bluuebunny/crossref_metadata_2025_split huggingface dataset:
Optimal solar power for control of smart irrigation system
Authors: Ogidan Olugbenga Kayode , Amusan Akinwumi Abimbola , Temikotan Kehinde Olusesan , Nkanga Iniubong Essien 
Published: February 2021

Abstract
Irrigation is very vital to food security but deployment of effective irrigation requires solar energy especially in the rural areas with no grid power. In this work, the optimal power required in the solar photovoltaic (PV) and the battery of a solar powered system (at any instance) for effective operation of a smart irrigation facility in Elizade University Ilara Mokin, Nigeria is determined. The system uses current and voltage sensors placed at the solar photovoltaic (PV) and the battery sections to perform real-time measurements on irrigation solenoid valves. Acquired current and voltage sensor values are passed to a microcontroller, readable in the computer serial monitor and later used to compute the required power in both PV and battery sections. The developed solar power system was implemented on a pilot farm with irrigation facilities consisting of sensors (moisture content, water level) and actuators (three solenoid valves). Tests were performed under the load-on condition. Results obtained reveal a maximum power threshold of 72.68 W for the solar PV and 14 W for the battery when three solenoid valves were loaded or operated at the same time and a minimum value of 31.55 W for the solar PV and 1.9 W for the battery when one valve is operated. The power thresholds obtained would be useful for configuring the smart irrigation system controller to ensure adequate delivery of water to crops as well as prolong the lifespan of the developed solar powered system.
Decubitus pump health device implementation with pressure sensor based on Atmega 328
Authors: Wicaksana Alan Rifky , Kartika Wisnu , Purwoko Heri 
Published: February 2021

Abstract
The decubitus, also known as pressure ulcer, is a wound that occurs due to pressure mainly on the protruding bones due to the patient is lying in bed on long time. This research purpose is to help prevent decubitus sores for immobility patients who are more bedridden during treatment at the hospital. This research module is a special mattress with an automatic pump which is equipped with an air pressure monitoring system on the mattress. The MPX5700 sensor measures mattress pressure. On the module testing, it can be observing that the largest error value on the low setting value measurement that is 2.25 % while the smallest error value on high setting measurement that is 1.84 %. Based on the results of tests and supported by the research, it can be concluded that the decubitus pump module can run well because it is still at the error tolerance threshold at ± 5 %.
The effect of coffee powder as a carburizing agent and preventing corrosion
Authors: Sidiq M. Fajar , Soebyakto  , Willis Galuh Renggani , Shidik M.Agus 
Published: February 2021

Abstract
Low carbon steel has a carbon content between 0.01% - 0.2% C, has properties of malleability and machining, usually used for machines, machinery and mild steel. The disadvantages of this low carbon steel are its relatively low mechanical strength and poor corrosion resistance. By using coffee powder as a carburizing agent and as an inhibitor corrosion, it is expected that the mechanical strength and corrosion resistance can be increased. This study aims to determine the effect of using coffee grounds in increasing wear resistance, and its hardness and corrosion resistance using coffee powder media. The process is carried out by carburizing at a temperature of 9150C and held for 30 minutes with coffee powder media as charcoal and tempering at a temperature of 3250C to increase its mechanical strength. The next process is testing its corrosion resistance using a coffee powder inhibitor with a percentage of 10 Ppm, 20 Ppm, and 30 Ppm. The results showed an increase in the mechanical strength of low carbon steel by carburizing the process using coffee grounds. There was an increase in the hardness value of the hardness test specimen from 180 HB in raw material to 395.3 HB. In the wear test, there was a decrease in the value of the wear volume from 0.079 mm3 to 0.041 mm3. In testing the corrosion rate using coffee grounds as a corrosion inhibitor medium, it was found that the corrosion rate of the raw material decreased with a value of 2.153 mm / yr to 1.495 mm / yr when using coffee inhibitors with a level of 30 Ppm.
The utilization of ijuk fibre and sawdust for manufacturing composite block with plastic waste as the matrix
Authors: Abdurachman  , Malik Jamaludin 
Published: February 2021

