Miracle-dz/UniFAR-FTUs huggingface dataset:
Simultaneously Learning Transferable Symbols and Language Groundings from Perceptual Data for Instruction Following

—Enabling robots to learn tasks and follow instructions as easily as humans is important for many real-world robot applications. Previous approaches have applied machine learning to teach the mapping from language to low dimensional symbolic representations constructed by hand, using demonstration trajectories paired with accompanying instructions. These symbolic methods lead to data efﬁcient learning. Other methods map language directly to high-dimensional control behavior, which requires less design effort but is data-intensive. We propose to ﬁrst learning symbolic abstractions from demonstration data and then mapping language to those learned abstractions. These symbolic abstractions can be learned with signiﬁcantly less data than end-to-end approaches, and support partial behavior spec-iﬁcation via natural language since they permit planning using traditional planners. During training, our approach requires only a small number of demonstration trajectories paired with natural language—without the use of a simulator—and results in a representation capable of planning to fulﬁll natural language instructions specifying a goal or partial plan. We apply our approach to two domains, including a mobile manipulator, where a small number of demonstrations enable the robot to follow navigation commands like “Take left at the end of the hallway,” in environments it has not encountered before.
Visualizing the structure of urban mobility with bundling: A case study of the city of São Paulo

Visualization of urban mobility data can facilitate the analysis and the decision-making process by public managers. However, mobility datasets tend to be very large and pose several challenges to the use of visualization, such as algorithm scalability and data occlusion. One approach to solve this problem is trail bundling, which groups motion trails that are spatially close in a simplified representation. This paper presents the results of adapting and using a recent bundling technique on a big dataset of urban mobility in São Paulo. The results show that bundling allows the visualization of various mobility patterns in the city.
How Context Matters: Childhood Family Structure and Early Family Formation in East and West Germany

This study investigated the association between childhood living arrangements and early family formation in Germany. Drawing on persisting socio-environmental differences between East and West Germany the author addressed the question whether the association of childhood family structure and the early transition to adulthood varies in different societal contexts. In line with research from other countries, the analysis based on data from the German Family Panel (pairfam/DemoDiff; N = 3643) showed that children from nontraditional family structures experience important demographic transitions faster than children who have been raised by both biological parents. In addition to this rather ubiquitous association, the study revealed considerable context-specific differences, which point to the long-term consequences of the post-war separation of East and West Germany. First, although increasing in relevance, family structure was less predictive for early family formation in East Germany. Second, the results indicated that the link between childhood family structure and the reproduction of social inequality, which has been found in many studies from the US, could only be replicated for West Germany. In East Germany, educational attainment did not mediate the effect of childhood living arrangements on early family formation, nor was it associated with an increased probability of ever having lived in an alternative family structure.
Mixed-precision iterative refinement using tensor cores on GPUs to accelerate solution of linear systems

Double-precision floating-point arithmetic (FP64) has been the de facto standard for engineering and scientific simulations for several decades. Problem complexity and the sheer volume of data coming from various instruments and sensors motivate researchers to mix and match various approaches to optimize compute resources, including different levels of floating-point precision. In recent years, machine learning has motivated hardware support for half-precision floating-point arithmetic. A primary challenge in high-performance computing is to leverage reduced-precision and mixed-precision hardware. We show how the FP16/FP32 Tensor Cores on NVIDIA GPUs can be exploited to accelerate the solution of linear systems of equations Ax = b without sacrificing numerical stability. The techniques we employ include multiprecision LU factorization, the preconditioned generalized minimal residual algorithm (GMRES), and scaling and auto-adaptive rounding to avoid overflow. We also show how to efficiently handle systems with multiple right-hand sides. On the NVIDIA Quadro GV100 (Volta) GPU, we achieve a 4×−5× performance increase and 5× better energy efficiency versus the standard FP64 implementation while maintaining an FP64 level of numerical stability.
Genetic Testing for Acute Myeloid Leukemia

