Miracle-dz/UniFAR-FTUs huggingface dataset:
Forging Women's Substantive Representation: Intersectional Interests, Political Parity, and Pensions in Bolivia

Abstract Lacking tools to measure substantive representation, empirical research to date has determined women’s substantive representation by identifying “women’s interests” a priori, with little attention to differences across race, class, or other inequalities. To address this problem, I develop the concept of intersectional interests and a method for identifying these. Intersectional interests represent multiple perspectives and are forged through a process of political intersectionality that purposefully includes historically marginalized perspectives. These interests can be parsed into three types: expansionist, integrationist, and reconceived. Identification of intersectional interests requires, first, an inductive mapping of the differing women’s perspectives that exist in a specific context and then an examination of the political processes that lead to these new, redefined interests. I demonstrate the concept of intersectional interests and how to identify these in Bolivia, where I focus on the political process of forging reconceived intersectional interests in Bolivia’s political parity and pension reforms.
Air Vehicle Simulator: an Application for a Cable Array Robot

The development of autonomous air vehicles can be an expensive research pursuit. To alleviate some of the financial burden of this process, we have constructed a system consisting of four winches each attached to a central pod (the simulated air vehicle) via cables — a cable-array robot. The system is capable of precisely controlling the three dimensional position of the pod allowing effective testing of sensing and control strategies before experimentation on a free-flying vehicle. In this paper, we present a brief overview of the system and provide a practical control strategy for such a system.
Using Data Linkage to Investigate Inconsistent Reporting of Self-Harm and Questionnaire Non-Response

The objective of this study was to examine agreement between self-reported and medically recorded self-harm, and investigate whether the prevalence of self-harm differs in questionnaire responders vs. non-responders. A total of 4,810 participants from the Avon Longitudinal Study of Parents and Children (ALSPAC) completed a self-harm questionnaire at age 16 years. Data from consenting participants were linked to medical records (number available for analyses ranges from 205–3,027). The prevalence of self-harm leading to hospital admission was somewhat higher in questionnaire non-responders than responders (2.0 vs. 1.2%). Hospital attendance with self-harm was under-reported on the questionnaire. One third reported self-harm inconsistently over time; inconsistent reporters were less likely to have depression and fewer had self-harmed with suicidal intent. Self-harm prevalence estimates derived from self-report may be underestimated; more accurate figures may come from combining data from multiple sources.
Compensation in frequency domain for HPA nonlinearity in MIMO OFDM systems using MMSE receiver

This paper presents a compensating method based on Neural Network (NN) of Non-Linear (NL) distortion, which caused by High Power Amplifier (HPA) in Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO OFDM) systems. In this work, we present and we evaluate with simulation, the effect of nonlinearity on the system capacity and the performance of NN compensator in frequency domain accompanied with Minimum Mean Square Error (MMSE) receiver in a VBLAST (Vertical Bell Laboratories Layered Space-Time) MIMO OFDM systems running under a Rayleigh fading channel.
Multi-class Elastic Data Traac: Bandwidth Engineering via Asymptotic Approximations

Engineering rules for dimensioning bandwidth for multi-class elastic data tra c are derived for a single bottleneck link via asymptotic approximations for a closed-queueingnetwork model in heavy tra c. Elastic data applications adapt to available bandwidth via a feedback control such as the Transmission Control Protocol, and we categorized them into di erent classes based on the le sizes and times between transfers. A quasipotential function is found that provides the logarithmic asymptotics of the non-productform distribution for the total number of active connections. The minimum point of the quasi-potential provides the approximation for the normalized mean, and the variance of the normal approximation is inversely proportional to the second derivative of the quasipotential at the minimum point. The problem of dimensioning bandwidth is solved with the normal approximation. Via numerical studies we show the dependence of statistical gain on per-class parameters and show that the most stressful case is when the per-class load is balanced. Thus, if a network designer wanted to avoid the complexity of estimating per-class parameters, yet still have a conservative design, they could do so by considering a single overall class.
The Difficulties of Achieving Technology Transfer: Issues of Absorptive Capacity

This article aims to elucidate theoretically the problematic dealing with the constraints of the success of technology transfer process to developing countries through synthesizing the main theoretical approaches. Numerous and important are barriers to implementation. They are dependent on several factors ranging from initial level of development of the receiving economy, the nature of the imported technology, the market structure, the state of competition. However, despite the size of these barriers to entry, it is obvious that the knowledge imparted should be properly absorbed by the receiving economy. This implies the ability of firms to learn and master imported technologies- which requires prerequisites in terms of human capital, basic skills, capital outlay required for the activity of RD as well as economic and social fundamentals of the host country for the proper handling of knowledge. This set of prerequisites identifies absorptive capacity which all developing countries wishing to optimize the transfer of technology should bring.
Diagonal stability of uncertain interval systems

