Miracle-dz/UniFAR-FTUs huggingface dataset:
Modeling Analysis of Bullwhip Effect in Supply Chain based on Auto-regressive Analysis

With development of economic globalization, people have realized gradually that competition among enterprises has converted to competition among supply chain. Based on this condition, research on supply chain home and abroad is heating up gradually at present, while efficiency of the supply chain is the hot point in it. As one of the most notable phenomena influencing the supply chain, Bullwhip Effect has been paid great attention. It refers to the phenomenon that requirement information of end user on the supply chain goes along the supply chain and gradually expands upstream. Due to it causes a series of problems such as chaos in production and management, increase of inventory as well as occupation of capital, which has seriously influenced business efficiency of enterprises. Therefore, conducting systematic analysis and comprehensive research on it has important theoretical and practical significance.
Chivalry, Masculinity, and the Importance of Maleness to Judicial Decision Making

Social science research on gender in the legal system has largely focused on the woman as the "other. " This research has looked for ways in which women judge or are judged differently from the norm. The results of this line of research have been mixed. Male-centered theories of masculinity and chivalry provide promising tools to help researchers understand the contribution that maleness has on outcomes in the legal system. Immigration appeals provide an ideal test of these theories, which predict that male judges will be harder on male immigrants and easier on female litigants than will female judges. In this paper, we implement a research design that takes seriously both female-centric and male-centric explanations of decision outcomes. Using an original database of immigration appeals in the U.S. Courts of Appeal, we find evidence to support the research of maleness on its own terms. We find that elements of chivalry and masculinity theory both operate to frame the decisions made by male judges. The introduction of women on the panel of judges is associated with significant changes in the relative success of male and female petitioners, but not in a way that is consistent with theories of women judges as representatives. In addition to providing support for masculinity theory to explain the behavior of male judges, our data raise new questions about how females temper the reaction of mixed-gender panels toward male and female parties in court.
Learning without the Phase: Regularized PhaseMax Achieves Optimal Sample Complexity

The problem of estimating an unknown signal, $\mathbf x_0\in \mathbb R^n$, from a vector $\mathbf y\in \mathbb R^m$ consisting of $m$ magnitude-only measurements of the form $y_i=|\mathbf a_i\mathbf x_0|$, where $\mathbf a_i$'s are the rows of a known measurement matrix $\mathbf A$ is a classical problem known as phase retrieval. This problem arises when measuring the phase is costly or altogether infeasible. In many applications in machine learning, signal processing, statistics, etc., the underlying signal has certain structure (sparse, low-rank, finite alphabet, etc.), opening of up the possibility of recovering $\mathbf x_0$ from a number of measurements smaller than the ambient dimension, i.e., $m<n$. Ideally, one would like to recover the signal from a number of phaseless measurements that is on the order of the "degrees of freedom" of the structured $\mathbf x_0$. To this end, inspired by the PhaseMax algorithm, we formulate a convex optimization problem, where the objective function relies on an initial estimate of the true signal and also includes an additive regularization term to encourage structure. The new formulation is referred to as {\textbf{regularized PhaseMax}}. We analyze the performance of regularized PhaseMax to find the minimum number of phaseless measurements required for perfect signal recovery. The results are asymptotic and are in terms of the geometrical properties (such as the Gaussian width) of certain convex cones. When the measurement matrix has i.i. d. Gaussian entries, we show that our proposed method is indeed order-wise optimal, allowing perfect recovery from a number of phaseless measurements that is only a constant factor away from the degrees of freedom. We explicitly compute this constant factor, in terms of the quality of the initial estimate, by deriving the exact phase transition. The theory well matches empirical results from numerical simulations.
Output Decomposition and the Monetary Policy Transmission Mechanism in Bangladesh: A Vector Autoregressive Approach

