Miracle-dz/UniFAR-FTUs huggingface dataset:
Hunger Pandemic: Urban Rodents' Boom and Bust During COVID-19

Shortly after the enactment of restrictions aimed at limiting the spread of COVID-19, local governments and public health authorities around the world reported an increased sighting of rats. We combined multi-catch rodent station data, rodent bait stations data, and rodent-related residents’ complaints data to explore the effects that social distancing and lockdown measures might have had on the rodent population within the City of Sydney, Australia. We found that rodent captures, activity, and rodent related residents’ complaints increased during the COVID-19 related lockdown period, followed by a steep decline post-lockdown. We found no changes in the geographical distribution of any of our indices of rodent abundance. We hypothesize that lockdown measures resulted in an increase in rodent activity driven by a reduction in human-derived food resources. This might have increased the mortality rate, triggering a population crash. There is a high chance that the surviving individuals might be rodenticide resistant. It is possible that the onset of COVID-19 might have disrupted commensal rodent populations, with profound implications for the future management of these ubiquitous urban indicator species.
COMPUTATIONAL ANALYSIS OF NARINGENIN AS AN ANTIDEPRESSANT

Objective: This works aims at analyzing the potential of Naringenin (NAR) as an antidepressant drug by computational methods. Methods: The database Protein Data Bank and PubChem were used to retrieve the three-dimensional structures of the protein and the compound. The software Discovery Studio was used to study the interactions between the protein and the ligand. Results: NAR, one of the flavanone, which has strong anti-inflammatory and antioxidant activities, is studied for its antidepressant and neuroprotective effects through in silico approach. Interaction study and pharmacophore analysis using Discovery Studio show that the molecule NAR interacts with the protein at different sites. The interaction has a maximum dock score at position B. Conclusion: The compound NAR shows to have antidepressant quality from the computational study. The docking studies show promising result that NAR can be explored further as a potential drug.
Facile Preparation of Gold Nanoparticle Modified Pencil Graphite Electrode

The purpose of this research was to prepare gold nanoparticle (AuNP) modified disposable pencil graphite electrode (PGE). The AuNP was prepared using trisodium citrate reduced gold ion solution. The PGE surface modification was carried out by immersing a bare PGE in poly (diallyldimethylammonium chloride) (PDDA) and then in AuNP solution at room temperature. The characterization of the bare and modified PGE surfaces was carried out using field emission scanning electron microscopy (FESEM) and cyclic voltammetry in the presence of 0.1 M NaOH. The electrochemical behavior of the modified PGE electrode was investigated using cyclic voltammetry, and impedance spectroscopy in the presence of 5 mM [Fe (CN)6]3-/4- redox probe solution. The obtained result indicated that the modification of AuNP on the PGE surface provided a good electrochemical signal. In order to obtain more sensitive electrochemical signals, the effect of adsorbed AuNP on the PGE surface was also studied.
Changing Rainfall Patterns in an Era of Climate Change: A Multiparameter Spatiotemporal Analysis of Trends & Impacts for India

The hydrological cycle that starts with rainfall has been under major threat from the global temperature rise and climatic changes. In India, rainfall changes not only jeopardize water security but also have a major set-back for socio-economic stability. There have been attempts to decode the changing rainfall patterns in India but most of them conducted at wider spatial resolution (such as national, state, or sub-divisional level) fail to capture the essence of spatial variation in rainfall characteristics. To get a clearer understanding of change in key rainfall parameters, this paper analyses more than 197 million 0.25˚ x 0.25˚ gridded rainfall data points. The fine resolution 117 years (1901-2017) of daily rainfall data is utilized to test significant spatiotemporal trends in the quantum of rainfall and other key rainfall parameters such as rainy days, monsoon onset and withdrawal dates, occurrences of extreme rainfall events, and frequency of drought and high rainfall years. With an emphasis on changing climatic patterns since perceived climate change onset in the 1970s, the study identifies the regions with significant changes in rainfall patterns by comparing key parameters pre- & post- 1970s. The paper also highlights the major repercussions and challenges for the identified regions with significant changing rainfall patterns.
Isolation and characterization of gum from Chrysophyllum albidum fruits as pharmaceutical excipient

