Miracle-dz/UniFAR-FTUs huggingface dataset:
A modified space truss analogy model for ultimate torsional capacity of ultra-high-performance concrete solid and box beams

This paper presents an analytical model using a modified space truss analogy for predicting the ultimate torsional capacity of reinforced ultra-high-performance concrete (R-UHPC) beams. Both solid and box beams are considered. The credibility of the proposed model is evaluated by comparing the theoretical predictions of the ultimate torsional capacity and its corresponding twist (Tu-αu) to experimental results of several R-UHPC beams (solid and box beams) available in the literature. The results are also compared with the calculation of the existing models. The comparisons show that the proposed model gives acceptable predictions of the ultimate limit torsional capacity of R-UHPC beams and the corresponding twist angle and offers better accuracy than the existing analytical models. Additionally, a parametric study was carried out to determine factors that influence the ultimate torsional capacity. The result shows that the ultimate torsional capacity is not just improved by the increase of the tensile strength of UHPC but also increased by the increase of the reinforcements (transversal and longitudinal).
Data-Driven Coordinated Voltage Control Method of Distribution Networks With High DG Penetration

The highly penetrated distributed generators (DGs) aggravate the voltage violations in active distribution networks (ADNs). The coordination of various regulation devices such as on-load tap changers (OLTCs) and DG inverters can effectively address the voltage issues. Considering the problems of inaccurate network parameters and rapid DG fluctuation in practical operation, multi-source data can be utilized to establish the data-driven control model. In this paper, a data-driven voltage control method with the coordination of OLTC and DG inverters on multiple time-scales is proposed without relying on the accurate physical model. First, based on the multi-source data, a data-driven voltage control model is established. Multiple regulation devices such as OLTC and DG are coordinated on multiple time-scales to maintain voltages within the desired range. Then, a critical measurement selection method is proposed to guarantee the voltage control performance under the partial measurements in practical ADNs. Finally, the proposed method is validated on the modified IEEE 33-node and IEEE 123-node test cases. Case studies illustrate the effectiveness of the proposed method, as well as the adaptability to DG uncertainties.
Beliefs and Supportive Actions of K-12 Superintendents Toward the Implementation of Trauma-Informed Strategies

This quantitative study explored the relationship between the beliefs of school district superintendents regarding the implementation of trauma-informed strategies and their actions in supporting building principals with the implementation of those strategies within the K-12 school system in New York State. The findings suggest that superintendents who believe in implementing trauma-informed strategies believe in doing so equally across elementary middle, and high schools; have had conversations with members of their Board of Education and perceive their support to implement said strategies; and that female superintendents were more likely to report they believe in implementing trauma-informed strategies than their male counterparts.
Determinants of Bank Closures: Exploring the Relationship between Neighborhood Characteristics and Bank Branch Locations

Abstract Retail Banking in Canada has experienced significant changes perpetuated by both digital trends in retail and changes in consumer demand. These changes have resulted in significant decreases in client interactions with physical branches in favor of digital platforms (online, mobile, phone banking). As the “Big Five” Canadian banks pursue network optimization strategies focused on reinvesting savings into their digital channels, branch closures will accelerate, resulting in market gaps. Thus, the central aim of this study is to understand the relationship between neighborhood characteristics (built environment and socio-economic) and bank branch locations. Using the city of Toronto as a case study, this research addresses three objectives: (i) to identify neighborhoods underserviced by the “Big Five” Canadian banks; (ii) to examine the spatial relationship between neighborhood characteristics and branch locations; and (iii) to quantify the key neighborhood characteristics linked to branch locations. This study finds that financial exclusion continues to be associated with local dynamics of physical topography, road network, demographics, and socio-economic status. While financial exclusion is becoming a growing area of concern for policy makers, this research finds that access to affordable financial services still proves to be an issue that requires attention.
Dispersal Increases Spatial Synchrony of Populations but Has Weak Effects on Population Variability: A Meta-analysis

