubis Graciela de Moraes , Noetzold Darlan , Silva Luis Augusto , Leithardt Valderi Reis Quietinho
Published: July 2024

In today’s digital landscape, organizations face significant challenges, including sensitive data leaks and the proliferation of hate speech, both of which can lead to severe consequences such as financial losses, reputational damage, and psychological impacts on employees. This work considers a comprehensive solution using a microservices architecture to monitor computer usage within organizations effectively. The approach incorporates spyware techniques to capture data from employee computers and a web application for alert management. The system detects data leaks, suspicious behaviors, and hate speech through efficient data capture and predictive modeling. Therefore, this paper presents a comparative performance analysis between Spring Boot and Quarkus, focusing on objective metrics and quantitative statistics. By utilizing recognized tools and benchmarks in the computer science community, the study provides an in-depth understanding of the performance differences between these two platforms. The implementation of Quarkus over Spring Boot demonstrated substantial improvements: memory usage was reduced by up to 80% and CPU usage by 95%, and system uptime decreased by 119%. This solution offers a robust framework for enhancing organizational security and mitigating potential threats through proactive monitoring and predictive analysis while also guiding developers and software architects in making informed technological choices.
Cell–Electrode Models for Impedance Analysis of Epithelial and Endothelial Monolayers Cultured on Microelectrodes
Authors: Chiu Wei-Chih , Chen Wei-Ling , Lai Yi-Ting , Hung Yu-Han , Lo Chun-Min
Published: July 2024

Electric cell–substrate impedance sensing has been used to measure transepithelial and transendothelial impedances of cultured cell layers and extract cell parameters such as junctional resistance, cell–substrate separation, and membrane capacitance. Previously, a three-path cell–electrode model comprising two transcellular pathways and one paracellular pathway was developed for the impedance analysis of MDCK cells. By ignoring the resistances of the lateral intercellular spaces, we develop a simplified three-path model for the impedance analysis of epithelial cells and solve the model equations in a closed form. The calculated impedance values obtained from this simplified cell–electrode model at frequencies ranging from 31.25 Hz to 100 kHz agree well with the experimental data obtained from MDCK and OVCA429 cells. We also describe how the change in each model-fitting parameter influences the electrical impedance spectra of MDCK cell layers. By assuming that the junctional resistance is much smaller than the specific impedance through the lateral cell membrane, the simplified three-path model reduces to a two-path model, which can be used for the impedance analysis of endothelial cells and other disk-shaped cells with low junctional resistances. The measured impedance spectra of HUVEC and HaCaT cell monolayers nearly coincide with the impedance data calculated from the two-path model.
Estimation of Prediction Intervals for Performance Assessment of Building Using Machine Learning
Authors: Shabbir Khurram , Umair Muhammad , Sim Sung-Han , Ali Usman , Noureldin Mohamed
Published: July 2024

This study utilizes artificial neural networks (ANN) to estimate prediction intervals (PI) for seismic performance assessment of buildings subjected to long-term ground motion. To address the uncertainty quantification in structural health monitoring (SHM), the quality-driven lower upper bound estimation (QD-LUBE) has been opted for global probabilistic assessment of damage at local and global levels, unlike traditional methods. A distribution-free machine learning model has been adopted for enhanced reliability in quantifying uncertainty and ensuring robustness in post-earthquake probabilistic assessments and early warning systems. The distribution-free machine learning model is capable of quantifying uncertainty with high accuracy as compared to previous methods such as the bootstrap method, etc. This research demonstrates the efficacy of the QD-LUBE method in complex seismic risk assessment scenarios, thereby contributing significant enhancement in building resilience and disaster management strategies. This study also validates the findings through fragility curve analysis, offering comprehensive insights into structural damage assessment and mitigation strategies.
Single-Track Magnetic Tape Absolute Position Sensor with Self-Adaptivity
Authors: Kántor Zoltán , Szabó Attila
Published: July 2024