This paper investigates the output composition of the monetary policy transmission mechanism for Bangladesh. Vector Auto-regression (VAR) models are used to analyse the data from 1973 to 2015. Although the central bank’s policy interest rate shock does not significantly affect the major compositions of the output, investment channel still works better than consumption. However, exchange rate shock effects more significantly on the real economy mainly through consumption than investment. This research, on one hand, demonstrates the potential channels of the monetary policy transmission mechanism. On the other hand, methodologically, it proposes a minor modified model that suite for economy of the developing countries like Bangladesh where the net export component of output is negative which creates some complexity in using the standard model used for developed countries like the USA, the EU, Japan and Australia.
Pollen tube taxol dependent structures co-assemble with neuronal HMW MAPs (MAP2)

Abstract Pollen tube microtubules (MTs) are as dynamic as animal MTs and they may interact with plasma membrane, endoplasmic reticulum, Golgi apparatus, mitocondria and a variety of cytoplasmic proteins. Bridges connecting MTs to each other and to membranes have been documented in pollen tubes by electron microscopy; however, the biochemical and molecular nature of these linkages is not known. In other cell types interaction between organelles and MTs require the participation of Microtubule-Associated Proteins (MAPs) that bridge the cytoskeleton to these organelles. Although biochemical documentation of such bridging MAPs in plant cells is lacking, it is reasonable to assume, by analogy with the animal systems, that specialized MAPs regulate MTs polymerization and dynamic in pollen tube. As a first step toward testing this hypothesis, the ability of Nicotiana tabacum pollen tube taxol-stabilized MTs to bind mammalian brain High Molecular Weight MAPs (HMWMAPs)(MAP2) was tested. This association analysis revealed the presence of mammalian MAP2-binding sites on pollen tube taxol-induced structures suggesting that the association presumably occurs at conserved domains on the tubulin molecules
ANALYSIS OF A VISCOUS TWO-FIELD GRADIENT DAMAGE MODEL PART II: PENALIZATION LIMIT

A viscous partial damage model is considered which features two damage variables coupled through a penalty term in the stored energy functional. While the well-posedness of the model was shown in a companion paper, this work analyses the behaviour of the model as the penalization parameter tends to infinity. It turns out that in the limit both damage variables coincide and satisfy a classical viscous damage model.
Adaptive Finite Element-Discrete Element Analysis for Microseismic Modelling of Hydraulic Fracture Propagation of Perforation in Horizontal Well considering Pre-Existing Fractures

Hydrofracturing technology of perforated horizontal well has been widely used to stimulate the tight hydrocarbon reservoirs for gas production. To predict the hydraulic fracture propagation, the microseismicity can be used to infer hydraulic fractures state; by the effective numerical methods, microseismic events can be addressed from changes of the computed stresses. In numerical models, due to the challenges in accurately representing the complex structure of naturally fractured reservoir, the interaction between hydraulic and pre-existing fractures has not yet been considered and handled satisfactorily. To overcome these challenges, the adaptive finite element-discrete element method is used to refine mesh, effectively identify the fractures propagation, and investigate microseismic modelling. Numerical models are composed of hydraulic fractures, pre-existing fractures, and microscale pores, and the seepage analysis based on the Darcy’s law is used to determine fluid flow; then moment tensors in microseismicity are computed based on the computed stresses. Unfractured and naturally fractured models are compared to assess the influences of pre-existing fractures on hydrofracturing. The damaged and contact slip events were detected by the magnitudes, -values, Hudson source type plots, and focal spheres.
Creating Cultures of Ecological Sustainability

1. Prefatory Remarks Thank you very much for inviting me to speak at your conference. I find it instructive that graduate students in Asian studies should identify the topic of sustainability as a key focus. it’s instructive because very few of you have probably ever taken a course entitled “sustainability in asian studies” yet it is a theme that rightly unites scholars of Asia who are concerned not simply about scholarship for the sake of scholarship but as a practical and ethical response to the field. It demonstrates a sense of responsibility and engagement with the world that I think stands in the very best traditions of academic work, and is something that I encourage all of you to pursue as best you may in your academic careers. All too often graduate school seems to focus on establishing distinctions from the “ordinary world:” we learn the languages of classical civilizations, mastering the abstruse vocabularies of fashionable french theorists, getting yourself published in journals that no one ever reads, and learning to sneer contemptuously at your undergrad friends who went into business and are now earning six figures. In a way this is hardly surprising given than our higher education system inherited the values of medieval monks who cherished being recondite as much as erudite.
Molecularly Imprinted Chitin Nanofiber Membranes: Multi-Stage Cascade Membrane Separation within the Membrane