The effects of dispersal on spatial synchrony and population variability have been well documented in theoretical research, and a growing number of empirical tests have been performed. Yet a synthesis is still lacking. Here, we conducted a meta-analysis of relevant experiments and examined how dispersal affected spatial synchrony and temporal population variability across scales. Our analyses showed that dispersal generally promoted spatial synchrony, and such effects increased with dispersal rate and decreased with environmental correlation among patches. The synchronizing effect of dispersal, however, was detected only when spatial synchrony was measured using the correlation-based index, not when the covariance-based index was used. In contrast to theoretical predictions, the effect of dispersal on local population variability was generally nonsignificant, except when environmental correlation among patches was negative and/or the experimental period was long. At the regional scale, while low dispersal stabilized metapopulation dynamics, high dispersal led to destabilization. Overall, the sign and strength of dispersal effects on spatial synchrony and population variability were modulated by taxa, environmental heterogeneity, type of perturbations, patch number, and experimental length. Our synthesis demonstrates that dispersal can affect the dynamics of spatially distributed populations, but its effects are context dependent on abiotic and biotic factors.
An Ensemble Deep Learning Approach for Emotion Detection in Arabic Tweets

—Now-a-days people use social media websites for different activities such as business, entertainment, following the news, expressing their thoughts, feelings, and much more. This initiated a great interest in analyzing and mining such user-generated content. In this paper, the problem of emotion detection (ED) in Arabic text is investigated by proposing an ensemble deep learning approach to analyze user-generated text from Twitter, in terms of the emotional insights that reflect different feelings. The proposed model is based on three state-of-the-art deep learning models. Two models are special types of Recurrent Neural Networks RNNs (Bi-LSTM and Bi-GRU), and the third model is a pre-trained language model (PLM) based on BERT and it is called MARBERT transformer. The experiments were evaluated using the SemEval-2018-Task1-Ar-Ec dataset that was published in a multilabel classification task: Emotion Classification (EC) inside the SemEval-2018 competition. MARBERT PLM is compared to one of the most famous PLM for dealing with the Arabic language (AraBERT). Experiments proved that MARBERT achieved better results with an improvement of 4%, 2.7%, 4.2%, and 3.5% regarding Jaccard accuracy, recall, F1 macro, and F1 micro scores respectively. Moreover, the proposed ensemble model showed outperformance over the individual models (Bi-LSTM, Bi-GRU, and MARBERT). It also outperforms the most recent related work with an improvement ranging from 0.2% to 4.2% in accuracy, and from 5.3% to 23.3% in macro F1 score.
The interdependence between collective practices and the green governance of an agroecology network

ABSTRACT Green governance of common goods balances the collective actions of economic production and the preservation of natural resources. This study improves the governance of sustainable initiatives with the concept of practice, answering the following question: how do collective practices support green governance? We performed an instrumental case study of the ‘Rede Ecovida,’ an agroecology network of 4,500 families. We adopted a qualitative approach based on experiential knowledge, collected through participant and non-participant observations, interviews, and documents and submitted to thematic analysis. We found that collective practices affect and are affected by the green governance constructs. Based on our findings, we evidence the dynamic interdependence between elements of practice and the constructs of green governance and we propose guidelines for the collective decision-making in sustainable initiatives.
Modeling and control of a bearingless permanent magnet synchronous motor

This paper presents a suspension force modeling method of BPMSMs based on Maxwell stress tensor method. By deducing the magnetic flux density of the airgap in BPMSMs using magnetic circuit analytic approach, the suspension force model with rotor eccentricity is established. And then the suspension force of a surface-mounted BPMSM is computed by the finite element method. Furthermore, in order to confirm the performance of the BPMSM and the magnetic suspension in real time, a prototype machine and its control scheme is set up and then corresponding experimental study is carried on. Rotor stabilization with magnetic levitation by using Maxwell tensor modeling method is verified by the simulation and experimental results.
An effective Smith predictor based fractional-order PID controller design methodology for preservation of design optimality and robust control performance in practice

