Miracle-dz/UniFAR-FTUs huggingface dataset:
Identification of the demographic and clinical factors in determining the effectiveness of robotic-assisted radical prostatectomy

Prostate cancer is a disease facing the male which has shown a significant increase worldwide and is ranked sixth globally. In Malaysia, prostate cancer is ranked sixth as the leading cause of death among male cancer patients. The breakthrough in technology has shown that the robotic-assisted radical prostatectomy (RARP) is a treatment of choice compared to the traditional open surgery. This study focuses on the effectiveness of the RARP as this procedure benefits the patients including faster return of urinary continence, erectile function and cancer control. Even though studies have shown that the RARP has resulted in quick recovery and better functional outcome, yet post surgeries by RARP have shown patients have a full return of urinary continence while a few others do not. This study was conducted to investigate the association among the potential risk factors and the effectiveness of the RARP and the association with the demographic as confounding factors. This study used the secondary data obtained from the Urology Department at Hospital Kuala Lumpur. The summary and descriptive statistics were performed to explain the demographic profile of the patients. The chi-square test was used to determine the association among the potential risk factors. The result indicates that all potential risk factors are not significantly associated with the effectiveness of the RARP except for detection of cancer. In addition it was found that Indians with margin location at apex has a chance of grade 2 effectiveness of RARP.
Lipopolysaccharides accelerate hepatic steatosis in the development of nonalcoholic fatty liver disease in Zucker rats

Nonalcoholic fatty liver disease (NAFLD) can develop into end-stage disease that includes cryptogenic cirrhosis and hepatocellular carcinoma. Bacterial endotoxin, for example lipopolysaccharide (LPS), plays an important role in the pathogenesis of NAFLD. The aim of this study was to assess the role of LPS in the development of NAFLD. Twenty-one male Zucker (fa/fa) rats were divided into three groups: rats fed for twelve weeks on a diet rich in disaccharide (D12 group), rats similarly managed but treated with LPS (LPS group), and those on the same diet for 24 weeks (D24 group). Histological examination demonstrated that this protocol induced hepatic steatosis in the LPS and D24 groups. Significant, marked accumulation of lipid droplets was observed in the LPS group, compared with the D24 group. Rats from the LPS group showed a decrease in plasma adiponectin levels, an increase in plasma leptin levels, and greater expression of FAS and SREBP-1c mRNA in the liver, compared with rats from the D24 group. These finding coincided with histological findings. We therefore suggest that LPS may accelerate the progression of hepatic steatosis.
Morphine-induced mu opioid receptor trafficking enhances reward yet prevents compulsive drug use

Morphine, heroin and other commonly abused opioids induce little mu opioid receptor (MOR) trafficking compared to endogenous opioids. We utilized knock‐in mice expressing a mutant recycling MOR (RMOR) that desensitizes and is internalized in response to morphine to show that facilitating MOR trafficking not only enhances morphine reward but, despite this, reduces the development of addiction‐like behaviours. To demonstrate this, we developed a novel model of the transition from controlled to compulsive drug use that recapitulates many features of human addiction, including persistent drug seeking despite adverse consequences and a decreased preference for alternative rewards. These behaviours emerged spontaneously in wild‐type but not RMOR mice, and their intensity predicted the reinstatement of morphine seeking after extended abstinence, while prior morphine intake did not. These results confirm previous findings in the rat that addiction can be dissociated from both reward and consumption. Most importantly, these results demonstrate that one can simultaneously reduce the ‘addictiveness’ of morphine and enhance its desirable effects by promoting agonist‐induced MOR trafficking.
phosphatase DEP-1 / PTPRJ oxidative inactivation of the tumor suppressor protein-tyrosine Cell transformation by FLT 3 ITD in acute myeloid leukemia involves

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Estimation of soil parameters over bare agriculture areas from C-band polarimetric SAR data using neural networks

