Miracle-dz/UniFAR-FTUs huggingface dataset:
Vulnerability Profile and Risk Perception towards an Inclusive Disaster Risk Reduction for the Flood Vulnerable Communities of Davao City

Development and disasters are closely linked but the cause-and-effect relationship between disasters and socio-economic development was ignored in the past. Thus, the United Nations International Strategy for Disaster Reduction (UNISDR) observed that disasters were seen in the context of emergency response and not as part of long-term development programming. Overtime, effects of disasters can seriously degrade a country’s long-term potential for sustained development. Vulnerable communities of Davao City have experienced flooding that leads to catastrophic effects costing damage to properties and loss of lives. Communities need to build its resiliency to respond to flooding and mitigate its negative impacts, while policy makers and leaders need to consciously, regularly review and update its existing policies to address gaps and promote effective community engagement. This study aims to examine and analyze the respondents’ vulnerability, awareness and perception of flood risks. A survey using multi-stage cluster sampling was conducted among 353 respondents from the top five (5) flood vulnerable barangays. Data from the key informant interviews and focus group discussions were also integrated to provide an in-depth explanation of the patterns emerging from the survey. Results of the study revealed that the vulnerability is associated with socio-demographic characteristics, experience in flooding and responses to flooding. Moreover, risk reduction strategies can be further enhanced through a risk communication management using a localized and participatory approach in the proper knowledge transfer of flood risk communication among the stakeholders involved. Community-based policies and well-defined communication processes must be strengthened to promote inclusive approach towards effective community-based disaster preparedness and management.
Atmospheric leach process for the recovery of nickel and cobalt from limonite and saprolite ores

A method in which the exudation of nickel iron laterite ore by wet metallurgy and atmospheric pressure at a temperature less than the boiling point of the pulp nickel and cobalt is extracted, is provided. Contains high iron laterite of limonite ore, it referred to as in contact with concentrated mineral acid to dissolve the iron and nickel. To maintain the oxidation-reduction potential of less than 1000mV increasing the cobalt dissolved during this process, and the reducing agent is used to maintain the third potential to the 1000-900mV to prevent the reduction of the iron. Mixing of the effusion slurry in the presence of sodium, potassium, ammonium is precipitated as a site at atmospheric pressure as iron. The iron content of the acid produced by the hydrolysis of iron laterite been neutralized by small intestine (corrosion rock) is dissolved nickel in the solution. The resulting slurry may be processed in a conventional manner to recover the nickel and cobalt from the solution.
On Spectral Relaxation Approach to Radiating Powell-Eyring Fluid Flow over a Stretching Disk with Newtonian Heating

In this study we use a new spectral relaxation method to investigate an axisymmetric law laminar boundary layer flow of a viscous incompressible non-Newtonian Eyring-Powell fluid and heat transfer over a heated disk with thermal radiation and Newtonian heating. The transformed boundary layer equations are solved numerically using the spectral relaxation method that has been proposed for the solution of nonlinear boundary layer equations. Numerical solutions are obtained for the local wall temperature, the local skin friction coefficient, as well as the velocity and temperature profiles. We show that the proposed technique is an efficient numerical algorithm with assured convergence that serves as an alternative to common numerical methods for solving nonlinear boundary value problems. We show that the convergence rate of the spectral relaxation method is significantly improved by using method in conjunction with the successive over-relaxation method. It is observed that CPU time is reduced in SOR method compare with SRM method.
Machine-Learning-Assisted Security and Privacy Provisioning for Edge Computing: A Survey