Molecularly imprinted nanofiber membranes were fabricated from chitin and print molecule of phenylalanine derivative by simultaneously applying an alternative molecular imprinting and an electrospinning. The D-enantiomer imprinted nanofiber membrane preferentially incorporated the D-enantiomer and selectively transported D-enantiomer and vice versa . The permselectivity was exponentially increased with the increase in the membrane thickness, implying that multi-stage cascade membrane separation was carried out within the nanofiber membrane. The present study led to the conclusion that a molecularly imprinted nanofiber membrane is one of suitable membrane forms for the separation membrane with relatively high flux and permselectivity.
To what extent should we lower HbA 1 c in diabetic subjects ?

Current recommendations regarding glycemic control suggest that HbA1c should be lower than 6.5%. This is supported by data regarding microvascular disease, namely retinopathy rather than nephropathy. The question is not completely solved regarding cardiovascular diseases, where a strategy of very low HbA1c (“the lower the better”) is expected to be effective. Some ongoing studies will help to answer these unsolved questions. © 2008 Elsevier Masson SAS. All rights reserved.
Degradation of acidic Orange G dye using UV-H2O2 in batch photoreactor

Degradation of Orange G dye has been investigated using UV irradiation with hydrogen peroxide (H2O2) in a batch photoreactor. UV irradiation and H2O2 resulted in significant photodegradation of the dye although the effect individual reaction was very little. The degradation was studied to elucidate the effect of various process parameters such as pH, concentration of dye, dose of H2O2, TiO2 and light intensity/light source with reflecting or non reflecting surface of photoreactor. Results showed the efficient degradation of Orange G for typical process conditions. Keywords: Orange G, UV/H2O2, photoreactor, degradation, process parameters.
A Machine-learning based Technique to Analyze the Dynamic Information for Visual Perception of Consonants

This paper proposes a machine-learning based technique to investigate the significance of the dynamic information for visual perception of consonants. The visual speech information can be described using static (facial appearance) or dynamic (movement) features. The aim of this research is to determine the saliency of dynamic information represented by the lower facial movement for visual speech perception. The experimental results indicate that the facial movement is distinguishable for nine English consonants with a success rate of 85% using the proposed approach. The results suggest that time-varying information of visual speech contained in lower facial movements is useful for machine recognition of consonants and may be an essential cue for human perception of visual speech.
The antimicrobial effects of green tea and lemon juice on Escherichia coli isolated from patients with urinary tract infection in holy Karbala city

Urinary tract infections (UTIs) are the second most common type of infection found in any organ system, and the most common type of nosocomial infection. The strains of Escherichia coli that infect the urinary tract are categorized as uropathogenic E. coli. The antimicrobial agents that have traditionally been used to treat UTIs (? -lactams, fluoroquinolones, trimethoprim
A Frame of Intrusion Detection Learning System Utilizing Radial Basis Function

The process of monitoring the events that occur in a computer system or network and analyzing them for signs of intrusion is known as Intrusion Detection System (IDS). Detection ability of most of the IDS are limited to known attack patterns; hence new signatures for novel attacks can be troublesome, time consuming and has high false alarm rate. To achieve this, system was trained and tested with known and unknown patterns with the help of Radial Basis Functions (RBF). KDD 99 IDE (Knowledge Discovery in Databases Intrusion Detection Evaluation) data set was used for training and testing. The IDS is supposed to distinguish normal traffic from intrusions and to classify them into four classes: DoS, probe, R2L and U2R. The dataset is quite unbalanced, with 79% of the traffic belonging to the DoS category, 19% is normal traffic and less than 2% constitute the other three categories. The usefulness of the data set used for experimental evaluation has been demonstrated. The different metrics available for the evaluation of IDS were also introduced. Experimental evaluations were shown that the proposed methods were having the capacity of detecting a significant percentage of rate and new attacks.
Estimation of Asphalt Pavement Surfaces Using Image Analysis Technique

