Miracle-dz/UniFAR-FTUs huggingface dataset:
Investment, Financial Factors and Cash Flow from Nigerian Panel Data

The study investigates how the incidence and severity of information and agency problems vary across firms and over time in Nigeria, and assesses the differential effects on corporate investment. A reduced form q-cash flow model and interaction approach was adopted to examine the effects of firm size, age and industry specific characteristics on cash flow. The model was estimated using panel data for Nigerian manufacturing firms from 1984-2000. Financial effects are generally important for investment in all firms. However, the extent and impact of financial effects are not uniformly distributed. The study concludes that the effect of size is neutral; however, older firms tend to rely more on internal funds to finance their corporate investment than the newer firms. The effect of financial factors on investment varies across firms according to their industrial characteristics.
Power Aware Dynamic Source Routing Protocol To Increase Lifetime Of Mobile Ad Hoc Networks

Mobile ad hoc network (MANET) is infrastructure less system of communication. Many remote areas where infrastructure based systems are not feasible. MANETs provide the perfect solution for that situation. Although, MANETs use various routing protocols but Dynamic Source Routing (DSR) is the widely used routing protocol among them because of the flexibility and efficiency of the protocol. MANET usually takes battery power for the operation and it determines the lifetime of MANET. In this paper, we have proposed two modifications in the algorithm of traditional DSR to increase the lifetime of MANET. It will prevent the network from being partitioning and helps node from being sinking down. Initial energy of node will determine the behaviour of the MANET. We have simulated our proposed methodology in ns2.35 and results are found impressive. It works perfectly at lower initial energy of nodes.
A Prism Vote Framework for Individualized Risk Prediction of Traits in Genome-wide Sequencing Data of Multiple Populations

Multi-population cohorts offer unprecedented opportunities for profiling disease risk in large samples, however, heterogeneous risk effects underlying complex traits across populations make integrative prediction challenging. In this study, we propose a novel Bayesian probability framework, the Prism Vote (PV), to construct risk predictions in heterogeneous genetic data. The PV views the trait of an individual as a composite risk from subpopulations, in which stratum-specific predictors can be formed in data of more homogeneous genetic structure. Since each individual is represented by a composition of subpopulation memberships, the framework enables individualized risk characterization. Simulations demonstrated that the PV framework applied with alternative prediction methods significantly improved prediction accuracy in mixed and admixed populations. The advantage of PV enlarges as the sample size, genetic heterogeneity, and population diversity increase. In two real genome-wide association data consists of multiple populations, we showed that the framework enhanced prediction accuracy of the linear mixed model by up to 12.1% in five-group cross validations. The proposed framework offers a new aspect to analyze individual’s disease risk and improve accuracy for predicting complex traits in genome data.
Double Quarter Wave Crab Cavity Field Profile Analysis and Higher Order Mode Characterization

The Large Hadron Collider (LHC) is underway for a major upgrade to increase its luminosity by an order of magnitude beyond its original design specifications. This novel machine configuration known as the High Luminosity LHC (HL-LHC) will rely on various innovative technologies including very compact and ultra-precise superconducting crab cavities for beam rotation. A double quarter wave crab cavity (DQWCC) has been designed at Brookhaven National Laboratory for the HL-LHC. This cavity as well as the structural support components were fabricated and assembled at Niowave. The field profile of the crabbing mode for the DQWCC was investigated using a phase shift bead pulling technique and compared with simulated results to ensure proper operation or discover discrepancies from modeled results and/or variation in fabrication tolerances. Higher-Order Mode (HOM) characterization was also performed and correlated with simulations.
THE ROLE OF MEDIA IN THE DEVELOPMENT AND PROMOTION OF ENGLISH IN PAKISTAN