The use of genetic testing for acute myeloid leukemia is considered medically necessary for the following: A. Genetic testing for FLT3 internal tandem duplication (FLT3/ITD), IDH1, IDH2, TET2, WT1, DNMT3A, ASXL1 and/or TP53 MEETS COVERAGE CRITERIA in adult and pediatric patients with suspected or confirmed AML of any type for prognostic and/or therapeutic purposes. B. Genetic testing for KIT mutations for adult and pediatric patients with confirmed core-binding factor (CBF) AML (AML with t(8;21)(q22;q22.1); RUNX1-RUNX1T1 or inv(16)(p13.1q22) /t(16;16)(p13.1;q22); CBFB-MYH11). C. Genetic testing for NPM1, CEBPA, and RUNX1 mutations for patients other than those with confirmed core binding factor AML or AML with myelodysplasia-related cytogenic abnormalities.
Applications of blockchain technology to education Policy

: - Blockchain technology can be applied to education, for both learners and teachers, in many innovative ways as for getting a diploma in management or for the achievements assessment, but also on formative evaluation, learning activities design and implementation, and keep tracking the whole learning processes. For this research, we will focus on analyzing the scientific production of Blockchain technology in education using bibliometric analysis. Then based on the analysis of the literature, identify some recommendations for policy in order to redesign the educational system based on the application of the blockchain technology.
Species Dispersal Modes in Amphitropical Plant Species of North and South America

Amphitropical disjunct plants are species that occur in both North and South America but not in the intermediate equatorial region. How amphitropical species dispersed across the Americas to their current distribution remains uncertain. To explain amphitropical distributions, three hypotheses were developed to test that (1) species dispersed successively through island hopping across the tropical zone in temperate microhabitats (= stepping stones), (2) species came to their current distribution through vicariance, or (3) species dispersed by a single long distance dispersal event. Twenty-five species were studied to infer their historical distributions with species distribution models in MaxEnt. Distribution models for each species were estimated under three different timelines: the current climate, the last glacial maximum (22,000 years ago), and the last interglacial maximum (120,000–140,000 years ago). Ecological niche models were generated in MaxEnt with 19 bioclimate variables from the WorldClim database. Across the three time slices, the vicariance hypothesis was rejected in all but one species for one of its time slices. In thirteen experiments, the long-distance dispersal and vicariance hypotheses were rejected in favor of the stepping stone hypothesis. In thirtyseven experiments, the stepping stone and vicariance hypotheses were rejected in favor of long distance dispersal. There were three species that could have dispersed by shorter-distance-dispersal events via intermediate dispersal from Mexico. Although our results suggest that long distance dispersal was the most dominant mechanism of dispersal among amphitropical species, they also convey that that numerous shorter-distancedispersal events via intermediate, favorable populations are an underappreciated mode of dispersal. Thesis Mentor: _____________________________ Dr. John Schenk Honors Director: _____________________________ Dr. Steven Engel April 2020 Department of Biology University Honors Program Georgia Southern University
iOracle: Automated Evaluation of Access Control Policies in iOS

Modern operating systems, such as iOS, use multiple access control policies to define an overall protection system. However, the complexity of these policies and their interactions can hide policy flaws that compromise the security of the protection system. We propose iOracle, a framework that logically models the iOS protection system such that queries can be made to automatically detect policy flaws. iOracle models policies and runtime context extracted from iOS firmware images, developer resources, and jailbroken devices, and iOracle significantly reduces the complexity of queries by modeling policy semantics. We evaluate iOracle by using it to successfully triage executables likely to have policy flaws and comparing our results to the executables exploited in four recent jailbreaks. When applied to iOS 10, iOracle identifies previously unknown policy flaws that allow attackers to modify or bypass access control policies. For compromised system processes, consequences of these policy flaws include sandbox escapes (with respect to read/write file access) and changing the ownership of arbitrary files. By automating the evaluation of iOS access control policies, iOracle provides a practical approach to hardening iOS security by identifying policy flaws before they are exploited.
STUDY OF WORKPLACE OSTRACISM, EMPLOYEE ENGAGEMENT AND INTERACTING EFFECT OF PSYCHOLOGICAL CAPITAL (PSCAP): A CONSERVATION OF RESOURCES THEORY PERSPECTIVE

