bluuebunny/crossref_metadata_2025 huggingface dataset:
Open farmland is a hotspot of soil fauna community around facility farmland during a cold wave event
Authors: Gao Meixiang , Jiang Yige , Sun Jiahuan , Lu Tingyu , Zheng Ye , Lai Jiangshan , Liu Jinwen
Published: October 2023

In the future, the frequency, duration, and intensity of extreme weather may increase, thus posing a threat to soil biodiversity in farmlands, particularly in agricultural production bases. However, little is known about the effect of cold wave events on the soil fauna community compared with other extreme weathers. Laboratory experiments fail to capture the complicated field environment of cold wave events. We investigated soil fauna communities in facility farmland (strawberry) and open farmland (green cabbage) during a cold wave event in Ningbo City, southeastern China. The results showed that the taxonomic richness of the total soil fauna community in facility farmland was significantly lower than that in open farmland, but the difference in abundance was not significant. The taxonomic richness and body size of soil mites and collembolan communities in facility farmland were significantly lower than those in the open farmland. Obvious differences in abundance, mean body length, mean body width, and ratio of body width to body length of Scheloribatidae, Galumnidae, Onychiuridae, Entomobryidae, and Enchytraeidae were detected between facility farmland and open farmland. The results of this study showed that the taxonomic richness, abundance, and body size of the soil fauna community in open farmland were significantly higher than those in facility farmland during a cold wave event. We suggested that the open farmland could be a “refuge” and “hot spot” of soil fauna community during the cold wave events.
Lessons Learned in Transcribing 5000 h of Air Traffic Control Communications for Robust Automatic Speech Understanding
Authors: Zuluaga-Gomez Juan , Nigmatulina Iuliia , Prasad Amrutha , Motlicek Petr , Khalil Driss , Madikeri Srikanth , Tart Allan , Szoke Igor , Lenders Vincent , Rigault Mickael , Choukri Khalid
Published: October 2023

Voice communication between air traffic controllers (ATCos) and pilots is critical for ensuring safe and efficient air traffic control (ATC). The handling of these voice communications requires high levels of awareness from ATCos and can be tedious and error-prone. Recent attempts aim at integrating artificial intelligence (AI) into ATC communications in order to lessen ATCos’s workload. However, the development of data-driven AI systems for understanding of spoken ATC communications demands large-scale annotated datasets, which are currently lacking in the field. This paper explores the lessons learned from the ATCO2 project, which aimed to develop an unique platform to collect, preprocess, and transcribe large amounts of ATC audio data from airspace in real time. This paper reviews (i) robust automatic speech recognition (ASR), (ii) natural language processing, (iii) English language identification, and (iv) contextual ASR biasing with surveillance data. The pipeline developed during the ATCO2 project, along with the open-sourcing of its data, encourages research in the ATC field, while the full corpus can be purchased through ELDA. ATCO2 corpora is suitable for developing ASR systems when little or near to no ATC audio transcribed data are available. For instance, the proposed ASR system trained with ATCO2 reaches as low as 17.9% WER on public ATC datasets which is 6.6% absolute WER better than with “out-of-domain” but gold transcriptions. Finally, the release of 5000 h of ASR transcribed speech—covering more than 10 airports worldwide—is a step forward towards more robust automatic speech understanding systems for ATC communications.
In Vitro Antimicrobial Activity of Plant Species against the Phytopathogens Ralstonia solanacearum, Phytophthora infestans, and Neopestalotiopsis javaensis
Authors: Ordóñez Yadira F. , Ruano Josué , Avila Pamela , Berutti Lennys , Guerrero Paola Chavez , Ordóñez Paola E.
Published: October 2023

Plants are prone to be attacked by various pathogenic microorganisms, leading to significant crop yield losses. Pesticides are used to control agricultural pathogens; however, frequently, they are toxic synthetic products. This work evaluated the antibacterial and antifungal activity of Pernettya prostrata, and Rubus roseus plant extracts against three phytopathogens Ralstonia solanacearum, Phytophthora infestans, and Neopestalotiopsis javaensis responsible for causing banana bacterial wilt, late blight y scab diseases, respectively. The extracts were obtained in methanol. The phytopathogens were isolated from diseased plants grown in Ecuador, R. solanacearum was isolated from samples of Musa paradiasiaca, P. infestans from samples of Solanum lycopersicum and N. javaensis from diseased samples of Persea americana—morphological and molecular methods identified the isolated pathogens. The antibacterial activity was determined by the microtiter broth dilution method; six serial concentrations of the extracts were tested. The antifungal activity was determined based on the effects of the plant extracts on the inhibition of radial growth of fungi; five serial concentrations of the extracts were tested. The extracts of P. prostrata and R. roseus showed activity against R. solanacearum and P. infestans with a MIC of 22.5 and 31.25 mg/mL, respectively.
Improving Farmer Livelihood Resilience to Climate Change in Rural Areas of Inner Mongolia, China
Authors: Han Zhiying , Youn Yeo-Chang , Kim Seunguk , Choe Hyeyeong
Published: October 2023

