bluuebunny/crossref_metadata_2025_split huggingface dataset:
Supplementation of tuna hydrolysate and insect larvae improves fishmeal replacement efficacy of poultry by-product in Lates calcarifer (Bloch, 1790) juveniles
Authors: Chaklader Md Reaz , Howieson Janet , Siddik Muhhammad A. B. , Foysal Md Javed , Fotedar Ravi 
Published: March 2021

AbstractThe effects of feeding different levels of poultry by-product meal (PBM) replacing fishmeal (FM) protein, supplemented with tuna hydrolysate (TH) and Hermetia illucens (HI) larvae, on the growth, fillet quality, histological traits, immune status, oxidative biomarker levels and gut microbiota of juvenile barramundi, Lates calcarifer were investigated for six weeks. Barramundi were fed four isonitrogenous and isolipidic diets in which a FM based diet was used as the Control diet (Diet1) and compared with other non-FM diets containing 80%, 85% and 90% PBM along with the concurrent supplementation of 5% and/or 10% TH and HI larvae meal. These treatment diets were designated as 80PBM10TH+10HI (Diet2), 85PBM5TH+10HI (Diet3) and 90PBM5TH+5HI (Diet4). The growth and condition factor of fish fed 80PBM10TH+10HI and 85PBM5TH+10HI were significantly higher than the Control. Total saturated, monounsaturated and polyunsaturated fatty acid retention in the fish muscle increased in fish fed PBM-based diets, supplemented with TH and HI larvae meal, with no adverse effect on post-harvest characteristics such as texture and colour of fish fillets. Improvement in serum total bilirubin and total protein content was found in all fish fed TH and HI larvae supplemented PBM. Similarly, immune response showed a significant increase in fish fed non-FM test diets than the Control. In the distal intestine, supplementation of any quantities of TH and HI larvae to PBM led to an increase in the microvilli density and neutral mucins while the number of goblet cells in the skin were unchanged. Liver, kidney, and spleen histology demonstrated a normal structure with no obvious changes in response to all test diets. Bacterial diversity increased in fish fed Diets 2 and 3 with a high abundance of Proteobacteria in Diets 1 and 4 and Firmicutes in Diets 2 and 3. The fish on test diets showed a lower abundance of genus Vibrio. Fish fed TH and HI larvae supplemented PBM diets showed lower infection rate to V. harveyi than the Control. Collectively, concurrent supplementation of TH and HI larvae could improve the quality of PBM diets with positive effects on growth, fillet quality, intestinal health, immunity, and disease resistance.
Targeted biologic inhibition of both tumor cell-intrinsic and intercellular CLPTM1L/CRR9-mediated chemotherapeutic drug resistance
Authors: Parashar Deepak , Geethadevi Anjali , McAllister Donna , Ebben Johnathan , Peterson Francis C. , Jensen Davin R. , Bishop Erin , Pradeep Sunila , Volkman Brian F. , Dwinell Michael B. , Chaluvally-Raghavan Pradeep , James Michael A. 
Published: March 2021

AbstractRecurrence of therapy-resistant tumors is a principal problem in solid tumor oncology, particularly in ovarian cancer. Despite common complete responses to first line, platinum-based therapies, most women with ovarian cancer recur, and eventually, nearly all with recurrent disease develop platinum resistance. Likewise, both intrinsic and acquired resistance contribute to the dismal prognosis of pancreatic cancer. Our previous work and that of others has established CLPTM1L (cleft lip and palate transmembrane protein 1-like)/CRR9 (cisplatin resistance related protein 9) as a cytoprotective oncofetal protein that is present on the tumor cell surface. We show that CLPTM1L is broadly overexpressed and accumulated on the plasma membrane of ovarian tumor cells, while weakly or not expressed in normal tissues. High expression of CLPTM1L is associated with poor outcome in ovarian serous adenocarcinoma. Robust re-sensitization of resistant ovarian cancer cells to platinum-based therapy was achieved using human monoclonal biologics inhibiting CLPTM1L in both orthotopic isografts and patient-derived cisplatin resistant xenograft models. Furthermore, we demonstrate that in addition to cell-autonomous cytoprotection by CLPTM1L, extracellular CLPTM1L confers resistance to chemotherapeutic killing in an ectodomain-dependent fashion, and that this intercellular resistance mechanism is inhibited by anti-CLPTM1L biologics. Specifically, exosomal CLPTM1L from cisplatin-resistant ovarian carcinoma cell lines conferred resistance to cisplatin in drug-sensitive parental cell lines. CLPTM1L is present in extracellular vesicle fractions of tumor culture supernatants and in patients’ serum with increasing abundance upon chemotherapy treatment. These findings have encouraging implications for the use of anti-CLPTM1L targeted biologics in the treatment of therapy-resistant tumors.
Von der KI-Ethik zur Bewusstseinsethik: Ethische Aspekte der Computational Psychiatry
Authors: Wiese Wanja 
Published: March 2021

