Miracle-dz/UniFAR-FTUs huggingface dataset:
Application of Massively Parallel Sequencing to Genetic Diagnosis in Multiplex Families with Idiopathic Sensorineural Hearing Impairment

Despite the clinical utility of genetic diagnosis to address idiopathic sensorineural hearing impairment (SNHI), the current strategy for screening mutations via Sanger sequencing suffers from the limitation that only a limited number of DNA fragments associated with common deafness mutations can be genotyped. Consequently, a definitive genetic diagnosis cannot be achieved in many families with discernible family history. To investigate the diagnostic utility of massively parallel sequencing (MPS), we applied the MPS technique to 12 multiplex families with idiopathic SNHI in which common deafness mutations had previously been ruled out. NimbleGen sequence capture array was designed to target all protein coding sequences (CDSs) and 100 bp of the flanking sequence of 80 common deafness genes. We performed MPS on the Illumina HiSeq2000, and applied BWA, SAMtools, Picard, GATK, Variant Tools, ANNOVAR, and IGV for bioinformatics analyses. Initial data filtering with allele frequencies (<5% in the 1000 Genomes Project and 5400 NHLBI exomes) and PolyPhen2/SIFT scores (>0.95) prioritized 5 indels (insertions/deletions) and 36 missense variants in the 12 multiplex families. After further validation by Sanger sequencing, segregation pattern, and evolutionary conservation of amino acid residues, we identified 4 variants in 4 different genes, which might lead to SNHI in 4 families compatible with autosomal dominant inheritance. These included GJB2 p.R75Q, MYO7A p.T381M, KCNQ4 p.S680F, and MYH9 p.E1256K. Among them, KCNQ4 p.S680F and MYH9 p.E1256K were novel. In conclusion, MPS allows genetic diagnosis in multiplex families with idiopathic SNHI by detecting mutations in relatively uncommon deafness genes.
An accidental release of flowback water from storage system : a risk assessment study

iii PREFACE . iv TABLE OF CONTENTS . v LIST OF TABLES . viii LIST OF FIGURES . ix LIST OF SYMBOLS AND ABBREVIATIONS . x ACKNOWLEDGEMENTS . xiii DEDICATION . xiv CHAPTER
Cloning and expression of the two genes coding for L-serine dehydratase from Peptostreptococcus asaccharolyticus: relationship of the iron-sulfur protein to both L-serine dehydratases from Escherichia coli

The structural genes sdhA and sdhB, coding for the alpha- and beta-subunits of the [4Fe-4S] cluster containing L-serine dehydratase from Peptostreptococcus asaccharolyticus, have been cloned and sequenced. Expression of modified sdhB together with sdhA in Escherichia coli led to overproduction of active His6-tagged L-serine dehydratase. E. coli MEW22, deficient in the L-serine dehydratase L-SD1, was complemented by this sdhBA construct. The derived amino acid sequence of SdhBA shares similarities with both monomeric L-serine dehydratases, L-SD1 and L-SD2, from E. coli and with a putative L-serine dehydratase from Haemophilus influenzae, which suggests that these three enzymes are also iron-sulfur proteins.
Evaluation of multiple enrollment for fingerprint recognition

Fusion of multiple impressions resulting from multiple fingerprint enrollments is one of the ways often used to improve fingerprint recognition performance. In this research, we perform an evaluation of the effectiveness of using multiple enrollment in fingerprint recognition systems. We design a multiple enrollment algorithm and use it together with existing fingerprint recognition techniques to carry out the evaluation. Our experimentation results and evaluations show that multiple enrollment as whole outperforms single enrollment. Multiple enrollment in experiment (1) improved the recognition performance by 83% from EER1 of 0.75% to EER of 0.13% with FVC2000-DB2, and by 79% from EER of 1.14% to EER of 0.28% with the SAS-DB2 fingerprint database. On the other hand, the multiple enrollment in experiment (2) improved the recognition performance by 71% from EER of 6.14% to EER of 1.75% with FVC2000-DB2 and improved recognition performance by 53% from EER of 14.97% to EER of 6.94% with SAS-DB2 fingerprint database.
A Quadratic Time-Space Tradeoff for Unrestricted Deterministic Decision Branching Programs

