Miracle-dz/UniFAR-FTUs huggingface dataset:
Coua Bird-Inspired Algorithm for Solving Power System Problem

In this paper an optimal short-term hydrothermal generation (OHG) is used to determine the optimal operation for cascaded hydropower plants and thermal plants considering equality constraints including water time delay, reservoir volume constraint, continuity water constraint , power balance constraint, and inequality constraints such as the limits of thermal and hydro generations. Coua bird-inspired algorithm (CA) is successfully applied for solving the OHG problem. Assessment of the technique’s enactment is done by comparing the obtained results from it and other methods reported in the paper on four hydrothermal systems in which thermal units consider the valve point loading effect and a four cascaded reservoir system is taken into account.
PointNet+LSTM for Target List-Based Gesture Recognition With Incoherent Radar Networks

Radar-based gesture recognition can provide autonomous electronic systems with a reliable way to infer a human's intention, e.g., in traffic environments involving vulnerable road users. Particularly in complex scenarios, algorithms operating on radar target lists derived from constant false-alarm rate outputs present an attractive solution, as they not only enable the filtering of relevant targets, but can also make full use of the diverse, high-resolution target parameters provided by modern radar sensors. Therefore, this article proposes PointNet+long short-term memory (LSTM) for the enhanced target list-based recognition of challenging traffic gestures, combining per-frame feature extraction with PointNet and learning from sequences with a LSTM. The approach is generalized to facilitate the use of multistatic radar data from sensor networks to exploit slightly different viewing angles, which is particularly helpful for motions with low radial velocity. The proposed method is validated on a comprehensive dataset comprising eight traffic gestures and data recorded from 35 participants. Measurements are conducted both indoors and outdoors with an incoherent radar sensor network comprising three chirp sequence–multiple-input multiple-output sensors. On this challenging dataset, our approach clearly outperforms a reference convolutional neural network, reaching up to $92.2 \%$ cross-validation accuracy.
Designing Multi-Step Fractional Factorial Split-Plots: A Combined JMP® and SAS® User Application

In the past 10 years, there has been an increase in research and software development in the design of experiments for split-plot situations. As supply chains grow across the globe and complexity increases, it is necessary to design experiments for processes involving three, four, or more steps. New features in PROC FACTEX in SAS® 9.2 make it possible to design fractional factorial split-plots for multi-step situations. This paper gives a brief introduction on how to design fractional factorial split-plots for multi-step situations using real industrial examples, and shows how JMP® users can take advantage of these new capabilities using a JMP® application.
Comparative evaluation of ELISA & CLIA screening assays in the effective detection of HIV infection in blood donor samples

Background: Since the set-up of the first blood bank in India in 1939, by the Bengal Red Cross Society, screening for transfusion transmissible infections in donated blood has been improvising steadily in the country. Currently it is either done by rapid diagnostic tests (RDTs) or the more common enzyme linked immunosorbent assay (ELISA) or the latest available sensitive assay namely, chemiluminescence immunoassay (CLIA). Aim: The prime objective of this analytical study was to assess the degree of performance of the readily available CLIA against two different ELISA testing methods for the serological screening of HIV. Methods: We have included 850 samples obtained from serial blood donors who donated blood dating from March 2021 to March 2022. All the collected blood samples were screened by two different ELISA testing methods & CLIA analyzer. The results were then computed and evaluated. Results: Out of 850 samples, 98 were ultimately confirmed to be HIV positive by qPCR testing. As far as sensitivity is considered, both CLIA and ELISA methods hadn’t shown much disparity.
A Two-Step Stability Assessment Method for Interconnection of DC Distribution Networks