This study evaluates how resilient farmers’ livelihoods are to climate change and what factors influence this resilience. To measure resilience, we constructed an indicator system based on the livelihood resilience analysis framework. We surveyed 42 experts and 630 farmers after a climate change disturbance in Aohan Banner, Inner Mongolia, from August to October 2021, and analyzed these data using the comprehensive index method. Meanwhile, we used a multiple linear regression model to analyze the key factors affecting farmer livelihood resilience across different livelihood types and towns. We found that farmers who primarily worked in agriculture had the highest resilience scores and that livelihood resilience differed by geographical location; specifically, livelihood resilience gradually declines from southern to northern areas and from forest and forest-grassland to grassland locations. The results also show that education level, agricultural technology training, transportation infrastructure, accessibility of information, awareness of climate change, climate change perception, change in livelihood strategies, family size, and the holding size of the arable area are positively associated with farmer livelihood resilience, while household head age is negatively associated with resilience. We therefore advise that policymakers should diversify agricultural livelihoods, afforest surrounding arable areas, improve transportation infrastructure, increase learning activities and skill training for farmers, and publicize climate change knowledge.
Thermal Balance in Male Water Buffaloes Transported by Long and Short Journeys
Authors: Rodríguez-González Daniela , Guerrero Legarreta Isabel , Chay-Canul Alfonso , Hernández-Avalos Ismael , Napolitano Fabio , García-Herrera Ricardo , Pereira Alfredo M. F. , Domínguez-Oliva Adriana , Casas-Alvarado Alejandro , Reyes-Sotelo Brenda , Mota-Rojas Daniel
Published: October 2023

Transport is a stressor that can cause physiological and metabolic imbalances in livestock, resulting in stress-induced hyperthermia. In water buffaloes, studies regarding the thermal state of animals during mobilization are scarce. Therefore, this study aimed to compare the thermal response of 1516 water buffaloes using infrared thermography (IRT) during 15 short trips (783 animals, 60,291 records, average duration = 50.33 min ± 5.48 min) and 14 long trips (733 animals, 56,441 records, average duration = 13.31 h ± 47.32 min). The surface temperature was assessed in 11 regions (periocular, lacrimal caruncle, nasal, lower eyelid, auricular, frontal-parietal, pelvic limb, torso, abdominal, lumbar, and thoracic) during seven phases from pasture to post-transport. It was found that the surface temperature of the periocular, lacrimal caruncle, nasal, auricular, frontal-parietal, pelvic limb, torso, abdominal, lumbar, and thoracic regions was significantly higher during SJs (+3 °C) when compared to LJs (p < 0.0001). In particular, the frontal-parietal region had a significant increase of 10 °C during the post-transport phase (p < 0.0001) in both groups, recording the highest temperatures during this phase. Likewise, a strong positive significant correlation between the different regions was found (r = 0.90, p < 0.0001). It is worth mentioning that the herding, loading, pre-, and post-transport phases were the ones where the greatest thermal response was recorded, possibly due to the influence of human interaction. Finally, a strong positive correlation (r above 0.9, p > 0.001) between the periocular, lacrimal caruncle, pinna, and pelvic limb was found. According to the results, SJ could be considered a stressful event that hinders thermal generation, contrarily to LJ.
Tenuipalpus Sensu Lato Donnadieu (Acari: Prostigmata: Tenuipalpidae); New Species Groups, a New Species, and Keys to the World Species
Authors: Elgoni Nasreldeen Ahmed , Kamran Muhammad , Alatawi Fahad Jaber
Published: October 2023

Four new species groups of the Tenuipalpus sensu lato group are proposed in the present study based on the total number of dorsal opisthosomal setae, namely, carolinensis with ten pairs of setae (214 species), dubinini with nine pairs of setae (33 species), granati with eight pairs of setae (29 species), and barticanus with seven pairs of setae (7 species) Additionally, diagnostic keys to species groups and 273 species of the Tenuipalpus sensu lato are provided. Three species, T. lustrabilis Chaudhri, T. guptai Sadana and Gupta, and T. solanensis Sadana and Gupta, are synonymized with T. punicae Pritchard and Baker. One species, T. rodionovi Chalilova, is suggested as a junior synonym of T. granati Sayed, and eight species, T. chiococcae De Leon, T. costarricensis Salas and Ochoa, T. ephedrae Livschitz and Mitrofanov, T. molinai Evans, T. santae Manson, T. simplychus Cromroy, T. tetrazygiae De Leon, and T. oxalis (Flechtmann), belonging to the carolinensis species group, are not included in the key. Furthermore, a new species of Tenuipalpus sensu lato, T. jazanensis sp. nov., is described and illustrated based on females collected from the Chamaerops spp. (Arecaceae).
An Update in Knowledge of Pigs as the Source of Zoonotic Pathogens
Authors: Augustyniak Agata , Pomorska-Mól Małgorzata
Published: October 2023

The available data indicate that the human world population will constantly grow in the subsequent decades. This constant increase in the number of people on the Earth will lead to growth in food demand, especially in food of high nutritional value. Therefore, it is expected that the world livestock population will also increase. Such a phenomenon enhances the risk of transmitting pathogens to humans. As pig production is one of the most significant branches of the world’s livestock production, zoonoses of porcine origins seem to be of particular importance. Therefore, in this review, we aim to introduce the latest data concerning, among other things, epidemiology and available preventive measures to control the most significant porcine zoonoses of viral, bacterial, and parasitic origin.
Artemisia brevifolia Wall. Ex DC Enhances Cefixime Susceptibility by Reforming Antimicrobial Resistance
Authors: Zafar Aroosa , Wasti Yusra , Majid Muhammad , Muntaqua Durdana , Bungau Simona Gabriela , Haq Ihsan ul
Published: October 2023