The intention of this study is to investigate the influence of Workplace ostracism on Employee Engagement, among the people working in the health care sector. Using Conservation of Resource Theory (COR), the research seeks to understand the moderating role of Psychological Capital.The data for the study has been gathered from leading private hospitals of Karachi, Pakistan. The sample size for the study was 345 full-time health care employees. After screening and the analysis of data, it was revealed that WorkplaceOstracism negatively and significantly influencesEmployee Engagement. The intervening influence of Psychological Capital was estimated by PROCESS macro (Hayes, 2013). The psychological capital exhibited significant moderation between workplace ostracism and employee engagement. The study discusses the theoretical and practical implication.
THE IMPLEMENTATION OF ISO 9001:2015 TO IMPROVE QUALITY OF SERVICE AT PUSAT KESIHATAN UNIVERSITI (PKU), UNIVERSITI UTARA MALAYSIA(UUM)

The purpose of this study is to review the implementation of ISO 9001:2015 in order to improve the quality of services at Pusat Kesihatan Universiti (PKU), Universiti Utara Malaysia. The respondents of this study were customers at the PKU, UUM. The questionnaire was distributed to 50 respondents. The data were analyzed using SPSS software version 24. The data were tested using descriptive statistics, and correlation analysis to answer the research questions and to achieve the objectives. The findings show that customers agree that implementation of ISO 9001:2015 give service at PKU, UUM is good and satisfied. Through the correlation test, the results showed that the relationship between the implementation of ISO 9001:2015 has a positive and significant impact on customer satisfaction and the effect of implementing ISO 9001:2015 has a positive and significant impact in improving quality of service at PKU, UUM. Through mean and standard deviation tests, results show that tangible dimensions are the main dimensions of customer satisfaction while dimensions with low values are dimensions of responsiveness. Therefore, all aspects of service in PKU, UUM will be strengthened and all aspects of the weaknesses could be addressed to improve the service in order to maintain good quality services.
Piezoelectric Layer Length and Thickness variation effects on Displacement of Cantilever type Piezoelectric Energy Harvester

Piezoelectric energy harvesters find applicability in remote area of application because of simple design and operation. MEMS process technology is utilized to fabricate these cantilever based structures. Piezoelectric layer length and thickness are the key parameters for controlling the resonance frequency and optimal output. In this paper the effect of length and thickness of the piezoelectric layer has been investigated. FEM results have been obtained for varying the length of piezoelectric layer from 50 to 200 μm for two different thicknesses of 2 and 5 μm. It has been observed the variation of the length of the piezoelectric layer has an effect on the total displacement of the cantilever which affects the net potential generated. As the thickness increases, the cantilever displacement decreases.
EFFECT OF SILYMARIN ON HISTOPATHOLOGICAL AND HISTOCHEMICAL LESIONS INDUCED BY THE ANTIMALARIAL DRUG CHLOROQUINE IN THE LIVER OF ALBINO MICE

The hepatoprotective effect of silymarin on histopathological and histochemical alterations induced by the antimalarial drug, chloroquine was studied in albino mice. Administration of chloroquine at a dose level of 10 mg/kg body weight, 4 times per week for 3 weeks induced many histopathological changes in the liver such as leucocytic infiltrations, cytoplasmic vacuolization of hepatocytes and congestion of blood vessels. Histochemical observations revealed marked reduction in total carbohydrates, DNA and total protein contents in the hepatocytes. Treating animals with chloroquine and silymarin led to an improvement in both histopathological and histochemical alterations.The hepatoprotective effect of silymarin was attributed to its antioxidant and free radicals scavenging properties.
A Deep Learning Solution for Automatized Interpretation of 12-Lead ECGs