This research study is centered on the role of media in the development and promotion of English in Pakistan. It relates to the national process and to the process of globalization in terms of information through T.V, radio and newspapers. It also deals with the challenges in this field, due to the advent of science and technology plus current innovations in this mode of communication. In recent years the media in Pakistan has developed at a fast pace and English has become one of its prominent languages. However, its lack of understanding by 90% of the population has created serious gaps in internal communication. To bridge the existing gap, the study looks at how media can be instrumental in the spread of English language and be a useful tool for improving the English language teaching situation. The study addresses the topic by taking a look at the language situation in Pakistan. Unlike many post colonial states which replaced English with indigenous languages, Pakistan retained English as an official language. However due to lack of a clear cut language policy towards English language teaching it has remained a controversial issue, badly affecting the process of education and development. This has impacted the language situation and its impact leads us to think and reinvent the role of media for teaching it. Given its premier position as the language of international commerce and science, proficiency in English is increasingly acknowledged as vital attribute for any state attempting to establish itself as knowledge based economy. This need is imperative as we are living in a global world. Globalization and issues related to it force us to have a futuristic vision. There is a need to equip our people to meet the demands of modern education. Therefore, we must introduce our students to it at an early stage and provide this opportunity to a large number of people as opposed to the privileged few. Electronic and print media by introducing English to the neglected sector of the society can play a unifying role to integrate the nation. It is in this back drop, the findings of the study are expected to suggest an essential direction of using media for instructional purposes, particularly to bring a constructive change in English language teaching in the country. A multi-method approach has been applied for the collection and analysis of the data. This has been done as triangulation yields more reliable results. This study has been concluded with the hope that media will look into this vital area and fulfill its responsibilities.
ANALISIS FAKTOR-FAKTOR YANG MEMPENGARUHI ADOPSI CLOUD COMPUTING DI RUMAH SAKIT MUHAMMADIYAH

This article aims to determine the factors influencing the adoption of cloud computing in the hospital Muhammadiyah in Indonesia by using Technology Acceptance Model (TAM). The sample used in this study is 51 samples. The analytical tool used Partial Least Square (PLS) on SmartPLS program version 2.0. Factors supporting the adoption of cloud computing: perceived ease of use, perceived usefulness, security effectiveness, reliabilty, needs, cost effectiveness, top management support, complexity, behavioral intention to use and actual usage. Evaluation of the goodness of fit and bootstrapping resampling is used to analyze the feasibility of the model. Evaluation of the goodness of fit of the structural model is measured using predictive value-relevance obtained a value of = 0.95, which means models have a very good predictive value. Hypothesis test results obtained using resampling bootstrapping to calculate the relationship between variables have the value t count bigger = 2.01 in the adoption of cloud computing in the hospital Muhammadiyah, 8 (eight) hypothesis is accepted, namely: Perceived usefulness,, Perceived ease of use, needs , top management support, complexity, and 3 (three) hypothesis is rejected, namely: security, reliabilty and cost effectivenes
Emergency modeling in transportation via queuing and game theory

OF THE DISSERTATION Emergency Modeling in Transportation via Queuing and Game Theory By ZHE DUAN Dissertation Director: Dr. Melike Baykal-Gursoy In modern transportation network, emergencies on roadway and man-made emergencies in the infrastructure can incur enormous costs to society directly and indirectly. The direct costs include transportation cost due to incident delay and traffic congestion, and various risks brought upon the infrastructure by man-made emergencies. The indirect cost can include economic and psychological impacts on society. Emergencies on roadways include accidents, disabled vehicles, adverse weather conditions, spilled loads, hazardous materials, etc. Under these cases, non-recurrent congestion will slow down the traffic flow on certain road link. In previous research, deterministic queuing models are often used for traffic flow modeling. However, due to the random environment of traffic flow, it is necessary to introduce stochastic elements into current traffic flow modeling. In our research, we use stochastic queuing models, such as Markov-modulated queuing systems, for traffic flow modeling under incidents. And non-recurrent and recurrent congestion models will be combined together to improve travel time estimation. Man-made emergencies in the infrastructure are terrorist attacks, suicide bombings, etc. Human casualties are the major goal of intelligent adversaries. We use game theory in order to allocate first responders’ resources inside the transit infrastructure to minimize human casualty. In the static zero-sum game model, we show that both the adversary
Elevated transferrin saturation in individuals with alcohol use disorder: Association with HFE polymorphism and alcohol withdrawal severity

Iron loading has been consistently reported in those with alcohol use disorder (AUD), but its effect on the clinical course of the disease is not yet fully understood. Here, we conducted a cohort study to examine whether peripheral iron measures, genetic variation in HFE rs1799945 and their interaction differed between 594 inpatient participants with alcohol use disorder (AUD) undergoing detoxification and 472 healthy controls (HC). We also assessed whether HFE rs1799945 was associated with elevated peripheral iron and can serve as a predictor of withdrawal severity. AUD patients showed significantly higher serum transferrin saturation than HC. Within the AUD group, transferrin saturation significantly predicted withdrawal symptoms (CIWA‐Ar) and cumulative dose of benzodiazepine treatment during the first week of detoxification, which is an indicator of withdrawal severity. HFE rs1799945 minor allele carriers showed elevated transferrin saturation compared to non‐carriers, both in AUD and healthy controls. Exploratory analyses indicated that, within the AUD cohort, HFE rs1799945 predicted CIWA withdrawal scores, and this relationship was significantly mediated by transferrin saturation. We provide evidence that serum transferrin saturation predicts alcohol withdrawal severity in AUD. Moreover, our findings replicated previous studies on elevated serum transferrin saturation in AUD and an involvement of HFE rs1799945 in serum transferrin saturation levels in both AUD and healthy controls. Future studies may use transferrin saturation measures as predictors for treatment or potentially treat iron overload to ameliorate withdrawal symptoms.
Deep sequencing of yeast and mouse tRNAs and tRNA fragments using OTTR

