Miracle-dz/UniFAR-FTUs huggingface dataset:
Gender differences in growth of school-aged children with schistosomiasis and geohelminth infection.

Light or moderate intensity infection with Schistosoma mansoni may contribute to growth deficits. We report on the effects of treatment for S. mansoni on growth and development in Brazilian schoolchildren. Anthropometric measurements were taken from 539 S. mansoni-infected children and their age- and sex-matched egg-negative controls between the ages of 7 and 15 years. The children as a whole exhibited chronic malnutrition, with growth retardation in height evident in 21% of the population. Infected children, however, were significantly smaller in height, weight, mid upper arm circumference (UAC), tricep skinfold (TSF), and subscapular skinfold (SSF) measurements than control children (P < 0.05). These differences were due primarily to a greater disparity between infected and egg-negative girls in height (P < 0.01), weight (P = 0.01), UAC (P = 0.O2), and TSF (P < 0.01). Nevertheless, girls demonstrated a better level of development and nutrition compared with boys. While infected boys were shorter and weighed less than controls, these differences were not significant. Growth and development in girls was negatively correlated with intensity of infection. Coinfection with S. mansoni and Trichuris appeared to act synergistically in the development of malnutrition.
Ix. Processing and Transmission of Information* A. a Method of Planar Prediction for Coding Pictures Fig. Ix-1. Planar Prediction Procedure

Prof. E. Arthurs Prof. J. M. Wozencraft T. S. Huang Prof. P. Elias Dr. M. Eden F. Jelinek Prof. R. M. Fano Dr. M. P. Schiitzenberger T. Kailath Prof. J. B. Dennis D. C. Coll L. Lofgren Prof. E. M. Hofstetter M. Corradetti B. Reiffen Prof. D. A. Huffman H. A. Ernst L. G. Roberts Prof. R. C. Jeffrey E. F. Ferretti J. L. Rosenfeld Prof. H. Rogers, Jr. R. G. Gallager N. K. H. Tam Prof. C. E. Shannon U. F. Gronemann W. L. Wells Prof. W. M. Siebert F. C. Hennie III H. P. Zeiger M. Horstein
Essays on technological development and competition in local bank markets

In this paper we analyzed the process of regional concentration of financial service production. For indicators of concentration we used specialization index and financial service production per capita in the region. Theoretical base of the study lies on new economic geography. Derived from the theory, we tested whether the intra-region trade effect measured by geographic area and the share of the potentially immobile labor force in the region affect on the concentration. Also the concentration towards existing centers was tested. We found that the region’s area has negative effect both on the specialization and production. Increase in share of immobile labor affected positively on specialization and negatively on per capita production. 1 We thank the useful comments made by the members of the research group in the project ’Bank competitition in globalized markets’ that was carried out at Turku School of Economics and Business Administration during 2000–2002 and an anonymous referee for detailed comments that improved the earlier draft substantially. Financial support from the OKO Bank Group’s Research Foundation and Yrjo Jahnsson Foundation is gratefully acknowledged. All remaining errors are ours. AKI T. KOPONEN, Research Associate Turku School of Economics and Business Administration • e-mail: aki.koponen@tukkk.fi MIKA WIDGREN, Professor of Economics Turku School of Economics and Business Administration, ETLA, CEPR and CESifo • e-mail: mika.widgren@tukkk.fi L T A 2 / 0 3 • P . 242– 2 6 3 51
Target tracking and localization of binocular mobile robot using camshift and SIFT

A real time dynamic target recognition and tracking method is presented for mobile robot in this paper. Firstly, the inter-frame difference method is applied to detect the moving target. And the proposed method computes the color histogram and extracts SIFT features in the target region. Then from the following frame, it extracts SIFT features, matches with SIFT features extracted from target, and calculates the center location of the matched features. Finally the Camshift algorithm, starting from the center location, is used to track the target. Experiments demonstrate that the proposed method can effectively recognize and track the moving target, and its performance is better than the classic Camshift algorithm
Spatial variance of color and boundary statistics for salient object detection

