Miracle-dz/UniFAR-FTUs huggingface dataset:
Gender at work in economic life

Part 1 Introduction: How Gender Works, in the Practice of Theory and Other Social Processes Part 2 Part I: Concepts of Gender Within Economic Change Part 3 Chapter 1: Archaeology and the Gender Without History Part 4 Chapter 2: Rain and Cattle: Gendered Structures and Political Economy in Precolonial Pare, Tanzania Part 5 Chapter 3: Woman-headed Households in Agrarian Societies: Not Just a Passing Phase Part 6 Part II: Entrepreneurs as Women Part 7 Chapter 4: Female Entrepreneurship in the Caribbean: A Multisite, Pilot Investigation of Gender and Work Part 8 Chapter 5: Women, Modernity, and the Global Economy: Negotiating Gender and Work in Ifugao, Upland Philippines Part 9 Chapter 6: Between Family and Market: Women and thew New Silk Road in Post-Soviet Kazakstan Part 10 Part III: Love and Entitlements Part 11 Chapter 7: Neoliberalism and Newar Economics of Practice: Gender and the Politics of Consciousness in a Nepalese Merchant Community Part 12 Chapter 8: Why Would She Fight Her Family? : Indian Women's Negotiations of Discourses of Inheritance Part 13 Chapter 9: Decision Making and Flows of Income and Expenses Among Households with Factory-Employed Members Part 14 Part IV: Migration Engendered Part 15 Chapter 10: Male Wealth and Claims to Motherhood: Gendered Resource Eaccess and Intergenerational Relations in the Gwembe Valley, Zambia Part 16 Chapter 11: Age, Masculinity and Migration: Gender and Wage Labor Among Samburu Pastoralists in Northern Kenya Part 17 Chapter 12: Women in a Brazilian Agricultural Frontier
Modeling Active Virtual Machines on IaaS Clouds Using an M/G/m/m+K Queue

This paper develops a novel approximate analytical model to evaluate the performance of active virtual machines in IaaS clouds using an M/G/m/m+K queue. The proposed model, combined with the transform-based analytical approach, enables the computation of the probability distribution of the number of jobs in the system and subsequently a set of performance measures, including the mean number of jobs in the system, the mean response time, the probability of immediate service, and the blocking probability. Compared to the existing Markov models of cloud data centers, our approach can reflect the system behavior more accurately even when the service-time distribution has a large coefficient of variation (> 1.5) in a medium-sized IaaS cloud. Numerical results obtained from the proposed analytical model are verified through extensive simulations under various system parameter settings, and compared with the results from existing models.
Design of Self-Directed E-Learning Material Recommendation System with On-Line Evaluation

Along with explosive growth of the IT and Internet, they have led much development on education, such as e-learning, distance learning and on-line learning etc., which provide learners with another better alternative for learning at anytime and anywhere. Practically, the essence of the Information technology application on education is that Learning is the essential and the technology is the auxiliary. That is, on education, the information technology just acts as a method or a tool in the process of learning. As the IT gets more mature, the e-learning becomes more popular. If the e-learning can effectively exploit the techniques of Data-mining, it will make user-learning more efficient. Thus, in this project, we not only continue the e-learning activity-based material recommendation system construction, but also design the self-evaluation system supporting with semantic search for an adaptive learning platform. In this paper, we mainly propose the ontology-based self-evaluation system with material recommendation system for providing a better learning platform. In the item bank construction, we will invite some domain experts to assist the collection and creation of examination questions and classification. We believe such self-directed learning system will be good for the improvement on the efficiency of the e-learning and will be beneficial to get more achievements on learning for learners.
Cognitive dysfunction in children with brain tumors at diagnosis

Survivors of brain tumors have a high risk for a wide range of cognitive problems. These dysfunctions are caused by the lesion itself and its surgical removal, as well as subsequent treatments (chemo‐ and/or radiation therapy). Multiple recent studies have indicated that children with brain tumors (BT) might already exhibit cognitive problems at diagnosis, i.e., before the start of any medical treatment. The aim of the present study was to investigate the baseline neuropsychological profile in children with BT compared to children with an oncological diagnosis not involving the central nervous system (CNS).
A PHONEMIC RESTORATION APPROACH FOR AUTOMATIC SPEECH RECOGNITION WITH HIGHLY NONSTATIONARY BACKGROUND NOISE

