bluuebunny/crossref_metadata_2025 huggingface dataset:
Spectral Mixture Modeling of an ASTER Bare Soil Synthetic Image Using a Representative Spectral Library to Map Soils in Central-Brazil
Authors: Novais Jean J. , Poppiel Raul R. , Lacerda Marilusa P. C. , Oliveira Manuel P. , Demattê José A. M.
Published: January 2023

Pedological maps in suitable scales are scarce in most countries due to the high costs involved in soil surveying. Therefore, methods for surveying and mapping must be developed to overpass the cartographic material obtention. In this sense, this work aims at assessing a digital soil map (DSM) built by multispectral data extrapolation from a source area to a target area using the ASTER time series modeling technique. For that process, eight representative toposequences were established in two contiguous micro-watersheds, with a total of 42 soil profiles for analyses and classification. We found Ferralsols, Plinthosols, Regosols, and a few Cambisols, Arenosols, Gleisols, and Histosols, typical of tropical regions. In the laboratory, surface soil samples were submitted to spectral readings from 0.40 µm to 2.50 µm. The soil spectra were morphologically interpreted, identifying shapes and main features typical of tropical soils. Soil texture grouped the curves by cluster analysis, forming a spectral library (SL). In parallel, an ASTER time series (2001, 2004, and 2006) was processed, generating a bare soil synthetic soil image (SySI) covering 39.7% of the target area. Multiple Endmember Spectral Mixture Analysis modeled the SL on the SySI generating DSM with 73% of Kappa index, in which identified about 77% is covered by rhodic Ferralsols. Besides the overestimation, the DSM represented the study area’s pedodiversity. Given the discussion raised, we consider including subsoil data and other features using other sensors in operations modeled by machine learning algorithms to improve results.
The Effect of Fertilization on the Structure of the Aboveground Biomass of Several Cultivars of Jerusalem Artichoke (Helianthus tuberosus L.)
Authors: Skiba Dominika , Jariene Elvyra , Barbaś Piotr , Krochmal-Marczak Barbara , Sawicka Barbara
Published: January 2023

JA (Jerusalem artichoke) cultivars react differently to mineral fertilization. Hence, the aim of this study was to assess the effect of mineral fertilization on the yield and yield structure of this species in terms of its aboveground biomass. The research was based on a field experiment carried out in 2016–2018 in Central and Eastern Poland using the randomized subblock method, in a split-split-plot-dependent system. The factors of the first-order experiment were the cultivars of Jerusalem artichoke (JA) (‘Albik’, ‘Rubik’ and ‘Violet de Renes’), while the second-order factors were differentiated mineral fertilizers (N0P0K0 as a control object and P43, K124, N100, P43K124, N50P43K124m N100P43K124, and N150P43K124) converted to their elemental forms compared with the full dose of manure. The third-order factors were nitrogen forms, including ammonium nitrate and amide. The aboveground biomass yield and its structure were determined. The tested cultivars did not differ significantly in yield, but had different yield structures. The use of mineral fertilization brought measurable effects in the form of an increase in the yield of aboveground biomass. The ‘Albik’ cultivar responded best to mineral fertilization, with the highest yield of aboveground biomass being obtained after applying 150 kg N ha−1 in the form of ammonium nitrate against the background of constant phosphorus–potassium fertilization. The ‘Rubik’ cultivar responded most favorably to the addition of 50 kg N ha−1 in the amide form against the background of phosphorus–potassium fertilization, while the ‘Violet de Renes’ cultivar produced the highest yield of aboveground biomass after the application of 100 kg N ha−1 in the amide form, including PK fertilization. It was found that it was advantageous to use a combination of nitrogen and phosphorus–potassium fertilization.
Cross-Section Observational Study to Assess Antimicrobial Resistance Prevalence among Bovine Respiratory Disease Bacterial Isolates from Commercial US Feedlots
Authors: Jobman Erin , Hagenmaier Jacob , Meyer Nathan , Harper Lee Bob , Taylor Lisa , Lukasiewicz Kip , Thomson Dan , Lowe James , Terrell Shane
Published: January 2023

Antimicrobial resistance (AMR) is a global public health threat that jeopardizes efficacy of antibiotics in veterinary and human medicine. Antibiotics are commonly administered to target the bacterial component of bovine respiratory disease (BRD). The objectives of this study were to obtain a better understanding of antibiotic resistance in BRD-associated bacteria (Mannheimia haemolytica, Pasteurella multocida, and Histophilus somni), investigate the clinical significance of AMR by monitoring clinical outcomes, and determine if regional differences exist in AMR trends. Deep pharyngeal swabs were used to sample beef cattle at initial BRD diagnosis (n = 453) from US feedlots representing three geographic regions. Organisms were identified by bacterial culture and subjected to broth microdilution antimicrobial susceptibility testing. Bacterium prevalence include P. multocida (36.0%), M. haemolytica (32.7%), and H. somni (28.5%). Of the Histophilus isolates, 39.5% were resistant to at least one antimicrobial, compared to 11.7% and 8.8% Pasteurella and Mannheimia, respectively. Non-susceptibility across all organisms was 5.7 X more likely in animals that received metaphylaxis, than those that did not (p < 0.0001; OR 5.7; CI 2.6–12.5). During days on feed 21–40, non-susceptibility of Histophilus was 8.7 X more likely than Mannheimia (p = 0.0002; OR 8.7; CI 2.8 to 27.4) and 6 X more likely than Pasteurella (p = 0.0016; OR 6.0; CI 2.0–18.0).
Antimicrobial Prescribing Practices in Hospital Settings in Italy: A Retrospective Study
Authors: Napolitano Francesco , Pelullo Concetta Paola , Lamberti Monica , Donnarumma Giovanna , Di Giuseppe Gabriella
Published: January 2023

