Miracle-dz/UniFAR-FTUs huggingface dataset:
A novel approach to leveraging social media for rapid flood mapping: a case study of the 2015 South Carolina floods

ABSTRACT Rapid flood mapping is critical for local authorities and emergency responders to identify areas in need of immediate attention. However, traditional data collection practices such as remote sensing and field surveying often fail to offer timely information during or right after a flooding event. Social media such as Twitter have emerged as a new data source for disaster management and flood mapping. Using the 2015 South Carolina floods as the study case, this paper introduces a novel approach to mapping the flood in near real time by leveraging Twitter data in geospatial processes. Specifically, in this study, we first analyzed the spatiotemporal patterns of flood-related tweets using quantitative methods to better understand how Twitter activity is related to flood phenomena. Then, a kernel-based flood mapping model was developed to map the flooding possibility for the study area based on the water height points derived from tweets and stream gauges. The identified patterns of Twitter activity were used to assign the weights of flood model parameters. The feasibility and accuracy of the model was evaluated by comparing the model output with official inundation maps. Results show that the proposed approach could provide a consistent and comparable estimation of the flood situation in near real time, which is essential for improving the situational awareness during a flooding event to support decision-making.
Central Sensitization in Patients with Chronic Pain Secondary to Carpal Tunnel Syndrome and Determinants

Purpose Central sensitization (CS) is commonly seen in chronic pain disorders, including neuropathic pain. However, there exist inconsistencies concerning the presence of CS in chronic pain secondary to carpal tunnel syndrome (CTS). CS and neuropathic pain manifestations in CTS remain not well established. Therefore, this study aims to investigate the CS and pain profiles in patients with CTS and to explore the potential determinants associated with CS. Patients and Methods Patients with suspected CTS symptoms lasting 3 months or above and healthy controls were enrolled. History, physical examinations, and nerve conduction studies were employed to confirm the diagnosis and severity of median nerve dysfunction. The central sensitization inventory (CSI) was used to screen CS. Other outcomes included neuropathic pain, CTS-specific symptom severity and functions, emotion, and health-related quality of life. Between-group comparisons were conducted in terms of the CS presence. Logistic regression analysis was performed to identify determinants associated with CS. Results Over 60% of participants with CTS were found with clinical CS, significantly higher than that in the control group. More than 70% of the CTS participants were identified to have possible or very likely neuropathic pain components. In addition, one-fourth of CTS cases had depression or anxiety. Anxiety was associated with an increased risk of developing CS in CTS (adjusted OR=1.31, 95% CI 1.08–1.59), whereas higher self-perceived general health rating was negatively associated with the presence of CS (adjusted OR=0.92, 95% CI 0.88–0.97) in the multivariate adjusted regression model. Conclusion CS is prevalent in patients with CTS. Predominant neuropathic pain characteristics were uncovered in CTS patients as well as comorbid psychological distress. Significant association was found between anxiety and CS presence. Self-perceived general health was inversely related to CS. Further research is warranted to explore the mechanisms of anxiety and central pain processing in painful entrapment neuropathy.
ASSESSMENT OF NEW YORK’S POLLUTION DISCHARGE ELIMINATION PERMITS FOR CAFO’S: A REGIONAL ANALYSIS

In this paper, we apply mathematical programming methods to account explicitly for restrictions on land application of nutrients from large dairy operations in New York and to analyze the effects on measured outcomes of farm management adjustments to the nutrient policy and to recent changes in relevant agricultural prices. Based on a set of unique data, we assess the effects of new regulations for nutrient management by confined animal feeding operations (CAFOs) on farm income, land use, manure and fertilizer management, and environmental quality for an important dairy production region in New York. Our mathematical methods also allow us to make distinctions between the value of land for production and as a manure disposal site so that we can assess the differential effects of the land nutrient application standards on the economic value of land. The results indicate that adjustments to dairy rations in response to the current high prices of traditional feed ingredients lead to increased nitrogen and phosphorus content in dairy waste. In addition, crop nutrient applications from manure far exceed the critical uptake levels for optimum yield and increase the risks of nutrient loading to the environment. In a related paper, we demonstrate that while the CAFO regulations correct for this problem, the reductions in the risks of nutrient loadings could be accompanied by losses to farm income. Our current application to an important dairy production region in Western New York further buttresses this point. We also demonstrate that farm net revenue is sensitive to the availability of nearby land suitable for manure disposal. Since the new nutrient restrictions require that about half of the manure produced on the dairy farms in the region be transported off-site for disposal, crops with higher potential to absorb field nutrients are more attractive than would otherwise be the case. The shadow prices for CAFO land with low soil phosphorus increase, reflecting not only the value of land for crop production but also its value as a site for manure disposal. These shadow prices reflect what the CAFOs could pay for additional land, and this price falls as the distance to the CAFO increases.
Assessment of Rainfall Intensity Equations Enlisted in the Egyptian Code for Designing Potable Water and Sewage Networks