The purpose of this study was to develop an approach to estimate soil surface parameters from C-band po-larimetric SAR data in the case of bare agricultural soils. An inversion technique based on multi-layer perceptron (MLP) neural networks was introduced. The neural networks were trained and validated on a noisy simulated dataset generated from the Integral Equation Model (IEM) on a wide range of surface roughness and soil moisture, as it is encountered in agricultural contexts for bare soils. The performances of neu-ral networks in retrieving soil moisture and surface roughness were tested for several inversion cases using or not using a-priori knowledge on soil parameters. The inversion approach was then validated using RADARSAT-2 images in polarimetric mode. The introduction of expert knowledge on the soil moisture (dry to wet soils or very wet soils) improves the soil moisture estimates, whereas the precision on the surface roughness estimation remains unchanged. Moreover, the use of polarimetric parameters α 1 and anisotropy were used to improve the soil parameters estimates. These parameters provide to neural networks the probable ranges of soil moisture (lower or higher than 0.30 cm 3 cm −3) and surface roughness (root mean square surface height lower or higher than 1.0 cm). Soil moisture can be retrieved correctly from C-band SAR data by using the neural networks technique. Soil moisture errors were estimated at about 0.098 cm 3 cm −3 without a-priori information on soil parameters and 0.065 cm 3 cm −3 (RMSE) applying a-priori information on the soil moisture. The retrieval of surface roughness is possible only for low and medium values (lower than 2 cm). Results show that the precision on the soil roughness estimates was about 0.7 cm. For surface roughness lower than 2 cm, the precision on the soil roughness is better with an RMSE about 0.5 cm. The use of polarimetric parameters improves only slightly the soil parameters estimates.
Support Receipt: Effect on Postsecondary Success of Students With Learning Disabilities

In contrast to the increase in college enrollment rates of youth with learning disabilities (LD), graduation rates have remained stagnant and low. Using propensity methods, this study examined the effect of disability-specific and universally available support receipt on the college perseverance and completion of students with LD. Based on secondary analysis of National Longitudinal Transition Study 2 (NLTS2), findings indicate that students who received supports—those available to the full student body and/or disability-specific supports—were more likely to persist in, and successfully complete, 2-year or 4-year college. Implications include that transition staff need to ensure students not only are prepared to seek disability supports once on campus, but that equal emphasis should be placed on helping students access supports available to the full student body.
An abandoned and removed object detection algorithm in a reactive smart surveillance system

Important issues such as low image quality and human operators' reactivity can seriously reduce the effectiveness of video surveillance systems. Digital video surveillance is used in conjunction with video analytics, which is the semantic analysis of video data through signal and image processing techniques. This paper presents a novel algorithm for real time detection of abandoned and removed objects, in the context of a reactive smart surveillance system, which notifies the occurrence of such events of interest to registered users, within seconds. The proposed algorithm is demonstrated to be completely adaptive and computationally efficient.
A Biopsychosocial Approach to Creative Dissociation: Remarks on a Case of Mediumistic Painting

A category of religious experience that still preserves much of the original blurring and fusion between art and religion is mediumistic or spirit painting. Performed by spiritualist mediums in different locations around the world, this form of religious experience is characterized by the supposed ability of an individual to serve as an instrument for deceased artists to continue to perform their works. In the manner of so-called automatic writing, mediums try to reproduce aspects of the style of deceased painters, in order to demonstrate their identity and survival of bodily death. Little scientific research has been conducted concerning this topic. We present a brief analysis of painting activity performed by Jacques Andrade, a Brazilian medium. Born in 1945, Andrade, who has been active in the Brazilian Kardecist movement for many years, has dedicated most of his religious life to mediumistic painting at his center (The Leonardo da Vinci Salon of Mediumistic Art). Data about the medium were collected on several different occasions, from 1998 to 2013, and include psychophysiological measures (hand temperature, heart rate, bilateral skin conductance, muscle tension, and electrical brain activity), psychological measures (Dissociative Experiences Scale, Tellegen Absorption Scale, Revised Transliminality Scale, and Childhood Trauma Questionnaire), artistic material, observational data (photographs of paintings, observations of the medium in action), and some basic socio-demographic and biographical information. Basically we sought to evaluate: a) general aspects of the painting technique and style employed by the medium, b) the main features of his pictorial production, and c) the general behavior shown by the medium during the mediumistic activity. In an effort to combine and integrate our findings about this case, we propose a biopsychosocial approach to the study of what might be called creative dissociation. NeuroQuantology | December 2013 | Volume 11 | Issue 4 | Page 544-572
Measuring and modifying the intrinsic memorability of images

this thesis, I developed and carried out a procedure to measure the memorability of an image by running hundreds of human-trials and making use of a custom designed image dataset, the Mem60k dataset. The large store of ground-truth memorability data enabled a variety of insights and applications. The data revealed information about what qualities (emotional content, aesthetic appeal, etc.) in an image make it memorable. Convolutional neural networks (CNNs) trained on the data could predict an image's relative memorability with high accuracy. CNNs could also generate memorability heat maps which pinpoint which parts of an image are memorable. Finally, with additional usage of a massive image database, I designed a pipeline that could modify the intrinsic memorability of an image. The performance of each application was tested and measured by running further human trials.
Image-based modeling and rendering of architecture with interactive photogrammetry and view-dependent texture mapping