In this study, we demonstrate a single-track magnetic code tape-based absolute position sensor system. Unlike traditional dual-track systems, our method simplifies manufacturing and avoids crosstalk between tracks, offering higher tolerance to alignment errors. The sensing system employs an array of magnetic field sensing elements that recognize the bit sequence encoded on the tape. This approach allows for accurate position determination even when the number of sensing elements is fewer than the number of bits covered, and without the need for specific spacing between sensing elements and bit length. We demonstrate the system’s ability to learn and adapt to various magnetic code patterns, including those that are irregular or have been altered. Our method can identify and localize the sensed magnetic field pattern directly within a self-learned magnetic field map, providing robust performance in diverse conditions. This self-adaptive capability enhances operational safety and reliability, as the system can continue functioning even when the magnetic tape is misaligned or has undergone changes.
Cautious Gait during Navigational Tasks in People with Hemiparesis: An Observational Study
Authors: Le Roy Albane , Dubois Fabien , Roche Nicolas , Brunel Helena , Bonnyaud Céline
Published: July 2024

Locomotor and balance disorders are major limitations for subjects with hemiparesis. The Timed Up and Go (TUG) test is a complex navigational task involving oriented walking and obstacle circumvention. We hypothesized that subjects with hemiparesis adopt a cautious gait during complex locomotor tasks. The primary aim was to compare spatio-temporal gait parameters, indicators of cautious gait, between the locomotor subtasks of the TUG (Go, Turn, Return) and a Straight-line walk in people with hemiparesis. Our secondary aim was to analyze the relationships between TUG performance and balance measures, compare spatio-temporal gait parameters between fallers and non-fallers, and identify the biomechanical determinants of TUG performance. Biomechanical parameters during the TUG and Straight-line walk were analyzed using a motion capture system. A repeated measures ANOVA and two stepwise ascending multiple regressions (with performance variables and biomechanical variables) were conducted. Gait speed, step length, and % single support phase (SSP) of the 29 participants were reduced during Turn compared to Go and Return and the Straight-line walk, and step width and % double support phase were increased. TUG performance was related to several balance measures. Turn performance (R2 = 63%) and Turn trajectory deviation followed by % SSP on the paretic side and the vertical center of mass velocity during Go (R2 = 71%) determined TUG performance time. People with hemiparesis adopt a cautious gait during complex navigation at the expense of performance.
Displacement Assay in a Polythiophene Sensor System Based on Supramacromolecuar Disassembly-Caused Emission Quenching
Authors: Minamiki Tsukuru , Esaka Ryosuke , Kurita Ryoji
Published: July 2024

Exploring new methodologies for simple and on-demand methods of manipulating the emission and sensing ability of fluorescence sensor devices with solid-state emission molecular systems is important for realizing on-site sensing platforms. In this regard, although conjugated polymers (CPs) are some of the best candidates for preparing molecular sensor devices owing to their luminescent and molecular recognition properties, the development of CP-based sensor devices is still in its early stages. In this study, we herein propose a novel strategy for preparing a chemical stimuli-responsive solid-state emission system based on supramacromolecular assembly-induced emission enhancement (SmAIEE). The system was spontaneously developed by mixing only the component polymers (i.e., polythiophene and a transient cross-linking polymer). The proposed strategy can be applied to the facile preparation of molecular sensor devices. The analyte-induced fluorescent response of polythiophene originated from the dynamic displacement of the transient cross-linker in the polythiophene ensemble and the generation of the polythiophene–analyte complex. Our successful demonstration of the spontaneous preparation of the fluorescence sensor system by mixing two component polymers could lead to the development of on-site molecular analyzers including the determination of multiple analytes.
Moho Imaging with Fiber Borehole Strainmeters Based on Ambient Noise Autocorrelation
Authors: Qi Guoheng , Huang Wenzhu , Pan Xinpeng , Zhang Wentao , Zhang Guanxin
Published: July 2024

