Miracle-dz/UniFAR-FTUs huggingface dataset:
Understanding cancer survivors’ information needs and information-seeking behaviors for complementary and alternative medicine from short- to long-term survival: a mixed-methods study

Objective The research examined complementary and alternative medicine (CAM) information-seeking behaviors and preferences from short- to long-term cancer survival, including goals, motivations, and information sources. Methods A mixed-methods approach was used with cancer survivors from the “Assessment of Patients’ Experience with Cancer Care” 2004 cohort. Data collection included a mail survey and phone interviews using the critical incident technique (CIT). Results Seventy survivors from the 2004 study responded to the survey, and eight participated in the CIT interviews. Quantitative results showed that CAM usage did not change significantly between 2004 and 2015. The following themes emerged from the CIT: families’ and friends’ provision of the initial introduction to a CAM, use of CAM to manage the emotional and psychological impact of cancer, utilization of trained CAM practitioners, and online resources as a prominent source for CAM information. The majority of participants expressed an interest in an online information-sharing portal for CAM. Conclusion Patients continue to use CAM well into long-term cancer survivorship. Finding trustworthy sources for information on CAM presents many challenges such as reliability of source, conflicting information on efficacy, and unknown interactions with conventional medications. Study participants expressed interest in an online portal to meet these needs through patient testimonials and linkage of claims to the scientific literature. Such a portal could also aid medical librarians and clinicians in locating and evaluating CAM information on behalf of patients.
Osteolytic Breast Cancer Causes Skeletal Muscle Weakness in an Immunocompetent Syngeneic Mouse Model

Muscle weakness and cachexia are significant paraneoplastic syndromes of many advanced cancers. Osteolytic bone metastases are common in advanced breast cancer and are a major contributor to decreased survival, performance, and quality of life for patients. Pathologic fracture caused by osteolytic cancer in bone (OCIB) leads to a significant (32%) increased risk of death compared to patients without fracture. Since muscle weakness is linked to risk of falls which are a major cause of fracture, we have investigated skeletal muscle response to OCIB. Here, we show that a syngeneic mouse model of OCIB (4T1 mammary tumor cells) leads to cachexia and skeletal muscle weakness associated with oxidation of the ryanodine receptor and calcium (Ca2+) release channel (RyR1). Muscle atrophy follows known pathways via both myostatin signaling and expression of muscle-specific ubiquitin ligases, atrogin-1 and MuRF1. We have identified a mechanism for skeletal muscle weakness due to increased oxidative stress on RyR1 via NAPDH oxidases [NADPH oxidase 2 (Nox2) and NADPH oxidase 4 (Nox4)]. In addition, SMAD3 phosphorylation is higher in muscle from tumor-bearing mice, a critical step in the intracellular signaling pathway that transmits TGFβ signaling to the nucleus. This is the first time that skeletal muscle weakness has been described in a syngeneic model of OCIB and represents a unique model system in which to study cachexia and changes in skeletal muscle.
Significance of Disk Failure Prediction in Datacenters

Modern datacenters assemble a very large number of disk drives under a single roof. Even if economic and technical factors where to make individual drives more reliable (which is not at all clear, given the commoditization of the technology), their sheer numbers combined with their ever increasing utilization in a well-balanced design makes achieving storage reliability a major challenge. In this paper, we assess the challenge of storage system reliability in the modern datacenter, and demonstrate how good disk failure prediction models can significantly improve the reliability of such systems.
Improving dynamic data analysis with aspect-oriented programming

In this paper we present a new instrumentation approach to reverse engineer a given software application. Our approach is based on aspect-oriented programming and provides support for dynamic feature analysis. The advantage of bur approach compared to other existing approaches is that we allow the engineer to obtain deeper insights into the program executions and to combine these insights with existing analysis techniques. As we show in this paper this significantly reduces the time necessary to obtain viable traces of a program's execution.
End-to-End Rate-Distortion Optimized Description Generation for H.264 Multiple Description Video Coding

