Miracle-dz/UniFAR-FTUs huggingface dataset:
Amino Acids and Minerals in Fresh and Processed Catfish, Mackerel and Pork

The main tissue of meat is the muscle and it is a very rich source of amino acids (aspartic acid, glutamic acid, histidine, arginine, valine, methionine, isoleucine, phenylalanine, threonine, and leucine) and some minerals like magnesium, calcium, phosphorus, sodium and potassium. In this study, essential amino acid profile in fresh catfish, mackerel, pork and their processed products were determined using High Performance Liquid Chromatography (HPLC). Minerals were determined in the form of cation (magnesium, calcium, potassium, ammonium and sodium) and anion (fluorine, chlorine, Nitrate, Sulphate and phosphate) by Cadmium.mtw and ASUP5 – 100 marvin.mtw respectively. The most abundant amino acids determined were aspartic acid, glutamic acid, arginine, methionine and threonine which were found in catfish, mackerel and pork. Values observed were higher (p<0.05) in catfish and mackerel than pork. Fresh catfish and mackerel recorded higher values in most of the amino acids in both raw product and their frankfurters (CF and MF) than fresh pork. Sulphate values were also higher (p<0.05) in raw meat than their Original Research Article Nkrumah and Akwetey; AJOB, 11(3): 7-14, 2021; Article no.AJOB. 64941 8 frankfurters. Higher level of calcium, magnesium, potassium, and sodium were observed in processed pork frankfurter than fresh pork. Minerals such as calcium and sodium were present but are at a smaller quantity in meat.
Damage Detection of Carbon Nanotube Cementitious Composites Using Thermal and Electrical Resistance Properties

This study aimed to detect damage based on thermal and electrical resistance properties by fabricating composites in which multi-walled carbon nanotubes (MWCNTs) and cement-based materials are mixed. The experimental parameters used were the cement-based material type, MWCNT concentration, curing period, and presence of damage. The experimental results showed that damage in cement paste can be detected using the heat property at every MWCNT concentration, and damage in mortar can be detected at MWCNT concentrations of ≤0.25 wt%. However, damage to concrete is difficult to detect using the heat property. Damage to cement paste, mortar, and concrete can be detected at every concentration using the electrical resistance property. Furthermore, field emission scanning electron microscopy (FE-SEM) results revealed uniformly dispersed MWCNTs inside the composites without agglomeration or the formation of carbon nanotube (CNT) networks.
Response of some durum wheat genotypes (Triticum durum Desf.) for Potassium fertilization levels in newly reclaimed soil.

The proper amount of fertilizer application is the main factor affecting thegrainyield and itscomponents of durum wheat. Hence, the field experiment was carried out in the tow growing seasons of 2017/2018 andits reported in 2018/2019, at Research Farm of Faculty of Agriculture, Sohag University,to study the effects of potassium fertilizer levels (zero, 25, 50 and 75 kgK2O /fed.) on yield and its components of four durum wheat genotypes (BaniSuef 6,NGB 7214, NGB 5399 and NGB 4816). A randomized complete block design (RCBD) was used in split-plot with three replicates.The results showed that potassium fertilizer levels were significantly effectedon all studied characters except plant height in the firstand second seasons, and harvest index in the firstseason only.As well as genotypes had significantly effect on the all studied traits; plant height (cm), spike length (cm),No. of Spikes /m 2 , No. of grains/spike ,1000-grain weight (g), grain yield (ard./fed.), biological yield (ton/fed.), straw yield (ton/fed.) and harvest index(%) in both growing seasons. Increasing K up to 75 kgK2O /fed.increased yield and its attributes of durum wheat in both growing seasons except plant height (cm) in the first and second seasons, and harvest index (%)in the firstseason only.BaniSuef 6 and NGB 7214 genotypes produced the highest values of grain yield compared to other genotypes in both seasons. Moreover, NGB 7214 accession produced the maximum values of spike length (cm), No. of Spikes /m 2 , No.of grains/spike, 1000-grain weight (g), biological yield (ton/fed.) and straw yield (ton/fed.) in the first and second seasons, respectively, while NGB 7214, NGB 5399 and NGB 4816 accessions produced the tallest plants comparing with the Egyptian variety (BaniSuef 6). Interaction effect showed significant differences on all studied traits.In general, the highest grain yield (20.27 and 19.70ard./fed.) were obtained fromBaniSuef 6 genotype when fertilized with 75 kgK2O /fed. , andNGB 7214 genotype when fertilized with50 kg K2O /fed.
Emergent physics-informed design of deep learning for microscopy

