bluuebunny/crossref_metadata_2025 huggingface dataset:
The Grammar and Socio-Political Implications of Kierkegaard’s Christian Virtue of Meekness
Authors: Vos Pieter
Published: November 2023

This paper argues that in Kierkegaard’s works, in his upbuilding discourses and late journal entries in particular, meekness or gentleness (Danish: Sagtmodighed) is presented as a distinctive moral and spiritual quality that exhibits a number of characteristics that are usually regarded as attributes of a virtue. Following a “grammatical approach” to what counts as a virtue, rather than a specifically Aristotelian-Thomistic interpretation, it is argued that Kierkegaard presents meekness as an encompassing attitude, a character trait, which can be acquired through imitation of exemplary persons, Christ, in particular, which aims for the good life, is conducive of the good, and is for the benefit of others and the self. It is demonstrated that according to Kierkegaard, meekness differs from other virtues such as courage and patience by its forgiving attitude towards the wrongdoer and nonviolent resistance to injustice and evil. As a virtue that disposes a person to nonviolent resistance, meekness has socio-political implications: injustice is uncovered and criticized for the benefit of “the poor”. A meek person does not confirm the world in its evil, but criticizes it, albeit in a way that is appropriate to meekness, i.e., in a forgiving and nonviolent way.
CNN-Based Self-Attention Weight Extraction for Fall Event Prediction Using Balance Test Score
Authors: El Marhraoui Youness , Bouilland Stéphane , Boukallel Mehdi , Anastassova Margarita , Ammi Mehdi
Published: November 2023

Injury, hospitalization, and even death are common consequences of falling for elderly people. Therefore, early and robust identification of people at risk of recurrent falling is crucial from a preventive point of view. This study aims to evaluate the effectiveness of an interpretable semi-supervised approach in identifying individuals at risk of falls by using the data provided by ankle-mounted IMU sensors. Our method benefits from the cause–effect link between a fall event and balance ability to pinpoint the moments with the highest fall probability. This framework also has the advantage of training on unlabeled data, and one can exploit its interpretation capacities to detect the target while only using patient metadata, especially those in relation to balance characteristics. This study shows that a visual-based self-attention model is able to infer the relationship between a fall event and loss of balance by attributing high values of weight to moments where the vertical acceleration component of the IMU sensors exceeds 5 m/s² during an especially short period. This semi-supervised approach uses interpretable features to highlight the moments of the recording that may explain the score of balance, thus revealing the moments with the highest risk of falling. Our model allows for the detection of 71% of the possible falling risk events in a window of 1 s (500 ms before and after the target) when compared with threshold-based approaches. This type of framework plays a paramount role in reducing the costs of annotation in the case of fall prevention when using wearable devices. Overall, this adaptive tool can provide valuable data to healthcare professionals, and it can assist them in enhancing fall prevention efforts on a larger scale with lower costs.
Microsphere-Based Microsensor for Miniature Motors’ Vibration Measurement
Authors: Xu Kaichuan , Jiang Chunlei , Ban Qilu , Dai Pan , Fan Yaqiang , Yang Shijie , Zhang Yue , Wang Jiacheng , Wang Yu , Chen Xiangfei , Zeng Jie , Wang Feng
Published: November 2023

We present a microsphere-based microsensor that can measure the vibrations of the miniature motor shaft (MMS) in a small space. The microsensor is composed of a stretched fiber and a microsphere with a diameter of 5 μm. When a light source is incident on the microsphere surface, the microsphere induces the phenomenon of photonic nanojet (PNJ), which causes light to pass through the front. The PNJ’s full width at half maximum is narrow, surpassing the diffraction limit, enables precise focusing on the MMS surface, and enhances the scattered or reflected light emitted from the MMS surface. With two of the proposed microsensors, the axial and radial vibration of the MMS are measured simultaneously. The performance of the microsensor has been calibrated with a standard vibration source, demonstrating measurement errors of less than 1.5%. The microsensor is expected to be used in a confined space for the vibration measurement of miniature motors in industry.
ConGPS: A Smart Container Positioning System Using Inertial Sensor and Electronic Map with Infrequent GPS
Authors: Huang Shan , Song Zihan , Choi Hyung-Rim , Kim Jae-Joong , Park Do-Myung , Park Byung-Kwon
Published: November 2023

Real-time global positioning is important for container-based logistics. However, a challenge in real-time global positioning arises from the frequency of both global positioning system (GPS) calls and GPS-denied environments during transportation. This paper proposes a novel system named ConGPS that integrates both inertial sensor and electronic map data. ConGPS estimates the speed and heading direction of a moving container based on the inertial sensor data, the container trajectory, and the speed limit information provided by an electronic map. The directional information from magnetometers, coupled with map-matching algorithms, is employed to compute container trajectories and current positions. ConGPS significantly reduces the frequency of GPS calls required to maintain an accurate current position. To evaluate the accuracy of the system, 280 min of driving data, covering a distance of 360 km, are collected. The results demonstrate that ConGPS can maintain positioning accuracy within a GPS-call interval of 15 min, even if using low-cost inertial sensors in GPS-denied environments.
Optimal Resource Provisioning and Task Offloading for Network-Aware and Federated Edge Computing
Authors: Nugroho Avilia Kusumaputeri , Shioda Shigeo , Kim Taewoon
Published: November 2023