Interconnection of DC distribution networks is raising concerns over their stability. With the increasing number of power electronics converters, the conventional stability assessment methods require detailed internal information of the converters and passive network and/or large storage and computing power. In this paper, to fully protect the highest level of trade secret and user privacy and to avoid the curse of dimensionality, an improved pre-processing method is first developed to deal with the distribution networks prior to their interconnection. Then, a two-step stability assessment method is formulated to analyze the stability of the anticipated distribution networks subsequent to their interconnection. By comparing with the existing methods, the proposed one simultaneously achieves three objectives: i) it regards both the converters and passive network as black boxes and assesses the stability of the interconnected network solely based on the measured impedance/admittance; ii) it assesses system stability with a reduced-order system minor-loop gain and therefore, overcomes some of the difficulties of dimensionality curse; and iii) it prevents from the internal instability and guarantees the global stability of the interconnected distribution network. Finally, a modified IEEE 37-bus DC distribution network is implemented in the Matlab/Simulink environment to verify the validity of the proposed method.
Acquired Methemoglobinemia in a Ketamine-induced Ulcerative Cystitis Patient: A Case Report

Introduction As ketamine gains traction as an alternative to opiates in the treatment of chronic pain, ketamine-induced ulcerative cystitis is now being recognized as a complication of its use. The first-line treatment is phenazopyridine, an over-the-counter medication for dysuria that historically has been known to cause methemoglobinemia. This report details the case of a patient presenting to the emergency department (ED) with methemoglobinemia. Case Report A 66-year-old woman with a complicated medical history presented to the ED with anemia and hypoxia after extended use of phenazopyridine for treatment of ketamine-induced ulcerative cystitis. She was found to have methemoglobinemia secondary to phenazopyridine used to treat her ketamine-induced ulcerative cystitis, a previously undocumented sequelae of chronic ketamine use. She was admitted to the hospital for three days and made a full recovery. Conclusion This case highlights the need to suspect ketamine-induced ulcerative cystitis in patients who use ketamine chronically and be judicious in the use of phenazopyridine for symptom management to prevent life-threatening complications.
Context adaptive ensemble classification mechanism with multi‐criteria decision making for network intrusion detection

Nowadays, intrusion detection systems (IDSs) enabled with computational intelligence for electing the suitable classifiers to learn the patterns of various types of network attacks are under study. Selection mechanism of single or ensemble classifiers based on performance and ranking is to be enabled in the IDS framework to make accurate pattern predictions. A new anomaly based network intrusion detection system framework is proposed using context adaptive classification through the technique for order of preference by similarity to ideal solution (TOPSIS) ranking mechanism with hierarchy based chi‐square and bat algorithms for feature selection. Parameters like accuracy, false positive rate (FPR), and classification model building time are explored for choosing the best and situation aware classifiers using TOPSIS. For experimentation, NSL‐KDD and UNSW‐NB15 datasets are used. The proposed system opts decision tree (DT) algorithm for NSL‐KDD and produces 98.77% accuracy, 0.03% FPR with 8 features. Ensemble learner is selected for the UNSW‐NB15 dataset using DT and support vector machine classifiers with 9 features. Combined classifier predicts 89.43% accuracy and 3.215% FPR. Experimentation on the proposed methodology with the state of the art approaches produces promising results.
Global Context-Aware-Based Deformable Residual Network Module for Precise Pest Recognition and Detection

An accurate and robust pest detection and recognition scheme is an important step to enable the high quality and yield of agricultural products according to integrated pest management (IPM). Due to pose-variant, serious overlap, dense distribution, and interclass similarity of agricultural pests, the precise detection of multi-classes pest faces great challenges. In this study, an end-to-end pest detection algorithm has been proposed on the basis of deep convolutional neural networks. The detection method adopts a deformable residual network to extract pest features and a global context-aware module for obtaining region-of-interests of agricultural pests. The detection results of the proposed method are compared with the detection results of other state-of-the-art methods, for example, RetinaNet, YOLO, SSD, FPN, and Cascade RCNN modules. The experimental results show that our method can achieve an average accuracy of 77.8% on 21 categories of agricultural pests. The proposed detection algorithm can achieve 20.9 frames per second, which can satisfy real-time pest detection.
A Lack of GD3 Synthase Leads to Impaired Renal Expression of Connexins and Pannexin1 in St8sia1 Knockout Mice