The design of combined sewage system networks is based on the sanitary discharge (domestic, industrial) and the runoff generated by rainfall. The Egyptian code of practice for designing potable water and sewage networks gives two Intensity-Duration-Frequency (IDF) equations to calculate the intensity of rainfall to be applied to all cities of Egypt. The purpose of this research is to study and assess the adequacy of the rainfall intensity equations suggested by the aforementioned Egyptian code. This is carried out taking into consideration the available rainfall ground station measurements and remote sensing Tropical Rainfall Measurement Mission (TRMM) satellite rainfall estimates. This assessment leads to the following results. For the Mediterranean coastal cities, the code of practice equations significantly underestimates the rainfall intensities for all storm durations, which may lead to road networks damage and accidents due to hydroplaning and road flooding. On the contrary, for many other southern cities along the Nile Valley, the code equations significantly overestimate the rainfall intensities, which affects the economical aspect of the sewage network. Consequently, the current research suggests new rainfall intensity equations instead of the code equations.
Magnetite exsolution in ilmenite from the Fe-Ti oxide gabbro in the Xinjie intrusion (SW China) and sources of unusually strong remnant magnetization

Abstract This study investigates magnetite exsolution in ilmenite from Fe-Ti oxide gabbro in the Xinjie intrusion, SW China. Exsolved magnetite lamellae in ilmenite contain nearly pure Fe304 with ~l wt% TiO2. EBSD-based analyses indicate that the magnetite lamellae have close-packed oxygen planes and directions parallel to those in the host ilmenite with {111}Mag//(0001)Ilm and <110>Mag//<1010>. The Fe2+ in the magnetite lamellae is probably derived from adjacent titanomagnetite by sub-solidus inter-oxide cation repartitioning of Fe2+ + Ti4+ = 2Fe3+ during cooling. It is thus suggested that only Fe3+ cations in the magnetite lamellae should be included into the composition of the Ilm-Hemss precursor for the Fe-Ti oxide oxy-thermometer. The existence of magnetite exsolution in ilmenite also provides an alternative explanation for unusually strong natural remnant magnetization in natural ilmenite.
Structural Safety Assessment of Shaft Steelwork – A Review

shaft steelwork is a component of critical infrastructure in underground mines. it connects the min - ing areas to the surface and enables the transport of personnel, equipment, and raw materials. its failure or malfunction poses a threat to people and causes economic losses. Shaft steelwork is an exceptional engineering structure exposed to dynamic loads from large masses moving at high speeds and is subject to intensive deterioration resulting from corrosion and geological or mining-induced deformations. These issues cause shaft steelwork to be subject to high structural safety requirements, design oversizing, demanding maintenance procedures, and costly replacement of corroded members. The importance and unique working conditions of shaft steelwork create practical design and maintenance problems that are of interest to engineers and scientists. This paper reviews publications on the structural safety of rigid shaft steelwork and summarises the range of research from the detection of guide rail failures through the assessment of load effects and guide resistance, to the evaluation of structural reliability. The effects of guide rail failures on guiding forces, models of the conveyance-steelwork interaction, the load-carrying capacity of shaft steelwork under advanced corrosion, and the probabilistic assessment of structural reliability are presented. Significant advances in understanding the mechanical behaviour of shaft steelwork and assessing its properties have been reported. This review summarises the current state of research on shaft steelwork structural safety and highlights key future development directions.
Low-profile reconfigurable saline water-based ultrawideband metamaterial absorber

Saline water solutions are widely used in the design of electromagnetic (EM) absorbers due to their high dielectric loss. However, most of the saline water solution-based absorbers are not reconfigurable. In this work, we propose a low-profile, reconfigurable saline water-based ultra-wideband metamaterial absorber. Two types of dielectric resonators, pyramid-shaped and cube-shaped cavities, are filled with saline water to create multi-frequency resonances and realize ultra-wideband absorption. We fabricate an absorber sample with 3D-printing technology and conduct experiments. It is demonstrated that the absorber exhibits an absorptivity of over 90% for EM waves within 6.7–63 GHz, with a relative bandwidth of 161.5%. The absorption performance remains stable under different incident angles of different polarizations, and the absorber can maintain a high absorbing capacity at different temperatures. Emptying the saline water causes complete reflection of all EM waves from 1 GHz to 53 GHz. Furthermore, the infrared radiation of the absorber can be effectively controlled at a low level by introducing cryogenic saline water. This saline-based reconfigurable absorber can find potential applications in EM camouflage and protection in military scenarios.
Les mollusques terrestres et fluviatiles du mont Nimba