Deep learning has revolutionised microscopy, enabling automated means for image classification, tracking and transformation. Beyond machine vision, deep learning has recently emerged as a universal and powerful tool to address challenging and previously untractable inverse image recovery problems. In seeking accurate, learned means of inversion, these advances have transformed conventional deep learning methods to those cognisant of the underlying physics of image formation, enabling robust, efficient and accurate recovery even in severely ill-posed conditions. In this perspective, we explore the emergence of physics-informed deep learning that will enable universal and accessible computational microscopy.
The Farsund Shear Zone: geochemical evidence for lithological diversity in the wall rock of the Rogaland Anorthosite Province, South Norway

The Rogaland Anorthosite Province (RAP) – a typical Proterozoic Anorthosite–Mangerite– Charnockite (AMC) plutonic complex exposed in the Sveconorwegian orogen in South Norway – was emplaced diapirically through the crust, along a shear zone, at c. 933–916 Ma. The shear zone, recently defined as the Farsund Shear Zone (FSZ), crops out along the eastern flank of the anorthosite province, and it is made up of strongly foliated, steeply dipping, banded gneisses. The banded gneisses comprise a diversity of lithologies: metabasites, granitoid gneisses, augen gneisses and kinzigitic gneisses. Major and trace element compositions of samples mostly from the banded gneisses
Robust Distributed Average Tracking for Disturbed Second-Order Multiagent Systems

This article investigates the distributed average tracking (DAT) problem for disturbed second-order multiagent systems, where a crowd of agents is required to track the average of the multiple time-varying signals. First, a new kind of distributed average estimator is developed for each agent to estimate the average of the multiple time-varying signals in finite time. The protocol possesses the distinguished feature of robustness to initialization errors, which can recover from network alterations. Then, an observer-based finite-time tracking protocol is proposed to make each agent exactly track the average of the multiple time-varying signals in finite time in the absence of velocity measurement. By carefully analyzing the dynamic properties of the tracking error system, a suitable Lyapunov function is constructed to estimate the settling time for convergence of the tracking error system theoretically. Furthermore, an adaptive DAT protocol is proposed, which is a fully distributed protocol because it can solve the DAT problem without using any global information. Finally, two simulation examples are provided to verify the effectiveness of the methods.
Development of fresh and dried noodle products with high resistant starch content from banana flour

Negative lifestyle patterns or poor diet play key roles in developing various health problems that lead to diseases. Noodles have been recognized as major wheat products served as the main carbohydrate-based food. They are high glycemic index (GI) foods because carbohydrates directly raise blood sugar levels (Ho & Che Dahri, 2016). This is a main cause of health risks related to several chronic diseases (obesity, cardiovascular disease, diabetes, and cancers). The incorporation of low GI ingredients in noodle products could lower their GI.
Order and disorder in NMC layered materials: a FAULTS simulation analysis

The program FAULTS has been used to simulate the X-ray powder diffraction (XRD), neutron powder diffraction (NPD), and electron diffraction (ED) patterns of several structural models for LiNi1/3Mn1/3Co1/3O2, including different types of ordering of the transition metal (TM) cations in the TM slabs, different amounts of Li+/NiII+ cation mixing and different amounts of stacking faults. The results demonstrate the relevance of the structural information provided by NPD and ED data as compared with XRD to characterize the microstructure of NMC (LiNi1−y-z Mn y Co z O2) compounds.
Credit Risk Model Based on Central Bank Credit Registry Data