Compared to cloud computing, mobile edge computing (MEC) is a promising solution for delay-sensitive applications due to its proximity to end users. Because of its ability to offload resource-intensive tasks to nearby edge servers, MEC allows a diverse range of compute- and storage-intensive applications to operate on resource-constrained devices. The optimal utilization of MEC can lead to enhanced responsiveness and quality of service, but it requires careful design from the perspective of user-base station association, virtualized resource provisioning, and task distribution. Also, considering the limited exploration of the federation concept in the existing literature, its impacts on the allocation and management of resources still remain not widely recognized. In this paper, we study the network and MEC resource scheduling problem, where some edge servers are federated, limiting resource expansion within the same federations. The integration of network and MEC is crucial, emphasizing the necessity of a joint approach. In this work, we present NAFEOS, a proposed solution formulated as a two-stage algorithm that can effectively integrate association optimization with vertical and horizontal scaling. The Stage-1 problem optimizes the user-base station association and federation assignment so that the edge servers can be utilized in a balanced manner. The following Stage-2 dynamically schedules both vertical and horizontal scaling so that the fluctuating task-offloading demands from users are fulfilled. The extensive evaluations and comparison results show that the proposed approach can effectively achieve optimal resource utilization.
A New Assistance Navigation Method for Substation Inspection Robots to Safely Cross Grass Areas
Authors: Yang Qiang , Ma Song , Zhang Gexiang , Xian Kaiyi , Zhang Lijia , Dai Zhongyu
Published: November 2023

With the development of intelligent substations, inspection robots are widely used to ensure the safe and stable operation of substations. Due to the prevalence of grass around the substation in the external environment, the inspection robot will be affected by grass when performing the inspection task, which can easily lead to the interruption of the inspection task. At present, inspection robots based on LiDAR sensors regard grass as hard obstacles such as stones, resulting in interruption of inspection tasks and decreased inspection efficiency. Moreover, there are inaccurate multiple object-detection boxes in grass recognition. To address these issues, this paper proposes a new assistance navigation method for substation inspection robots to cross grass areas safely. First, an assistant navigation algorithm is designed to enable the substation inspection robot to recognize grass and to cross the grass obstacles on the route of movement to continue the inspection work. Second, a three-layer convolutional structure of the Faster-RCNN network in the assistant navigation algorithm is improved instead of the original full connection structure for optimizing the object-detection boxes. Finally, compared with several Faster-RCNN networks with different convolutional kernel dimensions, the experimental results show that at the convolutional kernel dimension of 1024, the proposed method in this paper improves the mAP by 4.13% and the mAP is 91.25% at IoU threshold 0.5 in the range of IoU thresholds from 0.5 to 0.9 with respect to the basic network. In addition, the assistant navigation algorithm designed in this paper fuses the ultrasonic radar signals with the object recognition results and then performs the safety judgment to make the inspection robot safely cross the grass area, which improves the inspection efficiency.
High-Precision Control of Aviation Photoelectric-Stabilized Platform Using Extended State Observer-Based Kalman Filter
Authors: Wang Lu , Li Xiantao , Liu Yuzhang , Mao Dapeng , Zhang Bao
Published: November 2023

The accuracy of the line-of-sight of aviation photoelectric optoelectronic stabilization platforms is limited by two factors: external disturbance and sensor noise. An extended state observer (ESO) can effectively improve their anti-interference ability. However, due to the serious problem of gyroscope noise, further improvement of an ESO’s disturbance suppression effect is limited. This article proposes a control structure that combines a Kalman filter (KF) and ESO, effectively improving upon the interference suppression ability of a traditional ESO under the influence of noise. Firstly, an ESO was used to observe the lumped disturbance of the system, and then, the observed disturbance was compensated for in the control loop. Secondly, based on the compensation servo control system, the state equation of the system was reconstructed using a Kalman filter. Finally, the reconstructed filtered state variables were iterated onto the universal state observer, achieving the observation of disturbances while filtering out sensor noise. Under the conditions of a laboratory flight simulation turntable, the line-of-sight stability accuracy level was improved under disturbance excitation. It can be seen that the combination of a Kalman filter and extended disturbance observer proposed in this project improves the ESO’s anti-interference ability under the influence of noise.
Sensorized T-Shirt with Intarsia-Knitted Conductive Textile Integrated Interconnections: Performance Assessment of Cardiac Measurements during Daily Living Activities
Authors: Hafid Abdelakram , Gunnarsson Emanuel , Ramos Alberto , Rödby Kristian , Abtahi Farhad , Bamidis Panagiotis D. , Billis Antonis , Papachristou Panagiotis , Seoane Fernando
Published: November 2023