Edge computing (EC), is a technological game changer that has the ability to connect millions of sensors and provide services at the device end. The broad vision of EC integrates storage, processing, monitoring, and control of operations in the Edge of the network. Though EC provides end-to-end connectivity, speeds up operation, and reduces latency of data transfer, security is a major concern. The tremendous growth in the number of Edge Devices and the amount of sensitive information generated at the device and the cloud creates a broad surface of attack and therefore, the need to secure the static and mobile data is imperative. This article is a comprehensive survey that describes the security and privacy issues in various layers of the EC architecture that result from the networking of heterogeneous devices. Second, it discusses the wide range of machine learning and deep learning algorithms that are applied in EC use cases. Following this, this article broadly details the different types of attacks that the Edge network confronts, and the intrusion detection systems and the corresponding machine learning algorithms that overcome these security and privacy concerns. The details of machine learning and deep learning techniques for EC security are tabulated. Finally, the open issues in securing Edge networks and future research directions are provided.
Measurement of Radioactivity in the Granites of Pakistan: A Review

Abstract All human beings are exposed to primordial radiation. The main source of primordial radiation has been naturally radioactive building materials. In Pakistan, among building materials, granites are most commonly used. This paper reviews the previous studies conducted for the estimation of natural radioactivity of granites from Rustam-Koga, Shewa-Shahbazgarhi, Bunair, Mansehra, and Nagarparkar. The techniques used for these studies include gamma spectrometry and field surveys. To assess the radiation hazards associated with granites of Pakistan, primordial radionuclides and corresponding radiation hazards have been estimated. Most of these granites are found to be safe except Rustam-Koga granite, which presents high excess lifetime cancer risk.
Performance Analysis of Hybrid Cellular and Bidirectional Device-to-Device Cooperative NOMA Communication Systems

In this paper, we consider a coexisting network of cellular transmission and device-to-device (D2D) communication, in which two users need to receive downlink signals from base station (BS), meanwhile, they want to exchange information with each other. For such a network, a hybrid cellular and bidirectional D2D cooperative non-orthogonal multiple access (HCBD-CNOMA) scheme is proposed. To characterize the performance of our proposed scheme, we derive the closed-form ergodic rate and outage probability by considering both perfect and imperfect successive interference cancellation (SIC). To acquire more insights, their corresponding asymptotic expressions are obtained as well. Moreover, considering the fact that the nodes in Internet of Things (IoT) network are usually powered by battery and thus their power is limited, we further consider the scenario that two users are energy-constraint. In this scenario, users first need to harvest energy from the transmission of BS based on time splitting (TS) or power splitting (PS) energy harvesting (EH) protocol and then use these energy to accomplish subsequent communications. Similarly, the exact ergodic rate and outage probability as well as their asymptotic expressions for this scenario are analyzed. Simulation results validate the accuracy of analytical results, and reveal the performance gain of our schemes over the benchmark schemes.
The stability of multiple carbon ad-dimer defects in single-walled carbon nanotubes as a function of its distance from the nanotube end

Single-walled carbon nanotubes (SWCNTs) are considered as one of the most promising materials for a diverse range of applications. The multiple carbon ad-dimer defects in SWCNTs are particularly attractive structures. By using density functional theory calculations, the structural and electronic properties of a (4, 4) SWCNT with the positions of the defect states induced by multiple carbon ad-dimers and the chemisorption of hydrogen and fluorine on the surface of these nanotubes were studied. The results indicate that nanotubes with multiple carbon ad-dimers defect exhibit a higher reactivity than perfect ones. The chemisorptions of hydrogen and fluorine atoms can enhance the stability of defective SWCNTs. The reaction energy of chemisorption of hydrogen and fluorine atoms is almost independent of the positions of the defect states.
RAW MATERIAL SOURCE OF HYDROCARBONS OF THE ARCTIC ZONE OF RUSSIA

