bluuebunny/crossref_metadata_2025 huggingface dataset:
Fungal Exposure and Shelter Assessment in Syrian Refugee Settlements in Lebanon
Authors: Alaouie Malek , Troisi Gera M. , Saliba Najat , Shaib Houssam , Hajj Rayan , El Hajj Rawan , Malak Sandy , Jakarian Carla , Jaafar Wiaam
Published: September 2023

Over 1 million Syrian refugees have fled war to seek asylum in Lebanon. The population has been placed in substandard conditions which could lead to adverse health effects, particularly in vulnerable subgroups, notably due to evident chronic dampness and inadequate ventilation potentially leading to indoor mold growth. To investigate whether the types and conditions of Syrian refugee shelters influence indoor mold populations, a cross-sectional indoor environmental study was performed in 4 provinces of Lebanon. Accordingly, a total of 80 refugee households and 20 host population households (baseline) were selected. Mold air sampling and moisture measurements of shelter material were performed in residential, non-residential, and non-permanent shelters. Results revealed that although non-residential shelters had the highest mean total indoor count (1112 CFU/m3), Aspergillus, Stachybotrys, and Penicillium spp. were strongly associated with non-permanent shelters (p < 0.001). Additionally, occupancy was found to be strongly associated with Cladosporium (p < 0.05), Ulocladium (p < 0.05), and Stachybotrys spp. (p < 0.001). As for shelter conditions, the highest total indoor count (1243 CFU/m3) was reported in unfinished structures. These findings suggest that shelter category, condition and occupancy significantly influence indoor mold concentrations, increasing respiratory health risks for Syrian refugees in Lebanon.
Molecular Breeding of Zheyou810, an Indica–Japonica Hybrid Rice Variety with Superior Quality and High Yield
Authors: Song Jian , Cui Yongtao , Fan Honghuan , Tang Liqun , Wang Jianjun
Published: September 2023

Rice heterosis has played a significant role in improving rice yields in China since the 1970s. The utilization of heterosis between the indica and japonica subspecies of rice is especially important in this regard. However, inter-subspecies hybridization between indica and japonica rice is hampered by the inadequate seed-setting rate and inferior rice quality of hybrid offspring, which has limited its development. The discovery and cloning of wide-compatibility gene S5-n and the granular starch synthase gene Wx have provided a solution to this problem, paving the way for the breeding of inter-subspecies hybrid rice. Here we demonstrated the breeding process of Zheyou810 and its performances in regional trials. Employing marker-assisted selection through the utilization of KASP (Kompetitive Allele-Specific PCR), a high-yielding and superior-quality indica–japonica hybrid rice variety named Zheyou810 was developed. Zheyou810 achieved an average yield of 10,737.75 kg/ha (12.58% higher than control Jiayou5) in the national regional trials across 2019 and 2020, and 11,777.25 kg/ha (13.36% higher than Jiayou5) in the production trial in 2020, respectively. The quality of rice has also been improved, reaching the standards set by the Ministry of Agriculture of the People’s Republic of China for Grade 3 premium rice (NY/T593). In 2021, Zheyou810 was approved by the national examination showing broad application prospects.
Spatial Characteristics and Driving Forces of the Water Footprint of Spring Maize Production in Northern China
Authors: Zhao Xueqing , Shi Jin , Liu Meixia , Zafar Saud Uz , Liu Qin , Mian Ishaq A. , Khan Bushra , Khan Shadman , Zhuang Yan , Dong Wenyi , Liu Enke
Published: September 2023

Using the water footprint (WF) approach to evaluate the water-use efficiency in agricultural production is crucial for assessing the sustainable use of water resources and mitigating water scarcity and pollution. This study calculated the blue, grey, green and total water footprints of spring maize production in Northeast China in 2019 and 2020 and compared the water footprint values at the provincial and municipal scales. In addition, this study analyzed the spatial variation and drivers of the water footprint. The results show that the average water footprints of spring maize production in Northeast China in 2019 and 2020 were 1.78 m3kg−1 and 2.00 m3kg−1, out of which the grey water footprint contributed the most, accounting for 55.19% and 49.85% of the total water footprint, respectively, while the blue water footprint contributed the least, accounting for only 17.44% and 18.68% of the total water footprint. At the provincial level, the water footprint of spring maize production in Northeast China was spatially clustered, with the lowest total water footprint in Heilongjiang Province and the highest total water footprint in Jilin Province. The spatial distribution difference of the spring maize unit yield was the fundamental factor explaining the difference in the water footprint. The precipitation, surface water resources, average temperature, effective irrigated area and the proportion of effective irrigated area also had impacts on the water footprint. This study provides a scientific basis for optimizing the distribution of spring maize production in Northeast China, formulating appropriate sustainable water resource management plans, improving water-use efficiency and realizing sustainable water resource management in Northeast China.
An Overview of the Impacts of Climate Change on Vineyard Ecosystems in Niagara, Canada
Authors: Tosato Diana Ribeiro , VanVolkenburg Heather , Vasseur Liette
Published: September 2023