The development of smart wearable solutions for monitoring daily life health status is increasingly popular, with chest straps and wristbands being predominant. This study introduces a novel sensorized T-shirt design with textile electrodes connected via a knitting technique to a Movesense device. We aimed to investigate the impact of stationary and movement actions on electrocardiography (ECG) and heart rate (HR) measurements using our sensorized T-shirt. Various activities of daily living (ADLs), including sitting, standing, walking, and mopping, were evaluated by comparing our T-shirt with a commercial chest strap. Our findings demonstrate measurement equivalence across ADLs, regardless of the sensing approach. By comparing ECG and HR measurements, we gained valuable insights into the influence of physical activity on sensorized T-shirt development for monitoring. Notably, the ECG signals exhibited remarkable similarity between our sensorized T-shirt and the chest strap, with closely aligned HR distributions during both stationary and movement actions. The average mean absolute percentage error was below 3%, affirming the agreement between the two solutions. These findings underscore the robustness and accuracy of our sensorized T-shirt in monitoring ECG and HR during diverse ADLs, emphasizing the significance of considering physical activity in cardiovascular monitoring research and the development of personal health applications.
Stereoselective Voltammetric Biosensor for Myo-Inositol and D-Chiro-Inositol Recognition
Authors: Tortolini Cristina , Gigli Valeria , Rizzo Flavio , Lenzi Andrea , Bizzarri Mariano , Angeloni Antonio , Antiochia Riccarda
Published: November 2023

This paper describes the development of a simple voltammetric biosensor for the stereoselective discrimination of myo-inositol (myo-Ins) and D-chiro-inositol (D-chiro-Ins) by means of bovine serum albumin (BSA) adsorption onto a multi-walled carbon nanotube (MWCNT) graphite screen-printed electrode (MWCNT-GSPE), previously functionalized by the electropolymerization of methylene blue (MB). After a morphological characterization, the enantioselective biosensor platform was electrochemically characterized after each modification step by differential pulse voltammetry (DPV) and electrochemical impedance spectroscopy (EIS). The results show that the binding affinity between myo-Ins and BSA was higher than that between D-chiro-Ins and BSA, confirming the different interactions exhibited by the novel BSA/MB/MWCNT/GSPE platform towards the two diastereoisomers. The biosensor showed a linear response towards both stereoisomers in the range of 2–100 μM, with LODs of 0.5 and 1 μM for myo-Ins and D-chiro-Ins, respectively. Moreover, a stereoselectivity coefficient α of 1.6 was found, with association constants of 0.90 and 0.79, for the two stereoisomers, respectively. Lastly, the proposed biosensor allowed for the determination of the stereoisomeric composition of myo-/D-chiro-Ins mixtures in commercial pharmaceutical preparations, and thus, it is expected to be successfully applied in the chiral analysis of pharmaceuticals and illicit drugs of forensic interest.
Real-Time Person Detection in Wooded Areas Using Thermal Images from an Aerial Perspective
Authors: Ramírez-Ayala Oscar , González-Hernández Iván , Salazar Sergio , Flores Jonathan , Lozano Rogelio
Published: November 2023

Detecting people in images and videos captured from an aerial platform in wooded areas for search and rescue operations is a current problem. Detection is difficult due to the relatively small dimensions of the person captured by the sensor in relation to the environment. The environment can generate occlusion, complicating the timely detection of people. There are currently numerous RGB image datasets available that are used for person detection tasks in urban and wooded areas and consider the general characteristics of a person, like size, shape, and height, without considering the occlusion of the object of interest. The present research work focuses on developing a thermal image dataset, which considers the occlusion situation to develop CNN convolutional deep learning models to perform detection tasks in real-time from an aerial perspective using altitude control in a quadcopter prototype. Extended models are proposed considering the occlusion of the person, in conjunction with a thermal sensor, which allows for highlighting the desired characteristics of the occluded person.
Design and Characterization of 5 μm Pitch InGaAs Photodiodes Using In Situ Doping and Shallow Mesa Architecture for SWIR Sensing
Authors: Tillement Jules , Cervera Cyril , Baylet Jacques , Jany Christophe , Nardelli François , Di Rito Thomas , Georges Sylvain , Mugny Gabriel , Saxod Olivier , Gravrand Olivier , Baron Thierry , Roy François , Boeuf Frédéric
Published: November 2023

This paper presents the complete design, fabrication, and characterization of a shallow-mesa photodiode for short-wave infra-red (SWIR) sensing. We characterized and demonstrated photodiodes collecting 1.55 μm photons with a pixel pitch as small as 3 μm. For a 5 μm pixel pitch photodiode, we measured the external quantum efficiency reaching as high as 54%. With substrate removal and an ideal anti-reflective coating, we estimated the internal quantum efficiency as achieving 77% at 1.55 μm. The best measured dark current density reached 5 nA/cm2 at −0.1 V and at 23 °C. The main contributors responsible for this dark current were investigated through the study of its evolution with temperature. We also highlight the importance of passivation with a perimetric contribution analysis and the correlation between MIS capacitance characterization and dark current performance.
A Survey of the Security Analysis of Embedded Devices
Authors: Zhou Xu , Wang Pengfei , Zhou Lei , Xun Peng , Lu Kai
Published: November 2023

Embedded devices are pervasive nowadays with the rapid development of the Internet of Things (IoT). This brings significant security issues that make the security analysis of embedded devices important. This paper presents a survey on the security analysis research of embedded devices. First, we analyze the embedded device types and their operating systems. Then, we describe a major dynamic security analysis method for an embedded device, i.e., simulating the firmware of the embedded device and performing fuzzing on the web interface provided by the firmware. Third, we discuss some other issues in embedded security analysis, such as analyzing the attack surface, applying static analysis, and performing large-scale analysis. Based on these analyses, we finally conclude three challenges in the current research and present our insights for future research directions.
5G Positioning: An Analysis of Early Datasets
Authors: Pileggi Chiara , Grec Florin Catalin , Biagi Ludovico
Published: November 2023