For a decision problem from coding theory, we prove a quadratic expected time-space tradeoff of the form $\eT\eS=\Omega(\tfrac{n^2}{q})$ for $q$-way deterministic decision branching programs, where $q\geq 2$. Here $\eT$ is the expected computation time and $\eS$ is the expected space, when all inputs are equally likely. This bound is to our knowledge, the first such to show an exponential size requirement whenever $\eT = O(n^2)$. Previous exponential size tradeoffs for Boolean decision branching programs were valid for time-restricted models with $T=o(n\log_2{n})$. Proving quadratic time-space tradeoffs for unrestricted time decision branching programs has been a major goal of recent research -- this goal has already been achieved for multiple-output branching programs two decades ago. We also show the first quadratic time-space tradeoffs for Boolean decision branching programs verifying circular convolution, matrix-vector multiplication and discrete Fourier transform. Furthermore, we demonstrate a constructive Boolean decision function which has a quadratic expected time-space tradeoff in the Boolean deterministic decision branching program model. When $q$ is a constant the tradeoff results derived here for decision functions verifying various functions are order-comparable to previously known tradeoff bounds for calculating the corresponding multiple-output functions.
Off-equilibrium dynamics in finite-dimensional spin-glass models.

The low-temperature dynamics of the two- and three-dimensional Ising spin-glass model with Gaussian couplings is investigated via extensive Monte Carlo simulations. We find an algebraic decay of the remanent magnetization. For the autocorrelation function C(t,${\mathit{t}}_{\mathit{w}}$)=[〈${\mathit{S}}_{\mathit{i}}$(t+${\mathit{t}}_{\mathit{w}}$)${\mathit{S}}_{\mathit{i}}$(${\mathit{t}}_{\mathit{w}}$)〉${]}_{\mathrm{av}}$ a typical aging scenario with a t/${\mathit{t}}_{\mathit{w}}$ scaling is established. Investigating spatial correlations we find an algebraic growth law \ensuremath{\xi}(${\mathit{t}}_{\mathit{w}}$)\ensuremath{\sim}${\mathit{t}}_{\mathit{w}}^{\mathrm{\ensuremath{\alpha}}(\mathit{T})}$ of the average domain size. The spatial correlation function G(r,${\mathit{t}}_{\mathit{w}}$) =[〈${\mathit{S}}_{\mathit{i}}$(${\mathit{t}}_{\mathit{w}}$)${\mathit{S}}_{\mathit{i}+\mathit{r}}$(${\mathit{t}}_{\mathit{w}}$)${\mathrm{〉}}^{2}$${]}_{\mathrm{av}}$ scales with r/\ensuremath{\xi}(${\mathit{t}}_{\mathit{w}}$). The sensitivity of the correlations in the spin-glass phase with respect to temperature changes is examined by calculating a time-dependent overlap length. In the two-dimensional model we examine domain growth with the following method: first we determine the exact ground states of the various samples (of system sizes up to 100\ifmmode\times\else\texttimes\fi{}100) and then we calculate the correlations between this state and the states generated during a Monte Carlo simulation. \textcopyright{} 1996 The American Physical Society.
The risk profile problem for stock portfolio optimization (extended abstract)

This work initiates research into the problem of determining an optimal investment strategy for investors with different attitudes towards the trade-offs of risk and profit. The probability distribution of the return values of the stocks that are considered by the investor are assumed to Research supported in part by NSF grants CCR-9531028 and CCR-9974871. Current address: Department of Computer Science, Northwestern University, Evanston, IL 60201, USA. Research supported in part by Texas Advanced Research Program Grant 1997-003594-019.
Fast Localization of the Optic Disc Using Projection of Image Features