(1) Background: A possible solution to antimicrobial resistance (AMR) is synergism with plants like Artemisia brevifolia Wall. ex DC. (2) Methods: Phytochemical quantification of extracts (n-hexane (NH), ethyl acetate (EA), methanol (M), and aqueous (Aq)) was performed using RP-HPLC and chromogenic assays. Extracts were screened against resistant clinical isolates via disc diffusion, broth dilution, the checkerboard method, time–kill, and protein quantification assays. (3) Results: M extract had the maximum phenolic (15.98 ± 0.1 μg GAE/mgE) and flavonoid contents (9.93 ± 0.5 μg QE/mgE). RP-HPLC displayed the maximum polyphenols in the M extract. Secondary metabolite determination showed M extract to have the highest glycosides, alkaloids, and tannins. Preliminary resistance profiling indicated that selected isolates were resistant to cefixime (MIC 20–40 µg/mL). Extracts showed moderate antibacterial activity (MIC 60–100 µg/mL). The checkerboard method revealed a total synergy between EA extract and cefixime with 10-fold reductions in cefixime dose against resistant P. aeruginosa and MRSA. Moreover, A. brevifolia extracts potentiated the antibacterial effect of cefixime after 6 and 9 h. The synergistic combination was non- to slightly hemolytic and could inhibit bacterial protein in addition to cefixime disrupting the cell wall, thus making it difficult for bacteria to survive. (4) Conclusion: A. brevifolia in combination with cefixime has the potential to inhibit AMR.
Special Issue “Biogas as Renewable Energy Source”
Authors: Pilarska Agnieszka A. , Pilarski Krzysztof
Published: October 2023

With the development of civilisation, the demand for energy is increasing [...]
Temporomandibular Disorders and Serological Tests in Patients with Rheumatoid Arthritis
Authors: d’Apuzzo Fabrizia , Rotolo Rossana Patricia , Fordellone Mario , Cuomo Giovanna , Jamilian Abdolreza , Nucci Ludovica , Grassia Vincenzo
Published: October 2023

Background: Rheumatoid Arthritis (RA) is a systemic and chronic autoimmune disease with inflammation at the synovial joints. The purposes of this study were to evaluate the correlation between serological variables and temporomandibular disorders (TMDs) in patients diagnosed with RA, evaluated through diagnostic criteria for temporomandibular disorders (DC/TMD), and to check the influence of comorbidities on the different TMD signs and symptoms, or any serological variables. Methods: This observational cohort research study included seventeen patients affected by RA. The comorbidities and some variables from the initial serological analyses were collected from the clinical rheumatological charts. Then, the presence of any of the following TMD signs/symptoms, temporal myalgia, temporomandibular joint arthralgia, click or crepitus, was evaluated through the symptom questionnaire of the DC/TMD during clinical evaluation following the DC/TMD examination form. Results: Rheumatoid factor (RF), anticitrullinated protein antibodies (ACPA), and anti-nuclear antibody (ANA) positivity were present in 82.4%, 52.9%, and 41.2% of patients, respectively. Indicators of tissue inflammation were evaluated with median values of 21 mm/h for erythrocyte sedimentation rate (ESR) and 0.50 mg/dL for C-reactive protein (CRP). The RA patients presented comorbidities such as hypertension in 70.6% and diabetes in 23.5%. Negative ACPA had a significant association with myalgia (p = 0.03), and positive ANA was significantly associated with crepitus (p = 0.05). Conclusion: ANA and ACPA evaluation can be considered predictive serological tests associated with specific TMDs. Conversely, no influence of any comorbidities was found between different TMD signs and symptoms, or any serological variables.
Source Apportionment of Atmospheric Aerosols in Kraków, Poland, before and during the COVID-19 Pandemic at a Traffic Monitoring Station
Authors: Samek Lucyna , Ryś Anna , Dudek Jan , Stęgowski Zdzisław , Martins Vânia , Almeida Susana Marta , Styszko Katarzyna
Published: October 2023

PM10 samples were collected at the Kraków air quality traffic monitoring station during two periods: February–May 2018 and February–June 2020. The PM10 concentrations dropped by 50% from 74 ± 29 µg/m3 to 37 ± 13 µg/m3 in 2018 and 2020, respectively. The elemental concentrations were determined by the energy-dispersive X-ray fluorescence (EDXRF) method, and the ion concentrations were determined by ion chromatography (IC). The concentration ratios in 2018 to 2020 were greater than 1.7 for the following elements: S, Cl, K, Zn, Br, and the ions SO42−, Na+, and NH4+. Similar concentrations were observed in 2018 and 2020 for the following chemical species: Ca, Ti, Mn, Ni, Rb, Sr, K+, Mg2+, Ca2+, and PO43−. The Cr concentration was higher in 2020 compared to 2018. Four source profiles were obtained from the PMF (Positive Matrix Factorization) modelling. The following sources were attributed to this: solid fuel combustion, secondary inorganic aerosols, traffic/industry/construction work, and soil. The contributions of solid fuel combustion and secondary inorganic aerosols (SIA) were significantly lower in February and March 2020 than in February and March 2018. The relative differences were in the range 70–98%. Traffic/industry/construction work contributions were 6% and 36% lower in March and May 2020 compared to the same months in 2018, respectively. Two factors affected the characteristics of PM10: one was the ban of using coal and wood for heating purposes introduced in Krakow in September 2019, observed mainly in February and March, and the COVID-19 pandemic that was observed mainly in April and May.
Buckling Resistance of Tapered Steel Columns
Authors: Dokšanović Tihomir , Radić Ivan , Biserčić Bojan
Published: October 2023