Abstract
This paper presents the results of research on the utilization of wood waste in the form of wood-chips of sengon wood (S) and sawdust of pinewood (P), mixed with palm-fibres and plastic waste of polypropylene (PP) and polyethylene (PE), for the manufacture of wood plastic composite (WPC) products with three variations mixtures of flakes, fibres and the matrix: A = 50:25:25, B = 50:30:15 and C = 50:15:35. Physical and mechanical properties of the composite refer to the procedure and criteria of SNI 8154: 2015. The results revealed that the densities of the WPC are in accordance with the target ≥ 0.60 g/cm3 where the highest by 0.874 g/cm3 belongs to the composition of PEPB. The composite moisture content is much lower than the maximum water content required i.e 12%. MOE and MOR of the WPC that meet the standard requirement belong to the composition of PPSA and PESB by 20450.67 and 20286.67 kg/cm2 (MOE) and by 187.08 and 194.11 kg/cm2 (MOR). The highest screw-withdrawal strength was 71.33 kg achieved by PESC composition. Based on these characteristics, sengon and pine wood chips can be used as raw material for wood plastic composite mixed with palm-fibres as the reinforcing fiber and recycled plastic as the matrix.
Characterization of duck egg shells and bioceramic materials in making denture applications
Authors: Sabir Asmeati , Abbas Hammada , Amini Ahmad Yusran , Asmal Sapta 
Published: February 2021

Abstract
Duck egg shells contain higher calcium which potent to be use as materials of denture-bio-ceramic. Denture bioceramics were made from feldspar, quartz, kaolin, and duck egg shells. In this work, characterization and synthesis hydroxyapatite from duck egg shells as bioceramics for the manufacturing of artificial tooth was carry out. X-Ray Diffraction (XRD) was used to analyze the characteristics of hydroxyapatite. Synthesis hydroxyapatite from duck egg shells were produced calcium (Ca) is 99.63%, and CaO is 99.41%. Furthermore, calcination methods were used by XRD. The XRD results at the calcination temperature of 900°C were feldspar CaO content of 96.87%, SiO2 of 1,85%, quartz CaO of 1.58%, SiO2 of 95.47%, and Kaolin CaO of 68.08%. Among of three various samples used, sample of B with compositions of Ca and Si are 62.89, and 26.89, XRD results of eggshell powder produced the largest CaO compound at a burning temperature of 900°C for 1 hour with a hexagonal-shaped compound with a Ca / P ratio of 1.61. respectively has good result. In addition, bioceramics obtained is in accordance to standard manufacturing of denture. Therefore, synthesis hydroxyapatite from Duck egg shells contains very high calcium which is component that potential to be used for Dentures based bioceramic.
ASpli: integrative analysis of splicing landscapes through RNA-Seq assays
Authors: Mancini Estefania , Rabinovich Andres , Iserte Javier , Yanovsky Marcelo , Chernomoretz Ariel 
Published: February 2021

Abstract

Motivation
Genome-wide analysis of alternative splicing has been a very active field of research since the early days of next generation sequencing technologies. Since then, ever-growing data availability and the development of increasingly sophisticated analysis methods have uncovered the complexity of the general splicing repertoire. A large number of splicing analysis methodologies exist, each of them presenting its own strengths and weaknesses. For instance, methods exclusively relying on junction information do not take advantage of the large majority of reads produced in an RNA-seq assay, isoform reconstruction methods might not detect novel intron retention events, some solutions can only handle canonical splicing events, and many existing methods can only perform pairwise comparisons.

Results
In this contribution, we present ASpli, a computational suite implemented in R statistical language, that allows the identification of changes in both, annotated and novel alternative-splicing events and can deal with simple, multi-factor or paired experimental designs. Our integrative computational workflow, that considers the same GLM model applied to different sets of reads and junctions, allows computation of complementary splicing signals.
Analyzing simulated and real data, we found that the consolidation of these signals resulted in a robust proxy of the occurrence of splicing alterations. While the analysis of junctions allowed us to uncover annotated as well as non-annotated events, read coverage signals notably increased recall capabilities at a very competitive performance when compared against other state-of-the-art splicing analysis algorithms.