Automatic speech recognition for human computer interaction in vehicular environments is a challenging task due to existence of highly nonstationary background noise. At moderate signal-to-noise ratio ranging between 0 and 20 dB, word error rate can be dramatically reduced using methods such as speech enhancement and robust feature extraction. When a burst of nonstationary noise overlaps speech duration, however, the segmental signal-to-noise ratio often drops well below 0 dB making conventional methods almost ineffective. For this scenario, we propose a method exploiting the phonemic restoration effect to reduce word error rate. In this method we use a microphone array to determine speech duration corrupted by presence of nonstationary noise and mark features from that duration as unreliable. Then we selectively discard them, or reconstruct underlying speech features by examining adjacent features marked as reliable. Experimental results on the AVICAR database show that our proposed method reduce word error rate in a statistically meaningful sense.
Analysis of Power Magnetic Components With Nonlinear Static Hysteresis: Proper Orthogonal Decomposition and Model Reduction

We applied the proper orthogonal decomposition (POD) method to extract reduced-order models to efficiently solve nonlinear electromagnetic problems governed by Maxwell's equations with nonlinear hysteresis at low frequency (10 kHz), called static hysteresis, discretized by a finite-element method. We used a new domain-wall-motion hysteresis model for Power MAgnetic Components (POMACs) in the finite-element potential formulation via an efficient implicit-inverse model calculation. We propose a rational method for the selection of snapshots employed in the POD, used in conjunction with a fixed-point method for the solution of nonlinear POMAC problems. The reduced simulation time and great flexibility of the reduced-order models, as applied to nonlinear POMAC systems, suggest that the procedure can be applied to other electromagnetic problems with nonlinear hysteresis
An 8-bit 20 MS/s successive approximation register analog-to-digital converter for wireless intelligent control and information processing

In this paper, a 1.8-V 10-bit 20MS/s successive approximation register (SAR) analog-to-digital converter (ADC) implemented in TSMC 0.18-um CMOS process is presented for wireless intelligent control and information processing. By applying low input capacitance that reduces driving difficulty of the ADC, the proposed SAR ADC achieves less sampling time. Also, asynchronous control logic is used which doesn't need an external high frequency clock to drive ADC. Measured results show that at the supply voltage of 1.8 V and sampling rate of 20 MS/s, the proposed SAR ADC achieves a spurious-free dynamic range (SFDR) of 55.1 dB, a signal-to-noise and distortion ratio (SNDR) of 44.5 dB, an effective number of bits (ENOB) of 7.1 bits, a differential nonlinearity (DNL) of 0.81 LSB, an integral nonlinearity (INL) of 1.24 LSB and a power consumption of 588 μ\Υ. The overall chip area is only 0.53 mm2 with a small ADC core area of 0.73 mm2.
Genome Urbanization: Gene localization, spacing and direction of transcription in S. cerevisiae are constrained by DNA topological tension.

Background: The eukaryotic genome evolves under the dual constraint of maintaining co-ordinated gene transcription and performing effective DNA replication and cell division, the coupling of which brings about inevitable tension in DNA topology. This is resolved and in some cases even harnessed by the genome through the function of DNA topoisomerases, as has been shown in the concurrent transcriptional activation and suppression of genes upon transient deactivation of topoisomerase II and distinct areas of the genome are expected to be differentially affected by DNA topological constraints. The scope of this work is to identify positional and structural preferences in the distribution of genes, relative to their response to DNA topological stress. Results: By analyzing a genome wide run-on experiment upon thermal inactivation of topo II in S. cerevisiae we were able to define 117 gene clusters of concerted response (either positive or negative) to topological stress. A comprehensive analysis of these "topologically-constrained" gene clusters revealed pronounced preferences regarding their functional, regulatory and structural attributes. Our findings point towards a particular genome compartmentalization, according to which genes that negatively respond to topological stress, are positioned in gene-dense pericentromeric regions, are more conserved and associated to essential functions, while up-regulated gene clusters are preferentially located in the gene-sparse nuclear periphery, associated with secondary functions and under complex regulatory control. Conclusions: This multi-faceted "division of labour" is much resembling a "genome urbanization" process with a core of essential genes occupying a compact genomic "old town", whereas more recently acquired, condition-specific genes are located in a more spacious "suburban" genomic periphery.
Efficient information lookup for the Internet of Things

