bluuebunny/crossref_metadata_2025_split huggingface dataset:
A hybrid model using data mining and multi-criteria decision-making methods for landslide risk mapping at Golestan Province, Iran
Authors: Sardooi Elham Rafiei , Azareh Ali , Mesbahzadeh Tayyebeh , Sardoo Farshad Soleimani , Parteli Eric J. R. , Pradhan Biswajeet 
Published: July 2021

Abstract
The accurate modelling of landslide risk is essential pre-requisite for the development of reliable landslide control and mitigation strategies. However, landslide risk depends on the poorly known environmental and socio-economic factors for regional patterns of landslide occurrence probability and vulnerability, which constitute still a matter of research. Here, a hybrid model is described that couples data mining and multi-criteria decision-making methods for hazard and vulnerability mapping and presents its application to landslide risk assessment in Golestan Province, Northeastern Iran. To this end, landslide probability is mapped using three state-of-the-art machine learning (ML) algorithms – Maximum Entropy, Support Vector Machine and Genetic Algorithm for Rule Set Production – and combine the results with Fuzzy Analytical Hierarchy Process computations of vulnerability to obtain the landslide risk map. Based on obtained results, a discussion is presented on landslide probability as a function of the main relevant human-environmental conditioning factors in Golestan Province. In particular, from the response curves of the machine learning algorithms, it can be found that the probability 𝑝 of landslide occurrence decreases nearly exponentially with the distance 𝑥 to the next road, fault or river. Specifically, the results indicated that 𝑝≈exp(−𝜆𝑥), where the length-scale 𝜆 is about 0.0797 km−1 for road, 0.108 km−1 for fault and 0.734 km−1 for river. Furthermore, according to the results, 𝑝 follows, approximately, a lognormal function of elevation, while the equation 𝑝=𝑝0−𝐾∙(𝜃−𝜃0)2 fits well the dependence of landslide modeling on the slope-angle 𝜃, with 𝑝0≈0.64, 𝜃0≈25.6° and |𝐾|≈6.6×10−4. However, the highest predicted landslide risk levels in Golestan Province are located in the south and southwest areas surrounding Gorgan City, owing to the combined effect of dense local human occupation and strongly landslide-prone environmental conditions. Obtained results provide insights for quantitative modelling of landslide risk, as well as for priority planning in landslide risk management.
Eco-Friendly Basalt Fiber Reinforced Cement Composites (BFRC) Containing Waste Copper As Partial Replacement For Sand And Cement
Authors: Aeshah Mohammed Najı Ahmed Abu , Kaplan Gökhan 
Published: July 2021

Abstract
In this study, the use of copper slag and aggregate together with basalt fiber in cement-based composites was studied. It was aimed to contribute to the ecosystem by using copper waste, which is an environmental problem, in cement-based composites. In addition, the effect of basalt fiber on the strength and durability properties of composites was investigated. Taguchi optimization was carried out for cement-based composites. In this context, Taguchi L18 matrix was used. Copper slag was used at rates of 0, 7.5% and 15%, and copper aggregate at rates of 0, 25% and 50%. Basalt fibers of 6 and 12 mm length were used at the rates of 1%, 2% and 3%. The w/b ratios of the mixtures were chosen as 0.40, 0.50 and 0.60. Durability tests such as permeability, freeze-thaw and sulphate resistance with fresh and hardened mortar properties were performed on 18 different mixtures. In terms of the 7, 28 and 91-day flexural and compressive strength of the mixtures, the use of 1% of 6 mm long fiber in the mixtures with a w/b ratio of 0.40 provided more positive results. In terms of freeze-thaw resistance, it is necessary to use 3% of 6 mm long fiber in mixtures with 0.40 w/b. The use of 7.5% copper slag reduced the water penetration depth. The use of 15% copper slag in mixtures affected by sodium sulphate reduced the expansion values. Since the increase in the ratio of copper aggregate decreased the aggregate volume, it caused the drying shrinkage values to increase. As a result, it was observed that copper slag has a more positive effect than copper aggregate for the strength and durability of composites. However, by using 25% of copper aggregate by sacrificing some features, it can contribute to the environment and ecosystem. The use of basalt fiber with a length of 6 mm and a ratio of 1% increased the mechanical properties, while the use of 3% contributed significantly to the freeze-thaw resistance. It was determined that copper wastes contribute to the environment and ecosystem by using them instead of cement and aggregate.
Study of Phonon Transport Across Si/Ge Interfaces Using Full-Band Phonon Monte Carlo Simulation
Authors: Le Ngoc Duc , Davier Brice , Dollfus Philippe , Martin Jerome Saint 
Published: July 2021

