Miracle-dz/UniFAR-FTUs huggingface dataset:
PLXNA1 and PLXNA3 cooperate to pattern the nasal axons that guide gonadotropin-releasing hormone neurons

ABSTRACT Gonadotropin-releasing hormone (GnRH) neurons regulate puberty onset and sexual reproduction by secreting GnRH to activate and maintain the hypothalamic-pituitary-gonadal axis. During embryonic development, GnRH neurons migrate along olfactory and vomeronasal axons through the nose into the brain, where they project to the median eminence to release GnRH. The secreted glycoprotein SEMA3A binds its receptors neuropilin (NRP) 1 or NRP2 to position these axons for correct GnRH neuron migration, with an additional role for the NRP co-receptor PLXNA1. Accordingly, mutations in SEMA3A, NRP1, NRP2 and PLXNA1 have been linked to defective GnRH neuron development in mice and inherited GnRH deficiency in humans. Here, we show that only the combined loss of PLXNA1 and PLXNA3 phenocopied the full spectrum of nasal axon and GnRH neuron defects of SEMA3A knockout mice. Together with Plxna1, the human orthologue of Plxna3 should therefore be investigated as a candidate gene for inherited GnRH deficiency. Highlighted Article: PLXNA1 and PLXNA3 convey the pathfinding of olfactory and vomeronasal axons as a prerequisite for neuroendocrine neurons to migrate into the hypothalamus and release gonadotropins into the circulation.
The current status and future of andrology: A consensus report from the Cairo workshop group

In attempting to formulate potential WHO guidelines for the diagnosis of male infertility, the Evidence Synthesis Group noted a paucity of high‐quality data on which to base key recommendations. As a result, a number of authors suggested that key areas of research/evidence gaps should be identified, so that appropriate funding and policy actions could be undertaken to help address key questions.
Artificial Neural Network for Composite Hardness Modeling of Cu/Si Systems Fabricated Using Various Electrodeposition Parameters

Copper coatings are produced on silicon wafer by electrodeposition (ED) for various cathode current densities. The resulting composite systems consist of 10 μm monolayered copper films electrodeposited from sulphate bath on Si wafers with sputtered layers of Cr/Au. Hardness measurements were performed to evaluate properties of the composites. The composite hardness (Hc) was characterized using Vickers microindentation test. Then, an artificial neural network (ANN) model was used to study the relationship between the parameters of metallic composite and their hardness. Two experimental values: applied load during indentation test and current density during the ED process were used as the inputs to the neural network. Finally, the results of the composite hardness (experimental and predicted) were used to estimate the film hardness (Hf) of copper for each variations of the current density. This article shows that ANN is an useful tool in modeling composite hardness change with variation of experimental parameters predicting hardness change of composite Si/Cu with average error of 6 %. Using created ANN model it is possible to predict microhardness of Cu film for current density or indentation load for which we do not have experimental data.
Deep convolutional neural network-based feature extraction for steganalysis of content-adaptive JPEG steganography

Abstract. Deep learning-based steganalysis techniques have significantly progressed in recent years. Compared with typical steganalysis methods using rich model features and classifiers, deep learning-based steganalysis methods usually train a deep convolutional neural network (CNN) as the steganography detector. One advantage of a deep CNN is the strong capability for discriminative feature learning. The input feature map of the fully connected layer is the steganalysis feature learned using the deep CNN. We can, therefore, extract the steganalysis feature based on the trained deep CNN. Compared with steganalysis features constructed by hand, the extraction of steganalysis features using a deep CNN can take advantage of the strong feature-learning capability of such a network. Therefore, two types of typical steganalysis frameworks are first compared. Then, a deep CNN for steganalysis feature learning is constructed, and the setting of the image preprocessing layer is discussed. Next, the detection performances of the different learned steganalysis features are compared. Finally, the detailed extraction process of the proposed learned steganalysis feature is described. The experiment results show that the proposed steganalysis method, combining learned and handcrafted steganalysis features, can significantly improve the detection performance for content-adaptive JPEG steganography.
Telemetry Vibration Signal Analysis and Fault Detection based on Multi-scale Permutation Entropy