Availability and implementation
ASpli is freely available from the Bioconductor project site https://doi.org/doi:10.18129/B9.bioc.ASpli.

Supplementary information
Supplementary data are available at Bioinformatics online.
From the Strengths Perspective to an Empowerment–Participation–Strengths Model in Social Work Practice
Authors: Kam Ping Kwong 
Published: February 2021

AbstractOver recent years, the strengths perspective has been promoted as a practice model with a range of social service users. Despite acknowledging its positive aspects, there has been increasing discussion about its application in actual practice, underlining the need to advance a practice model that helps enhance its use in social work practice. This article aims to do this by proposing the adoption of an Empowerment–Participation–Strengths (EPS) model that integrates the strengths perspective with two other important concepts in social work, participation and empowerment. The EPS model integrates these three concepts by proposing that social workers use the strengths perspective to look at service users, encourage their participation and then help them to empower themselves. The strengths perspective is the base, participation is considered as a useful method, and empowerment is the goal. These three concepts are equally important, and none can be disregarded. This article first reviews the issues in applying the strengths perspective. It then presents the special features of the model and discusses how this enhances the strengths perspective in social work practice.
Deep Multi-Stage Approach For Emotional Body Gesture Recognition In Job Interview
Authors: Khalifa Intissar , Ejbali Ridha , Schettini Raimondo , Zaied Mourad 
Published: February 2021

Abstract
Affective computing is a key research topic in artificial intelligence which is applied to psychology and machines. It consists of the estimation and measurement of human emotions. A person’s body language is one of the most significant sources of information during job interview, and it reflects a deep psychological state that is often missing from other data sources. In our work, we combine two tasks of pose estimation and emotion classification for emotional body gesture recognition to propose a deep multi-stage architecture that is able to deal with both tasks. Our deep pose decoding method detects and tracks the candidate’s skeleton in a video using a combination of depthwise convolutional network and detection-based method for 2D pose reconstruction. Moreover, we propose a representation technique based on the superposition of skeletons to generate for each video sequence a single image synthesizing the different poses of the subject. We call this image: ‘history pose image’, and it is used as input to the convolutional neural network model based on the Visual Geometry Group architecture. We demonstrate the effectiveness of our method in comparison with other methods in the state of the art on the standard Common Object in Context keypoint dataset and Face and Body gesture video database.
Humans influence shrimp movement: a conservation behavior case study with “Shrimp Watching” ecotourism
Authors: Hongjamrassilp Watcharapong , Blumstein Daniel T 
Published: February 2021

Abstract
An increase in ecotourism adversely impacts many animals and contributes to biodiversity loss. To mitigate these impacts, we illustrate the application of a conservation behavior framework toward the development of a sustainable ecotourism management plan. In Ubon Ratchathani, Thailand, thousands of tourists annually come to see a unique mass migration of shrimps on land (referred to as “shrimp parading”). Preliminary work suggests that this tourism has negatively impacted the shrimps. To reduce tourism-related impacts we studied: 1) the decisions shrimps make when parading and 2) how shrimps respond to different light intensities and colors. We created an artificial stream and tested the conditions that influence parading by experimentally varying the presence of light and systematically manipulating water velocity (10, 60, and 100 cm/s). Additionally, we conducted an in situ experiment to study how shrimps respond to tourists’ lights under three intensities (50,400, and 9,000 lux) and five colors (white, blue, green, orange, and red). We found most shrimps prefer to leave the river when it is dark and there is low water flow. Shrimps responded the least to red (λmax = 630 nm) and orange (λmax = 625 nm) light at 50 lux. These findings were used to develop a management plan by creating three different tourist zones, which maximize tourist needs and minimize the anthropogenic impacts on the shrimps. This work could be used as an example of the application of conservation behavior framework in developing management plan for sustainable ecotourism for other invertebrate taxa.
A statistical framework for QTL hotspot detection
Authors: Wu Po-Ya , Yang Man-Hsia , Kao Chen-Hung 
Published: February 2021