Abstract
A Full Band Monte Carlo simulatorhas been developed to considerphonon transmission across interfaces disposedperpendicularlyto the heat flux. This solver of the Boltzmann transport equation does not require any assumption on the shape the phonon distribution and can naturally consider all phonon transport regimes from the diffusive to the fully ballistic regime. This simulatoris used to study single and double Si/Ge heterostructures from the micrometer scale downto the nanometer scale,i.e. in all phonon transport regime from fully diffusive toballistic.A methodology to determine the thermal conductivity atthermal interfaces is presented.
Unsteady Aerodynamic Characteristics of Transversely Inclined Prisms Under Forced-Vibration---The Base Intensification Phenomenon
Authors: Chen Zengshun , Bai Jie , Li Cruz Y. , Xu Yemeng , Hua Jianmin , Xue Xuanyi 
Published: July 2021

Abstract
This work, through a series of forced-vibration wind tunnel experiments, investigates the aerodynamic characteristics of square prisms subject to the transverse inclination. An aeroelastic prism was tested under different wind speeds, inclination angles, and oscillation amplitudes. Through analysis on the mean pressure distribution, local force coefficient, force spectra, and aerodynamic damping coefficient, the unsteady aerodynamic characteristics of the configuration were revealed. Empirical observations discovered the Base Intensification phenomenon, which refers to a fundamental change in the structure’s aerodynamic behaviors given any degrees of transverse inclination. Specifically, it is the intensification of the aerodynamic loading, vortical activities, and aerodynamic damping on only the lower portion of an inclined structure. The phenomenon, being almost impactless to the upper portion, is also insensitive to changes in inclination angle and tip amplitude once triggered by the initial inclination. Analysis also revealed that the origin of Base Intensification phenomenon traces back to fix-end three-dimensional effects like the horseshoe vortex, instead of the predominant Bérnard-Kármán vortex shedding. Moreover, results showed that wind speed is the decisive factor for the structure’s crosswind motions. Inside the lock-in region, structure loadings, vortical activities, and the effects of Base Intensification are significantly amplified. Beyond the range, the configuration gradually resorts to a quasi-steady linearity. Finally, results from the force-vibration tests were used for the prediction of structure response. Experimental comparison revealed that the predictions notably outperform those based on rigid tests, forecasting the actual responses with a markedly improved accuracy.
Predicting Cognitive Scores With Graph Neural Networks Through Sample Selection Learning
Authors: Hanik Martin , Demirtaş Mehmet Arif , Gharsallaoui Mohammed Amine , Rekik Islem 
Published: July 2021

Abstract
Analyzing the relation between intelligence and neural activity is of the utmost importance in understanding the working principles of the human brain in health and disease. In existing literature, functional brain connectomes have been used successfully to predict cognitive measures such as intelligence quotient (IQ) scores in both healthy and disordered cohorts using machine learning models. However, existing methods resort to flattening the brain connectome (i.e., graph) through vectorization which overlooks its topological properties. To address this limitation and inspired from the emerging graph neural networks (GNNs), we design a novel regression GNN model (namely RegGNN) for predicting IQ scores from brain connectivity. On top of that, we introduce a novel, fully modular sample selection method to select the best samples to learn from for our target prediction task. However, since such deep learning architectures are computationally expensive to train, we further propose a \emph{learning-based sample selection} method that learns how to choose the training samples with the highest expected predictive power on unseen samples. For this, we capitalize on the fact that connectomes (i.e., their adjacency matrices) lie in the symmetric positive definite (SPD) matrix cone. Our results on full-scale and verbal IQ prediction outperforms comparison methods in autism spectrum disorder cohorts and achieves a competitive performance for neurotypical subjects using 3-fold cross-validation. Furthermore, we show that our sample selection approach generalizes to other learning-based methods, which shows its usefulness beyond our GNN architecture.
Household Solid Waste Management in Inaccessible Neighborhoods – Jordan
Authors: TAl Raed Salem Al , Mukheimer Tala , Aburomman Zain , Hajjaj Ihab Al , AlSmadi Ala’a , Janbek Ala 
Published: July 2021

