Miracle-dz/UniFAR-FTUs huggingface dataset:
Anatomical characterization of PDF‐tri neurons and peptidergic neurons associated with eclosion behavior in Drosophila

The peptidergic Pigment‐dispersing factor (PDF)‐Tri neurons are a group of non‐clock neurons that appear transiently around the time of adult ecdysis (=eclosion) in the fruit fly Drosophila melanogaster. This specific developmental pattern points to a function of these neurons in eclosion or other processes that are active around pupal–adult transition. As a first step to understand the role of these neurons, we here characterize the anatomy of the PDF‐Tri neurons. In addition, we describe a further set of peptidergic neurons that have been associated with eclosion behavior, eclosion hormone (EH), and crustacean cardioactive peptide (CCAP) neurons, to single cell level in the pharate adult brain. PDF‐Tri neurons as well as CCAP neurons co‐express a classical transmitter indicated by the occurrence of small clear vesicles in addition to dense‐core vesicles containing the peptides. In the tritocerebrum, gnathal ganglion and the superior protocerebrum PDF‐Tri neurites contain peptidergic varicosities and both pre‐ and postsynaptic sites, suggesting that the PDF‐Tri neurons represent modulatory rather than pure interneurons that connect the subesophageal zone with the superior protocerebrum. The extensive overlap of PDF‐Tri arborizations with neurites of CCAP‐ and EH‐expressing neurons in distinct brain regions provides anatomical evidence for a possible function of the PDF‐Tri neurons in eclosion behavior.
Workforce gender, company size and corporate financial support are predictors of availability of healthy meals in Danish worksite canteens

Abstract Objective Environmental strategies at worksites may help consumers change dietary behaviour towards a more healthy diet. The present study aimed to evaluate the availability of healthy meal options at Danish worksite canteens and to identify predictors of worksite canteens providing healthy meals. Design A self-administered questionnaire was randomly mailed to 1967 worksite canteen managers. Besides information and characteristics about the canteen and the worksite, the canteen managers specified the menus available. Two different health groups (Healthy and Less Healthy) were defined in three different meal categories (Sandwiches, Hot meals and Salads) as well as a combined category (Combined) combining all the three meal categories. The characteristics of the worksites were compared with regard to the different health groups. Setting Randomly selected Danish worksite canteens. Subjects 553 Danish worksite canteen managers replied, resulting in a response rate of 29 %. Results Only 12 % of the canteens applied to the Healthy group combining all the three meal categories. In particular, worksites with more than 75 % female employees served healthy menus on a frequent basis. The size of the worksite was positively correlated with more healthy meal options. Furthermore, the present study suggests a positive relationship between corporate financial support and the availability of healthy meal options. Conclusions Among the selected variables studied, workforce gender, company size and corporate financial support were significant predictors of the availability of healthy meal options in worksite canteens. More research is needed on the role that variance in organisation environment plays for the potential of worksite intervention, to make a difference in terms of healthy eating.
Morbidity of Staging Inframesenteric Paraaortic Lymphadenectomy in Locally Advanced Cervical Cancer Compared With Infrarenal Lymphadenectomy

Objective Extended-field chemoradiation is typically used for the management of patients with locally advanced cervical cancer. Given the low rate of skipped metastases above the inferior mesenteric artery, ilioinframesenteric dissection seems to be an acceptable pattern of paraaortic lymph node dissection (LND). Our objective is to compare the surgical morbidity of inframesenteric LND (IM-LND) with infrarenal LND (IR-LND). Methods In our center, all of the patients with locally advanced cervical cancer and negative magnetic resonance imaging and positron emission tomography–computed tomography imaging at the paraaortic level were offered laparoscopic staging including a diagnostic laparoscopy followed, if negative, by an extraperitoneal paraaortic lymphadenectomy. From January 2011 to September 2015, we included patients who had paraaortic LND from both common iliac bifurcations and divided them into 2 groups according to dissection pattern: to the inferior mesenteric artery (IM-LND) level or to the left renal vein (IR-LND) level. The perioperative and postoperative data were retrospectively recorded. Results A total of 119 women were included in our study: 56 in the IM-LND group and 63 in the IR-LND group. There was no difference in the patients' characteristics between groups. Regarding the surgical procedure, the operating time was shorter in the IM-LND group than the IR-LND group, 174 ± 50 minutes versus 209 ± 61 minutes (P = 0.001), respectively. There was no significant difference in intra- and postoperative complications, overall survival, or progression-free survival. Conclusions In our series, exclusive IM-LND surgery is faster than IR-LND and results in similar morbidity and survival rates. These results confirm the feasibility and the applicability of IM-LND to simplify the surgical procedure without impacting survival. More patients should be included in the study to demonstrate the lower rate of morbidity.
Sparse and Robust Reject Option Classifier using Successive Linear Programming