Optic Disc (OD) localization is an important pre-processing step that significantly simplifies subsequent segmentation of the OD and other retinal structures. Current OD localization techniques suffer from impractically-high computation times (few minutes per image). In this work, we present a fast technique that requires less than a second to localize the OD. The technique is based upon obtaining two projections of certain image features that encode the x- and y- coordinates of the OD. The resulting 1-D projections are then searched to determine the location of the OD. This avoids searching the 2-D image space and, thus, enhances the speed of the OD localization process. Image features such as retinal vessels orientation and the OD brightness are used in the current method. Four publicly-available databases, including STARE and DRIVE, are used to evaluate the proposed technique. The OD was successfully located in 330 images out of 340 images (97%) with an average computation time of 0.65 s.
Algorithms of Two-Level Parallelization for DSMC of Unsteady Flows in Molecular Gasdynamics

The general scheme of two-level parallelization (TLP) for direct simulation Monte Carlo of unsteady gas flows on shared memory multiprocessor computers has been described. The high efficient algorithm of parallel independent runs is used on the first level. The data parallelization is employed for the second one. Two versions of TLP algorithm are elaborated with static and dynamic load balancing. The method of dynamic processor reallocation is used for dynamic load balancing. Two gasdynamic unsteady problems were used to study speedup and efficiency of the algorithms. The conditions of efficient application field for the algorithms have been determined.
Geographic-Based Service Request Scheduling Model for Mobile Cloud Computing

With Internet environment is getting optimized and users preferring mobile communications, Cloud Service Providers (CSP) aim to provide services to users depending on their geographic locations with higher service availability and faster access speed. Mobile cloud computing falls into this category, where mobile users can move around and request cloud services at any given geographic locations. To build such a geographic-based mobile cloud services, an effective mobile cloud resource allocation and service request scheduling scheme is highly desired. To this end, the presented service request scheduling scheme takes a comprehensive approach by considering system parameters from both CSP and mobile users such as computation, energy, connectivity, service payment, mobile users' satisfaction, etc. Finally, the performance evaluation of the proposed scheduling scheme is evaluated through simulations where the results show that the presented scheme achieves better system overall gain compared to traditional over-provisioning approaches.
The independent components of natural images are perceptually dependent

The independent components of natural images are a set of linear filters which are optimized for statistical independence. With such a set of filters images can be represented without loss of information. Intriguingly, the filter shapes are localized, oriented, and bandpass, resembling important properties of V1 simple cell receptive fields. Here we address the question of whether the independent components of natural images are also perceptually less dependent than other image components. We compared the pixel basis, the ICA basis and the discrete cosine basis by asking subjects to interactively predict missing pixels (for the pixel basis) or to predict the coefficients of ICA and DCT basis functions in patches of natural images. Like Kersten (1987)1 we find the pixel basis to be perceptually highly redundant but perhaps surprisingly, the ICA basis showed significantly higher perceptual dependencies than the DCT basis. This shows a dissociation between statistical and perceptual dependence measures.
Generalized ABBA Space-Time Block Codes

Linear space-time block codes (STBCs) of unitary rate and full diversity, systematically constructed over arbitrary constellations for any number of transmit antennas are introduced. The codes are obtained by generalizing the existing ABBA STBCs, a.k. a quasi-orthogonal STBCs (QO-STBCs). Furthermore, a fully orthogonal (symbol-by-symbol) decoder for the new generalized ABBA (GABBA) codes is provided. This remarkably low-complexity decoder relies on partition orthogonality properties of the code structure to decompose the received signal vector into lower-dimension tuples, each dependent only on certain subsets of the transmitted symbols. Orthogonal decodability results from the nested application of this technique, with no matrix inversion or iterative signal processing required. The exact bit-error-rate probability of GABBA codes over generalized fading channels with maximum likelihood (ML) decoding is evaluated analytically and compared against simulation results obtained with the proposed orthogonal decoder. The comparison reveals that the proposed GABBA solution, despite its very low complexity, achieves nearly the same performance of the bound corresponding to the ML-decoded system, especially in systems with large numbers of antennas.
An Analytical Mechanics Model for the Rotary Sliding Triboelectric Nanogenerator