— Asphalt concrete pavements gradually lose their skid resistance causing safety problems especially under wet conditions and high driving speeds. In order to enact the actual field polishing and wearing process of asphalt pavement surfaces in a laboratory setting, several laboratory-scale accelerated polishing devices were developed by different agencies. To mimic the actual process, friction and texture measuring devices are needed to quantify surface deterioration at different polishing intervals that reflect different stages of the pavement life. The test could still be considered lengthy and to some extent labor-intensive. Therefore, there is a need to come up with another method that can assist in investigating the bituminous pavement surface characteristics in a practical and time-efficient test procedure. The purpose of this paper is to utilize a well-developed image analysis technique to characterize asphalt pavement surfaces without the need to use conventional friction and texture measuring devices in an attempt to shorten and simplify the polishing procedure in the lab. Promising findings showed the possibility of using image analysis in lieu of the labor-sensitive-variable-in-nature friction and texture measurements. It was found that the exposed aggregate surface area of asphalt specimens made from limestone and gravel aggregates produced solid evidence of the validity of this method in describing asphalt pavement surfaces. Image analysis results correlated well with the British Pendulum Numbers (BPN), Polish Values (PV) and Mean Texture Depth (MTD) values.
Agama lizard: A potential biomarker of environmental heavy metal pollution assessment

In this study, the suitability of Agama lizard as a biomarker in assessing environmental pollution levels of arsenium (As), barium (Ba), cadmium (Cd), copper (Cu), manganese (Mn), lead (Pb) and zinc (Zn) was investigated. Samples of top soil and agama lizards were taken from five sites within a university community in Nigeria for the study. Soil samples, livers and kidneys from the lizards were subjected to wet acid digestion and levels of heavy metals in the digested samples were determined using an atomic absorption spectrophotometer (AAS). Results of the study showed that the levels of the metals ranged from Cd, 20.4 ± 2.6 ig/g to Zn, 978.6 ± 2.2 ig/g in soil; Cd, not detected to Zn, 42.2 ± 0.3 ig/g in liver; As and Ba, not detected to 47.6 ± 1.0 ig/g Zn in kidney. The inter matrices correlation coefficient values obtained for the heavy metals showed that the kidney of lizards would be more relevant in assessing soil levels of such heavy metals as As, Ba, Cd, Mn and Pb among others. Key words : Agama lizard, environmental pollution, soil, heavy metals, liver, kidney.
College students’ engagement in e-tutoring children in remote areas

To bridge the digital divide and learning gap among children in remote areas, an online tutoring service has been initiated for after-school learning in remote schools. College students were recruited for the role of teaching and supporting remote learners through online tutoring. This research aimed to study college students’ involvement in e-tutoring children in remote areas. Two major issues were explored as follows: (1) how was the online tutoring teamwork organised and (2) what were the factors that influence students’ involvement in the online tutoring tasks? Findings revealed college students’ engagement in the e-tutoring task include the following: motive to serve, competence building, responsibility and self-discipline for serving, development of positive values from serving.
Genetic Polymorphism of Glutathione-S-Transferase Gene (GSTP1) in Type 2 Diabetes Mellitus Patients in Basra Province/Iraq