Le present article reprend toutes les especes deja signalees du mont Nimba ainsi que plusieurs autres qui etaient connues des regions forestieres avoisinantes, mais non encore recoltees dans le massif du mont Nimba proprement dit. Deux especes apparemment nouvelles sont egalement decrites et figurees sous les noms provisoires de Trachycystis sp. 1 et sp. 2.
An Efficient Model for Plant Disease Detection in Agriculture Using Deep Learning Approaches

Detecting plant diseases is crucial as they can significantly impact plant growth. At the same time, several machine-learning methodologies have been employed to distinguish and categorize plant diseases. Deep learning, a subset of machine learning, has shown promising results in terms of accuracy. Using CNN architectures and visualization methods, scientists can develop and implement effective strategies for detecting and classifying plant disease symptoms. These methods primarily rely on analyzing leaf characteristics such as color and damage. A plant-village dataset of 54,306 images representing 14 different crop classes and 26 types of infections was used to train the models. The convolutional neural networks (CNNs) and additional machine learning models were trained on this dataset and achieved an impressive accuracy rate of 95% in identifying disease symptoms on plant leaves. Additionally, an efficient web-based application for crop disease detection was developed as part of this approach.
GEOPHYSICAL INVESTIGATION OF ABANDONED BACK-FILLED RAILWAY LINE: IMPLICATION ON ADJACENT BUILDINGS

A geophysical investigation was carried out on a back-filled segment of an abandoned railway route at Okebadan Estate, Ibadan using electrical resistivity imaging. The study is aimed at depicting the cause(s) of settlement that led to building foundation failure. Five profile lines were established during the study and the apparent resistivity values obtained from the traverse were plotted against the mid-point of electrode separation using least-squares inversion algorithm. Pockets of low resistivity region were obtained from the inverted sections with resistivity values ranging from 77 Ω-m to ˂400 Ω-m. The suspected back-filled earth materials were suspected to be clay and clayey sand. Results indicated that materials used in back filling the abandoned rail route were not well compacted. Consequently, the structural failure of buildings along this abandoned route was attributed to differential settlements of clays and clayey sands on which they were erected. Keywords: Backfill, Foundation, Resistivity, Settlement
Social responsibility and green practices in organizational performance: Corporate image as mediating mechanism

Sustainability-related endeavors are progressively employed to cultivate a favorable business reputation that enhances consumer loyalty and, as a result, enhances organizational performance. This study is situated within a specific research issue and seeks to examine the mediating function of corporate image in the association between social and moral responsibility, green practices in the workplace, and organizational performance. The study sample consisted of 223 individuals who were employed as workers, ranging in age from 18 to 64 years. The study was operationalized using a quantitative methodology. Data were collected through four questionnaires assessing employees' perceptions of social and moral responsibility, green practices in the workplace, corporate image, and the performance of the organization where they work. The results revealed that social and moral responsibility, green practices in the workplace, and corporate image have a significant positive influence on organizational performance. It was also found that when corporate image enters the model with the status of a mediating variable, the effect of social and moral responsibility on organizational performance decreases but remains significant. These results suggest that when organizational performance is evaluated, the importance attributed to corporate image overlaps with social and moral responsibility. This research highlights the importance of cultivating a positive corporate image. It also helps to increase perceptions of the organization's social and environmental responsibility and to strengthen customer loyalty by improving its reputation and fostering higher levels of trust. These improvements can subsequently increase sales, boost profits, and expand the organization's market share.
Social factors in the management of youth participation in the labor market in Asia: Justification of causal dependencies

The study aims to determine social factors in the management of youth participation in the labor market in Asia based on causal analysis. The information base involves youth employment and youth working-age population by education levels, rural/urban areas, marital and disability status, time arrangement, and job contract. The sample covers 14 countries the ILO assigned to the Asia group for 2012–2021. Correlation analysis identifies dependencies between social factors and youth employment and determines their nature and strength, considering time lags when this influence becomes maximally significant. Granger causality analysis contributes to the establishment of causal dependencies within identified relationships. The greatest causal effect on youth employment is identified for educational level (basic educational level is a cause of positive changes in youth employment level in four countries, and youth employment level is a cause of growth of basic educational level in eight countries, including three countries with bidirectional causality, mostly with strong/very strong strength without lag). Quantitative indicator of youth working-age population by gender influences youth employment in Azerbaijan, Israel, the Philippines, and Thailand (from moderate to strong strength with lag from 0 to 2 years), by marital status – in Cyprus, Georgia, Korea, and Thailand (mostly very strong, time lag – from 0 to 2 years), by social factor of disability – in Shri-Lanka and Mongolia (very strong with 1-year time lag). The results can be used to form directions for managing youth participation in the labor market to improve social, educational, and youth policy.
Nanoarray of Vivaldi Rectenna for Infrared-energy Harvesting