In this paper we consider the problem of diagonal stability of interval systems. We investigate the existence and evaluation of a common diagonal solution to the Lyapunov and Stein matrix inequalities for third order interval systems. We show that these problems are equivalent to minimax problem with polynomial goal functions. We suggest an interesting approach to solve the corresponding game problems. This approach uses the opennes property of the set of solutions. Examples show that the proposed method is effective and sufficiently fast.
Dynamic sink location update scope control mechanism for mobile sink Wireless Sensor Networks

Several recent works propose mobile sink based data gathering approaches to distribute energy consumption in Wireless Sensor Networks. However, mobility based algorithms require the sink to periodically update its location to the network to ensure multi-hop connectivity. This additional information increases the control traffic overhead, and thus energy consumption also increases. In this paper, we propose a distributive energy efficient sink location update mechanism for mobile sink WSNs, along with a preemptive buffering data collection technique. This sink location update mechanism combines MPR based broadcast [2] algorithm with a distributed local repair mechanism, whereby, sensor nodes dynamically control the scope of sink location update messages. In preemptive buffering mechanism, sink's neighbor nodes act as temporary data collection points, referred as roots, to prevent data loss when sink moves out of their vicinity. We show by simulations that our proposal effectively reduces the energy consumption and data losses of the network.
Mexican Hat Wavelet Kernel ELM for Multiclass Classification

Kernel extreme learning machine (KELM) is a novel feedforward neural network, which is widely used in classification problems. To some extent, it solves the existing problems of the invalid nodes and the large computational complexity in ELM. However, the traditional KELM classifier usually has a low test accuracy when it faces multiclass classification problems. In order to solve the above problem, a new classifier, Mexican Hat wavelet KELM classifier, is proposed in this paper. The proposed classifier successfully improves the training accuracy and reduces the training time in the multiclass classification problems. Moreover, the validity of the Mexican Hat wavelet as a kernel function of ELM is rigorously proved. Experimental results on different data sets show that the performance of the proposed classifier is significantly superior to the compared classifiers.
POPmine: Tracking Political Opinion on the Web

The automatic content analysis of mass media in the social sciences has become necessary and possible with the raise of social media and computational power. One particularly promising avenue of research concerns the use of opinion mining. We design and implement the POPmine system which is able to collect texts from web-based conventional media (news items in mainstream media sites) and social media (blogs and Twitter) and to process those texts, recognizing topics and political actors, analyzing relevant linguistic units, and generating indicators of both frequency of mention and polarity (positivity/negativity) of mentions to political actors across sources, types of sources, and across time.
How are Love, Loneliness, and Health Related?

Love and loneliness are not thought of as relating to each other, but under some circumstances, they do. This article reviews the concepts of intimacy and love. It explores what each of these concepts are, and the positive effects that love has on us psychologically, emotionally and physically. We describe what happens when love wanes, the impact it has on our romantic union, what are the causes for its disappearance and how loneliness may, thus, become an integral part of the relationship.
FORMULATION AND EVALUATION OF CHLORPHENERAMINE MALEATE BILAYERED BUCCAL TABLETS

The aim of the study was to prepare bilayered buccal tablets of Chlorpheneramine maleate using Carbopol 934 as primary polymer with secondary polymers like HPMC K4M and HPMC K15M by direct compression technology. The Preformulation study using FTIR and DSC spectroscopy revealed that there was no drug-polymer and polymerpolymer interaction. The tablets were evaluated for weight variation, thickness, hardness, friability, uniformity of drug content and surface pH concluded that all these parameters were in acceptable range of pharmacopoeial specification. The tablets were studied for swelling index, in vitro drug release and also the effect of Carbopol concentration on these parameters was studied. The buccal tablet showed good swelling of >80% up to 6 hrs maintaining the integrity of polymers. As the concentration of Carbopol 934 increased there was significantly increase in viscosity and swelling index. The optimized formulations F4 and F8 showed 88.7% and 91.2% release in 6 hr in vitro dissolution studies. The in vitro release obeyed First order kinetic with mechanism of release was erosion followed by non fickian diffusion. Hence Carbopol 934 and other polymers can be used to prepare bilayered buccal tablets of Chlorpheneramine maleate having prolonged therapeutic effect with enhanced bioavailability.
Stability of lipids on peritoneal dialysis in a patient with familial LCAT deficiency.