Abstract
This research examines challenges and responses in collecting household solid waste in high populated inaccessible neighborhoods in Amman, the capital of Jordan. The main questions of the research are: to which extent is the physical and behavioral environment affect waste management process; how waste is collected in inaccessible areas? In order to answer these questions, two major aspects will be analyzed the traditional planning methods and the environmental impact assessment. The researchers employed a mixed used method qualitative and quantitative data approaches. The research is based on field and desk study conducted in one of the most informal and services inaccessible settlement in Jordan. The results revealed that Greater Amman Municipality (GAM) uses unconventional measures and unreliable solid waste collection strategies to overcome the accessibility challenges in the site despite a lack of cooperation of the residents. The study also revealed that the absence of adequate urban regeneration and renewal programs by (GAM) to control the root cause for inadequate solid waste management in informal settlements in the city. This study is important since it establishes a cornerstone for stakeholders to make assessments and control waste management strategies in inaccessible neighborhoods in Amman and similar areas in the country. Moreover, it forms a useful resource for future researches about waste management studies in informal settlements. There is a scarcity in the literature on the relationship between the problem of solid waste management and informal inaccessible settlements in Jordan.
Effect of 12 Months of Exercise With Stachys Lavandulifolia Consumption on Anxiety, Metabolic Syndrome Profiles and Antioxidant Defense and Lipid Peroxidation in Women With Metabolic Syndrome
Authors: Osali Ali , Rostami Alireza 
Published: July 2021

Abstract
Background: The purpose of this study was to investigate the effect of 12 months of aerobic exercise combining stachys lavandulifolia (S. lavandulifolia) consumption on anxiety, Metabolic Syndrome profiles and antioxidant defense (Glutathione) and lipid peroxidation (Malondialdehyde) in 50-65 years old women with metabolic syndrome.Methods: 48 women with Metabolic syndrome were randomly divided into four groups: exercise (n=12), exercise+S. lavandulifolia (n=12), S. lavandulifolia (n=12) and control group (n=12). S. lavandulifolia groups consumed 3 g aerial parts of S. lavandulifolia daily. Training groups performed an exercise protocol of aerobic exercise for 12 months (three sessions per week). Blood samples were obtained before and after training period for antioxidant indicators and lipid degradation measurement. Also, Beck anxiety questionnaire used for evaluating levels of anxiety. T-test and one-way analysis of variance were used for the evaluation of within-group and between-group differences, respectively.Results: A significant increase was observed in serum levels of Malondialdehyde (P =0.004), Catalase indexes (Pvalue= 0.01), and Glutathione (P=0.001) in the training group and S. lavandulifolia groups after 12 months. Body weight, BMI, and SBP and Anexiety was decreased significantly greater in exercise +S. lavandulifolia group compared to control, exercise and S. lavandulifolia groups (P=0.001)Conclusion: Anxiolytic effect and Anti-Oxidative Stress Activity was seen, so taking S. lavandulifolia along with exercises may have beneficial effects on reinforcement the antioxidant system and prevention of anxiety and The negative effects of indicators related to cardiovascular disease in women with metabolic syndrome.
Unsupervised Spatially Embedded Deep Representation of Spatial Transcriptomics
Authors: Chen Jinmiao , Fu Huazhu , XU Hang , Chong Kelvin , Li Mengwei , Ang Kok Siong , Lee Hong Kai , Ling Jingjing , Chen Ao , Shao Ling , Liu Longqi 
Published: July 2021

