Miracle-dz/UniFAR-FTUs huggingface dataset:
Scleral Micro-RNA Signatures in Adult and Fetal Eyes

Introduction In human eyes, ocular enlargement/growth reflects active extracellular matrix remodeling of the outer scleral shell. Micro-RNAs are small non-coding RNAs that regulate gene expression by base pairing with target sequences. They serve as nodes of signaling networks. We hypothesized that the sclera, like most tissues, expresses micro-RNAs, some of which modulate genes regulating ocular growth. In this study, the scleral micro-RNA expression profile of rapidly growing human fetal eyes was compared with that of stable adult donor eyes using high-throughput microarray and quantitative PCR analyses. Methods Scleral samples from normal human fetal (24 wk) and normal adult donor eyes were obtained (n=4 to 6, each group), and RNA extracted. Genome-wide micro-RNA profiling was performed using the Agilent micro-RNA microarray platform. Micro-RNA target predictions were obtained using Microcosm, TargetScan and PicTar algorithms. TaqMan® micro-RNA assays targeting micro-RNAs showing either highest significance, detection, or fold differences, and collagen specificity, were applied to scleral samples from posterior and peripheral ocular regions (n=7, each group). Microarray data were analyzed using R, and quantitative PCR data with 2^-deltaCt methods. Results Human sclera was found to express micro-RNAs, and comparison of microarray results for adult and fetal samples revealed many to be differentially expressed (p<0.01, min p= 6.5x1011). Specifically, fetal sclera showed increased expression of mir-214, let-7c, let-7e, mir-103, mir-107, and mir-98 (1.5 to 4 fold changes, p<0.01). However, no significant regionally specific differences . i.e., posterior vs. peripheral sclera, were observed for either adult or fetal samples. Conclusion For the first time, micro-RNA expression has been catalogued in human sclera. Some micro-RNAs show age-related differential regulation, higher in the sclera of rapidly growing fetal eyes, consistent with a role in ocular growth regulation. Thus micro-RNAs represent potential targets for ocular growth manipulation, related to myopia and/or other disorders such as scleral ectasia.
Structural Problems in Namibia's Sectoral and Sub-Sectoral Performance During the 1968-1992 Years

A flexible production function analysis is addressed to Namibia's data for the 1968-1992 period to test for evidence of structural problems in sectoral and sub-sectoral performance. The analysis found the primary sector to be characterized by constant returns to scale through the entire 25 years. The secondary sector experienced constant returns to scale pre-1980 and severe diseconomies post-1980, while the tertiary sector was marked by constant returns to scale pre-1980, and questionable increasing returns to scale post-1980. The changes imply structural problems inasmuch as factor productivities and the rates of technical change declined, and little support for domestic capital formation was found.
Pose-Invariant Face Recognition via RGB-D Images

Three-dimensional (3D) face models can intrinsically handle large pose face recognition problem. In this paper, we propose a novel pose-invariant face recognition method via RGB-D images. By employing depth, our method is able to handle self-occlusion and deformation, both of which are challenging problems in two-dimensional (2D) face recognition. Texture images in the gallery can be rendered to the same view as the probe via depth. Meanwhile, depth is also used for similarity measure via frontalization and symmetric filling. Finally, both texture and depth contribute to the final identity estimation. Experiments on Bosphorus, CurtinFaces, Eurecom, and Kiwi databases demonstrate that the additional depth information has improved the performance of face recognition with large pose variations and under even more challenging conditions.
Apex: extending Android permission model and enforcement with user-defined runtime constraints

Android is the first mass-produced consumer-market open source mobile platform that allows developers to easily create applications and users to readily install them. However, giving users the ability to install third-party applications poses serious security concerns. While the existing security mechanism in Android allows a mobile phone user to see which resources an application requires, she has no choice but to allow access to all the requested permissions if she wishes to use the applications. There is no way of granting some permissions and denying others. Moreover, there is no way of restricting the usage of resources based on runtime constraints such as the location of the device or the number of times a resource has been previously used. In this paper, we present Apex -- a policy enforcement framework for Android that allows a user to selectively grant permissions to applications as well as impose constraints on the usage of resources. We also describe an extended package installer that allows the user to set these constraints through an easy-to-use interface. Our enforcement framework is implemented through a minimal change to the existing Android code base and is backward compatible with the current security mechanism.
L-EnsNMF: Boosted Local Topic Discovery via Ensemble of Nonnegative Matrix Factorization