This study describes the morphology, physicochemical and compressional characteristics of a natural gum derived from the fruits of Chrysophyllum albidum. Preliminary phytochemical screening and physicochemical properties of Chrysophyllum albidum gum (in comparison with tragacanth gum) were determined while scanning electron microscopy (SEM), Fourier transform infra red (FTIR) and differential scanning calorimetry (DSC) were used to characterize the morphology of the gum. The compressional behaviour of the gum in comparison with that of corn starch BP was analyzed using density measurements and indices of plasticity from the Heckel and Kawakita equations. Chrysophyllum albidum gum contains saponins, polysaccharide, flavonoids, tannins and non- reducing sugar. The pH of 1% w/v suspension of Chrysophyllum albidum was 4.13. The angle of repose of Chrysophyllum albidum gum was high and indicative of a slightly poor flow. FTIR Spectra reveal absorption peaks between 1638 and 1454 cm-1 while the absorption bands between 800 and 1200 cm-1 represent the fingerprint region for carbohydrates. The SEM images reveal that the particles are round and regular in shape while the DSC thermogram shows a gradual increase in heat flow which suggests that Chrysophyllum albidum gum exhibits only the amorphous structure. Chrysophyllum albidum is a Type C material which exhibits a slower onset of plastic deformation than corn starch but had a lower overall amount of plastic deformation during the compression process. The results establish the fundamental characteristic of Chrysophyllum albidum gum and explain the rationale behind its use as raw material in pharmaceutical formulationsKeywords: Chrysophyllum albidum; Gum; Excipients; Compressional properties
Challenges in marketing channel selection by smallholder pineapple growers in Samarahan, Sarawak, Malaysia

Pineapples are very perishable and require an immediate sale to consumers. This has triggered the local growers to market their produce and rely on the middleman. Thus, this present study was conducted to identify the challenges that affect the marketing channel selection of smallholder pineapple growers in Samarahan, Sarawak. The primary data used for this study were collected from 123 smallholder pineapple growers using simple random sampling method with a well-structured close-ended questionnaire via face-toface survey. The descriptive analysis was used to describe the socio-demographic characteristics of the pineapple growers meanwhile exploratory factor analysis (EFA) using principal component analysis approach with orthogonal rotation (varimax) was used to reduce data to a smaller set of summary variables and to identify the structure of the relationship between the variables and the respondents. The findings revealed that five main challenges have caused pineapple growers to carefully select the marketing channel in marketing their produce namely; lack of market information; inefficient transportation; price volatility; market distance; and product perishability. Inadequate marketing information about supply and demand markets, potential buyers, bargaining, and negotiation have caused concerned for the pineapple growers to take the risk in marketing their produce to various customers. Lack of transportation facility and high transportation cost has caused the pineapple growers to sell their produce at the farm gate to reduce losses during the distribution channel. Moreover, the unstable pineapple price has created a risk to the growers due to its negative effect on farm income stability. Besides, the distance between farms and marketplace has significantly affected marketable surplus of pineapple fruits thus resorts to the growers to rely on the middleman to market their produce. Conclusively, all the challenges highlighted in this study should be given adequate attention by the relevant agencies to improve and continue their effective roles in the pineapple market and to enhance farmers’ livelihoods. This can be achieved by strengthening the fruit supply chain management, adopting comprehensive approaches such as policies, programs and strategies pertaining to the marketing of pineapple fruits that require a collective effort and commitment from the public and private sectors.
Educational Data Mining To Improve The Academic Performance in Higher Education