The aim of this study was to determine the effects of altered ganglioside composition on the expression of Cx37, Cx40, Cx43, Cx45, and Panx1 in different kidney regions of St8sia1 gene knockout mice (St8sia1 KO) lacking the GD3 synthase enzyme. Experiments were performed in twelve male 6-month-old mice: four wild-type (C57BL/6-type, WT) and eight St8sia1 KO mice. After euthanasia, kidney tissue was harvested, embedded in paraffin wax, and processed for immunohistochemistry. The expression of connexins and Panx1 was determined in different regions of the kidney: cortex (CTX.), outer stripe of outer medulla (O.S.), inner stripe of outer medulla (IN.S.), and inner medulla (IN.MED.). We determined significantly lower expression of Cx37, Cx40, Cx45, and Panx1 in different parts of the kidneys of St8sia1 KO mice compared with WT. The most consistent decrease was found in the O.S. where all markers (Cx 37, 40, 45 and Panx1) were disrupted in St8si1 KO mice. In the CTX. region, we observed decrease in the expression of Cx37, Cx45, and Panx1, while reduced expression of Cx37 and Panx1 was more specific to IN.S. The results of the present study suggest that deficiency of GD3 synthase in St8sia1 KO mice leads to disruption of renal Cx expression, which is probably related to alteration of ganglioside composition.
Measuring and observing of ambient temperature of broiler chicken farm at Gianyar region by SMS based AVR ATmega16 microcontroller

This article designs a measurement tool and an ambient temperature monitor of Broiler chicken farm at Gianyar region by applying LM35 temperature sensor as temperature detector, ATmega16 Microcontroller is functioned as the main control of the system and SIM 800L Module is functioned as SMS sender and receiver. Optimal ambient temperature of broiler chicken farm is between 16 C till 26 C [7]. The made tool will report the temperature of broiler chicken cage automatically through SMS massage if the cage temperature is less or more than optimal temperature limits. The monitoring is also done every second by sending SMS massage “Lapor” to the hand phone number that has been installed on SIM 800L module and the tool made to reply the massage is temperature report to the sender. Calibration result of sensor LM35 done at BBMKG region III Denpasar said that the uncertainty of measurements is avowed at confidence level that is not less than 95 %. Experiment result of the test equipment on broiler chicken farm at Gianyar region monitored by SMS for 4 days showed that average ambient temperature of broiler chicken cage was 28,22 C.
Generation of probabilistically optimal paths for nonholonomic needle insertion

Rapidly-exploring Random Tree (RRT) is a sampling-based algorithm which is designed for path planning problems. It is efficient to handle high-dimensional configuration space (C-space) and nonholonomic constraints. Under the nonholonomic constraints, the RRT can generate paths between an initial state and a goal state while avoiding obstacles. Since this framework assumes that a system is deterministic, more improvement should be added when the method is applied to a system with uncertainty. In robotic systems with motion uncertainty, probability for successful targeting and obstacle avoidance are more suitable measurement than the deterministic distance between the robot system and the target position. In this paper, the probabilistic targeting error is defined as a root-mean-square (RMS) distance between the system to the desired target. The proximity of the obstacle to the system is also defined as an averaged distance of obstacles to the robotic system. Then, we consider a cost function that is a sum of the targeting error and the obstacle proximity. By numerically minimizing the cost, we can obtain the optimal path. In this paper, a method for efficient evaluation and minimization of this cost function is proposed and the proposed method is applied to nonholonomic flexible medical needles for performance tests.Copyright © 2016 by ASME
Limiares de reconhecimento de sentenças em indivíduos normo-ouvintes na presença de ruído incidente de diferentes ângulos Sentences recognition thresholds in normal hearing individuals in the presence of inciding noise from different angles