In this paper, H.264/AVC primary and redundant slices interlaced multiple description video coding (PRSI-MDVC) is studied due to its high coding efficiency and ease of constructing multiple descriptions by interleaving primary and redundant slices, where the problem of optimal description generation in the rate-distortion sense is addressed. Optimal description generation requires minimization of end-to-end distortion consisting of both source coding distortion determined by quality of primary slices and channel distortion associated with redundant slice coding, subject to a rate constraint. The relevant existing works on the description generation mainly focus on the estimation of channel distortion to determine the amount of inserted redundancy (quality of redundant slices) but ignore the source distortion estimation for the quality of primary slices, thus a comprehensive end-to-end rate-distortion optimization is still unavailable. In this paper, we attack the minimization of the end-to-end distortion by fully exploring temporal coding dependency. Specifically, on one hand, a most recently developed source distortion temporal propagation model is employed to determine coding options of primary slices in the PRSI-MDVC. On the other hand, channel distortion estimation is mainly concerned with the mismatch error estimation when primary slices are lost. Unlike the existing channel distortion estimation approach under the asymptotic fine quantization assumption which is not valid in most practical cases (e.g., at low or medium coding rates), we develop a novel and more feasible estimation scheme, based on which coding parameters of the redundant slices can be better determined. Simulation results show the effectiveness of the proposed frame-level rate-distortion optimized description generation scheme compared with the relevant approaches.
Controlling the segmentation parameters by case-based reasoning

We propose a case-based image segmentation method, which takes the non-image information and the image characteristics and selects among a set of cases the case which fits best to the current case. The segmentation parameter associated to the close case are applied to the segmentation unit and taken for segmentation of the current case. By taking into account the non-image and image information we break down our complex solution space to a subspace of relevant cases where the variation among the cases is limited. Besides that with case based reasoning we can incrementally learn new image segmentation parameters. We use our approach for determination of brain/liquor ratio in CT images. This parameter is used for diagnosis of Alzheimer disease.
Neural Network Partitioning by NO and cGMP

The stomatogastric ganglion (STG) of the crab Cancer productus contains ∼30 neurons arrayed into two different networks (gastric mill and pyloric), each of which produces a distinct motor pattern in vitro. Here we show that the functional division of the STG into these two networks requires intact NO–cGMP signaling. Multiple nitric oxide synthase (NOS)-like proteins are expressed in the stomatogastric nervous system, and NO appears to be released as an orthograde transmitter from descending inputs to the STG. The receptor of NO, a soluble guanylate cyclase (sGC), is expressed in a subset of neurons in both motor networks. When NO diffusion or sGC activation are blocked within the ganglion, the two networks combine into a single conjoint circuit. The gastric mill motor rhythm breaks down, and several gastric neurons pattern switch and begin firing in pyloric time. The functional reorganization of the STG is both rapid and reversible, and the gastric mill motor rhythm is restored when the ganglion is returned to normal saline. Finally, pharmacological manipulations of the NO–cGMP pathway are ineffective when descending modulatory inputs to the STG are blocked. This suggests that the NO–cGMP pathway may interact with other biochemical cascades to partition rhythmic motor output from the ganglion.
Counting on Friends: Cues to Perceived Trustworthiness in Facebook Profiles

Personal profiles on social network sites have become an important tool for social evaluation – that is, assessing profile owners’ characteristics (e.g., personality traits, narcissism, physical and social attractiveness). The present study is one of the first to examine how users’ trustworthiness is evaluated by naïve observers based on information contained in Facebook profiles, or profile cues. Drawing on uncertainty reduction theory, warranting theory, and hardwired perceptions of facial displays, we propose a framework that identifies cues associated with trustworthiness in Facebook profiles. Results show that six profile cues (number of friends, number of tagged photographs, number of “about me” categories filled out, number of comments and “likes” received from friends, and smiling profile photographs) explained about a third of the variance in Facebook users’ perceived trustworthiness. Number of friends had a curvilinear, U-shaped effect on trustworthiness perceptions, with an inflection point at about 500 friends. That is, trustworthiness decreased as number of friends increased up to 500, and then trustworthiness increased as number of friends increased beyond 500. Theoretical and design implications of the findings are discussed.
Catadioptric camera calibration using geometric invariants

