Miracle-dz/UniFAR-FTUs huggingface dataset:
Inferring the landscape of recombination using recurrent neural networks

Accurately inferring the genome-wide landscape of recombination rates in natural populations is a central aim in genomics, as patterns of linkage influence everything from genetic mapping to understanding evolutionary history. Here we describe ReLERNN, a deep learning method for accurately estimating a genome-wide recombination landscape using as few as four samples. Rather than use summaries of linkage disequilibrium as its input, ReLERNN considers columns from a genotype alignment, which are then modeled as a sequence across the genome using a recurrent neural network. We demonstrate that ReLERNN improves accuracy and reduces bias relative to existing methods and maintains high accuracy in the face of demographic model misspecification. We apply ReLERNN to natural populations of African Drosophila melanogaster and show that genome-wide recombination landscapes, while largely correlated among populations, exhibit important population-specific differences. Lastly, we connect the inferred patterns of recombination with the frequencies of major inversions segregating in natural Drosophila populations.
Quantitative modeling links in vivo microstructural and macrofunctional organization of human and macaque insular cortex, and predicts cognitive control abilities

The human insular cortex is a heterogenous brain structure which plays an integrative role in guiding behavior. The cytoarchitectonic organization of the human insula has been investigated over the last century using postmortem brains but there has been little progress in noninvasive in vivo mapping of its microstructure and large-scale functional circuitry. Quantitative modeling of multi-shell diffusion MRI (dMRI) data from 440 HCP participants revealed that human insula microstructure differs significantly across its functionally defined dorsal anterior, ventral anterior, and posterior insula subdivisions that serve distinct cognitive and affective functions. The microstructural organization of the insula was mirrored in its functionally interconnected circuits with the anterior cingulate cortex that anchor the salience network, a system important for adaptive switching of cognitive control systems. Novel validation of the human insula findings came from quantitative dMRI modeling in macaques which revealed microstructural features consistent with known primate insula cytoarchitecture. Theoretical analysis and computer simulations, using realistic 3-dimensional models of neuronal morphology from postmortem tissue, demonstrated that dMRI signals reflect the cellular organization of cortical gray matter, and that these signals are sensitive to cell size and the presence of large neurons such as the von Economo neurons. Crucially, insular microstructural features were linked to behavior and predicted individual differences in cognitive control ability. Our findings open new possibilities for probing psychiatric and neurological disorders impacted by insular cortex dysfunction, including autism, schizophrenia, and fronto-temporal dementia. Statement of Significance The human insular cortex is a heterogenous brain structure which plays an integrative role in identifying salient sensory, affective, and cognitive cues for guiding attention and behavior. It is also is one of the most widely activated brain regions in all of human neuroimaging research. Here we use novel quantitative tools with in vivo diffusion MRI in large group (N=440) of individuals to uncover several unique microstructural features of the human insula and its macrofunctional circuits. Crucially, microstructural properties of the insular cortex predicted human cognitive control abilities, in agreement with its crucial role in adaptive human behaviors. Our findings open new possibilities for probing psychiatric and neurological disorders impacted by insular dysfunction, including autism, schizophrenia, and fronto-temporal dementia.
Physiological responses and transcriptome analysis of the Kochia prostrata (L.) Schrad. to seedling drought stress