Abstract
Spatial transcriptomics enable us to dissect tissue heterogeneity and map out inter-cellular communications. Optimal integration of transcriptomics data and associated spatial information is essential towards fully exploiting the data. We present SEDR, an unsupervised spatially embedded deep representation of both transcript and spatial information. The SEDR pipeline uses a deep autoencoder to construct a low-dimensional latent representation of gene expression, which is then simultaneously embedded with the corresponding spatial information through a variational graph autoencoder. We applied SEDR on human dorsolateral prefrontal cortex data and achieved better clustering accuracy, and correctly retraced the prenatal cortex development order with trajectory analysis. We also found the SEDR representation to be eminently suited for batch integration. Applying SEDR to human breast cancer data, we discerned heterogeneous sub-regions within a visually homogenous tumor region, identifying a tumor core with pro-inflammatory microenvironment and an outer ring region enriched with tumor associated macrophages which drives an immune suppressive microenvironment.
Adipose-derived mesenchymal stromal cell-derived exosomes alleviate testicular torsion injury via activation of PI3K/AKT and MAPK/ERK1/2 pathways
Authors: Liu Hengchen , Shi Manyu , Li Xiangqi , Lu Wenjun , Zhang Mingzhao , Zhang Tingting , Wu Yang , Zhang Zenan , Cui Qingbo , Yang Shulong , Li Zhaozhu 
Published: July 2021

Abstract
Background

Exosomes have became a new nano-scale therapeutic method in recent years. Adipose-derived mesenchymal stromal cell-derived exosomes (ADSC-Exos) have shown great potential in the treatment of ischemia-reperfusion injury. However, there is no research on whether ADSC-Exos can alleviate testicular torsion injury. Therefore, we investigated the protective effect of ADSC-Exos in alleviating testicular torsion-detorsion injury.

Methods

ADSC-Exos were isolated by ultracentrifugation and injected into the torsion-detorsion-affected testes of rats. H&E staining and sperm quality were used to evaluate the therapeutic effects of ADSC-Exos, and the level of tissue oxidative stress was determined using malondialdehyde (MDA) and superoxide dismutase (SOD). In addition, TUNEL staining and immunohistological analyses (Ki67, cleaved Caspase-3, IL-6, IL-10, CCR7, and CD163) were used to clarify the effects of ADSC-Exos on spermatogenic cell proliferation, apoptosis, and the inflammatory microenvironment in vivo . Possible signaling pathways were predicted using sequencing technology and bioinformatics analysis. The signaling pathways were validated by proliferation (EdU), migration (transwell and scratch test), and apoptosis (flow cytometry, TUNEL, and western blot) in vitro .

Results

ADSC-Exos alleviated testicular torsion-detorsion injury by attenuating oxidative stress and inflammatory responses. In addition, ADSC-Exos promoted the proliferation and migration of spermatogenic cells and inhibited their apoptosis by activating the PI3K/AKT and MAPK/ERK1/2 signaling pathways.

Conclusions

Overall, we demonstrated that ADSC-Exos can alleviate testicular torsion injury and provided a new approach for treating testicular torsion injury.
Reversing GABA polarity corrects synaptic physiology and behavioural deficits in young adolescent Syngap1+/- mice
Authors: Verma Vijaya , Kumar MJ Vijay , Sharma Kavita , Rajaram Sridhar , Muddashetty Ravi , Manjithaya Ravi , Behnisch Thomas , Clement James 
Published: July 2021

Abstract
Haploinsufficiency in SYNGAP1 is implicated in Intellectual Disability (ID) and Autism Spectrum disorder (ASD) and affects the maturation of dendritic spines. The abnormal spine development has been suggested to cause disbalance of excitatory and inhibitory (E/I) neurotransmission at distinct developmental periods. In addition, E/I imbalances in Syngap1+/- mice might be due to abnormalities in K+-Cl- co-transporter function (NKCC1, KCC2), in a similar manner as in the murine models of Fragile-X and Rett syndromes. To study whether an altered intracellular chloride ion concentration represents an underlying mechanism of altered function of GABAergic synapses in Dentate Gyrus Granule Cells of Syngap1+/- recordings were performed at different developmental stages of the mice. We observed that neurons at P14-15 of Syngap1+/- mice had depolarised membrane potential and a decreased Cl- reversal potential. The KCC2 expression was decreased compared to Wild-type (WT) mice at P14-15. Furtherly, the small molecule GSK-3β inhibitor, 6-bromoindirubin-3`-oxime (6BIO), was tested in an attempt to restore the function of GABAergic synapses. We discovered that intraperitoneal administration of 6BIO during the critical period or young adolescents normalized an altered E/I balance, the deficits of synaptic transmission, and behavioral performance like social novelty, anxiety, and memory of the Syngap1+/- mice. In summary, altered functionality of GABAergic synapses in Syngap1+/- mice is based on a reduced KCC2 expression and a subsequent increase in the intracellular chloride concentration that can be counteracted by the small molecule 6BIO. The 6BIO sufficiently restored cognitive, emotional, and social symptoms by pharmacological intervention, particularly, in adulthood.
Bank Transaction Analyze for Recognize of Money Laundering Using Decision Tree Algorithm (DTA)
Authors: DadashzadehFahim Somayeh , Karimi Ramin , Faghihrasoul Zahra 
Published: July 2021