Central catadioptric cameras are imaging devices that use mirrors to enhance the field of view while preserving a single effective viewpoint. In this paper, we propose a novel method for the calibration of central catadioptric cameras using geometric invariants. Lines and spheres in space are all projected into conics in the catadioptric image plane. We prove that the projection of a line can provide three invariants whereas the projection of a sphere can only provide two. From these invariants, constraint equations for the intrinsic parameters of catadioptric camera are derived. Therefore, there are two kinds of variants of this novel method. The first one uses projections of lines and the second one uses projections of spheres. In general, the projections of two lines or three spheres are sufficient to achieve catadioptric camera calibration. One important conclusion in this paper is that the method based on projections of spheres is more robust and has higher accuracy than that based on projections of lines. The performances of our method are demonstrated by both the results of simulations and experiments with real images.
An automated system for the controlled stripping of thin silicon layers

2014 An automated apparatus, consisting of an electronic programmer and a specially designed electrolitic cell, has been set up for the controlled stripping of silicon layers. The apparatus has been planned to be used in the determination of impurity concentration profiles with the technique of differentiel resistivity measurements by layer stripping. REVUE DE PHYSIQUE APPLIQUÉE TOME 13, FÉVRIER 1978, PAGE Classification Physics Abstracts 07 . 50
Integrating OpenStreetMap with Google Street View using image processing and machine learning

OpenStreetMap is rapidly expanding crowd-sourced data base of world map. This data, if integrated with visual information from Google Street View would be an immense store of information without manual crowd collection. This paper proposes a method of probabilistically evaluating values of heading or camera angle of Google Street View which points directly to the entity of interest whose latitude and longitude information is provided by OpenStreetMap. A classifier is pre-trained on a set of images for a fixed number of classes present in OSM textual data. This classifier is then used to predict the probability of a particular heading value for a given location marked by its geolocation information. The final accuracy of prediction of heading is obtained as 27%
P3N: profiling the potential of a peer-based data management system

A large number of peer-to-peer (P2P) networks have been introduced in the literature since their popular advent in the late 1990s. In particular, structured P2P overlays have gained much attention since 2001. They are noted mainly for their theoretical properties such as balancing of communication, storage and processing load, as well as elegance of design.
Tissue and organ donation for research in forensic pathology: the MRC Sudden Death Brain and Tissue Bank

Novel methodological approaches to the investigation of brain and non‐central nervous system disorders have led to increased demand for well‐characterized, high quality human tissue samples, particularly from control cases. In the setting of the new Human Tissue legislation, we sought to determine whether relatives who have been suddenly bereaved are willing to grant authorization for research use of post mortem tissue samples and organs in sufficient numbers to support the establishment of a brain and tissue bank based in the forensic service. Research authorization was sought from families on the day prior to forensic post mortem examination followed up by written confirmation. We have to date selected individuals who have died suddenly (age range 1–89 years) and who were likely to have normal brains or who had displayed symptoms of a CNS disorder of interest to researchers, including psychiatric disorders. One hundred and eleven families have been approached during the first 2 years of this project. Research use of tissue samples was authorized by 96% of families and 17% agreed to whole brain donation. Audit of families' experience does not suggest that they are further distressed by being approached. Respondents expressed a clear view that the opportunity for research donation should be open to all bereaved families. Despite the sometimes long post mortem intervals, the quality of tissue samples is good, as assessed by a range of markers including Agilent BioAnalyzer quantification of RNA integrity (mean value 6.4). We conclude that the vast majority of families are willing to support research use of post mortem tissues even in the context of sudden bereavement and despite previous adverse publicity. The potential for acquisition of normal CNS and non‐CNS tissues and of various hard‐to‐get CNS disorders suggests that efforts to access the forensic post mortem service for research material are eminently worthwhile. Copyright © 2007 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.
A new approach for image segmentation with MATLAB