Tapered steel members are widely used in structural and architectural engineering for their efficiency and adaptability, allowing for optimal material usage tailored to specific load levels. However, their complex stability characteristics have hindered their representation in modern design standards like EN 1993 and AISC 360. Existing buckling solutions are limited, and practical research is lacking. This paper comprehensively examines the buckling resistance calculation methodologies for members with variable cross-sections, addressing discrepancies across the methodologies, particularly regarding the tapering ratio. A parametric analysis and numerical simulations were conducted to evaluate each methodology’s applicability, emphasizing the need to balance computational simplicity and accuracy. The study primarily focused on tapered steel beams, considering the different tapering ratios and loading conditions. The findings provide valuable insights into the buckling behavior in tapered members and the practical implications for real-world structural designs. By examining the available analytical methods for calculating the buckling resistance of tapered elements, a better understanding of how to accommodate the non-uniformity of a member was gained, enabling an overview of the variance in the determined resistances and an assessment of the method’s applicability. Moreover, specific calculation methodologies were found to have shortcomings that require modifications for a more accurate parametric analysis. This research contributes to the field by bridging the gaps in modern design standards and enhancing the understanding of buckling in tapered steel members.
Experimental Investigation on Effect of Temperature on FDM 3D Printing Polymers: ABS, PETG, and PLA
Authors: Mendenhall Ryan , Eslami Babak
Published: October 2023

Four-dimensional printing is a process in which a 3D-printed object is intentionally transformed in response to an external stimulus such as temperature, which is useful when the final geometry of a 3D-printed part is not easily manufacturable. One method to demonstrate this is to print a part made of thin strips of material on a sheet of paper, heat the part, and allow it to cool. This causes the part to curl due to the difference in the thermal expansion coefficients of the paper and plastic. In an attempt to quantify the effect of different temperatures on various materials, samples of three common 3D printing filaments, acrylonitrile butadiene styrene (ABS), polyethylene terephthalate glycol (PETG), and polylactic acid (PLA), were heated at different temperatures (85 °C, 105 °C, and 125 °C) for intervals of 15 min and then allowed to cool until curling stopped. This heating and cooling cycle was repeated three times for each sample to determine if repeated heating and cooling influenced the curling. Each sample was filmed as it was cooling, which allowed the radius of curvature to be measured by tracking the uppermost point of the part, knowing the arc length, and calibrating the video based on a known linear length. After three cycles, all three materials showed a decrease in the radius of curvature (tighter curl) as heating temperature increased, with PLA showing the trend much more predominantly than ABS and PETG. Furthermore, for PETG and PLA, the radius of curvature decreased with each cycle at all temperatures, with the decrease being more significant from cycle 1 to 2 than cycle 2 to 3. Conversely, ABS only shared this trend at 125 °C. The findings of this work can provide guidelines to users on the temperature dosage for the mass manufacturing of complex geometries such as packaging, self-assembly robots, and drug delivery applications.
Digging Performance and Stress Characteristic of the Excavator Bucket
Authors: Sun Yuan , Wang Yong , Wang Linlin , Li Chenchen , Tang Liang , Wang Dagang , Ma Ruiyong , Xue Ziao , Wei Xuefeng , Cui Muchun , Chong Hailang , Xu Wei
Published: October 2023

In this study, a dynamic–discrete element-finite element coupling method is proposed to investigate the influence of structural parameters on the excavation performance and stress deformation of the bucket. The main research work is as follows: through ADAMS-EDEM co-simulation of the digging process of the bucket, the digging resistance and the loose force of each part of the bucket are obtained. The influence law of the change of the structural parameters of the excavator bucket on the digging resistance, filling rate and energy consumption is revealed. Through the coupling simulation of EDEM-ANSYS, the loose force is introduced into the finite element model of the bucket to enable the coupling of ADAMS-EDEM-ANSYS. The influence of the change of the bucket structure parameters on the stress and deformation of the bucket components is explored. The results show that the cutting angle and angle of throat of the bucket has a major influence on the digging performance of the bucket. While the angle of the throat and the thickness of the ear plate have a minor influence on the digging performance of the bucket. In the process of excavation, the teeth of the bucket are subjected to the largest digging resistance, resulting in relatively large deformation. All of the components of the bucket are subjected to different degrees of excavation resistance, but the stress concentration at the ear plate is the most obvious. The deformation and stress of the whole bucket can be reduced, to some extent, by reducing the thickness of the ear plate along with increasing the thickness of the stiffening plate. The results can be used to improve the digging performance of the bucket and reduce the stress and deformation of the bucket.
Research on Optimization Design of Tunnel Blasting Scheme Adjacent to Buildings
Authors: Ren Kuan , Jiang Annan , Guo Xinping , Min Qinghua
Published: October 2023