Moho tomography is important for studying the deep Earth structure and geodynamics, and fiber borehole strainmeters are broadband, low-noise, and attractive tools for seismic observation. Recently, many studies have shown that fiber optic seismic sensors can be used for subsurface structure imaging based on ambient noise cross-correlation, similar to conventional geophones. However, this array-dependent cross-correlation method is not suitable for fiber borehole strainmeters. Here, we developed a Moho imaging scheme for the characteristics of fiber borehole strainmeters based on ambient noise autocorrelation. S-wave reflection signals were extracted from the ambient noise through a series of processing steps, including phase autocorrelation (PAC), phase-weighted stacking (PWS), etc. Subsequently, the time-to-depth conversion crustal thickness beneath the station was calculated. We applied our scheme to continuous four-component recordings from four fiber borehole strainmeters in Lu’an, Anhui Province, China. The obtained Moho depth was consistent with the previous research results. Our work shows that this method is suitable for Moho imaging with fiber borehole strainmeters without relying on the number of stations.
Network Slicing in 6G: A Strategic Framework for IoT in Smart Cities
Authors: Alwakeel Ahmed M. , Alnaim Abdulrahman K.
Published: July 2024

The emergence of 6G communication technologies brings both opportunities and challenges for the Internet of Things (IoT) in smart cities. In this paper, we introduce an advanced network slicing framework designed to meet the complex demands of 6G smart cities’ IoT deployments. The framework development follows a detailed methodology that encompasses requirement analysis, metric formulation, constraint specification, objective setting, mathematical modeling, configuration optimization, performance evaluation, parameter tuning, and validation of the final design. Our evaluations demonstrate the framework’s high efficiency, evidenced by low round-trip time (RTT), minimal packet loss, increased availability, and enhanced throughput. Notably, the framework scales effectively, managing multiple connections simultaneously without compromising resource efficiency. Enhanced security is achieved through robust features such as 256-bit encryption and a high rate of authentication success. The discussion elaborates on these findings, underscoring the framework’s impressive performance, scalability, and security capabilities.
Nucleic Acid Target Sensing Using a Vibrating Sharp-Tip Capillary and Digital Droplet Loop-Mediated Isothermal Amplification (ddLAMP)
Authors: Fike Bethany J. , Curtin Kathrine , Li Peng
Published: July 2024

Nucleic acid tests are key tools for the detection and diagnosis of many diseases. In many cases, the amplification of the nucleic acids is required to reach a detectable level. To make nucleic acid amplification tests more accessible to a point-of-care (POC) setting, isothermal amplification can be performed with a simple heating source. Although these tests are being performed in bulk reactions, the quantification is not as accurate as it would be with digital amplification. Here, we introduce the use of the vibrating sharp-tip capillary for a simple and portable system for tunable on-demand droplet generation. Because of the large range of droplet sizes possible and the tunability of the vibrating sharp-tip capillary, a high dynamic range (~2 to 6000 copies/µL) digital droplet loop-mediated isothermal amplification (ddLAMP) system has been developed. It was also noted that by changing the type of capillary on the vibrating sharp-tip capillary, the same mechanism can be used for simple and portable DNA fragmentation. With the incorporation of these elements, the present work paves the way for achieving digital nucleic acid tests in a POC setting with limited resources.
A Retinal Vessel Segmentation Method Based on the Sharpness-Aware Minimization Model
Authors: Mariam Iqra , Xue Xiaorong , Gadson Kaleb
Published: July 2024

Retinal vessel segmentation is crucial for diagnosing and monitoring various eye diseases such as diabetic retinopathy, glaucoma, and hypertension. In this study, we examine how sharpness-aware minimization (SAM) can improve RF-UNet’s generalization performance. RF-UNet is a novel model for retinal vessel segmentation. We focused our experiments on the digital retinal images for vessel extraction (DRIVE) dataset, which is a benchmark for retinal vessel segmentation, and our test results show that adding SAM to the training procedure leads to notable improvements. Compared to the non-SAM model (training loss of 0.45709 and validation loss of 0.40266), the SAM-trained RF-UNet model achieved a significant reduction in both training loss (0.094225) and validation loss (0.08053). Furthermore, compared to the non-SAM model (training accuracy of 0.90169 and validation accuracy of 0.93999), the SAM-trained model demonstrated higher training accuracy (0.96225) and validation accuracy (0.96821). Additionally, the model performed better in terms of sensitivity, specificity, AUC, and F1 score, indicating improved generalization to unseen data. Our results corroborate the notion that SAM facilitates the learning of flatter minima, thereby improving generalization, and are consistent with other research highlighting the advantages of advanced optimization methods. With wider implications for other medical imaging tasks, these results imply that SAM can successfully reduce overfitting and enhance the robustness of retinal vessel segmentation models. Prospective research avenues encompass verifying the model on vaster and more diverse datasets and investigating its practical implementation in real-world clinical situations.
Cost-Effective Data Acquisition Systems for Advanced Structural Health Monitoring
Authors: Özdemir Kamer , Kömeç Mutlu Ahu
Published: July 2024

