Miracle-dz/UniFAR-FTUs huggingface dataset:
Dynamics of axonal regeneration in adult and aging zebrafish reveal the promoting effect of a first lesion

Significance The posterior lateral line of zebrafish is a suitable system to study axonal regeneration in vivo because of the superficial location of neurons and targets, allowing one to follow reinnervation in live fish on a daily basis. Here we demonstrate the effectiveness and fidelity of regeneration throughout adulthood. We show that the latency before the nerve regenerates increases with age but is reduced after a second nerve cut at all ages, suggesting that a regeneration-promoting factor induced by the first cut facilitates regeneration on a second cut. We provide evidence that this factor remains present at the site of the first lesion for several days and is intrinsic to the neurons themselves. Axonal regeneration is a major issue in the maintenance of adult nervous systems, both after nerve injuries and in neurodegenerative diseases. However, studying this process in vivo is difficult or even impossible in most vertebrates. Here we show that the posterior lateral line (PLL) of zebrafish is a suitable system to study axonal regeneration in vivo because of both the superficial location and reproducible spatial arrangement of neurons and targets, and the possibility of following reinnervation in live fish on a daily basis. Axonal regeneration after nerve cut has been demonstrated in this system during the first few days of life, leading to complete regeneration within 24 h. However, the potential for PLL nerve regeneration has not been tested yet beyond the early larval stage. We explore the regeneration potential and dynamics of the PLL nerve in adult zebrafish and report that regeneration occurs throughout adulthood. We observed that irregularities in the original branching pattern are faithfully reproduced after regeneration, suggesting that regenerating axons follow the path laid down by the original nerve branches. We quantified the extent of target reinnervation after a nerve cut and found that the latency before the nerve regenerates increases with age. This latency is reduced after a second nerve cut at all ages, suggesting that a regeneration-promoting factor induced by the first cut facilitates regeneration on a second cut. We provide evidence that this factor remains present at the site of the first lesion for several days and is intrinsic to the neurons.
Large Scale Distributed Data Science from scratch using Apache Spark 2.0

Apache Spark is an open-source cluster computing framework. It has emerged as the next generation big data processing engine, overtaking Hadoop MapReduce which helped ignite the big data revolution. Spark maintains MapReduce's linear scalability and fault tolerance, but extends it in a few important ways: it is much faster (100 times faster for certain applications), much easier to program in due to its rich APIs in Python, Java, Scala, SQL and R (MapReduce has 2 core calls) , and its core data abstraction, the distributed data frame. In addition, it goes far beyond batch applications to support a variety of compute-intensive tasks, including interactive queries, streaming, machine learning, and graph processing. With massive amounts of computational power, deep learning has been shown to produce state-of-the-art results on various tasks in different fields like computer vision, automatic speech recognition, natural language processing and online advertising targeting. Thanks to the open-source frameworks, e.g. Torch, Theano, Caffe, MxNet, Keras and TensorFlow, we can build deep learning model in a much easier way. Among all these framework, TensorFlow is probably the most popular open source deep learning library. TensorFlow 1.0 was released recently, which provide a more stable, flexible and powerful computation tool for numerical computation using data flow graphs. Keras is a high-level neural networks library, written in Python and capable of running on top of either TensorFlow or Theano. It was developed with a focus on enabling fast experimentation. This tutorial will provide an accessible introduction to large-scale distributed machine learning and data mining, and to Spark and its potential to revolutionize academic and commercial data science practices. It is divided into three parts: the first part will cover fundamental Spark concepts, including Spark Core, functional programming ala map-reduce, data frames, the Spark Shell, Spark Streaming, Spark SQL, MLlib, and more; the second part will focus on hands-on algorithmic design and development with Spark (developing algorithms from scratch such as decision tree learning, association rule mining (aPriori), graph processing algorithms such as pagerank/shortest path, gradient descent algorithms such as support vectors machines and matrix factorization. Industrial applications and deployments of Spark will also be presented. ; the third part will introduce deep learning concepts, how to implement a deep learning model through TensorFlow, Keras and run the model on Spark. Example code will be made available in python (pySpark) notebooks.
Distributing Text Mining tasks with librAIry