Nonnegative matrix factorization (NMF) has beenwidely applied in many domains. In document analysis, it hasbeen increasingly used in topic modeling applications, where aset of underlying topics are revealed by a low-rank factor matrixfrom NMF. However, it is often the case that the resulting topicsgive only general topic information in the data, which tends notto convey much information. To tackle this problem, we proposea novel ensemble model of nonnegative matrix factorizationfor discovering high-quality local topics. Our method leveragesthe idea of an ensemble model, which has been successfulin supervised learning, into an unsupervised topic modelingcontext. That is, our model successively performs NMF givena residual matrix obtained from previous stages and generatesa sequence of topic sets. Our algorithm for updating the inputmatrix has novelty in two aspects. The first lies in utilizing theresidual matrix inspired by a state-of-the-art gradient boostingmodel, and the second stems from applying a sophisticatedlocal weighting scheme on the given matrix to enhance thelocality of topics, which in turn delivers high-quality, focusedtopics of interest to users. We evaluate our proposed method bycomparing it against other topic modeling methods, such as afew variants of NMF and latent Dirichlet allocation, in termsof various evaluation measures representing topic coherence, diversity, coverage, computing time, and so on. We also presentqualitative evaluation on the topics discovered by our methodusing several real-world data sets.
Capability-based Communication Analysis for Enterprise Modelling

Capability-oriented enterprise modelling can provide effective solutions to face changing business context. In the business domain, the notion of capability has gained a lot of attention since it guides the activities of service specification and design. Simultaneously, the research community has been promoting the integration of model-driven development (MDD) approaches with enterprise modelling to support the link between enterprise and software specifications. This integration has becoming vital to ensure the traceability of enterprise models and software implementations, acceleration of software time to market, quality assurance, and enterprise model evolution support. The capability-driven development (CDD) method has been recently developed and applied in various industrial use cases. But, the link between the CDD method and strong funded MDD approaches has not been explored. In this paper we explore the integration of the CDD method with the Communication Analysis method (a communication-oriented business process modelling method), which is supported by means of MDD frameworks. Among the advantages to add the communicational perspective to the CDD method, we want to highlight the possibility to offer a high level analysis of business process models that focus on the communications between different organisational actors, as so as to offer further transformation facilities into software components. With this integration, we give the first steps to offer automation facilities to capability-driven environments.
Efficient Tool Path Generation for √3 Subdivision Surface

An approach of three-axis NC cutter path generation for √3 subdivision surface is proposed. A computing formula for error estimating √3 subdivision surface is derived. Using the formula, one can predict how many steps of subdivision are necessary to meet a user-specified tolerance without subdivision the meshes actually. Tool path planning is generated automatically based on cutter location surface. A collision detection and avoidance is developed for the interfere-free. The generated tool paths comply with a certain tolerance and surface finish specified on the surface. We implement our approach and present results. Our approach reduces the computational complexity and is robust efficiently
Both Gene Amplification and Allelic Loss Occur at 14q13.3 in Lung Cancer

Purpose: Because loss of Nkx2-8 increases lung cancer in the mouse, we studied suppressive mechanisms in human lung cancer. Experimental Design:NKX2-8 is located within 14q13.3, adjacent to its close relative TTF1/NKX2-1. We first analyzed LOH of 14q13.3 in forty-five matched human lung cancer and control specimens. DNA from tumors with LOH was then analyzed with high-density single-nucleotide polymorphism (SNP) arrays. For correlation with this genetic analysis, we quantified expression of Nkx2-8 and TTF1 mRNA in tumors. Finally, suppressive function of Nkx2-8 was assessed via colony formation assays in five lung cancer cell lines. Results: Thirteen of forty-five (29%) tumors had LOH. In six tumors, most adenocarcinomas, LOH was caused by gene amplification. The 0.8-Mb common region of amplification included MBIP, SFTA, TTF1, NKX2-8, and PAX9. In 4 squamous or adenosquamous cancers, LOH was caused by deletion. In three other tumors, LOH resulted from whole chromosome mechanisms (14−, 14+, or aneuploidy). The 1.2-Mb common region of deletion included MBIP, SFTA, TTF1, NKX2-8, PAX9, SLC25A21, and MIPOL1. Most tumors had low expression of Nkx2-8. Nevertheless, sequencing did not show NKX2-8 mutations that could explain the low expression. TTF1 overexpression, in contrast, was common and usually independent of Nkx2-8 expression. Finally, stable transfection of Nkx2-8 selectively inhibited growth of H522 lung cancer cells. Conclusions: 14q13.3, which contains NKX2-8, is subject to both amplification and deletion in lung cancer. Most tumors have low expression of Nkx2-8, and its expression can inhibit growth of some lung cancer cells. Clin Cancer Res; 17(4); 690–9. ©2010 AACR.
Enhancing Home Health Mobile Phone App Usability Through General Smartphone Training: Usability and Learnability Case Study