In this study, an optimal and robust fractional order PID (FOPID) controller design approach is suggested for Smith predictor based FOPID (SP-FOPID) control system design. This new design approach considers continued fraction expansion (CFE) based approximate models in the optimal design task of FOPID controllers, and this approach preserves the design optimality in control applications. For this purpose, an inverse controller loop shaping design methodology is performed in order to approximate the frequency response of a Bode’s ideal loop reference model, and robust performance CFE based FOPID controller models are obtained by solving a multi-objective optimisation problem via a genetic algorithm. Thus, the suggested algorithm can deal with several controller realisation concerns in the design task of FOPID controllers and overcome real-world controller performance issues related with model approximation errors and signal saturation boundaries of electronic hardware. Illustrative design examples demonstrate that the suggested design scheme can preserve design optimality and improve practical control performance in practice.
PEMODELAN BOD DAN COD DENGAN PENDEKATAN REGRESINONPARAMETRIK BIRESPON PADA DATA LONGITUDINAL BERDASARKAN ESTIMATOR POLINOMIAL LOKAL (STUDI KASUS: DAERAH AIR MENGALIR SUNGAI SURABAYA SEBAGAI BAHAN BAKU AIR PDAM)

Fungsi Sungai Surabaya adalah sebagai penyedia air bersih, komunikasi, dan sebagai konservasi alam. Disamping itu, fungsi fital Sungai Surabaya pada kota Surabaya sebagai bahan baku air PDAM Surabaya. Peranannya sebagai tempat penampungan limbah industri dan limbah domestik menyebabkan penurunan kualitas air di bagian hilir Sungai Surabaya. Pada tahun 2015 sebanyak 62% pencemaran sungai di Surabaya diakibatkan oleh limbah domestik rumah tangga, sedangkan 38% sisanya limbah industri dan limbah lainnya. Beberapa variabel kualitas air yang digunakan dalam menentukan tercemarnya sungai, sesuai dengan peraturan Dewan Pemerintahan Jawa Timur nomor 2 tahun 2002, yaitu antara lain Dissolve Oxygen (DO), Chemical Oxygen Demand (COD), dan Biochemical Oxygen Demand (BOD). BOD dan COD merupakan variabel kualitas air yang juga dapat dipantau dari kadar DO yang ada di aliran sungai. Skripsi ini menggunakan regresi nonparametrik birespon pada data longitudinal berdasarkan estimator polinomial lokal. Skripsi ini menggunakan 8 subjek Daerah Air Mengalir yaitu, Dam Canggu bridge, Dam Perning bridge, Dam Jrebeng bridge, Dam Cangkir Tambangan, Dam Bambe Tambangan, Dam Jembatan Sepanjang, Dam Gunungsari, dan Dam Jagir. Setiap subyek memiliki 12 observasi yang diteliti dari Januari sampai Desember 2015. Model terbaik dengan menggunakan estimator polinomial lokal dengan orde pada BOD yaitu satu dan COD yaitu dua. Hasil estimasi menjelaskan bahwa. Ketika DO menurun maka BOD dan COD akan meningkat hal ini berarti ekosistem yang ada di sungai menjadi tidak sehat. Pada Dam Jagir observasi BOD dan COD menjauhi kurva estimasi, hal ini disebabkan karena Jagir merupakan bagian hilir dari Sungai Surabaya yang menjadi tempat penumpukan limbah yang berasal dari hulu sungai.
SH003 and Docetaxel Show Synergistic Anticancer Effects by Inhibiting EGFR Activation in Triple-Negative Breast Cancer