The Internet of Things is an emerging paradigm that allows the association of information with objects. The information about an object is stored in databases, distributed around the globe, maintained by various stakeholders that participate in the object's supply chain. A Discovery Service (DS) is responsible for collecting all these database URIs and feeding them to clients that query about an object. DSs are usually centralized and are designed to effectively aggregate as many information sources as possible, rather than trying to respond optimally to unforeseen user queries. In this paper we propose a novel, Information-Centric Networking (ICN) inspired, architecture that eliminates the need for a separate DS, enabling at the same time multi-ownership and flexible management of information that is associated with an object. In our ICN approach, information about an object is organized in scopes. Each scope has its own access control rules allowing easy control of information dissemination. Moreover scopes can be hierarchically organized, creating complex access structures that can reflect business relationships. In our architecture companies provide information about an object to the appropriate scopes, but they never lose control of this information. To access information associated with an object,a user queries the scope that corresponds to the desired context, which will forward the query to a service that will respond with the appropriate data. The query will not reveal any extra information, not authorized to be retrieved.
A New Approach to Image Copy Detection Based on Extended Feature Sets

Conventional image copy detection research concentrates on finding features that are robust enough to resist various kinds of image attacks. However, finding a globally effective feature is difficult and, in many cases, domain dependent. Instead of simply extracting features from copyrighted images directly, we propose a new framework called the extended feature set for detecting copies of images. In our approach, virtual prior attacks are applied to copyrighted images to generate novel features, which serve as training data. The copy-detection problem can be solved by learning classifiers from the training data, thus, generated. Our approach can be integrated into existing copy detectors to further improve their performance. Experiment results demonstrate that the proposed approach can substantially enhance the accuracy of copy detection.
Iterated Rician Denoising

We propose a novel variational method for Magnetic Resonance Image denoising which is based on the modelling of Rician noise. In the context of MAP estimation the resulting energy functional is minimized embedding its Euler-Lagrange equation in an iterative regularization scheme. The algorithm is tested with synthetic MR images and the results show the effectiveness of the method which provides high contrast denoised images.
Feature vectors of the cruciate ligaments of the knee joint

The most important and primary aims of this article are two elements. The first one is a presentation of the feature vectors of the anterior and posterior cruciate ligaments of the knee joint and the second element is a discussion on the choice of the most effective features. In order to build the feature vectors, the extraction of the cruciate ligaments structures from the MRI images of the knee joint was necessary. This operation has been made on the basis of the following fuzzy methods: fuzzy C-means algorithm with median modification (in order to find a region of interest including cruciate ligaments), and fuzzy connectedness (in order to extract the cruciate ligaments). The presented methodology has been tested on 74 clinical T1-weighted MRI slices of the knee joint. On the basis of the described methodology a software application has been built. This software application is dedicated for the anterior and posterior cruciate ligaments diagnostics and it seems to be a very helpful for the orthopedists.
The Impact of Strategies on the Stylized Facts in the FX Market