Background Each year, millions of older adults fall, with more than 1 out of 4 older people experiencing a fall annually, thereby causing a major social and economic impact. Falling once doubles one’s chances of falling again, making fall prediction an important aspect of preventative strategies. In this study, 22 older adults aged between 65 and 85 years were trained in the use of a smartphone-based fall prediction system. The system is designed to continuously assess fall risk by measuring various gait and balance parameters using a smart insole and smartphone, and is also designed to detect falls. The use case of the fall prediction system in question required the users to interact with the smartphone via an app for device syncing, data uploads, and checking system status. Objective The objective of this study was to observe the effect that basic smartphone training could have on the user experience of a group that is not technically proficient with smartphones when using a new connected health system. It was expected that even short rudimentary training could have a large effect on user experience and therefore increase the chances of the group accepting the new technology. Methods All participants received training on how to use the system smartphone app; half of the participants (training group) also received extra training on how to use basic functions of the smartphone, such as making calls and sending text messages, whereas the other half did not receive this extra training (no extra training group). Comparison of training group and no extra training group was carried out using metrics such as satisfaction rating, time taken to complete tasks, cues required to complete tasks, and errors made during tasks. Results The training group fared better in the first 3 days of using the system. There were significant recorded differences in number of cues required and errors committed between the two groups. By the fourth and fifth day of use, both groups were performing at the same level when using the system. Conclusions Supplementary basic smartphone training may be critical in trials where a smartphone app–based system for health intervention purposes is being introduced to a population that is not proficient with technology. This training could prevent early technology rejection and increase the engagement of older participants and their overall user experience with the system.
Suicide Protective Factors in Outpatient Substance Abuse Patients: Religious Faith and Family Support

ABSTRACT The purpose of this study was to identify the protective roles of religious faith and family support in buffering against suicidal behavior in a sample of substance abuse outpatients seeking treatment. Data were collected from 112 clinical outpatients seeking treatment for substance abuse. We hypothesized that religious faith would be related to lower levels of suicidal behavior through a negative association with depressive symptoms. We expected this mediation effect would differ across varying levels of family support, providing support for a moderated mediation effect. The results indicate that religious faith exerts stronger direct and indirect effects on suicidal behavior at low levels of family support. Religious faith was significantly and negatively related to suicidal behavior only at low levels of family support. The findings suggest that in the absence of family support, religious faith may play a compensatory role in protecting against suicidal behavior.
Visualization of IoV Warning Data Based on Warning Velocity Association Model

Due to the frequent occurrence of the traffic accidents, the passive safety devices fail to meet people's needs. Growing attention has been paid to active safety strategies such as the collision warnings. This paper aims at discovering the related characteristics between the active safety strategy and velocity through the visual analysis of Internet of Vehicles (IoV) warning data. First, seven datasets are collected, in which five datasets are used to formulate hypotheses, and the other two datasets are used for visualization. Second, the relationship hypotheses found between warnings and velocity is that one or more warnings tend to occur when the velocity is at a certain level, and one or more levels of velocity tend to make occurrence of certain warning. Then, the warning velocity association model (WVAM) is designed to visually validate the relation between warnings and velocity. With the help of visual analysis tool Gephi, we get renderings of relationship embodied in WVAM.
An optimal transform architecture for H.264/AVC

This paper presents the design of the area optimized integer Two Dimensional Discrete Cosine Transform (2-D DCT) used in H.264/AVC codecs. The 2-D DCT calculation is performed by utilizing the separability property, in such a way that 2-D DCT is divided into two 1-D DCT calculation that are joined through a common memory. Due to its area optimized approach, the design will find application in mobile devices. Verilog hardware description language (HDL) in cadence environment has been used for design, compilation, simulation and synthesis of transform block in 0. 18µ TSMC technology.
Cerebral β-Amyloidosis in Mice Investigated by Ultramicroscopy

Alzheimer´s disease (AD) is the most common neurodegenerative disorder. AD neuropathology is characterized by intracellular neurofibrillary tangles and extracellular β-amyloid deposits in the brain. To elucidate the complexity of AD pathogenesis a variety of transgenic mouse models have been generated. An ideal imaging system for monitoring β-amyloid plaque deposition in the brain of these animals should allow 3D-reconstructions of β-amyloid plaques via a single scan of an uncropped brain. Ultramicroscopy makes this possible by replacing mechanical slicing in standard histology by optical sectioning. It allows a time efficient analysis of the amyloid plaque distribution in the entire mouse brain with 3D cellular resolution. We herein labeled β-amyloid deposits in a transgenic mouse model of cerebral β-amyloidosis (APPPS1 transgenic mice) with two intraperitoneal injections of the amyloid-binding fluorescent dye methoxy-X04. Upon postmortem analysis the total number of β-amyloid plaques, the β-amyloid load (volume percent) and the amyloid plaque size distributions were measured in the frontal cortex of two age groups (2.5 versus 7-8.5 month old mice). Applying ultramicroscopy we found in a proof-of-principle study that the number of β-amyloid plaques increases with age. In our experiments we further observed an increase of large plaques in the older age group of mice. We demonstrate that ultramicroscopy is a fast, and accurate analysis technique for studying β-amyloid lesions in transgenic mice allowing the 3D staging of β-amyloid plaque development. This in turn is the basis to study neural network degeneration upon cerebral β-amyloidosis and to assess Aβ -targeting therapeutics.
Subjectivity Detection through Socio-Linguistic Features

