Miracle-dz/UniFAR-FTUs huggingface dataset:
Ecological Niche Modelling of King Cobra, Ophiophagus hannah (Cantor, 1836) in Nepal

The fragile ecosystem of greater Himalaya is home to diverse flora and fauna which are vulnerable to climate change impact. This study aimed to determine the suitable habitat of King Cobra Ophiophagus hannah (Cantor, 1836) in the current scenario and near-future scenario of the year 2040-2060 (RCP 2.6, RCP 4.5, and RCP 8.5). Geographic coordinates of its occurrence were obtained from published literature and environmental layers were obtained from worldclim.org and processed using ArcGIS and software R. The model was developed using MaxENT algorithms. The model was validated using the area under the curve (AUC) and True skill statistics (TSS), which showed that the model is very good (AUC =0.86) and (TSS=0.6). The results showed that altitude is a prime factor affecting the distribution of King Cobra in Nepal with a percent contribution of 31% followed by actual evapotranspiration 14.4% and least by Mean diurnal range (Bio2nep) 7%. The model predicted an area of 41,214 Km2 as suitable habitat for King Cobra in Nepal. The Chitwan National Park possesses a maximum suitable area (726.89 km2) followed by Chitwan-Buffer Zone (601.68 sq. Km2) and least by Sagarmatha National Park (1.73 km2) and Shey-Phoksundo-buffer zone (1.73 Km2). Our data indicate urban areas being the most suitable sites followed by open forest covers. The projection indicates contraction of 8% and 4% in a suitable area for RCP 4.5 and RCP 2.6 respectively, whereas RCP 8.5 showed expansion of 4%. Having probably suitable habitat in urban areas research proposes frequent awareness camping about conservation and protection of vulnerable King Cobra in Nepal.
On Cooperation in Multi-Agent Reinforcement Learning

Advancements in Multi-Agent Reinforcement Learning (MARL) are motivated by cooperation in agents arising from Game Theory (GT). Agents must collaborate in practical scenarios in order to achieve complex objectives and attain strategies which depict optimal behavior. The need for cooperation is further highlighted in the case of partially-observed settings wherein agents have restricted access to environment observations. We revisit cooperation in MARL from the viewpoint of GT and stochastic dynamics of environments. We analyze and demonstrate the effectiveness of cooperative MARL in the case of complex and partially-observed tasks consisting of high-dimensional action spaces and stochastic dynamics. We leverage the empirical demonstrations to construct a novel optimization objective which addresses the detrimental effects of stochastic states across agents. Our large-scale experiments carried out on the StarCraft II benchmark depict the effectiveness of cooperative MARL and our novel objective for obtaining optimal strategies under stochastic dynamics.
Advanced diagnostic techniques for paediatric chronic kidney disease in a developing country: A narrative review

Abstract: Chronic kidney disease (CKD) is described as a complex and progressive condition that arises from both non-communicable diseases (NCD) and communicable diseases (CD). Approximately a tenth of adults are affected worldwide, but the global prevalence of paediatric CKD remains unknown. Unfortunately, advanced diagnostic techniques and interventions are not readily available in most developing countries. This review seeks to create more awareness about paediatric CKD in a developing country like Nigeria and the need to intensify efforts to make new technologies for its diagnosis available and more affordable.
Commutation Angle Maps Evaluation for Magnet Arrangements of Interior Permanent Magnet Synchronous Machines in Electric Vehicles

The commutation angle, $\gamma$, of an interior permanent magnet synchronous motor's (IPMSM) vector diagram, plays an important role in compensating the back electromotive force; both under load phase current variations and/or when an extended speed range, being near the constant power range, is required by the application. This commutation angle is defined as the angle between the fundamental of the phase current and the fundamental of the back-emf. It can be utilized to provide a compensating effect in IPMSMs. This is due to the reluctance torque component being dependent on the phase current before the extended speed range. A real-time maximum torque per current and voltage strategy is employed to find the trajectory and optimum commutation angles, $\gamma$, where the level of accuracy depends on the application and available computational speed. A magnet volume reduction is proposed in this paper to minimize the permanent magnet mass to motor torque density, whilst maintaining the phase current below its maximum rated value. A mapping of $\gamma$ allows the determination of the optimum angles as shown in this paper. The 3rd generation Toyota Prius IPMSM is considered the reference motor, where only the rotor configuration is altered to allow for an individual assessment. The electric vehicle's performance during acceleration and deceleration using various IPMSM rotor configurations is evaluated for a given four-wheel-drive vehicle. The powertrain uses two single-gear onboard, under standard drive cycles.
Dosimetric comparison of different radiotherapy techniques to determine the absorbed fetal dose in pregnant patients with left-sided breast cancer