One of the most critical design issues that developers face in electronic markets is that of the agents’ trading strategies. In this paper, we aim to examine the impact of trading strategies on the high-frequency Foreign Exchange market. In particular, our goal is to explore the emergence of the stylized facts (statistical properties) in the trading activity when the market is populated with agents with three different strategies: a variation of the zero-intelligence with a constraint (ZI-CV) strategy; the zero-intelligence directional-change event (ZI-DCT0) strategy; and a genetic programming-based (GP) strategy. A series of experiments were conducted in an existing agent-based FX market with these three strategies and the results were compared against those of a high-frequency dataset from the FX market. Our results show that the ZI-DCT0 agents best reproduce and explain the properties and phenomena observed in the FX market real transactions data. Our study suggests that the observed properties of the trading activity in the FX market could be the result of introducing a threshold which triggers the agents to respond to fixed periodic patterns in the price time series.
Phase and Jitter Noise analysis of Phase Locks Loop (PLL) as Frequency Synthesiser

In this paper, we are evaluating the performance of the phase lock loop in the presence of phase noise and jitter noise. We are analysing the performance of PLL in one application of signal processing as frequency synthesiser. All the components of PLL contribute to the noise of the system. Two type of noise are presented that affect the performance of the system that are phase noise and jitter noise. Firstly, the Phase noise is generally used for representing short term random frequency variations of a signal. Non linear oscillators naturally produce high phase noise. Secondly, Jitter is generally used to refer to the time variation of a periodic signal in relation to the clock. The phase and jitter are the critical performance parameter to analysis the performance of the PLL. Simulation Result reveals that the performance of the PLL system is affected more by jitter noise compared to that of phase noise. Extensive simulation result is presented to demonstrate the effectiveness of the proposed techniques.
Vehicle tracking in low hue contrast based on CAMShift and background subtraction

This paper proposes a method to track vehicle in highway using CAMShift-based method. The Continuously Adaptive Mean Shift (CAMShift) is a well-known algorithm in object tracking. However, the ordinary CAMShift works fairly well only for tracking object that can identify by hue, when the difference between object color and background is large. This is not the case in vehicle tracking. The objective of our proposed method is to be able to track vehicles in highway when the hue contrast is low. We incorporate in CAMShift an adaptive background subtraction to help in object localization when lost tracking occurs. The experimental result illustrates a significant improvement in tracking accuracy.
Calibration of different interest rate models for a good fit of yield curves

One of the first mathematical models to describe the interest rate over time was the Vasicek model (1978). Soon after, the Cox Ingersoll Ross (CIR) model (1985) was introduced. The Vasicek model and the CIR model belong to the family of short interest rate models. Through transformation these models can be applied to compute the interest rate values. Classical techniques such as the Maximum Likelihood Estimate (MLE) and Least Squares Method (LSM) are used to estimate the parameters in the short rate model from the historical data. One must understand that the short rate values cannot be observed from the financial market. However, we can observe the bond prices and from these we can compute the interest rates values. It turns out that when the short interest rate values are not known, MLE and LSM cannot be used to estimate the parameters in the CIR model. Rabobank encountered this problem. My assignment was to estimate the parameters in the CIR model using the historical data collected by Rabobank. When doing calibration using MLE or LSM for the Vasicek model, it turns out that the drift parameters are estimated with very high bias. Rabobank uses the Long Term Quantile (LTQ) method, which is expected to have no bias. My assignment was to test this claim and see whether there is a bias and if so I had to eliminate this bias.
High Density Lipoprotein Cholesterol Increasing Therapy: The Unmet Cardiovascular Need

Despite aggressive strategies are now available to reduce LDL-cholesterol, the risk of cardiovascular events in patients with coronary artery disease remains substantial. Several preclinical and clinical studies have shown that drug therapy ultimately leads to a regression of the angiographic lesions but also results in a reduction in cardiovascular events. The dramatic failure of clinical trials evaluating the cholesterol ester transfer protein (CEPT) inhibitors, torcetrapib and dalcetrapib, has led to considerable doubt about the value of the current strategy to raise high-density lipoprotein cholesterol (HDL-C) as a treatment for cardiovascular disease. These clinical results, as well as animal studies, have revealed the complexity of HDL metabolism, assessing a more important role of functional quality compared to circulating quantity of HDL. As a result, HDL-based therapeutic interventions that maintain or enhance HDL functionality, such as improving its main property, the reverse cholesterol transport, require closer investigation. In this review, we will discuss HDL metabolism and function, clinical-trial data available for HDL-raising agents, and potential strategies for future HDL-based therapies.
A fully integrated 96GHz 2×2 focal-plane array with On-Chip antenna