Background: This study aims to evaluate the antimicrobial prescribing practices in hospital settings in Italy, focusing on the appropriateness of antibiotic use. Methods: This study was carried out through a retrospective review of medical records of patients admitted in three public hospitals located in Campania Region (Italy) between 1 January and 31 December 2018. Results: More than one third (34.2%) of patients received at least one inappropriate antibiotic prescription (antibiotic administered and not indicated). Being female, having a >1 Charlson comorbidity index score, and having a longer hospital stay were significant determinants of an inappropriate antibiotic prescription. Instead, patients who had had a non-urgent hospital admission, an infection on hospital admission, and a microbiological culture test during hospital stay were significantly less likely to have an inappropriate prescription. When the antibiotic prescriptions were analyzed, in 26.6% of cases they were not indicated, while among the 687 antibiotic prescriptions with indication, incorrect choice of antibiotics (36.8%) was the most common reason of the inappropriateness. Conclusions: The findings of the study indicate that the inappropriate use of antibiotics continues to be a relevant issue in the hospital setting and specific interventions are needed to encourage a wider utilization of diagnostic tools to practice targeted therapies and to counter the antimicrobial resistance.
Characterization of Two Novel AmpC Beta-Lactamases from the Emerging Opportunistic Pathogen, Cedecea neteri
Authors: Sharkady Stephen M. , Bailey Brandon , Thompson Dorothea K.
Published: January 2023

The genus Cedecea (family Enterobacteriaceae) causes a wide spectrum of acute infections in immunocompromised hosts, from pneumonia and bacteremia to oral ulcers and dialysis-related peritonitis. While Cedecea infections are reported infrequently in the literature, documented clinical cases of this emerging opportunistic human pathogen have occurred worldwide. Cedecea neteri has clinical significance and exhibits antimicrobial drug resistance. However, little is known about the molecular basis underlying the resistance phenotypes in C. neteri. We previously hypothesized that the open-reading frame cnt10470 in the C. neteri SSMD04 genome encodes a chromosomal Ambler class C (AmpC) β-lactamase based on sequence homology. In this study, recombinant polyhistidine-tagged proteins were created by cloning the putative ampC genes from SSMD04 and C. neteri ATCC 33855 (a clinical isolate) into the pET-6xHN expression vector, overexpressing the proteins, and then purifying the recombinant AmpCs (rAmpCs) using immobilized metal affinity chromatography (Ni-NTA). The in vitro enzymatic analysis of the purified rAmpCs was performed to determine the Km and kcat for various β-lactam substrates. The rAmpCs are functional class C β-lactamases when assayed using the chromogenic β-lactamase substrate, nitrocefin. The presence of functional AmpCs in both C. neteri strains underscores the necessity of performing antibiotic susceptibility testing in the management of C. neteri infections.
Development of a Clinical Score to Stratify the Risk for Carbapenem-Resistant Enterobacterales Bacteremia in Patients with Cancer and Hematopoietic Stem Cell Transplantation
Authors: Herrera Fabián , Torres Diego , Laborde Ana , Berruezo Lorena , Jordán Rosana , Rossi Inés Roccia , Valledor Alejandra , Costantini Patricia , Dictar Miguel , Nenna Andrea , Pereyra María Laura , Lambert Sandra , Benso José , Poletta Fernando , Gonzalez Ibañez María Luz , Baldoni Nadia , Eusebio María José , Lovano Fiorella , Barcán Laura , Luck Martín , Racioppi Agustina , Tula Lucas , Pasterán Fernando , Corso Alejandra , Rapoport Melina , Nicola Federico , García Damiano María Cristina , Carbone Ruth , Monge Renata , Reynaldi Mariana , Greco Graciela , Bronzi Marcelo , Valle Sandra , Chaves María Laura , Vilches Viviana , Blanco Miriam , Carena Alberto Ángel
Published: January 2023