In this paper, we propose a new sparse and robust reject option classifier based on minimization of $l_1$ regularized risk under double ramp loss $L_{dr,\rho}$. We use DC programming to find the risk minimizer. The algorithm solves a sequence of linear programs to learn the reject option classifier. Moreover, we show that the risk under $L_{dr,\rho}$ is minimized by generalized Bayes classifier in the reject option setting. We also provide the excess risk bound for $L_{dr,\rho}$. We show the effectiveness of the proposed approach by experimenting it on several real world datasets.
Visualizing elements of order 7 in the Tate–Shafarevich group of an elliptic curve

We study the elliptic curves in Cremona’s tables that are predicted by the Birch–SwinnertonDyer conjecture to have elements of order 7 in their Tate–Shafarevich group. We show that in many cases these elements are visible in an abelian surface or abelian 3-fold.
Speech Recognition for the iCub Platform

This paper describes open source software (available at https://github.com/robotology/natural-speech) to build automatic speech recognition (ASR) systems and run them within the YARP platform. The toolkit is designed (i) to allow non-ASR experts to easily create their own ASR system and run it on iCub and (ii) to build deep learning-based models specifically addressing the main challenges an ASR system faces in the context of verbal human–iCub interactions. The toolkit mostly consists of Python, C++ code and shell scripts integrated in YARP. As additional contribution, a second codebase (written in Matlab) is provided for more expert ASR users who want to experiment with bio-inspired and developmental learning-inspired ASR systems. Specifically, we provide code for two distinct kinds of speech recognition: “articulatory” and “unsupervised” speech recognition. The first is largely inspired by influential neurobiological theories of speech perception which assume speech perception to be mediated by brain motor cortex activities. Our articulatory systems have been shown to outperform strong deep learning-based baselines. The second type of recognition systems, the “unsupervised” systems, do not use any supervised information (contrary to most ASR systems, including our articulatory systems). To some extent, they mimic an infant who has to discover the basic speech units of a language by herself. In addition, we provide resources consisting of pre-trained deep learning models for ASR, and a 2.5-h speech dataset of spoken commands, the VoCub dataset, which can be used to adapt an ASR system to the typical acoustic environments in which iCub operates.
Study of Optical Fiber Sensors for Cryogenic Temperature Measurements

In this work, the performance of five different fiber optic sensors at cryogenic temperatures has been analyzed. A photonic crystal fiber Fabry-Pérot interferometer, two Sagnac interferometers, a commercial fiber Bragg grating (FBG), and a π-phase shifted fiber Bragg grating interrogated in a random distributed feedback fiber laser have been studied. Their sensitivities and resolutions as sensors for cryogenic temperatures have been compared regarding their advantages and disadvantages. Additionally, the results have been compared with the given by a commercial optical backscatter reflectometer that allowed for distributed temperature measurements of a single mode fiber.
The Amount of Melanin Influences p16 Loss in Spitzoid Melanocytic Lesions: Correlation With CDKN2A Status by FISH and MLPA

Aims: The risk assessment of spitzoid lesions is one of the most difficult challenges in dermatopathology practice. In this regard, the loss of p16 expression and the homozygous deletion of CDKN2A, have been pointed in the literature as reliable indicators of high risk. However, these findings are poorly reproducible, and the molecular bases underlying the loss of p16 expression remain unclear. We aimed to identify the underlying events causing loss of CDKN2A/p16 in spitzoid tumors. Materials and Methods: We evaluated the immunohistochemical expression of p16, and the presence of CDKN2A genetic alterations detected through fluorescence in situ hybridization (FISH) and multiplex ligation-dependent probe amplification (MLPA), in a series of 130 Spitz nevi, 20 atypical spitzoid tumors, and 11 spitzoid melanoma. Results: We found a significant loss of p16 expression in cases with high amount of melanin content in the 3 groups (P<0.000001) and a similar proportion of p16-negative cases in the group of Spitz nevi and atypical spitzoid tumors. MLPA allowed the recognition of CDKN2A microdeletions, which correlated with p16 loss (P=0.01). MLPA and FISH were more accurate than immunohistochemistry to detect CDKN2A alterations; although contrary to MLPA, FISH fails to recognize CDKN2A microdeletions. Conclusions: According to our results, p16 expression may be useful in the study of cases with atypical features and low melanin content, but it has no value in highly pigmented spitzoid lesions.
The Transcription Factor MYB29 Is a Regulator of ALTERNATIVE OXIDASE1a1

