Miracle-dz/UniFAR-FTUs huggingface dataset:
Oat Agronomic and Grain Quality Responses to Growth Regulators1

Lodging often limits oat (Avena sativa L.) yields and retards or prevents establishment of forage legumes seeded with it. We tried to determine whether growth regulators might be used to prevent oat lodging and to learn their effects on grain yield and quality. Ten chemical growth regulators were applied to foliage of two cultivars at two stages of development. Studies were conducted over a 3-year period (1971–1973) at Arlington, Wis. on ‘Froker,’ a stiff-strawed cultivar, and ‘Ajax,’ a weak-strawed cultivar. Agronomic characteristics evaluated included grain yield, test weight, plant height, and lodging. Quality aspects evaluated included groat protein yield, weight, percent, oil concentration, fatty acid composition, and protein and mineral concentrations of both groats and hulls. Several chemical treatments reduced plant height and lodging; however, these were often accompanied by lower test weights and lower yields. Low rates of application which were ineffective in reducing lodging also resulted in few beneficial effects on yield. With a few exceptions the treatments had little effect on grain quality.
6th China-Japan-Korea Joint Symposium on Optimization of Structural and Mechanical Systems

A hybrid approach of multiobjective optimization and antioptimization is presented for force design of tensegrity structures. The objective functions are to maximize the lowest eigenvalue of the tangent stiffness matrix, and to minimize the deviation of forces from the specified distribution, which are defined as the worst values due to the possible uncertainties. The worst values are found by solving the antioptimization problems using the enumeration of the vertices of the uncertain region of the prestresses. The Pareto solutions for the two-objective optimization problem are found using a nonlinear programming algorithm for minimizing linear-weighted-sum of the objective functions. It is shown in a numerical example that Pareto optimal solutions can be successfully found for a tensegrity grid by solving the two-level optimization-antioptimization problem using vertex enumeration technique combined with a nonlinear programming approach.
Hemodynamic monitoring using trans esophageal echocardiography in patients with shock

Circulatory shock is a life-threatening condition responsible for inadequate tissue perfusion. The objectives of hemodynamic monitoring in this setting are multiple: identifying the mechanisms of shock (hypovolemic, distributive, cardiogenic, obstructive); choosing the adequate therapeutic intervention, and evaluating the patient’s response. Echocardiography is proposed as a first line tool for this assessment in the intensive care unit. As compared to trans-thoracic echocardiography (TTE), trans-esophageal echocardiography (TEE) offers a better echogenicity and is the best way to evaluate deep anatomic structures. The therapeutic implication of TEE leads to frequent changes in clinical management. It also allows depicting sources of inaccuracy of thermodilution-based hemodynamic monitoring. It is a semi invasive tool with a low rate of complications. The first step in the hemodynamic evaluation of shock is to characterize the mechanisms of circulatory failure among hypovolemia, vasoplegia, cardiac dysfunction, and obstruction. Echocardiographic evaluation includes evaluation of LV systolic and diastolic function, as well as RV function, pericardium, measure of stroke volume and cardiac output, and evaluation of hypovolemia and fluid responsiveness. TEE can be used as a semi-continuous monitoring tool and can be repeated before and after therapeutic interventions (vasopressors, inotropes, fluid therapy, specific treatment such as pericardial effusion evacuation) to evaluate efficacy and tolerance of therapeutic interventions. In conclusion, TEE plays an important role in the management of circulatory failure when TTE is not enough to answer to the questions, although it is not a continuous tool of monitoring. TEE results must be integrated in a global evaluation, the first step being clinical examination. Whether TEE-directed therapy and close hemodynamic monitoring of shock has an impact on outcome remains debated.
Density-Based Clustering for 3D Object Detection in Point Clouds

Current 3D detection networks either rely on 2D object proposals or try to directly predict bounding box parameters from each point in a scene. While former methods are dependent on performance of 2D detectors, latter approaches are challenging due to the sparsity and occlusion in point clouds, making it difficult to regress accurate parameters. In this work, we introduce a novel approach for 3D object detection that is significant in two main aspects: a) cascaded modular approach that focuses the receptive field of each module on specific points in the point cloud, for improved feature learning and b) a class agnostic instance segmentation module that is initiated using unsupervised clustering. The objective of a cascaded approach is to sequentially minimize the number of points running through the network. While three different modules perform the tasks of background-foreground segmentation, class agnostic instance segmentation and object detection, through individually trained point based networks. We also evaluate bayesian uncertainty in modules, demonstrating the over all level of confidence in our prediction results. Performance of the network is evaluated on the SUN RGB-D benchmark dataset, that demonstrates an improvement as compared to state-of-the-art methods.
Attitude and Hovering Control of Quadrotor Systems using Pole Placement Method