The section of Jialingjiang Road Station to Xiangjiang Road Station along Qingdao Metro Line 13 is located in Qingdao, China. All of them show obvious characteristics, being soft on the top and hard on the bottom, and the interval tunnel is faced with the problem of existing adjacent buildings. In order to ensure the smooth progress of construction, as well as minimize the damage to the buildings, a new mechanical excavation combined with a blasting construction scheme for the adjacent buildings is proposed. In this scheme, the step method is used for excavation. The upper step is in the weak stratum, and the mechanical method is therefore used for excavation; the lower step is in the hard stratum, and the drilling-and-blasting method is thus used for excavation. Using FLAC3D 5.0 finite difference software and the method based on blasting an equivalent load, the vibration velocity at adjacent buildings caused by the combined mechanical excavation and blasting scheme, as well as the traditional full-section blasting scheme, is compared and analyzed. Further, the construction parameters of the combined mechanical excavation and blasting scheme are compared and selected based on building settlement, the plastic zone of surrounding rocks, building vibration velocity and other factors. The results show that under the mechanical excavation blasting scheme, the peak particle velocity of each monitoring point decreases significantly compared with that under the full-section blasting scheme, with a maximum reduction of 61.1%, which is within the allowable range of the project, demonstrating the rationality of the new scheme. Finally, the mechanical excavation advance in the upper step is determined as 0.5 m. The optimized parameter construction effect is monitored and evaluated, the problems encountered in the project are successfully solved using the combined mechanical excavation and blasting scheme, and the expected construction period is shortened by 3 months, which shows the rationality of the blasting construction scheme proposed and its parameters, as well as the validity of the calculation results. The research results can be used as a reference for the construction scheme design of similar projects.
Experimental Research and Numerical Analysis of Marine Oil Leakage and Accidental Ignition in Fishing Vessels
Authors: Li Na , Zhang Bin , Liu Xiaolei , Wang Kan , Wang Hao
Published: October 2023

The hazard of highly combustible marine oil leakage greatly increases fishing vessel operation risks. This research integrates an experiment to explore the coupling mechanism of a typical heated surface of an engine room as a source to ignite marine oil. A numerical model is established that depicts the dynamic process of and variations in the combined effects regarding multiple factors of oil ignition under actual experiment. The leaked marine oil is ignited with a heated surface, relevant models are applied to reproduce the results, and the influences of specific parameters of a fishing vessel’s engine room are analyzed. The results indicate that the leaked oil boils violently on the heated surface, and a vapor film forms on the oil surface. Increased heated-surface temperatures lead to a significant difference in the initial ignition occurrences of marine oil, and the distance between the ignition height and oil is closely related to the engine room environment. The ignition probability of marine oil shows a gradually increasing trend with elevated heated-surface temperatures. The ignition height presents a downward trend with the increase in the heated-surface temperature, while the engine room’s humidity in air inhibits the upward transfer of heat; however, the degree of inhibition is limited accordingly. The results evidence that this comparative work can be an effective approach to reveal the impacts of marine oil, heat source, ventilation velocity, and humidity on initial ignition characteristics. Additionally, this work provides a basis for setting up emergency planning with appropriate monitoring equipment and further preventing vessel fires due to oil–thermal ignition.
High-Efficiency Simulation of Dynamic Stability Derivatives Based on a Particle Swarm Optimization and Long Short-Term Memory Network (PSO-LSTM) Coupling Aerodynamic Model
Authors: Cheng Wenqi , Mi Baigang
Published: October 2023

A new high-efficiency method based on a particle swarm optimization and long short-term memory network is proposed in this study to predict the aerodynamic forces in an unsteady state. Based on the predicted aerodynamic forces, the dynamic derivative is further calculated. Using particle swarm optimization to optimize the hyper-parameters of a neural network, the long short-term memory network prediction model can be constructed according to the known simulating aerodynamic data to predict the aerodynamic performance of aircraft in unknown states. By coupling the least-squares method in an aerodynamic derivative model, the dynamic derivative can be quickly obtained. Unsteady motion of NACA 0012 airfoil was taken as the research example to verify this method, and its longitudinal combined dynamic derivatives were predicted and compared with CFD simulation results. The results show that the dynamic derivatives predicted by the PSO-LSTM method have high accuracy, with an error of no more than 1% compared to CFD, and a 70% improvement in efficiency. The method proposed in this study has good generalization ability and can realize fast and accurate prediction of dynamic derivatives with a small number of samples.
Evaluating the Performance of the Generalized Linear Model (glm) R Package Using Single-Cell RNA-Sequencing Data
Authors: Alaqeeli Omar , Alturki Raad
Published: October 2023