Vineyards are agroecosystems of great importance in the Niagara Region, Ontario (Canada). Due to its microclimate, this region is projected to be impacted by climate change with temperature increases, changes in precipitation patterns in all seasons, and greater frequency of extreme weather events. The aim of this review paper is to summarize which seasonal changes are expected to occur in the Niagara Region and assess how such changes are likely to affect the main components of the vineyard ecosystem (i.e., soil, vines, invertebrates, and pathogens). It is expected that by 2080 the region will experience an increase in temperature in all four seasons; an increase in precipitation during the fall, winter, and spring; and a decrease in precipitation during summer months. Impacts of the projected changes will likely lead to vine water stress, yield loss, increases in incidents of diseases, increases in the spread of new pests, and changes in grape quality ultimately resulting in lower wine quality and/or production. Current management practices will need to be better understood and adaptive strategies introduced to enhance grape growers’ ability to minimize these impacts.
Edwardsiella tarda in Tambaqui (Colossoma macropomum): A Pathogenicity, Antimicrobial Susceptibility, and Genetic Analysis of Brazilian Isolates
Authors: Reis Francisco Yan Tavares , Rocha Victória Pontes , Janampa-Sarmiento Peter Charrie , Costa Henrique Lopes , Egger Renata Catão , Passos Naísa Cristine , de Assis Carlos Henrique Santos , Carneiro Sarah Portes , Santos Ágna Ferreira , Silva Brendhal Almeida , Dorella Fernanda Alves , Leibowitz Márcia Pimenta , Luz Ronald Kennedy , Pierezan Felipe , Gallani Sílvia Umeda , Tavares Guilherme Campos , Figueiredo Henrique César Pereira
Published: September 2023

Edwardsiella tarda is a crucial pathogenic bacterium in tropical aquaculture. This bacterium was recently isolated from tambaqui (Colossoma macropomum), a commercially important fish species in Brazil. This study assessed the antimicrobial susceptibility, pathogenicity, and genetic diversity of the tambaqui-derived E. tarda isolates. Fourteen bacterial isolates isolated from tambaqui were identified as E. tarda by using matrix-assisted laser desorption/ionization–time-of-flight mass spectrometry and dnaJ gene sequencing. Antimicrobial susceptibility tests were conducted against seven drugs using the disc diffusion assay. The pathogenicity test conducted by intraperitoneal injection of 2.4 × 107 colony-forming units (CFU) fish−1 of E. tarda (ED38-17) into tambaqui juveniles eventually revealed that neither clinical signs nor death were present. However, splenomegaly and whitish areas in the spleen and kidneys were observed. The histological investigation also revealed granulomatous splenitis, nephritis, and hepatitis occurring internally. Repetitive extragenic palindromic-PCR fingerprinting separated the 14 isolates into three genetic groups. The antibiogram revealed that all E. tarda isolates were wild-type (WT) to florfenicol (FLO), norfloxacin (NOR), neomycin (NEO), erythromycin (ERY), and oxytetracycline (OXY); however, some were non-wild-type to sulfamethoxazole/trimethoprim (7.1%) and amoxicillin (21.4%). Therefore, through experimental infection, E. tarda ED38-17 could induce pathogenic effects in C. macropomum. Additionally, three distinct genetic types were found, and the E. tarda isolates were WT to FLO, NOR, NEO, ERY, and OXY. These findings raise awareness of a bacteria causing unseen lesions, a pathogen that will potentially impact tambaqui aquaculture in the future.
Three-Dimensional Imaging and Histopathological Features of Third Metacarpal/Tarsal Parasagittal Groove and Proximal Phalanx Sagittal Groove Fissures in Thoroughbred Horses
Authors: Lin Szu-Ting , Foote Alastair K. , Bolas Nicholas M. , Peter Vanessa G. , Pokora Rachel , Patrick Hayley , Sargan David R. , Murray Rachel C.
Published: September 2023

Fissure in the third metacarpal/tarsal parasagittal groove and proximal phalanx sagittal groove is a potential prodromal pathology of fracture; therefore, early identification and characterisation of fissures using non-invasive imaging could be of clinical value. Thirty-three equine cadaver limbs underwent standing cone-beam (CB) computed tomography (CT), fan-beam (FB) CT, low-field magnetic resonance imaging (MRI), and macro/histo-pathological examination. Imaging diagnoses of fissures were compared to microscopic examination. Imaging features of fissures were described. Histopathological findings were scored and compared between locations with and without fissures on CT. Microscopic examination identified 114/291 locations with fissures. The diagnostic sensitivity and specificity were 88.5% and 61.3% for CBCT, 84.1% and 72.3% for FBCT, and 43.6% and 85.2% for MRI. Four types of imaging features of fissures were characterised on CT: (1) CBCT/FBCT hypoattenuating linear defects, (2) CBCT/FBCT striated hypoattenuated lines, (3) CBCT/FBCT subchondral irregularity, and (4) CBCT striated hypoattenuating lines and FBCT subchondral irregularity. Fissures on MRI appeared as subchondral bone hypo-/hyperintense defects. Microscopic scores of subchondral bone sclerosis, microcracks, and collapse were significantly higher in locations with CT-identified fissures. All imaging modalities were able to identify fissures. Fissures identified on CT were associated with histopathology of fatigue injuries.
A Nuanced Examination of Primate Capture and Consumption and Human Socio-Economic Well-Being in Kirindy Mitea National Park, Madagascar
Authors: Romanello Domenic , Thompson Katharine E. T. , Borgerson Cortni , Randriamanetsy Jeanne Mathilde , Andriamavosoloarisoa Niaina Nirina Mahefa , Andrianantenaina Mamy Yves , Razafindrahasy Théofrico Alexander , Surkis Claire , Wright Patricia C. , Twiss Katheryn C. , Lewis Rebecca J.
Published: September 2023