In this paper, we propose a control scheme for quadrotor system using a pole placement method. When using a state feedback controller, a lot of trial and error in selection of control gains are often required to improve system performance. In order to relax this complicated process, we analyze the closed-loop system associated with control gains. Then, we present a control gain selection algorithm for control gains using a pole placement method to improve the system performance. The proposed control method is applied to the actual quadrotor system to illustrate the validity of the proposed method. 요 약 본 논문에서는 극 배치 기법을 활용하여 쿼드로터 시스템의 제어기법을 제안한다. 일반적으로 상태 궤환 제어기를 사용하 여 제어된 시스템 성능을 개선하기 위해서는 많은 제어 이득 값 선정에서의 시행착오가 필요하다. 이러한 복잡성을 완화시키 고, 체계적인 제어 이득 선정을 위해 쿼드로터의 폐루프 시스템을 분석한다. 시스템 성능을 개선시키기 위해 극 배치 기법을 활용한 제어 이득 결정 알고리즘을 제안한다. 제안된 제어기법은 실제 시스템인 쿼드로터에 적용하여 유효성을 입증한다.
Immobilization of Pseudomonas Aeruginosa in Different Matrices for the Production of Alkaline Protease

Numerous enzymes are used in various types of industries, and one such enzyme used in several of these industries is proteases. Aforementioned, industries such as dairy, detergent, leather, fermentation and several other industries are benefitted with protease enzyme. In the present study, the efficiency of protease production was studied by enriching and immobilizing several matrices by a gram negative bacteria known as Pseudomonas aeruginosa . The immobilization was carried out by four different matrices under two different concentrations of 3% and 4%. Yielded results revealed highest enzymatic activity of 240 (U/ml) in 3% calcium alginate. Still, second highest enzymatic activity of 230 (U/ml) was seen in 4% calcium alginate. On the contrary, free microbial cells showed an enzymatic activity of 100 (U/ml). The peak activities for other methods area as follows: 4% calcium alginate - 133 (U/ml), 3% agar-agar - 100 (U/ml), 4% agar-agar - 91 (U/ml), 3% Gelatin - 85 (U/ml), 4% Gelatin - 88 (U/ml) and Polyacrylamide – 104 (U/ml). The most optimum matrix for the cellular entrapment of Pseudomonas aeruginosa is seen in 3% calcium alginate for alkaline protease production.
Haw the Default Probability is Defined by The Credit Portfolio Models: A Comparative Theoretical Analysis between the Structural Models?

This paper is elaborate of which the main is to present a theoretical analysis between the structural models. There are currently three types of models to consider the risk of credit: the structural models (The KMV Moody’s model and the CreditMetrics model) also defined by the models of the value of the firm, reduced form models also defined by models with intensity (actuarial models) and the econometric models (The macro-factors models). The development of its three types of models is based on a theoretical basis developed by several researchers and many financial institutions. These models are dedicated to measurement the default probability of credit portfolio. The evaluation of their default frequencies and the size of the credit portfolio are expressed as functions of macro-economic and micro-economic conditions as well as unobservable credit risk factors, which explained by other factors. We developed three sections to explain the different characteristics of the structural models of credit portfolio management. The purpose of all its models is to express the probability of default.
kini ditentukan melalui beberapa indikator, antaranya bilangan penerbitan yang tinggi. Ahli akademik yang mempunyai bilangan penerbitan yang tinggi selalunya akan menjadi perhatian rakan sekerja dan majikan kerana mampu membawa reputasi yang baik kepada universiti. Pentadbir menggunakan penerbitan s

The excellence of academicians in universities at present is determined by several indicators, including the high number of publications. Academicians with a high number of publications will often be attentive to colleagues and employers for being able to bring a good reputation to the university. Administrators use publishing as one of the key criteria in measuring the competence of an academician and determining promotion. The study aims to explore factors that contribute to the performance of publishing among academic staff in UKM. This study uses a qualitative app inroach to collect and analyze findings. In-depth interviews using semi-structured questions are the primary means of data collection. This study involved a total of 10 informants consisting of two target groups which are excellent in publishing group and less excellent in publishing group. Analysis was conducted thematically. The findings show three main factors contributing to the excellence of publications namely (i) personal (ii) workplace climate, and (iii) interpersonal relationships in the workplace. In conclusion, success in determining excellence in publications requires the balance and well-being of the social environment. The recommendations of Revised Manuscript Received on September 25, 2019 First Author name, Nasrudin Subhi is a lecturer in the Faculty of Social Science and Humanitarian, University Kebangsaan MALAYSIA. CoAuthors name, Salina Nen, Nor Jana Saim, Mastura Mahmud & Norulhuda Sarnon are lecturers in the Faculty of Social Science and Humanitarian, Universiti Kebangsaan MALAYSIA this study can be used as means to assist university management to increase publications among the academic staff of the university.
Endometriosis and ovarian cancer risk, an epigenetic connection