Globalization and Innovation are mainly consider the great interest public sector and private business in the world especially in the higher education institutions. Educational Data Mining is mainly one of the business processes nowadays that attempt to bring the global innovation through improving and enhancing their processes and procedures to fulfill all the requirements and needs of the students as well as the institutions. The Educational Data Mining considered mostly concern with any research concerning the applications of the data mining and developing innovative techniques for data mining (DM) in the educational sector. This study mainly combined the use of the powerful online E-learning management system (Moodle) with data mining tools to improve the performance and effectiveness of the learning and teaching manners by using the innovative daily data that collected from the educational institutions.
Amyloid β-Targeted Inhibitory Peptides for Alzheimer’s Disease: Current State and Future Perspectives

ABSTRACT Alzheimer’s disease is the most common irreversible neurodegenerative disorder. To date, there is no cure for Alzheimer’s disease. While multiple pathological mechanisms have been proposed for the onset and progression of Alzheimer’s disease, the hypothesis that attracted much attention is the amyloid hypothesis. The senile plaques that accumulate in the brain of Alzheimer’s disease patients are predominantly composed of beta amyloid (Aβ). Aβ deposition in the brain is thought to occur years before the emergence of clinical symptoms. The overproduction, aggregation, and fibrillation of Aβ, combined with reduced clearance, eventually lead to amyloid plaque formation and subsequent neurotoxicity. Hence, inhibition of Aβ aggregation and the promotion of Aβ clearance have been actively explored as therapeutic strategies for Alzheimer’s disease. This chapter provides an overview of the current knowledge on one such strategy, Aβ-targeted inhibitory peptides.
Solubility Relationships of Iron and Evaluation of its Fertility Status in Degraded Soils

ABSTRACT This study was conducted to determine the solubility of iron (Fe) and identify the solid phases responsible for controlling its solubility in these soils by using Baker soil test (BST) computer program. The results indicated that the ferric ion (Fe3+) activity in all the soils, except the acidic ones, nearly approached the theoretical solubility line of known minerals, namely soil-Fe, amorphous-Fe, maghemite, and lepidocrocite. Solubility of Fe in acid soils of Ranchi (soil 3) and Cooch-Behar (soil 6) did not match the theoretical solubility lines of any of the known minerals. The acidic soils of Ranchi and Cooch-Behar were sufficient for Fe with respect to both quantity and intensity factor based on BST rating, while alkaline (soil 1) and calcareous (soil 5) were sufficient in reserve Fe; deficiency of iron still could be suspected because of high pH. These findings elucidate the role of solid phase controlling iron solubility in soil solution of degraded soils.
Changes in the performance and blood indices of Red Sokoto bucks fed diets containing soybean curd residue

The investigation was carried out to examine the outcome of soybean curd residue (SCR) supplementation in the diets of Red Sokoto bucks on growth performance and some blood parameters. Five (5) mixed ration was formulated to contain 14% crude protein, four (4) of which was SCR based at inclusion levels of 0% (control), 5%, 7.5%, 10% and 12.5% denoted as T1 , T2 , T3 , T4 and T5 respectively. Twenty (20) Red Sokoto bucks were used for the experiment for a period of twelve (12) weeks. They were randomly assigned to the five dietary groups of 4 bucks each in a completely randomize design. Laboratory analyses were carried out on the SCR and the experimental diets. Parameters measured were on growth performance and some blood parameters. The results obtained showed that SCR was high in DM (93.53%), energy (3435.15 kcal/kg), protein (30.66%) and NFE (49.12%) values. The results revealed significant differences (P<0.05) among all treatments. The highest values for daily weight gain was observed in T5 (122.86 g/day); daily feed intake and feed conversion ratio was observed in T3 (481.29 g/day and 4.66 respectively). High significant (P<0.05) values for packed cell volume and haemoglobin were observed in T5 (26% and 8.6 g/dl) compared to the control. Meanwhile, white blood cell was highest significantly (P<0.05) in T3 (8.50 ×109 /L). Most of the blood parameters observed in this study were within standard normal range for goat. This study showed that SCR did not pose any health risk to the bucks. It was concluded that supplementing soybean curd residue in the diets of goats up to 12.5% can produce a better performance.
OPTIMIZING THE QUARANTINE COST FOR SUPPRESSION OF THE COVID-19 EPIDEMIC IN MEXICO

