Miracle-dz/UniFAR-FTUs huggingface dataset:
Prevalence and Social Risk Factors for Hearing Impairment in Chinese Children—A National Survey

Hearing impairment may affect children’s communication skills, social development, and educational achievement. Little is known about the prevalence of hearing impairment among Chinese children. Data were taken from the 2006 second China National Survey on Disability (CNSD). Hearing impairment was defined as moderate (41–60 dB HL), severe (61–80 dB HL), profound (81–90 dB HL), or complete (>91 dB HL). Logistic regression was used to estimate the odds ratio (OR) and 95% confidence intervals (CI). A weighted number of 567,915 hearing impairment children were identified, yielding a prevalence of 17.49 per 10,000 people (95% CI: 16.90–18.08), with prevention or treatment options possible for 64.6% of hearing impairment children. The main causes of hearing impairment were hereditary, tympanitis, and drug intoxication. Illiteracy in one or both parents (mother: OR = 1.388, 95% CI: 1.125–1.714, p < 0.0001; father: OR = 1.537, 95% CI: 1.152–2.049, p < 0.0001 relative to no school or primary school), annual family income lower than national average (OR = 1.323, 95% CI: 1.044–1.675, p = 0.0203, relative to higher than national average), household size larger than three people (OR = 1.432, 95% CI: 1.164–1.762, p = 0.0007, relative to smaller than three people) and single-mother family (OR = 2.056, 95% CI: 1.390–3.042, p = 0.0176, relative to intact family) were the independence risk factors for hearing impairment among Chinese children. Lower annual family income, male children, larger household size, single-mother family, and lower levels of maternal and paternal education were independent risk factors for hearing impairment for Chinese children. Further studies on hearing impairment prevention and the relationship between parental social factors and the risk of hearing impairment are needed.
A Semantic Framework for the Declarative Debugging of Wrong and Missing Answers in Declarative Constraint Programming

Debugging tools are a practical need for helping programmers to understand why their programs do not work as intended. Declarative programming paradigms involving complex operational details, such as constraint solving and lazy evaluation, do not fit well to traditional debugging techniques relying on the inspection of low-level computation traces. As a solution to this problem, and following a seminal idea by Shapiro (Shapiro, 1982), declarative debugging (a.k.a. declarative diagnosis or algorithmic debugging) uses Computation Trees (shortly, CTs) in place of traces. CTs are built a posteriori to represent the structure of a computation whose top-level outcome is regarded as a symptom of the unexpected behavior by the user. Each node in a CT represents the computation of some observable result, depending on the results of its children nodes, using a program fragment also attached to the node. Declarative diagnosis explores a CT looking for a so-called buggy node which computes an unexpected result from children whose results are all expected. Each buggy node points to a program fragment responsible for the unexpected behavior. The search for a buggy node can be implemented with the help of an external oracle (usually the user with some semiautomatic support) who has a reliable declarative knowledge of the expected program semantics, the so-called intended interpretation.
Loss of adipocyte specification and necrosis augment tumor-associated inflammation

Most tumors are typified by a chronic, unresolved inflammatory response that potentiates angiogenesis and therefore enables tumor progression. We have determined that dysfunctional tumor-associated adipocytes contribute to tumor-associated inflammation. In three tumor models, tumor-associated adipose tissue was characterized by thin and fragile adipocyte membranes, necrosis, robust expression of the pro-inflammatory factor HMGB1, and loss of the lipid storage mediator, perilipin-1. By transmission electron microscopy, macrophages in tumor-associated adipose tissue contained lipid droplets and resembled foam cells, which are commonly observed in inflamed tissues. In vitro co-culture studies showed that tumor-associated adipose tissue conditioned-medium stimulated monocyte-to-macrophage differentiation, adhesion, spreading, and lipid uptake. Compared with normal adipose tissue, tumor-associated adipose tissue secreted 3-fold higher levels of IL-6 and IL-6 was sufficient to stimulate macrophage differentiation and adhesion. These results suggest that, in tumors, loss of adipocyte specification, necrosis, and scavenging of adipocyte debris directly activates macrophages and contributes to tumor-associated inflammation. Thus, adipocyte dysfunction may facilitate tumor progression, especially in tumors closely aligned with adipose tissue, in particular, breast cancer.
Spiritual intelligence and mindfulness as sources of transformational leadership