Abstract Kochia prostrata is a good forage plant, which has important economic and ecological value in arid and semi-arid regions of China. Drought is one of the main factors affecting its productivity. At present, there are few studies on the mechanism of drought resistance. In order to reveal the changes of physiological and biochemical indexes, stomatal structure and gene expression profiles of Kochia prostrata under drought treatment, the classical determination method and high-throughput Illumina Hiseq sequencing platform were applied to the control group (CK) and drought treatment group of Kochia prostrata. The results showed that under the condition of moderate to mild drought stress, the SOD activity reached the maximum value of 350.68 U/g min on the 5th day of stress, and under the condition of severe drought stress, the SOD activity reached the maximum on the 2nd day of stress. The accumulation of Proline remained at a high level on the 5th day of stress, and there was at least one epidermal cell interval between the two adult stomatal of the leaf epidermis, so that the evaporation shell of each stomatal did not overlap, it ensures the efficient gas exchange of the stomatal, indicating that the Kochia prostrata has strong drought resistance. A total of 1,177.46 M reads were obtained by sequencing, with a total of 352.25 Gbp data and Q30 of 85%. In the differential gene annotation to the biological process (BP), a total of 261 GO terms were enriched in the up-regulated genes, and a total of 231 GO terms were enriched in the down-regulated genes. The differentially expressed genes (DEGs) were obtained in 27 KEGG metabolic pathways, which laid a foundation for revealing the molecular mechanism of drought tolerance.
Active Suspension Control with Direct-Drive Tubular Linear Brushless Permanent-Magnet Motor

Recently, active suspension has been applied to many commercial automobiles. To develop the control algorithm for active suspension, a quarter-car test bed was built by using a direct-drive tubular linear brushless permanent-magnet motor (LBPMM) as a force-generating component. Modified lead-lag control, linear-quadratic (LQ) servo control with a Kalman filter, the fuzzy control methodologies were implemented for active-suspension control. In the case of fuzzy control, an asymmetric membership function was introduced. This controller could attenuate road disturbance by up to 78%. Both simulation and experimental results are presented to demonstrate the effectiveness of these control methodologies.
Morphological Analyzer for Classical Tamil Texts: A Rule- based approach

Morphology is the identification, analysis, and description of the structure of a given language's morphemes and other linguistic units, such as root words, affixes, parts of speech, intonations and stresses, or implied context. Morphological analysis is a process of segmenting words into morphemes and a process of analyzing the word formation. Morphological Analyzer is a program which takes words as input and produces its grammatical structure as output. It identifies and segments the words and assigns the grammatical information. Capturing the agglutinative structure of Classical Tamil words by an automatic system is a challenging job. This paper deals with how the Morphological Analyzer is developed for Classical Tamil texts using rule-based approach.
Symbol Grounding or the Emergence of Symbols? Vocabulary Growth in Children and a Connectionist Net

Abstract The Symbolic Grounding Problem is viewed as a by-product of the classical cognitivist approach to studying the mind. In contrast, an epigenetic interpretation of connectionist approaches to studying the mind is shown to offer an account of symbolic skills as an emergent, developmental phenomenon. We describe a connectionist model of concept formation and vocabulary growth that auto-associates image representations and their associated labels. The image representations consist of clusters of random dot figures, generated by distorting prototypes. Any given label is associated with a cluster of random dot figures. The network model is tested on its ability to reproduce image representations given input labels alone (comprehension) and to identify labels given input images alone (production). The model implements several well-documented findings in the literature on early semantic development; the occurrence of over- and under-extension errors; a vocabulary spurt; a comprehension/production asymmetr.
COMPUTER RECOGNITION OF THREE-DIMENSIONAL OBJECTS IN A VISUAL SCENE

Methods are presented 1) to partition or decompose a visual scene into the bodies forming it; 2) to position these bodies in three-dimensional space, by combining two scenes that make a stereoscopic pair; 3) to find the regions or zones of a visual scene that belong to its background; 4) to carry out the isolation of the objects in 1) when the input has inaccuracies. Running computer programs implement the methods and many examples illustrate their behavior. The input is a two-dimensional line-drawing of the scene, assumed to contain three-dimensional bodies possessing flat faces (polyhedra); some of them may be partially occluded. Suggestions are made for extending the work to curved objects. Some comparisons are made with human visual perception. The main conclusion is that it is possible to separate a picture or scene into the constituent objects exclusively on the basis of monocular geometric properties (on the basis of pure form); in fact, successful methods are shown.
Radio Telemetering from within the Body