Endometriosis is a gynecological disorder that affects 176 million women worldwide and 1 in 10 females in the United States. Endometriosis most often affects women of child-bearing age, with most going undiagnosed. Endometriosis also shares many characteristics common to invasive cancer and has been known to be associated with epithelial ovarian cancer. Ovarian cancer is the 11th most common cancer among women and over 22,000 new cases will be diagnosed within the next year. Women most commonly diagnosed with this cancer are between the ages of 55–64 years, outside the range of the age of women affected with endometriosis. While no known cause of either disease has been established, epigenetic regulation is thought to play a major role in both. This review focuses on epigenetic changes that occur within each individual disease as well as those that are similar in both, suggesting a possible etiological link between the two diseases.
Large-Scale Analysis of Linear Massive MIMO Precoders in the Presence of Phase Noise

— We study the impact of phase noise on the downlink performance of a multi-user multiple-input multiple-output system, where the base station (BS) employs a large number of transmit antennas M. We consider a setup where the BS employs Mosc freerunning oscillators, and M/Mosc antennas are connected to each oscillator. For this configuration, we analyze the impact of phase noise on the performance of the zero-forcing (ZF), regularized ZF, and matched filter (MF) precoders when M and the number of users K are asymptotically large, while the ratio M/K = _ is fixed.
Modeling Seasonal Trophic Interactions of Adfluvial Bull Trout in Lake Billy Chinook, Oregon

Abstract We examined the trophic interactions of bull trout Salvelinus confluentus in Lake Billy Chinook, Oregon, using a bioenergetics model combined with data on annual growth, seasonal diet, distribution, and thermal experience to determine the seasonal and size-specific prey requirements of bull trout and the influence of bull trout predation on some of their major prey species in the reservoir. Per capita estimates of consumption were expanded to population-level estimates based on estimates of size structure and the abundance of the bull trout population. Bull trout became progressively more piscivorous with increasing size, and fish were the primary prey of predators of 450 mm fork length (FL) or more. Kokanee (lacustrine sockeye salmon Oncorhynchus nerka) and other salmonids (predominantly bull trout and rainbow trout O. mykiss) represented the largest fraction of fish prey in the diet, although cyprinids, cottids, and catostomids were also consumed. Predation on kokanee occurred primarily in autu.
Mutual Information Based Framework of Quality Parameter Formulation for Similarity Index between Two Musical Notes

Thepaper presents an approach of formulating a parameter to access the relative quality of a musical note with reference to the standard musical note. The tonal quality perceived by an individual is prominently subjective. The work in the paper focusses on the objectivity of this comparison. The objectivity introduced essentially will be helpful to come up with at least basic conclusive step regarding the relative tonal quality. The proposed parameter is also evaluated against the rating given by the raters to the tonal quality of a musical note with reference to reference note to prove its effectiveness and agreement with raters. Harmonium and flute are taken as the instruments for experimentation. The approach proposed can be applied to any two musical notes produced with different instruments with one instrument reference. The quality parameter is proposed by evaluating different parameters of musical note and then using the technique of minimum redundancy maximum relevance (mRmR) technique of feature ranking. The Empirical way is formulated to develop the quality parameter which is also put to test against rankings of raters. Thus the paper provide a systematic way of deducing the quality parameter which will be in agreement with the tonal quality perceived by human ears.
CRITICAL E-LEARNING RECOGNITION FACTORS: AN EMPIRICAL RESEARCH OF STUDENT PERCEPTIONS IN NORTHEAST INDIA

– IT companies with the information era and tide of on-line education, it is necessary to explore learners’-learning recognition behaviors. By investigating critical factors on e-learning in Northeast (NE) India, our study attempts to probe the innate mechanism for individual e-learning intention with data collection place of Northeast India. Findings indicate that instructor characteristics and teaching resources are the predictors of the perceived usefulness of e-learning and perceived usefulness and joyfulness are the predictors of the e-learning recognition. While statistically significant, perceived adaptability was shown to have the weakest effect on the e-learning recognition among the predictors. All these results are very consistent with the previous studies conducted in other countries, proving the universal nature of the learners’ perceptions and behavior towards e-learning. Managerial implications of the findings and future research directions are also discussed eventually.
Plant Disease Detection and Localization using GRADCAM