Zusammenfassung
Ziel Ermittlung ethischer Probleme, die sich aus KI-Forschung und Computational Psychiatry für die psychiatrische Forschung und Praxis ergeben.
Methode Begriffliche Analyse und Diskussion ethisch relevanter Projekte innerhalb der Computational Psychiatry.
Ergebnisse Die Computational Psychiatry verspricht v. a. einen Beitrag zur Verbesserung von Diagnostik und Therapie(-prognosen). Ethische Probleme betreffen u. a. den Umgang mit Datenschutz, Folgen für unser Selbstverständnis sowie das Risiko der Biologisierung und der Vernachlässigung des bewussten Erlebens.
Schlussfolgerung Es ist erforderlich, sich jetzt mit möglichen Anwendungen der KI und Computational Psychiatry zu befassen, um die Voraussetzungen für einen verantwortungsvollen Umgang in der Zukunft zu schaffen. Dies setzt Grundkenntnisse der Funktionsweise von KI-Anwendungen und der damit zusammenhängenden ethischen Probleme voraus.
In situ scanning x-ray diffraction reveals strain variations in electrochemically grown nanowires
Authors: Larsson Alfred , Abbondanza Giuseppe , Rämisch Lisa , Linpé Weronica , Novikov Dmitri V , Lundgren Edvin , Harlow Gary S 
Published: March 2021

Abstract
Templated electrochemical growth in nanoporous alumina can be used to fabricate nanowires with applications in magnetic storage devices, hydrogen sensors, and electrocatalysis. It is known that nanowires, grown in such templates, are strained. The strain in nanoscale materials can influence their performance in applications such as catalysts and electronic devices. However, it is not well established how the nanoporous template affects the lattice strain in the nanowires and how this develops during the growth process due to the lack of non-destructive in situ studies with spatial resolution. We have measured the strain and grain size of palladium nanowires in nanoporous templates during the growth process. For this, we performed in situ scanning x-ray diffraction with a submicron focused x-ray beam. We found a tensile strain in the nanowires and that it is more pronounced along the growth direction than in the confined direction of the templates. The tensile strain measured in situ is higher than previous ex situ reports, possibly due to hydrogen absorption during the growth. With the spatial information made possible with the focused synchrotron x-ray beam, we could observe local variations in the strain as a function of height. A region of local strain variation is found near the bottom of the nanowires where growth is initiated in branches at the pore bottoms. Knowledge of how nanoporous templates influences the strain of the nanowires may allow for atomic scale tailoring of the catalytic activity of such nanowires or minimizing strain to optimize electronic device performance.
Numerical homogenization of thermal conductivity of particle-filled thermal interface material by fast Fourier transform method
Authors: Lu Xiaoxin , Fu Xueqiong , Lu Jibao , Sun Rong , Xu Jianbin , Yan Changzeng , Wong Ching-Ping 
Published: March 2021

Abstract
Thermal interface material (TIM) is pivotal for the heat dissipation between layers of high-density electronic packaging. The most widely used TIMs are particle-filled composite materials, in which highly conductive particulate fillers are added into the polymer matrix to promote heat conduction. The numerical simulation of heat transfer in the composites is essential for the design of TIMs; however, the widely used finite element method (FEM) requires large memory and presents limited computational time for the composites with dense particles. In this work, a numerical homogenization algorithm based on fast Fourier transform was adopted to estimate the thermal conductivity of composites with randomly dispersed particles in 3D space. The unit cell problem is solved by means of a polarization-based iterative scheme, which can accelerate the convergence procedure regardless of the contrast between various components. The algorithm shows good precision and requires dramatically reduced computation time and cost compared with FEM. Moreover, the effect of the particle volume fraction, interface thermal resistance between particles (R-PP), interface thermal resistance between particle and matrix (R-PM), and particle size have been estimated. It turns out that the effective conductivity of the particulate composites increases sharply at a critical filler volume fraction, after which it is sensitive to the variation of filler loading. We can observe that the effective thermal conductivity of the composites with low filler volume fraction is sensitive to R-PM, whereas the it is governed by R-PP for the composites with high filler content. The algorithm presents excellent efficiency and accuracy, showing potential for the future design of highly thermally conductive TIMs.
Motility and energetics of randomly flashing ratchets
Authors: Xu Xining , Zhang Yunxin 
Published: March 2021