Article history: Received: 26th Mar. 2021 Accepted: 2nd June 2021 This study aimed to measure the dose exposed by the fetus during three-dimensional conformal radiotherapy (3D-CRT) and intensity-modulated radiotherapy (IMRT) treatment techniques in pregnant patients who had to undergo radiotherapy due to breast cancer with thermoluminescence dosimetry (TLD) and compare these measurements with treatment planning system (TPS). 2.5 mmthick computed tomography (CT) images of Alderson Rando phantom device were taken for measurements. Heart, ipsilateral lung, contralateral lung and contralateral breast were defined as critical organs at risk (OARs) and planned tumor volume (PTV) as target volume. In TPS (Eclipse, version 15.1), using 3D-CRT and IMRT treatment methods, the criterion that 95% of the PTV volume should receive more than 95% of the predicted dose was taken into consideration. OAR has been preserved as much as possible in the used techniques. In order to compare the TPS and TLD readings in PTV, 60 TLDs were placed in the target volume in the Rando phantom. Twenty-four TLDs were placed in the 30th and 31st sections of the phantom, which is likely to be in the volumetric size of the first trimester of pregnancy which is also located 25.84 cm from the lower limit of the PTV. Six MV were used in seven different treatment techniques and the measurements were repeated 5 times for each technique and averaged. The differences between the average TPS and TLD readings for PTV were 1.34%, 0.86%, 1.04%, 0.64%, 0.48%, 0.84% and 0.73% for 3D-CRT, 5 MSS-IMRT, 5 SW-IMRT, 7 MSS-IMRT, 7 SW-IMRT, 9 MSS-IMRT and 9 SW-IMRT, respectively. Fetal doses for all treatment techniques in TPS were found as 0.00 cGy. However, in TLD measurements fetal doses were found as, 3.36 ± 0.19 cGy, 9.32 ± 0.91 cGy 10.29 ± 1.19 cGy, 12.35 ± 1.42 cGy, 12.99 ± 1.46 cGy, 13.18 ± 1.53 cGy and 16.10 ± 2.04 cGy for 3D-CRT, 5 MSS-IMRT, 5 SW-IMRT, 7 MSS-IMRT, 7 SW-IMRT, 9 MSS-IMRT and 9 SW-IMRT, respectively. In 3D-CRT treatment technique the fetus received the lowest dose. In addition, for plans made using the IMRT method, it is seen that the MSS-IMRT technique provides better fetal protection compared to the SW-IMRT technique. The 3D-CRT should be the first priority for a pregnant patient who has to undergo left breast RT, but if the desired dose-volume histogram (DVH) cannot be obtained with 3D-CRT, 5 MSS-IMRT technique may be preferred.
IoT Botnet Detection using Machine Learning Techniques

The widespread use of the internet of things (IoT) has led to serious security problems such as the denial of service (DoS) attack caused by a large group of compromised IoT devices. The IoT devices can easily be compromised as they do not have a good security posture. IoT devices have full internet access without any packet filtration in place, making them suitable to be a part of the zombie network. Although many researchers have proposed various IoT botnet detection techniques, many challenges remain unaddressed. In this paper, various machine learning techniques are proposed to effectively identify the presence of IoT botnet. The detection models predict the IoT botnet based on the network traffic information. The proposed model uses feature selection to achieve a faster detection rate with less false positive. The Random Forest classifier model outperformed the other machine learning models and deep learning model with an accuracy of 94.47% with a lesser detection time. Therefore, this model can be considered as an appropriate solution to effectively detect the IoT botnet.
An Efficient Video Denoising using Patch-based Method, Optical Flow Estimation and Multiresolution Bilateral Filter