We present librAIry, a novel architecture to store, process and analyze large collections of textual resources, integrating existing algorithms and tools into a common, distributed, high-performance workflow. Available text mining techniques can be incorporated as independent plug&play modules working in a collaborative manner into the framework. In the absence of a pre-defined flow, librAIry leverages on the aggregation of operations executed by different components in response to an emergent chain of events. Extensive use of Linked Data (LD) and Representational State Transfer (REST) principles are made to provide individually addressable resources from textual documents. We have described the architecture design and its implementation and tested its effectiveness in real-world scenarios such as collections of research papers, patents or ICT aids, with the objective of providing solutions for decision makers and experts in those domains. Major advantages of the framework and lessons-learned from these experiments are reported.
Using MRF approach to wetland classification of high spatial resolution remote sensing imagery: A case study in Xixi Westland National Park, Hangzhou, China

The accurate discrimination of distinct thematic classes using classification techniques developed for medium/low resolution images is not effective when apply to very high spatial resolution (HR) data (e.g. Quickbird, IKONOS) due to the spatial heterogeneity issue. In this paper, Markov random field (MRF) models, which are useful tools for integrating contextual (considering spatial dependence within and between pixels) information into classification process is used to model spatial heterogeneity for improving the classification accuracy. Two novel MRF approaches are evaluated using a Quickbird HR image covers Xixi National Wetland Park, Hangzhou, China. The experimental results show this method is effective to exact segmentation of land boundaries and suppress classification noises. In addition, the improved MRF models outperform than conventional method in terms of classification accuracy and time-efficiency.
The Influence of Arc-Flash and Fire-Resistant Clothing on Thermoregulation during Exercise in the Heat

We evaluated the effect of arc-flash and fire-resistant (AFR) clothing ensembles (CE) on whole-body heat dissipation during work in the heat. On 10 occasions, 7 males performed four 15-min cycling bouts at a fixed rate of metabolic heat production (400 W) in the heat (35°C), each separated by 15-min of recovery. Whole-body heat loss and metabolic heat production were measured by direct and indirect calorimetry, respectively. Body heat storage was calculated as the temporal summation of heat production and heat loss. Responses were compared in a semi-nude state and while wearing two CE styles: (1) single-piece (coveralls) and (2) two-piece (workpant + long-sleeve shirt). For group 1, there was one non-AFR single-piece CE (CE1STD) and three single-piece CE with AFR properties (CE2AFR, CE3AFR, CE4AFR). For group 2, there was one non-AFR two-piece CE (CE5STD) and four two-piece CE with AFR properties (CE6AFR, CE7AFR, CE8AFR, CE9AFR). The workpants for CE6AFR were not AFR-rated, while a cotton undershirt was also worn for conditions CE8AFR and CE9AFR and for all single-piece CE. Heat storage for all conditions (CE1STD: 328 ± 55, CE2AFR: 335 ± 87, CE3AFR: 309 ± 95, CE4AFR: 403 ± 104, CE5STD: 253 ± 78, CE6AFR: 268 ± 89, CE7AFR: 302 ± 70, CE8AFR: 360 ± 36, CE9AFR: 381 ± 99 kJ) was greater than the semi-nude state (160 ± 124 kJ) (all p ≤ 0.05). No differences were measured between single-piece uniforms (p = 0.273). Among the two-piece uniforms, heat storage was greater for CE8AFR and CE9AFR relative to CE5STD and CE6AFR (all p ≤ 0.05), but not CE7AFR (both p > 0.05). Differences between clothing styles were measured such that greater heat storage was observed in both CE1STD and CE2-4AFR relative to CE5STD. Further, heat storage was greater in CE2AFR and CE4AFR relative to CE6AFR, while it was greater in CE4AFR compared to CE7AFR. Body heat storage during work in the heat was not influenced by the use of AFR fabrics in the single- or two-piece uniforms albeit less heat was stored in the two-piece uniforms when no undershirt was worn. However, heat storage was comparable between clothing styles when an undershirt was worn with the two-piece uniform.
Packet Loss and Delay Measurement for MPLS Networks