Bottom-up saliency detection algorithms identify distinct regions in an image, with rare occurrence of local feature distributions. Notable among those works published recently, use local and global contrast, spectral analysis of the entire image or graph based feature mapping. Whereas, we propose a novel unsupervised method using color compactness and statistical modeling of the background cues, to segment the salient foreground region and thus the salient object. At the first stage of processing, the image is segmented into clusters using color feature. First component proposed for our saliency measure combines disparity in color and spatial distance between patches. In addition to rarity of feature, we propose another component for saliency computation that estimates the divergence of the color of a patch from those in the set of patches at the boundary of the image, representing the background. Combination of these two complementary components provides a much improved saliency map for salient object detection.We verify the performance of our proposed method of saliency detection on two popular benchmark datasets, with one or more salient regions and diverse saliency characteristics. Experimental results show that our method out-performs many existing state-of-the-art methods.
Development of a complete game based system for physical therapy with kinect

Games can create an immersive environment from recreational resources to aid in physical and motor rehabilitation, assisting the patient in the correct execution of movements through stimulation from interactive elements of digital games. However, for a game to be able to assist in rehabilitation it is necessary that it presents a set of features to accompany the exercises and help treatment. To this end, this work conducted an investigation in search of the key needs for physical rehabilitation games that use Kinect, generating a set of requirements, and developing a system that meets all needed requirements for motor rehabilitation. The game system created is composed of three modules: a module for the physiotherapist, a server module and the patient module, that is composed of two games.
An Analysis of the Price-Concentration Relationship in the Botswana Commercial Banking Industry

There are two different schools of thought on the relationship between pricing and measures of market structure such as concentration and market share in the banking industry. The structure-conduct-performance (market power) school suggests that concentration is empirically evident via the setting of prices which are less favorable to consumers (higher-borrowing rates and lower-deposit rates). Here conduct is structure driven and leads to further increases in welfare reducing concentration. The other school of thought - efficient-structure-suggests that due to X-efficiency some firms derive their higher profits by keeping costs lower via better management or production technologies. The other idea of the efficient-structure school is that though firms may have similar management and technology, some firms are capable of producing at more efficient scales than others and therefore also have lower unit costs and higher unit profits. This papers adds to the debate by using data on the banking industry in Botswana to examine the above theories. Preliminary findings support the structure-conduct hypothesis.
Transcription factors dynamically control the spatial organization of the yeast genome

ABSTRACT In yeast, inducible genes such as INO1, PRM1 and HIS4 reposition from the nucleoplasm to nuclear periphery upon activation. This leads to a physical interaction with nuclear pore complex (NPC), interchromosomal clustering, and stronger transcription. Repositioning to the nuclear periphery is controlled by cis-acting transcription factor (TF) binding sites located within the promoters of these genes and the TFs that bind to them. Such elements are both necessary and sufficient to control positioning of genes to the nuclear periphery. We have identified 4 TFs capable of controlling the regulated positioning of genes to the nuclear periphery in budding yeast under different conditions: Put3, Cbf1, Gcn4 and Ste12. In each case, we have defined the molecular basis of regulated relocalization to the nuclear periphery. Put3- and Cbf1-mediated targeting to nuclear periphery is regulated through local recruitment of Rpd3(L) histone deacetylase complex by transcriptional repressors. Rpd3(L), through its histone deacetylase activity, prevents TF-mediated gene positioning by blocking TF binding. Many yeast transcriptional repressors were capable of blocking Put3-mediated recruitment; 11 of these required Rpd3. Thus, it is a general function of transcription repressors to regulate TF-mediated recruitment. However, Ste12 and Gcn4-mediated recruitment is regulated independently of Rpd3(L) and transcriptional repressors. Ste12-mediated recruitment is regulated by phosphorylation of an inhibitor called Dig2, and Gcn4-mediated gene targeting is up-regulated by increasing Gcn4 protein levels. The ability to control spatial position of genes in yeast represents a novel function for TFs and different regulatory strategies provide dynamic control of the yeast genome through different time scales.
Ovary-intact, but not ovariectomized female ACI rats treated with 17beta-estradiol rapidly develop mammary carcinoma.