The transfer rate of transformational leadership training is considered marginal; it is estimated that less than 30% of leaders who participate in the training change their behavior once back in the workplace. Most quantitative investigations have focused on predictors of transformational leadership, providing insufficient information about possible internal driving forces that influence leaders to behave in a transformational manner; furthermore, some correlations of those predictors with specific dimensions of transformational leadership have not been thoroughly explained. In the present quantitative, survey-based, cross-sectional research, we tested the effects of spiritual intelligence and mindfulness on transformational leadership behavior patterns among a sample of 542 leaders in Peru, with the results suggesting that mindfulness partially mediates the effects of spiritual intelligence on transformational leadership. Based on these findings, we propose that introducing spiritual intelligence and mindfulness training as part of the traditional curricula for transformational leadership training will improve the transfer of knowledge to leaders.
UWB phased array antennas for high resolution radars

In this paper we present a new UWB antenna and its linear phased array. The single UWB element has omnidirectional and stable radiation patterns over a wide-bandwidth that make it suitable for UWB wireless communication. In addition an E-plane phased array design of four proposed UWB antennas has been simulated to achieve beam steering capability which is used in high accuracy phased array radar. Phase of each element applied by the well-known progressive phase shift method. The proposed phased array antenna has a wide beam steering capability of ±30° and an average of -10 dB side lobe level (SLL) in over a wide bandwidth from 3 to 11 GHz. The simulated and measured results of return loss for the single antenna, both single and array Gain, and beam scanning feature will be discussed. The simulation results confirm that the proposed UWB phased array has a stable radiation pattern and perfect cross polar isolation in the entire band of operation for mentioned beam scanning angles.
Study of Existing Method of Finding Aliases and Improve Method of Finding Aliases from Web

We know that the person might be referred by his nickname and we finds the information using internet. Extracting information from the internet not an easy task because the same name having different entity or same entity might be referred by different name like name and its nickname. So we should know the nickname to find out the information about particular entity. We know that various sites of web contain aliases of popular celebrity in various field like music, cinema, sport etc., and does not contain alias information about common man. There is one existing methods of extracting aliases through lexical pattern based retrieval tested using real-world name-alias pairs using training data related to limited domains. In this paper, we discuss what are the problem arrive while retrieving the information, and how we should correct alias extraction in Inter-disciplinary fields. Keyword : Retrieval ,semantic metadata
Aprendizaje profundo para el procesamiento del lenguaje natural

The work carried out is part of natural language processing area and it is focused specifically on text classification problems like sentiment analysis and topic detection about content published on Twitter, using deep learning models such as convolutional and recurrent neural networks. In order to estimate the parameters of these models in problems where the input is a sequence of linguistic units, a representation that retains the most discriminative information for a given task (contextual information, semantic, syntactic, etc.) is required. For this reason, in the present work, suitable representations for the addressed tasks are proposed and comparisons are made among the different representations, as well as among the different models of neural networks that use these representations. All the tasks addressed have been proposed in workshops of national and international congresses such as SemEval and IberEval. Furthermore, in these tasks we have obtained competitive results, reaching a 1st place in the tasks COSET and Gender (Ibereval 2017@SEPLN ), a 4th place in Stance (Ibereval 2017@SEPLN ) and a 3rd place in Sentiment Analysis in Twitter (SemEval 2017@ACL).
The Web as A Tool For Proving: The Web as A Tool For Proving

The Web may critically transform the way we understand the activity of proving. The Web as a collaborative medium allows the active participation of people with different backgrounds, interests, viewpoints, and styles. Mathematical formal proofs are inadequate for capturing Web-based proofs. This article claims that Web provings can be studied as a particular type of Goguen's proof-events. Web-based proof-events have a social component, communication medium, prover-interpreter interaction, interpretation process, understanding and validation, historical component, and styles. To demonstrate its claim, the article discusses the Kumo and Polymath projects, both of which employ Web-based communication as part of proving. Web proving is a novel type of proving activity that may have a serious impact on the change in mathematical practices, despite the fact that it is not currently a universally acceptable methodology.
Controlled diffusion processes

This article gives an overview of the developments in controlled diffusion processes, emphasizing key results regarding existence of optimal controls and their characterization via dynamic programming for a variety of cost criteria and structural assumptions. Stochastic maximum principle and control under partial observations (equivalently, control of nonlinear filters) are also discussed. Several other related topics are briefly sketched.
Shape Based Learning for Grasping Novel Objects in Cluttered Scenes

Abstract This paper presents a novel approach to clearing a table with a heap of objects. Form, size, position, orientation and constellation of the objects are a priori unknown. Coping with incomplete point cloud data is an additional challenge. There are three key contributions. First, we introduce Height Accumulated Features (HAF) which provide an efficient way of calculating grasp related feature values. The second contribution is an extensible machine learning system for binary classification of grasp hypotheses based on raw point cloud data. Finally, a practical heuristic for selection of the most robust grasp hypothesis is introduced. We evaluate our system in experiments where a robot was required to autonomously clear a table with a heap of unknown objects. Despite the complexity of the scenarios, our system cleared the table each time without human interaction and with a grasp failure rate below three percent.
On Constructing Optimal One-Time Signatures