Many service provider service level agreements (SLAs) depend on the ability to measure and monitor performance metrics for packet loss and one-way and two-way delay, as well as related metrics such as delay variation and channel throughput. This measurement capability also provides operators with greater visibility into the performance characteristics of their networks, thereby facilitating planning, troubleshooting, and network performance evaluation. This document specifies protocol mechanisms to enable the efficient and accurate measurement of these performance metrics in MPLS networks. [STANDARDS- TRACK]
Clients' pretreatment role expectations, the therapeutic alliance, and clinical outcomes in outpatient therapy.

OBJECTIVES The present study examined the associations between pretreatment role expectations, working alliance, and therapy outcome. A mediational model was hypothesized wherein the therapeutic alliance mediates the relationship between clients' pretreatment role expectations and psychotherapy outcome. METHOD Sixty-eight clients completed the Expectations About Counseling-Brief Form at pretreatment, the Working Alliance Inventory-Short Form Revised after Session 3, and the Outcome Questionairre-45 at both pretreatment and the final session. RESULTS All 3 expectations factors (Personal Commitment, Facilitative Conditions, Counselor Expertise) were related to the alliance. However, only expectations for Counselor Expertise were related to outcome, although this relationship did not appear to be mediated by the alliance. CONCLUSIONS Suggested research directions, clinical implications, and study limitations are discussed.
Simultaneous Wavelength- and Mode-Division (De)multiplexing for High-Capacity On-Chip Data Transmission Link

We present designs of wavelength-division-multiplexing (WDM) and mode-division-multiplexing (MDM) optical links using mode de/multiplexers (DE/MUXs) based on multimode interference (MMI) couplers with a tilt joint as a phase shifter. The properties of WDM-MDM links with three wavelengths and two optical modes are numerically studied by using 3-D beam propagation method. In the first design, the wavelength combiner is also an MMI coupler type. The insertion loss of the design is around 6 dB because of the inherent loss of the MMI combiner. The size of the main passive optical parts (mode DE/MUXs and wavelength combiner) of the design is only 10.4 × 114.2 μm2, making the design promising for future compact and high-capacity optical interconnection applications. In another design, arrayed waveguide gratings are used for wavelength multiplexing, leading to a lower insertion loss of the optical connections. For both designs, the mode crosstalk between the two different modes for the same wavelength are below -22 dB.
Uniform belief propagation processor for massive MIMO detection and GF(2n) LDPC decoding

Both massive multiple-input multiple-output (MI-MO) technique and low-density parity-check (LDPC) codes have been considered as indispensable parts of 5G wireless. To improve the hardware efficiency and flexibility, a uniform belief propagation (BP) processor which can take care of both massive MIMO detection and GF(2n) LDPC decoding is proposed. To this end, the unified BP representation for BP detection and decoding is first proposed. Folding technique has been considered for further improvement of hardware efficiency and flexibility. For better illustration, a folded prototype of (8, 4) GF(2) LDPC coded 2×2 4-QAM MIMO system is implemented with FPGA. Numerical simulations and implementation results have demonstrated the feasibility of the proposed design methodology.
Chemical Signals from Host Plant and Sexual Behavior in a Moth

In the phytophagous corn earworm, Helicoverpa (Heliothis) zea, females delay their reproductive behaviors until they find a suitable host on which to deposit their eggs. Perception of volatile chemical signals from corn silk triggers the production of sex pheromone followed by its release, which leads to mating. Several natural corn silk volatiles, including the plant hormone ethylene, induced pheromone production in H. zea females. Because H. zea larvae feed on the fruiting parts of a wide variety of hosts, ethylene, which is associated with fruit ripening, could act as a common cue.
Online Display Advertising: Modeling the Effects of Multiple Creatives and Individual Impression Histories