Global Navigation Satellite Systems (GNSSs) are nowadays the prevailing technology for positioning and navigation. However, with the roll-out of 5G technology, there is a shift towards ‘hybrid positioning’: indeed, 5G time-of-arrival (ToA) measurements can provide additional ranging for positioning, especially in environments where few GNSS satellites are visible. This work reports a preliminary analysis, the processing, and the results of field measurements collected as part of the GINTO5G project funded by ESA’s EGEP programme. The data used in this project were shared by the European Space Agency (ESA) with the DICA of Politecnico di Milano as part of a collaboration within the ESALab@PoliMi research framework established in 2022 between the two organizations. The ToA data were collected during a real-world measurement campaign and they cover a wide range of user environments, such as indoor areas, outdoor open sky, and outdoor obstructed scenarios. Within the test area, eleven self-made replica 5G base stations were set up. A trolley, carrying a self-made 5G receiver and a data storage unit, was moved along predefined trajectories; the trolley’s accurate trajectories were determined by a total station, which provided benchmark positions. In the present work, the 5G data are processed using the least squares method, testing and comparing different strategies. Therefore, the primary goal is to evaluate algorithms for position determination of a user based on 5G observations, and to empirically assess their accuracy. The results obtained are promising, with positional accuracy ranging from decimeters to a few meters in the worst cases.
Research on a Time Difference Processing Method for RTD-Fluxgate Data Based on the Combination of the Mahalanobis Distance and Group Covariance
Authors: Pang Na , Wang Dan , Yang Yuhan , Wang Rui
Published: November 2023

During the measurement of magnetic fields, Residence Time Difference (RTD)-fluxgate sensors suffer from abnormal time difference jumps due to the random interference of magnetic core noise and environmental noise, which results in gross errors. This situation restricts the improvement of sensor accuracy and stability. In order to solve the above problems efficiently, a time difference gross error processing method based on the combination of the Mahalanobis distance (MD) and group covariance is presented in this paper, and the processing effects of different methods are compared and analyzed. The results of the simulation and experiment indicate that the proposed method is more advantageous in identifying the gross error in time difference. The signal-to-noise ratio for the time difference is improved by about 34 times, while the fluctuation of the Negative Magnetic Saturation Time (NMST) ΔTNMST is reduced by 95.402%, which significantly reduces the fluctuation of time difference and effectively improves the accuracy and stability of the sensor.
Guided Wave Characteristic Research and Probabilistic Crack Evaluation in Complex Multi-Layer Stringer Splice Joint Structure
Authors: Chen Jian , Xu Yusen , Yuan Shenfang , Qin Zhen
Published: November 2023

Multi-layer and multi-rivet connection structures are critical components in the structural integrity of a commercial aircraft, in which elements like skin, splice plate, strengthen patch, and stringer are fastened together layer by layer with multiple rows of rivets for assembling the fuselage and wings. Their non-detachability and inaccessibility pose significant challenges for assessing their health states. Guided wave-based structural health monitoring (SHM) has shown great potential for on-line damage monitoring in hidden structural elements. However, the multi-layer and multi-rivet features introduce complex boundary conditions for guided wave propagation and sensor layouts. Few studies have discussed the guided wave characteristic and damage diagnosis in multi-layer and multi-rivet connection structures. This paper comprehensively researches guided wave propagation characteristics in the multi-layer stringer splice joint (MLSSJ) structure through experiments and numerical simulations for the first time, consequently developing sensor layout rules for such complex structures. Moreover, a Gaussian process (GP)-based probabilistic mining diagnosis method with path-wave band features is proposed. Experiments on a batch of MLSSJ specimens are performed for validation, in which increasing crack lengths are set in each specimen. The results indicate the effectiveness of the proposed probabilistic evaluation method. The maximum root mean squared error of the GP quantitative diagnosis is 1.5 mm.
LLM Multimodal Traffic Accident Forecasting
Authors: de Zarzà I. , de Curtò J. , Roig Gemma , Calafate Carlos T.
Published: November 2023

With the rise in traffic congestion in urban centers, predicting accidents has become paramount for city planning and public safety. This work comprehensively studied the efficacy of modern deep learning (DL) methods in forecasting traffic accidents and enhancing Level-4 and Level-5 (L-4 and L-5) driving assistants with actionable visual and language cues. Using a rich dataset detailing accident occurrences, we juxtaposed the Transformer model against traditional time series models like ARIMA and the more recent Prophet model. Additionally, through detailed analysis, we delved deep into feature importance using principal component analysis (PCA) loadings, uncovering key factors contributing to accidents. We introduce the idea of using real-time interventions with large language models (LLMs) in autonomous driving with the use of lightweight compact LLMs like LLaMA-2 and Zephyr-7b-α. Our exploration extends to the realm of multimodality, through the use of Large Language-and-Vision Assistant (LLaVA)—a bridge between visual and linguistic cues by means of a Visual Language Model (VLM)—in conjunction with deep probabilistic reasoning, enhancing the real-time responsiveness of autonomous driving systems. In this study, we elucidate the advantages of employing large multimodal models within DL and deep probabilistic programming for enhancing the performance and usability of time series forecasting and feature weight importance, particularly in a self-driving scenario. This work paves the way for safer, smarter cities, underpinned by data-driven decision making.
An Urban Acoustic Rainfall Estimation Technique Using a CNN Inversion Approach for Potential Smart City Applications
Authors: Alkhatib Mohammed I. I. , Talei Amin , Chang Tak Kwin , Pauwels Valentijn R. N. , Chow Ming Fai
Published: November 2023