Social media platforms have opened new dimensions within the information retrieval domain leading to a novel concept known as Social Information Retrieval. We argue that the concept of Social Information Retrieval can be extended by augmenting the huge amount of content on the traditional Web with the ever-growing rich Social Web content to increase the information richness of today’s search engines. This paper proposes a subjectivity detection framework which can lead towards a proposed emotion-aware search engine interface. Our proposed method differs from previous subjectivity analysis approaches in that it is the first method that takes into account social features of social media platforms for the subjectivity classification task. Through experimental evaluations, we observe the accuracy of the proposed method to be 86.21% which demonstrates a promising outcome for large-scale application of our proposed subjectivity analysis technique.
An experimental study on designing of a dual band antenna using CSRR structure with a single band antenna

The complementary split ring resonator (CSRR) is a widely used planar metamaterial structure in the design of microstrip antennas and other microstrip elements. In this work, a study has been made on converting a single band microstrip antenna into a dual band microstrip antenna by etching a CSRR structure from the ground plane below the patch. Initially, a simulation based study of the phenomenon is performed for a rectangular patch antenna. Then the same phenomenon is studied on an antenna of arbitrary shape. Using this approach, a 2.4 GHz antenna for IEEE 802.11 standard WLAN application has been designed, simulated and fabricated.
CD11b+Ly6G+ cells inhibit tumor growth by suppressing IL-17 production at early stages of tumorigenesis

Neutrophils are important innate immune cells involved in microbial clearance at the sites of infection. However, their role in cancer development is unclear. We hypothesized that neutrophils mediate antitumor effects in early tumorigenesis. To test this, we first studied the cytotoxic effects of neutrophils in vitro. Neutrophils were cytotoxic against tumor cells, with neutrophils isolated from tumor-bearing mice trending to have increased cytotoxic activities. We then injected an ELR+ CXC chemokine-producing tumor cell line into C57BL/6 and Cxcr2−/− mice, the latter lacking the receptors for neutrophil chemokines. We observed increased tumor growth in Cxcr2−/− mice. As expected, tumors from Cxcr2−/− mice contained fewer neutrophils. Surprisingly, these tumors also contained fewer CD8+ T cells, but more IL-17-producing cells. Replenishment of functional neutrophils was correlated with decreased IL-17-producing cells, increased CD8+ T cells, and decreased tumor size in Cxcr2−/− mice, while depletion of neutrophils in C57BL/6 mice showed the opposite effects. Results from a non-ELR+ CXC chemokine producing tumor further supported that functional neutrophils indirectly mediate tumor control by suppressing IL-17A production. We further studied the correlation of IL-17A and CD8+ T cells in vitro. IL-17A suppressed proliferation and IFNγ production of CD8+ T cells, while CD11b+Ly6G+ neutrophils did not suppress CD8+ T cell function. Taken together, these data demonstrate that, while neutrophils could control tumor growth by direct cytotoxic effects, the primary mechanism by which neutrophils exert antitumor effects is to regulate IL-17 production, through which they indirectly promote CD8+ T cell responses.
Acceptance Testing of Web Applications with Test Description Language

Acceptance tests are usually created by a client after a part of a system is implemented. However, some methodologies propose the elaboration of test ca- ses before implementing a system. This approach increases the probability of system implementation that fulfills requirements, but may be problematic for customers and testers. To allow acceptance testing in such conditions, we pro- pose to define test cases by recording them on an interactive mockup (a low detailed user-interface prototype). The paper focuses on Test Description Lan- guage, a notation used to store test cases.
A probabilistic framework for perceptual grouping of features for human face detection

Present approaches to human face detection have made several assumptions that restrict their ability to be extended to general imaging conditions. We identify that the key factor in a generic and robust system is that of exploiting a large amount of evidence, related and reinforced by model knowledge through a probabilistic framework. In this paper, we propose a face detection framework that groups image features into meaningful entities-using perceptual organization, assigns probabilities to each of them, and reinforce there probabilities using Bayesian reasoning techniques. True hypotheses of faces will be reinforced to a high probability. The detection of faces under scale, orientation and viewpoint variations will be examined in a subsequent paper.