One-time signatures (OTS) offer a viable alternative to public keybased digital signatures. OTS security is based only on the strength of the underlying one-way function and does not depend on the conjectured difficulty of a mathematical problem. OTS methods have been proposed in the past but no solid foundation exists for judging their efficiency or optimality. This paper develops a new methodology for evaluating OTS methods and presents optimal OTS techniques for a single OTS or a tree with many OTSs. These techniques can be used in a see-saw mode to obtain desired tradeoff between various parameters such as the cost of signature generation and its subsequent verification and the cost of traditional signature verification and OTS verification.
Tumour necrosis factor-alpha expression in segmental colitis associated with diverticulosis down-regulates after treatment.

BACKGROUND AND AIMS Tumour necrosis factor-α (TNF-α) expression may be increased in segmental colitis associated with diverticulosis (SCAD). Our aim was to assess TNF-α expression in SCAD in relationship to the treatment. METHODS 10 patients affected by severe (type B and D) SCAD were studied (6 males, 4 females, mean age 60.54 years, range 43-85 years). All patients were treated with beclomethasone dipropionate 10 mg/day plus a probiotic preparation VSL#3 for 8 weeks. At that time, clinical, endoscopic and histological reassessment was performed. Controls were 5 patients with active ulcerative colitis (UC). RESULTS After treatment, all SCAD B and no SCAD D patients were in remission. The TNF-α expression dropped from 42.7% (+/-7.58) to 15.7% (+/-2.6) in SCAD B patients (p=0.001), and from 40% (+/-5.9) to 28.6% (+/-5.3) in SCAD D patients (p=0.005). In UC patients, the TNF-α expression dropped from 45.5% (+/-5.09) to 22.5% (+/-2.5) (p=0.001). Neither SCAD B nor SCAD D patients showed a significant difference in TNF-α expression compared to UC after treatment. Finally, TNF-α was significantly overexpressed in SCAD D than in SCAD B at the end of treatment (p=0.048). CONCLUSIONS TNF-α expression in SCAD down regulates after treatment, and seems to be related to the clinical response to therapy. This behaviour, similar to that of Inflammatory Bowel Diseases (IBD), confirms that this disease should be considered as a subtype of IBD.
1 JSK , a GST-activated nitric oxide generator , induces DNA double strand breaks , activates DNA damage response pathways , and induces apoptosis in vitro and in vivo in human multiple myeloma cells

Jerome Lipper Multiple Myeloma Center, Department of Medical Oncology, DanaFarber Cancer Institute and Harvard Medical School, Boston, MA 02115 Biological Engineering Division and Department of Chemistry, Massachusetts Institute of Technology, Cambridge, MA 02139 Departments of Pathology and Medicine, Brigham and Women’s Hospital, Harvard Medical School, 75 Francis Street, Boston, MA 02115 SAIC-Frederick, MD 21702 Laboratory of Comparative Carcinogenesis, NCI-NIH, Frederick, MD 21702 Division of Medical Oncology, University of Utah and Salt Lake City, Utah 84112
MHD Effects on Blood Flow in a Stenosis

The fundamental problem of blood flow in a channel with stenosis under the influence of a steady uniform magnetic field is studied. The mathematical model used for the formulation of the problem is consistent with the principles of Magnetohydrodynamics (MHD). Blood is considered as a homogeneous Newtonian fluid and is treated as an electrically conducting magnetic fluid. The finite volume (FV) discretization scheme in curvilinear coordinates is used for the discretization of the system of equations governing the MHD blood flow. For the numerical solution of the problem, which is described by a coupled, nonlinear system of PDEs, with appropriate boundary conditions, the SIMPLE method is adopted. Results concerning the velocity, pressure, and skin friction indicate that the presence of the magnetic field influences considerably the flow field.
What Overweight Women Want From a Weight Loss App: A Qualitative Study on Arabic Women