Abstract
We consider randomly flashing ratchets, where the potential acting can be switched to another at random time instants with Poisson statistics. Using coupled Fokker–Planck equations, we formulate explicit expressions of mean velocity, dispersion and quantities measuring thermodynamics. How potential landscapes and transitions affect the motility and energetics is exemplified by numerical calculations on random on-off ratchets. Randomly flashing ratchets with shifted sawtooth potentials are further discussed. We find that the dynamics and output power of such system present symmetry w.r.t. the shift between the two potentials Δmax + Δmin, which is the sum of the shift between the two peaks (Δmax) and the shift between the two bottoms (Δmin). The mean velocity and output power both reach the optimal performance at Δmax + Δmin = 1, provided that the asymmetry α

i
of potential U

i
implies a positive flux respectively, i.e.,
α

i
> 0.5 for i = 1, 2.
An Efficient Prediction Model based on Machine Learning Techniques for Prediction of the Stock Market
Authors: Madeeh Omar D. , Abdullah Hasanen S. 
Published: March 2021

Abstract
Nowadays, the stock market’s prediction is a topic that attracted researchers in the world. Stock market prediction is a process that requires a comprehensive understanding of the data stock movement and analysis it accurately. Therefore, it needs intelligent methods to deal with this task to ensure that the prediction is as correct as possible, which will return profitable benefits to investors. The main goal of this article is the employment of effective machine learning techniques to build a strong model for stock market prediction. The work involved three stages, the first stage involved preprocessing for the stock market data set, then the second stage which involved employing two from supervised machine learning techniques namely K-Nearest Neighbor (K-NN) and Random Forest (RF), and finally, the evaluation stage of accuracy and efficiency of the prediction for the two proposed models. The results experiments showed that the two proposed models achieved a high accuracy ratio and the RF model was the best of prediction accuracy, where it reached 93.23%, 93.12% and 93.17% respectively according to evaluation measures precision, recall, and F-measure.
The Convergence of Iterative Methods for Quasi δ-Contraction Mappings
Authors: Thajil A Q , Maibed Z H 
Published: March 2021

Abstract
In this article, we will present a quasi-contraction mapping approach for D iteration, and we will prove that this iteration with modified SP iteration has the same convergence rate. At the other hand, we prove that the D iteration approach for quasi-contraction maps is faster than certain current leading iteration methods such as, Mann and Ishikawa. We are giving a numerical example, too.
Mixed Penalty with Gradient, Gradient Projection and Frank Wolfe Methods for Solving Nonlinear Hyperbolic Optimal Control Sate Constraints
Authors: Al-Hawasy J A , Al-Rawdanee E H 
Published: March 2021

Abstract
This paper is focused on studying the numerical solution (NUSO) for the discrete classical optimal control problem (DISCOPCP) ruled by a nonlinear hyperbolic boundary value problem (NHYBVP) with state constraints (SCONs). When the discrete classical control (DISCC) is given, the existence and uniqueness theorem for the discrete classical solution of the discrete weak form (DISWF) is proved. The proof for the existence theorem of the discrete classical optimal control (DISCOPC) and the necessary and sufficient conditions (NECOs and SUCOs) of the problem are given. Moreover. The DISCOPCP is found numerically from the Galerkin finite element method (GFE) for variable space and implicit finite difference scheme (IFD) for time variable (GFEIFDM) to find the NUSO of the DISWF and then the DISCOPC is found from solving the optimization problem (OPTP) (the minimum of discrete cost functional (DISCF)) by using the mixed Penalty method with the Gradient method (PGMTH), the Gradient projection method (PGPMTH) and the Frank Wolfe method (PFWMTH). Inside these three methods, the Armijo step option (ASO) is used to get a better direction of the optimal search. Finally, illustrative example for the problem is given to exam the accuracy and efficiency of these methods.
E-Satisfaction based on E-service Quality among university students
Authors: Jameel Alaa S , Hamdi Sameer S. , Karem Mohammed A. , Raewf Manaf B. , Ahmad Abd Rahman 
Published: March 2021