Identifying the risk factors for carbapenem-resistant Enterobacterales (CRE) bacteremia in cancer and hematopoietic stem cell transplantation (HSCT) patients would allow earlier initiation of an appropriate empirical antibiotic treatment. This is a prospective multicenter observational study in patients from 12 centers in Argentina, who presented with cancer or hematopoietic stem-cell transplant and developed Enterobacterales bacteremia. A multiple logistic regression model identified risk factors for CRE bacteremia, and a score was developed according to the regression coefficient. This was validated by the bootstrap resampling technique. Four hundred and forty-three patients with Enterobacterales bacteremia were included: 59 with CRE and 384 with carbapenem-susceptible Enterobacterales (CSE). The risk factors that were identified and the points assigned to each of them were: ≥10 days of hospitalization until bacteremia: OR 4.03, 95% CI 1.88–8.66 (2 points); previous antibiotics > 7 days: OR 4.65, 95% CI 2.29–9.46 (2 points); current colonization with KPC-carbapenemase-producing Enterobacterales: 33.08, 95% CI 11.74–93.25 (5 points). With a cut-off of 7 points, a sensitivity of 35.59%, specificity of 98.43%, PPV of 77.7%, and NPV of 90.9% were obtained. The overall performance of the score was satisfactory (AUROC of 0.85, 95% CI 0.80–0.91). Finally, the post-test probability of CRE occurrence in patients with none of the risk factors was 1.9%, which would virtually rule out the presence of CRE bacteremia.
GIS-Based Urban Traffic Assessment in a Historical European City under the Influence of Infrastructure Works and COVID-19
Authors: Droj Gabriela , Droj Laurențiu , Badea Ana-Cornelia , Dragomir Petre Iuliu
Published: January 2023

Urban areas have developed organically over time, driven by the economic success of cities. However, this development has usually been accompanied by the side effects of urbanization, such as increased traffic and its associated problems: traffic congestion, increased accident rates and pollution. As urban populations grow and expand, the importance of GIS lies in its ability to collect a large amount of geospatial data, including human-generated data. This data is necessary to understand the complexity of the city, set priorities, solve complicated planning problems and perform a variety of spatial analysis, which shows not only the feasibility but also the consistency of the proposed infrastructure with the requirements of a sustainable city. In this paper, we demonstrate the benefits of integrating real-time traffic data with GIS technology and remote sensing data for analyzing the impact of infrastructure works and COVID-19 on traffic in Oradea, Romania. The case study was focused on the historical center of Oradea and was based on remote sensing data collected before, during, and after traffic restrictions. The study also shows the need for using GIS and crowdsourcing-based applications in traffic analysis and planning.
Investigation of Intermetallics Formation and Joint Performance of Laser Welded Ni to Al
Authors: Cao Lichao , Liu Yongfeng , Chen Hui-Chi , Zhang Li , Sun Hua , Bi Guijun
Published: January 2023

In this paper, laser welding Ni to Al using pulsed wave (PW) and continuous wave (CW) lasers was investigated. Weld quality and strength were evaluated in terms of cross-section examination, intermetallic compounds formation, microhardness, shear test and 90-degree peel test. The results show that deep penetration welding Ni to Al causes high melting pool temperature and severe material mixing, which could result in dominant AlNi3 and AlNi intermetallics (IMCs) in the weld. These IMCs could significantly increase the hardness of the welding zone, but could also lead to the formation of defects, as well as reducing the ability to withstand the shear force and peel force applied to the weld. In comparison, using process optimization to maintain a shallow penetration or form a weld-braze joint, low melting pool temperature and minimum material mixing can be achieved. Hence, low-hardness Al3Ni IMCs are prevalent in the weld. This helps generate a defect-free dissimilar weld joint to withstand higher shear force and peel force. The findings show promising applications, such as the battery management system of electric vehicles, in which joining a Ni adaptor to an Al bus bar is required.
3D Displacement Measurement of Railway Bridge According to Cyclic Loads of Different Types of Railcars with Sequential Photogrammetry
Authors: Lee Hyoseong , Oh Jaehong
Published: January 2023

In the early days of railroads in Korea, railway bridges were constructed as steel plate-girder structures, which are vulnerable to vibration and torsion. Many of these bridges have since been replaced with concrete-slab structures, which have high stability. Nevertheless, steel railway bridges still remain all over the country, and a lot of manpower and cost is being invested in the maintenance and repair of such bridges. Moreover, there have not been experimental analyses aiming to measure the cyclic loads that occur when a train enters. To ensure bridge safety, it is necessary to periodically inspect deformations. To this end, the present study proposed a sequential photogrammetric technique for measuring the deformation of a steel railway bridge for three types of railcars. Sequential stereo images of the bridge with multiple feature points are obtained using sequential photographing cameras, to determine the ground coordinates of each point as a function of time based on the space intersection from the relative orientation with coplanarity and the scale adjustment. All of these processes are performed through automated techniques using only the cameras and the targets. With this setup, the 3-dimensional dynamic motions of the bridge due to the cyclic loading of trains could be measured. In addition, the displacements by the proposed method were compared to those obtained with the 3D Laser tracker. The horizontal displacements errors did not exceed 0.5 mm and the vertical error was within 2.3 mm in root mean square error (RMSE) at camera-to-object distances of about 9 m.
Music for the Heart—Can Heart Rate Be Influenced by Different Music Genres or Modulated Sounds? A Comparison between Healthy Young and Elderly People and Patients with Parkinson’s Disease
Authors: Ohlendorf Daniela , Rader Tobias , Maurer-Grubinger Christian , Keil Fee , Wanke Eileen M. , Uibel Stefanie , Holzgreve Fabian , Groneberg David A.
Published: January 2023