Data science and machine-learning techniques help banks to optimize enterprise operations, enhance risk analyses and gain competitive advantage. There is a vast amount of research in credit risk, but to our knowledge, none of them uses credit registry as a data source to model the probability of default for individual clients. The goal of this paper is to evaluate different machine-learning models to create accurate model for credit risk assessment using the data from the real credit registry dataset of the Central Bank of Republic of North Macedonia. We strongly believe that the model developed in this research will be an additional source of valuable information to commercial banks, by leveraging historical data for all the population of the country in all the commercial banks. Thus, in this research, we compare five machine-learning models to classify credit risk data, i.e., logistic regression, decision tree, random forest, support vector machines (SVM) and neural network. We evaluate the five models using different machine-learning metrics, and we propose a model based on credit registry data from the central bank with detailed methodology that can predict the credit risk based on credit history of the population in the country. Our results show that the best accuracy is achieved by using decision tree performing on imbalanced data with and without scaling, followed by random forest and linear regression.
Cellulose Non Freezing Bound Water and Activation Energy of Desorption by Thermogravimetric Analysis

Understand water-cellulose interaction isa key factor in cellulose processing strategies and to achieve the best propertiesfor each application. The emergence of new advanced materials based on nanocelluloses calls for more precise methods to study these systems. In this work, we described the study of water-cellulose interaction by thermogravimetric analysis (TGA), comparing dynamic and auto stepwise methods. The auto stepwise method was able to identify with precision the different species of water: i) the free water or freezing water, ii) the freezing bound water and iii) the non-freezing bound water. The Ozawa-Flynn-Wall method was used to estimate the activation energy of bound water desorption, Ea average = 50.45 kJ.mol-1 and the cellulose degradation energy, Ea average = 143.18 kJ.mol-1. The results obtained given a new knowledge on the interaction between water and cellulose since other techniques such as DSC are not sensitive to non-freezing bound water increasing the range of water content that can be studied.
Determination of Diffusion Coefficients of Lithium in Solid Electrolyte LiPON

A structural model of LiPON solid electrolyte, containing elements that simulate drift conductivity, diffusion conductivity, and leakage current was proposed. The dependence of the impedance of the structural model on frequency was calculated, and the parameters of the model at which the theoretical curve best approximates the experimental Nyquist diagrams were determined. Based on these data, the ion diffusion coefficient and conductivity of LiPON were calculated, which are D1 = 1.5 × 10−11 cm2/s and σ = 1.9 × 10−6 S/cm, respectively.
Design and Implementation of Virtual Stream Management for NAND Flash-Based Storage

NAND flash memory is being widely used as data storage in consumer electronics devices such as tablet computers and smartphones. However, due to the inherent nature of NAND flash memory where in-place update is not supported, NAND flash-based SSDs (Solid-State Drives) suffer from severe performance degradation as they need to move valid data during garbage collection (GC). Recently, multi-streamed SSDs have been proposed to reduce the cost of GC in the SSDs. However, commercial SSDs used in consumer electronics devices support only a small number of streams due to the device’s limitation in hardware resources. This makes it difficult to fully utilize the benefits of the multi-streamed SSDs. In this article, we propose a new concept of virtual streams (vStreams) that are independent of the number of available streams within the multi-streamed SSDs. We present the design and implementation of virtual stream management architecture, called vStream-FTL, for efficient stream management in the SSD. Specifically, we present novel mechanisms to monitor the lifetime of each stream with a negligible memory overhead and map one or more vStreams into a physical stream at run time according to the lifetime of vStream. In addition, we implement the enhanced garbage collection scheme, called vStream-aware GC that increases the benefits of multi-streamed SSDs further. Our vStream-FTL allows embedded system developers to manage a sufficient number of streams regardless of the physical streams supported by the device. The evaluation results with smartphone workload show that the proposed vStream-FTL improves throughput by 48% compared to the Legacy-FTL with no stream support.
Effect of interventions to reduce wait times for diagnosis and treatment of sleep-disordered breathing in adults: A systematic review