We have examined the ability of 17beta-estradiol (E2) to induce development of mammary cancers in the female ACI rat. Continuous treatment with E2, delivered through release from s.c. Silastic tubing implants containing 27.5 mg crystalline hormone, resulted in rapid development of palpable mammary tumors in ovary-intact ACI rats. In a population of 21 E2-treated rats, palpable tumors were first observed following 99 days treatment and 100% of the treated population developed tumors within 197 days. The median and mean times to appearance of first palpable tumor were 143 and 145 days respectively. All mammary tumors were classified as carcinomas and invasive features were observed. Circulating E2 levels in the treated animals at the time of sacrifice averaged 185 pg/ml serum. Mammary tumors were not observed in ovary-intact female ACI rats that were not treated with E2. This is the first report indicating that this naturally occurring estrogen is capable of inducing mammary cancers in the ACI rat strain. Mammary carcinoma did not develop in a population of 11 ovariectomized female ACI rats treated with E2 for a period of 140 days. Circulating E2 levels in the treated ovariectomized animals averaged 207 pg/ml. These data indicate that the ovary modulates estrogen-mediated mammary carcinogenesis in this rat strain. Both ovary-intact and ovariectomized female ACI rats displayed similar susceptibilities to E2-induced pituitary tumors and hyperprolactinemia. Pituitary weight was increased 6.0-fold in ovary-intact ACI rats and 5.3-fold in ovariectomized female rats. Circulating prolactin levels averaged 2318 ng/ml in E2-treated, ovary-intact rats and 2285 ng/ml in E2-treated, ovariectomized ACI rats. These data indicate that estrogen-induced hyperprolactinemia is not the sole factor leading to development of mammary cancers in the E2-treated ACI rat.
A stochastic approach to modeling the role of rainfall variability in drainage basin evolution

We develop a simple stochastic theory for erosion and sediment transport, based on the Poisson pulse rainfall model, in order to analyze how variability in rainfall and runoff influences drainage basin evolution. Two cases are considered: sediment transport by runoff in rills and channels and particle detachment from bedrock or cohesive soils. Analytical and numerical results show that under some circumstances, rainfall variability can have an impact equal to or greater than that of mean rainfall amount. The predicted sensitivity to rainfall variability is greatest when (1) thresholds for runoff generation and/or particle detachment are significant and/or (2) erosion and transport are strong nonlinear functions of discharge. In general, sediment transport capacity is predicted to increase with increasing rainfall variability. Depending on the degree of nonlinearity, particle detachment capacity may either increase or decrease with increasing rainfall variability. These findings underscore the critical importance of hydrogeomorphic thresholds and other sources of nonlinearity in process dynamics. The morphologic consequences of rainfall variability are illustrated by incorporating the pulse rainfall theory into a landscape simulation model. The simulation results imply that, all else being equal, catchments experiencing a shift toward greater climate variability will tend to have (1) higher erosion rates, (2) higher drainage density (because of increased runoff erosion efficiency), and ultimately (3) reduced relief. The stochastic approach provides a useful method for incorporating physically meaningful climate data within the current generation of landscape evolution models.
A Two-Stage Approach for Computing Cubature Formulae for the Sphere