Aiming at the characteristics of strong noise and non-stationarity of telemetry vibration signals, a multi-scale entropy-based telemetry vibration signal analysis and fault detection method was proposed. Firstly, the collected signals were modified with zero-drift and tendency eliminating. Secondly, the mutual information and Cao’s algorithm were used to select the delay time and embedding dimension, we could have more excellent performance to distinguish the abnormities of telemetry vibration signal through this step. Finally, the partial mean of multi-scale permutation entropy of all signals was calculated, which were used to distinguish the abnormities of telemetry vibration signal. The measured data demonstrated the effectiveness of this method.
Optimization Makes Estimation Much More Worse

Mean-variance optimization as a modern portfolio theory is a major model for theoretical purposes, however, in practice portfolio managers don’t have enough interest despite some other ad hoc methods for many reasons such as estimation errors. Recently, the significance of modern portfolio theory has been analyzed that it doesn’t beat the simple naive 1/N rule not only in many real empirical databases but also in a simulation. By this paper, due to inherent weakness of Sharpe ratio we first express more common use and adjusted measurements such as adjusted expected utility of portfolio under ambiguity aversion to analyze their effects on portfolio optimization after this consideration, because using only sample mean and variance (Sharpe ratio) to evaluate performance value for the portfolio models may be subject to considerable bias. Second, we propose a new model based on the new measurement (adjusting ambiguity Sharpe ratio) to improve portfolio optimization problem. Our result states that by using the new measurement mean- variance optimization beats the naive rule by applying the adjusted measurement and also the novel model outperforms Markowitz in terms of Sharpe ratio while the interesting is that for adjusting Sharpe ratio inverse result exists. Therefore, our study expresses optimization makes estimation almost worse when we try to use a measurement as an optimization target. Keywords: portfolio selection, optimization, measurement, Sharpe ratio.
EARTHQUAKE TRIGGERING BY STATIC, DYNAMIC, AND POSTSEISMIC STRESS TRANSFER

▪ Abstract Earthquake triggering is the process by which stress changes associated with an earthquake can induce or retard seismic activity in the surrounding region or trigger other earthquakes at great distances. Calculations of static Coulomb stress changes associated with earthquake slip have proven to be a powerful tool in explaining many seismic observations, including aftershock distributions, earthquake sequences, and the quiescence of broad, normally active regions following large earthquakes. Delayed earthquake triggering, which can range from seconds to decades, can be explained by a variety of time-dependent stress transfer mechanisms, such as viscous relaxation, poroelastic rebound, or afterslip, or by reductions in fault friction, such as predicted by rate and state constitutive relations. Rapid remote triggering of earthquakes at great distances (from several fault lengths to 1000s of km) is best explained by the passage of transient (dynamic) seismic waves, which either immediately induce .
THE INFLUENCE OF CHANGES IN SPRINT ABlLlN ON THE SLED VELOCIN PROFILE DURING THE SKELETON START

Sprint times are key predictors of skeleton start petformanoe, but the effect of enhancing sprint ability on the development of sled velocity is unknown. Twelve well-trained skeleton athletes performed three dry-land push-starts and three 30-m sprints before and after 16 training weeks. Sled velocity profiles were characterised using three descriptors (pre-load velocity, pre-load distance and load effectiveness) and a sled acceleration index was used to evaluate performance. Increases in pre-load velocity and distance were related to improved sprint times. However, enhanced sprint ability did not guarantee a faster start as reductions in load effectiveness were also obsewed when higher velocities were attained. Coaches could supplement physical conditioning with load technique training to potentially improve the transfer of training-induced sled velocity increases across the loading phase.
Chinese Students¡¯ Knowledge of Environmentally and Socially Sustainable Apparel and Sustainable Purchase Intentions

