Miracle-dz/UniFAR-FTUs huggingface dataset:
Analysis of Multiple Sarcoma Expression Datasets: Implications for Classification, Oncogenic Pathway Activation and Chemotherapy Resistance

Background Diagnosis of soft tissue sarcomas (STS) is challenging. Many remain unclassified (not-otherwise-specified, NOS) or grouped in controversial categories such as malignant fibrous histiocytoma (MFH), with unclear therapeutic value. We analyzed several independent microarray datasets, to identify a predictor, use it to classify unclassifiable sarcomas, and assess oncogenic pathway activation and chemotherapy response. Methodology/Principal Findings We analyzed 5 independent datasets (325 tumor arrays). We developed and validated a predictor, which was used to reclassify MFH and NOS sarcomas. The molecular “match” between MFH and their predicted subtypes was assessed using genome-wide hierarchical clustering and Subclass-Mapping. Findings were validated in 15 paraffin samples profiled on the DASL platform. Bayesian models of oncogenic pathway activation and chemotherapy response were applied to individual STS samples. A 170-gene predictor was developed and independently validated (80-85% accuracy in all datasets). Most MFH and NOS tumors were reclassified as leiomyosarcomas, liposarcomas and fibrosarcomas. “Molecular match” between MFH and their predicted STS subtypes was confirmed both within and across datasets. This classification revealed previously unrecognized tissue differentiation lines (adipocyte, fibroblastic, smooth-muscle) and was reproduced in paraffin specimens. Different sarcoma subtypes demonstrated distinct oncogenic pathway activation patterns, and reclassified MFH tumors shared oncogenic pathway activation patterns with their predicted subtypes. These patterns were associated with predicted resistance to chemotherapeutic agents commonly used in sarcomas. Conclusions/Significance STS profiling can aid in diagnosis through a predictor tracking distinct tissue differentiation in unclassified tumors, and in therapeutic management via oncogenic pathway activation and chemotherapy response assessment.
Human-Assisted Calibration of an Angulation Based Indoor Location System

A simple setup process is essential for the adoption of location systems. Existing systems often require a time consuming calibration process. In this paper we present an approach for the calibration of an angulation-based indoor location system which only requires from the user to walk through the room. The novelty of this approach is that the localization of the nodes is realized without any prior knowledge about sensor positions and orientations and the location of the moving person. It is shown that nevertheless an accurate localization of the sensor nodes is possible. The presented algorithm is based on the Newton-Raphson method for solving non-linear equation systems. The accuracy of the approach is evaluated by some simulations and a real-world test scenario utilizing a location system that exploits the thermal radiation of humans for localization.
The Scots in England – a different kind of diaspora?

ABSTRACT There is a growing interest in the Scottish diaspora, with the Scottish Government keen to develop links with Scots elsewhere. The closest diaspora is in England but appears relatively weak, with Scottish identity declining in strength. Using qualitative interviews, we explore the nature of the Scottish diaspora in England, seeking to explain why it appears less strong than diasporas overseas, for example in North America. We conclude that fewer Scots are migrating to England and that the children of migrant Scots are more likely to adopt an English identity. The diaspora is not, therefore, being ‘refreshed’ and is declining.
Mycobacterial PE/PPE Proteins at the Host-Pathogen Interface

The mycobacterial PE/PPE proteins have attracted much interest since their formal identification just over a decade ago. It has been widely speculated that these proteins may play a role in evasion of host immune responses, possibly via antigenic variation. Although a cohesive understanding of their function(s) has yet to be established, emerging data increasingly supports a role for the PE/PPE proteins at multiple levels of the infectious process. This paper will delineate salient features of the families revealed by comparative genomics, bioinformatic analyses and genome-wide screening approaches and will summarise existing knowledge of subcellular localization, secretion pathways, and protein structure. These characteristics will be considered in light of findings on innate and adaptive host responses to PE/PPE proteins, and we will review the increasing body of data on B and T cell recognition of these proteins. Finally, we will consider how current knowledge and future explorations may contribute to a more comprehensive understanding of these intriguing proteins and their involvement in host pathogen interactions. Ultimately this information could underpin future intervention strategies, for example, in the area of new and improved diagnostic tools and vaccine candidates.
On Energy-efficiency in Wireless Networks: A Game-theoretic Approach to Cooperation Inspired by Evolutionary Biology