The study of the hydrocarbon potential of the Arctic is being considered in Russia as the most crucial direction of preparing a new raw material base of oil and gas, which will replace the extracted reserves in traditional areas of development during the second third of this century. The sharp fall in global hydrocarbon prices has led to a reduction in research and exploration costs, especially in hard-to-reach areas and hard-to-recover reserves as well as the need to determine the contribution to the country's fuel and energy balance from the hydrocarbons development of the Arctic zone, including the shelf, without which it is impossible to plan and develop new expensive projects. A fair assessment of oil and gas potential, based on a set of ideas about the processes of formation of sedimentary basins and oil and gas generation processes, contributed to obtaining new geophysical information on the results of seismic work executed in the Arctic zone of the Russian Federation between 2010 and 2020. A quantitative assessment of oil and gas resources was performed using geological analogies (for wellstudied geological and geophysical areas) and the volume-genetic method (for less studied basins). It showed significant differences from the most well-known assessments of the Arctic, both in terms of the total volume of hydrocarbons and their phase composition. It was concluded that there is ambiguity in assessing the potential of deepwater zones of the Arctic seas. Because of that, it is important to study coastal and shallow areas, especially oil content.
Household Perceptions and Patterns of Crop Loss by Wild Pigs in North India

Loss to cultivated crops by wild pigs (Sus scrofa) is widespread and can jeopardize low-income farmers. In India, although there is lot of political interest in the problem, efforts to understand the patterns, correlates, and underlying reasons for wild pig conflict continue to be minimal. We quantified loss of wheat (Triticum aestivum) to wild pigs and assessed the spatial patterns of damage in a forest settlement of Van Gujjar (Haridwar, India), which is a dairy-based pastoralist community. We chose a 4-km2 cultivated area comprising 400 farmlands (each measuring 0.8 ha and belonging to a family) and assessed crop damage by wild pigs through field surveys during the harvest season. We interviewed 159 respondents who manage 219 of the total 400 farmlands in the study area to compare actual crop loss with perceived losses. Wild pigs damaged 2.29 tonnes (2,290 kg) of wheat, which was about 2.6% of the potential yield in the study area. A total of 39 farmlands (9.5%), managed by 28 respondents, suffered losses during the survey period at an average loss of about 58.8 kg (SD ± 89.5, range = 0.7–388 kg). During interviews, 81 respondents managing 155 farmlands (70.7%) reported having suffered wild pig-related crop loss during the survey period. They also perceived losing about 23.4% of the potential yield of wheat due to wild pigs. The perceived losses were much higher than actual losses. Actual losses measured through field surveys underscore the dichotomy between actual and perceived crop loss due to wild pigs. About 81% of recorded wild pig-related damage to wheat occurred within 200 m from the forest edge. The crop protection measures aimed at stopping wild pigs from entering the fields were mostly reactive. Although overall crop losses due to wild pigs seem low at the settlement level, for affected individual families, the losses were financially significant. Such recurrent crop losses can cause families to go into debt, trigger animosity toward conservation, and lead to retaliation measures, which may be indiscriminate and have the potential to affect other endangered mammals in conservation priority landscapes. Because crop losses by wild pigs are severe along the narrow band of fields along the edge of the forest, channeling monetary benefits through insurance-based compensation schemes can help assuage losses to farmers. Further, because crop damage by wild pigs is seasonal, experimenting with mobile fences that can be dismantled and packed away after use would be beneficial.
Processing causatives in first language acquisition: A computational approach

One of the most challenging tasks for infant language learners is to extractmeaning from the speech stream they hear. Linguistic contexts often stand as themain cues for children to infer the semantics of words. For instance, uponhearing the sentence “you broke the window”, to understand the meaning of“broke”, children have to first recognize the two participants “you” and “thewindow” in the utterance, and later establish the causal relation between them.The semantics embedded in linguistic contexts, often referred to as distributionalsemantics, plays an important role in children’s semantic learning (Erickson &Thiessen, 2015; Theakston, Lieven, Pine, & Rowland, 2001; Tomasello, 2003). However, many studies have looked at only specific contextual patterns orselected semantic features to examine semantics in first language acquisition,therefore lacking comprehensiveness in their approach. In this study, weexamined semantics with a computational approach that comprehensivelyaccesses linguistic contexts to generate semantic representations. Using lexicalcausatives as a test case, we processed causative semantics in both Englishchild­directed speech (CDS) and child speech (CS), thereby investigating thesemantic development in parent­child interaction.
OBTAINING AND CHARACTERIZATION OF ROMANIAN ZEOLITE SUPPORTING SILVER IONS