Although many anticancer drugs have been developed for triple-negative breast cancer (TNBC) treatment, there are no obvious therapies. Moreover, the combination of epidermal growth factor receptor- (EGFR-) targeted therapeutics and classical chemotherapeutic drugs has been assessed in clinical trials for TNBC treatment, but those are not yet approved. Our serial studies for newly developed herbal medicine named SH003 provide evidence of its broad effectiveness in various cancers, especially on TNBC. The current study demonstrates a synergic effect of combinatorial treatment of SH003 and docetaxel (DTX) by targeting EGFR activation. The combinatorial treatment reduced the viability of both BT-20 and MDA-MB-231 TNBC cells, displaying the synergism. The combination of SH003 and DTX also caused the synergistic effect on apoptosis. Mechanistically, the cotreatment of SH003 and DTX inhibited phosphorylation of EGFR and AKT in both BT-20 and MDA-MB-231 cells. Moreover, our xenograft mouse tumor growth assays showed the inhibitory effect of the combinatorial treatment with no effect on body weight. Our immunohistochemistry confirmed its inhibition of EGFR phosphorylation in vivo. Collectively, combinatorial treatment of SH003 and DTX has a synergistic anticancer effect at a relatively low concentration by targeting EGFR in TNBC, indicating safety and efficacy of SH003 as adjuvant combination therapy with docetaxel. Thus, it is worth testing the combinatorial effect in clinics for treating TNBC.
Exploiting multiple view geometry in X-ray testing: Part I, theory

Multiple view geometry is increasingly being used in machine vision. In the first part of this two part paper, we present a mathematical background of the multiple view geometry that is normally used in X-ray computer vision. The article describes an explicit model which relates the three dimensional coordinates of an object to the two dimensional coordinates of the digital X-ray image pixel, the geometric and algebraic constraints between two, three and four X-ray images taken at different projections of the object and the problem of three dimensional reconstruction from n views. Part II, to appear in the December issue, will present the application of multiple view geometry to X-ray testing and describe applications which use the theory.
MapStakes: a tool for mapping, involving and monitoring stakeholders in co-creation processes

Despite widespread use of stakeholder approaches in environmental research, the tools and methodologies for mapping and involving actors are not particularly robust. Existing approaches can lead to methodological ambiguity, limited transparency in the process of stakeholder selection, and lack of robustness when monitoring and evaluating these processes. To respond to these challenges, we developed a tool for increasing objectivity of stakeholder mapping, engagement, and monitoring of co-creation processes. The tool provides a stepwise approach for users with little or no experience of participatory methods.
Improving the damage tolerance of Si3N4 by forming laminate composites with refractory metals

The objective of this research was to demonstrate that the damage tolerance of Si3N4 could be significantly improved by forming laminate composites with refractory metals, providing materials that undergo graceful failure, rather than the fast-fracture mechanism exhibited by monolithic Si3N4. A damage tolerant Si3N4 could be used as a ring material in an all-ceramic bearing, decreasing the chance for catastrophic failure if the ring is stressed in tension during operation. The technical approach formed a laminate composite material using alternating Si3N4-metallic layers, with both outer layers being Si3N4 to take advantage of its greater wear resistance, chemical stability, and thermal stability. The metallic layers are designed to arrest any cracks in the outer layers, thus producing a toughened Si3N4 and avoiding the catastrophic failure behavior exhibited by monolithic ceramics. The laminate composites were fabricated using a combination of tape-casting Si3N4 and metals from slurries, as well as metal foils, followed by hot pressing at 1500°C. The metallic materials employed were chromium, titanium, and tantalum. Analysis confirmed that the interfaces were well formed, and the laminates with chromium and titanium formed intermetallic compounds more readily than the composites with tantalum. The Si3N4-Ta laminates demonstrated crack deflection and bridging behavior during failure and flexural strength of 800–900 MPa. The hardness and elastic modulus of Si3N4-Ta laminates measured by nanoindentation were similar to those reported in literature. The hardness across the interface of the Si3N4-Ta composite varied according to the composition of the interface, which displayed a profile indicative of a diffusion bond.
Deformed Identity Crime Detection of Online Credit Application as A First Stage of Credit Life Cycle

Now a day's identity crime is well known, prevalent and prominent in our society. The fraud of credit application is a specific case of identity crime. There are some algorithms which have been implemented to detect or resolve resilience identity. To address the limitation of existing algorithm and to detect and combat identity crime in real time this paper proposes a new multilayer detection system complemented with two additional layer click detection and deformation of spike detection. Click finds real social relationship to reduce the suspicion score with fixed set of attribute. Deformation of spike detects spikes in duplicates to increase the suspicion score and finally rejects the invalid entries. Although multilayer mining algorithm is specific to credit application fraud detection, but the concept of resilience or deformation are general to design, implement and evaluate of all detection system to detect and remove fraud identities.
Hippocampal Mitochondrial Abnormalities Induced the Dendritic Complexity Reduction and Cognitive Decline in a Rat Model of Spinal Cord Injury