Video denoising is a longstanding area of research. The core problem is to remove noise without affecting image details. The paper presents a new algorithm which combines motion compensation, patch based method and multiresolution bilateral filter for denoising. The proposed approach takes advantage of the self-similarity and redundancy of adjacent frames. Motion compensation by optical flow method permits the use of spatio-temporal patches for a more robust comparison. The use of singular value decomposition (SVD) for patches preserves fine details such as edges and texture. Multiresolution bilateral filter framework, which integrates both bilateral filter and soft thresholding, has the potential of eliminating low-frequency noise components. Experimental results shows that the proposed method eliminate most of the artifacts due to noise and improves texture and detail preservation.
Derivatizing Reagents for Detection of Organic Compounds By HPLC

Derivatization is the process of chemically modifying a compound to develope a new compound which has properties that are suitable for analysis using HPLC. Derivatization improves the detectability of a target analyte by reaction with suitable derivatizing agent. Derivatization reactions are simple chemical modification of substance that make it compatible with the selected separation method or transforms substance with a low UV- absorption into highly sensitive product. Derivatization reactions in liquid chromatography modify the solutes adding a chomophore for easy UV detection or a fluorophore for sensitive fluorescent detection. The chemical structure of the compound remains same and just modifies the specific functional group for reacting compounds to derivative of deviating chemical and physical properties in order to make them detectable. Introduction of certain elements or groups through chemical derivatization may enhance the detector’s response helpful for the elucidation of structure of analytes. In conclusion, the present review describe various derivatization reagents for pre-column and post column derivatization process in HPLC by UV-visible and fluorescence detection are summarized along with reactions and some practical aspects. The commonly used derivatizing reagents in HPLC are 1-fluoro-2, 4-dinitrobenzene, ninhydrine, 4-N-N-dimethylaminoazobenzene-4’-sulfonyl chloride, benzoyl chloride, phenyl isocyanate for UV-visible detection and o-phthalaldehyde, fluorescamine, 1-dimethylaminonapthalene-5-sulfonyl chloride (DNS-Cl), 9-fluorenylmethyl chloroformate (Fmoc-Cl), benzofurans for Fluorescence detection.
FAST ROBUST ARITHMETICS FOR GEOMETRIC ALGORITHMS AND APPLICATIONS TO GIS

Abstract. Geometric predicates are used in many GIS algorithms, such as the construction of Delaunay Triangulations for Triangulated Irregular Networks (TIN) or geospatial predicates. With floating-point arithmetic, these computations can incur roundoff errors that may lead to incorrect results and inconsistencies, causing computations to fail. This issue has been addressed using a combination of exact arithmetics for robustness and floating-point filters to mitigate the computational cost of exact computations. The implementation of exact computations and floating-point filters can be a difficult task, and code generation tools have been proposed to address this. We present a new C++ meta-programming framework for the generation of fast, robust predicates for arbitrary geometric predicates based on polynomial expressions. We show examples of how this approach produces correct results for GIS data sets that could lead to incorrect predicate results for naive implementations. We also show benchmark results that demonstrate that our implementation can compete with state-of-the-art solutions.
Radiomics in oncology - uncovering tumor phenotype from medical images: a short introduction

Radiomics is a promising method to quantify and describe the tumor phenotype on medical images. High numbers of image features are extracted from medical images and can be used within a clinical decision support system by integrating this data with clinical and pathological variables. Herein, we give a short introduction into this image analysis method and present an overview on the workflow.
Delay Optimization for URLLC in Software Deﬁned Networks: A Case Study on Platooning

—The autonomous driving in a platoon network requires reliable data transfer and strict latency on downlink trafﬁc. These two requirements have been addressed in 5G under the Ultra-Reliable Low Latency Communication (URLLC) speciﬁcation. In this study, we focus on this 5G service, and we design a novel Software-Deﬁned Platoon Network (SDPN) to optimize the end-to-end Delay (e2eDelay). Our SDPN deﬁnes the e2eDelay in a closed-form expression that covers Data and Control planes. To optimize e2eDelay, we propose a Mixed Integer Linear Problem (MILP) that jointly considers the constraints in the vehicle to vehicle (V2V) and the vehicle to infrastructure (V2I) links. Due to the NP-hard characteristic of our MILP optimization and to reduce the computational complexity of the optimization at the same time, we propose a novel Centralized Set Cover algorithm that ﬁnds the optimum set cover of vehicles by building platoons. According to the results, our SDPN serves e2eDelay under 3.5 msecs with a 45% improvement over the conventional approach.
Bene cial Effect of Dimethyl Fumarate on Experimental Autoimmune Uveitis is Dependent of Pro-In ammatory Markers Immunomodulation