Online advertising campaigns often consist of multiple ads, each with different creative content. We consider how various creatives in a campaign differentially affect behavior given the targeted individual's ad impression history, as characterized by the timing and mix of previously seen ad creatives. Specifically, we examine the impact that each ad impression has on visiting and conversion behavior at the advertised brand's website. We accommodate both observed and unobserved individual heterogeneity and take into account correlations among the rates of ad impressions, website visits, and conversions. We also allow for the accumulation and decay of advertising effects, as well as ad wearout and restoration effects. Our results highlight the importance of accommodating both the existence of multiple ad creatives in an ad campaign and the impact of an individual's ad impression history. Simulation results suggest that online advertisers can increase the number of website visits and conversions by varying the creative content shown to an individual according to that person's history of previous ad impressions. For our data, we show a 12.7% increase in the expected number of visits and a 13.8% increase in the expected number of conversions.
Models of Neuron Coding in Retinal Ganglion Cells and Clustering by Receptive Field

One of the fundamental questions in neuroscience today is understanding the functional relationship between stimuli and the firing of neurons, often referred to as the neuron coding problem. [1] In this report, we consider both biologicallyinspired Maximum-Likelihood estimators and feedforward neural networks in order to learn models of the retina and its response to visual stimuli. Data is taken from recordings of retinal ganglion cells taken by Steve Baccus’s lab at Stanford [2]. A comparison of these models is presented based on the Pearson Correlation Coefficient between the true test response of a neuron, and the models’ predicted outputs. Using this metric, we show that the deep Artificial Neural Network used has superior generalization to unseen data, as compared with the probabilistic models. Using parameters fit to a Linear-NonlinearPoisson model, we also present a hierarchical clustering of learned space-time receptive fields of all 28 recorded retinal neurons resulting in six primary clusters.
Stromelysin-3 Induction and Interstitial Collagenase Repression by Retinoic Acid

Human stromelysin-3 and interstitial collagenase are matrix metalloproteinases whose expression by stromal cells in several types of carcinomas has been associated with cancer progression. We compared here the regulation of the expression of both proteinases by retinoids in human fibroblasts. Physiological concentrations of retinoic acid were found to simultaneously induce stromelysin-3 and repress interstitial collagenase. In both cases, the involvement of a transcriptional mechanism was supported by run-on assays. Furthermore, in transient transfection experiments, the activity of the stromelysin-3 promoter was induced by retinoic acid through endogenous receptors acting on a DR1 retinoic acid-responsive element. The ligand-dependent activation of the receptors was also investigated by using selective synthetic retinoids, and we demonstrated that retinoic acid-retinoid X receptor heterodimers were the most potent functional units controlling both stromelysin-3 induction and interstitial collagenase repression. However, specific retinoids dissociating the transactivation and the AP-1-mediated transrepression functions of the receptors were found to repress interstitial collagenase without inducing stromelysin-3. These findings indicate that such retinoids may represent efficient inhibitors of matrix metalloproteinase expression in the treatment of human carcinomas.
The effect of a 12-month weight loss intervention on vitamin D status in severely obese Caucasians and African American adults

Vitamin D deficiency is a potential risk factor for several chronic conditions, including cardiovascular disease, diabetes and immune disorders. Several studies have found an association between Vitamin D deficiency and obesity, yet it is unclear whether Vitamin D contributes to obesity, or obesity itself causes Vitamin D deficiency. The purpose of this study is to determine the relationship between obesity and Vitamin D status and to examine the effects of weight loss and physical activity on Vitamin D status in severely obese Caucasians and African Americans. 50 class II and class III obese women participated in a 12-month diet and exercise intervention. Vitamin D status was examined at baseline, 6 and 12 months to determine the relationship between Vitamin D and weight loss, fat loss, race and physical activity. At baseline, both the Class I and Class III obese subjects were considered Vitamin D insufficient (20-30 ng/mL). The Class II subjects were considered deficient ( 30 ng/mL). Caucasians in the Class I and III obese groups had significantly higher Vitamin D than African Americans. Vitamin D increased significantly following 6 months of weight loss. There was no significant relationship between change in Vitamin D and change in body weight or body fat. Vitamin D decreased at 12 months despite a period of weight maintenance yet remained significantly greater than baseline. Meal replacement shakes containing Vitamin D were taken twice per day from baseline to 6 months and once per day from 6-12 months, contributing to the increase in Vitamin D at 6 months and 12 months. Throughout the intervention, Vitamin D status was significantly greater in Caucasians than African Americans. There was no relationship between Vitamin D status and physical activity at 6 or 12 months. The results of this study confirm that Vitamin D deficiency or insufficiency is related to degree of adiposity and is more prevalent in African Americans than Caucasians. Moreover, a dietary weight loss intervention significantly increased Vitamin D in severely obese women, indicating that lower Vitamin D in obesity is amenable to weight loss intervention.
Inscription of Fiber Bragg Grating Arrays in Pure Silica Suspended Core Fibers