The futures of human and nonhuman primates are closely tied in protected areas. Understanding this interconnectedness is especially urgent in Madagascar, one of the world’s most impoverished biodiversity hotspots. Yet, no study has evaluated the relationship between poverty and lemur hunting and consumption using a composite poverty metric that includes health, education, and living standards. To address this gap, and to inform primate conservation practice and policy, we administered annual surveys to 81 households over six consecutive months (September 2018 to March 2019) in a village on the border of Kirindy Mitea National Park, Madagascar. We observed extreme deprivation scores across multiple dimensions of poverty and identified ninety-five percent of households as ‘impoverished’. Of these, three-quarters (77%) of households were identified as being in ‘severe poverty’. One-fifth (19%) of all households hunted lemurs and half (49%) of households consumed lemurs. While poverty eradication is an urgent need in communities around Kirindy Mitea National Park, our findings show no relationship between poverty and lemur hunting and consumption, perhaps due to the lack of variance in poverty. Our results highlight the need to investigate other contributory factors to lemur hunting and consumption locally. Because food insecurity is a known driver of lemur hunting and consumption among the study community, and because domestic meats can be preferred over protected species, we recommend testing the efficacy of livestock interventions near Kirindy Mitea National Park.
In Vitro Efficacy of Dalbavancin as a Long-Acting Anti-Biofilm Agent Loaded in Bone Cement
Authors: Sánchez-Somolinos Mar , Díaz-Navarro Marta , Benjumea Antonio , Matas José , Vaquero Javier , Muñoz Patricia , Sanz-Ruíz Pablo , Guembe María
Published: September 2023

Based on previous studies by our group in which we demonstrated that dalbavancin loaded in bone cement had good elution capacity for the treatment of biofilm-related periprosthetic infections, we now assess the anti-biofilm activity of dalbavancin and compare it with that of vancomycin over a 3-month period. We designed an in vitro model in which we calculated the percentage reduction in log cfu/mL counts of sonicated steel discs contaminated with staphylococci and further exposed to bone cement discs loaded with 2.5% or 5% vancomycin and dalbavancin at various timepoints (24 h, 48 h, 1 week, 2 weeks, 6 weeks, and 3 months). In addition, we tested the anti-biofilm activity of eluted vancomycin and dalbavancin at each timepoint based on a 96-well plate model in which we assessed the percentage reduction in metabolic activity. We observed a significant decrease in the dalbavancin concentration from 2 weeks of incubation, with sustained anti-biofilm activity up to 3 months. In the case of vancomycin, we observed a significant decrease at 1 week. The concentration gradually increased, leading to significantly lower anti-biofilm activity. The percentage reduction in cfu/mL counts was higher for dalbavancin than for vancomycin at both the 2.5% and the 5% concentrations. The reduction in log cfu/mL counts was higher for S. epidermidis than for S. aureus and was particularly more notable for 5% dalbavancin at 3 months. In addition, the percentage reduction in metabolic activity also decreased at 3 months in 5% dalbavancin and 5% vancomycin, with more notable values recorded for the latter.
Strongly Metal-Adhesive and Self-Healing Gelatin@Polydopamine-Based Hydrogels with Long-Term Antioxidant Activity
Authors: Hirtzel Jordana , Leks Guillaume , Favre Julie , Frisch Benoît , Talon Isabelle , Ball Vincent
Published: September 2023

Bioinspired adhesives have been increasingly developed, especially towards a biomedical application. Therefore, in this study, dopamine (DA) was oxidized into polydopamine (PDA) in a gelatin mixture via titration with NaIO4 as a strong oxidant to easily obtain an adhesive antioxidant and self-healing PDA–gelatin hydrogel. Rheology experiments show a stiffness in the order of kPa and a thermal resistance above 50 °C, much above the gel–sol transition temperature of pristine gelatin. After heating at 55 °C, the gel is self-healing. In addition, just after formulation, it shows strong peeling-rate-dependent adhesion to steel with a tensile work per unit area (W) of up to 100 ± 39 J/m2, which is 2.5 times higher than that of the same gel without PDA at a peeling rate of 1000 µm/s. The increase in W between peeling rates of 10 and 1000 µm/s was studied and interpreted in terms of the gels’ viscoelasticity. Moreover, this hydrogel offers significant antioxidant activity (measured by DPPH scavenging) that lasts with storage for at least over 15 days, this being then prolonged for 2 additional days, which seems particularly relevant considering the importance of reactive oxygen species (ROS) in wound healing. To summarize, PDA–gelatin gel is a promising strong and antioxidant adhesive.
A Fast Approach to Optimize Tread Pattern Shape for Tire Noise Reduction
Authors: Zhu Bin , Hu Debin , Liao Fagen , Chen Jiali , Su Benlong , Wu Jian , Wang Youshan
Published: September 2023