The aim of this work was to obtain Ag doped zeolite as antibacterial material using natural and sodium form of zeolite from Mirsid Romania with the dimensions ranged between 0.8-1.2 mm. The comparative structural characterization of natural and Ag doped zeolite were performed using Laser Induced Breakdown Spectroscopy (LIBS), X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), Atomic Force Microscopy (AFM), and Infrared Spectroscopy (IR). In addition, the ion exchange total capacities for silver of natural and sodium forms of zeolite were determined. The quantitative assessment of silver amount incorporated into zeolite lattice was achieved by Inductively Coupled Plasma Atomic Emission Spectroscopy (ICP-AES).
Carbon Monoxide Adsorption and Carbon Monoxide Oxidation Studies on Thiolate Supported Gold Nanoclusters Dispensed on Metallic Oxides

Thiolate-protected gold nanoclusters represent atomically well-defined active centers for catalysis with resolved crystal structures, enabling the creation of a homogeneous and defined surface. The correlation of characterization via FT-IR spectroscopy with kinetics studies gives insight into the gold clusters activity and tests their utilization to bridge the gap between organometallic complex-based homogenous catalysis and nanoparticle based heterogeneous catalysis as well as the gap between the bulk crystal structure model catalysis and real-world catalysis.
Environmental Sound Classification via Time–Frequency Attention and Framewise Self-Attention-Based Deep Neural Networks

Environmental sound classification (ESC) is crucial to understanding the surroundings in Internet of Things (IoT) applications. The state-of-the-art deep learning approaches do not have good ESC performance when there exists various clutter interference, which is common in IoT scenarios. In this article, we present a novel deep neural network framework based on time–frequency attention and framewise self-attention (TFFS-DNN). It consists of two major novel architectures: 1) gradient and 2) latent feature-based DNN to generate our time–frequency attention, which can locate the relevant time–frequency (i.e., spectral) features accurately, and self-attention normalization DNN to generate our framewise self-attentions which properly indicate the relevance of frames. By conjoining these two sorts of distinct and complementary attentions with spectrograms, we are able to identify the importance or relevance in terms of time, frequency, and frame of the sounds using TFFS-DNN, which helps in distinguishing clutter such as background as well as model interpretation to some extent. Thus, the proposed TFFS-DNN can classify environmental sounds with clutter. The evaluation using four real-world environmental sound data sets demonstrates the superior performance of the proposed framework over several state-of-the-art schemes. Notably, we achieve 79.23% classification accuracy on the UrbanSound data set, a raw environmental sound data set that is full of clutter. The ablation study demonstrates a relative 3%–9% improvement of classification accuracy by the proposed framework over the baseline deep model.
Preparation and Characterization of Chloride-Free Alumina-Supported Platinum Catalysts

Supported precious metal catalysts are extensively used as efficient catalysts. This kind of catalysts, particularly chloride-free catalysts, sintesized using organoplatinum compounds as precursors has attracted immense research interest compared to their parent metals due to their unique physico-chemical properties. The main objective of this research is to prepare and characterize the chloride-free alumina-supported platinum catalysts. An organometallic compound of ammonium bisoxalatoplatinate(II) hydrate was used to prepare unsupported and alumina supported platinum catalysts. A series method including IR, XRD, SEM, TEM, EDA, and XPS was used to characterize samples. The research shows that ammonium bisoxalatoplatinate(II) hydrate could be synthesized and used to prepare unsupported and alumina supported platinum free of chloride impurities.
Find Your Organization in MMORPGs