In simulating interstellar dust clouds astrophysicists need high accuracy integration formulae for functions on the sphere. To construct better formu-lae than previously used, almost equidistantly spaced nodes on the sphere and weights belonging to these nodes are required. This problem is closely related to a facility dispersion problem on the sphere and to the theories of spherical designs and multivariate Gauss quadrature formulae. We propose a two-stage algorithm to compute optimal facility locations on the unit sphere with high accuracy and an appropriate algorithm to calculate the corresponding weights of the cubature formulae. These algorithms can be extended to other facility dispersion problems. Numerical examples show that the constructed formulae yield impressive small integration errors of approximately 10 ? 12 .
A Maximum Entropy-based Word Sense Disambiguation System

In this paper, a supervised learning system of word sense disambiguation is presented. It is based on conditional maximum entropy models. This system acquires the linguistic knowledge from an annotated corpus and this knowledge is represented in the form of features. Several types of features have been analyzed using the SENSEVAL-2 data for the Spanish lexical sample task. Such analysis shows that instead of training with the same kind of information for all words, each one is more effectively learned using a different set of features. This best-feature-selection is used to build some systems based on different maximum entropy classifiers, and a voting system helped by a knowledge-based method.
Ergonomic considerations for anthropomorphic wrist exoskeletons: A simulation study on the effects of joint misalignment

This work focuses on anthropomorphic exoskeletons for the human wrist. We consider a 2 dof model for the human wrist with non intersecting joints and a similar model for the exoskeleton. We assume a viscoelastic attachment between the human hand and the handle of the exoskeleton which on one side allows the different kinematics of the exoskeleton to follow the human wrist and, on the other side, induces reaction forces at all joints, in particular causing discomfort. We quantify discomfort as the amount of potential energy stored in the deformation of the viscoelastic attachment. For a specific exoskeleton implementation, based on kinematic simulations, we report the kinematic mismatch (i.e. differences between the human joints and the corresponding exoskeleton joints) as well as the reaction forces arising when the human joints assume postures throughout their physiological range of motion. Considering a typical distribution of joint offset for humans (derived from literature) and the asymmetry in the discomfort function (derived from our simulations) we address the “one-size-fits-all” problem and propose an optimal joint offset for the exoskeleton, based on the minimization of the aggregate loss function.
NetMODE: Network Motif Detection without Nauty

A motif in a network is a connected graph that occurs significantly more frequently as an induced subgraph than would be expected in a similar randomized network. By virtue of being atypical, it is thought that motifs might play a more important role than arbitrary subgraphs. Recently, a flurry of advances in the study of network motifs has created demand for faster computational means for identifying motifs in increasingly larger networks. Motif detection is typically performed by enumerating subgraphs in an input network and in an ensemble of comparison networks; this poses a significant computational problem. Classifying the subgraphs encountered, for instance, is typically performed using a graph canonical labeling package, such as Nauty, and will typically be called billions of times. In this article, we describe an implementation of a network motif detection package, which we call NetMODE. NetMODE can only perform motif detection for [Formula: see text]-node subgraphs when [Formula: see text], but does so without the use of Nauty. To avoid using Nauty, NetMODE has an initial pretreatment phase, where [Formula: see text]-node graph data is stored in memory ([Formula: see text]). For [Formula: see text] we take a novel approach, which relates to the Reconstruction Conjecture for directed graphs. We find that NetMODE can perform up to around [Formula: see text] times faster than its predecessors when [Formula: see text] and up to around [Formula: see text] times faster when [Formula: see text] (the exact improvement varies considerably). NetMODE also (a) includes a method for generating comparison graphs uniformly at random, (b) can interface with external packages (e.g. R), and (c) can utilize multi-core architectures. NetMODE is available from netmode.sf. net.
Active gel model of amoeboid cell motility