The glm R package is commonly used for generalized linear modeling. In this paper, we evaluate the ability of the glm package to predict binomial outcomes using logistic regression. We use single-cell RNA-sequencing datasets, after a series of normalization, to fit data into glm models repeatedly using 10-fold cross-validation over 100 iterations. Our evaluation criteria are glm’s Precision, Recall, F1-Score, Area Under the Curve (AUC), and Runtime. Scores for each evaluation category are collected, and their medians are calculated. Our findings show that glm has fluctuating Precision and F1-Scores. In terms of Recall, glm has shown more stable performance, while in the AUC category, glm shows remarkable performance. Also, the Runtime of glm is consistent. Our findings also show that there are no correlations between the size of fitted data and glm’s Precision, Recall, F1-Score, and AUC, except for Runtime.
iRoute—An Adaptive Route Planning Solution for Commercial Vehicle Fleets
Authors: Anghelache Florian , Marian Constantin Viorel , Mitrea Dan Alexandru , Goga Nicolae , Vasilateanu Andrei , Radulescu Vladut , Musat Daniel , Scurtu Diana
Published: October 2023

This article presents the results and conclusions of a research and development project for creating a commercial solution for vehicle fleets that will help businesses to have more adaptive routes optimized to the way they are running their businesses, local conditions, and drivers’ knowledge, avoiding road hazards known by drivers that frequently use the road path. Our solution consists of a data ingestion service from GPS devices, an integration layer with the end-customer applications, a route optimization engine, and two end-user applications: web and mobile. The solution presented in this article differs from other approaches as it uses historical route data to better adjust and optimize the final routes so that the results are more likely to be executed by drivers according to the initial criteria and plan in terms of distance and time. By using an innovative way of adjusting the optimized routes considering historical tracks, we obtained good results with up to a 20% improvement in terms of real executed distance and time versus standard optimizing algorithms. That means the business owners can better rely on the optimization process results, having access to a more realistic optimization plan that their drivers can easily follow.
Machine Learning for COVID-19 and Influenza Classification during Coexisting Outbreaks
Authors: Viana dos Santos Santana Iris , Sobrinho Álvaro , Dias da Silva Leandro , Perkusich Angelo
Published: October 2023

This study compares the performance of machine learning models for selecting COVID-19 and influenza tests during coexisting outbreaks in Brazil, avoiding the waste of resources in healthcare units. We used COVID-19 and influenza datasets from Brazil to train the Decision Tree (DT), Multilayer Perceptron (MLP), Gradient Boosting Machine (GBM), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), K-Nearest Neighbors, Support Vector Machine (SVM), and Logistic Regression algorithms. Moreover, we tested the models using the 10-fold cross-validation method to increase confidence in the results. During the experiments, the GBM, DT, RF, XGBoost, and SVM models showed the best performances, with similar results. The high performance of tree-based models is relevant for the classification of COVID-19 and influenza because they are usually easier to interpret, positively impacting the decision-making of health professionals.
Investigation of the Clinical Effectiveness and Prognostic Factors of Voice Therapy in Voice Disorders: A Pilot Study
Authors: Lee Ji-Yeoun , Park Ji-Hye , Lee Ji-Na , Jung Ah-Ra
Published: October 2023

Examining the relationship between the prognostic factors and the effectiveness of voice therapy is a crucial step in developing personalized treatment strategies for individuals with voice disorders. This study recommends using the multilayer perceptron model (MLP) to comprehensively analyze the prognostic factors, with various parameters, including personal habits and acoustic parameters, that can influence the effectiveness of before-and-after voice therapy in individuals with speech disorders. Various methods, including the assessment of personal characteristics, acoustic analysis, statistical analysis, binomial logistic regression analysis, and MLP, are implemented in this experiment. Accuracies of 87.5% and 85.71% are shown for the combination of optimal input parameters for female and male voices, respectively, through the MLP model. This fact validates the selection of input parameters when building our model. Good prognostic indicators for the clinical effectiveness of voice therapy in voice disorders are jitter (post-treatment) for females and MPT (pre-treatment) for males. The results are expected to provide a foundation for modeling research utilizing artificial intelligence in voice therapy for voice disorders. In terms of follow-up studies, it will be necessary to conduct research that utilizes big data to analyze the optimal parameters for predicting the clinical effectiveness of voice disorders.
UAV Image Small Object Detection Based on RSAD Algorithm
Authors: Song Jian , Yu Zhihong , Qi Guimei , Su Qiang , Xie Jingjing , Liu Wenhang
Published: October 2023

There are many small objects in UAV images, and the object scale varies greatly. When the SSD algorithm detects them, the backbone network’s feature extraction capabilities are poor; it does not fully utilize the semantic information in the deeper feature layer, and it does not give enough consideration to the little items in the loss function, which result in serious missing object detection and low object detection accuracy. To tackle these issues, a new algorithm called RSAD (Resnet Self-Attention Detector) that takes advantage of the self-attention mechanism has been proposed. The proposed RSAD algorithm utilises the residual structure of the ResNet-50 backbone network, which is more capable of feature extraction, in order to extract deeper features from UAV image information. It then utilises the SAFM (Self-Attention Fusion Module) to reshape and concatenate the shallow and deep features of the backbone network, selectively weighted by attention units, ensuring the efficient fusion of features to provide rich semantic features for small object detection. Lastly, it introduces the Focal Loss loss function, which adjusts the corresponding parameters to enhance the contribution of small objects to the detection model. The ablation experiments show that the mAP of RSAD is 10.6% higher than that of the SSD model, with SAFM providing the highest mAP enhancement of 7.4% and ResNet-50 and Focal Loss providing 1.3% and 1.9% enhancements, respectively. The detection speed is only reduced by 3FPS, but it meets the real-time requirement. Comparison experiments show that in terms of mAP, it is far ahead of Faster R-CNN, Cascade R-CNN, RetinaNet, CenterNet, YOLOv5s, and YOLOv8n, which are the mainstream object detection models; In terms of FPS, it slightly inferior to YOLOv5s and YOLOv8n. Thus, RSAD has a good balance between detection speed and accuracy, and it can facilitate the advancement of the UAV to complete object detection tasks in different scenarios.
Research on Scheme Design and Decision of Multiple Unmanned Aerial Vehicle Cooperation Anti-Submarine Based on Knowledge-Driven Soft Actor-Critic
Authors: Zhang Xiaoyong , Yue Wei , Tang Wenbin
Published: October 2023