AbstractQuantitative trait loci (QTL) hotspots (genomic locations enriched in QTL) are a common and notable feature when collecting many QTL for various traits in many areas of biological studies. The QTL hotspots are important and attractive since they are highly informative and may harbor genes for the quantitative traits. So far, the current statistical methods for QTL hotspot detection use either the individual-level data from the genetical genomics experiments or the summarized data from public QTL databases to proceed with the detection analysis. These methods may suffer from the problems of ignoring the correlation structure among traits, neglecting the magnitude of LOD scores for the QTL, or paying a very high computational cost, which often lead to the detection of excessive spurious hotspots, failure to discover biologically interesting hotspots composed of a small-to-moderate number of QTL with strong LOD scores, and computational intractability, respectively, during the detection process. In this article, we describe a statistical framework that can handle both types of data as well as address all the problems at a time for QTL hotspot detection. Our statistical framework directly operates on the QTL matrix and hence has a very cheap computational cost and is deployed to take advantage of the QTL mapping results for assisting the detection analysis. Two special devices, trait grouping and top γn,α profile, are introduced into the framework. The trait grouping attempts to group the traits controlled by closely linked or pleiotropic QTL together into the same trait groups and randomly allocates these QTL together across the genomic positions separately by trait group to account for the correlation structure among traits, so as to have the ability to obtain much stricter thresholds and dismiss spurious hotspots. The top γn,α profile is designed to outline the LOD-score pattern of QTL in a hotspot across the different hotspot architectures, so that it can serve to identify and characterize the types of QTL hotspots with varying sizes and LOD-score distributions. Real examples, numerical analysis, and simulation study are performed to validate our statistical framework, investigate the detection properties, and also compare with the current methods in QTL hotspot detection. The results demonstrate that the proposed statistical framework can effectively accommodate the correlation structure among traits, identify the types of hotspots, and still keep the notable features of easy implementation and fast computation for practical QTL hotspot detection.
Moving Toward the Promise of Participatory Engagement of Older Adults in Gerotechnology
Authors: Grigorovich Alisa , Kontos Pia , Jenkins Amanda , Kirkland Susan 
Published: February 2021

Abstract
Limited uptake and use of developed technologies by older adults have prompted interest in participatory design and related approaches in the gerotechnology field. Despite this, recent systematic reviews suggest that researchers continue to passively engage older adults in research projects, often only providing advice or feedback in the early or later phases of research. A key barrier to more meaningful and active engagement of older adults is a lack of understanding as to how participatory design differs from other participatory approaches, and in particular, participatory action research. We address this gap in understanding by exploring the theoretical similarities and differences of participatory design and participatory action research, including their scope, goals, and the nature of the involvement of older adults in each. We conclude with key barriers that are critical to address in order to achieve greater involvement of older adults in gerotechnology and to broaden and enrich the goals of this field.
Determination of Fentanyl, Alpha-Methylfentanyl, Beta-Hydroxyfentanyl and the Metabolite Norfentanyl in Rat Urine by LC–MS-MS
Authors: Li Lu , Yu Xuejiao , Lyu Lihong , Duan Hongbin , Chen Yao , Bian Jing , Xu Zhiru , Liu Li , Zhang Yurong 
Published: February 2021