We develop a game-theoretic framework to investigate the effect of cooperation on the energy efficiency in wireless networks. We address two examples of network architectures, resembling ad-hoc network and network with central infrastructure node. Most present approaches address the issue of energy efficiency in communication networks by using complex algorithms to enforce cooperation in the network, followed by extensive signal processing at the network nodes. Instead, we address cooperative communication scenarios which are governed by simple, evolutionary-like, local rules, and do not require strategic complexity of the network nodes. The approach is motivated by recent results in evolutionary biology which suggest that cooperation can emerge in Nature by evolution, i. e. can be favoured by natural selection, if certain mechanism is at work. As result, we are able to show by experiments that cooperative behavior can indeed emerge and persist in wireless networks, even if the behavior of the individual nodes is driven by selfish decision making. The results from this work indicate that uncomplicated local rules, followed by simple fitness evaluation, can promote cooperation and generate network behavior which yields global energy efficiency in certain wireless networks.
The effects of extracorporeal shock wave therapy on pain, disability, and depression of chronic low back pain patients

[Purpose] The purpose of this study was to examine the effects of extracorporeal shock wave therapy on pain, disability, and depression of chronic low back pain patients. [Subjects] In this study, 30 chronic low back pain patients were divided into an extracorporeal shock wave therapy group (ESWTG, n=15) and a conservative physical therapy group (CPTG, n=15). [Methods] The ESWTG received extracorporeal shock wave therapy and the CPTG received general conservative physical therapy two times per week for six weeks. Pain was measured using a visual analog scale (VAS), the degree of disability of the patients was assessed using the Oswestry Disability Index (ODI), and their degree of depression was measured using the Beck depression index (BDI). [Results] In intra-group comparisons, ESWTG and CPTG showed significant decreases in VAS, ODI, and BDI scores. Intergroup comparisons revealed that these decreases in VAS, ODI, and BDI scores were significantly larger in ESWTG than in CPTG. [Conclusion] Extracorporeal shock wave therapy is an effective intervention for the treatment of pain, disability, and depression in chronic low back pain patients.
Computerized training of working memory in children with ADHD--a randomized, controlled trial.

OBJECTIVE Deficits in executive functioning, including working memory (WM) deficits, have been suggested to be important in attention-deficit/hyperactivity disorder (ADHD). During 2002 to 2003, the authors conducted a multicenter, randomized, controlled, double-blind trial to investigate the effect of improving WM by computerized, systematic practice of WM tasks. METHOD Included in the trial were 53 children with ADHD (9 girls; 15 of 53 inattentive subtype), aged 7 to 12 years, without stimulant medication. The compliance criterion (>20 days of training) was met by 44 subjects, 42 of whom were also evaluated at follow-up 3 months later. Participants were randomly assigned to use either the treatment computer program for training WM or a comparison program. The main outcome measure was the span-board task, a visuospatial WM task that was not part of the training program. RESULTS For the span-board task, there was a significant treatment effect both post-intervention and at follow-up. In addition, there were significant effects for secondary outcome tasks measuring verbal WM, response inhibition, and complex reasoning. Parent ratings showed significant reduction in symptoms of inattention and hyperactivity/impulsivity, both post-intervention and at follow-up. CONCLUSIONS This study shows that WM can be improved by training in children with ADHD. This training also improved response inhibition and reasoning and resulted in a reduction of the parent-rated inattentive symptoms of ADHD.
Fixed point optimization of deep convolutional neural networks for object recognition