Impact force induced by tread pattern is one of the major mechanisms of tire noise; thus, how to reduce tire impact noise has been an important issue in regard to tire technology. In this paper, the mechanism of tire–pavement interaction noise is briefly described, and a prediction model for pattern noise is proposed. The prediction model was validated with indoor semi-anechoic chamber and pass-by noise experiments. Then, an optimization method for the tread pattern was proposed by using the basis vector method, and the synthetic pattern shape was generated through a linear combination of basis shape vectors. Finally, a novel multi-objective function was proposed, aimed at minimizing the impact noise generated by the tire pattern, and the weight factors of the basis vectors were optimized with a genetic algorithm. The method proposed in this paper can be used to evaluate or improve pattern performance and reduce trial and error in the pattern design stage.
Prediction of Inbound and Outbound Passenger Flow in Urban Rail Transit Based on Spatio-Temporal Attention Residual Network
Authors: Yang Jun , Dong Xueru , Yang Huifan , Han Xiao , Wang Yan , Chen Jiayue
Published: September 2023

Passenger flow prediction is a critical approach to ensure the effective functioning of urban rail transit. However, there are few studies that combine multiple influencing factors for short-term passenger flow prediction. It is also a challenge to accurately predict passenger flow at all stations in the line at the same time. To overcome the above limitations, a deep learning-based method named ST-RANet is proposed, which consists of three spatio-temporal modules and one external module. The model is capable of predicting inbound and outbound passenger flow for all stations within the network simultaneously. We model the spatio-temporal data in terms of three temporal characteristics, including closeness, period, and trend. For each characteristic, we construct a spatio-temporal module that innovatively integrates the attention mechanisms into the middle of residual units and convolutional neural networks (CNNs) to extract and learn spatio-temporal features. Subsequently, the results of the three modules are integrated using a parameter matrix method, which allows for dynamic aggregation based on data. The integration results are further combined with external factors, such as holidays and meteorological information, to obtain passenger flow prediction values for each station. The proposed model is validated using real data from Beijing Subway, and optimized parameters are applied for 30-min granularity passenger flow predictions. Comparing the performance against 5 baseline models and verifying with data from multiple lines, the results indicate that the proposed ST-RANet model shows the best results. It is demonstrated that the method proposed in this paper has high prediction accuracy and good applicability.
Advances in Three Dimensional Bioprinting for Wound Healing: A Comprehensive Review
Authors: Umur Egemen , Bayrak Emirhan , Arslan Fahriye , Bulut Safiye Betül , Baysoy Engin , Kaleli-Can Gizem , Ayan Bugra
Published: September 2023

The vulnerability of skin wounds has made efficient wound dressing a challenging issue for decades, seeking to mimic the natural microenvironment of cells to facilitate cell binding, augmentation, and metamorphosis. Many three-dimensional (3D) bioprinted hydrogel-based configurations have been developed using high-tech devices to overcome the limitations of traditional dressing materials. Based on a material perspective, this review examines current state-of-the-art 3D bioprinting for hydrogel-based dressings, including both their advantages and limitations. Accordingly, their potential applications in terms of their performance in vitro and in vivo, as well as their adaptability to clinical settings, were investigated. Moreover, different configurations of 3D bioprinters are discussed. Finally, a roadmap for advancing wound dressings fabricated with 3D bioprinting is presented.
Multi-Level Training and Testing of CNN Models in Diagnosing Multi-Center COVID-19 and Pneumonia X-ray Images
Authors: Talaat Mohamed , Si Xiuhua , Xi Jinxiang
Published: September 2023

This study aimed to address three questions in AI-assisted COVID-19 diagnostic systems: (1) How does a CNN model trained on one dataset perform on test datasets from disparate medical centers? (2) What accuracy gains can be achieved by enriching the training dataset with new images? (3) How can learned features elucidate classification results, and how do they vary among different models? To achieve these aims, four CNN models—AlexNet, ResNet-50, MobileNet, and VGG-19—were trained in five rounds by incrementally adding new images to a baseline training set comprising 11,538 chest X-ray images. In each round, the models were tested on four datasets with decreasing levels of image similarity. Notably, all models showed performance drops when tested on datasets containing outlier images or sourced from other clinics. In Round 1, 95.2~99.2% accuracy was achieved for the Level 1 testing dataset (i.e., from the same clinic but set apart for testing only), and 94.7~98.3% for Level 2 (i.e., from an external clinic but similar). However, model performance drastically decreased for Level 3 (i.e., outlier images with rotation or deformation), with the mean sensitivity plummeting from 99% to 36%. For the Level 4 testing dataset (i.e., from another clinic), accuracy decreased from 97% to 86%, and sensitivity from 99% to 67%. In Rounds 2 and 3, adding 25% and 50% of the outlier images to the training dataset improved the average Level-3 accuracy by 15% and 23% (i.e., from 56% to 71% to 83%). In Rounds 4 and 5, adding 25% and 50% of the external images increased the average Level-4 accuracy from 81% to 92% and 95%, respectively. Among the models, ResNet-50 demonstrated the most robust performance across the five-round training/testing phases, while VGG-19 persistently underperformed. Heatmaps and intermediate activation features showed visual correlations to COVID-19 and pneumonia X-ray manifestations but were insufficient to explicitly explain the classification. However, heatmaps and activation features at different rounds shed light on the progression of the models’ learning behavior.
Influence of Variable Height of Piers on the Dynamic Characteristics of High-Speed Train–Track–Bridge Coupled Systems in Mountainous Areas
Authors: Zeng Yingying , Jiang Lizhong , Zhang Zhixiong , Zhao Han , Hu Huifang , Zhang Peng , Tang Fang , Xiang Ping
Published: September 2023