The transcription factor MYB29 integrates various hormonal, growth, and stress signals with mitochondrial retrograde signaling in Arabidopsis. Plants sense and integrate a variety of signals from the environment through different interacting signal transduction pathways that involve hormones and signaling molecules. Using ALTERNATIVE OXIDASE1a (AOX1a) gene expression as a model system of retrograde or stress signaling between mitochondria and the nucleus, MYB DOMAIN PROTEIN29 (MYB29) was identified as a negative regulator (regulator of alternative oxidase1a 7 [rao7] mutant) in a genetic screen of Arabidopsis (Arabidopsis thaliana). rao7/myb29 mutants have increased levels of AOX1a transcript and protein compared to wild type after induction with antimycin A. A variety of genes previously associated with the mitochondrial stress response also display enhanced transcript abundance, indicating that RAO7/MYB29 negatively regulates mitochondrial stress responses in general. Meta-analysis of hormone-responsive marker genes and identification of downstream transcription factor networks revealed that MYB29 functions in the complex interplay of ethylene, jasmonic acid, salicylic acid, and reactive oxygen species signaling by regulating the expression of various ETHYLENE RESPONSE FACTOR and WRKY transcription factors. Despite an enhanced induction of mitochondrial stress response genes, rao7/myb29 mutants displayed an increased sensitivity to combined moderate light and drought stress. These results uncover interactions between mitochondrial retrograde signaling and the regulation of glucosinolate biosynthesis, both regulated by RAO7/MYB29. This common regulator can explain why perturbation of the mitochondrial function leads to transcriptomic responses overlapping with responses to biotic stress.
Navy Prototype Optical Interferometer Observations of the Double Stars Mizar A and Matar

We present a detailed analysis of two spectroscopic binaries based on new observations obtained with the Navy Prototype Optical Interferometer (NPOI). While the data calibration needs refinement, first results show the impressive potential of NPOI, both in terms of speed and precision, for imaging and modeling the orbits of spectroscopic binaries. We determine the orbital parameters of Mizar A (ζ1 Ursae Majoris) and Matar (η Pegasi), and derive masses and luminosities using published radial velocities and Hipparcos trigonometric parallaxes. The results on Mizar A are compared to earlier work done with the Mark III interferometer, while data from this instrument were combined with NPOI data in the Matar analysis.
An attempt to optimize the process of automatic point matching for homogeneous surface objects

: In recent years the progress in algorithms optimization has resulted in many solutions in the area of fully automatic reconstructing of 3D model of any object from a sequence of non-metric images. An important step in the formation of a 3D model is so-called matching process of homologous points in the sequence of images. This stage is still a bottleneck for the reconstruction of objects consisting of uniform surfaces, such as sculptures, reliefs, or even the human body. The solution may be to apply an artificial variety to surfaces by covering them with a random texture pattern. A wide range of multimedia projectors, with increasingly higher resolutions and luminosities, enables us to perform the projection of any texture on the object, and then to register it. In this article, we present the idea of creating an artificial pattern, a structure that will provide significant improvement of automatic point identification stage, and the proper mapping of homologous points in the sequence of images. While creating a pattern allowing easy feature extraction does not present much of a problem, assurance of its uniqueness for the whole object for matching purposes, requires a deliberate idea. Statistical formulation of the problem demonstrates the high efficiency of the method.
Comparative protein structure modeling by combining multiple templates and optimizing sequence-to-structure alignments

MOTIVATION Two major bottlenecks in advancing comparative protein structure modeling are the efficient combination of multiple template structures and the generation of a correct input target-template alignment. RESULTS A novel method, Multiple Mapping Method with Multiple Templates (M4T) is introduced that implements an algorithm to automatically select and combine Multiple Template structures (MT) and an alignment optimization protocol (Multiple Mapping Method, MMM). The MT module of M4T selects and combines multiple template structures through an iterative clustering approach that takes into account the 'unique' contribution of each template, their sequence similarity among themselves and to the target sequence, and their experimental resolution. MMM is a sequence-to-structure alignment method that optimally combines alternatively aligned regions according to their fit in the structural environment of the template structure. The resulting M4T alignment is used as input to a comparative modeling module. The performance of M4T has been benchmarked on CASP6 comparative modeling target sequences and on a larger independent test set, and showed favorable performance to current state of the art methods.
Mixed Link Networks

On the basis of the analysis by revealing the equivalence of modern networks, we find that both ResNet and DenseNet are essentially derived from the same "dense topology", yet they only differ in the form of connection: addition (dubbed "inner link") vs. concatenation (dubbed "outer link"). However, both forms of connections have the superiority and insufficiency. To combine their advantages and avoid certain limitations on representation learning, we present a highly efficient and modularized Mixed Link Network (MixNet) which is equipped with flexible inner link and outer link modules. Consequently, ResNet, DenseNet and Dual Path Network (DPN) can be regarded as a special case of MixNet, respectively. Furthermore, we demonstrate that MixNets can achieve superior efficiency in parameter over the state-of-the-art architectures on many competitive datasets like CIFAR-10/100, SVHN and ImageNet.
Non-Malleable Codes