Cha a TOUIL-BOUKOFFA (  touilboukoffa@yahoo.fr ) Universite des Sciences et de la Technologie Houari Boumediene Faculte des Sciences Biologiques https://orcid.org/0000-0001-8026-9373 Moussa Labsi USTHB: Universite des Sciences et de la Technologie Houari Boumediene Imene Sou i USTHB: Universite des Sciences et de la Technologie Houari Boumediene Houda Belguendouz USTHB: Universite des Sciences et de la Technologie Houari Boumediene Sara Djebbara USTHB: Universite des Sciences et de la Technologie Houari Boumediene Leila Hannachi Centre Hospitalo universitaire Mustapha Bacha Zine-Charaf Amir Centre Hospitalo Univeristaire Mustapha Bacha
Swim test for joint angles dispersion analysis during hind limb motor function assessment in SCI models

In the most of functional studies, various stress tests are used to assess functional improvement following spinal cord injury in animal models. However, available methods of motor function evaluation are not always accurate and unbiased. The main objective of the study was to create a new method of motor activity assessment in minor animal models of spinal cord injury. This method should provide an objective and accurate evaluation of limb motor function in models having severe neurological disorders following contusion spinal cord injury. The swimming test was used as the key behavioral test. To assess the motor function of swimming animals’ hind limbs, we measured angles of hind limbs movements adjusted to the motion direction axis. Then we calculated individual angles dispersion for each joint and limb using the parameters of angles sample dispersion and amplitude-depending dispersion. The current study included two groups of Sprague-Dawley rats: control group and a group of animals having moderate thoracic spinal cord contusion injury. Control animals demonstrated stable dispersion indicators for 6 weeks of follow-up. In the experimental group, a tendency to the improvement of motor function in hind limbs between 1 and 3 weeks was revealed followed by stabilization and preservation of both indicators between 3 and 6 weeks. Provided method based on the measurement of joint angles adjusted to the movement direction axis followed by calculation of indicators of variance of a random variable and amplitude-depending variance can be an effective and objective alternative for motor function evaluation.
Evaluation of Anemia in the Residents of Tambaklorok Exposed to Plumbum

BACKGROUND: Anemia is a health condition characterized by a decreased in the levels of hemoglobin (Hb), hematocrit (Ht), and the number of erythrocytes. It is usually caused through exposure to plumbum (Pb) common in most industrial areas. Based on several studies, Tambaklorok is located in the Northern part of the city of Semarang in Indonesia with Pb levels higher than the normal threshold. AIM: Therefore, the purpose of this study was to determine the level of anemia among the residents of Tambaklorok based on the characteristics of the respondents. METHODS: Characteristics assessed include length of stay in the area, the use of personal protective equipment (PPE), smoking habits, and consumption of shellfish. The methods are the cross-sectional research method was used with analytic study approach. The study sample was made up of 104 respondents with the characteristics evaluated through questionnaires. The levels of Hb, Ht, and erythrocytes were analyzed using Hematology Analyzer. RESULTS: The results showed that 38.6% of residents with over 30 years of stay, 42.2% with other jobs, 45.3% not wearing PPE, 26.7% smokers, and 38.7% of respondents had anemia. In addition, the Gamma statistical test results showed a significant relationship between the use of PPE with the levels of Hb (p = 0.001) and Ht (p = 0.012). CONCLUSION: The conclusion is generally, 41% of Tambaklorok residents in Semarang had mild anemia based on the industrial activities in the region.
The diagnostic value of apparent diffusion coefficient to differentiate benign and malignant meningiomas