Plant diseases are diseases that change or disrupt its important functions. The reduction in the age at which a plant dies is the main danger of plant diseases. And farmers around the world have to face the challenge of identifying and classifying these diseases and changing their treatments for each disease. This task becomes more difficult when they have to rely on naked eyes to identify diseases due to the lack of proper financial resources. But with the widespread use of smartphones by farmers and advances made in the field of deep learning, researchers around the world are trying to find a solution to this problem. Similarly, the purpose of this paper is to classify these diseases using deep learning and localize them on their respective leaves. We have considered two main models for classification called resnet and efficientnet and for localizing these diseases we have used GRADCAM and CAM. GRADCAM was able to localize diseases better than CAM Keyword: Plant Leaf Diseases , Deep Learning, Efficientnet , GRADCAM.
A boundary and finite element coupling for a magnetically nonlinear eddy current problem

The aim of this paper is to provide a mathematical and numerical analysis for a FEM-BEM coupling approximation of a magnetically nonlinear eddy current formulation by using FEM only on the conducting domain, and by imposing the integral conditions on its boundary. The nonlinear relationship between flux density and the magnetic field intensity is given by a physical parameter called magnetic reluctivity, which is assumed to depend on the Euclidean norm of the magnetic induction in the conducting domain. We use the nonlinear monotone operator theory for parabolic equations to show that the continuous formulation obtained for the coupling is a well-posed problem. Furthermore, we use Nédélec edge elements, standard nodal finite elements, and a backward-Euler time scheme, to obtain a fully discrete formulation and to prove quasi-optimal error estimates.
LANGUAGE MODEL FOR DIGITAL RECOURSE OBJECTS RETRIEVAL

Language model has been successfully applied for use in information retrieval to retrieve structure and unstructured information. Typically, language model involves three basic models namely: N-gram language models, smoothing model and estimation model. Language model has been approved outperforms of other retrieval model such as vector space model and probabilistic model. The problem arises when language model uses to retrieve digital Resource Objects which use metadata to describe their content. Digital Resource Objects have special three characteristics: lack in metadata content (short document), short query, and heterogeneity metadata content. This paper presents a performance comparison among information retrieval models (Vector Space Model and Probabilistic Model) using a Digital Resource Objects (CHiC2013 collection). Further, an overview for language model approaches to determine which models are suitable for digital Resource Objects, despite being a traditional review, a comprehensive comparative analysis is conducted among different approaches of Language model.
Increasing the Accuracy of Video Abstraction from Multiple Sources in the Internet of Things

: - I n this paper a multiple sources video abstraction scheme is proposed for summarizing video content in the Internet of Things IoT). The proposed scheme borrows concepts from the IoT in case of events’ recording from different cameras around a specific geo-location. In particular the proposed abstraction method assumes that frame trajectories are created and an interpolation scheme is designed to optimally approximate these trajectories. The selected points on every trajectory are extracted as key-frames. Key-frames from all different sources are put in chronological order to produce the video abstract. In case a user demands more accuracy, he/she can increase it by refining the number of key-frames. In this case an optimal accuracy increasing approach is proposed and the video abstract is tuned according to the needs of the user. Experimental results on real world videos exhibit the promising performance of the proposed scheme.
Z-DAG: A Practical Performance Analysis

—The following document outlines a performance benchmarking analysis of Syscoin’s Z-DAG implementation. This paper describes the testing methodologies employed by the Whiteblock team within these initiatives and presents the results of these efforts. All tests were conducted on the Whiteblock Genesis blockchain testing platform. Each test series was engineered to observe the effects of various environmental conditions on application performance, speciﬁcally in regard to capabilities concerning transactional throughput which consistently presented in the range of 14,000 - 30,000 transactions per second (TPS) in an environment which emulated high degrees of activity under realistic Wide Area Network (WAN) conditions. While results are substantially higher in comparison to those achieved by alternative contemporary blockchain systems, it is important to note that these tests were designed only to observe the practical performance of Syscoin’s Z-DAG implementation and not the Syscoin platform as a whole. As such, these results should only be considered to reﬂect the capabilities of said implementation and may not be indicative of the holistic performance of the platform itself.
HIGH-CAPACITY MULTI-LAYER FRAMEWORK FOR HIGHLY ROBUST TEXTUAL STEGANOGRAPHY

- A novel approach has been proposed to improve security and imperceptibility to achieve secure communication. Information hiding has been extensively functional on diverse fields due to enormous use of internet, with support of two major branches, digital watermarking and Steganography. The security issues become prime and necessary concern and energized requirement for better techniques for securing info. In this paper we have proposed a novel text steganography technique by using its technical properties. Proposed technique is storing of text files require less memory and it works faster and makes communication preferable to other mediums of steganography. Paper aim is to develop model to improve capacity, imperceptibility and robustness by multilayer textual steganography with combination of encryption, compression and embedding approach for data obscurity. Various functions are used to encrypt secret word for number of times in our proposed method. Compression is achieved through Lemple-ZIV compression method which as a result reduces size of secret word and embedding is achieved with help of permutation method. Experimental results show that proposed scheme has improved stego features as early research uses less embedding capacity approach which affects other two features.