With the increase in the occupancy ratio of bridges and the speed of trains, the probability of trains being located on bridges during earthquakes increases, and the risk of derailment increases. To investigate the influence of unequal-height piers on the dynamic response of high-speed railway train bridge systems, a seismic action model of high-speed train–track–bridge dynamic systems was established based on the in-house code using the finite element method and multi-body dynamics method. It is found that (1) compared to equal-height piers, the peak lateral dynamic response of unequal-height piers (with gradually increasing pier heights) decreases, while the peak vertical dynamic response increases; (2) the peak lateral dynamic response of unequal-height piers (with a steep increase in pier height) increases sharply, while the peak vertical dynamic response decreases; and (3) the safety indicators of equal-height piers are significantly superior to the two unequal-height pier operating conditions.
Noise Reduction Based on a CEEMD-WPT Crack Acoustic Emission Dataset
Authors: Zhao Yongfeng , Ma Yunrui , Du Junli , Wang Chaohua , Xia Dawei , Xin Weifeng , Zhan Zhenyu , Zhang Runfeng , Chen Jiangyi
Published: September 2023

In order to solve the noise reduction problem of acoustic emission signals with cracks, a method combining Complementary Ensemble Empirical Mode Decomposition (CEEMD) and wavelet packet (WPT) is proposed and named CEEMD-WPT. Firstly, the single Empirical Mode Decomposition (EMD) used in the traditional CEEMD is improved into the WPT-EMD with a more stable noise reduction effect. Secondly, after decomposition, the threshold value of the correlation coefficient is determined for the Intrinsic Mode Function (IMF), and the low correlation component is further processed by WPT. In addition, in order to solve the problem that it is difficult to quantify the real signal noise reduction effect, a new quantization index “principal interval coefficient (PIC)” is designed in this paper, and its reliability is verified through simulation experiments. Finally, noise reduction experiments are carried out on the real crack acoustic emission dataset consisting of tensile, shear, and mixed signals. The results show that CEEMD-WPT has the highest number of signals with a principal interval coefficient of 0–0.2, which has a better noise reduction effect compared with traditional CEEMD and Complementary Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN). Moreover, the statistical variance of CEEMD-WPT is evidently one order of magnitude smaller than that of CEEMD, so it has stronger stability.
Investigation of Rock Joint and Fracture Influence on Delayed Blasting Performance
Authors: Zhang Pengfei , Bai Runcai , Sun Xue , Wang Tianheng
Published: September 2023

Geological structures such as joints and faults in rock mass have a significant influence on open-pit mining. Hence, it is critical to develop an understanding of dynamic joint behavior under blasting loading. This, in turn, can provide both theoretical and practical guidance to improve blasting rock fragmentation and associated bucket excavating efficiency. In this paper, delayed blasting on a highwall bench at an open-pit mine is used as an example; a nonlinear joint blasting model is also constructed. By simplifying the blasting wave propagation velocity and combining the relevant stress and displacement theories of type I and II cracks, equipotential diagrams of the stress and displacement field with the vibration velocity of the particle are obtained. Additionally, ANSYS is used to analyze the distribution of the stress field. This is able to be visualized by the degree of color change post-processing. It is concluded that, with the attenuation of the detonation wave energy, the stress exhibited a decreasing trend in this process. According to the distribution of the peak effective stress, it is found that the peak value first increases to 10–12 MPa and then shows a downward trend.
Three-Dimensional Mineral Prospectivity Modeling with the Integration of Ore-Forming Computational Simulation in the Xiadian Gold Deposit, Eastern China
Authors: Liu Zhankun , Guo Zhenyu , Wang Jinli , Wang Rongchao , Shan Wenfa , Zhong Huiting , Chen Yudong , Chen Jin , Deng Hao , Mao Xiancheng
Published: September 2023

Finding new, effective predictive variables for 3D mineral prospectivity modeling is both important and challenging. The 3D ore-forming numerical modeling quantitively characterizes the complex coupling-mineralization process of the structure, fluid, heat, and wall rock, which may be potential indicators for mineral exploration. We here conducted 3D mineral prospectivity modeling with the integration of ore-forming computational simulation information in the Xiadian orogenic gold deposit, China, to examine whether the simulation data input can improve the reliability of prospectivity modeling. First, we constructed the 3D models of the orebody and fault to extract the fault geometric features using spatial analysis, as they are always considered to be the crucial controls of gold distribution. Second, we performed 3D numerical modeling of the deformation–fluid–heat-coupling process of the structurally controlled hydrothermal Au system using the FLAC3D platform. Finally, the fault-geometry features (buffer, dip, dip variation, and undulation) and the ore-formation-simulation indices (volume strain, shear strain, temperature variation, and fluid flux) were integrated using Bayesian decomposition modeling, which has a promising nonlinear model ability and a flexible variable-integration ability. The prospectivity modeling results demonstrated that the model generated by combining geometry and simulation variables achieved significantly higher AUC, precision, accuracy, Kappa, and F1 scores compared to other models using a single-predictor-variable dataset. This suggests that the joint use of geometry and simulation variables construct a comprehensive association between gold and its ore-controlling factors, thereby resulting in a highly reliable prospectivity model. Thus, the approach of 3D mineral prospectivity modeling aided by ore-forming numerical simulation proves to be more useful in guiding mineral exploration, especially in the condition of fewer variables. Based on the prospectivity modeling outcomes, we identified four gold targets at depth in the Xiadian district that warrant focused exploration efforts.
A Numerical Gear Rolling Test Method for Face-Hobbed Hypoid Gears
Authors: Du Jinfu , Mao Hong , Liu Yongxiang , Zhang Qunlin
Published: September 2023