Abstract
Bank Transaction Analyze for Recognize of Money Laundering Using DTA One of the important problems of the banking systems is illegal transactions based on fraud and money laundering that can destroy the economy and financial foundation of a country. Fraud and money laundering are used to escape from tax payment or inject dirty money to the economy cycle. The offenders use lots of transactions to show their illegal funds rightful. One important problem of fraud and money laundering recognize in banking system is high complexity of it. We need to use knowledge discover methods like learning machine and data mining. We can mostly recognize the hidden pattern of illegal transactions by using various learning machines or data mining like Bayesian Network, DT, Support Vector Machine or Artificial Neural Network. To recognize the pattern and classify the banking transactions, ML methods need to classify in two categories Normal and Abnormal to find suitable features for increase their accuracy. Actually, the feature selection is too important in bank fraud recognition and it is a kind of optimization too because the suitable feature selection causes recognize error go down by techniques like DT. In this research we use DTA to select important features related with bank fraud to decide and knowledge discovery which has a good speed in discover of bank fraud. When the features of bank fraud select in right way and with good accuracy then the accuracy of DT will be increased and we must select those features that are more important to get better accuracy in recognition of fraud and money laundering.
iGrow: A Smart Agriculture Solution to Autonomous Greenhouse Control
Authors: Cao Xiaoyan , Yao Yao , Li Lanqing , Zhang Wanpeng , An Zhicheng , Zhang Zhong , Guo Shihui , Xiao Li , Cao Xiaoyu , Luo Dijun 
Published: July 2021

Abstract
Agriculture is the foundation of human civilization. However, the rapid increase and aging of the global population pose challenges on this cornerstone by demanding more healthy and fresh food. Internet of Things (IoT) technology makes modern autonomous greenhouse a viable and reliable engine of food production. However, the educated and skilled labor capable of overseeing high-tech greenhouses is scarce. Artificial intelligence (AI) and cloud computing technologies are promising solutions for precision control and high-efficiency production in such controlled environments. In this paper, we propose a smart agriculture solution, namely iGrow: (1) we use IoT and cloud computing technologies to measure, collect, and manage growing data, to support iteration of our decision-making AI module, which consists of an incremental model and an optimization algorithm; (2) we propose a three-stage incremental model based on accumulating data, enabling growers/central computers to schedule control strategies conveniently and at low cost; (3) we propose a model-based iterative optimization algorithm, which can dynamically optimize the greenhouse control strategy in real-time production. In the simulated experiment, evaluation results show the accuracy of our incremental model is comparable to an advanced tomato simulator, while our optimization algorithms can beat the champion of the 2nd Autonomous Greenhouse Challenge. Compelling results from the A/B test in real greenhouses demonstrate that our solution significantly increases production (commercially sellable fruits) (+10.15%) and net profit (+87.07%) with statistical significance compared to planting experts. The data and source codes of our work are provided as supplementary materials, and more details are available at: https://github.com/holmescao/SmartAgricultureSolution-iGrow.
Influence of diffuser design on selected operating variables for wastewater flotation systems: a review
Authors: Mukandi M. R. , Basitere M. , Okeleye B. I. , Chidi B. S. , Ntwampe S. K. O. , Thole A. 
Published: July 2021

Abstract
Air diffusers or spargers have been used in separation processes that include conventional wastewater treatment. Over the years, there have been advancements in diffuser design in terms of shape, pore size, orientation and materials of construction as a way of mitigating challenges such as fouling, clogging, energy consumption and poor system efficiency. Some of the available air diffusers are inadequate to solve most of these challenges due to reduced quality and increased quantity of wastewater being treated. Additionally, there is a paucity of information regarding air diffuser design and their effect on operational parameters in wastewater treatment. This review seeks to address the advancement in diffuser design and also the effects of design factors including parameters of air diffusers with a focus of their use in a column flotation system for wastewater treatment.