This article presents the design of an array of rectennas operating at 28.3 THz for infrared (IR) energy harvesting applications. The basic element of the array consists of a Vivaldi-dipole rectenna composed of two arms made with different conductors (gold and titanium). A metal-insulator-metal (MIM) tunnel diode is used to rectify the THz ac current. The proposed MIM diode consists of a very thin layer of Al2O3 sandwiched between the two metal electrodes. Arrays of two, three, and four rectennas are investigated. The improvement of the energy captured by coupling several elements in the same structure with a common gap is also investigated. This array architecture, without feeding network, may reduce the number of rectifying diodes and, therefore, decrease losses and increase the overall efficiency. Finally, it has been found that the four-elements rectenna array has a maximum electric field intensity of 62.4 × 104 V/m at 28.3 THz.
Detecting Android Malware: Unleashing the Power of Machine Learning

As smartphones continue to dominate the digital landscape, the threat of Android malware looms large, compromising user privacy and security. This study delves into the realm of machine learning to tackle the ever evolving challenge of detecting Android malware, unleashing the power of advanced algorithms to enhance malware detection capabilities. A comprehensive dataset comprising a diverse range of benign and malicious applications is collected and analyzed. Meticulous data preprocessing and feature engineering techniques are employed to extract meaningful attributes that capture the intricate behaviors and characteristics of malware. The research focuses on employing a variety of machine learning algorithms, including logistic regression, KNN, random forest, decision trees and ensemble models to identify the most suitable algorithm that exhibits optimal performance in terms of accuracy, precision, recall, and F1_score. Furthermore, the research evaluates the trained model on a separate testing dataset, meticulously measuring its effectiveness in real-world scenarios and analyze key evaluation metrics such as accuracy and the area under the receiver operating characteristic curve (ROC-AUC) to provide a comprehensive assessment of the model's performance. The outcomes of this study pave the way for enhanced cybersecurity measures, empowering users to safeguard their smartphones from the ever-present threats of malicious applications.
The Effect of Work-Life Balance And Job Embeddedness On Organizational Citizenship Behavior: The Mediating Role of Job Satisfaction

Good governance requires improving the bureaucracy that understands the various desires of the community, especially related to public services, so that the Human Resources (HR) of the government apparatus have an important role in achieving Good Governance. The emergence of disparities in behavior that prioritizes individual or group tasks, different acceptance if there are additional tasks outside of their basic duties, objections if required to work outside working hours indicate that there are still problems related to organizational citizenship behavior. The purpose of this study is to determine the direct influence of work-life balance and job embeddedness on organizational citizenship behavior, as well as the indirect influence of work-life balance and job embeddedness on organizational citizenship behavior through job satisfaction of civil servants at the Directorate General of Intellectual Property. The research method used was quantitative research using survey techniques and questionnaires on civil servants of the Directorate General of Intellectual Property with a sample of 235 respondents. Data analysis using Structural Equation Modeling (SEM) with SmartPLS v.3. 2.9 software. The results showed that work-life balance and job embeddedness had a positive and significant direct influence on organizational citizenship behavior and a positive and significant indirect influence through job satisfaction
Imaging thermal plasma mass and velocity analyzer

We present the design and principle of operation of the imaging ion mass and velocity analyzer on the Enhanced Polar Outflow Probe (e‐POP), which measures low‐energy (1–90 eV/e) ion mass composition (1–40 AMU/e) and velocity distributions using a hemispherical electrostatic analyzer (HEA), a time‐of‐flight (TOF) gate, and a pair of toroidal electrostatic deflectors (TED). The HEA and TOF gate measure the energy‐per‐charge and azimuth of each detected ion and the ion transit time inside the analyzer, respectively, providing the 2‐D velocity distribution of each major ionospheric ion species and resolving the minor ion species under favorable conditions. The TED are in front of the TOF gate and optionally sample ions at different elevation angles up to ±60°, for measurement of 3‐D velocity distribution. We present examples of observation data to illustrate the measurement capability of the analyzer, and show the occurrence of enhanced densities of heavy “minor” O++, N+, and molecular ions and intermittent, high‐velocity (a few km/s) upward and downward flowing H+ ions in localized regions of the quiet time topside high‐latitude ionosphere.