With the growing demand for infrastructure and transportation facilities, the need for advanced structural health monitoring (SHM) systems is critical. This study introduces two innovative, cost-effective, standalone, and open-source data acquisition devices designed to enhance SHM through the latest sensing technologies. The first device, termed CEDAS_acc, integrates the ADXL355 MEMS accelerometer with a RaspberryPi mini-computer, ideal for measuring strong ground motions and assessing structural modal properties during forced vibration tests and structural monitoring of mid-rise buildings. The second device, CEDAS_geo, incorporates the SM24 geophone sensor with a Raspberry Pi, designed for weak ground motion measurements, making it suitable for seismograph networks, seismological research, and early warning systems. Both devices function as acceleration/velocity Data Acquisition Systems (DAS) and standalone data loggers, featuring hardware components such as a single-board mini-computer, sensors, Analog-to-Digital Converters (ADCs), and micro-SD cards housed in protective casings. The CEDAS_acc includes a triaxial MEMS accelerometer with three ADCs, while the CEDAS_geo uses horizontal and vertical geophone elements with an ADC board. To validate these devices, rigorous tests were conducted. Offset Test, conducted by placing the sensor on a leveled flat surface in six orientations, demonstrating the accelerometer’s ability to provide accurate measurements using gravity as a reference; Frequency Response Test, performed at the Gebze Technical University Earthquake and Structure Laboratory (GTU-ESL), comparing the devices’ responses to the GURALP-5TDE reference sensor, with CEDAS_acc evaluated on a shaking table and CEDAS_geo’s performance assessed using ambient vibration records; and Noise Test, executed in a low-noise rural area to determine the intrinsic noise of CEDAS_geo, showing its capability to capture vibrations lower than ambient noise levels. Further field tests were conducted on a 10-story reinforced concrete building in Gaziantep, Turkey, instrumented with 8 CEDAS_acc and 1 CEDAS_geo devices. The building’s response to a magnitude 3.2 earthquake and ambient vibrations was analyzed, comparing results to the GURALP-5TDE reference sensors and demonstrating the devices’ accuracy in capturing peak accelerations and modal frequencies with minimal deviations. The study also introduced the Record Analyzer (RECANA) web application for managing data analysis on CEDAS devices, supporting various data formats, and providing tools for filtering, calibrating, and exporting data. This comprehensive study presents valuable, practical solutions for SHM, enhancing accessibility, reliability, and efficiency in structural and seismic monitoring applications and offering robust alternatives to traditional, costlier systems.
Drone-Borne Magnetic Gradiometry in Archaeological Applications
Authors: Accomando Filippo , Florio Giovanni
Published: July 2024

The use of magnetometers arranged in a gradiometer configuration offers a practical and widely used solution, particularly in archaeological applications where the sources of interest are generally shallow. Since magnetic anomalies due to archaeological remains often have low amplitudes, highly sensitive magnetic sensors are kept very close to the ground to reveal buried structures. However, the deployment of Unmanned Aerial Vehicles (UAVs) is increasingly becoming a reliable and valuable tool for the acquisition of magnetic data, providing uniform coverage of large areas and access to even very steep terrain, saving time and reducing risks. However, the application of a vertical gradiometer for drone-borne measurements is still challenging due to the instability of the system drone magnetometer in flight and noise issues due to the magnetic interference of the mobile platform or related to the oscillation of the suspended sensors. We present the implementation of a magnetic vertical gradiometer UAV system and its use in an archaeological area of Southern Italy. To reduce the magnetic and electromagnetic noise caused by the aircraft, the magnetometer was suspended 3m below the drone using ropes. A Continuous Wavelet Transform analysis of data collected in controlled tests confirmed that several characteristic power spectrum peaks occur at frequencies compatible with the magnetometer oscillations. This noise was then eliminated with a properly designed low-pass filter. The resulting drone-borne vertical gradient data compare very well with ground-based magnetic measurements collected in the same area and taken as a control dataset.
New Solid-State Acoustic Motion Sensors: Sensing Potential Estimation for Different Piezo Plate Materials
Authors: Shevelko Michail , Baranov Andrey , Popkova Ekaterina , Staroverova Yasemin , Peregudov Aleksandr , Kukaev Alexander , Shevchenko Sergey
Published: July 2024