Deep convolutional neural networks have shown promising results in image and speech recognition applications. The learning capability of the network improves with increasing depth and size of each layer. However this capability comes at the cost of increased computational complexity. Thus reduction in hardware complexity and faster classification are highly desired. This work proposes an optimization method for fixed point deep convolutional neural networks. The parameters of a pre-trained high precision network are first directly quantized using L2 error minimization. We quantize each layer one by one, while other layers keep computation with high precision, to know the layer-wise sensitivity on word-length reduction. Then the network is retrained with quantized weights. Two examples on object recognition, MNIST and CIFAR-10, are presented. Our results indicate that quantization induces sparsity in the network which reduces the effective number of network parameters and improves generalization. This work reduces the required memory storage by a factor of 1/10 and achieves better classification results than the high precision networks.
XMM-Newton Observations of IGR J00291+5934: Signs of a Thermal Spectral Component during Quiescence

We present X-ray observations of the transient accretion-powered millisecond pulsar IGR J00291+5934 during quiescence. IGR J00291+5934 is the first source among accretion-powered millisecond pulsars to show signs of a thermal component in its quiescent spectrum. Fitting this component with a neutron star atmosphere or a blackbody model we obtain soft temperatures (~64 and ~110 eV, respectively). As in other sources of this class a hard spectral component is also present, comprising more than 60% of the unabsorbed 0.5-10 keV flux. Interpreting the soft component as cooling emission from the neutron star, we can conclude that the compact object can be spun up to millisecond periods by accreting only ≲0.2 M☉.
c-jun Is Dispensable for Developmental Cell Death and Axogenesis in the Retina

Although a number of studies have implicated c-Jun in neuronal death and axonal regeneration, it is unknown whether Jun function is essential for either response. One approach to resolve this issue is to analyze knock-out mice. However, c-jun-null mice die at midgestation, precluding critical investigation. Therefore, a xenograft paradigm was used in which retinas from embryonic day 12.5 (E12.5) c-jun nullizygous or wild-type mice were transplanted onto the superior colliculus of newborn rats. The rats were allowed to develop, and the grafts were assayed at various times for cell death and axon growth. Histologically, grafts of both genotypes developed in identical manners and had morphological characteristics of retinas. A functional c-jun allele was not essential for axogenesis, because ganglion cells in retinal grafts from c-jun nullizygous mice developed axons that projected into the colliculus. Programmed cell death (PCD) was also evident in the age-appropriate regions of the retina in both wild-type and c-jun-null grafts. Furthermore, there were no discernible differences in the number or location of dying cells in the two genotypes. That c-jun was not essential for PCD was supported by two additional findings. First, a c-jun-lacZ reporter gene was expressed in many cells in developing and grafted retinas, although only a few of these cells were destined to die. Second, in E12.5 c-jun-null embryos there were normal levels of PCD in the trigeminal ganglion. Together, these data indicate that c-Jun is not essential for axon growth in the retina or for PCD in the retina and trigeminal ganglion.
Robust model order selection for corneal height data based on τ estimation

Corneal height data, typically measured with a videokeratoscope, is modeled as a set of Zernike polynomials. Accurate corneal modeling is important, e.g. prior to surgery. The measurements require a good quality of the pre-corneal tear film and sufficiently wide eyelid aperture, which is not always fulfilled in practice. This results in missing values or outliers in the corneal topography map. We suggest to treat this problem by a new two step model selection procedure and introduce a criterion based on τ-estimation, which is simultaneously statistically robust and efficient. For this, we exploit the asymptotic equivalence of τ-estimation to M-estimation. The performance is evaluated using simulations, as well as real data.
T cell receptor V gene usage by human T cells stimulated with the superantigen streptococcal M protein