ABSTRACT Purpose: To determine and compare the sentence recognition thresholds in the noise, in sound field, in the presence of incident noise from different angles, and to verify the most unfavorable hearing condition, in normal-hearing individuals. Methods: The Portuguese Sentences Lists test was carried out in 38 young adults, evaluated in acoustic booth. The sentences were presented at 0o - 0o azimuth, and the competitive noise at 0o - 0°, 0° - 90°, 0° - 180°, and 0° - 270° azimuth, in a fixed loudness of 65 dB NPS (A). Results: The signal-to-noise ratios in which the sentence recognition thresholds were obtained for these incidence angles were, respectively: -7.56, -11.11, -9.45, and -10.43 dB. Differences were found between the results in the conditions: 0o - 0o and 0o - 90o; 0o - 0o and 0o - 180o; -0o - 0o and 0o - 270o. Conclusion: The following sentence recognition thresholds in the noise, in sound field, were obtained for these signal-to-noise ratios: 0° - 0° = -7.56 dB; -0o - 90o = -11.11 dB; -0o - 180° = -9.75 dB; 0o - 270o = -10.43 dB. The better thresholds were obtained with the incidence angles of 0o - 90o and 0o - 270o, followed by the 0o - 180o condition, and, finally, by the 0o - 0o condition. The most unfavorable hearing condition was that in which the noise was in the same incidence angle of the speech, in front of the evaluated subject.
JOAGT: Latency-Oriented Joint Optimization of Computation Offloading and Resource Allocation in D2D-Assisted MEC System

Driven by the visions of Internet of Things and 5G communications, mobile edge computing (MEC) as a new paradigm promises dramatic reduction in latency. In recent years, an increasing number of scholars introduce D2D communication into the MEC system to further reduce the latency. In this letter, we propose a D2D-enabled MEC three-layer partial offloading scenario and design a joint optimization algorithm based on game theory (JOAGT). The proposed algorithm includes offloading mode selection, offloading fraction allocation, and resource allocation. Simulation results show that the proposed scenario and algorithm can significantly reduce the total latency, and the algorithm can exhibit good performance.
Perceived Intensification in Harmful Algal Blooms Is a Wave of Cumulative Threat to the Aquatic Ecosystems

Simple Summary Harmful algal blooms (HABs) are a serious threat to aquatic environments. The intensive expansion of HABs across the world is a warning signal of environmental deterioration. Global climatic change enforced variations in environmental factors causing stressed environments in aquatic ecosystems that favor the occurrence, distribution, and persistence of HABs. Perceived intensification in HABs increases toxin production, affecting the ecological quality as well as serious consequences on organisms including humans. This review outlines the causes and impacts of harmful algal blooms, including algal toxicity, grazing defense, management, control measures, emerging technologies, and their limitations for controlling HABs in aquatic ecosystems. Abstract Aquatic pollution is considered a major threat to sustainable development across the world, and deterioration of aquatic ecosystems is caused usually by harmful algal blooms (HABs). In recent times, HABs have gained attention from scientists to better understand these phenomena given that these blooms are increasing in intensity and distribution with considerable impacts on aquatic ecosystems. Many exogenous factors such as variations in climatic patterns, eutrophication, wind blowing, dust storms, and upwelling of water currents form these blooms. Globally, the HAB formation is increasing the toxicity in the natural water sources, ultimately leading the deleterious and hazardous effects on the aquatic fauna and flora. This review summarizes the types of HABs with their potential effects, toxicity, grazing defense, human health impacts, management, and control of these harmful entities. This review offers a systematic approach towards the understanding of HABs, eliciting to rethink the increasing threat caused by HABs in aquatic ecosystems across the world. Therefore, to mitigate this increasing threat to aquatic environments, advanced scientific research in ecology and environmental sciences should be prioritized.
A thermophilic 8-oxoguanine DNA glycosylase from Thermococcus barophiluss Ch5 is a new member of AGOG DNA glycosylase family