In the article "Radio telemetering from within the body" by R. Stuart Mackay [Science 134, 1196 (20 Oct. 1961)] one line was omitted and another line was printed twice in the paragraph beginning just above the middle of column 1, page 1199. The first line of the paragraph is repeated in the fourth line. The first two sentences should have read: "The permissible radio-frequency deviation is limited to the bandwidth of the receiver if loss of signal is never to occur. Receivers can record higher-deviation signals by tracking them with a standard automatic frequency-control circuit, the frequency-discriminator signal then being the useful output (8)"(italicized words omitted).
An improved fault tolerant architecture at CMOS level

A previous realization of a fault tolerant architecture at CMOS level, while guaranteeing the correct behavior of the circuit both in the fault-free situation and in the presence of stuck-on faults, was characterized by a neither null nor +V/sub dd/ output voltage when faults occurred. An improved architecture is here presented, which by adding additional transistors, achieves the fault tolerance property without degrading the performance of the circuit in terms of output voltage and short circuit current.
Workflow Modelling of Coordinated Inter-Health-Provider Care Plans.

Workflow in healthcare, particularly for the shared and coordinated management of chronic illnesses, is very difficult to model. It is also difficult to support via current Clinical Information Systems and current information technologies. This dissertation contributes significant enhancements to the current methodologies for designing and implementing Workflow Management Systems (Wf MSs ) suitable for healthcare. The contribution comprises three interrelated aspects of workflow system architecture as follows:• Firstly, it shifts the emphasis of workflow modelling and enactment to a focus on goals, and the monitoring and facilitation of their achievement. • Secondly, it introduces the concept of self-modifying workflow in the context of health care planning, whereby explicit tasks in the goal-based care plan are devoted to assessing and modifying downstream workflow. • Thirdly, this dissertation proposes methodologies for identifying and dealing with tasks which overlap, subsume or interfere with other tasks elsewhere in a given workflow. The language and methods introduced in goal-based requirements engineering research have been carried into the domain of Wf MSs and adapted by the author as a mechanism for deriving workflow models that can be communicated and enacted by health care providers contributing to the shared care of a patient. A methodology is described, whereby a hierarchical goal-based view for the management of a chronic condition or conditions can be automatically translated into a workflow schema. This workflow schema contains subworkflows corresponding to each goal, together with specific tasks dedicated to monitoring, and, if necessary, altering the downstream workflow to optimally achieve each goal target.
Creating physically embodied agents using realistic human motion models

Many simulations are populated with physically embodied agents capable of taking physical actions in the virtual world. Creating these agents, or virtual humans, is demanding; not only must the agents demonstrate visual verisimilitude, but they must plan and act in a way that is consistent with that of humans, especially for training simulations in which the participants are attempting to learn real-world skills. This article discusses an approach for adapting agent decision-making techniques to accurately model the physical capabilities of human subjects. To achieve this, the authors rely on human movement data acquired with a motion capture apparatus to build physically realistic models of human movement. To aid agents' planning, the authors construct a physical capability model for the agents, an accurate estimate of the time required for a real human to perform various movement sequences. A cost map over the space of agent actions is calculated by creating and stochastically sampling motion graphs assembled from the human data exemplars. The agents can use this cost model during the planning process to select between equivalent goal-achieving plans. This technique leverages highly accurate movement information acquired from human subjects to create agents that plan in physically realistic ways.
Digital Rectal Examination (DRE); A Despised Clinical Sign among Medical Students?