Although many studies have focused on the relationship between consumersi¯ purchase intentions and their knowledge and attitudes of socially and environmentally responsible issues pertaining to the apparel and textiles (AT) industry, few studies have focused on consumers outside the US and UK. Therefore, the purpose of this study was to better understand the sustainability knowledge, attitudes, and purchasing intentions of Chinese consumers. A paper questionnaire consisting of approximately 80 questions and five scales was given to 52 Chinese undergraduate students enrolled in a course at a university located in the Zhejiang province of China during the summer of 2015. As a result of the data analysis, the Chinese students were much more informed of environmental issues within the AT industry as compared to issues of social responsibility, yet also reported strong attitudes regarding the treatment and safety of workers in AT production and how these issues might influence their purchasing intentions.
Author ' s personal copy

Dispersal limitations contribute to shaping plant distribution patterns and thus are significant for biodiversity conservation and urban ecology. In fleshy-fruited plants, for example, any preference of frugivorous birds affects dispersal capacities of certain fruit species. We conducted a removal experiment with fruits of Ilex aquifolium, a species that is currently expanding its range margin in northern Europe in response to climate change. The species is also a popular ornamental tree and naturalization has been observed in many parts of its range. Fruits of native I. aquifolium and of three cultivars were offered to birds at the expanding range margin in urban habitats in eastern Denmark. The four fruit types were removed at different rates and red fruits were preferred over a yellow cultivar. Small fruit diameter was positively related to fruit removal, and removal was faster under tree canopies compared with open habitats. The preference for red cultivars compared with native I. aquifolium may contribute to naturalization and potential invasion of garden escapes. Preferential foraging under closed canopies indicates trees and shrubs as recruitment foci for fleshy-fruited plants in urban landscapes. The results should be included in urban forestry and planting of potentially invasive ornamental species. © 2011 Elsevier GmbH. All rights reserved.
Prediction model for successful radiocephalic arteriovenous fistula creation in patients with diabetic nephropathy

Arteriovenous fistula (AVF) is the most appropriate vascular access for all chronic kidney disease patients for hemodialysis. However, patients with diabetic nephropathy are at increased risk for primary failure after AVF creation, mainly due to atherosclerosis and calcification of blood vessels. We conducted this study to find out the risk factors for primary failure of radiocephalic AVF in end-stage renal disease (ESRD) patients due to diabetic nephropathy and develop a risk predicting model. This study was conducted at a tertiary care teaching hospital of South India. Patients with ESRD due to diabetic nephropathy whom underwent left radiocephalic AVF at wrist were enrolled. Risk factors for primary failure were analyzed by univariate and multivariate logistic regression models. Sixty-six patients were included in the study. Thirty-one patients had a primary failure. Independent risk factors for primary failure were palpable vessel wall of the radial artery (P = 0.003, odds ratio [OR] = 15.317), smaller radial artery diameter (P = 0.001, OR = 16.526), radial artery peak systolic velocity (PSV) <45 cm/s (P = 0.005, OR = 8.494), and linear radial artery calcification (P = 0.006, OR = 7.942). The risk predicting model obtained by adding the score given for each risk factors (vessel wall not palpable = 0, palpable = 1, no linear calcification in digital X-ray = 0, linear calcification = 1, PSV ≥45 cm/s = 0, <45 cm/s = 1 and 2.5 - radial artery diameter in mm) had an area under receiver-operating characteristic curve of 0.886. Cutoff score of 1.5 had sensitivity of 83.9% and specificity of 80.0% for primary failure. Risk predicting model for primary failure based on condition of the vessel wall on palpation, radial artery diameter, flow velocity, and calcification may be helpful for suitable patient selection.
A Dual-Band Antenna Array with High Gain and Miniaturized Structure

This paper presents a dual-band antenna array with high gain and miniaturized structure which can be applicated to 5G communication systems. The antenna array is composed of two monopole elements. By protruding the ground branches in the metal plane of the antenna array, the isolation between these two elements has been improved greatly and the size has been reduced. The fabricated sample is measured and the results are in perfect accordance with simulation. These results show the designed antenna array with dual operating frequency band from 3.23 GHz to 4.16 GHz and from 4.6 GHz to 5.54 GHz. Its isolation is lower than -15 dB which covers the middle-frequency band of commercial 5G system. Especially, the size of proposed antenna array is 42×34×1.6 mm3 only. It can be used in handheld wireless devices in the 5G application.
Lifted Relational Variational Inferences