Abstract RATIONALE: Sleep disordered breathing (SDB) is associated with adverse health consequences that can be mitigated through timely and effective management. Guidelines provide wait time targets, but the evidence supporting them is unclear. The purpose of this systematic review was to explore the relationship between interventions to improve wait times for SDB and the effects on patient or provider outcomes. METHODS: A targeted search of medical databases was performed from database inception to June 2017. Included studies described an intervention intended to reduce wait times for the diagnosis or treatment of SDB and reported on a patient- or provider-level outcome. RESULTS: The search produced 2,944 abstracts and 51 articles underwent full text review. Ten articles were included in the final review. Five trials reported wait times to diagnosis and treatment, 3 studies described wait times for diagnosis only and 2 studies discussed time to treatment exclusively. All studies were of moderate methodological quality. Wait times were improved in most studies, but due to short follow-up periods a clear relationship with improved health outcomes was rarely established. The variety of interventions limited the characterization of specific wait-times reduction strategies that could reliably improve outcomes. CONCLUSIONS: This review highlights the scarcity of studies but suggests a possible clinical benefit of interventions to reduce wait times. However, generalizability is limited and the short follow-up periods likely underestimate potential positive impacts of reduced wait times. Further studies are needed to better characterize this relationship and to identify additional interventions to deliver more timely patient care.
ECG signal classification using capsule neural networks

Cardiovascular diseases (CVD) are the dominant cause of deaths in the world, of which 90% are curable. The electrocardiogram (ECG) measures the electrical stimulus of the heart noninvasively. Convolutional neural networks (CNN) act as one of the powerful machine learning techniques to classify ECG arrhythmia classification and other CVDs. Nonetheless, they have some functional flaws like ignorance of spatial hierarchies be-tween the features and are unable to acquire a rotational invariance. To overcome these problems of CNN, a novel neural network named capsule network (CapsNet) is proposed as an efficient algorithm to provide error ‐ free implementation of deep learning over the databases. The main focus of this work is to apply and implement CapsNet for ECG signal classification from the MIT ‐ BIH database and compare its efficiency with the pretrained CNN networks.
Lower limbs muscle activation during instep kick in soccer: effects of dominance and ball condition

ABSTRACT Muscle activation has been studied in soccer players kicking stationary balls with the dominant foot. This study evaluated swinging and support limb muscle activation during the instep kick using different feet and ball approach conditions.Vastus medialis (VM), biceps femoris (BF), gastrocnemius medialis (GM) and tibialis anterior (TA) activations were evaluated during maximal instep kicks with both feet and the ball in five conditions (n = 18): stationary (STAT), approaching anteriorly (ANT), posteriorly (POST), laterally (LAT) and medially (MED). A repeated-measures two-way ANOVA compared activations between feet and ball conditions throughout the kicking (0–100%) and follow-through phases (101–200%). Close to ball contact (81–124%), non-dominant support GM had greater activation than the dominant one. The LAT and MED conditions differed within the cycle in the swinging VM (0–21%; 191–200%), BF (13–70%; 121–161%), GM (22–82%; 121–143%) and TA (0–32%; 55–97%; 186–200%) and in support VM (0–81%), BF (6–24%; 121–161%) and GM (24–87%). Players require greater support GM activation to stabilize the ankle during non-dominant kicks. Muscle activation differences between LAT and MED indicate that the kicking strategies are altered when kicking balls approaching from different directions.
The Arab Spring and the Egypt-United States of America’s Relations in Post-Revolution Era

Egypt has experienced drastic changes in government recently. Studying these changes can lead to more understanding of the revolutions caused by the Arab Spring in other countries and can also explain the hegemonic conduct of the United States. This qualitative study was conducted through 1) reviewing scholarly published documents and other relevant official news resources that were published on the relationship between Egypt and the United States after the 2011 revolution, and 2) interviewing 12 key informants (ethnic, academic, and administrative elites). Qualitative content analysis was the main approach to data analysis. The results with a focus on both Obama’s administration and Trumps’ administration revealed that Egypt and the United States relations were affected due to Egypt’s anti-western agenda. Later, the United States’ main strategies in maintaining its hegemony in Egypt were discussed. Among these factors, 1) the United States’ aid policy, 2) the United States’ tolerance policy, 3) aborting FJP, 4) imposing the western culture, and 4) the United States’ support of street protests can be mentioned. Areas for further research are discussed at the end of the study.
A 24 GHz Direct Conversion Receiver for FMCW Ranging Radar Based on Low Flicker Noise Mixer