This paper is one of the few attempts to use the optimal control theory to find optimal quarantine strategies for eradication of the spread of the COVID-19 infection in the Mexican human population. This is achieved by introducing into the SEIR model a bounded control function of time that reflects these quarantine measures. The objective function to be minimized is the weighted sum of the total infection level in the population and the total cost of the quarantine. An optimal control problem reflecting the search for an effective quarantine strategy is stated and solved analytically and numerically. The properties of the corresponding optimal control are established analytically by applying the Pontryagin maximum principle. The optimal solution is obtained numerically by solving the two-point boundary value problem for the maximum principle using MATLAB software. A detailed discussion of the results and the corresponding practical conclusions are presented.
Joint User Pairing and Subcarrier Allocation for NOMA-based Hybrid Power Line and Visible Light Communication Systems

With the rapid growth of the number of mobile communication users, the radio frequency bands occupied by traditional radio frequency (RF) communication are becoming more and more crowded, and visible light communication (VLC) based on light emitting diode (LED) has become a powerful candidate. However, visible light cannot be used directly as an information source, and power line communication (PLC) is needed to provide data to the VLC transmitter. In a hybrid power line and visible light communication (HPV) system, the PLC can transmit data to the VLC transmitter. In order to improve spectrum utilization, we introduce non-orthogonal multiple access (NOMA) technology, but allocating all users to a resource block will result in higher computational complexity and decoding delay. This paper proposes a joint user pairing and subcarrier allocation algorithm based on fairness (IGA-JUPSA). While ensuring the performance of the system, the algorithm can also reduce the complexity of calculation and improve user satisfaction. The simulation results show that the proposed IGA-JUPSA scheme can reduce the computational complexity while ensuring the performance of the HPV system, and can also take into account the fairness of the HPV system and user satisfaction.
An Ontology-based Name Entity Recognition NER and NLP Systems in Arabic Storytelling

Ontology is a descriptive model representing domain knowledge with robust specifications that solve interoperability between humans and machines. In this work, a practical methodology presented for Arabic Storytelling ontology construction for domain ontology extraction from unstructured Arabic story documents. However, the manual construction of ontologies is a time-consuming and challenging process. Still, ontology construction and learning, which extracts ontological knowledge from various data types automatically or semi-automatically, can overcome the bottleneck of knowledge acquisition. This paper intends to investigate the problem of automatically construct and build an Arabic storytelling ontology based on Arabic named entity recognition (NER) from unstructured story text. This paper presents a system designed based on Machine Learning (ML) approach. The system framework is a combination of five main stages: The first stage determines the requirement analysis—second document pre-processing using NLP tasks. The third is Conceptualization. The fourth stage is formal design and construction, and the final step is evaluation .
Architecture for Virtualization and Collaboration in Edge Computing: an implementation based on FIWARE building blocks

Edge Computing is a novel paradigm that allows moving the computation closer to the end-users and/or data sources. In this paper, we present a three-tier architecture for virtualization and collaboration of Virtual Nodes that leverages the Edge tier to meet those emerging IoT applications that demand requirements such as low latency, geo-localization, and energy efficiency. Besides the Edge tier, our implementation is based on the mix of lightweight virtualization and microservices using the building blocks from the FIWARE platform to interact with the physical environment. Furthermore, we presented two experiments to assess our architecture under severe and realistic conditions, regarding the network latency and fault-tolerance.
Named Entity Recognition in English Text

Natural Language processing has been one of the challenging field of computational linguistics. Language processing occurs in several steps in which Named Entity Recognition is one of the prominent phase. NER frameworks have been contemplated and created generally for a considerable length of time, however precise frameworks utilizing profound neural systems (NN) have just been presented over the most recent couple of years. We present a far reaching review of profound neural system models for NER, and balance them with past ways to deal with NER dependent on highlight designing and other regulated or semi-administered learning calculations.
Deep reinforcement learning based computation offloading and resource allocation for low-latency fog radio access networks