Image segmentation is the first step in many computer vision methods and serves to simplify the problem by grouping the pixels in the image in logical ways. Here we develop a new approach to deal with the problem of image segmentation in the framework of MATLAB programming environment which integrates thresholding, edge extraction and color information and shows good results when applied to some sample images. Further, we describe the merits and demerits of the proposed algorithm. In fact we can use this segmentation technique as an improvement over the in-built MATLAB 'edge detection' function.
sox21a directs lateral line patterning by modulating FGF signaling

The development of organs composed by repeated functional units is, in many cases, accomplished by the transition of cells from a progenitor to a differentiation domain, triggering a reiterated developmental program. Yet, how these discrete fields are formed during development is still a largely unresolved question. The posterior lateral line (pLL), a sensory organ present in fish and amphibians, develops from a primordium that migrates along the flanks of the animal periodically depositing neuromasts, the pLL functional units. In zebrafish (Danio rerio), the developmental program of the pLL is triggered by the transit of progenitor cells from a Wnt to a Fgf signaling domain. It has been proposed that these two fields are defined by the antagonistic activity of these two signaling pathways, but how they are formed and maintained is still an open question in the development of the pLL. In this work, we show that sox21a, an HMG ‐box transcription factor, is expressed within the Fgf domain. We demonstrate that, while the Fgf signaling pathway do not control sox21a, knockdown of sox21a causes impairment of Fgf signaling, expansion of the Wnt signaling domain and disruption of neuromast development. These results suggest that sox21a is a key player in the pLL primordium patterning, fine‐tuning the border of the Fgf and Wnt signaling domains. © 2014 Wiley Periodicals, Inc. Develop Neurobiol 75: 80–92, 2015
Attention Deficit Hyperactivity Disorder and Social Anxiety in Istanbul Heavy Metal Bar Patrons

Objective: We aimed to examine the heavy metal bar patrons in Istanbul by means of self-reported questionnaires for psychiatric disorder symptoms. Material and Methods: Seventy-one volunteers from 4 popular heavy metal bars were included to the study. The Beck Depression Inventory, the Liebowitz Social Anxiety Scale (LSAS), the Adult Attention Deficit Disorder/Attention Deficit and Hyperactivity Disorder (ADD/ADHD) Scale and the Michigan Alcoholism Screening Test (MAST) were administered to the participants. Results: One fourth of the participants (25.4%) were under high risk for a depressive episode (BDIagt;17), 22 (32.3%) reported significant social anxiety (LSASagt;30), and 41 (57.7%) showed moderate ADHD symptoms (Adult ADD/ADHD scale: 20-59). According to BDI score participants who were under the risk for depression showed higher scores in Adult ADD/ADHD scale scores than that of participants who were not under a risk for depression (p=0.001 for attention deficit; p=0.003 for hyperactivity; p=0.002 for impulsivity; p=0.001 for total score). In the study group, ADD/ADHD scale attention deficit score was positively correlated with the total fear, total avoidence and the total scores of LSAS (r=.359 palt;0.01; r=.332 palt;0.01; r=.358 palt;0.01, respectively). Conclusion: Heavy metal bar patrons appear to be a particular social group with an increased risk of psychopathology.
Large scale malware collection : lessons learned

In order to assure accuracy and realism of resilience assessment methods and tools, it is essential to have access to field data that are unbiased and representative. Several initiatives are taking place that offer access to malware samples for research purposes. Papers are published where techniques have been assessed thanks to these samples. Definition of benchmarking datasets is the next step ahead. In this paper, we report on the lessons learned while collecting and analysing malware samples in a large scale collaborative effort. Three different environments are described and their integration used to highlight the open issues that remain with such data collection. Three main lessons are offered to the reader. First, creation of representative malware samples datasets is probably an impossible task. Second, false negative alerts are not what we think they are. Third, false positive alerts exist where we were not used to see them. These three lessons have to be taken into account by those who want to assess the resilience of techniques with respect to malicious faults.
Genome Sequence of a Ranavirus Isolated from Pike-Perch Sander lucioperca