The need for robust rainfall estimation has increased with more frequent and intense floods due to human-induced land use and climate change, especially in urban areas. Besides the existing rainfall measurement systems, citizen science can offer unconventional methods to provide complementary rainfall data for enhancing spatial and temporal data coverage. This demand for accurate rainfall data is particularly crucial in the context of smart city innovations, where real-time weather information is essential for effective urban planning, flood management, and environmental sustainability. Therefore, this study provides proof-of-concept for a novel method of estimating rainfall intensity using its recorded audio in an urban area, which can be incorporated into a smart city as part of its real-time weather forecasting system. This study proposes a convolutional neural network (CNN) inversion model for acoustic rainfall intensity estimation. The developed CNN rainfall sensing model showed a significant improvement in performance over the traditional approach, which relies on the loudness feature as an input, especially for simulating rainfall intensities above 60 mm/h. Also, a CNN-based denoising framework was developed to attenuate unwanted noises in rainfall recordings, which achieved up to 98% accuracy on the validation and testing datasets. This study and its promising results are a step towards developing an acoustic rainfall sensing tool for citizen-science applications in smart cities. However, further investigation is necessary to upgrade this proof-of-concept for practical applications.
Integrated Location Selection and Scheduling Problems for Inland Container Transportation
Authors: Wei Wenchao , Dong Zining , Fan Jinkui
Published: November 2023

Well-organized network configuration is the key to the success of inland container transportation systems. In this study, we firstly propose an integrated framework for the location selection of inland container depots (ICDs) and the scheduling of containers and trucks. The objective is to minimize the total cost of setting up the ICDs and transportation cost associated with trucks and containers. A mixed-integer linear programming (MILP) model is developed to solve the proposed problem. The computational studies show that the proposed decision approach is effective and can reduce the total operating costs of ICDs and transportation costs of containers. Sensitivity analysis on the impact of customer distributions and the number of ICDs on the total cost are conducted to reveal the characteristics of the problem. The utilization of ICDs can significantly improve the efficiency of the transportation network, i.e., the total cost is reduced by at least 27% for the proposed instances, and the transportation distance of empty containers is reduced by at least 4%. Finally, managerial insights and future research directions are provided.
Synthesis of an Eco-Friendly Xylooligosaccharides and Its Mechanistic Evaluation in Water-Based Drilling Fluids
Authors: Zhang Fan , Li Yutong , Zhang Wangyuan , Wang Yu , Ai Erxin , Liu Zhikun , Wei Lei , Li Qi
Published: November 2023

This study investigates the preparation and application mechanism of Xylooligosaccharides (XOS), an environmentally friendly oligosaccharide additive derived from black fungus in water-based drilling fluids (WBFs). The distinctive molecular characteristics of XOS are revealed through Fourier-transform infrared spectroscopy. Thermogravimetric analysis confirms its stability at temperatures below 150 °C. In terms of performance enhancement, incorporating XOS improves rheological properties and filtration efficiency. Elevated XOS concentrations increase viscosity, diminish fluid loss, suppress clay hydration, and enhance cohesive strength, especially at higher temperatures. Additionally, incorporating XOS prompts the formation of a lubricating layer on particle surfaces, facilitating improved interaction between particles and the surrounding fluid. This layer substantially reduces friction coefficients, thereby significantly boosting the lubrication efficiency of the drilling fluid. At the microstructural level, the incorporation of XOS leads to noticeable microstructural refinement in the matrix mud cake, resulting in a smoother particle distribution due to interactions between XOS and particles. Mechanistically, introducing XOS results in a significant shift in the distribution of clay particle sizes. This phenomenon can be attributed to XOS’s ability to create a stable hydration film within the WBFs. As a result, this film mitigates particle aggregation, leading to a reduction in particle size. XOS emerges as a versatile and sustainable oligosaccharide inhibitor, effectively optimizing the performance of WBFs. Its diverse contributions to lubrication, inhibition, and microstructure refinement position XOS as a promising solution for efficiently extracting oil and gas resource.
Addressing Information Consumer Experience through a User-Centered Information Management System in a Chilean University
Authors: Godoy María Paz , Rusu Cristian , Hatibovic Fuad , Granollers Toni , Ugalde Jonathan
Published: November 2023