Introduction: The aim of the present study was to analyze the influence of different music genres, three modulated noises and a pink noise on the heart rate (HR) and to compare between young healthy adults (YA), elderly healthy adults was (EA) and patients with Parkinson’s disease (PD). Furthermore, a sound condition comparison for each group was conducted. Methods: A total of 77 subjects (41m/36w) were divided into healthy adults aged 20–35 years (YA) and 55–76 years (EA) as well as adults diagnosed with Parkinson’s disease (42–76 years) (PD). The “Polar OH1”, an optical pulse sensor, determined the heart rate. All test persons used identical wireless headphones (Bose QC35). The music genres were classical, relaxation and heavy metal with different speeds (bpm) while the three modulated noises were equivalent to these three music styles. To exclude visual information, everyone wore a blindfold. Significance was set at 5%. Results: When comparing experimental conditions within a subject group, there was a significant difference (p ≤ 0.001). between the different measurement mostly in group YA but barely noticeable in group EA. Subject group PD had no significant condition differences. For each sound condition the median HR was higher in YA than in EA (p ≤ 0.001–0.05). Conclusion: The heart rate was not affected by wearing headphones with or without the noise canceling mode. While listening to the music or the tones, younger people have a higher HR variability than older people which may, thus, make them more sensitive to the conditions studied. It can be assumed that the listening to music has no systematic influence on decreasing or increasing the HR.
Prediction of Tunnel Blasting Vibration Velocity Considering the Influence of Free Surface
Authors: Zeng Xiaohui , Zhang Xuemin , Zhou Xianshun , Duan Ya , Chen Jin
Published: January 2023

The blast vibration attenuation will change as the tunnel cut hole is blasted to create a new free surface. To guarantee safe tunnel construction and optimize blast design parameters, it is crucial to understand the impact of the free surface on blast vibration attenuation. Previous studies have often only qualitatively evaluated the effect of the free surface on blast vibration, failing to quantify these impacts on vibration attenuation. In this paper, by analyzing the decay law of the blast vibration velocity under different free surfaces, we quantitatively assessed the effect of the number of free faces and burden distance on the peak vibration velocity. Then, we introduced free-face parameters to enhance the current formula for predicting blast vibration velocity. The results show that the peak vibration velocity decreases with the increasing free surface number and increases with increasing burden distance; the free surface factor cannot be ignored in the decay of vibration velocity and contributes about 21% more to the total decay factor than the scale distance factor. The average tolerance rises from 24.79% in the Sadovsky formula to 13.32% in the correction formula, and the correction formula more precisely predicts the peak vibration velocity. The accuracy of the correction formula provides a good scientific basis for the design of tunnel blasting parameters. The research results were successfully applied to the Jiujiawan proximity tunnel on the Duyun-Anshun highway in Guizhou, effectively guaranteeing blasting safety with a minimum clear distance of 17.2 m.
Influence of ZnO (Nano)Rods on the Dielectric Properties of DGEBF Epoxy Exposed to Progressive Artificial Weathering for VHF/Early UHF Applications
Authors: Papalampris Georgios , Georgiou Pantelitsa , Argyropoulos Theodore , Hristoforou Evangelos , Vassiliou Panayota
Published: January 2023

An as-produced epoxy material reinforced with ZnO (nano)rods for outdoor use was produced for the purpose of enclosing VHF/early UHF transceiving elements. Three different ZnO (nano)rod percentages were dispersed (0.1 wt%, 0.5 wt% and 2 wt%) in epoxy samples and were consequently exposed to an artificial weathering environment for a total period of 2880 h. SEM and XRD characterizations were followed by gravimetric, colorimetric and dielectric measurements that were conducted every 576-h AWE treatment intervals and were complemented by FTIR, UV-Vis, contact angle and gloss measurements. The composite exhibited favourable dielectric behaviour: ZnO presence inflicted minimal impact to the composites’ loss tangent, while dielectric permittivity was reduced for low ZnO content (0.1 wt%/0.5 wt%), especially until the 1152-h interval, while it suffered an increase for 2 wt% samples that was maintained from the beginning until the end of the experiment. Hence, the low-k (4–5.2) constructed material, compared to bare epoxy resin, maintained moderate loss tangent levels (0.55–0.7) in the VHF/early UHF spectrum, throughout the full AWE treatment, and also attained reduced dielectric permittivity, thus exhibiting moderate radio frequency transparency, together with enhanced endurance against environmental fatigue.
Processing of AZ91D Magnesium Alloy by Laser Powder Bed Fusion
Authors: Nopová Klára , Jaroš Jan , Červinek Ondřej , Pantělejev Libor , Gneiger Stefan , Senck Sascha , Koutný Daniel
Published: January 2023

Magnesium alloys are perspective materials for use in transportation, aerospace and medical industries, mainly because of their good load-to-weight ratio, biocompatibility and biodegradability. For the effective production of magnesium components by the laser powder bed fusion (LPBF) process, the process parameters with verified mechanical properties need to be determined. In this paper, we prepared bulk samples with a high relative density of AZ91D magnesium alloy. Tensile tests were then performed on LPBF samples to evaluate the mechanical properties. Our results show that the bulk samples achieved a relative density >99%, in multiple planes over the full sample height, while the mechanical properties reached values of YS = 181 MPa, UTS = 305 MPa and A5.65 = 5.2%. The analysis by scanning electron microscope revealed fine β-Mg17Al12 particles in the microstructure, which have a positive effect on the mechanical properties. The chemical composition of magnesium alloy AZ91D changed slightly during processing by LPBF due to the evaporation of the Mg content. However, the resulting composition still corresponds to the range specified by the ASTM standard for the AZ91D alloy.
Cone Beam Computed Tomography Radiomics for Prostate Cancer: Favourable vs. Unfavourable Prognosis Prediction
Authors: Mendes Bruno , Domingues Inês , Dias Filipe , Santos João
Published: January 2023