A 37-year-old man of northern European descent withfamilial lecithin:cholesterol acyltransferase (LCAT)deficiency started peritoneal dialysis (PD) one yearago, for end-stage renal failure.Proteinuria and an abnormal lipid profile were firstnoted in his early 20s. At the age of 29, he suffered analkali burn to his right eye. When assessed by anophthalmologist, diffuse lipid deposition in the corneaswith accentuated arcus and preservation of his visualacuity were noted. At the age of 30 (in 1999), thefollowing clinical findings were observed at nephrologyand lipid specialist appointments: blood pressure140/80, weight 112kg (BMI 33), and marked arcuscornealis bilaterally. He was anaemic (haemoglobin11.4g/dl), but had preserved renal function. Urinalysisrevealed proteinuria and microhaematuria. A 24-hurine collection showed nephrotic range proteinuria at6g/day. His total cholesterol (TC) was 270mg/dl(6.99mmol/l), triglycerides (TG) 946mg/dl(10.68mmol/l) and HDL-C 15mg/dl (0.38mmol/l). Familial LCAT deficiency (FLD) was confirmed byLCAT assay. Interestingly, he was found to be acompound heterozygote for two novel missense muta-tions in the LCAT gene, namely V28M in Exon 1 andA211T in Exon 5. The patient’s older brother hadreceived a renal transplant many years previously,experienced graft failure and died in his 40s. Of the twoyounger brothers, one had proteinuria and the otherrefused testing.Our patient was evaluated 5 years later (August2004) because of severe hypertension (180/100mmHg)and renal failure with serum creatinine 6.7mg/dl(593
Support Vector Machine Based on Conditional Value-at-Risk Minimization

A binary linear classification method, CGS method, was recently proposed by Gotoh and Takeda. The classification model was developed by introducing a risk measure known as the conditional value-at-risk (β-CVaR). CVaR minimization for the margin distribution leads to CGS problem, equivalent to ν-SVC of Schölkopf et al. in the convex case and Extended ν-SVC of Perez-Cruz et al. in the nonconvex case. The objective of this work is to investigate the properties of nonconvex CGS problem, or equivalently, Extended ν-SVC. We adopt a kernel function in the CGS problem by following SVC, and deal with its nonlinear kernel-based variants as β-SVC. We discuss theoretical aspects, mainly generalization performance, of β-SVC. The formula of generalization error includes β-CVaR or a related quantity, and the minimum β-CVaR obtained via β-SVC plays an important role to control generalization error. From a practical point of view, predictions made by β-SVC seem to be fairly reliable and accurate in comparison with those of ν-SVC. Indeed, β-SVC gave better estimations with parameter values β not permissible in ν-SVC, when several publicly available datasets were applied. We also derive a CVaR minimization problem for a regression problem, which is equivalent to ν-SVR of Schölkopf et al.
Exploring the Influences of Implementation Intention on Information Security Behaviors

ABSTACT Although information security knowledge is spreading and management tools are improving, information security incidents remain widely heard. Studies have investigated information security behaviors through motivational theories like the Theory of Planned Behavior. Since implementation intentions are considered as a behavior changing technique that may overcome goal deviations, this paper attempts to explore information security behaviors from the volitional perspective. Synthesizing the findings of twelve implementation intention studies, the proposed research model postulates that implementation intention intervention may affect information security behaviors. Besides, the moderating effects of two factors are included in the research model: difficulty of information security behaviors and strength of commitment to the goal intention. This research-in-progress paper describes the experimental methodology and provides instruments to validate the proposed model. The results are expected to establish the importance of action plans in improving information security behaviors.
Inhibitory Activity of Allelochemicals on Barnyardgrass (Echinochloa crus-galli L) Seed and Seedling Parameters

3 Abstract: Allelochemical compounds are known as a phenomenon for ecological control of weeds. in order to investigation of inhibitory potential of six allelochemicals on barnyardgrass (Echinochloa crus-galli L.) germination and seedling parameters an experiment was conducted in factorial arrangement based on completely randomized design. These allelochemicals consist of ferulic acid, m- coumaric acid, p-coumaric acid, vanillic acid, p-hydroxybanzoic acid and cinnamic acid. The results of analysis of variance showed highly significant differences among allelochemicals and concentrations (10 , 10 and 10 M). Allelochemicals showed high 34 5 inhibitory activity compared to control. Results indicated that, cinnamic acid had the highest inhibitory activity in terms of root and shoot length, total fresh weight and chlorophyll content (67.93, 25.41, 33.32 and 73.12% respectively). In term of total dry weight, germination rate and germination percentage the highest inhibitory activity was related to m-coumaric acid by 33.75, 55.68 and 41%, respectively. Root elongation was sensitive to allelopathic compounds rather than shoot elongation. Generally, the inhibitory effects of mentioned allelochemicals were increased with increasing of their concentrations from 10 to 10 M. 53
The practice of executive coaching to improve leadership capacity in academic deans at American higher education institutions