We overview an approach to modeling and rendering architectural scenes from a sparse set of photographs. The approach is designed to require no special hardware and to produce real-time renderings on standard graphics hardware. The modeling method is an interactive photogrammetric modeling tool for recovering geometric models of architectural scenes from photographs. The tool is practical as an interactive method because it solves directly for architectural dimensions rather than for a multitude of vertex coordinates or depth measurements. The technique also determines the camera positions of the photographs, allowing the photographs to be taken from arbitrary unrecorded locations. The rendering method creates novel views of the scene based on the recovered model and the original photographs. A view-dependent texture mapping method allows all available image information to be used to produce the most photorealistic renderings. We focus on a number of results and applications of the method.
Medical Image Segmentation with Split-and-Merge Method

The processing of microscopic tissue images and especially the detection of cell nuclei is nowadays done more and more using digital imagery and special immunodiagnostic software products. One of the most promising methods is region growing but it is quite memory intensive. The size of highresolution tissue images can easily reach the order of a hundred megabytes therefore the memory requirement for the region growing is more than one gigabyte. To provide the execution in low-end clients we have to split the whole image into smaller tiles and after the processing of each individual tiles we have to merge the results. Keywords—medical image segmentation, parallel algorithm, gpgpu, split-and-merge
Entrepreneurship, Innovation, and Dynamic Growth vs. Instability in the Market Motivation

The challenge of the current study is to introduce entrepreneurship into Microeconomics theory for greater extendability and realism yet capture its unique aspects in a manageable analytical model. The model starts with a perfectly competitive market and then adds a subset of agents with unique skills, capabilities, startup savings, and risk preferences, called entrepreneurs. These profit-seeking agents, raising funds from the financial markets, modify a fraction of the existing products with additional (close substitute) attributes. Thus, a situation of monopolistic competition is created. A unique contribution developed is that entrepreneurship creates an endogenous cycle which brings growth but also instability and inequality at the same time caused by the risky decisions an entrepreneur has made before. The expected profit motive drives entrepreneurs to create new products, which expands supply. In perfect competition, markets' price competition erodes entrepreneurs’ monopoly rents to zero with a new equilibrium. However, in the current model, entrepreneurs simultaneously change the structure of the market toward monopolistic competition, creating a dynamic cycle where the prospect of entrepreneurial rents drives more product innovation, supply to the market, and structural change; while, at the same time, higher profit rates induce entry and price-cutting and force out old capacity and products.
Feedback stabilizes propagation of synchronous spiking in cortical neural networks

Significance Feedback projections are ubiquitous in the brain, but little is known about what they contribute to information processing. The results presented here provide testable hypotheses for the functional role of the feedback projections in the brain. Our work suggests that feedback projections could be responsible for information encoded in spike times to reliably propagate through cortex, and thus could serve as an attentional mechanism to regulate the flow of information in the cortex. Our work also suggests that feedback projections may also be critically involved in organizing neural populations involved in cognitive functions by generating and sharpening spike-time synchronization among populations of neurons. Thus, feedback projections could be key to understanding how the cortex is globally organized. Precisely timed action potentials related to stimuli and behavior have been observed in the cerebral cortex. However, information carried by the precise spike timing has to propagate through many cortical areas, and noise could disrupt millisecond precision during the transmission. Previous studies have demonstrated that only strong stimuli that evoke a large number of spikes with small dispersion of spike times can propagate through multilayer networks without degrading the temporal precision. Here we show that feedback projections can increase the number of spikes in spike volleys without degrading their temporal precision. Feedback also increased the range of spike volleys that can propagate through multilayer networks. Our work suggests that feedback projections could be responsible for the reliable propagation of information encoded in spike times through cortex, and thus could serve as an attentional mechanism to regulate the flow of information in the cortex. Feedback projections may also participate in generating spike synchronization that is engaged in cognitive behaviors by the same mechanisms described here for spike propagation.
A case for context-aware TCP/IP

This paper discusses the design and evaluation of CATNIP, a Context-Aware Transport/Network Internet Protocol for the Web. This integrated protocol uses application-layer knowledge (i.e., Web document size) to provide explicit context information to the TCP and IP protocols. While this approach violates the traditional layered Internet protocol architecture, it enables informed decision-making, both at network endpoints and at network touters, regarding flow control, congestion control, and packet discard decisions.We evaluate the performance of the context-aware TCP/IP approach first using ns-2 network simulation, and then using WAN emulation to test a prototype implementation of CATNIP in the Linux kernel of an Apache Web server. The advantages of the CATNIP approach are particularly evident in a congested Internet with 1-10% packet loss. Simulation results indicate a 10-20% reduction in TCP packet loss using simple endpoint control mechanisms, with no adverse impact on Web page retrieval times. More importantly, using CATNIP context information at IP touters can reduce mean Web page retrieval times by 20-80%, and the standard deviation by 60-90%. The CATNIP algorithm can also interoperate with Random Early Detection (RED) for active queue management.
A Semantic Information Retrieval in a Robot Museum Guide Application

