Miracle-dz/UniFAR-FTUs huggingface dataset:
Resting-State Functional Connectivity by Independent Component Analysis-Based Markers Corresponds to Areas of Initial Seizure Propagation Established by Prior Modalities from the Hypothalamus

Abstract The aims of this study were to evaluate a clinically practical functional connectivity (fc) protocol designed to blindly identify the corresponding areas of initial seizure propagation and also to differentiate these areas from remote secondary areas affected by seizure. The patients in this cohort had intractable epilepsy caused by intrahypothalamic hamartoma, which is the location of the ictal focus. The ictal propagation pathway is homogeneous and established, thus creating the optimum situation for the proposed method validation study. Twelve patients with seizures from hypothalamic hamartoma and six normal control patients underwent resting-state functional MRI, using independent component analysis (ICA) to identify network differences in patients. This was followed by seed-based connectivity measures to determine the extent of fc derangement between hypothalamus and these areas. The areas with significant change in connectivity were compared with the results of prior studies' modalities used to evaluate seizure propagation. The left amygdala-parahippocampal gyrus area, cingulate gyrus, and occipitotemporal gyrus demonstrated the highest derangement in connectivity with the hypothalamus, p < 0.01, corresponding to the initial seizure propagation areas established by prior modalities. Areas of secondary ictal propagation were differentiated from these initial locations by first being identified as an abnormal neuronal signal source through ICA, but did not show significant connectivity directly with the known ictal focus. Noninvasive connectivity measures correspond to areas of initial ictal propagation and differentiate such areas from secondary ictal propagation, which may aid in ictal focus surgical disconnection planning and support the use of this newer modality for adjunctive information in epilepsy surgery evaluation.
Shrinkage estimation of NFL field goal success probabilities

National Football League (NFL) kickers have displayed improvement in both range and accuracy in recent years. NFL management in turn has displayed a rather low tolerance for missed field goals, particularly in game-deciding situations. However, these actions may be a consequence of a perceived appreciable variability in NFL kicker ability. In this paper, we consider shrinkage estimation of NFL kicker field goal success probabilities. The idea derives from the literature on estimating batting averages in baseball, though the classic James-Stein shrinkage approaches there do not apply to independent binary field goal attempt trials. We study a variety of weighting schemes for shrinking model-based kicker-specific field goal success probability estimates to a league-wide estimate, as a function of distance. As part of the development, we briefly detail collecting NFL play-by-play data with the R statistical software package, identify the complementary log-log link function as preferable to the more commonly applied logit link function in a generalized linear model for field goal success, and demonstrate the desired variance-reduction, both in and out of sample, enjoyed by our proposed shrinkage estimators. We illustrate our methods by ranking NFL kickers from 1998 to 2014, analyzing individual kicker success at mid-range and long-range field goal attempts, and studying kicker ability over the last decade. Stadium effects are added to the model and found to be highly significant and to have an impact on the kicker rankings. 6
An in vitro model of the brain tissue reaction to chronically implanted recording electrodes reveals essential roles for serum and bFGF in glial scarring

An In Vitro Model of the Brain Tissue Reaction to Chronically Implanted Recording Electrodes Reveals Essential Roles for Serum and bFGF in Glial Scarring by Vadim Steven Polikov Department of Biomedical Engineering Duke University Date:_______________________ Approved: ___________________________ William “Monty” Reichert, PhD, Committee Chair ___________________________ Jau-Shyong Hong, PhD ___________________________ Bruce Klitzman, PhD ___________________________ Sidney Simon, PhD ___________________________ Patrick Wolf, PhD An abstract of a dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Biomedical Engineering in the Graduate School of Duke University 2009 Copyright by Vadim Steven Polikov 2009
A short course of recombinant human growth hormone treatment stimulates osteoblasts and activates bone remodeling in normal human volunteers

The effects of recombinant human growth hormone (rhGH) on biochemical markers of bone turnover and bone mineral content (BMC) were investigated in 20 normal male volunteers (aged 22‐31 years) randomized to treatment for 7 days with either rhGH (0.1 IU/kg subcutaneously twice a day) or placebo. Serum somatomedin C rose during treatment (p < 0.001) but was not significantly different from baseline at day 14. The fasting urinary hydroxyproiine/creatinine (p < 0.001) and calcium/creatinine ratios (p < 0.01) increased during treatment and remained elevated for 4 and 2 weeks, respectively. Serum bone 7‐carboxyglutamic acid‐containing protein (BGP) increased during treatment (p < 0.001) and remained elevated for 6 months (p < 0.02). Serum bone alkaline phosphatase (B‐AP), after an initial fall in the treatment period (p < 0.001), increased slightly in the following months (p < 0.01). In the rhGH group BMC was significantly higher than the prestudy value at day 14 (p < 0.05) but was unaltered at the end of study. The simultaneous increase in markers of bone resorption and formation during rhGH treatment followed by a decline in resorption parameters within a few weeks and the prolonged effect on BGP and B‐AP demonstrate that rhGH treatment stimulates osteoblasts and activates bone remodeling.
Extracorporeal shock wave lithotripsy: An opinion on its future