ABSTRACT The pike-perch iridovirus (PPIV) was isolated in Finland from apparently healthy pike-perch fingerlings during routine disease surveillance. Our phylogenomic analysis revealed that PPIV is the first fish member of a clade of ranaviruses previously described from European and Chinese amphibians.
Post-translational Regulation of Adipose Differentiation-related Protein by the Ubiquitin/Proteasome Pathway*

Adipose differentiation-related protein (ADRP) is localized to lipid droplets in most mammalian cells. ADRP, proposed to regulate fatty acid mobilization and lipid droplet formation, is linked to lipid accumulation in foam cells of human atherosclerotic lesions. In this report, we show that ADRP protein accumulates in Chinese hamster ovary fibroblastic cells cultured in the presence of oleic acid but is destabilized when fatty acid sources are removed from culture serum. The latter effect was blocked by the proteasome inhibitor MG132, whereas inhibitors of other proteolytic processes were ineffective. Pulse-chase experiments confirmed that ADRP degradation is inhibited by MG132. Conditions that stimulate ADRP degradation also promoted the covalent modification of ADRP by ubiquitin, whereas the addition of oleic acid to culture media, which promotes triacylglycerol deposition, blunted the appearance of ubiquitinated-ADRP. Treatment with MG132 increased the levels of ADRP associated with lipid droplets, as well as throughout the cytosol. Finally, we demonstrate that the disappearance of ADRP protein after the onset of perilipin expression during adipocyte differentiation is due to degradation by proteasomes Thus, proteolytic degradation of ADRP mediated through the ubiquitin/proteasome pathway appears to be a major mode for the post-translational regulation of ADRP.
Addendum to “An Efficient Algorithm to Find All Small-Size Stopping Sets of Low-Density Parity-Check Matrices”

In an earlier transactions paper, Rosnes and Ytrehus presented an efficient algorithm for determining all stopping sets of low-density parity-check (LDPC) codes, up to a specified weight, and also gave results for a number of well-known codes including the family of IEEE 802.16e LDPC codes, commonly referred to as the WiMax codes. It is the purpose of this short paper to review the algorithm for determining the initial part of the stopping set weight spectrum (which includes the codeword weight spectrum), and to provide some improvements to the algorithm. As a consequence, complete stopping set weight spectra up to weight 32 (for selected IEEE 802.16e LDPC codes) can be provided, while in previous work only stopping set weights up to 28 are reported. In the published standard for the IEEE 802.16e codes there are two methods of construction presented, depending upon the code rate and the code length. We compare the stopping sets of the resulting codes and provide complete stopping set weight spectra (up to five terms) for all IEEE 802.16e LDPC codes using both construction methods.
On the exact decryption range for Gentry–Halevi's implementation of fully homomorphic encryption

Abstract In this paper, we revisit the fully homomorphic encryption (FHE) scheme implemented by Gentry and Halevi, which is just an instantiation of Gentry's original scheme based on ideal lattices. Their FHE scheme starts from a somewhat homomorphic encryption (SHE) scheme, and its decryption range is deeply related with the FHE construction. Gentry and Halevi gave an experimental evaluation of the decryption range, but theoretical evaluations have not been given so far. Moreover, we give a theoretical upper bound, and reconsider suitable parameters for theoretically obtaining an FHE scheme. In particular, while Gentry and Halevi use the Euclidean norm evaluation in the noise management of ciphertexts, our theoretical bound enables us to use the ∞-norm evaluation, and hence it helps to lower the difficulty of controlling the noise density of ciphertexts.