Prior research on the successful design and construction of data visualization systems or information management systems has not fully taken into account the holistic experience of employees working with information within the organization but has centered on specific aspects, such as user experience or data quality, attempting to go against information management quality, as those approaches can significantly influence users’ perceptions and their motivation to effectively use such tools for decision making. This study addresses the information consumer experience (ICX) in a Chilean Higher Education institution through the design and implementation of an user-centric centralized information management system. This system was created using an adapted design thinking methodology with an ICX perspective to identify and integrate the information consumers’ demands and other factors correlated with ICX into the system’s design. The proposed system is a technological extension of an information resource validation process that involves senior data analysts from the Analytics Department and external data analysts from other departments across the organization. This process helps to address data quality and information management quality (IMQ) problems of the organization, representing a centralized data source for all information consumers into the organization, offering consistent, accessible, and good quality data to address daily work and enhance information consumers experience, and managerial work.
Analysis of Head Displacement during a Frontal Collision at a Speed of 20 km/h—Experimental Studies
Authors: Frej Damian
Published: November 2023

The aim of the research is to compare the head displacements of volunteers with the head displacements of the KPSIT C50 dummy, taking into account the change of vehicle seat belts. Unfortunately, sudden braking or collisions between vehicles is becoming more and more common, especially during traffic jams. There is considerable ignorance in the literature on the behavior of the human body during a low-speed collision, which motivates the development of low-speed crash test procedures in order to reduce the risk of cervical spine injuries. The tests were carried out at a teaching station designed to measure the forces in seat belts and the displacements of individual body elements (dummy or volunteer) during a low-speed crash test. The article is part of extensive research on crash tests using volunteers and KPSIT physical dummies. The study involved 150 volunteers who were divided into specific percentile groups. The article compares the head displacements of the constructed KPSIT C50 dummy with the head displacements of volunteers representing the 50th percentile group of the male population. The study conducted with volunteers was under control and was completely safe for people participating in the study. The research shows that the use of a bucket sports seat equipped with four-point or five-point seat belts significantly reduces the movement of the head during a low-speed collision. This type of vehicle seat is safer and provides a reduced risk of injury from hitting the head on the steering column in a low-speed collision when the airbag has not deployed. Moreover, research shows that standard seat belts placed in passenger vehicles allow the head to move freely forward in the event of an accident or low-speed collision. Therefore, if the speed is too low to deploy the airbag, there is a high probability that the driver and passengers will hit their heads against the cockpit of the passenger vehicle during a collision at a speed of 20 km/h.
A Dynamic and Pseudo-Homogeneous MBs-icELISA for the Early Detection of Aflatoxin B1 in Food and Feed
Authors: Wei Lin , Xu Deyan , Yuan Bei , Pang Chengchen , Xu Haitao , Nie Kunying , Yang Qingqing , Ozkan Sibel A. , Zhang Yanyan , Guo Yemin , Sun Xia
Published: November 2023

Aflatoxin B1 (AFB1) is one of the most toxic and harmful fungal toxins to humans and animals, and the fundamental way to prevent its entry into humans is to detect its presence in advance. In this paper, the monoclonal antibody mAbA2-2 was obtained via three-step sample amplification and multi-concentration standard detection using a subcloning method based on the limited dilution method with AFB1 as the target. A dynamic and pseucdo-homogeneous magnetic beads enzyme-linked immunosorbent assay (MBs-icELISA) was established using the prepared antibody as the recognition element and immunomagnetic beads as the antigen carrier. The MBs-icELISA showed good linear correlation in the concentration range of 0.004–10 ng/mL with R2 = 0.99396. The limit of detection (LOD) of the MBs-icELISA for AFB1 was 0.0013 ng/mL. This new ELISA strategy significantly shortened AFB1 detection time through improved sensitivity compared to the conventional ELISA method.
Characterization of Beta-Lactamase and Fluoroquinolone Resistance Determinants in Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa Isolates from a Tertiary Hospital in Yola, Nigeria
Authors: Kawa Diane E. , Tickler Isabella A. , Tenover Fred C. , Shettima Shuwaram A.
Published: November 2023

Infections due to antimicrobial resistant gram-negative bacteria cause significant morbidity and mortality in sub-Saharan Africa. To elucidate the molecular epidemiology of antimicrobial resistance in gram-negative bacteria, we characterized beta-lactam and fluoroquinolone resistance determinants in Escherichia coli, Klebsiella pneumoniae, and Pseudomonas aeruginosa isolates collected from November 2017 to February 2018 (Period 1) and October 2021 to January 2022 (Period 2) in a tertiary medical center in north-eastern Nigeria. Whole genome sequencing (WGS) was used to identify sequence types and resistance determinants in 52 non-duplicate, phenotypically resistant isolates. Antimicrobial susceptibility was determined using broth microdilution and modified Kirby–Bauer disk diffusion methods. Twenty sequence types (STs) were identified among isolates from both periods using WGS, with increased strain diversity observed in Period 2. Common ESBL genes identified included blaCTX-M, blaSHV, and blaTEM in both E. coli and K. pneumoniae. Notably, 50% of the E. coli in Period 2 harbored either blaCTX-M-15 or blaCTX-M-1 4 and phenotypically produced ESBLs. The blaNDM-7 and blaVIM-5 metallo-beta-lactamase genes were dominant in E. coli and P. aeruginosa in Period 1, but in Period 2, only K. pneumoniae contained blaNDM-7, while blaNDM-1 was predominant in P. aeruginosa. The overall rate of fluoroquinolone resistance was 77% in Period 1 but decreased to 47.8% in Period 2. Various plasmid-mediated quinolone resistance (PMQR) genes were identified in both periods, including aac(6′)-Ib-cr, oqxA/oqxB, qnrA1, qnrB1, qnrB6, qnrB18, qnrVC1, as well as mutations in the chromosomal gyrA, parC and parE genes. One E. coli isolate in Period 2, which was phenotypically multidrug resistant, had ESBL blaCTX-M-15, the serine carbapenemase, blaOXA-181 and mutations in the gyrA gene. The co-existence of beta-lactam and fluoroquinolone resistance markers observed in this study is consistent with widespread use of these antimicrobial agents in Nigeria. The presence of multidrug resistant isolates is concerning and highlights the importance of continued surveillance to support antimicrobial stewardship programs and curb the spread of antimicrobial resistance.
Assessment of Water Quality and Parasitofauna, and a Biometric Analysis of the Prussian Carp of the Romanian Lentic Ecosystem in Moara Domnească, Ilfov County
Authors: Sandu Mirela Alina , Madjar Roxana Maria , Preda Mihaela , Vîrsta Ana , Stavrescu-Bedivan Mala-Maria , Vasile Scăețeanu Gina
Published: November 2023