A broad variety of algorithms for detection and classification of rhythm and morphology abnormalities in ECG recordings have been proposed in the last years. Although some of them have reported very promising results, they have been mostly validated on short and non-public datasets, thus making their comparison extremely difficult. PhysioNet/CinC Challenge 2020 provides an interesting opportunity to compare these and other algorithms on a wide set of ECG recordings. The present model was created by “ELBIT” team. The algorithm is based on deep learning, and the segmentation of all beats in the 12-lead ECG recording, generating a new signal for each one by concatenating sequentially the information found in each lead. The resulting signal is then transformed into a 2-D image through a continuous Wavelet transform and inputted to a convolutional neural network. According to the competition guidelines, classification results were evaluated in terms of a class-weighted F-score (Fβand a generalization of the Jaccard measure (Gβ). In average for all training signals, these metrics were 0.933 and 0.811, respectively. Regarding validation on the testing set from the first phase of the challenge, mean values for both performance indices were 0.654 and 0.372, respectively.
Proteomics Uncovers Immunosuppression in COVID-19 Patients with Long Disease Course

Little is known regarding why a subset of COVID-19 patients exhibited prolonged positivity of SARS-CoV-2 infection. Here, we present a longitudinal sera proteomic resource for 37 COVID-19 patients over nine weeks, in which 2700 proteins were quantified with high quality. Remarkably, we found that during the first three weeks since disease onset, while clinical symptoms and outcome were indistinguishable, patients with prolonged disease course displayed characteristic immunological responses including enhanced Natural Killer (NK) cell-mediated innate immunity and regulatory T cell-mediated immunosuppression. We further showed that it is possible to predict the length of disease course using machine learning based on blood protein levels during the first three weeks. Validation in an independent cohort achieved an accuracy of 82%. In summary, this study presents a rich serum proteomic resource to understand host responses in COVID-19 patients and identifies characteristic Treg-mediated immunosuppression in LC patients, nominating new therapeutic target and diagnosis strategy.
Joint Angle and Doppler Frequency Estimation for MIMO Radar with One-Bit Sampling: A Maximum Likelihood-Based Method

We consider a multiple-input multiple-output (MIMO) radar that works through one-bit sampling of received radar echoes. The application of one-bit sampling significantly reduces the hardware cost, energy consumption, and systematic complexity, but it also poses serious challenges to extracting highly accurate target information from one-bit quantized data. In this article, we propose a maximum likelihood (ML)-based method that first iteratively maximizes the likelihood function to recover a virtual array data matrix and then jointly estimates the angle and Doppler parameters from the recovered matrix. Because the ML problem is convex, we can successfully apply a computationally efficient gradient descent algorithm to solve it. Based on our analysis of the Cram$\acute{\text{e}}$r–Rao bound of the ML-based method, a pre-estimation-assisted threshold (PET) strategy is developed to improve the estimation performance. Numerical experiments demonstrate that the proposed ML-based method, combined with the PET strategy, can provide highly accurate parameter estimation performance, close to that of the classic MIMO radar.
Psychometric properties of the N-SEMIE 1 Psychometric properties of the Norwegian self-efficacy for managing interpersonal events (N-SEMIE) Authors

Background: The Intentional Relationship Model addresses the use of different therapeutic approaches according to client needs, but also the therapist’s need to manage the relational challenges that inevitably arise in therapeutic encounters. However, measures of therapist self-efficacy related to managing such challenges have not been previously developed. Aim: This study aimed to examine the psychometric properties of a new measure, the Norwegian self-efficacy for managing interpersonal events (N-SEMIE). Methods: Occupational therapy students (n = 106) completed the instrument along with sociodemographic information. Factor analysis was performed using Principal Components Analysis in combination with Parallel Analysis, and internal consistency was assessed with Cronbach’s α and inter-item correlations. Results: All scale items belonged to the same latent factor (factor loadings 0.72-0.84), and Cronbach’s α was 0.94 (mean inter-item correlation 0.60) for the scale items. Conclusion: The N-SEMIE scale is unidimensional; the items have very high internal consistency; and the scale may be useful in research and audits related to therapist management of the interpersonal aspects of occupational therapy practice.
Strictly convex realization in two-phase image segmentation