The present paper discusses the scientific and technical problem of optimizing the design and characteristics of a new type of solid-state sensors for motion parameters on bulk acoustic waves in order to increase the signal-to-noise ratio and the detectability of an informative signal against the background of its own noise and interference. Criteria for choosing materials for structural elements, including piezoelectric transducers of the sensitive element, were identified; a corresponding numerical simulation was performed using the developed program; and experimental studies according to the suggested method were carried out to validate the obtained analytical and calculated positions. The experimental results revealed the correctness of the chosen criteria for the optimization of design parameters and characteristics, demonstrated the high correlation between the results of modeling and field studies, and, thus, confirmed the prospects of using this new type of solid-state acoustic sensors of motion parameters in the navigation and control systems of highly dynamic objects.
Securing IoT Networks from DDoS Attacks Using a Temporary Dynamic IP Strategy
Authors: El Fawal Ahmad Hani , Mansour Ali , Ammad Uddin Mohammad , Nasser Abbass
Published: July 2024

The progression of the Internet of Things (IoT) has brought about a complete transformation in the way we interact with the physical world. However, this transformation has brought with it a slew of challenges. The advent of intelligent machines that can not only gather data for analysis and decision-making, but also learn and make independent decisions has been a breakthrough. However, the low-cost requirement of IoT devices requires the use of limited resources in processing and storage, which typically leads to a lack of security measures. Consequently, most IoT devices are susceptible to security breaches, turning them into “Bots” that are used in Distributed Denial of Service (DDoS) attacks. In this paper, we propose a new strategy labeled “Temporary Dynamic IP” (TDIP), which offers effective protection against DDoS attacks. The TDIP solution rotates Internet Protocol (IP) addresses frequently, creating a significant deterrent to potential attackers. By maintaining an “IP lease-time” that is short enough to prevent unauthorized access, TDIP enhances overall system security. Our testing, conducted via OMNET++, demonstrated that TDIP was highly effective in preventing DDoS attacks and, at the same time, improving network efficiency and IoT network protection.
‘I Just Don’t Trust Them’: Reasons for Distrust and Non-Disclosure in Demographic Questionnaires for Individuals in STEM
Authors: Goldshtein Maria , Chiou Erin K. , Roscoe Rod D.
Published: July 2024

Demographic data pertain to people’s identities and behaviors. Analyses of demographic data are used to describe patterns and predict behaviors, to inform interface design, and even institutional decision-making processes. Demographic data thus need to be complete and correct to ensure they can be analyzed in ways that reflect reality. This study consists of interviews with 40 people in STEM and addresses how causes of relational (dis)trust in demographic data collection contribute to pervasive problems of missing and incorrect responses and disobliging responses (e.g., non-disclosure, false responses, attrition, and hesitancy to use services). The findings then guide a preliminary set of recommendations for cultivating trustworthiness based on recent developments in trust theory and designing for responsive and trustworthy systems. Specifically, we explore how demographic questionnaire design (e.g., item construction and instructions) can communicate necessary reassurances and transparency for users. The ongoing research provides interview-based recommendations for improving the quality and completeness of demographic data collection. This research adds to other recommendations on improving demographic questionnaires.
Small Island Risks: Research Reflections for Disaster Anthropologists and Climate Ethnographers
Authors: Felima Crystal A.
Published: July 2024