In this paper, a 24 GHz direct conversion receiver (DCR) for frequency-modulated continuous-wave (FMCW) ranging radar based on low flicker noise mixer in 90 nm silicon-on-insulator (SOI) CMOS technology is presented. A low-noise and low-power low-noise-amplifier (LNA) adopting simultaneous noise and input matching (SNIM) method is designed. Neutralized technology and boost inductor are introduced to improve performance. The measurement results of standalone LNA show that the peak gain is 17.2 dB at 23.8 GHz and the −3 dB bandwidth is around 2.2 GHz from 22.8 GHz to 25 GHz. The LNA achieves an average 3 dB NF within the 24 GHz band. A current-bleeding mixer is used to lower noise and the factors influencing flicker noise have been discussed. Proper element values and local oscillator (LO) power have been chosen to make the mixer low-noise. Measurement results illustrate that the receiver exhibits 20.3 dB peak gain, 7 dB SSB noise figure (NF) and −22 dBm IP1dB. Flicker noise of the mixer and the receiver are measured respectively and the noise knee-point of receiver is observed 60 kHz. The receiver consumes only 16 mW with chip area of 0.65 mm2 including pads. The results demonstrate that the proposed receiver can be a promising candidate for FMCW ranging radar.
Cooperative fencing control of multiple second‐order vehicles for a moving target with and without velocity measurements

This article studies the moving‐target‐fencing problem of multiple second‐order vehicles, where the target moves with an unknown constant velocity. Without a predefined stand‐off distance or formation, two classes of local cooperative controllers are proposed with and without velocity measurements. Specifically, the first controller uses the relative position information from the target and vehicle's neighbors, as well as the vehicle's velocity measurement, while the second controller relaxes the common requirement of velocity measurement of the vehicles. It is proved that both controllers simultaneously assure target fencing, collision avoidance, and velocity convergence. Finally, numerical simulations are provided to verify the efficacy of the proposed controllers.
Field calculation of electric dipole excitation of a metafilm printed on a finite‐thickness dielectric slab using the susceptibility homogenization method

Here, the authors calculate the fields due to the electric dipole that excites a homogenized metasurface which is printed on a finite thickness dielectric slab. The problem is solved by replacing the total parts below the periodic array which contain the dielectric slab and the half ‐ space under it, with an effective homogenous half ‐ space. Furthermore, the static interaction constants between dipoles which are located at two different materials’ interface are calculated. Then, with the help of the Lorentz method, the analytical formulae are presented to calculate the surface susceptibility densities of the homogenized metasurface located at two materials’ interface. These analytical formulae can be applied to arrays with both square and rectangular periodicity. An array of circular patches printed on dielectric slabs with different thicknesses is considered to verify the results. The results show good agreement compared to the fields calculated by commercial numerical software FEKO.
Assessing Product Creativity in Computing Education: A Systematic Mapping Study

Creativity has emerged as an important 21st-century competency. Although it is traditionally associated with arts and literature, it can also be developed as part of computing education. Therefore, this article -presents a systematic mapping of approaches for assessing creativity based on the analysis of computer programs created by the students. As result, only ten approaches reported in eleven articles have been encountered. These reveal the absence of a commonly accepted definition of product creativity customized to computer education, confirming only originality as one of the well-established characteristics. Several approaches seem to lack clearly defined criteria for effective, efficient and useful creativity assessment. Diverse techniques are used including rubrics, mathematical models and machine learning, supporting manual and automated approaches. Few performed a comprehensive evaluation of the proposed approach regarding their reliability and validity. These results can help instructors to choose and adopt assessment approaches and guide researchers by pointing out shortcomings.