A fully integrated 96GHz 2×2 focal-plane array (FPA) direct conversion imager in 0. 18µm SiGe BiCMOS (f<inf>T</inf>/ƒ<inf>max</inf>=200/180GHz) employing four integrated antennas with Dicke switches and LO generation/distribution is presented. The PLL plus tripler achieves a locking range of 92.67–98.2GHz and phase noise of −93dBc/Hz at 96GHz measured at 1MHz offset. The 3.5×3mm<sup>2</sup> chip achieves an average responsivity and NEP of 285MV/W and 8.1fW/√Hz, respectively, across 86–106GHz band and an NETD of 0.48K. The chip consumes 695mW from 1.8V/2.5V supplies.
Credibility Modeling via Spline Nonparametrie Regression

Credibility modeling is a rate making process which allows actuaries to adjust future premiums according to the past experience of a risk or group of risks. Current methods in credibility theory often rely on parametric models. Blihlmann (1967) developed an approach based on the best linear approximation, which leads to an estimator that is a linear combination of current observations and past records. During the last decade, the existence of high speed computers and statistical software packages allowed the introduction of more sophisticated methodologies. Some of these techniques are based on Markov Chain Monte Carlo (MCMC) approach to Bayesian inference, which requires extensive computations. However, very few of these methods made use of the additional covariate information related to the risk, or group of risks; and at the same time account for the correlated structure in the data. In this paper, we consider a Bayesian nonparametric approach to the problem of risk modeling. The model incorporates past and present observations related to the risk, as well as relevant covariate information. The Bayesian modeling is carried out by sampling from a multivariate Gaussian prior, where the covariance structure is based on a thin-plate spline (Wahba, 1990). The model uses MCMC technique to compute the predictive distribution of the future claims based on the available data. Extensive data analysis is conducted to study the properties of the proposed estimator, and compare against the existing techniques.
The Human Sodium-Glucose Cotransporter (hSGLT1) Is a Disulfide-Bridged Homodimer with a Re-Entrant C-Terminal Loop

Na-coupled cotransporters are proteins that use the trans-membrane electrochemical gradient of Na to activate the transport of a second solute. The sodium-glucose cotransporter 1 (SGLT1) constitutes a well-studied prototype of this transport mechanism but essential molecular characteristics, namely its quaternary structure and the exact arrangement of the C-terminal transmembrane segments, are still debated. After expression in Xenopus oocytes, human SGLT1 molecules (hSGLT1) were labelled on an externally accessible cysteine residue with a thiol-reactive fluorophore (tetramethylrhodamine-C5-maleimide, TMR). Addition of dipicrylamine (DPA, a negatively-charged amphiphatic fluorescence “quencher”) to the fluorescently-labelled oocytes is used to quench the fluorescence originating from hSGLT1 in a voltage-dependent manner. Using this arrangement with a cysteine residue introduced at position 624 in the loop between transmembrane segments 12 and 13, the voltage-dependent fluorescence signal clearly indicated that this portion of the 12–13 loop is located on the external side of the membrane. As the 12–13 loop begins on the intracellular side of the membrane, this suggests that the 12–13 loop is re-entrant. Using fluorescence resonance energy transfer (FRET), we observed that different hSGLT1 molecules are within molecular distances from each other suggesting a multimeric complex arrangement. In agreement with this conclusion, a western blot analysis showed that hSGLT1 migrates as either a monomer or a dimer in reducing and non-reducing conditions, respectively. A systematic mutational study of endogenous cysteine residues in hSGLT1 showed that a disulfide bridge is formed between the C355 residues of two neighbouring hSGLT1 molecules. It is concluded that, 1) hSGLT1 is expressed as a disulfide bridged homodimer via C355 and that 2) a portion of the intracellular 12–13 loop is re-entrant and readily accessible from the extracellular milieu.