Abstract
The importance of e-service and e-satisfaction in the education sector has increased nowadays due to the COVID 19 pandemic and most of the universities have shifted to electronic platforms to communicate with their students. Some studies had been conducted in Iraq and other developing countries to measure e-service and e-satisfaction in the education sector. the purpose of this study was to investigate the impact of e-service on e-satisfaction among undergraduate students. The survey was conducted at three private universities located in Erbil, Iraq. The study employed a convenience sample and the data was collected using questionnaires. Later, the questionnaire responses were analysed by AMOS after ensuring the validity and reliability of the model. The results showed that the responsiveness and privacy and security had a positive and significant effect on students’ e-satisfaction. On the other hand, efficiency, reliability and ease of use had an insignificant impact on e-satisfaction among students. The results indicated that responsiveness was the most important factor and led to an increase in the e-satisfaction among students. As such, the decision-makers at universities should be concerned and work towards enhancing the responsiveness as well the privacy and security for students.
Speech Scrambler Based on Discrete Cosine Transform and Novel Seven-Dimension Hyper Chaotic System
Authors: Zghair Hayder Kadhim , Mehdi Sadiq A. , Sadkhan Sattar B. 
Published: March 2021

Abstract
Because of their inherent features related to cryptography, the hyperchaotic system has strong potential in security systems. In this paper, a new cryptography scheme for speech scrambling has been proposed which gives it more security level. Also, it introduced a novel seven dimensions (7D) nonlinear hyperchaotic system in third-order which has twelve positive parameters. A chaotic behavior for the proposed novel system is analyzed. The hyperchaotic system is demonstrated that beside it appropriates for speech scrambler. PRNG (Pseudo Random Number Generated) is created based on the proposed 7D hyperchaotic result. The proposed scheme depends on this novel hyperchaotic system as PRNG to generate a random keystream bit. The input speech signal in this work is first squeezed by discrete cosine transformation (DCT) to minimize the residual intelligibility (R. I.). Increasing the number of system parameters accomplished a high key space, therefore, improves the security to resist several cryptographic attacks. The scheme is measured using various tests like. Peak Signal-to-Noise Ratio (PSNR), Signal to noise ratio (SNR), percentage of Difference (P. Diff.), Segmental Signal to Noise Ratio Measure (SSNR), Crest factor measure (CF), Correlation coefficient Measure (R_C), root mean square measure (RMS), histogram, key sensitivity, spectrogram, and waveform The results of simulation and comparison prove that the algorithm can achieve better performance in encryption that means the scheme is stronger and highly secure against various types of attacks than many recent similar audio encryption schemes. Simulated and implemented the result using Mathematica and MATLAB programs to simulation results, provided qualitatively, and figures.
Predication of Quality of Service (QoS) in Cloud Services: A Survey
Authors: Abdullah Muayad N. , Bhaya Wesam S. 
Published: March 2021

Abstract
Quality of Service (QoS) in cloud computing and web service has been commonly used as an essential measure for evaluating services of nonfunctional attributes. However, QoS prediction has become one of the key factors in services recommendation and selection to build high-quality software systems, so it becomes an urgent and crucial research area in both academia and industry. Therefore, several methods and techniques of service recommendation based on collaborative filtering (CF) have been exist for optimizing service selection. We investigate the different exist methods to solve challenging problems. Thence, we discuss and compare these approaches to provide an overview of the latest researches in the field.
Analysis the Results of Laboratory Tests of Gypsum Soil Samples at Salah-Aldeen City by Using the GIS Program
Authors: Al-Hassany Gheidaa Sabeeh Hadi , Abdulwadood Huda Wogod , Mustafa Reem Ibrahim 
Published: March 2021