Silently asymptomatic at an early stage and often painless, requiring only active surveillance, Prostate Cancer (PCa) is traditionally diagnosed by a Digital Rectal Examination (DRE) and a Prostate Specific Antigen (PSA) blood test. A histological examination, searching for pattern irregularities on the prostate glandular tissue, is performed to quantify the aggressiveness of PCa. The assigned Gleason Score (GS), usually combined with Transrectal Ultrasound Guided Biopsy (TRUS), allows the stratification of patients according to their risk group. Intermediate-risk patients may have a favourable (GS = 3 + 4) or unfavourable (GS = 4 + 3) prognosis. This borderline is critical for defining treatments and possible outcomes, while External Beam Radiotherapy (EBRT) is a curative option for localised and locally advanced disease and as a palliative option for metastatic low-volume disease; active surveillance or watchful waiting can also be an option for patients with a favourable prognosis. With radiomics, quantifying phenotypic characteristics in medical imaging is now possible. In the EBRT workflow, there are several imaging modalities, such as Magnetic Ressonance Imaging (MRI), Computed Tomography (CT), Positron Emission Tomography (PET), Ultrasound and Cone Beam Computed Tomography (CBCT). Most radiomic PCa studies focused on MRI and addressed tumour staging, GS, PSA or Biochemical Recurrence (BCR). This study intends to use CBCT radiomics to distinguish between favourable and unfavourable cases, with the potential of evaluating an ongoing treatment. Seven of the most used feature selection methods, combined with 14 different classifiers, were evaluated in a total of 98 pipelines. From those, six stood out with Area Under the Receiver Operating Characteristic (AUROC) values ≥ 0.79. To the best of our knowledge, this is the first work to evaluate a PCa favourable vs. unfavourable prognosis model based on CBCT radiomics.
Automatic Detection of Corrosion in Large-Scale Industrial Buildings Based on Artificial Intelligence and Unmanned Aerial Vehicles
Authors: Lemos Rafael , Cabral Rafael , Ribeiro Diogo , Santos Ricardo , Alves Vinicius , Dias André
Published: January 2023

In recent years, Artificial Intelligence (AI) provided essential tools to enhance the productivity of activities related to civil engineering, particularly in design, construction, and maintenance. In this framework, the present work proposes a novel AI computer vision methodology for automatically identifying the corrosion phenomenon on roofing systems of large-scale industrial buildings. The proposed method can be incorporated into computational packages for easier integration by the industry to enhance the inspection activities’ performance. For this purpose, a dedicated image database with more than 8k high-resolution aerial images was developed for supervised training. An Unmanned Aerial Vehicle (UAV) was used to acquire remote georeferenced images safely and efficiently. The corrosion anomalies were manually annotated using a segmentation strategy summing up 18,381 instances. These anomalies were identified through instance segmentation using the Mask based Region-Convolution Neural Network (Mask R-CNN) framework adjusted to the created dataset. Some adjustments were performed to enhance the performance of the classification model, particularly defining an adequate input image size, data augmentation strategy, Intersection over a Union (IoU) threshold during training, and type of backbone network. The inferences show promising results, with correct detections even under complex backgrounds, poor illumination conditions, and instances of significantly reduced dimensions. Furthermore, in scenarios without a roofing system, the model proved reliable, not producing any false positive occurrences. The best model achieved metrics’ values equal to 65.1% for the bounding box detection Average Precision (AP) and 59.2% for the mask AP, considering an IoU of 50%. Regarding classification metrics, the precision and recall were equal to 85.8% and 84.0%, respectively. The developed methodology proved to be extremely valuable for guiding infrastructure managers in taking physically informed decisions based on the real assets condition.
A Comparative Study of Effective Domain Adaptation Approaches for Arabic Sentiment Classification
Authors: Alqahtani Yathrib , Al-Twairesh Nora , Alsanad Ahmed
Published: January 2023

Over the last decade, many methods have been developed to address the domain dependency problem of sentiment classification under domain shift. This problem is exacerbated in Arabic by its feature sparsity induced by morphological complexity and dialect variability. However, only a few studies have proposed sentiment domain adaptation methods for Arabic, with inconsistent comparisons resulting from different datasets and settings, making it difficult to identify the most effective approaches. This is the first comparative study of the most effective domain adaptation methods for Arabic sentiment classification. We replicate the existing methods proposed for Arabic and compare their effectiveness on the standard dataset settings. To further examine the extent to which adaptation performance differs between Modern Standard Arabic (MSA) and Dialectal Arabic (DA), we employ two public multi-domain sentiment datasets. We also test two well-established methods that have been thoroughly utilized in English-related studies and examine if they maintain the same levels of performance when applied to Arabic. Our findings indicate that adaptation performanace on MSA is better than on DA for all traditional approaches. However, implementing adaptation on top of transformer-based language models shows superior performance on DA. Finally, methods that have proven to excel in English suffer from low performance when applied to Arabic and exhibit negative transfer in most cases.
A New Technique for Determining the Shape of a Paper Sample in In-Plane Compression Test Using Image Sequence Analysis
Authors: Pełczyński Paweł , Szewczyk Włodzimierz , Bieńkowska Maria , Kołakowski Zbigniew
Published: January 2023