To enhance the anti-submarine and search capabilities of multiple Unmanned Aerial Vehicle (UAV) groups in complex marine environments, this paper proposes a flexible action-evaluation algorithm known as Knowledge-Driven Soft Actor-Critic (KD-SAC), which can effectively interact with real-time environmental information. KD-SAC is a reinforcement learning algorithm that consists of two main components: UAV Group Search Knowledge Base (UGSKB) and path planning strategy. Firstly, based on the UGSKB, we establish a cooperation search framework that comprises three layers of information models: the data layer provides prior information and fundamental search rules to the system, the knowledge layer enriches search rules and database in continuous searching processes, and the decision layer utilizes above two layers of information models to enable autonomous decision-making by UAVs. Secondly, we propose a rule-based deductive inference return visit (RDIRV) strategy to enhance the knowledge base of search. The core concept of this strategy is to enable UAVs to learn from both successful and unsuccessful experiences, thereby enriching the search rules based on optimal decisions as exemplary cases. This approach can significantly enhance the learning performance of KD-SAC. The subsequent step involves designing an event-based UGSKB calling mechanism at the decision-making level, which calls a template based on the target and current motion. Finally, it uses a punishment function, and is then employed to achieve optimal decision-making for UAV actions and states. The feasibility and superiority of our proposed algorithm are demonstrated through experimental comparisons with alternative methods. The final results demonstrate that the proposed method achieves a success rate of 73.63% in multi-UAV flight path planning within complex environments, surpassing the other three algorithms by 17.27%, 29.88%, and 33.51%, respectively. In addition, the KD-SAC algorithm outperforms the other three algorithms in terms of synergy and average search reward.
Unraveling Microbial Endosymbiosis Dynamics in Plant-Parasitic Nematodes with a Genome Skimming Strategy
Authors: Wasala Sulochana K. , Hesse Cedar , Wram Catherine L. , Howe Dana K. , Zasada Inga A. , Denver Dee R.
Published: October 2023

Bacterial endosymbionts, in genera Wolbachia and Cardinium, infect various arthropods and some nematode groups. Manipulating these microbial symbionts presents a promising biocontrol strategy for managing disease-causing parasites. However, the diversity of Wolbachia and Cardinium in nematodes remains unclear. This study employed a genome skimming strategy to uncover their occurrence in plant-parasitic nematodes, analyzing 52 populations of 12 species. A metagenome analysis revealed varying endosymbiont genome content, leading to the categorization of strong, weak, and no evidence for endosymbiont genomes. Strong evidence for Wolbachia was found in five populations, and for Cardinium in one population, suggesting a limited occurrence. Strong Wolbachia evidence was noted in Pratylenchus penetrans and Radopholus similis from North/South America and Africa. Heterodera glycines from North America showed strong Cardinium evidence. Weak genomic evidence for Wolbachia was observed in Globodera pallida, Meloidogyne incognita, Rotylenchus reniformis, Pratylechus coffeae, Pratylenchus neglectus, and Pratylenchus thornei; for Cardinium was found in G. pallida, R. reniformis and P. neglectus; 27/52 populations exhibited no endosymbiont evidence. Wolbachia and Cardinium presence varied within nematode species, suggesting non-obligate mutualism. Wolbachia and Cardinium genomes differed among nematode species, indicating potential species-specific functionality. This study advances knowledge of plant-parasitic nematode–bacteria symbiosis, providing insights for downstream eco-friendly biocontrol strategies.
The Impact of Anthropogenic VOC Emissions on Atmospheric Pollution: A Case Study of a Typical Industrialized Area in China
Authors: Gao Xin , Wang Yanan , Wu Lin , Zheng Fangyuan , Sun Naixiu , Liu Guangxun , Liu Yongji , Meng Peng , Sun Luna , Jing Boyu
Published: October 2023