Fiber Bragg grating (FBG) arrays in pure silica four-leaf-clover-shaped suspended core fibers were inscribed with two-beam interference and a deep UV femtosecond laser source. The target fibers are pure silica and do not contain any dopants, nor were they treated with hydrogen before grating inscription. The inscription method is appropriate to measure the effective mode field index of the fiber and allows confinement factors of the guided modes to be derived. Applications of such FBGs can be expected especially for fiber sensing.
A Robust Secure DS-AKA with Mutual Authentication for LTE-A

The authentication and key agreement (AKA) protocol for Long Term Evolution-Advanced (LTE-A) which is proposed to solve the vulnerabilities found in previous communication systems such as 2G and 3G systems. They still contain the vulnerabilities like redirection and man-in-the-middle attack. They gave way to the eavesdroppers to utilize and misuse the subscribers resources and make the communication system to mischarge the customers. In this paper we propose an authentication key agreement algorithm which is secure and able to solve the vulnerabilities in the communication system. This reduces the bandwidth utilization for authentication and number of transactions required for authentication is reduced.
Excitation Winding Short-Circuits in Hybrid Excitation Permanent Magnet Motor

This paper presents two short-circuit fault models of a hybrid excitation flux switching permanent magnet machine, i.e., excitation phase short-circuit and interturn short-circuit in excitation windings. Two-dimensional finite element (FE) method is used to calculate the major parameters, such as armature and excitation inductances, which are not only functions of rotor position, but also of armature and excitation currents. Moreover, in case of short-circuits, the variations of armature and excitation currents are often significant. This in turn leads to an important change in winding inductances. Therefore, in order to precisely predict machine performance under short-circuit conditions, the use of inductances versus rotor position and RMS currents is essential. With the obtained FE results, two MATLAB/Simulink-based models are established. Then, the previously mentioned short-circuits have been studied and their influences on electromagnetic performances, such as armature and excitation currents, speed and torque, armature and excitation copper losses, stator and rotor core iron losses, as well as permanent magnet (PM) eddy current losses are analyzed. Experiments have been carried out to validate the simulations.
Constitutive expression of the poplar WRKY transcription factor PtoWRKY60 enhances resistance to Dothiorella gregaria Sacc. in transgenic plants.

WRKY proteins are involved in various physiological processes in plants, especially in coping with diverse biotic and abiotic stresses. However, limited information is available on the roles of specific WRKY transcription factors in poplar defense. In this study, we reported the characterization of PtoWRKY60, a Group IIa WRKY member, from Populus tomentosa Carr. The gene expression profile of PtoWRKY60 in various tissues showed that it significantly accumulated in old leaves. Phylogenetic analyses revealed that PtoWRKY60 had a close relationship with AtWRKY18, AtWRKY40 and AtWRKY60. PtoWRKY60 was induced mainly by salicylic acid (SA) and slightly by Dothiorella gregaria Sacc. , jasmonic acid, wounding treatment, low temperature and salinity stresses. Overexpression of PtoWRKY60 in poplar resulted in increased resistance to D. gregaria. The defense-associated genes, such as PR5.1, PR5.2, PR5.4, PR5.5 and CPR5, were markedly up-regulated in transgenic plants overexpressing PtoWRKY60. These results indicate that PtoWRKY60 might be partly involved in the signal transduction pathway initiated by SA in Populus.