The aim of this study was to perform a morphometric analysis of Prussian carp individuals collected from the Moara Domnească pond in Ilfov County, Romania. This was accompanied by a physico-chemical characterization of the water, which was sampled from the same location. Consequently, we analyzed a total of 60 Prussian carp individuals that were caught in April (N = 32) and May 2023 (N = 28). For the Carassius gibelio in the study site, we provided, for the first time, data on the weight–length relationships (WLRs), the Fulton K condition factor and the biometric features, including the total length (TL), standard length (SL), head length (HL), snout length (SNL), body depth (BD), girth and ratios for the TL/HL, as well for the TL/BD and TL/SL. A negative growth type was estimated for both the samples of C. gibelio. Based on other studies and fishing reports, besides C. gibelio, there are another 11 species that belong to the Cypriniformes order, and there are two teleost members of the Perciformes order (Lepomis gibbosus and Perca fluviatilis)—these were also associated with this habitat. Water samples were collected from 12 sampling points (SP), which were subjected to physico-chemical characterizations that consisted of an assessment of the turbidity (T), pH, electrical conductivity (EC), chloride (Cl−), total hardness (TH), oxygen regime parameters, phosphate phosphorus (P-PO43−), nitrate nitrogen (N-NO3−), nitrite nitrogen (N-NO2−) and ammonium nitrogen (N-NH4+) levels. In addition, considering their characteristics (high toxicity, non-biodegradability, long-range atmospheric transport and bioaccumulation potential), a number of organochlorine pollutants (OCPs) were identified. The total hardness values presented a very significant correlation with conductivity (r = 0.5974 ***) and with pH (r = 0.5854 ***). The results allowed for the water samples to be placed into the quality classes established by legislation, and they were also discussed in relation to the fishes’ requirements.
Quinoid Redox Mediators and Their Involvement in Environmental Pollution Treatment
Authors: Zhang Haikun , Cheng Manman , Li Yan , Chen Wenhao
Published: November 2023

In recent years, quinoid redox mediators (QRMs) have attracted increasing attention because of their key role in wastewater biotreatment. Previous studies have shown that the anaerobic respiration of many bacteria could be coupled to the reduction and reoxidation of quinone groups. Thus, QRMs are widely involved in the microbial transformation of various organic and inorganic substances. To date, few reviews have focused on the involvement of quinoid compounds in environmental pollution biotreatment processes. In this paper, we review the different types of QRMs that interact closely with microorganisms, the characteristics of those QRMs, the involvement of QRMs during the biotransformation of recalcitrant organic pollutants, heavy metal ions and metallic oxides, and their enhancement on microbial fuel cells. Finally, the future research focus and application prospects with regard to different types of QRMs are proposed. This study can improve our understanding of QRM-mediated environmental pollution biotreatment processes and provide fundamental guidance on what kinds of QRMs are practical for engineering applications.
IDENTIFICATION OF THE BOUNDARIES OF THE HEIGHT OF THE NEW DEVELOPMENT IN THE HISTORICAL CENTER OF PENZA
Authors: Sokolova N. , Uhabin V.
Published: November 2023

The historical center of the city is the main keeper of the cultural code of the city, since the most important historical and cultural objects are concentrated within its borders, the historical environment is preserved. The appearance of high-rise buildings has become a familiar result of the process of urban reconstruction of historical city centers. As a result, there is a compositional destruction of the historical environment, distortion and spatial destruction of the established historical ensembles. The city of Penza is no exception: dozens of historical buildings have been lost, and their place has been taken by buildings of a larger scale and height that destroy the historical environment. The problem of regulating the height of new buildings in the historical environment of the city of Penza has acquired the most acute character and requires its solution. The purpose of the study is to develop a height regulation for the historical center of Penza as an approbation of the previously proposed "comprehensive methodology for identifying the boundaries of the height of a new development in the historical center of a large city based on landscape-visual analysis." The research is based on the study of the problems of regulating the height of buildings in historical city centers in Russia and abroad, the analysis of scientific works and the legislative framework of the Russian Federation and the city of Penza in the field of height regulation, the systematization of domestic and foreign experience in the formation and regulation of height restrictions in historical city centers, a full-scale survey of the city, retrospective and landscape-visual analysis, graphical modeling. As a result of the conducted research, positive results were obtained: the proposed methodology, as a result of testing, confirmed its effectiveness, made it possible to identify landscape and visual features of the historical center of Penza and to form height restrictions within the boundaries of the historical center of the city, the structure and content of the high-rise regulations for the development of the historical center of the city were formed, options for integrating the high-rise regulations into the urban planning documentation of the municipal level were considered.
Incidence of Kidney Failure after Primary Organ Transplant
Authors: Jan Adina , Schappe Tyler , Caddell Keenan B. , Cheng Xingxing S. , Sanoff Scott , Lu Yee , Shaw Brian I. , Samoylova Mariya L. , Peskoe Sarah , Pendergast Jane , McElroy Lisa M.
Published: November 2023