The development of miniaturized nephroscopes which allow one-stage stone clearance with minimal morbidity has brought the role of shock wave lithotripsy (SWL) in stone management into question. Design innovations in SWL machines over the last decade have attempted to address this problem. We reviewed the recent literature on SWL using a MEDLINE/PUBMED research. For commenting on the future of SWL, we took the subjective opinion of two senior urologists, one mid-level expert, and an upcoming junior fellow. There have been a number of recent changes in lithotripter design and techniques. This includes the use of multiple focus machines and improved coupling designs. Additional changes involve better localization real-time monitoring. The main goal of stone treatment today seems to be to get rid of the stone in one session rather than being treated multiple times non-invasively. Stone treatment in the future will be individualized by genetic screening of stone formers, using improved SWL devices for small stones only. However, there is still no consensus about the design of the ideal lithotripter. Innovative concepts such as emergency SWL for ureteric stones may be implemented in clinical routine.
Adaptive state feedback control of robotic manipulators using neural networks

In this paper, a neural network based adaptive state feedback control scheme is proposed to solve the problem of trajectory tracking in the joint space for robotic manipulators with the presence of high uncertainty in the system parameters. First nonlinear behavior of the robot is approximately eliminated by applying a linearizing control, the closed loop dynamics is stabilized using static compensator. Then the parametric uncertainty is parameterized and eliminated using a single hidden layer neural network. The adaptation law for the NN and the boundedness of the error signals are proved from Lyapunov theorem of stability. The performance of the proposed controller is validated on two-link manipulator and demonstrated through computer simulation.
Essays in Quantitative Finance

This thesis contributes to the quantitative finance literature and consists of four research papers.Paper 1. This paper constructs a hybrid commodity interest rate market model with a stochastic local volatility function that allows the model to simultaneously fit the implied volatility of commodity and interest rate options. Because liquid market prices are only available for options on commodity futures (not forwards), a convexity correction formula is derived to account for the difference between forward and futures prices. A procedure for efficiently calibrating the model to interest rate and commodity volatility smiles is constructed. Finally, the model is fitted to an exogenously given cross-correlation structure between forward interest rates and commodity prices. When calibrating to options on forwards (rather than futures), the fitting of cross-correlation preserves the (separate) calibration in the two markets (interest rate and commodity options), whereas in the case of futures, a (rapidly converging) iterative fitting procedure is presented. The cross-correlation fitting is reduced to finding an optimal rotation of volatility vectors, which is shown to be an appropriately modified version of the “orthonormal Procrustes” problem. The calibration approach is demonstrated on market data for oil futures.Paper 2. This paper describes an efficient American Monte Carlo approach for pricing Bermudan swaptions in the LIBOR market model using the Stochastic Grid Bundling Method (SGBM) which is a regression-based Monte Carlo method in which the continuation value is projected onto a space in which the distribution is known. We demonstrate an algorithm to obtain accurate and tight lower–upper bound values without the need for the nested Monte Carlo simulations that are generally required for regression-based methods.Paper 3. The credit valuation adjustment (CVA) for over-the-counter derivatives are computed using the portfolio’s exposure over its lifetime. Usually, future exposure is approximated by Monte Carlo simulations. For derivatives that lack an analytical approximation for their mark-to-market (MtM) value, such as Bermudan swaptions, the standard practice is to use the regression functions from the least squares Monte Carlo method to approximate their simulated MtMs. However, such approximations have significant bias and noise, resulting in an inaccurate CVA charge. This paper extend the SGBM to efficiently compute expected exposure, potential future exposure, and CVA for Bermudan swaptions. A novel contribution of the paper is that it demonstrates how different measures, such as spot and terminal measures, can simultaneously be employed in the SGBM framework to significantly reduce the variance and bias.Paper 4. This paper presents an algorithm for simulation of options on Levy driven assets. The simulation is performed on the inverse transition matrix of a discretised partial differential equation. We demonstrate how one can obtain accurate option prices and deltas on the variance gamma (VG) and CGMY model through finite element-based Monte Carlo simulations. (Less)
Urban water demand forecasting using the stochastic nature of short term historical water demand and supply pattern