The article presents a new technique for analyzing phenomena occurring during the measurement of the strength properties of paper in the conditions of compression of the tested samples with forces acting in the paper plane. The technique is based on collecting data on the current distance of the clamps holding the tested sample and the force exerted on the sample using a universal testing machine and on the simultaneous recording of image sequence of the sample during the measurement. Next, the resulting images are subjected to processing and analysis, the purpose of which is to extract information about the shape of the sample edge in all phases of the measurement. Its advantage is the ability to determine the deflection arrow of the sample and describe its shape using the selected function given by the analytical parametric formula. It will be helpful in further research on the development of an analytical model describing the phenomena occurring during paper compression, and a method to determine the mechanism of paper destruction and the corresponding maximum force that destroys a paper sample.
A Deep-Learning Approach for Identifying a Drunk Person Using Gait Recognition
Authors: Park Suah , Bae Byunghoon , Kang Kyungmin , Kim Hyunjee , Nam Mi Song , Um Jumyung , Heo Yun Jung
Published: January 2023

Various accidents caused by alcohol consumption have recently increased in prevalence and have become a huge social problem. There have been efforts to identify drunk individuals using mobile devices; however, it is difficult to apply this method to a large number of people. A promising approach that does not involve wearing any sensors or subject cooperation is a markerless, vision-based method that only requires a camera to classify a drunk gait. Herein, we first propose a markerless, vision-based method to determine whether a human is drunk or not based on his or her gait pattern. We employed a convolutional neural network to analyze gait patterns with image augmentation depending on gait energy images. Gait images captured through a camera allow a complex neural network to detect the human body shape accurately. It is necessary for removing the background behind human shape in the gait image because it disrupts the detection algorithm. A process of conversion into gait energy images and augmenting image data is then applied to the dataset of the gait images. A total of 20 participants participated in the experiment. They were required to walk along a line both with and without wearing the Drunk Busters Goggles, which were intended to collect sober and drunk gait images. Validation accuracy for the recognition of a drunk state in 20 persons was approximately 74.94% under optimal conditions. If the present approach fulfills its promise, we can prevent safety accidents due to alcohol, thus decreasing its burden on industries and society.
A Declarative Application Framework for Evaluating Advanced V2X-Based ADAS Solutions
Authors: Wippelhauser András , Edelmayer András , Bokor László
Published: January 2023

Application of Vehicular Ad Hoc Networks (VANETs) aims to help in the solution of some problems that have arisen in road transportation systems via short-range, low-latency mobile communication. The application of V2X (Vehicle-to-Everything) communication technologies to the next generation of Advanced Driver Assistance Systems (ADAS) is essential to the extension of the operational design domain (ODD) of the systems to provide safe, secure, and efficient automated driving solutions. Due to the safety-critical nature of the problem, the large-scale testing of V2X enabled ADAS solutions to evaluate and measure the anticipated quality and functionality of the experimental system is of great significance. This article proposes a novel ADAS application prototyping framework, using declarative programming, built on top of the popular Artery/OMNeT++ simulator. The framework is capable of simulating V2X-enabled ADAS applications using accurate network simulation and realistic simulated traffic on real-world maps. The solution features XML descriptions for application specification. The sensor model of Artery is used to provide information to applications. By using the simulator, one can conclude the performance of the applications and discover locations, circumstances and design patterns, where design limits should apply.
AI-Enabled Wearable Medical Internet of Things in Healthcare System: A Survey
Authors: Subhan Fazli , Mirza Alina , Su’ud Mazliham Bin Mohd , Alam Muhammad Mansoor , Nisar Shibli , Habib Usman , Iqbal Muhammad Zubair
Published: January 2023

Technology has played a vital part in improving quality of life, especially in healthcare. Artificial intelligence (AI) and the Internet of Things (IoT) are extensively employed to link accessible medical resources and deliver dependable and effective intelligent healthcare. Body wearable devices have garnered attention as powerful devices for healthcare applications, leading to various commercially available devices for multiple purposes, including individual healthcare, activity alerts, and fitness. The paper aims to cover all the advancements made in the wearable Medical Internet of Things (IoMT) for healthcare systems, which have been scrutinized from the perceptions of their efficacy in detecting, preventing, and monitoring diseases in healthcare. The latest healthcare issues are also included, such as COVID-19 and monkeypox. This paper thoroughly discusses all the directions proposed by the researchers to improve healthcare through wearable devices and artificial intelligence. The approaches adopted by the researchers to improve the overall accuracy, efficiency, and security of the healthcare system are discussed in detail. This paper also highlights all the constraints and opportunities of developing AI enabled IoT-based healthcare systems.
IWGAN: Anomaly Detection in Airport Based on Improved Wasserstein Generative Adversarial Network
Authors: Huang Ko-Wei , Chen Guan-Wei , Huang Zih-Hao , Lee Shih-Hsiung
Published: January 2023