A numerical gear rolling test (NGRT) method for actual tooth surfaces was proposed. The non-uniform rational B-spline (NURBS) fitting method was adapted to reconstruct the actual tooth surface, and the instant meshing point as well as the transmission error of two meshing gears were solved. The instant contact ellipse boundary of each meshing point can be accurately searched, and then the contact pattern formed by a series of contact ellipses on the actual tooth surface can be obtained. Finally, the rolling test experiment for a pair of hypoid gears was conducted to verify the feasibility of the proposed method. The result shows that the contact pattern obtained is consistent with the actual rolling test result, the relative errors of the transmission error amplitudes were only 4.5% and 5.3% for the drive and coast sides, respectively, and the contact ellipse of the actual tooth surface is not necessarily a standard ellipse and the instant contact path is not necessarily a straight line. This NGRT method helps to reduce equipment and time costs in closed-loop gear manufacturing, which is of great significance for mass production.
Neural Machine Translation of Electrical Engineering with Fusion of Memory Information
Authors: Chen Yuan , Liu Zikang , Zhang Juwei
Published: September 2023

This paper proposes a new neural machine translation model of electrical engineering that combines a transformer with gated recurrent unit (GRU) networks. By fusing global information and memory information, the model effectively improves the performance of low-resource neural machine translation. Unlike traditional transformers, our proposed model includes two different encoders: one is the global information encoder, which focuses on contextual information, and the other is the memory encoder, which is responsible for capturing recurrent memory information. The model with these two types of attention can encode both global and memory information and learn richer semantic knowledge. Because transformers require global attention calculation for each word position, the time and space complexity are both squared with the length of the source language sequence. When the length of the source language sequence becomes too long, the performance of the transformer will sharply decline. Therefore, we propose a memory information encoder based on the GRU to improve this drawback. The model proposed in this paper has a maximum improvement of 2.04 BLEU points over the baseline model in the field of electrical engineering with low resources.
Assessing Efficiency in Artificial Neural Networks
Authors: Schaub Nicholas J. , Hotaling Nathan
Published: September 2023

The purpose of this work was to develop an assessment technique and subsequent metrics that help in developing an understanding of the balance between network size and task performance in simple model networks. Here, exhaustive tests on simple model neural networks and datasets are used to validate both the assessment approach and the metrics derived from it. The concept of neural layer state space is introduced as a simple mechanism for understanding layer utilization, where a state is the on/off activation state of all neurons in a layer for an input. Neural efficiency is computed from state space to measure neural layer utilization, and a second metric called the artificial intelligence quotient (aIQ) was created to balance neural network performance and neural efficiency. To study aIQ and neural efficiency, two simple neural networks were trained on MNIST: a fully connected network (LeNet-300-100) and a convolutional neural network (LeNet-5). The LeNet-5 network with the highest aIQ was 2.32% less accurate but contained 30,912 times fewer parameters than the network with the highest accuracy. Both batch normalization and dropout layers were found to increase neural efficiency. Finally, networks with a high aIQ are shown to be resistant to memorization and overtraining as well as capable of learning proper digit classification with an accuracy of 92.51%, even when 75% of the class labels are randomized. These results demonstrate the utility of aIQ and neural efficiency as metrics for determining the performance and size of a small network using exemplar data.
Study on Pavement Performance of Recycled Asphalt Mixture Modified by Carbon Nanotubes and Waste Engine Oil
Authors: Li Wei , Yao Haitao , Yang Dongjin , Peng Chao , Wang Hongjian , Chen Zhuang , Zhao Yuxing
Published: September 2023

The large amount of recycled asphalt pavement mixture (RAP) generated during renovations has a negative impact on the environment. In recent years, how to rationally recycle and reuse RAP has become a hot research direction in the field of highway construction. However, the recycled asphalt binder has some problems such as instability, easy aging and decreased adhesion. In this paper, carbon nanotubes and waste engine oil were used to modify recycled asphalt binder. Through a high-temperature rutting test, low-temperature bending test and Marshall stability test, the properties of an asphalt mixture with 40% RAP modified by carbon nanotubes and waste engine oil, an asphalt mixture with 40% RAP and an asphalt mixture without RAP were compared and analyzed. The tests showed that 1.5 wt% carbon nanotubes could improve the performance of the old asphalt binder most significantly. After adding 1.5 wt% carbon nanotubes, the high-temperature rutting resistance of the asphalt mixture was increased by 24.3%, and the bending stiffness modulus and the best crack resistance at low temperature increased significantly. In addition, after adding 1.5 wt% carbon nanotubes, the Marshall stability of the waste-engine-oil-modified RAP could be restored to the level of the new asphalt mixture. In summary, carbon nanotubes can improve the high-temperature stability, low-temperature crack resistance and Marshall stability of waste-engine-oil-modified RAP.
Application of Azolla spp. as a Growing Medium Component for Melon Grown in a Soilless Culture System
Authors: Intana Warin , Khomphet Thanet , Srichai Naramit , Bundit Nattawadee , Islam Shams Shaila
Published: September 2023