Today's big city water utility companies are experiencing high level of water loss due to various problems in covering a large scale of water supply pipeline networks, therefore any significant improvement of water loss prevention from supply network to treatment plant would require an apprehends stochastic nature of historical water demand and supply pattern. For this reason urban water demand forecasting is one of key important parameters used when water utility companies are trying to find more efficient and robust ways of supplying water for a large number of urban consumers. Water demand forecasting also plays a significant role in managing and planning water supply operations and water conservation and optimization strategies. However, traditional forecasting approaches based on a set of deterministic design capacity factors or using demand forecasting algorithms without evaluating the relationship between supply reliability in response to the stochastic nature of historical water consumption data and supply pattern often become misleading due to the inability to sufficiently forecast forthcoming events and lack of relevant historical pattern and data. This paper presents an analysis and water demand forecasting demonstration using the stochastic nature of short term historical water demand and supply Pattern for Lille University Z6 pipeline networks research area in France.
Childhood antecedents of personality disorder

Purpose of review Given the substantial continuity of personality and axis I psychopathology from childhood to adult life, the present review explores whether and how recent research findings support the notion that personality disorders have their developmental precipitants in childhood. Potential childhood personality disorder antecedents will be reviewed from different research areas to enhance an insight into the genesis of a major set of adult psychiatric disorders with profound impact on the daily life. Recent findings There exists increasing evidence that personality disorders have their origins in early years of life at the observable symptomatic, biological, and genetic levels. A clear need for prospective (behavior genetic) studies, however, exists that will ultimately verify how and when childhood personality disorder features turn into adult maladaptive trait patterns. It is further suggested that these designs require a comprehensive taxonomy for the description of personality disorder antecedents in a developmentally appropriate way. Summary The call for a developmental perspective on adult personality disorders in recent debates on the construction of Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, has created new avenues for an integrative longitudinal perspective on personality disorders and should stimulate child psychiatrists to consider the significance of emerging personality disorder symptoms at a young age.
Genetic Susceptibility to Childhood Acute Lymphoblastic Leukemia

Acute lymphoblastic leukemia (ALL) is the most common pediatric cancer. The origin of this disease can be explained by a combination of genetic susceptibility factors and environmental exposures. For the purpose of our study it can be considered as a complex disease, caused by the “carcinogenic” effect of the environment modified by a series of genes. In population, these genes tend to occur in allelic forms representing functional polymorphisms thus explaining inter-individual variability in cancer susceptibility. The latter can be evaluated more realistically in childhood ALL than in sporadic cancers of the adult because of its relatively short latency period. We asked therefore, the question about the role of genes controlling the efficiency of xenobiotics metabolism in childhood leukemogenesis. Xenobiotics (drugs and carcinogens) are excreted from the body after metabolic conversion by enzymes mediating oxidation activation (Phase I) and conjugation detoxificaton (Phase II). Functional variants of these enzymes, resulting from known DNA polymorphisms in the corresponding genes, were shown to influence the risk to a variety of solid tumours in adults. A case-control study on ALL patients and healthy controls in a French-Canadian population was carried out by examining the loci of Phase I, CYP1A1 and CYP2D6, as well as Phase II enzymes, GSTM1, GSTT1, NAT1 and NAT2. The NAT2 slow-acetylator, CYP1A1*2A and GSTM1 null genotypes were shown to be significant risk determinants of ALL (OR=1.6, 1.8 and 1.8, respectively), whereas, polymorphisms in CYP2D6 and GSTT1 genes did not seem to play an important role in the aetiology of ALL. Interestingly, the risk associated with NAT2 slow-acetylators was most apparent among males homozygous for NAT1* 4 (OR=3.3) whereas girls carrying the CYP1A1* 4 allele were significantly underrepresented in the patient group (OR=0.2). These findings point to a gender-specific effect of DNA variants which, at least in part, may explain why ALL is more prevalent among boys. To assess gene-gene interactions, NAT2 slow-acetylators were considered together with GSTM1 null genotypes and CYP1A1 *2A alleles. The combined presence of two risk-elevating genotypes appeared to confer an increased risk of ALL among the carriers (OR=2.6). This risk was increased further (OR=3.3) when all three genotypes occurred in the same individuals indicating that the combination of susceptibility variants is more predictive of risk then either of them independently. The association of leukemogenesis in children with metabolising gene variants suggests causal relation to environmental exposures.
Mu-GSIM: A mutation testing simulator on GPUs