: Fog Radio Access Networks (F-RANs) have been considered a groundbreaking technique to support the services of Internet of Things by leveraging edge caching and edge computing. However, the current contributions in computation ofﬂoading and resource allocation are inefﬁcient; moreover, they merely consider the static communication mode, and the increasing demand for low latency services and high throughput poses tremendous challenges in F-RANs. A joint problem of mode selection, resource allocation, and power allocation is formulated to minimize latency under various constraints. We propose a Deep Reinforcement Learning (DRL) based joint computation ofﬂoading and resource allocation scheme that achieves a suboptimal solution in F-RANs. The core idea of the proposal is that the DRL controller intelligently decides whether to process the generated computation task locally at the device level or ofﬂoad the task to a fog access point or cloud server and allocates an optimal amount of computation and power resources on the basis of the serving tier. Simulation results show that the proposed approach signiﬁcantly minimizes latency and increases throughput in the system.
Effect of Zeolite, Potassium Fertilizer and Irrigation Interval on Yield and Quality of Sugar Beet in Sandy Soil

Two field experiments were carried out at Al-Hussein Agricultural Society Farm, Giza Governorate, Egypt, during 2017/2018 and 2018/2019 growing seasons to study the effect of three irrigation intervals [every 3 days (the conventional practice), 5 and 7 days], two levels of zeolite (zero and 500 kg/fed) and four levels of potassium fertilizer the first one in the form of potassium sulphate as a control [100% of the recommended K-dose], which was applied to the soil and three foliar doses of nano- potassium (500, 1000 and 1500 mg /l) on yield and quality of sugar beet grown under drip irrigation system in a sandy soil. The treatments were arranged in a complete block design in a split-split plot with three replications. Results revealed that increasing irrigation interval from 3 up to 7 days significantly reduced biochemical and physiological traits and root and sugar yields/fed. Soil application of zeolite achieved the highest values of all the parameters studied as compared to the untreated soil. Spraying beets with 1500 mg /l of nano-K gave the same trend of the recommended K-dose. Water use efficiency (WUE) for sugar yield increased with decreasing the amounts of applied irrigation water. Under conditions of the present work, adding 500 kg of zeolite/fed to the sandy soil, spraying beets with 1500 mg l-1 as nano-K fertilizer and irrigating the crop every 5 days using drip irrigation can be recommended to get the highest root and sugar yields as well as to save water and increasing water use efficiency.
Influence of Gender and Marital Status on Mobile Phone Addictive Behaviours of Students Exposed to Cognitive and Behavioural Therapies

a study showed mobile learning. A study by revealed mobile phone dependency psychosocial individual’s wellbeing. Other studies confirm the harmful effects mobile phones have on physical, Abstract: The study was to investigate the influence of gender and marital status on mobile phone addictive behaviours of students exposed to cognitive and behavioural therapies. Sixty research participants (undergraduate regular students from three Colleges in the University of Cape Coast) were involved in the study. The multistage sampling technique was used in the selection of the research participants. The quasi-experimental pre-test, post-test (non-equivalent) control group design was employed to conduct the study. Three groups were involved in the study: two experimental groups and a control group. An adapted form of Choliz (2012) Test of Mobile Phone Dependence was used to collect the data. It was a structured questionnaire on a 5-point Likert-type scale, consisting of sixty (60) items. Two-way Analysis of Covariance (ANCOVA)at an alpha level of . 05was used to test the hypotheses. The main findings revealed that gender and marital status did not have a significant influence on mobile phone addictive behaviours of students exposed to cognitive and behavioural therapies. Both male and female participants who were either single or married did not necessarily respond differently to both therapies. Based on the findings, it was recommended that any of the therapies can reduce mobile phone addiction regardless of gender and marital status. Counsellors should therefore apply any of the therapies in dealing with the mobile phone addictive behaviours of their clients irrespective of their gender and marital status.