Glutathione S-transferases (GSTs) are enzymes that included, in a wide range of detoxifying reactions by conjugation of glutathione, to electrophilic material. Polymorphisms in the genes that are responsible for GSTs affect, the function of the GSTs. GSTs play an active role in protection of cell against oxidative stress mechanism. Polymorphisms of GSTP1 at codon 105 amino acids forms GSTP1 important site for bind of hydrophobic electrophiles and the substitution of Ile/Val affect substrate specially catalytic activity of the enzyme and may correlate with reach to different diseases in human like diabetes mellitus type2 disease. Correlation between these polymorphisms and changes in the parameters file of diabetic patients has also been found, therefore, the results vary considerably among the studies. The polymerase chain reaction-restriction fragment length polymorphism was used to study GSTP1genetic polymorphism in 60 T2DM patients and 40 healthy individuals. Our results showed that presence of the GSTP1 heterozygous mutant allele Ile/Val was more common in subjects with T2DM than in the control group (35.00% and 17.50. 00%, respectively. Among patients there is an association between GSTP1and the risk of T2MD, both genotypes Ile/Val and Val/Val were more prevalent which result in 2.90 and 2.58 respectively risk towards T2DM . According to Hardy–Weinberg principle there was no deviation appears in the distribution of GSTP1 Alleles. GSTP1 genotypes do not have an effect on blood lipids after infection with diabetes mellitus.
Predictors of hypertension in Oman

Background: According to the Oman World Health Survey in 2008, the prevalence of hypertension in Oman is about 40%. Hypertension is associated with old people, male gender, smoker and impaired glucose tolerance. The objective of the study was to find out the important predictors of hypertension in Oman.Methods: A cross sectional study in Omani adults more than 18 years of age was conducted. Blood pressure was measured and participants were classified as having hypertension. Height and weight was measured and body mass index was used to classify obesity by WHO guidelines. Multiple logistic regression was used to find the predictors of hypertension.Results: Increase in age and body mass index were found to be important covariates of hypertension. People in the age group of 30 to 50 years were at high risk of hypertension (OR 1.6, p<0.05); likelihood increased to three times in more than 50 years age group (p<0.01) in univariate analysis. Overweight had almost 2 times (p<0.05) and obese had five times (p<0.01) more likelihood of hypertension than normal weight people. People with less education had more likelihood of hypertension. Smokers (OR 2.9, p<0.01) and males (OR 1.5, p<0.05) were at a higher risk of hypertension than non-smokers and females in multivariate analysis. Percentage accuracy of classification was 67.4%. Conclusions: Age more than 50 years, male gender, BMI more than 30 and smoking were important predictors of hypertension in the study population.
Hyperglycemia Increases Mitochondrial Protein Expression in the Absence of Oxidative Stress

Oxidative Stress By Francisco E. Vasquez Submitted to the department of Pharmacology & Toxicology and the Faculty of the Graduate School of the University of Kansas in partial fulfillment of the requirements for the degree of Master of Science. Thesis Committee: __________________________________________________________________ Rick T. Dobrowsky, Ph.D, Professor and Chair of the Thesis Committee __________________________________________________________________ Jackob Moskovitz, Ph.D, Assistant Professor and Thesis Committee Member __________________________________________________________________ Jeff Staudinger, Ph.D,Associate Professor and Thesis Committee Member
Self-consistent evolution of accreting low-mass stars and brown dwarfs

We present self-consistent calculations coupling numerical hydrodynamics simulations of collapsing pre-stellar cores and stellar evolution models of accreting objects. We analyse the main impact of consistent accretion history on the evolution and lithium depletion of young low-mass stars and brown dwarfs. These consistent models confirm the generation of a luminosity spread in Herzsprung-Russell diagrams at ages $\sim$ 1-10 Myr. They also confirm that early accretion can produce objects with abnormal Li depletion, as found in a previous study that was based on arbitrary accretion rates. The results strengthen that objects with anomalously high level of Li depletion in young clusters should be extremely rare. We also find that early phases of burst accretion can produce coeval models of similar mass with a range of different Li surface abundances, and in particular with Li-excess compared to the predictions of non-accreting counterparts. This result is due to a subtle competition between the effect of burst accretion and its impact on the central stellar temperature, the growth of the stellar radiative core and the accretion of fresh Li from the accretion disk. Only consistent models could reveal such a subtle combination of effects. This new result could explain the recent, puzzling observations of Li-excess of fast rotators in the young cluster NGC 2264. Present self-consistent accreting models are available in electronic form.