Graphics Processing Units (GPUs) have recently gained widespread usage as an advanced parallel platform for accelerating compute intensive applications. The maturity of programming interfaces and the improved programmability of GPUs have enabled the development of parallel algorithms that leverage the wealth of compute power provided by them. In this paper, we present μ-GSIM, a GPU-based simulation tool that leverages the inherent bit parallelism of GPUs for accelerating simulations of mutated digital circuits. We propose an efficient mapping of multiple mutated circuits on the GPU's device memory, where we exploit as much data parallelism as possible so our GPU simulation kernel can achieve maximal performance by operating on independent data. Results show that with the largest ITC'99 circuit benchmarks we were able to achieve a 60% decrease in memory usage while gaining a 5.4× increase in simulation performance. Additionally, we demonstrated a speedup of at least 95× against a commercial event-driven simulation tool running on a conventional processor. This is beneficial in the quest for improving test quality.
Systematic Review Systematic review and meta-analysis: association between water and sanitation environment and maternal mortality

objective To assess whether the lack of water or the lack of sanitation facilities in either the home or in health facilities is associated with an increased risk of maternal mortality and to quantify the effect sizes. methods Systematic review of published literature in Medline, Embase, Popline and Africa Wide EBSCO since 1980. results Fourteen articles were found. Four of five ecological studies that considered sanitation found that poor sanitation was associated with higher maternal mortality. Meta-analysis of adjusted estimates in individual-level studies indicated that women in households with poor sanitation had 3.07 (95% CI 1.72–5.49) higher odds of maternal mortality. Four of six ecological studies assessing water environment found that poor water environment was associated with higher maternal mortality. The only individual-level study looking at the adjusted effect of water showed a significant association with maternal mortality (OR = 1.50, 95% CI 1.10–2.10). Two ecological and one facility-based study found an association between a combined measure of water and sanitation environment and maternal mortality. conclusions There is evidence of association between sanitation and maternal mortality and between water and maternal mortality. Both associations are of substantial magnitude and are maintained after adjusting for confounders. However, these conclusions are based on a very small number of studies, few of which set out to examine sanitation or water as risk factors, and only some of which adjusted for potential confounders. Nevertheless, there are plausible pathways through which such associations may operate.
The Course of Back Pain in Primary Care

Study Design Review paper of outcome studies among primary care back pain patients. Objectives To determine the short‐term and long‐term pain and functional outcomes of patients with back pain who are seeking treatment in primary care settings. Summary of Background Data Back pain has been viewed as running either an acute or a chronic course, but most patients experience recurrent back pain. This review summarizes outcome studies in light of the episodic course of back pain. Methods Studies reporting pain and functional outcome data for consecutive primary care patients with back pain were reviewed. Results Back pain among primary care patients typically is a recurrent condition for which definitions of acute and chronic pain based on a single episode are inadequate. Because a majority of patients experience recurrences, describing only the outcome of the initial back pain episode may convey a more favorable picture of long‐term outcome than warranted. For the short‐term follow‐up evaluation, most patients improve considerably during the first 4 weeks after seeking treatment. Sixty‐six percent to 75% continue to experience at least mild back pain 1 month after seeking care. At 1 month, approximately 33% report continuing pain of at least moderate intensity, whereas 20‐25% report substantial activity limitations. For the long‐term follow‐up (1 year or more) period, approximately 33% report intermittent or persistent pain of at least moderate intensity, one in seven continue to report back pain of severe intensity, and one in five report substantial activity limitations. Conclusion Results from existing studies suggest that back pain among primary care patients typically runs a recurrent course characterized by variation and change, rather than an acute, self‐limiting course.
Energy-Efficient Design for Downlink OFDMA with Delay-Sensitive Traffic

The tremendous popularity of smart phones and electronic tablets has spurred the explosive growth of high-rate multimedia services and promptly boomed energy consumption in wireless networks. Therefore, energy-efficient design in wireless networks is very important and is attracting more and more attention, just like the conventional spectral-efficient design. In this paper, we study energy-efficient design in downlink orthogonal frequency division multiple access (OFDMA) networks with effective capacity-based delay provisioning for delay-sensitive traffic. By integrating information theory with the concept of effective capacity, we formulate an energy efficiency (EE) optimization problem with statistical delay provisioning, which is a complicated nonconvex combinatorial fractional programming problem. To solve the problem, we first relax it with an upper bound on the original one and then prove and exploit the quasiconcave property of the EE-versus-transmit power curve, which facilitates the optimal algorithm development. Then, we demonstrate that the resultant solution is quite close to the true optimal value when the number of subcarriers is larger than that of the users. We also analyze the tradeoff between EE and delay, the relationship between spectral-efficient and energy-efficient designs, and the impact of system parameters, including circuit power and delay exponents, on the overall performance. Numerical results show that the proposed energy-efficient design scheme greatly improves EE while maintaining the delay requirement.