We develop a model of amoeboid cell motility based on active gel theory. Modeling the motile apparatus of a eukaryotic cell as a confined layer of finite length of poroelastic active gel permeated by a solvent, we first show that, due to active stress and gel turnover, an initially static and homogeneous layer can undergo a contractile-type instability to a polarized moving state in which the rear is enriched in gel polymer. This agrees qualitatively with motile cells containing an actomyosin-rich uropod at their rear. We find that the gel layer settles into a steadily moving, inhomogeneous state at long times, sustained by a balance between contractility and filament turnover. In addition, our model predicts an optimal value of the gel–substrate adhesion leading to maximum layer speed, in agreement with cell motility assays. The model may be relevant to motility of cells translocating in complex, confining environments that can be mimicked experimentally by cell migration through microchannels.
A comprehensive study of hot carrier stress-induced drain leakage current degradation in thin-oxide n-MOSFETs

The mechanisms and characteristics of hot carrier stress-induced drain leakage current degradation in thin-oxide n-MOSFETs are investigated. Both interface trap and oxide charge effects are analyzed. Various drain leakage current components at zero V/sub gs/ such as drain-to source subthreshold leakage, band-to-band tunneling current, and interface trap-induced leakage are taken into account. The trap-assisted drain leakage mechanisms include charge sequential tunneling current, thermionic-field emission current, and Shockley-Read-Hall generation current. The dependence of drain leakage current on supply voltage, temperature, and oxide thickness is characterized. Our result shows that the trap-assisted leakage may become a dominant drain leakage mechanism as supply voltage is reduced. In addition, a strong oxide thickness dependence of drain leakage degradation is observed. In ultra-thin gate oxide (30 /spl Aring/) n-MOSFETs, drain leakage current degradation is attributed mostly to interface trap creation, while in thicker oxide (53 /spl Aring/) devices, the drain leakage current exhibits two-stage degradation, a power law degradation rate in the initial stage due to interface trap generation, followed by an accelerated degradation rate in the second stage caused by oxide charge creation.
Schooling in capitalist America revisited

Recent research has entirely vindicated the authors' once-controversial estimates of high levels of intergenerational persistence of economic status, the unimportance of the heritability of IQ in this process, and the fact that the contribution of schooling to cognitive development plays little part in explaining why those with more schooling have higher earnings. Additional research has supported the authors' hypotheses concerning the role of personality traits, rather than skills, per se, as determinants of labor market success. Recent contributions to the study of cultural evolution allow the authors to be considerably more specific about how behaviors are learned in school
The dynamics of lone mothers' incomes: public and private income sources compared: report to the Department of Social Security

The report examines the dynamics of lone mothers’ income packages. It complements analysis of the dynamics of private income sources, namely maintenance income (child support from the non-resident father) and labour earnings, with analysis of the receipt of cash social security benefits, namely Income Support, Family Credit and Housing Benefit, thereby allowing us to compare the stability from one year to the next of private and public income sources. The first part of the report analyses the stability of each of these types of income receipt, and the second relates changes in the composition and level of total household income to movements into and off receipt of each type. The analysis is based on a sample comprising women in the first six waves of the British Household Panel Survey (covering 1991-6) who were observed as lone mothers at two or more consecutive annual interviews Acknowledgements Research undertaken for and funded by the Department of Social Security. Core funding support from the Economic and Social Research Council and the University of Essex is also acknowledged.
A New ICA-SOM Based Method for Compound Faults Diagnosis

Compound faults diagnosis is an important but difficult task in diagnostics. When several faults arise at the same time, vibration measurements by sensors show themselves as a complex integrated symptom, not as a simple and linear combination of several single faults, which makes it difficult to detect compound faults correctly. We proposed a new ICA-SOM based method for compound faults diagnosis by combining independent component analysis (ICA) based feature extraction with the self-organizing map (SOM) based classifier. ICA is a powerful tool for redundancy reduction, with which the multichannel measurements were fused. By the use of a novel-processing unit for further feature extraction, features about underlying sources embedded into the measurements were captured subsequently. At last, a medium-scale SOM network was constructed for symptom decomposition and topological display of these features. Experiment results of single and compound faults diagnosis show that our new method is effective and of great potential in health condition monitoring of machines