8-Oxoguanine (8oxoG) in DNA is a major oxidized base that poses a severe threat to genome stability. To counteract the mutagenic effect generated by 8oxoG in DNA, cells have evolved 8oxoG DNA glycosylase (OGG) that can excise this oxidized base from DNA. Currently, OGG enzymes have been divided into three families: OGG1, OGG2 and AGOG (archaeal 8oxoG DNA glycosylase). Due to the limited reports, our understanding on AGOG enzymes remains incomplete. Herein, we present evidence that an AGOG from the hyperthermophilic euryarchaeon Thermo Coccus barophilus Ch5 (Tb-AGOG) excises 8oxoG from DNA at high temperature. The enzyme displays maximum efficiency at 75°C–95°C and at pH 9.0. As expected, Tb-AGOG is a bifunctional glycosylase that harbors glycosylase activity and AP (apurinic/apyrimidinic) lyase activity. Importantly, we reveal for the first time that residue D41 in Tb-AGOG is essential for 8oxoG excision and intermediate formation, but not essential for DNA binding or AP cleavage. Furthermore, residue E79 in Tb-AGOG is essential for 8oxoG excision and intermediate formation, and is partially involved in DNA binding and AP cleavage, which has not been described among the reported AGOG members to date. Overall, our work provides new insights into catalytic mechanism of AGOG enzymes.
Influence of Socio-economic Attributes on Travel Behaviour in the Rural Areas of Nigeria: Towards a Sustainable Rural Planning and Development

ABSTRACT The socio-economic characteristics of individual and group have been found to significantly have an impact on their mobility and travel behaviour. Hence, this study examined the influence of socio-economic characteristics of households in the Rural areas of Nigeria on trip making. The study adopted the multi-stage sampling technique method where 12, 365 registered buildings were systematically selected out of a total of 28,341 buildings. Systematic sampling technique was used to survey 4 percent of households, representing 495 household heads of a total 12,365 registered buildings by means of questionnaire administration. The study revealed that majority of the respondents were between the age of 60–69 years and utilized the non-motorized (walk & bicycle) means of transport. The result of the multiple regression analysis further revealed that Age and Income were the significant socio-economic variables influencing trip making of households. This study thus advocates the influence of demographic attributes on households’ travel behaviour. Therefore, rural communities should be given equal privilege as urban areas when formulating transport policies as a result of their unique and distinct socio-economic attributes.
A systematic review of drying methods and their impact on technological characteristics of sourdough type III

2452-0721/2452-0721 © 2022 sociedade Brasileira de Biotecnologia. this is an Open access article distributed under the terms of the creative commons attribution-Noncommercial No Derivative license, which permits unrestricted noncommercial use, distribution, and reproduction in any medium provided the original work is properly cited and the work is not changed in any A systematic review of drying methods and their impact on technological characteristics of sourdough type III
Grain Size Distribution of the Sediments from Odi River, Bayelsa State, Nigeria

Ten samples from Odi River bed were collected by divers at different locations and sent to the laboratory for granulometric analysis. Samples were dried to remove moisture content and poured into a set of BSS standard sieves and mechanically vibrated for at least fifteen minutes to enable the grains to separate into their different sizes. Textural and statistical parameters were then calculated from the results of the particle size distribution. The result shows that the grain size ranges from -2 φ – -1 φ (granules) to 3 φ – 4 φ (very fine sand). The average mean of the population is 0.89 φ, with a modal class in the 1 φ – 2 φ size grade. The average sorting value is 1.26 σ which indicates a poorly sorted population. Skewness varies through the population, but, the average skewness is -0.16 (Negatively skewed). 60% of the sediments range from leptokurtic to extremely leptokurtic, 10% are very platykurtic, 10% are platykurtic and 20% are mesokurtic. Traction and saltation transport modes were inferred from the cumulative curves of the sediments. The plot of skewness versus kurtosis shows the energy of deposition to be fluctuating between high and low, depositing coarse and fine sands facies respectively. The grain size distribution is observed to be finer downstream.