A key role for the knowledge sharing on the Web is the constructive interaction between system and user. It is presented an application implemented on Cicerobot, a RWI B21 autonomous robot . It is based on a cognitive architecture and works on tasks related with guided tours in the Archae ological Museum of Agrigento. Interaction between Cicerobot and the user is base d on a first step towards semantics sharing between them. To this purpose kn wledge is represented through sub -symbolically model inside the robot. Being Cicerobot a node on the Web, its knowledge can be shared and virtual interaction during the visit is permitted. Experimental results ar e also presented showing the effectiveness of the retrieval system.
Co-creation – child, sibling or adopted cousin of open innovation?

ABSTRACT As the concept of co-creation has evolved in the innovation management literature its meaning has become ambiguous and the boundaries between it and the concept of open innovation have become opaque. The purpose of this paper is to more clearly define the concept of co-creation and to articulate how it differs from and relates to the concept of open innovation. Scholars are divided as to whether co-creation is a subsidiary concept of open innovation, a surrogate concept that is essentially indistinguishable from open innovation, or a separate concept that developed independently but was subsequently intermingled and interfused with open innovation. This paper addresses this scholarly confusion by conducting a systematic two-stage review of the innovation management literature, commencing with of a ‘broad brush’ bibliometric analysis, focused on the origins and evolution of co-creation and open innovation, followed by a ‘deep dive’ literature review in which the two concepts were rigorously compared. By proposing a cogent definition and taxonomy of co-creation, and thereby distinguishing it from open innovation, the paper goes beyond the current state of the literature and provides a more robust basis for future research.
Innovation And Productivity: Evidence From China

This paper investigates a lesser-known effect of innovation on the productivity of manufacturing firms in China using data that cover more than 330,000 firms across 40 sectors from 1998 to 2008. Innovation plays a key role in the productivity of firms and it matters for all types of firms, new as well as established. The ratio of new product output to the firm’s total outputs is used to measure innovation ability in this paper. A higher ratio is expected to have a positive impact on a firm’s productivity since new products are likely to be more differentiated than old products from other firms’ goods, which allows for a higher mark-up and thus greater profits. Comparisons are conducted for different types of firms, domestic firms, foreign firms and Hong Kong, Macau, Taiwan-affiliated firms. I also implement different measures of productivity, such as total factor productivity and labor productivity. After controlling for a number of factors, I find a significantly positive relationship between innovation and productivity across all types of firms in China. * Thanks also to the Reader, Prof. Daniel LaFave. † Department of Economics, Colby College, 5230 Mayflower Hill Drive, Waterville, ME 04901, USA. Email: jingyingxu716@gmail.com
Sensitivity Analysis of Neural Network Parameters for Identifying the Factors for College Student Success

Predicting student graduation rates in institutes of higher education is of great value to the institution and an enormous potential utility for targeted intervention. During the past decade a number of researchers applied various methodologies in order to predict enrollment rates, persistence rates, and/or graduation rates. In this paper we present the development and performance of an Artificial Neural Network (ANN) for predicting community college graduation outcomes as well as the results of applying sensitivity analysis on the ANN parameters in order to identify the factors that result into a successful graduation outcome. A sample of 1,407 student profiles was used to train and test our ANN. The average predictability rate for the ANN’s training and test sets were higher than any other reported in the literature (77% and 68%, respectively). The need for disability services, the need for support services, and the student’s age at the time of application to the college were identified as the three factors most contributory to a successful/ unsuccessful graduation outcome.
Techniques and Systems for Image and Video Retrieval

Storage and retrieval of multimedia has become a requirement for many contemporary information systems. These systems need to provide browsing, querying, navigation, and, sometimes, composition capabilities involving various forms of media. In this survey, we review techniques and systems for image and video retrieval. We first look at visual features for image retrieval such as color, texture, shape, and spatial relationships. The indexing techniques are discussed for these features. Nonvisual features include captions, annotations, relational attributes, and structural descriptions. Temporal aspects of video retrieval and video segmentation are discussed next. We review several systems for image and video retrieval including research, commercial, and World Wide Web-based systems. We conclude with an overview of current challenges and future trends for image and video retrieval.