Among the major classes of RNAs in the cell, tRNAs remain the most difficult to characterize via deep sequencing approaches, as tRNA secondary structure and nucleotide modifications can both interfere with cDNA synthesis by commonly-used reverse transcriptases (RTs). Here, we benchmark a recently-developed RNA cloning protocol, termed Ordered Two-Template Relay (OTTR), to characterize intact tRNAs and tRNA fragments in budding yeast and in mouse tissues. We find that OTTR robustly captures full-length tRNAs in budding yeast and in mouse testis, with relatively low levels of premature termination at known barriers – 1-methylguanine, N2,N2-dimethylguanine, and 1-methyladenine – to typical reverse transcriptases. Moreover, these and several other nucleotide modifications leave misincorporation signatures in OTTR datasets which enables their detection without any additional protocol steps. Turning to analysis of small RNAs such as tRNA cleavage products, we compare OTTR with several standard small RNA-Seq protocols, finding that OTTR provides the most accurate picture of tRNA fragment levels by comparison to “ground truth” Northern blots. Applying this protocol to mature mouse spermatozoa, our data dramatically alter our understanding of the small RNA cargo of mature mammalian sperm, revealing a far more complex population of tRFs – including both 5’ and 3’ tRNA halves derived from the majority of tRNAs – than previously appreciated. Taken together, our data confirm the superior performance of OTTR to commercial protocols in analysis of tRNA fragments, and force a reappraisal of potential epigenetic functions of the sperm small RNA payload.
Implementation of Robot Control Algorithms by Real-Time Control System

The paper deals with development and implementation of the direct and inverse kinematics to control of 6 DOF industrial robot SEF-ROBOTER SR25 by a real time control system. To obtain the angular position of each joint an iterative algorithm is applied that is developed in the Simulink program. This solution creates a basis for real time control of the robot drives utilizing features of SIEMENS SINAMICS family of frequency converters. The developed control system presents a universal platform enabling to debug any robot control algorithm and also easy to change a desired trajectory of the end effector. The equipment is suitable for testing different trajectories of the robot and is suitable also for educational purposes.
HYDRAULIC EROSION OF COHESIVE SOILS

The mechanism of erosion of saturated and unsaturated soils was studied by examining the effect of initial water content on the critical shear stress required to initiate erosion. Erosion tests on saturated and unsaturated soils were carried out in a rotating cylinder and a flume apparatus respectively. To provide a valid comparison of the critical shear stresses obtained on two different measuring devices, identical saturated samples were tested in both to show that the critical shear stress is independent of the testing apparatus. Critical shear stresses obtained as a function of water content on saturated and compacted samples were compared. The mechanism causing erosion in both cases has been shown to be due to swelling. The mechanism causing swelling in the saturated samples is shown to be due to differences in concentration gradient. Test results are also presented to show the influence of structure and water content on the slaking of soils.
The Activity of Some Herbs with or Without Honey in Protecting the Liver against Carbon Tetrachloride Hepatotoxicity in Female Albino Rats

A total number of 50 Sprague Dawley strain female albino rats (200±10g each) were used in the present study, to evaluate the effect of phytogenic diet (Gentiana, Glycyrrhizae, Ginseng and Rheum) at 9% levels on the body weight gain (BWG), liver enzymes activities (ALT and AST), serum protein fractions (TP, ALB, GLB and ALB/GLB ratio), lipids profile (TC, TG, VLDL-c, LDL-c and HDL-c) and AI. Rats divided into 10 groups (5 rats each) including control negative (–Ve) fed on basal diet only, control positive (+Ve) fed on basal diet and injected with CCl4, as well as 4 groups consumed a diet containing 9% of herbs without honey and other 4 groups consumed their diets containing 4.5% of herbs powder plus 4.5% of honey. Microscopic evaluations of the liver revealed CCl4-induced lesions and related toxic manifestations that were minimal in the liver of rats pretreated with powders at the dose of 9%/ kg of body weight. The results revealed that all herbs improved the tested parameters, especially that of the Rheum diet. In all diets treatments honey alleviated more the hepatopathy in CCl4 injected rats.
P o S ( E P SH E P 2 0 2 1 ) 6 3 4 Heavy Neutrinos at Future Linear e + e − Colliders