In recent years, global attention towards new energy has surged due to increasing energy demand and environmental concerns. Researchers have intensified their focus on new energy, leading to advancements in technologies like triboelectrification, which harnesses energy from the environment. The invention of the triboelectric nanogenerator (TENG) has led to new possibilities, with the rotary sliding TENG standing out for its superior performance. However, understanding its mechanical behavior remains a challenge, potentially leading to structural issues. This paper introduces a novel analytical mechanics model to analyze the mechanical performance of the stator of the rotary sliding TENG, offering a new analytical solution. The solution also presents an innovative approach to solving axisymmetric problems in elasticity theory since it challenges a traditional assumption that the stress function depends solely on the radial coordinate, proposing a new stress function to derive a more general solution, supplementing the classical approach in the theory of elasticity. Through the obtained solutions, the mechanical characteristics of the rotary sliding TENG during operation are analyzed. A clearer relationship between mechanical characteristics and electrical output is expected to provide a theoretical basis for the design of the rotary sliding TENG.
Selective Combination of Pivot and Direct Statistical Machine Translation Models

In this paper, we propose a selective combination approach of pivot and direct statistical machine translation (SMT) models to improve translation quality. We work with Persian-Arabic SMT as a case study. We show positive results (from 0.4 to 3.1 BLEU on different direct training corpus sizes) in addition to a large reduction of pivot translation model size.
Quantum Watermarking by Frequency of Error when Observing Qubits in Dissimilar Bases

We present a so-called fuzzy watermarking scheme based on the relative frequency of error in observing qubits in a dissimilar basis from the one in which they were written. Then we discuss possible attacks on the system and speculate on how to implement this watermarking scheme for particular kinds of messages (images, formated text, etc.).
Best insertion algorithm for resource-constrained project scheduling problem

This paper considers heuristics for well known resource-constrained project scheduling problem (RCPSP). First a feasible schedule is constructed using randomized best insertion algorithm. The construction is followed by a local search where a new solution is generated as follows: first we randomly delete m activities from the list, which are then reinserted in the list in consecutive order. At the end of run, the schedule with the minimum makespan is selected. Experimental work shows very good results on standard test instances found in PSPLIB
Construction of a predictive model for bone metastasis from first primary lung adenocarcinoma within 3 cm based on machine learning algorithm: a retrospective study

Background Adenocarcinoma, the most prevalent histological subtype of non-small cell lung cancer, is associated with a significantly higher likelihood of bone metastasis compared to other subtypes. The presence of bone metastasis has a profound adverse impact on patient prognosis. However, to date, there is a lack of accurate bone metastasis prediction models. As a result, this study aims to employ machine learning algorithms for predicting the risk of bone metastasis in patients. Method We collected a dataset comprising 19,454 cases of solitary, primary lung adenocarcinoma with pulmonary nodules measuring less than 3 cm. These cases were diagnosed between 2010 and 2015 and were sourced from the Surveillance, Epidemiology, and End Results (SEER) database. Utilizing clinical feature indicators, we developed predictive models using seven machine learning algorithms, namely extreme gradient boosting (XGBoost), logistic regression (LR), light gradient boosting machine (LightGBM), Adaptive Boosting (AdaBoost), Gaussian Naive Bayes (GNB), multilayer perceptron (MLP) and support vector machine (SVM). Results The results demonstrated that XGBoost exhibited superior performance among the four algorithms (training set: AUC: 0.913; test set: AUC: 0.853). Furthermore, for convenient application, we created an online scoring system accessible at the following URL: https://www.xsmartanalysis. com/model/predict/? mid=731symbol=7Fr16wX56AR9Mk233917, which is based on the highest performing model. Conclusion XGBoost proves to be an effective algorithm for predicting the occurrence of bone metastasis in patients with solitary, primary lung adenocarcinoma featuring pulmonary nodules below 3 cm in size. Moreover, its robust clinical applicability enhances its potential utility.
Proteomic analysis of brain proteins in APP/PS‐1 human double mutant knock‐in mice with increasing amyloid β‐peptide deposition: Insights into the effects of in vivo treatment with N‐acetylcysteine as a potential therapeutic intervention in mild cognitive impairment and Alzheimer's disease