M proteins, the major virulence factor of group A streptococci, have been implicated in the pathogenesis of acute rheumatic fever (ARF) and other streptococcal related autoimmune diseases. A 22-kD fragment of M type 5 protein is a potent stimulant of human T cells and has recently been shown by our laboratory to belong to the newly designated family of superantigens. Using flow cytometry and the polymerase chain reaction, we demonstrate that this molecule reacts with subsets of human T cells expressing specific T cell receptor (TCR) V beta elements, namely V beta 2, 4, and 8. We employed similar techniques to analyze the TCR V alpha usage of pep M5-stimulated T cells. These studies revealed that the preferential usage of particular V alpha elements is not specific for the superantigen; rather, it may reflect the repertoire of the individual being tested. The expansion of a large number of T cells bearing specific TCR V beta sequences by M protein may account for its role in mediating the pathogenesis of post- streptococcal diseases. Furthermore, the preferential usage of TCR V alpha elements in certain individuals may be an important factor that predisposes them to development of self-reactivity.
Stop-and-Wait Hybrid-ARQ Performance at IP Level under Imperfect Feedback

We investigate several types of Stop and Wait HARQ schemes under imperfect feedback conditions. Performance are measured through the usual metrics, i.e., packet error rate, delay, and efficiency. The main novelties of this paper are twofold: i) the considered feedback undergoes the random arrival time of the acknowledgment. ii) the analysis is done at the network level (IP) which enlarges the vision of practical systems performance. In particular, our analysis enables us to consider a recent cross-layer MAC-IP allocation strategy. Finally our results provide a way to design the feedback link.
Impact of a Vertical Vorticity Constraint in Variational Dual-Doppler Wind Analysis: Tests with Real and Simulated Supercell Data

AbstractOne of the greatest challenges to dual-Doppler retrieval of the vertical wind is the lack of low-level divergence information available to the mass conservation constraint. This study examines the impact of a vertical vorticity equation constraint on vertical velocity retrievals when radar observations are lacking near the ground. The analysis proceeds in a three-dimensional variational data assimilation (3DVAR) framework with the anelastic form of the vertical vorticity equation imposed along with traditional data, mass conservation, and smoothness constraints. The technique is tested using emulated radial wind observations of a supercell storm simulated by the Advanced Regional Prediction System (ARPS), as well as real dual-Doppler observations of a supercell storm that occurred in Oklahoma on 8 May 2003. Special attention is given to procedures to evaluate the vorticity tendency term, including spatially variable advection correction and estimation of the intrinsic evolution. Volume scan times .
Genus Statistics for Galaxy Clusters and Nonlinear Biasing of Dark Matter Halos

We derive an analytic formula of genus for dark matter halos assuming that the primordial mass density field obeys the random-Gaussian statistics. In particular, we for the first time take account of the nonlinear nature of the halo biasing, in addition to the nonlinear gravitational evolution of the underlying mass distribution. We examine in detail the extent to which the predicted genus for halos depends on the redshift, smoothing scale of the density field, and the mass of those halos in representative cold dark matter models. In addition to the full model predictions, we derive an explicit perturbation formula for the halo genus which can be applied to a wider class of biasing model for dark matter halos. With the empirical relation between the halo mass and the luminosity/temperature of galaxy clusters, our prediction can be compared with the upcoming cluster redshift catalogs in the optical and X-ray bands. Furthermore, we discuss the detectability of the biasing and cosmological model dependence from the future data.
EMT and Stem Cell-Like Properties Associated with HIF-2α Are Involved in Arsenite-Induced Transformation of Human Bronchial Epithelial Cells

Background Arsenic is well-established as a human carcinogen, but the molecular mechanisms leading to arsenic-induced carcinogenesis are complex and elusive. It is not been determined if the epithelial-mesenchymal transition (EMT) and stem cell-like properties contribute in causing to carcinogen-induced malignant transformation and subsequent tumor formation. Methods To investigate the molecular mechanisms underlying EMT and the emergence of cancer stem cell-like properties during neoplastic transformation of human bronchial epithelial (HBE) cells induced by chronic exposure to arsenite. HBE cells were continuously exposed to arsenite. Spheroid formation assays and analyses of side populations (SPs) were performed to confirm that arsenite induces the acquired EMT and cancer stem cell-like phenotype. Treated HBE cells were molecularly characterized by RT-PCR, Western blots, immunofluorescence, Southwestern assays, reporter assays, and chromatin immunoprecipitation. Results With chronic exposure to arsenite, HBE cells undergo an EMT and then acquire a malignant cancer stem cell-like phenotype. Twist1 and Bmi1 are involved in arsenite-induced EMT. The process is directly regulated by HIF-2α. The self-renewal genes, Oct4, Bmi1, and ALDH1, are necessary for arsenite-mediated maintenance of stem cells. Conclusions EMT, regulated by HIF-2α, and the development of a cancer stem cell-like phenotype are associated with arsenite-induced transformation of HBE cells.
Inter-Ring Traffic Engineering for Bridged IEEE 802.17 Resilient Packet Rings