In this report,based on the paper of Dziembowski et al.'s [DPW10], we explain how we can construct an e cient code that is nonmalleable with respect to modi cations that e ect each bit of the codeword arbitrarily. A variety of modi cations of codewords are considered such as ipping each bit of the codeword, leaving it untouched, or setting it to either 0 or 1 but independently of the value of the other bits of the codeword. The main idea for constructing an e cient non-malleable code with respect to bit wise tampering family FBit is using Algebraic Manipulation Detection code and a type of Linear Error-Correcting SecretSharing schemes.
Network Motif Discovery: A GPU Approach

The identification of network motifs has important applications in numerous domains, such as pattern detection in biological networks and graph analysis in digital circuits. However, mining network motifs is computationally challenging, as it requires enumerating subgraphs from a real-life graph, and computing the frequency of each subgraph in a large number of random graphs. In particular, existing solutions often require days to derive network motifs from biological networks with only a few thousand vertices. To address this problem, this paper presents a novel study on network motif discovery using Graphical Processing Units (GPUs). The basic idea is to employ GPUs to parallelize a large number of subgraph matching tasks in computing subgraph frequencies from random graphs, so as to reduce the overall computation time of network motif discovery. We explore the design space of GPU-based subgraph matching algorithms, with careful analysis of several crucial factors (such as branch divergences and memory coalescing) that affect the performance of GPU programs. Based on our analysis, we develop a GPU-based solution that (i) considerably differs from existing CPU-based methods in how it enumerates subgraphs, and (ii) exploits the strengths of GPUs in terms of parallelism while mitigating their limitations in terms of the computation power per GPU core. With extensive experiments on a variety of biological networks, we show that our solution is up to two orders of magnitude faster than the best CPU-based approach, and is around $20$ times more cost-effective than the latter, when taking into account the monetary costs of the CPU and GPUs used.
The Evolutionary Origins of Hierarchy

Hierarchical organization—the recursive composition of sub-modules—is ubiquitous in biological networks, including neural, metabolic, ecological, and genetic regulatory networks, and in human-made systems, such as large organizations and the Internet. To date, most research on hierarchy in networks has been limited to quantifying this property. However, an open, important question in evolutionary biology is why hierarchical organization evolves in the first place. It has recently been shown that modularity evolves because of the presence of a cost for network connections. Here we investigate whether such connection costs also tend to cause a hierarchical organization of such modules. In computational simulations, we find that networks without a connection cost do not evolve to be hierarchical, even when the task has a hierarchical structure. However, with a connection cost, networks evolve to be both modular and hierarchical, and these networks exhibit higher overall performance and evolvability (i.e. faster adaptation to new environments). Additional analyses confirm that hierarchy independently improves adaptability after controlling for modularity. Overall, our results suggest that the same force–the cost of connections–promotes the evolution of both hierarchy and modularity, and that these properties are important drivers of network performance and adaptability. In addition to shedding light on the emergence of hierarchy across the many domains in which it appears, these findings will also accelerate future research into evolving more complex, intelligent computational brains in the fields of artificial intelligence and robotics.
XIST/miR‐544 axis induces neuropathic pain by activating STAT3 in a rat model

An increasing number of studies have reported that lncRNAs are responsible for the development of neuropathic pain. In our current study, chronic constriction injury (CCI) rat models were established and we observed that lncRNA XIST was greatly increased. Knockdown of XIST can relieve pain characteristics including both mechanical and thermal hyperalgesia in CCI rats. Meanwhile, XIST down‐regulation could inhibit neuro‐inflammation by reducing expression of inflammatory cytokines including tumor necrosis factor (TNF)‐α, IL‐1β, and IL‐6 and in CCI rats. By performing bioinformatics technology, miR‐544 was predicted to have interactions with XIST and dual‐luciferase reporter assays validated the correlation between them. A negative correlation between miR‐544 and XIST was observed by carrying out XIST loss or gain of function tests. miR‐544 markedly alleviated neuropathic pain development in CCI rats via targeting inflammatory cytokines, which was reversed by XIST over‐expression. Moreover, STAT3 was manifested to be a target gene of miR‐544 by bioinformatics predictions and it was activated in CCI rats. Over‐expression of STAT3 was able to induce neuropathic pain and miR‐544 inhibited this process in vivo. Furthermore, XIST increased STAT3 expression by sponging miR‐544 in neuropathic pain development. To conclude, our present study indicated that XIST can contribute to neuropathic pain progression in rats through down‐regulating miR‐544 and up‐regulating STAT3. Our results suggested that XIST/miR‐544/STAT3 axis can serve as a novel therapeutic target in neuropathic pain development.