Abstract
This paper has dealing with experimentally works which includes properties of materials and testing program. The testing program includes rotine characterization tests, chemical, and physical tests for samples of gypseous soil. Samples of disturbed and undisturbed soil was obtained of seven different locations of Salah-Aldeen province. The unified classification system was adopted of study region. Except sample 7, soil categorization (as poorly graded sand) was a good graded sand soil. Samples had non plasticity rate (NP). The results of laboratory tests (by using Arc-Map GIS program) were enhanced by spatial interpolation mapping utilizing Inverse Distance Weighted Scheme.
Integrated Spectrum Sensing and Frequency Reconfigurable Antennas for Inter-Weave Cognitive-Radio Applications
Authors: Mohammed Ali A. , Abdullah Abdulkareem S. 
Published: March 2021

Abstract
A dual-port antenna configuration composed of an ultra-wideband (UWB) sensing antenna and a dual-band reconfigurable communicating antenna is proposed and studied in this paper. The sensing antenna is an elliptical disk radiator covers a frequency range of (1.8-11) GHz. The communicating antenna is a modified dual-band rectangular radiator. By controlling the length of a stub attached to the communicating antenna with the aid of two PIN-diodes, the dual-band antenna can reconfigure its resonant frequencies to (2, 2.2) GHz, (3.25, 3.8) GHz, and (4.3, 5.6) GHz. Both simulated and experimental results for the return loss, mutual coupling, radiation patterns and gain are presented, and they reveal the antenna compatibility with the inter-weave cognitive radio applications.
Hyperparameter Determines the Best Learning Curve on Single, Multi-Layer and Deep Neural Network of Student Grade Prediction of Pokhara University Nepal
Authors: Rimal Yagyanath , Pandit Palvi , Gocchait Saikat , Butt Shariq Aziz , Obaid Ahmed J. 
Published: March 2021

Abstract
This primary study tries to explore the best machine learning model of hyperparameter tuning using single, multiple, and deep neural networks for predicting engineering student grade of Pokhara University Nepal in the year 2019. Generally, hyperparameter algorithms are adjusted from the data sets automatically when the model was designed. This is not a good idea for all sort of algorithm, with less flexibility of user choices. Therefore this article ties to meet the research gap between automatic calculation vs external model hyperparameter calculation on the same data sets applying comparison. The single neuron predicts 92 percent accuracy of the student’s A, B, C, D grade of university examination with correlation with their internal marks respectively. The five-neuron multilayer neural network produces 72 percent accuracy and deep neural network with drop-out layer (32, 64) examines, the most suitable hyperparameter determines to produce an accurate result of 50 percent accurate when 32 hidden levels were used over 64 hyperparameters produce quite less accuracy (44 percent) of their final score in constituent campus Pokhara. The main objective of this study is to examine the comparison between various neural networks for educational settings for optimization of model deployment accurately when categorical large data prediction of student grade. Therefore, this study compares three comparisons of the neural network model with the same data sets for best hypermeter prediction.
Design and Implementation of Electronic Enterprise University Human Resource Management System
Authors: Shukur Hanan M. , Zeebaree Subhi R. M. , Zebari Rizgar R. , Hussan Bzar Kh. , Jader Omid H. , Haji Lialan M. 
Published: March 2021

Abstract
Electronic Human Resource Management System (EHRMS) is a paperless-based system, which plays a vital role in facilitating organizational processes, overcoming all obstacles of a paper-based system, reducing cost, time, and efforts, enhancing the quality of services (QoS), and providing more accurate data. In addition, it is beneficial for competitive advantages and it eases the tasks of the HR managers to make decisions. In this paper, an efficient EHRMS is proposed, designed, and implemented. The system is called Enterprise Electronic University Human Resource Management System (EEUHRMS). The proposed system consists of fourteen modules that provide four groups of services. The first group is related to applicant services: Online Recruitment. The second group is related to staff services: Registration, Acknowledgements/Punishments, Annual Premium, Leaves, Leave Deduction, Archive, Dispatch, Extra Fees, Salary, and Service Summary. The third group is related to institutions and presidency services: Post and Statistics. While the fourth group is related to university services: Authentication and Statistics. The proposed system is evaluated by using the System Usability Scale (SUS) to get results via specific questionnaires that are checked by the university staff. The evaluation score of the questionnaire was about (85) which is considered a good result. The proposed system is developed using the Laravel framework.