 Abstract — Background: Digital Rectal Examination is used in the diagnosis of different urogenital and lower gastrointestinal pathology. The knowledge and practice of this is taught in the medical schools. Final year medical students who have completed their clinical rotations are expected to have learnt and practiced this in the course of their training. This study evaluates the knowledge and practice of DRE amongst final year medical students of University of Ibadan. Methodology:- A cross sectional study of 2 consecutive sets of final year medical students of University of Ibadan, was conducted just before their final examination using a semi-structure questionnaire. This was done at completion of all their clinical rotation. Result:- Out of the 120 medical students who consented to the study, 110 (92%) have been taught DRE. Eighty seven (79%) of those who have been taught, have done digital rectal examination.
A logical neural network that adapts to changes in the pattern environment

An online, unsupervised training algorithm is presented, which allows a logical neural network already trained to identify classes of objects to adapt to changes in the environment. This algorithm enables the system to operate continuously, without danger of overgeneralisation and displays useful noise-reduction properties. Results indicating its capabilities and characteristics in this adaptation task are described. The algorithm's self-organisation characteristics are also evaluated. <<ETX>>
A high frequency hybrid chaotic oscillator

This paper reports the experiments of a high frequency Digital Signal Processing chaos generator. Many methods have been proposed in analog domain. However the high accuracy matching of the transmitter and the receiver, especially in high frequencies, is difficult to achieve in real systems. In the other hand high speed digital signal processing technology is bandwidth limited in high frequency applications like wireless LANs, mobile communications, e.t. c. To overcome the above deficiencies of the above technologies the proposed circuit merges the two domains in hybrid integration.
Anomaly based Malicious Traffic Identification using Kernel Extreme Machine Learning (KELM) Classifier and Kernel Principal Component Analysis (KPCA)

Objectives: The rapid growth of new vulnerabilities causes the network by Denial of Service attack (DoS). The DoSattack causes traffic flow in network. Therefore it increases the difficulties to detect the DoSattack in traffic by means of misuse detection. The behavior patterns are analyzed in anomaly Anomaly detection to identify the attack. Methods: In detection of unknown worms anomaly detection is more comfortable than misuse detection. In this paper, hybrid optimization and extreme machine learning classifier is proposed for anomaly detection. This approach detects the DoSattack by analyzing the profiles of traffic patterns. Findings: Principal Component Analysis (PCA) is adopted in this approach to extract the feature from the dataset. A short time window is utilized to gather all features from packet headers. Extreme learning machine based HGAPSO is used to classify the unknown attack. Improvement: thus the proposed system is implemented as real-time. Performance evaluation shows that this approach provides 1.016s time consumption and 95 % accuracy tan existing approach during detection of DoSin network traffic.
A New Triple-Switch-Triple-Mode High Step-Up Converter With Wide Range of Duty Cycle for DC Microgrid Applications

DC microgrid is gaining attraction and a recent trend in distribution power generation system due to penetration of renewables (especially photovoltaic or fuel cell). In this paper, a new triple-switch-triple-mode high step-up converter (TSTM-HS converter) is presented for dc microgrid applications. In the proposed converter, voltage lift technique is employed and range of duty cycle is extended by incorporating an additional switch in converter circuitry. By doing this, high voltage conversion ratio is achieved without using a transformer, coupled inductor, and multiple stages of switched capacitors. Moreover, the TSTM-HS converter operated in three modes with two types of the duty cycles to achieve low to high voltage conversion without using high duty cycle for each switch. The effects of difference in the inductance values on the regulation and operating behavior of the TSTM-HS converter are discussed. The continuous conduction mode and discontinuous conduction mode characteristics of the TSTM-HS converter are discussed in detail with steady-state analysis and boundary condition. The comparison is provided to highlight the benefits of the TSTM-HS converter. The selection of semiconductor devices and the design of reactive components are discussed for the TSTM-HS converter. The experimental results of the proposed converter are provided which validate the theoretical approach, performance, and feasibility of converter.
Unified optimal linear estimation fusion. I. Unified models and fusion rules