Azolla spp. is a prominent macrophyte and one of the world’s fastest growing plants, making it a highly important resource that has been widely exploited as a biofertilizer, food and feed, and biofuel production. As a result, the uses, promotion, and application of Azolla spp. in sustainable agriculture would be of significant interest. The objectives of this study were (i) to assess the feasibility of using Azolla as a growing media of melons with a reduction in fertigation concentration in a soilless culture system, and (ii) to compare the agronomic and fruit quality traits of melons grown in different Azolla treatments. The experiment was carried out using a completely randomized design with 4 treatments including: (1) control treatment (1:1 combination of chopped coconut mesocarp (CCM) and coconut coir (CC) with recommended fertigation concentration (RFC)), (2) dried Azolla (1:1:2 combination of CCM, CC, and dried Azolla with 75% of RFC), (3) fermented Azolla (1:1:2 combination of CCM, CC, and fermented Azolla with 75% of RFC), and (4) fresh Azolla (1:1:2 combination of CCM, CC, and fresh Azolla with 75% of RFC). Seven melons per treatment were recorded on the agronomic traits (stem length, stem diameter, leaf width, leaf length, and leaf number) and fruit quality (fruit weight, fruit height, fruit perimeter, rind thickness, pulp thickness, fruit cavity, pulp firmness, pulp color (L*, a*, b*, Hue, and c*), total soluble solid, juice electrical conductivity, juice pH, and juice titratable acidity). Statistical analyses revealed the differences among melon agronomic and yield traits under different Azolla treatments. Nutrient analysis results showed that fermented and fresh Azolla had a high nutritional value as compared to dried Azolla. Most fruit traits from fermented and fresh Azolla treatments with a fertilizer reduction were not significantly different as compared to control. Both treatments were recommended for melon production in a soilless culture system, since these treatments can reduce fertigation use by 25% while maintaining growth and fruit quality when compared to conventional practice.
Zeroes of Multifunctions with Noncompact Image Sets
Authors: Kasyanov Pavlo O. , Levenchuk Liudmyla B. , Piatova Angela V.
Published: September 2023

In this article we consider zeroes for multifunctions with possibly noncompact image sets. We introduce the notion of multifunction with K-inf-compact support. We also establish three types of applications: the Bayesian approach for analysis of financial operational risk under certain constraints, occupational health and safety measures optimization, and transfer of space innovations and technologies.
Using i-GONAD for Cell-Type-Specific and Systematic Analysis of Developmental Transcription Factors In Vivo
Authors: Wiegreffe Christoph , Ehricke Simon , Schmid Luisa , Andratschke Jacqueline , Britsch Stefan
Published: September 2023

Transcription factors (TFs) regulate gene expression via direct DNA binding together with cofactors and in chromatin remodeling complexes. Their function is thus regulated in a spatiotemporal and cell-type-specific manner. To analyze the functions of TFs in a cell-type-specific context, genome-wide DNA binding, as well as the identification of interacting proteins, is required. We used i-GONAD (improved genome editing via oviductal nucleic acids delivery) in mice to genetically modify TFs by adding fluorescent reporter and affinity tags that can be exploited for the imaging and enrichment of target cells as well as chromatin immunoprecipitation and pull-down assays. As proof-of-principle, we showed the functional genetic modification of the closely related developmental TFs, Bcl11a and Bcl11b, in defined cell types of newborn mice. i-GONAD is a highly efficient procedure for modifying TF-encoding genes via the integration of small insertions, such as reporter and affinity tags. The novel Bcl11a and Bcl11b mouse lines, described in this study, will be used to improve our understanding of the Bcl11 family’s function in neurodevelopment and associated disease.
Advancing Healthcare: Synergizing Biosensors and Machine Learning for Early Cancer Diagnosis
Authors: Kokabi Mahtab , Tahir Muhammad Nabeel , Singh Darshan , Javanmard Mehdi
Published: September 2023

Cancer is a fatal disease and a significant cause of millions of deaths. Traditional methods for cancer detection often have limitations in identifying the disease in its early stages, and they can be expensive and time-consuming. Since cancer typically lacks symptoms and is often only detected at advanced stages, it is crucial to use affordable technologies that can provide quick results at the point of care for early diagnosis. Biosensors that target specific biomarkers associated with different types of cancer offer an alternative diagnostic approach at the point of care. Recent advancements in manufacturing and design technologies have enabled the miniaturization and cost reduction of point-of-care devices, making them practical for diagnosing various cancer diseases. Furthermore, machine learning (ML) algorithms have been employed to analyze sensor data and extract valuable information through the use of statistical techniques. In this review paper, we provide details on how various machine learning algorithms contribute to the ongoing development of advanced data processing techniques for biosensors, which are continually emerging. We also provide information on the various technologies used in point-of-care cancer diagnostic biosensors, along with a comparison of the performance of different ML algorithms and sensing modalities in terms of classification accuracy.
Macro-Modelling of IP-OoP Interaction in Unreinforced Solid Masonry Infills under Earthquake-Induced Actions: A Review
Authors: Rostamkalaee Soheil , Peloso Simone , Brunesi Emanuele
Published: September 2023