We present a lifted inference algorithm for relational hybrid graphical models. Hybrid graphical models with continuous and discrete variables naturally represent many real-world applications in robotics, financial market predictions, and weather analysis. Inference with such large models is challenging because relational structures deteriorate rapidly with current inference procedures. The main contribution of this paper is a relational variational-inference lemma that enables factoring density functions into a mixture of independent identically distributed multi-valued Bernoulli trials. This lemma enables a relational factoring step that takes hybrid ground potentials and finds a close to optimal lifted relational model for the joint density. This step is then used for efficient inference without referring to ground random variables. The new method allows us to build various efficient inference algorithms. As an example, we provide a lifted Markov Chain Monte Carlo (MCMC) algorithm that requires fewer samples and generates each sample faster than possible before. We provide an error analysis of the variational method when applying to relational models. Our approach is applicable to general large relational models.
Association of Sex With Outcomes in Patients Undergoing Percutaneous Coronary Intervention: A Subgroup Analysis of the GLOBAL LEADERS Randomized Clinical Trial.

Importance Women experience worse ischemic and bleeding outcomes after percutaneous coronary intervention (PCI). Objectives To assess the association of sex with patient outcomes at 2 years after contemporary PCI and with the efficacy and safety of 2 antiplatelet strategies. Design, Setting, and Analysis This study is a prespecified subgroup analysis of the investigator-initiated, prospective, randomized GLOBAL LEADERS study evaluating 2 strategies of antiplatelet therapy after PCI in an unselected population including 130 secondary/tertiary care hospitals in different countries. The main study enrolled 15 991 unselected patients undergoing PCI between July 2013 and November 2015. Patients had an outpatient clinic visit at 30 days and 3, 6, 12, 18, and 24 months after the index procedure. Data were analyzed between January 1, 2019, and March 31, 2019. Interventions Eligible patients were randomized to either the experimental or reference antiplatelet strategy. Experimental strategy consisted of 1 month of dual antiplatelet therapy (DAPT) followed by 23 months of ticagrelor monotherapy, while the reference strategy comprised of 12 months of DAPT followed by 12 months of aspirin monotherapy. Main Outcomes and Measures The primary efficacy end point was the composite of all-cause mortality and new Q-wave myocardial infarction at 2 years. The secondary safety end point was Bleeding Academic Research Consortium type 3 or 5 bleeding. Results Of the 15 968 patients included in this study, 3714 (23.3%) were women. The risk of the primary end point at 2 years was similar between women and men (adjusted hazard ratio [HR], 1.00; 95% CI, 0.83-1.20). Compared with men, women had higher risk of Bleeding Academic Research Consortium type 3 or 5 bleeding (adjusted HR, 1.32; 95% CI, 1.04-1.67) and hemorrhagic stroke at 2 years (adjusted HR, 4.76; 95% CI, 1.92-11.81). At 2 years, there was no between-sex difference in the efficacy and safety of the 2 antiplatelet strategies. At 1 year, compared with DAPT, ticagrelor monotherapy was associated with a lower risk of bleeding in men (HR, 0.72; 95% CI, 0.53-0.98) but not in women (HR, 1.23; 95% CI, 0.80-1.89; P for interaction = .045). Conclusions and Relevance Compared with men, women experienced a higher risk of bleeding and hemorrhagic stroke after PCI. The effect of 2 antiplatelet strategies on death and Q-wave myocardial infarction following PCI did not differ between the sexes at 2 years. Trial Registration ClinicalTrials.gov identifier: NCT01813435.
Lightweight Polygonal Approximation-Based ECG Signal Processing Platform