Neutrinos are probably the most mysterious particles of the Standard Model. The mass hierarchy and oscillations, as well as the nature of their antiparticles, are currently being studied in experiments around the world. Moreover, in many models of New Physics, baryon asymmetry or dark matter density in the universe are explained by introducing new species of neutrinos. Among others, heavy neutrinos of the Dirac or Majorana nature were proposed to solve problems persistent in the Standard Model. Such neutrinos with masses above the electroweak scale could be produced at future linear 4+4− colliders, such as the Compact LInear Collider (CLIC) or the International Linear Collider (ILC). We studied the possibility of observing production and decays of heavy neutrinos in the @@; final state at the ILC running at 500 GeV and 1 TeV and the CLIC running at 3 TeV. The analysis is based on theWhizard event generation and fast simulation of the detector responsewithDelphes. Dirac and Majorana neutrinos with masses from 200 GeV to 3.2 TeV were considered. Estimated limits on the production cross sections and on the neutrino-lepton coupling are compared with the current limits coming from the LHC running at 13 TeV, as well as the expected future limits from hadron colliders. Obtained results are stricter than other limit estimates published so far.
Overview of the main methods used to combine proteins with nanosystems: absorption, bioconjugation, and encapsulation

: The latest development of protein engineering allows the production of proteins having desired properties and large potential markets, but the clinical advances of therapeutical proteins are still limited by their fragility. Nanotechnology could provide optimal vectors able to protect from degradation therapeutical biomolecules such as proteins, enzymes or specific polypeptides. On the other hand, some proteins can be also used as active ligands to help nanoparticles loaded with chemotherapeutic or other drugs to reach particular sites in the body. The aim of this review is to provide an overall picture of the general aspects of the most successful approaches used to combine proteins with nanosystems. This combination is mainly achieved by absorption, bioconjugation and encapsulation. Interactions of nanoparticles with biomolecules and caveats related to protein denaturation are also pointed out. A clear understanding of nanoparticle-protein interactions could make possible the design of precise and versatile hybrid nanosystems. This could further allow control of their pharmacokinetics as well as activity, and safety.
A Reduced Swift-Hohenberg Style Model for Vegetation Patterns in Drylands

One in three people worldwide live in drylands, which are particularly vulnerable to desertification. In these ecosystems, where natural resources are limited, vegetation survives by organizing itself into patterns. The ecological factors governing these patterns were captured by Zelnik and others in a reaction-diffusion model consisting of two coupled equations for groundwater and biomass. In this paper, we leverage the strong water-biomass relation suggested by our simulations to derive a groundwater equation in terms of biomass and its spatial derivatives. Through this procedure we reduce Zelnik’s model to a single Swift-Hohenberg style biomass equation. Our model differs from the classical Swift-Hohenberg models in that nonlinear terms multiply second and higher spatial derivatives of biomass. This feature reflects that vegetation regulates its own water induced growth. The model presented shares the pattern forming properties of SwiftHohenberg models, making it mathematically tractable while conserving clear ecological meaning. Hence, our biomass equation allows for the extensive study of drylands’ resilience to changing climate conditions.
A Systematic Literature Review on Software Vulnerability Detection Using Machine Learning Approaches

— Software vulnerabilities are security flaws, defects, or weaknesses in software architecture, design, or implementation. With the explosion of open source code available for analysis, there is a chance to learn about bug patterns that can lead to security vulnerabilities to assist in the discovery of vulnerabilities. Recent advances in deep learning in natural language processing, speech recognition, and image processing have demonstrated the great potential of neural models to understand natural language. This has encouraged researchers in the cybersecurity sector and software engineering to utilize deep learning to learn and understand vulnerable code patterns and semantics that indicate vulnerable code properties. In this paper, we review and analyze the recent state-of-the-art research adopting machine learning and deep learning techniques to detect software vulnerabilities, aiming to investigate how to leverage neural techniques for learning and understanding code semantics to facilitate vulnerability detection. From this paper's results, 12 primary studies were found from the search processes. 7 out of them were published in IEEE, 2 were published in ACM, 2 were published in Springer and the rest of them were published in different conferences and journals. Most primary studies worked on NVD and SARD datasets, and others used open-source projects. Results show that machine learning and deep learning techniques give promising results in the automatic detection of vulnerabilities, but there are still some gaps in existing models that need to be addressed in future research.