Volatile organic compounds (VOCs) are the main precursors of pollution from ground ozone (O3) and PM2.5, which cause the deterioration of urban air quality. The emissions of VOCs from industrialized areas are significant and their characteristics are complex, which nowadays contribute significantly to the challenges of investigating the emission inventory. Taking a typical industrialized area in Tianjin as a case study, the anthropogenic VOCs emission inventory for 2020 was established in this study by using the activity data from a large-scale survey and the latest emission factors. The impact of VOCs on the environment was analyzed from the perspective of the combined control of PM2.5 and O3. The results showed that the total emission of VOCs in 2020 was about 1.68 Gg, mainly from industrial processes and mobile sources, which accounted for 38.4% and 36.5% of the total emissions, respectively. The top 10 emitted VOCs were toluene, acetone, ethylbenzene, m/p-xylene, i-pentane, n-hexane, formaldehyde, benzene, ethyl acetate and ethylene. The dominant species of O3 formation potential (OFP) were almost all aromatic hydrocarbons and alkenes, with m/p-xylene contributing the most to the OFP emissions (8.90%). The top 10 secondary organic aerosols formation potential (SOAP) emission species were aromatic hydrocarbons and long-chain alkanes, and the largest emission came from toluene (39.9%). An analysis of an ADMS diffusion model showed that VOCs emitted from traffic-heavy main roads and industrialized central areas had the greatest impact on the air quality in the surrounding areas. The VOCs concentration was higher in winter due to unfavorable meteorological conditions. Our research updated the VOC inventory of industrialized areas and evaluated VOCs species reactivity and their impact on ambient air quality.
Regression Estimation with Errors in the Variables via the Laplace Transform
Authors: Guo Huijun , Bai Qingqun
Published: October 2023

This paper considers nonparametric regression estimation with errors in the variables. It is a standard assumption that the characteristic function of the covariate error does not vanish on the real line. This assumption is rather strong. In this paper, we assume the covariate error distribution is a convolution of uniform distributions, the characteristic function of which contains zeros on the real line. Our regression estimator is constructed via the Laplace transform. We prove its strong consistency and show its convergence rate. It turns out that zeros in the characteristic function have no effect on the convergence rate of our estimator.
A Time-Fractional Differential Inequality of Sobolev Type on an Annulus
Authors: Alshabanat Amal , Almoalim Eman , Jleli Mohamed , Samet Bessem
Published: October 2023

Several phenomena from natural sciences can be described by partial differential equations of Sobolev-type. On the other hand, it was shown that in many cases, the use of fractional derivatives provides a more realistic model than the use of standard derivatives. The goal of this paper is to study the nonexistence of weak solutions to a time-fractional differential inequality of Sobolev-type. Namely, we give sufficient conditions for the nonexistence or equivalently necessary conditions for the existence. Our method makes use of the nonlinear capacity method, which consists in making an appropriate choice of test functions in the weak formulation of the problem. This technique has been employed in previous papers for some classes of time-fractional differential inequalities of Sobolev-type posed on the whole space RN. The originality of this work is that the considered problem is posed on an annulus domain, which leads to some difficulties concerning the choice of adequate test functions.
Verification and Validation of Lower Body Negative Pressure as a Non-Invasive Bioengineering Tool for Testing Technologies for Monitoring Human Hemorrhage
Authors: Convertino Victor A. , Snider Eric J. , Hernandez-Torres Sofia I. , Collier James P. , Eaton Samantha K. , Holmes David R. , Haider Clifton R. , Salinas Jose
Published: October 2023

Since hemorrhage is a leading cause of preventable death in both civilian and military settings, the development of advanced decision support monitoring capabilities is necessary to promote improved clinical outcomes. The emergence of lower body negative pressure (LBNP) has provided a bioengineering technology for inducing progressive reductions in central blood volume shown to be accurate as a model for the study of the early compensatory stages of hemorrhage. In this context, the specific aim of this study was to provide for the first time a systematic technical evaluation to meet a commonly accepted engineering standard based on the FDA-recognized Standard for Assessing Credibility of Modeling through Verification and Validation (V&V) for Medical Devices (ASME standard V&V 40) specifically highlighting LBNP as a valuable resource for the safe study of hemorrhage physiology in humans. As an experimental tool, evidence is presented that LBNP is credible, repeatable, and validated as an analog for the study of human hemorrhage physiology compared to actual blood loss. The LBNP tool can promote the testing and development of advanced monitoring algorithms and evaluating wearable sensors with the goal of improving clinical outcomes during use in emergency medical settings.
Tissue-Specific Transcriptomes in the Secondary Cell Wall Provide an Understanding of Stem Growth Enhancement in Solidago canadensis during Invasion
Authors: Zhang Yu , Tian Zhongsai , Shi Jiaqi , Yu Ruoyu , Zhang Shuxin , Qiang Sheng
Published: October 2023

Invasive plants generally present a significant enhancement in aboveground vegetative growth, which is mainly caused by variation in secondary cell wall (SCW) deposition and vascular tissue development. However, the coordination of the transcriptional regulators of SCW biosynthesis is complex, and a comprehensive regulation map has not yet been clarified at a transcriptional level to explain the invasive mechanism of S. canadensis. Here, RNA sequencing was performed in the phloem and xylem of two typical native (US01) and invasive (CN25) S. canadensis populations with different stem morphologies. A total of 296.14 million high-quality clean reads were generated; 438,605 transcripts and 156,968 unigenes were assembled; and 66,648 and 19,510 differential expression genes (DEGs) were identified in the phloem and xylem, respectively. Bioinformatics analysis indicated that the SCW transcriptional network was dramatically altered during the successful invasion of S.canadensis. Based on a comprehensive analysis of SCW deposition gene expression profiles, we revealed that the invasive population is dedicated to synthesizing cellulose and reducing lignification, leading to an SCW with high cellulose content and low lignin content. A hypothesis thus has been proposed to explain the enhanced stem growth of S. canadensis through the modification of the SCW composition.