Anomaly detection is an important research topic in the field of artificial intelligence and visual scene understanding. The most significant challenge in real-world anomaly detection problems is the high imbalance of available data (i.e., non-anomalous versus anomalous data). This limits the use of supervised learning methods. Furthermore, the abnormal—and even normal—datasets in the airport field are relatively insufficient, causing them to be difficult to use to train deep neural networks when conducting experiments. Because generative adversarial networks (GANs) are able to effectively learn the latent vector space of all images, the present study adopted a GAN variant with autoencoders to create a hybrid model for detecting anomalies and hazards in the airport environment. The proposed method, which integrates the Wasserstein-GAN (WGAN) and Skip-GANomaly models to distinguish between normal and abnormal images, is called the Improved Wasserstein Skip-Connection GAN (IWGAN). In the experimental stage, we evaluated different hyper-parameters—including the activation function, learning rate, decay rate, training times of discriminator, and method of label smoothing—to identify the optimal combination. The proposed model’s performance was compared with that of existing models, such as U-Net, GAN, WGAN, GANomaly, and Skip-GANomaly. Our experimental results indicate that the proposed model yields exceptional performance.
Projected Rainfall Triggered Landslide Susceptibility Changes in the Hengduan Mountain Region, Southwest China under 1.5–4.0 °C Warming Scenarios Based on CMIP6 Models
Authors: Yin Huaxiang , Zhang Jiahui , Mondal Sanjit Kumar , Wang Bingwei , Zhou Lingfeng , Wang Leibin , Lin Qigen
Published: January 2023

Landslides are one of the most prevalent environmental disasters in the Hengduan Mountain Region. Landslides lead to severe economic damage and property loss, as well as fatalities. Furthermore, they tend to increase in the context of climate change. The purpose of this study is to comprehensively assess landslide susceptibility across the Hengduan Mountain Region in southwest China. Specifically, the analysis is focused on the eastern boundary of the Tibetan Plateau within the context of future climate change scenarios, which are based on the latest Coupled Model Intercomparison Project Phase 6 (CMIP6) global climate model ensemble. The Generalized Additive Model (GAM), Random Forest (RF), and Light Gradient Boosting Machine (LightGBM) were selected in order to map landslide susceptibility within the context of 1.5–4.0 °C warming scenarios. This was achieved by considering the changes in extreme rainfall that exceeded the landslide triggering thresholds. The results show that the frequency over extreme rainfall thresholds (FOERT) tend to increase in conjunction with warming targets, thereby ranging from 2.3/a (at a 1.5 °C warming) to 9.0/a (at a 4.0 °C warming) on average. Such elevated extreme precipitation events contribute to an increase in projected future zones of high landslide susceptibility when compared to the historical baseline period ranging from −1.2% (at a 1.5 °C warming) to 4.0% (at a 4.0 °C warming) using different machine learning models. Moreover, the extent of high susceptibility zones increases more significantly in the context of 4.0 °C warming when compared to the historical baseline results. These results indicate the importance of limiting the global temperature rise to 1.5 as well as 2 °C. The high landslide susceptibility zones estimated by the CMIP6 multi-models ensemble are mainly located in the central and southeastern regions of the Hengduan Mountain Region. The possible changes in terms of introducing extreme precipitation in order to assess landslide susceptibility in the context of climate change that is proposed in this study may be further applied to additional study areas. These projections under different targets can provide scientific guidelines for the purposes of the development of climate change adaptation strategies.
On the Impact of GPS Multipath Correction Maps and Post-Fit Residuals on Slant Wet Delays for Tracking Severe Weather Events
Authors: Hunegnaw Addisu , Duman Hüseyin , Ejigu Yohannes Getachew , Baltaci Hakki , Douša Jan , Teferle Felix Norman
Published: January 2023

Climate change has increased the frequency and intensity of weather events with heavy precipitation, making communities worldwide more vulnerable to flash flooding. As a result, accurate fore- and nowcasting of impending excessive rainfall is crucial for warning and mitigating these hydro-meteorological hazards. The measurement of integrated water vapour along slant paths is made possible by ground-based global positioning system (GPS) receiver networks, delivering three-dimensional (3D) water vapour distributions at low cost and in real-time. As a result, these data are an invaluable supplementary source of knowledge for monitoring storm events and determining their paths. However, it is generally known that multipath effects at GPS stations have an influence on incoming signals, particularly at low elevations. Although estimates of zenith total delay and horizontal linear gradients make up the majority of the GPS products for meteorology to date, these products are not sufficient for understanding the full 3D distribution of water vapour above a station. Direct utilization of slant delays can address this lack of azimuthal information, although, at low elevations it is more prone to multipath (MP) errors. This study uses the convective storm event that happened on 27 July 2017 over Bulgaria, Greece, and Turkey, which caused flash floods and severe damage, to examine the effects of multipath-corrected slant wet delay (SWD) estimations on monitoring severe weather events. First, we reconstructed the one-way SWD by adding GPS post-fit phase residuals, describing the anisotropic component of the SWD. Because MP errors in the GPS phase observables can considerably impact SWD from individual satellites, we used an averaging technique to build station-specific MP correction maps by stacking the post-fit phase residuals acquired from a precise point positioning (PPP) processing strategy. The stacking was created by spatially organizing the residuals into congruent cells with an optimal resolution in terms of the elevation and azimuth at the local horizon.This enables approximately equal numbers of post-fit residuals to be distributed across each congruent cell. Finally, using these MP correction maps, the one-way SWD was improved for use in the weather event analysis. We found that the anisotropic component of the one-way SWD accounts for up to 20% of the overall SWD estimates. For a station that is strongly influenced by site-specific multipath error, the anisotropic component of SWD can reach up to 4.3 mm in equivalent precipitable water vapour. The result also showed that the spatio-temporal changes in the SWD as measured by GPS closely reflected the moisture field estimated from a numerical weather prediction model (ERA5 reanalysis) associated with this weather event.
Do Patients Aged 85 Years and above Benefit from Their Cochlear Implants?
Authors: Hallin Karin , Larsson Ulrika , Schart-Morén Nadine
Published: January 2023