In this paper, we borrow an idea from already well-known in some geometric problems (e.g., [1], [10]) to ﬁnd a global minimizer related to the two-phase Mumford-Shah functional via strictly convex formulations. We will brieﬂy review how it applies to ﬁnd the true minimizers of the original non-convex problem. More importantly, we will clearly address the possibility of a solution’s non-uniqueness for non-strict convex problems mentioned but unresolved in [13], which is any non-strict convex problem’s issue, using our formulations. The same answer applies to [14], [3] as well. Hence, one should consider this strictly convex formulation where the well-known convex formulations [14], [3] come into play.
rFSH Pretreatment Followed by rFSH-hCG in Three Males with CongenitalHypogonadotropic Hypogonadism Diagnosed during Childhood due toExtremely Small Testes, Micropenis and/or Bilateral Cryptorchidism

Backgrounds: Congenital male hypogonadotropic hypogonadism (CMHH) is usually treated with hCG-recombinant human FSH combination therapy (hCG-rFSH) to attain fertility. In 25% cases, sufficient spermatogenesis is not observed under the current gonadotropin replacement therapy (GRT) in CMHH like Kallmann syndrome and isolated gonadotropin deficiency. The effectiveness of pretreatment with rFSH monotherapy followed by GRT to improve testicular development and spermatogenesis in adult CMHH and gonadotropin-deficient boys with small testes has been reported by some studies as the physiological treatment for gonadotropin secretion. However, pubertal growth and future spermatogenesis during GRT in CMMH patients diagnosed during childhood because of severe phenotypes such as small testes, micropenis, and cryptorchidism have not been sufficiently evaluated. Objectives: To mimic the physiological gonadotropin secretion, we introduced a fixed period pretreatment with rFSH monotherapy followed by a low-dose escalation of hCG-rFSH to prevent rapid pubertal progression and observed the patient's pubertal growth, sexual maturity, and spermatogenesis. Design: A retrospective clinical study conducted at a university hospital and two pediatric endocrinology outpatient clinics. Patients: Three Kallmann syndrome patients aged 14.6 18 years with CMHH diagnosed during childhood because of their extremely small testes (testicular volume: TV < 1 mL), micropenis and/or bilateral cryptorchidism at childhood were included. Methods and Treatment Protocol: After pretreatment with rFSH (75 IU) daily for 2/4 months, hCG-rFSH was administered based on age-appropriate therapeutic doses. Results: TV increased two-fold after pretreatment with rFSH monotherapy. TV significantly increased from 0.7 ± 0.3 to 8.3 ± 3.5 mL and serum testosterone elevated to adult levels during hCG-rFSH. Total sperm number per ejaculate in Case 3 was only approximately five sperms by first semen analysis: Cases 1 and 3 experienced emissions and ejaculation. No patient showed rapid bone age progression (ΔCA/BA ratio annually as < 1 in Cases 1 and 2) and pubertal growth was 16.6 ± 4.1 cm and reached almost normal adult height during treatment. The average treatment period was 4.8 ± 0.8 years.
A Survey on Image Tampering Detection Using Probability Of Block Matching

- As image editing tools are easily available, the authenticity of the images has become questionable. Therefore the image tampering detection has become very important nowadays, as it can be used for misleading the general public as well as false evidence in court . In this paper we focus our research on copy-move forgery detection where a region of image is copied and pasted into the same image. Firstly divide the image into overlapping blocks. We propose fusion methodology for feature extraction, and Support Vector Machine for feature matching. Then calculate the probability of each matched block and compare it with a threshold value