Background Overweight and obesity are international public health issues. With mobile and app use growing globally, the development of weight loss apps are increasing along with evidence that interventions using technology have been effective in the treatment of obesity. Although studies have been conducted regarding what content health professionals would recommend within weight loss apps, there are limited studies that explore users’ viewpoints. There is specifically a paucity of research that takes the cultural background of the user into consideration, especially in Middle Eastern countries where the lives and weight loss intervention needs of women not only vary vastly from the West, but the obesity rate is also increasing exponentially. Objective The current study sought to explore the proposed features of an Arabic weight loss app by seeking the experiences and opinions of overweight and obese Saudi Arabian users in order to design a mobile phone app to fit their needs. Methods Focus group discussions were conducted with a purposive sample of volunteer overweight and obese Saudi women (BMI ≥ 25) who were older than 18 years and who owned a mobile phone. The most common Arabic and English weight loss mobile apps were downloaded to initiate dialogue about app usage and to get their opinions on what an ideal weight loss app would look like and the features it would include. All transcribed, translated discussions were thematically analyzed, categorized for each of the main topics of the discussion, and specific quotations were identified. Results Four focus groups were conducted with a total of 39 participants. Most participants owned an Android mobile phone and only a few participants were aware of the availability of health-related apps. Barriers to weight loss were identified including: motivation, support (social and professional), boring diets, customs, and lifestyle. Diverse themes emerged as suggestions for an ideal weight loss app including: Arabic language and culturally sensitive; motivational support and social networking; dietary and physical activity tools; and a tailorable, user-friendly interface. Conclusions This study identifies weight loss app features from the users’ perspective, which should be considered in the development of a weight loss app for this population.
Assessing the Impact of Using Fault Prediction in Industry

Software developers and testers need realistic ways to measure the practical effects of using fault prediction models to guide software quality improvement methods such as testing, code reviews, and refactoring. Will the availability of fault predictions lead to discovery of different faults, or to more efficient means of finding the same faults? Or do fault predictions have no practical impact at all? In this challenge paper we describe the difficulties of answering these questions, and the issues involved in devising meaningful ways to assess the impact of using prediction models. We present several experimental design options and discuss the pros and cons of each.
Modal types for mobile code

In this dissertation I argue that modal type systems provide an elegant and practical means for controlling local resources in spatially distributed computer programs. A distributed program is one that executes in multiple physical or logical places. It usually does so because those places have local resources that can only be used in those locations. Such resources can include processing power, proximity to data, hardware, or the physical presence of a user. Programmers that write distributed applications therefore need to be able to reason about the places in which their programs will execute. This work provides an elegant and practical way to think about such programs in the form of a type system derived from modal logic. Modal logic allows for reasoning about truth from multiple simultaneous perspectives. These perspectives, called "worlds," are identified with the locations in the distributed program. This enables the programming language to be simultaneously aware of the various hosts involved in a program, their local resources, and their differing perspectives on each other's code and data. This leads to a clean and general type structure for programs that respects locality while permitting high-level language features. To argue that this system is elegant, I present a modal logic formulated for this purpose and then prove its global soundness and completeness and its equivalence to known logics. I then show how a small programming language can be derived from the logic, and how it can be implemented, proving properties of this abstract compilation procedure. All of these theorems are formalized in Twelf and can be checked by computer. To demonstrate that it is practical, I then extend the modal calculus to a full-fledged programming language based on ML. I implemented a compiler for this language for the specific case of web applications, a distributed computation involving two hosts with widely different capabilities: the web server and the web browser. I then use the completed implementation to build realistic web applications.
Large speed increase using novel GPU based algorithms to simulate cardiac excitation waves in 3D rabbit ventricles

Large-scale biophysically detailed computer models of the heart provide a useful tool to understand dynamics of cardiac excitation and mechanisms underlying lethal cardiac arrhythmias. However, high demanding of intensive high performance computing environments limits the practical application of such models. This paper presents a novel use of a desktop personal computer and the CUDA parallel computing architecture for a highly efficient method of parallel simulation of a 3D ventricular model. We show that substantial speed increases can be obtained using a desktop Graphical Processing Unit (GPU) compared to a single desktop Central Processing Unit (CPU), and that a single GPU can be an effective substitute to large numbers of CPUs.
Interactive Spoken Document Retrieval With Suggested Key Terms Ranked by a Markov Decision Process

Interaction with users is a powerful strategy that potentially yields better information retrieval for all types of media, including text, images, and videos. While spoken document retrieval (SDR) is a crucial technology for multimedia access in the network era, it is also more challenging than text information retrieval because of the inevitable recognition errors. It is therefore reasonable to consider interactive functionalities for SDR systems. We propose an interactive SDR approach in which given the user's query, the system returns not only the retrieval results but also a short list of key terms describing distinct topics. The user selects these key terms to expand the query if the retrieval results are not satisfactory. The entire retrieval process is organized around a hierarchy of key terms that define the allowable state transitions; this is modeled by a Markov decision process, which is popularly used in spoken dialogue systems. By reinforcement learning with simulated users, the key terms on the short list are properly ranked such that the retrieval success rate is maximized while the number of interactive steps is minimized. Significant improvements over existing approaches were observed in preliminary experiments performed on information needs provided by real users. A prototype system was also implemented.