This paper deals with data fusion for the purpose of estimation. Three fusion architectures are considered: centralized, distributed, and hybrid. A unified linear model and general framework for these three architectures are established. Optimal fusion rules in the sense of best linear unbiased estimation (BLUE), weighted least squares (WLS), and their generalized versions are presented for cases with either complete, incomplete, or no prior information. These rules are much more general and flexible than previous results. For example, they are in a unified form that are optimal for all the three fusion architectures with arbitrary correlation of local estimates or observation noises across sensors or across time. They are also in explicit forms convenient for implementation. The relationships among these rules are also presented.
Sexual and reproductive traits of the pearl oyster shrimp Pontonia margarita (Decapoda: Palemonidae), symbiotically inhabiting the mantle cavity of the rugose pen shell Pinna rugosa (Bivalvia: Pinnidae)

Symbiosis between decapods and mollusks provides a unique opportunity to examine some of the evolutionary strategies employed by marine invertebrates. We describe the sexual and reproductive traits of the pearl oyster shrimp, Pontoniamargarita Verril, 1869, found symbiotically inhabiting the mantle cavity of the rugose pen shell, Pinnarugosa Sowerby, 1835. Solitary males and females (ovigerous and non-ovigerous) and heterosexual pairs (with ovigerous and non-ovigerous females) were found in a total of 47 rugose pen shells collected from a sandy area with seagrass meadows on the southeastern coast of the Gulf of California, Mexico. The body length (BL) of female P.margarita was correlated with the shell volume of their rugose pen shell host. The sex ratio was female-biased (0.85M:1F). Female P.margarita were larger than their male counterparts in terms of BL, cephalothorax length (CL), and the maximum chelae length of the second pereopod (MCL). The CL and MCL were more strongly correlated for males (r = 0.70, p = 0.01). The number and volume of eggs per ovigerous female varied from 95 to 1,571 and from 5.46 ± 0.48 to 8.85 ± 0.97 mm3, respectively. Our results indicate polygamous behavior and social monogamy among P.margarita, and a short-term pairing system for their association with P.rugosa.
CMOS IC nanometer technology failure mechanisms

CMOS IC test targets are moving markedly with each nanometer technology node. Relatively stable defects, such as bridges and opens endure, but their detection is now often shrouded in a noisy environment with IC parameters that vary widely within the die, from die-to-die, wafer-to-wafer, or lot-to-lot. This variance in parameters introduces new concerns over failure mechanisms that laid mostly dormant for previous technologies. ICs can now fail from an "unlucky" distribution of parameters even though a defect is not present. Die-to-die reordering of critical timing paths is seen in modern ICs. This paper uses the defect-based approach to failure mechanisms that describes their electrical properties and then attempts to match a test method.
Online path planning under uncertainty

The authors deal with an online planning algorithm. The work is motivated by robot navigation and manipulation tasks in unstructured, dynamic environments. It is assumed that sensory information is incomplete and must be expanded and/or redefined by active sensing during an exploratory motion phase. Candidate targets are modeled as attractors, while obstacles are modeled as repellers. Path planning is reduced to an iterative Newton scheme that can readily adapt to changes in the environment and to new sensory information. Julia sets are used to detect and avoid chaotic convergence. <<ETX>>
Wireless networks of opportunity in support of secure field operations

Under the Defense Advanced Research Projects Agency (DARPA) funding for joint military and law enforcement technologies and Global Mobile Information Systems (GloMo), demonstrations were held in September 1996 of secure information transfer in support of military operations other than war and law enforcement (OOTW/LE), via wireless and wired technology. Wireless networks of opportunity encompassed building, campus, metropolitan, and national scales. Data was encrypted via FORTEZZA technology, for use over unsecured networks. Mechanisms for the guarded transport of data through the secret-high military tactical Internet were included, to support joint law enforcement and crisis management missions. A secure World Wide Web (WWW) browser formed the primary interface for information retrieval and submission. Both still and motion compressed video were demonstrated, along with secure voice transmission from laptop computers in the field. Issues of network bandwidth, air-time costs, and deployment status are discussed.