Social relationships are the basis for communication and collaboration between players in many online games. In this article, we propose a machine-learning-based approach to model the relationship between players and guilds in online games. Our approach combines deep learning techniques with useful prior expert knowledge, where the core component is a graph convolutional network that is designed to utilize both social relationships and behavior preferences of players. For each player in the game, the model is trained to estimate the likelihood of whether the player matches the guild, which enables rapid matching of players and guilds via recommendation. The proposed approach is evaluated on an industrial dataset collected from a popular online game and also deployed in the game as a basic component of the social system. Experimental results show that our approach is not only intuitive but also very superior to other baseline methods.
Analysis of Lycopene and Vitamin C Levels of Pomelo Citrus Fruit (Citrus maxima (Burm) Merr) Red n White Varieties From South Sulawesi

Pomelo citrus (Citrus maxima (Burm) Merr) is a fruit plant that has many chemical ingredients that are beneficial to health, including lycopene, flavonoids, provitamin A, vitamin C, pectin, carbohydrates, retinol, calcium and phosphorus. Lycopene is a bright red carotenoid pigment, which is found in red fruits as well as vitamin C. The purpose of this study was to determine of lycopene and vitamin C levels in pomelo citrus (Citrus maxima (Burm) Merr) red and white varieties from Pangkep Regency, South Sulawesi. The method using UV-Vis Spectrophotometry, at a wavelength of 471 nm for lycopene and 494 nm for vitamin C. The results showed that levels of lycopene pomelo citrus red variety was 32,444 mg/kg and white variety 2,801 mg/kg. Levels of Vitamin C in pomelo citrus red variety was 0,721 mg/g and white variety 0,107 mg /g. The content of lycopene and vitamin C of pomelo citrus red variety is greater than of white variety.
Molecular Dynamics Investigation of Graphene Nanoplate Diffusion Behavior in Poly-α-Olefin Lubricating Oil

Graphene as a type of novel additive significantly enhanced the tribological performance of blended lubricating oil. However, the dispersibility of graphene with long-term stability in lubricating oil is still a challenge. Chemical modification for graphene, rather than using surfactants, provided a better method to improve the dispersibility of graphene in lubricants. In this study, the equilibrium molecular dynamics (EMD) simulations were carried out to investigate the diffusion behavior of graphene nanoplates in poly-α-olefin (PAO) lubricating oil. The effects of graphene-size, edge-functionalization, temperature, and pressure on the diffusion coefficient were studied. In order to understand the influence of edge-functionalization, three different functional groups were grafted to the edge of graphene nanoplates: COOH, COON(CH3)2, CONH(CH2)8CH3 (termed GO, MG, and AG, respectively). The EMD simulations results demonstrated that the relationships between diffusion coefficient and graphene-size and number of functional groups were linear while the temperature and pressure had a nonlinear influence on the diffusion coefficient. It was found that the larger dimension and more functional groups provided the lower diffusion coefficient. AG with eight CONH(CH2)8CH3 groups exhibited the lowest diffusion coefficient. Furthermore, the experimental results and radial distribution function for graphene-PAO illustrated that the diffusion coefficient reflected the dispersibility of nanoparticles in nanofluids to some degree. To our best knowledge, this study is the first time the diffusion behavior of graphene in PAO lubricating oil was investigated using EMD simulations.
Signal Synthesis Model Reference Adaptive Controller with Artificial Intelligent Technique for a Control of Continuous Stirred Tank Reactor

Abstract Modelling and controlling of Continuous stirred tank reactor (CSTR) is one of the major problems in the process industry. The nonlinear characteristic of CSTR may change the variation of temperature in either direction from the given set value. Chemical reactions within the CSTR depends on the given reference temperature. Such variation from reference values may result in degrading the variety of biomass. Design and implementation of the precise control device in such system are difficult for researchers. This paper proposes the MIT based control scheme as a solution to control problem of CSTR. An improvement of signal synthesis MIT system has been proposed in this study to enhance the steady-state and transient performance of CSTR. Artificial Bee Colony (ABC) based controller parameter tuning technique is applied to get the optimal performance of the controller. This paper shows the design and implementation of conventional PID tuned with the Z-N method, adaptive PID tune with ABC, MIT and ABC-MIT for CSTR. Detailed comparison based on simulation studies is presented which shows that ABC-MIT based control scheme improves the transient and steady state response.