ABSTRACT The history and sociology of faculty career transitions to academic deanships is an intriguing phenomenon, given that the skill sets of accomplished scholars vary immensely from the duties and responsibilities of academic deans. On top of that, today’s academic deans continue to face particularly challenging leadership dilemmas. This exploratory, qualitative study sought to learn if executive coaching is an effective strategy to swiftly and ably prepare deans for the unique requirements of the position, as well as to equip them with and/or improve transformational leadership skills. Results were favourable towards coaching and showed associations in transformational leadership to be strongest in the component of intellectual stimulation. Deans also described improvements in empathetic behaviour, self-awareness and self-care – outcomes that suggest deans received value on a personal level and not just professionally. As perceived by the deans, coaches achieved these outcomes by the superior quality of their listening skills, their ability to offer useful perspectives, and by building trust. The information provided in this study might challenge institutions of higher education to consider executive coaching as a way to eliminate blind spots and address personal and organisational challenges that academic deans and other senior-level administrators encounter.
Optimal sensor fusion for distributed sensors subject to random delay and packet loss

In this paper we study optimal information fusion for sampled linear systems where the sensors are distributed and measurements are collected to central unit via a wireless network. Every sensor measurement is subject to random delay or might even be completely lost. We show that optimal sensor fusion consist in a time-varying Kalman filter with bufferized measurements. We also propose a suboptimal but computationally efficient fusion architecture based on a bank of static gains that can be optimally designed if packet delay statics are known. Finally, algorithms to check for the existence of stable estimators and to evaluate their error covariance are given and some special cases are analyzed.
Finding Extremal Complex Polytope Norms for Families of Real Matrices

In this paper we consider finite families ${\cal F}$ of real $n\! \times\! n$ matrices. In particular, we focus on the computation of the joint spectral radius $\rho({\cal F})$ via the detection of an extremal norm in the class of complex polytope norms, whose unit balls are balanced complex polytopes with a finite essential system of vertices. Such a finiteness property is very useful in view of the construction of efficient computational algorithms. More precisely, we improve the results obtained in our previous paper [N. Guglielmi, F. Wirth, and M. Zennaro, SIAM J. Matrix Anal. Appl. , 27 (2005), pp. 721-743], where we gave some conditions on the family ${\cal F}$ which are sufficient to guarantee the existence of an extremal complex polytope norm. Unfortunately, they exclude unnecessarily many interesting cases of real families. Therefore, here we relax the conditions given in our previous paper in order to provide a more satisfactory treatment of the real case.
Discovery of cross-reactive probes and polymorphic CpGs in the Illumina Infinium HumanMethylation450 microarray

DNA methylation, an important type of epigenetic modification in humans, participates in crucial cellular processes, such as embryonic development, X-inactivation, genomic imprinting and chromosome stability. Several platforms have been developed to study genome-wide DNA methylation. Many investigators in the field have chosen the Illumina Infinium HumanMethylation microarray for its ability to reliably assess DNA methylation following sodium bisulfite conversion. Here, we analyzed methylation profiles of 489 adult males and 357 adult females generated by the Infinium HumanMethylation450 microarray. Among the autosomal CpG sites that displayed significant methylation differences between the two sexes, we observed a significant enrichment of cross-reactive probes co-hybridizing to the sex chromosomes with more than 94% sequence identity. This could lead investigators to mistakenly infer the existence of significant autosomal sex-associated methylation. Using sequence identity cutoffs derived from the sex methylation analysis, we concluded that 6% of the array probes can potentially generate spurious signals because of co-hybridization to alternate genomic sequences highly homologous to the intended targets. Additionally, we discovered probes targeting polymorphic CpGs that overlapped SNPs. The methylation levels detected by these probes are simply the reflection of underlying genetic polymorphisms but could be misinterpreted as true signals. The existence of probes that are cross-reactive or of target polymorphic CpGs in the Illumina HumanMethylation microarrays can confound data obtained from such microarrays. Therefore, investigators should exercise caution when significant biological associations are found using these array platforms. A list of all cross-reactive probes and polymorphic CpGs identified by us are annotated in this paper.
Automatic semantic image classification and retrieval based on the weighted feature algorithm

Organizing images into meaningful (semantically) categories using low-level visual features is a challenging and important problem in content-based image retrieval. Clustering algorithms make it possible to represent visual features of images with finite symbols. However, there are two problems in most current image clustering algorithms. One is without considering the choice of the initial cluster centers which have a direct impact on the formation of final clusters, and the other is without considering the relevant features and assigning equal weights to these feature dimensions. According to the two problems we propose a weighted features algorithm. First, we use the labeled image samples to calculate the weight for each feature according to the feature degree of discrete. These weighted features have been used to calculate the initial cluster centers because they can well represent the cluster. Then, we use the weighted features(based on the different image data set) algorithm to discard the irrelevant features and reduce the feature dimensions through the whole clustering process. Experimental results and comparisons are given to illustrate the performance of the new algorithm.