Abstract
Fentanyl and its analogs are potent synthetic opioids with a high potential for abuse and dependence. They have become major contributors to opioid deaths. This study aimed to determine whether the metabolites of fentanyl, alpha-methylfentanyl and beta-hydroxyfentanyl, excreted in the urine, can demonstrate historical drug exposure. Fentanyl is primarily metabolized via CYP3A4 into norfentanyl, although there is little research on its metabolization into alpha-methylfentanyl and beta-hydroxyfentanyl. We conducted in vitro experiments with human liver microsomes (HLMs) and rat liver microsomes (RLMs) to elucidate the major metabolic pathways of alpha-methylfentanyl and beta-hydroxyfentanyl using ultra-high-performance liquid chromatography coupled with mass spectrometry. The results showed that both alpha-methylfentanyl and beta-hydroxyfentanyl were predominantly metabolized into norfentanyl in HLM and RLM. Urine samples were collected at different intervals from 0 h to 72 h after intravenous administration of alpha-methylfentanyl and beta-hydroxyfentanyl (20 μg/kg) to Sprague-Dawley rats. We prepared the samples by liquid–liquid extraction, and the internal standard (IS) was cariprazine. A sensitive, rapid liquid chromatography-tandem mass spectrometry method was developed and validated to determine four analytes in the urine. The lower limit of qualification in urine was 2 pg/mL for fentanyl, 5 pg/mL for alpha-methylfentanyl, 10 pg/mL for beta-hydroxyfentanyl and 40 pg/mL for norfentanyl. The analytical range was 0.002–2 ng/mL for fentanyl, 0.005–5 ng/mL for alpha-methylfentanyl, 0.01–10 ng/mL for beta-hydroxyfentanyl and 0.04–40 ng/mL for norfentanyl. All analytes demonstrated good linearity (R2 &gt; 0.99). The extraction recoveries were in the 67.8%–92.1% range, and the IS-normalized matrix effects were between 55.5% and 74.0% (coefficient of variance &lt; 15%). Our data indicated that norfentanyl has a higher concentration in rat urine and was detectable for at least 3 days after exposure to these compounds. This developed method may be useful in various fields, including forensic analysis, workplace drug testing and monitoring drug abuse.
Aquaporins, and not changes in root structure, provide new insights into physiological responses to drought, flooding, and salinity
Authors: Domec Jean-Christophe , King John S , Carmichael Mary J , Overby Anna Treado , Wortemann Remi , Smith William K , Miao Guofang , Noormets Asko , Johnson Daniel M 
Published: February 2021

Abstract
The influence of aquaporin (AQP) activity on plant water movement remains unclear, especially in plants subject to unfavorable conditions. We applied a multitiered approach at a range of plant scales to (i) characterize the resistances controlling water transport under drought, flooding, and flooding plus salinity conditions; (ii) quantify the respective effects of AQP activity and xylem structure on root (Kroot), stem (Kstem), and leaf (Kleaf) conductances; and (iii) evaluate the impact of AQP-regulated transport capacity on gas exchange. We found that drought, flooding, and flooding plus salinity reduced Kroot and root AQP activity in Pinus taeda, whereas Kroot of the flood-tolerant Taxodium distichum did not decline under flooding. The extent of the AQP control of transport efficiency varied among organs and species, ranging from 35–55% in Kroot to 10–30% in Kstem and Kleaf. In response to treatments, AQP-mediated inhibition of Kroot rather than changes in xylem acclimation controlled the fluctuations in Kroot. The reduction in stomatal conductance and its sensitivity to vapor pressure deficit were direct responses to decreased whole-plant conductance triggered by lower Kroot and larger resistance belowground. Our results provide new mechanistic and functional insights on plant hydraulics that are essential to quantifying the influences of future stress on ecosystem function.
Variability, periodicity, and contact binaries in WISE
Authors: Petrosky Evan , Hwang Hsiang-Chih , Zakamska Nadia L , Chandra Vedant , Hill Matthew J 
Published: February 2021

ABSTRACT
The time-series component of Wide-field Infrared Survey Explorer (WISE) is a valuable resource for the study of variable objects. We present an analysis of an all-sky sample of ∼450 000 AllWISE+NEOWISE infrared light curves of likely variables identified in AllWISE. By computing periodograms of all these sources, we identify ∼56 000 periodic variables. Of these, ∼42 000 are short-period (P &lt; 1 d), near-contact, or contact eclipsing binaries, many of which are on the main sequence. We use the periodic and aperiodic variables to test computationally inexpensive methods of periodic variable classification and identification, utilizing various measures of the probability distribution function of fluxes and of time-scales of variability. The combination of variability measures from our periodogram and non-parametric analyses with infrared colours from WISE and absolute magnitudes, colours, and variability amplitude from Gaia is useful for the identification and classification of periodic variables. Furthermore, we show that the effectiveness of non-parametric methods for the identification of periodic variables is comparable to that of the periodogram but at a much lower computational cost. Future surveys can utilize these methods to accelerate more traditional time-series analyses and to identify evolving sources missed by periodogram-based selections.