Unreinforced masonry-infilled reinforced concrete frames are a prevalent taxonomy class not only in the Mediterranean region but also in Europe and worldwide, where buildings of this type abound or are ubiquitous. Thus, somewhat expectedly, various earthquake events and sequences have repeatedly shown the poor seismic behaviour of masonry infill walls, which, in turn, have brought into question issues of the variability, uncertainty, and interaction of in-plane (IP) and out-of-plane (OoP) responses. The latter aspect is examined in this paper, which provides a systematic review concerning the conceptualisation and development of numerical macro-models for simulating the behaviour of solid infill wall panels taking their IP–OoP interaction into account. To this end, the most important parameters involved in the cyclic behaviour of unreinforced solid masonry infill walls are addressed first, and then the main models currently available in the literature are scrutinised and key features discussed, with emphasis posed on issues of accuracy/suitability and easiness or level of complexity/sophistication.
Hani Mushroom House Building Adaptability
Authors: Bai Xueyue , Duan Yutong , Li Dafang
Published: September 2023

The Hani Rice Terraces are a famous World Heritage Site. The mushroom houses in the terraced fields have a unique architectural style and national cultural characteristics. This study focused on four traditional villages with the most obvious characteristics of mushroom houses: Azheke Village, Dayutang Village, Yakou Village, and Dayazi Village. A total of 34 mushroom houses were mapped. The forms of the mushroom houses were classified first, and then, the basic prototype of the building structure of the Hani mushroom houses was extracted for structural modeling. Finally, the structure of the prototype of the mushroom houses under different load conditions was analyzed. The results show that the Hani mushroom house design has a simple structure and good stability, can adapt to the local natural environment, and is the product of the Hani people’s adaptation to the local natural environment.
Immunohistochemical Evaluation of the Expression of Specific Membrane Antigens in Patients with Pancreatic Ductal Adenocarcinoma
Authors: Nicoletti Alberto , Vitale Federica , Quero Giuseppe , Paratore Mattia , Fiorillo Claudio , Negri Marcantonio , Carlino Angela , Inzani Frediano , Gasbarrini Antonio , Alfieri Sergio , Zileri Dal Verme Lorenzo
Published: September 2023

(1) Background: Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal malignancies. The lack of validated disease biomarkers makes timely diagnosis challenging in most cases. Cell membrane and surface proteins play a crucial role in several routes of oncogenesis. The aim of this study was to evaluate the expression of six membrane antigens on PDAC (CA 19-9, mucin 1 and 4 (MUC1, MUC4), mesothelin (MSLN), Annexin A10 (ANXA10), Glypican-1 (GPC-1)) and their correlation with oncologic outcomes. (2) Methods: Immunohistochemical staining for CA 19.9, MUC1, MUC4, MSLN, ANXA10, and GPC-1 of surgical samples of 50 consecutive patients with PDAC was performed. Antigen expression for tumor, ductal, and acinar tissues was classified according to the histo-score (H-score) by two pathologists. (3) Results: Recurrence rate was 47% and 18 patients (36%) deceased (median follow-up 21.5 months). Immunostaining for CA 19-9 and MUC1 showed a significantly higher expression in the neoplastic tissue compared to non-tumor ductal and acinar tissues (p < 0.001). MUC4, MSLN, ANXA10, and GPC-1 were selectively expressed in the neoplastic tissue (p < 0.001). A CA 19-9 H-score value >270 was independently associated with a worse overall survival (p = 0.05) and disease-free survival (p = 0.05). (4) Conclusions: CA 19-9 and MUC1 are highly expressed in PDAC cells. The histological expression of CA 19-9 may predict prognosis. MUC4, MSLN, ANXA10, and GPC-1 are selectively expressed by neoplastic tissue and may represent a potential histological biomarker of disease.
The Gum–Gut Axis: Periodontitis and the Risk of Gastrointestinal Cancers
Authors: Baima Giacomo , Ribaldone Davide , Romano Federica , Aimetti Mario , Romandini Mario
Published: September 2023

Periodontitis has been linked to an increased risk of various chronic non-communicable diseases, including gastrointestinal cancers. Indeed, dysbiosis of the oral microbiome and immune-inflammatory pathways related to periodontitis may impact the pathophysiology of the gastrointestinal tract and its accessory organs through the so-called “gum–gut axis”. In addition to the hematogenous spread of periodontal pathogens and inflammatory cytokines, recent research suggests that oral pathobionts may translocate to the gastrointestinal tract through saliva, possibly impacting neoplastic processes in the gastrointestinal, liver, and pancreatic systems. The exact mechanisms by which oral pathogens contribute to the development of digestive tract cancers are not fully understood but may involve dysbiosis of the gut microbiome, chronic inflammation, and immune modulation/evasion, mainly through the interaction with T-helper and monocytic cells. Specifically, keystone periodontal pathogens, including Porphyromonas gingivalis and Fusobacterium nucleatum, are known to interact with the molecular hallmarks of gastrointestinal cancers, inducing genomic mutations, and promote a permissive immune microenvironment by impairing anti-tumor checkpoints. The evidence gathered here suggests a possible role of periodontitis and oral dysbiosis in the carcinogenesis of the enteral tract. The “gum–gut axis” may therefore represent a promising target for the development of strategies for the prevention and treatment of gastrointestinal cancers.