An electrocardiogram (ECG) signal is one of the most important bio-signals because it is caused by the heart's electrical activity. Therefore, ECG-signal analysis provides information about the heart's condition, especially heart disease. For ECG-signal processing, the original method applied to Internet-of-Things edge devices (such as wearable devices) is server-centric digital signal processing. Edge devices have some restrictions, such as small memory size, limited performance, and poor power supply. Although these devices perform only simple processing, including data acquisition and transmission, the devices' power consumption is high because of a large amount of communication. To solve this problem, we propose a polygonal approximation-based ECG-signal processing platform that is lightweight enough to be implemented in edge devices. In this platform, the ECG data are compressed to a small number of vertices by polygonal approximation, and only vertices are transmitted to the server. Therefore, the amount of communication decreases, thereby reducing the edge device's power consumption. The proposed platform was validated on a virtual edge device, which consists of a RaspberryPi 3 model B microcontroller (MCU) and HealthyPi v3. Results showed a 98% reduction in power consumption compared to a server-centric digital signal processor.
Common Deoxyribonucleic Acid Sequences in Mycoplasma genitalium and Mycoplasma pneumoniae Genomes

Southern blot hybridization of digested deoxyribonucleic acids (DNAs) of Mycoplasma genitalium, M. pneumoniae, and M. gallisepticum with probes made of total DNA of any one of these mycoplasmas revealed hybridization bands additional to those containing ribosomal ribonucleic acid (rRNA) gene sequences, which were identifiable by specific rRNA gene probes. The number and intensity of these additional bands were most pronounced with the M. genitalium-M. pneumoniae pair, which shares major antigenic determinants. Hybridization with M. pulmonis and Spiroplasma citri DNAs as probes revealed only the rRNA gene bands in digested DNAs of M. genitalium, M. pneumoniae, and M. gallisepticum. DNA-DNA hybridization tests in solution, with M. genitalium and M. pneumoniae DNA as probes, corroborated the Southern blotting data by showing the highest homology values between M. genitalium and M. pneumoniae (6.5 to 8.1%), lower with M. gallisepticum (3.5 to 4.0%), and lowest with S. citri (0.5 to 0.9%). The new hybridization approach provides visual evidence for genetic relatedness between M. genitalium and M. pneumoniae and may facilitate the identification and cloning of genomic DNA segments carrying genes shared by two or more mycoplasmas.
Value and Limitations of Analogs in Teaching Mathematics.

Analogical reasoning is frequently used in acquisition of mathematical concepts. Concrete representation used to teach mathematics are essentially analogs of mathematical concepts, and it is argued that analogies enter into mathematical concept acquisition in numerous other ways as well. According to Gentner's theory, analogies entail a structure-preserving mapping from a base or source to the ta:get. Although concrete aids can provide valuable assistance to concept acquisition, their oft-noted failure to provide the anticipated benefits has been a source of some puzzlement. It is suggested that the reason for the failure may be the processing loads imposed by structure mapping. Some representative mathematical concepts are examined, together with typical concrete representations, and the nature of the processing loads analyzed. These loads can be reduced by recoding concepts into more abstract form, but it is argued that structure mapping also plays a role in abstraction. Analysis of this process provides insight into sources of difficulty, and recommendations are made for improving the efficiency of instruction. Thirty-nine references arc listed. (Author/YP) **************************A******************************************** A Reproductions supplied by EDRS are the best t;lat can be made from the original document. *********************************************************************** Value and Limitations of Analogs in Teaching Mathematics Graeme S. Halford and Gillian M. Boulton-Lewis University of Queensland and Brisbane College of Advanced Education U.S. DEPARTMENT OF EDUCATION Office of Educatronal Researen and Improvement EDUCATIONAL RESOURCES INFORMATION CENTER tERt() Trus document nas teen reproduceu as received from the person or organqatron ongInating if C Minor changes have been made to unprove reproduction quality Popnts of new or opinions stated this doc u merit do not neCassahly rep-wen} offic$04 Of RI postion or pore', 'PERMISSION TO REPRODUCE THIS MATERIAL HAS BEEN GRANTED BY Cit-raeme-S OtraSprA TO THE EDUCATIONAL RESOURCES INFORMATION CENTER (ERIC). " Paper presented to the Third Conference of the European Association for Research on Learning and Instruction, Madrid, Spain, September 4-7, 1989. To be published in A. Demetriou and M. Shayer (Eds.), (title not known), London: Routledge and Kegan Paul. Running head: Analogs in Mathematics This work was supported by a grant from the Australian Research Grants Scheme. Author's address: Professor Graeme Halford, Psychology Department, University of Queensland, St. Lucia, 4067, AUSTRALIA