Key Points

Incidence of ESKD in the first year after primary organ transplant ranges from 2.4% to 3.6% and from 1.4% to 1.8% in the second year post-transplant.

National data sources do not currently collect sufficiently reliable follow-up data to identify pretransplant predictors of ESKD.

Background

Careful selection of multiorgan transplant candidates is required to avoid unintended consequences to patients waiting for kidney transplant alone. The need for a safety net among heart and lung transplant recipients is unknown. The objective of this study was to quantify the incidence of kidney failure after liver, heart, or lung transplantation and identify pretransplant predictors of post-transplant kidney failure.

Methods

A retrospective cross-sectional study of adults who received liver, heart, or lung transplant between January 1, 2008, and December 31, 2018, was conducted using data from the Scientific Registry of Transplant Recipient and the United States Renal Data System. Post-transplant renal failure was defined as (1) new start of dialysis, (2) eGFR of <25 ml/min, (3) a new waitlisting for a kidney transplant, or (4) receipt of a kidney transplant.

Results

The final descriptive cohort included 53,620 liver transplant recipients, 22,042 heart transplant recipients, and 10,688 lung transplant recipients. In the first year post-transplant, the probability of ESKD was comparable among heart transplant recipients (0.036; 95% confidence interval [CI], 0.033 to 0.038) and liver transplant recipients (0.033; 95% CI, 0.031 to 0.035) but was markedly lower in lung transplant recipients (0.024; 95% CI, 0.021 to 0.027). In the second year post-transplant, the probability of ESKD was comparable among liver (0.016; 95% CI, 0.015 to 0.017), lung (0.018; 95% CI, 0.015 to 0.021), and heart transplant recipients (0.014; 95% CI, 0.013 to 0.016).

Conclusions

Candidates for thoracic transplant would likely benefit from a safety net policy similar to the one enacted in 2017 for liver transplant so as to maintain judicious patient selection for simultaneous multiorgan transplant. National data sources do not currently collect sufficiently reliable follow-up data to identify pretransplant predictors of ESKD, pointing to a need for transplant centers to consistently report kidney impairment data to national databases.
Keep it simple: a implementação de um bundle de prevenção de infecção do sítio cirúrgico foi eficaz na redução das taxas de infecções relacionada à fraturas
Authors: Silva Raquel Bandeira , Couto Braulio Roberto Goncalves Marinho , Vieira Matheus Nascimento Otoni , Santos Filipe Siqueira , Da Rosa Erick Veiga Franco , Muniz Mateus Rocha , Messias Glauco Sobreira , Gontijo Thiago de Carvalho
Published: November 2023

Infecções relacionada à fraturas (IRF) é uma das complicações mais desafiadoras na cirurgia do trauma, uma vez que, tais infecções prejudicam a formação do calo ósseo, podendo levar a soltura séptica dos implantes e a não consolidação (não união) causando sequelas de elevada morbidade.  Tais sequelas impedem que o paciente retorne as suas funcionalidades, o que compromete sua qualidade de vida e renda onerando assim o sistema previdenciário do país. O presente estudo visa avaliar o impacto de um bundle de prevenção de infecção de sítio cirúrgico (ISC) na redução das taxas de IRF no Hospital Universitário Ciências Médicas. Trata-se de estudo de coorte unicêntrico realizado entre janeiro/2021 e dez/2022, no qual compara-se a taxa de IRF nos pacientes submetidos a qualquer tipo de cirurgia ortopédica para estabilização óssea por fraturas fechadas antes e depois da implementação do bundle. O pacote do bundle consistiu de 4 intervenções: profilaxia antibiótica de espectro estendido, repique intraoperatório de antibiótico quando necessário, auditoria dos procedimentos cirúrgicos com feedbacks e treinamento/sensibilização do corpo clinico para medidas de prevenção de ISC. A implementação do Bundle se mostrou eficiente, levando a uma queda do risco geral de desenvolver IRF em 59%. O risco relativo de desenvolvimento de IRF após implementação do Bundle foi 0,4 (p=0.000; IC 95% [0.22; 0.58). A estratégia Bundle implementada se apresentou eficaz para redução das taxas de IRF. Sua efetividade associada ao seu baixo custo e facilidade de implementação, permite que a mesma seja replicada em centro ortopédicos de países em desenvolvimento e com isso reduzir a morbidade e os custos sociais que as IRF’s causam nestes países.