BACKGROUNDMeningiomas are the most common primary extra-axial non-glial intracranial tumors. The severe grade of meningioma, according to WHO, has the highest recurrence rate accompanied by high morbidity and mortality rates. Therefore, it is imperative to perform pre-operative assessments so the clinician can give prompt treatment to gain a better prognosis. It is a novel alternative way of predicting meningioma’s malignancy by calculating the tumor’s apparent diffusion coefficient (ADC) value. The objective of the study was to determine the value of ADC for differentiating benign and malignant meningiomas. METHODSThis cross-sectional study involved 32 subjects with clinically diagnosed or histologically verified meningioma (21 benign and 11 malignant). They underwent a head-magnetic resonance imaging (MRI) examination and biopsy. We calculated the ADC value by creating regions of interest (ROIs) on the solid part of the tumor, guided by contrast and fluid-attenuated inversion recovery (FLAIR) sequence. We analyzed the ADC value with independent t-test and Bland-Altman graphs, calculated the average difference, CI 95%, limit of agreement between observers, and ROC. RESULTSMean ADC of malignant meningiomas (0.877 ± 0.167 x 10-3 mm2/s) was significantly lower than that of benign meningiomas (0.990 ± 0.105 x 10-3 mm2/s) (p<0.05). The ADC threshold is 0.886 x 10-3 mm2/s with sensitivity 63.6%, specificity 85.7%, positive predictive value 70% and negative predictive value 81.8%. CONCLUSIONThe ADC value measurement provides a discriminative feature to differentiate between benign and malignant meningiomas. However, the clinical applicability still needs to be elucidated, as histopathological confirmation remains the mainstay of definitive diagnosis.
Assessment of Tourism in Nepal with Reference to Regional Countries: Trend Analysis and ARIMA Approach

Tourism (either domestic or international or both) is an internationally flourished business or industry all over the world. The economic foundations of tourism are essentially the cultural assets, the cultural property and the nature of the travel location. So, it has a greater contribution to the country’s balance of payments. Simple trend analysis was carried out using a set of line graphs along simple linear regression. For forecasting of international tourist arrivals of period: 1962-2020, and real per capita international tourist receipts of period: 1995-2018, the suitable Auto-Regressive Integrated Moving Average (ARIMA) models were developed using Akaike Information Criterion along with method of autocorrelation function and partial autocorrelation function. Nepal has a significant growth rate of 1.372 of the international tourist arrivals. It has the eighth position for international tourist arrivals among nine counties. Likewise, Nepal has a significant growth rate of 1.315 of real per capita international tourist receipts. It has the fourth position for real per capita international tourist receipts among nine counties. Nepal has been receiving its international tourist arrivals, growth as well as real per capita international tourist receipts. Forecasts of international tourist arrivals of Nepal are 879638.3 in 2018, 860459.0 in 2019, 875824.1 in 2020, 891189.3 in 2021, and 906554.4 in 2022. Forecasts of real per capita international receipts in dollars are 687000000 in 2019, 727000000 in 2020, 807000000 in 2021, and 845000000 in 2022.
Effects of call reminders, short message services (SMS) reminders, and SMS immunization facts on childhood routine vaccination timing and completion in Ilorin, Nigeria

Background Reminders via mobile devices deployed as short message services (SMS) or calls have been identified to be a useful strategy in improving routine immunization uptake in several countries. Objective To identify the timeliness of appointments with reminders (calls or SMS), SMS health education and the routine care, and the vaccination completion rates in Ilorin, Nigeria. Method Mother-infant pairs presenting for the first vaccination appointment were randomized into four (three interventions, one control) groups, each consisting of 140 participants. Intervention groups were reminders via calls (A), SMS reminders (B), immunization fact SMS messages (C) and controls on usual care (D). Reminders were made a day before the appointment while SMS immunization facts were sent at five weeks, nine weeks and eight months. Appropriate timing was defined as the scheduled visit ±3 days. Results The immunization completion rates after the nine months' visit were 99.2%, 99.3%, 97% and 90.4% for Groups A, B, C and D respectively. Compared with controls, Group A had the highest odds [AOR 8.78 (6.10, 12.63)] of presenting at an appropriate time, followed by Group B [AOR 2.56 (1.96, 3.35)], then Group C [AOR 2.44 (1.87, 3.18)]. Conclusion Reminders/SMS immunization facts improve vaccination completion rates.