Disasters and climate-related events, including tropical storms, droughts, coastal erosion, and ocean acidification, threaten small island nations. Given the urgency of reducing disaster risks and the effects of climate change on vulnerable populations, this reflection essay pursues three objectives. First, it highlights the role of anthropology, ethnography, and multi-sited research in exploring disaster impacts, climate crises, and public policy in island communities. It then highlights national planning and inter-regional activities to build awareness of various risk reduction efforts by island nations and multi-governmental organizations. This article concludes with discussion prompts to engage researchers, scholars, students, and practitioners studying and working in small island nations. Due to the growing interest in climate equity and justice, this paper argues that anthropologists can offer valuable methodologies and approaches to develop transdisciplinary and nuanced insights into researching disaster risk reduction efforts and climate policy networks in and across island nations.
“Are Journalists Traitors of the State, Really?”—Self-Censorship Development during the Russian–Ukrainian War: The Case of Latvian PSM
Authors: Rožukalne Anda , Kažoka Aija , Siliņa Linda
Published: July 2024

Media self-censorship related to war and military conflict is usually analysed by evaluating the journalistic practices of the countries involved in the war. The objective of this study is to explore how the self-censorship of Latvian public service media (Latvian Radio and Latvian Television) employees developed in response to changes in the internal socio-political discourse after Russia’s full-scale invasion in Ukraine, because of which the Latvian PSM found themselves in the crossfire of long-term criticism and attacks by politicians and audience representatives. Employing semi-structured interviews and qualitative content analysis, this study analyses the perception of self-censorship at all levels (journalists, producers, programme hosts, editors) (15 informants), factors that influence the development of self-censorship, informants’ coping strategies, and the impact of self-censorship on PSM content (78 items of content on various channels and platforms). The conceptual framework of this study is based on Bourdieu’s field theory and Spiral of Silence Theory, exploring how self-censorship affects journalists’ professional habitus, social capital, and agency. The results of this study show that, although Latvia is not involved in the nearby war, politician- and audience member-driven self-censorship affects PSM platforms’ daily agenda, source selection, and editorial line, reducing the diversity and pluralism of PSM content.
Determinants of Intention to Use of Hospital Information Systems among Healthcare Professionals
Authors: Pejić Bach Mirjana , Mihajlović Iris , Stanković Marino , Khawaja Sarwar , Qureshi Fayyaz Hussain
Published: July 2024

Health information systems (HISs) are instrumental in improving the efficiency and effectiveness of hospital operations, from managing patient data to enhancing decision-making processes. This study, which holds significant implications for the healthcare industry, aimed to identify the factors that influence users’ intentions to use HISs. The research involved interviews with healthcare professionals licensed to use the HIS of a public hospital. The survey, conducted in 2020, received 113 responses. Statistical methods of descriptive analysis, correlation, and multiple linear regression were used. Two models were examined. The first model investigated the relationship between the dependent variable of the intention to use an HIS and the independent variables of perceived time savings and perceived privacy protection. The second model explored the impact of age and education as control variables in the connection between the intention to use an HIS and time savings and privacy protection. A significant moderate positive correlation was found between the intention to use an HIS and perceived time savings, while a significant weak positive correlation was detected between the intention to use an HIS and education. Regression analysis in the first model revealed a significant connection between the intention to use an HIS and perceived time savings. However, the perceived privacy protection variable did not show a significant relationship with the dependent variable. The second model showed statistical significance in the relationship between the intention to use an HIS and education, but not with the second control variable, age. It can be concluded that education strengthens the positive impact of perceived time savings on the intention to use a health information system (HIS), a finding that has immediate and practical implications for healthcare professionals and researchers in the field of health information systems and healthcare management, underlining the importance of this research in advancing the understanding and adoption of HISs in healthcare settings.
Recurrent urinary tract infections and prophylactic antibiotic use in women: a cross-sectional study in primary care
Authors: Sanyaolu Leigh , Best Victoria , Cannings-John Rebecca , Wood Fiona , Edwards Adrian , Akbari Ashley , Hayward Gail , Ahmed Haroon
Published: July 2024

Background

Despite the considerable morbidity caused by recurrent urinary tract infections (rUTIs), and the wider personal and public health implications from frequent antibiotic use, few studies adequately describe the prevalence and characteristics of women with rUTIs or those who use prophylactic antibiotics.