The present study aims to investigate the usage and benefits of cochlear implants (CIs) in elderly patients aged ≥85 years, including their device-handling issues, follow-ups, and the influence on their well-being. The patients answered one questionnaire regarding quality of life, EQ5D-3L, and one questionnaire, obtained from the Swedish CI quality register, regarding usage, handling, satisfaction, remaining difficulties, etc. The medical records were searched for the implantation date, implant model, speech processor model, monosyllabic (MS) word scores, infections over the implant, and compliance regarding scheduled visits to the clinic. The results show that most elderly patients are satisfied full-time users of their implants. Even though most patients had no problems handling their CI, handling issues must be considered. Recurring guidance and training on device operation are needed. We suggest that follow-up visits are essentially needed for this group of patients on a regular basis. CI surgery is considered a safe treatment, even for the elderly. Upgrads to new external equipment (e.g., sound processors) should not be excluded because of their age. The results suggested that the CI positively affected their well-being. This study was approved by the Swedish Ethical Review Authority (5/10-2021, Dnr: 2021-04970).
The Gut Microbiota in Kidney Transplantation: A Target for Personalized Therapy?
Authors: García-Martínez Yuselys , Borriello Margherita , Capolongo Giovanna , Ingrosso Diego , Perna Alessandra F.
Published: January 2023

Kidney transplantation improves quality of life, morbidity, and mortality of patients with kidney failure. However, integrated immunosuppressive therapy required to preserve graft function is associated with the development of post-transplant complications, including infections, altered immunosuppressive metabolism, gastrointestinal toxicity, and diarrhea. The gut microbiota has emerged as a potential therapeutic target for personalizing immunosuppressive therapy and managing post-transplant complications. This review reports current evidence on gut microbial dysbiosis in kidney transplant recipients, alterations in their gut microbiota associated with kidney transplantation outcomes, and the application of gut microbiota intervention therapies in treating post-transplant complications.
Microfluidics for COVID-19: From Current Work to Future Perspective
Authors: Li Qi , Zhou Xingchen , Wang Qian , Liu Wenfang , Chen Chuanpin
Published: January 2023

Spread of coronavirus disease 2019 (COVID-19) has significantly impacted the public health and economic sectors. It is urgently necessary to develop rapid, convenient, and cost-effective point-of-care testing (POCT) technologies for the early diagnosis and control of the plague’s transmission. Developing POCT methods and related devices is critical for achieving point-of-care diagnosis. With the advantages of miniaturization, high throughput, small sample requirements, and low actual consumption, microfluidics is an essential technology for the development of POCT devices. In this review, according to the different driving forces of the fluid, we introduce the common POCT devices based on microfluidic technology on the market, including paper-based microfluidic, centrifugal microfluidic, optical fluid, and digital microfluidic platforms. Furthermore, various microfluidic-based assays for diagnosing COVID-19 are summarized, including immunoassays, such as ELISA, and molecular assays, such as PCR. Finally, the challenges of and future perspectives on microfluidic device design and development are presented. The ultimate goals of this paper are to provide new insights and directions for the development of microfluidic diagnostics while expecting to contribute to the control of COVID-19.
The Nature of Paired Associate Learning Deficits in Chinese Children with Developmental Dyslexia
Authors: Yang Ting , Cai Yan , Liu Hong , Liu Xiangping
Published: January 2023

Previous studies have found that individuals with dyslexia perform poorly in paired associate learning (PAL) tasks, which were explained by a deficit in cross-modal association or verbal demand in alphabetic language. However, the nature of PAL deficits in non-alphabetic languages remains unclear. In this study, we conducted PAL and priming tasks in visual–visual, visual–verbal, verbal–visual, and verbal–verbal conditions to dissociate the cross-modal and verbal demands in Chinese children with dyslexia. In Experiment 1, children with dyslexia performed worse in verbal-involved PAL (visual–verbal, verbal–visual, and verbal–verbal) than the control children. Experiment 2 revealed that children with dyslexia performed better than the control children in the verbal–visual condition. Our results suggest that children with dyslexia have an intact ability to form cross-modal associations, which also implies that phonological deficits might be the key to PAL deficits in Chinese children with dyslexia.