When bridging resilient packet rings, previous research have focused on how to prevent the flooding of inter-ring traffic, or traffic whose source and destination nodes are on different rings. In this paper, we propose that attention should also be paid to buffer overflow at the bridges, because packets dropped in transit reduce the overall network performance. The reasons that make buffer overflow more likely to occur in bridged RPR networks than in other bridged networks are analyzed. The concept of global fairness for inter-ring traffic and the global fairness algorithm for implementing global fairness are proposed. Then we propose how the global fairness algorithm can be extended to successfully prevent buffer overflow from occurring. Simulation results are then presented to support our proposals
Optimal distributed all pairs shortest paths and applications

We present an algorithm to compute All Pairs Shortest Paths (APSP) of a network in a distributed way. The model of distributed computation we consider is the message passing model: in each synchronous round, every node can transmit a different (but short) message to each of its neighbors. We provide an algorithm that computes APSP in O(n) communication rounds, where n denotes the number of nodes in the network. This implies a linear time algorithm for computing the diameter of a network. Due to a lower bound these two algorithms are optimal up to a logarithmic factor. Furthermore, we present a new lower bound for approximating the diameter D of a graph: Being allowed to answer D+1 or D can speed up the computation by at most a factor D. On the positive side, we provide an algorithm that achieves such a speedup of D and computes an (1+εepsilon) multiplicative approximation of the diameter. We extend these algorithms to compute or approximate other problems, such as girth, radius, center and peripheral vertices. At the heart of these approximation algorithms is the S-Shortest Paths problem which we solve in O(|S|+D) time.
PENGARUH PERSEPSI PELAKU USAHA MIKRO KECIL DAN MENENGAH TENTANG AKUNTANSI, PENGETAHUAN AKUNTANSI, DAN SKALA USAHA TERHADAP PENGGUNAAN INFORMASI AKUNTANSI

Penelitian ini bertujuan untuk mengetahui:(1) pengaruh persepsi pelaku UMKM tentang akuntansi terhadap penggunaan informasi akuntansi, (2) pengaruh pengetahuan akuntansi terhadap penggunaan informasi akuntansi, (3) pengaruh skala usaha terhadap penggunaan informasi akuntansi, (4) pengaruh terhadap penggunaan informasi akuntansi. Penelitian ini merupakan penelitian kausal. Sampel penelitian adalah pelaku UMKM di Kota Yogyakarta sebanyak 152 pelaku UMKM. Metode pengambilan sampel adalah Proportional Random Sampling . Teknik analisis data menggunakan analisis statistik deskriptif, uji prasyarat analisis, dan analisis regresi linier berganda. Hasil penelitian ini menunjukkan bahwa: (1) terdapat pengaruh positif persespi pelaku UMKM terhadap penggunaan informasi. (2) terdapat pengaruh positif pengetahuan akuntansi terhadap penggunaan informasi akuntansi. (3) tidak terdapat pengaruh positif skala usaha terhadap penggunaan informasi akuntansi. (4) terdapat pengaruh positif persepsi pelaku UMKM tentang akuntansi, pengetahuan akuntansi, dan skala usaha terhadap penggunaan informasi akuntansi. Kata kunci: Persepsi Pelaku UMKM tentang Akuntansi, Pengetahuan Akuntansi, Skala usaha, Penggunaan Informasi Akuntansi.