Spinal cord injury (SCI) is a progressive neurodegenerative disease in addition to a traumatic event. Cognitive dysfunction following SCI has been widely reported in patients and animal models. However, the neuroanatomical changes affecting cognitive function after SCI, as well as the mechanisms behind these changes, have so far remained elusive. Herein, we found that SCI accelerates oxidative stress damage of hippocampal neuronal mitochondria. Then, for the first time, we presented a three-dimensional morphological atlas of rat hippocampal neurons generated using a fluorescence Micro-Optical Sectioning Tomography system, a method that accurately identifies the spatial localization of neurons and trace neurites. We showed that the number of dendritic branches and dendritic length was decreased in late stage of SCI. Western blot and transmission electron microscopy analyses also showed a decrease in synaptic communication. In addition, a battery of behavioral tests in these animals revealed hippocampal based cognitive dysfunction, which could be attributed to changes in the dendritic complexity of hippocampal neurons. Taken together, these results suggested that mitochondrial abnormalities in hippocampal neurons induced the dendritic complexity reduction and cognitive decline following SCI. Our study highlights the neuroanatomical basis and importance of mitochondria in brain degeneration following SCI, which might contribute to propose new therapeutic strategies.
Classification of Osteoporosis in the Lumbar Vertebrae using L2 Regularized Neural Network based on PHOG Features

—One of the most common bone diseases in humans is osteoporosis, which is a major concern for the public health. Osteoporosis can be prevented if it is detected at an early stage. The research agenda consists of two phases: pre-processing of X-ray images of the spine and analysis of texture features from trabecular bone lumbar vertebrae L1-L4 for detecting osteoporosis. The preprocessing involves image enhancement of texture features and co-register the images in order to segment the L1-L4 regions in the lumbar spine. Range filtering and Pyramid Histogram of Orientation Gradient (PHOG) are used to analyze texture features. Input images are filtered with a range filter to adjust the local sub range intensities in a specified window to detect edges. Then a PHOG algorithm is designed to determine both the local shape of an image texture and its spatial layout. Based on texture features of lumbar vertebrae L1-L4, classify them as normal or osteoporotic using neural network (NN) models with L2 regularization. In an experiment, X-ray images and dual-energy X-ray absorptiometry (DXA) reports of individual patients are used to verify the system. DXA reports describe a statistical analysis of normal and osteoporotic results. However, the proposed work is categorized according to the texture features as normal or osteoporotic. 99.34% classification accuracy is achieved; cross-validation of these classified results is done with the DXA reports. Diagnostic accuracy of the proposed method is higher than that of the existing DXA with X-ray. Further, the area under the Receiver Operating Characteristic (ROC) curve for L1-L4 had a significantly higher sensitivity for osteoporosis.
The nature of the vortical structures in the near wake of the Ahmed body

This study presents the results from high-spatial-resolution water-channel velocity-field measurements behind an Ahmed body with 25° rear slant angle. The Ahmed body represents a simplified generic model of a hatchback automobile that has been widely used to study near-wake flow dynamics. The results help clarify the unresolved question of whether the time-mean near-wake flow structure is topologically equivalent to a toroidal vortex or better described by a pair of horizontally aligned horseshoe vortices, with their legs pointing downstream. The velocimetry data presented allows the tracking of the vortical structures throughout the near wake through a set of orthogonal planes, as well as the measurement of their circulation. The spanwise vortices that form as the flow separates from the top and bottom rear edges are shown to tilt downstream at the sides of the body, while no evidence is found of a time-mean attached toroidal vortex, at least for the Reynolds number (based on the square root of the frontal area) of R e FA ~ 30 , 000 under consideration.