Proteomics analyses were performed on the brains of wild‐type (WT) controls and an Alzheimer's disease (AD) mouse model, APP/PS‐1 human double mutant knock‐in mice. Mice were given either drinking water or water supplemented with N‐acetylcysteine (NAC) (2 mg/kg body weight) for a period of five months. The time periods of treatment correspond to ages prior to Aβ deposition (i.e. 4–9 months), resembling human mild cognitive impairment (MCI), and after Aβ deposition (i.e. 7–12 months), more closely resembling advancing stages of AD. Substantial differences exist between the proteomes of WT and APP/PS‐1 mice at 9 or 12 months, indicating that Aβ deposition and oxidative stress lead to downstream changes in protein expression. Altered proteins are involved in energy‐related pathways, excitotoxicity, cell cycle signaling, synaptic abnormalities, and cellular defense and structure. Overall, the proteomic results support the notion that NAC may be beneficial for increasing cellular stress responses in WT mice and for influencing the levels of energy‐ and mitochondria‐related proteins in APP/PS‐1 mice.
Recently Deglaciated High-Altitude Soils of the Himalaya: Diverse Environments, Heterogenous Bacterial Communities and Long-Range Dust Inputs from the Upper Troposphere

Background The Himalaya with its altitude and geographical position forms a barrier to atmospheric transport, which produces much aqueous-particle monsoon precipitation and makes it the largest continuous ice-covered area outside polar regions. There is a paucity of data on high-altitude microbial communities, their native environments and responses to environmental-spatial variables relative to seasonal and deglaciation events. Methodology/Principal Findings Soils were sampled along altitude transects from 5000 m to 6000 m to determine environmental, spatial and seasonal factors structuring bacterial communities characterized by 16 S rRNA gene deep sequencing. Dust traps and fresh-snow samples were used to assess dust abundance and viability, community structure and abundance of dust associated microbial communities. Significantly different habitats among the altitude-transect samples corresponded to both phylogenetically distant and closely-related communities at distances as short as 50 m showing high community spatial divergence. High within-group variability that was related to an order of magnitude higher dust deposition obscured seasonal and temporal rearrangements in microbial communities. Although dust particle and associated cell deposition rates were highly correlated, seasonal dust communities of bacteria were distinct and differed significantly from recipient soil communities. Analysis of closest relatives to dust OTUs, HYSPLIT back-calculation of airmass trajectories and small dust particle size (4–12 µm) suggested that the deposited dust and microbes came from distant continental, lacustrine and marine sources, e.g. Sahara, India, Caspian Sea and Tibetan plateau. Cyanobacteria represented less than 0.5% of microbial communities suggesting that the microbial communities benefitted from (co)deposited carbon which was reflected in the psychrotolerant nature of dust-particle associated bacteria. Conclusions/Significance The spatial, environmental and temporal complexity of the high-altitude soils of the Himalaya generates ongoing disturbance and colonization events that subject heterogeneous microniches to stochastic colonization by far away dust associated microbes and result in the observed spatially divergent bacterial communities.
A Numerical Model Investigation of the Role of the Glacier Bed in Regulating Grounding Line Retreat of Thwaites Glacier, West Antarctica

i ACKNOWLEDGEMENTS . iii LIST OF FIGURES . viii LIST OF ABBREVIATIONS . xi LIST OF SYMBOLS . xii 1.0 INTRODUCTION . 1 1.1 Physical Setting . 2 1.2 Climate Context . 7 1.3 Glaciological Context . 8 1.4 Research Question . 9 2.0 METHODS . 10 2.1 Governing Equations . 11 2.2 Constitutive Equations . 13 2.3 Ice Flow Approximations . 15 2.4 Boundary Conditions . 17 2.5 Numerical Model . 22 2.6 Model Domain and Boundaries . 26 2.7 Bed Topography. 27 2.8 Model Initialization . 29 2.8. 1 Implementation and Spatial Maps . 33 2.9 Oceanic Forcing . 36 2.9. 1 Perturbation and Experiment Design . 41 3.0 RESULTS . 43