Aim

To describe the prevalence, characteristics, and urine profiles of women with rUTIs with and without prophylactic antibiotic use in Welsh primary care.

Design and setting

This was a retrospective cross-sectional study in Welsh general practice using the Secure Anonymised Information Linkage (SAIL) Databank.

Method

The characteristics of women aged ≥18 years with rUTIs or using prophylactic antibiotics from 2010 to 2020, and associated urine culture results from 2015 to 2020, are described.

Results

In total, 6.0% (n= 92 213/N= 1 547 919) had rUTIs, and 1.7% (n= 26 862/N= 1 547 919) were prescribed prophylactic antibiotics with the rates increasing after 57 years of age. Only 49.0% (n=13 149/N= 26 862) of users of prophylactic antibiotics met the definition of rUTIs before initiation. The study found that 80.8% (n= 44 947/N= 55 652) of women with rUTIs had a urine culture result in the preceding 12 months with high rates of resistance to trimethoprim and amoxicillin. Of women taking prophylactic antibiotics, 64.2% (n= 9926/N= 15 455) had a urine culture result before initiation and 18.5% (n= 320/N= 1730) of women prescribed trimethoprim had resistance to it on the antecedent sample.

Conclusion

A substantial proportion of women had rUTIs or incident prophylactic antibiotic use. However, 64.2% (n= 9926/N= 15 455) of women had urine cultured before starting prophylaxis. There was a high proportion of cultured bacteria resistant to two antibiotics used for rUTI prevention and evidence of resistance to the prescribed antibiotic. More frequent urine cultures for rUTI diagnosis and before prophylactic antibiotic initiation could better inform antibiotic choices.
expropriação do mais-trabalho no contexto da “caça apaixonada do valor”
Authors: Bizerra Fernando Araújo
Published: July 2024

O presente artigo oferece uma síntese teórico-interpretativa, a partir de exegeses e análises econômicas de Karl Marx, sobre a expropriação do mais-trabalho na sociedade capitalista. Fruto de pesquisa bibliográfica, apreende, num primeiro momento, as características essenciais da produção da riqueza subordinada à lógica mercantil, donde provém a infinitude de mercadorias que cristalizam o valor criado pelos trabalhadores. Na sequência, evidencia como, na busca obstinada pelo valor, os capitalistas exploram a força de trabalho e expropriam o excedente. Os elementos coligidos permitem a compreensão de que a expropriação do mais-trabalho que nutre os capitalistas ao longo dos últimos séculos ocorre em plena sintonia com a dinâmica sociorreprodutiva do capital, sendo, pois, uma exigência inflexível deste.
Neoliberalismo: a lógica irracional do capitalismo em decadência
Authors: Santos Natália Perdomo dos
Published: July 2024

Este artigo propõe analisar, a partir de uma perspectiva pautada na tradição inaugurada pela obra marxiana, os fundamentos constitutivos do neoliberalismo, que o configuram como uma estratégia de reprodução do capitalismo tardio. Emergente no processo de maturação da sociedade burguesa, o neoliberalismo reformula a ação do Estado para adaptá-lo às necessidades impostas pelas novas formas de gestão da acumulação que, diante da hegemonia do capital portador de juros, só pode garantir a valorização do valor com um poder destrutivo incontrolável. Este movimento revela a barbárie que constitui este modo de produção, e especialmente exposta nos países de capitalismo dependente. Resulta desta etapa a reconfiguração das relações e dos seres sociais na sua totalidade, os quais passam a expressar nos costumes o irracionalismo do capitalismo em decadência. Este é o marco a partir do qual será tecida uma crítica ao pensamento mistificador formulado pelos foucaultianos Dardot e Laval, exposta no livro 'A Nova Razão do Mundo'. O livro, apesar de propor-se crítico ao neoliberalismo, limita-se à epiderme do problema para salvaguardar a lógica estrutural da sociedade burguesa, representando, neste sentido, a típica deformação ideológica desta etapa corrente.