nils-herrmann/clean_scirepeval huggingface dataset:
Cause specific mortality for 240 causes in China during 1990 2013: a systematic subnational analysis for the Global Burden of Disease Study 2013
Venue: The Lancet

China has experienced a remarkable epidemiological and demographic transition during the past three decades. Far less is known about this transition at the subnational level. Timely and accurate assessment of the provincial burden of disease is needed for evidence based priority setting at the local level in China.  Following the methods of the Global Burden of Disease Study 2013 (GBD 2013) we have systematically analysed all available demographic and epidemiological data sources for China at the provincial level. We developed methods to aggregate county level surveillance data to inform provincial level analysis, and we used local data to develop specific garbage code redistribution procedures for China. We assessed levels of and trends in all cause mortality, causes of death, and years of life lost (YLL) in all 33 province level administrative units in mainland China, all of which we refer to as provinces, for the years between 1990 and 2013.  All provinces in mainland China have made substantial strides to improve life expectancy at birth between 1990 and 2013. Increases ranged from 4.0 years in Hebei province to 14.2 years in Tibet. Improvements in female life expectancy exceeded those in male life expectancy in all provinces except Shanghai, Macao, and Hong Kong. We saw significant heterogeneity among provinces in life expectancy at birth and probability of death at ages 0 14, 15 49, and 50 74 years. Such heterogeneity is also present in cause of death structures between sexes and provinces. From 1990 to 2013, leading causes of YLLs changed substantially. In 1990, 16 of 33 provinces had lower respiratory infections or preterm birth complications as the leading causes of YLLs. 15 provinces had cerebrovascular disease and two (Hong Kong and Macao) had ischaemic heart disease. By 2013, 27 provinces had cerebrovascular disease as the leading cause, five had ischaemic heart disease, and one had lung cancer (Hong Kong) Road injuries have become a top ten cause of death in all provinces in mainland China. The most common non communicable diseases, including ischaemic heart disease, stroke, chronic obstructive pulmonary disease, and cancers (liver, stomach, and lung) contributed much more to YLLs in 2013 compared with 1990.  Rapid transitions are occurring across China, but the leading health problems and the challenges imposed on the health system by epidemiological and demographic change differ between groups of Chinese provinces. Localised health policies need to be implemented to tackle the diverse challenges faced by local health care systems.  and Bill Melinda Gates Foundation.
Scalable line based wavelet image coding in wireless sensor networks
Venue: J. Vis. Commun. Image Represent.

Visual sensor nodes have little RAM and lined based external memory.Existing scalable wavelet image coding approaches require large RAM.A novel line based scalable wavelet image coder for low RAM sensors is developed.The novel coding approach requires RAM memory for only two image lines.The coder achieves the RD performance of SPHIT and has no scalable coding overhead. Existing scalable wavelet image coding approaches, such as set partitioning in hierarchical trees and its derivatives, employ a memory intensive tree based coding structure. Existing tree based wavelet coding approaches are therefore not suitable for memory constrained sensor nodes. In this paper, we introduce a scalable wavelet image coding approach based on a line structure that requires very little memory. The proposed line based approach is suitable for scalable wavelet image coding in memory constrained sensor nodes, requiring only a few kilobytes of memory for a 256 256 pixel image. The presented line based wavelet coding algorithm accesses the image data line by line and thus conforms with the data access patterns in current flash memory technology. Our performance evaluations demonstrate that the proposed scalable line based image wavelet coding approach has no overhead compared to one run (non scalable) wavelet image coding and has competitive compression performance compared to JPEG 2000 and the recent Google WebP image format.
Analyzing performance determinants: Conventional versus Islamic Banks in Pakistan

The aim of this study is to empirically examine the bank specific, financial, and macroeconomic determinants of performance of Islamic and conventional banks in Pakistan. To do this, we first constructed the financial performance index (FPI) based on CAMELS' ratios and then run the computed index on the said determinants. We have used an unbalanced annual panel data covering the period 2006 2012. The GLS regression results show that operating efficiency, reserves, and overheads are significant determinants of conventional banks' performance, whereas, operating efficiency, deposits, and market concentration are significant in explaining performance of Islamic banks. We also show that the impact of GDP and the lending interest rate on performance is negative for both types of banks. Bank managers may focus on controlling overheads and operating costs to improve performance because, according the empirical results presented in the study, both of these variables are negatively related to the FPI. Our results suggest that advancements in overall management practices and new standards in operating efficiency and financial risk management are essential to enhance performance of banks.
FPGA implementation of low complexity LDPC iterative decoder

Low density parity check (LDPC) codes, proposed by Gallager, emerged as a class of codes which can yield very good performance on the additive white Gaussian noise channel as well as on the binary symmetric channel. LDPC codes have gained lots of importance due to their capacity achieving property and excellent performance in the noisy channel. Belief propagation (BP) algorithm and its approximations, most notably min sum, are popular iterative decoding algorithms used for LDPC and turbo codes. The trade off between the hardware complexity and the decoding throughput is a critical factor in the implementation of the practical decoder. This article presents introduction to LDPC codes and its various decoding algorithms followed by realisation of LDPC decoder by using simplified message passing algorithm and partially parallel decoder architecture. Simplified message passing algorithm has been proposed for trade off between low decoding complexity and decoder performance. It greatly reduces the routing and check node complexity of the decoder. Partially parallel decoder architecture possesses high speed and reduced complexity. The improved design of the decoder possesses a maximum symbol throughput of 92.95 Mbps and a maximum of 18 decoding iterations. The article presents implementation of 9216 bits, rate 1/2, (3, 6) LDPC decoder on Xilinx XC3D3400A device from Spartan 3A DSP family.
"They Treat Us Like Human Beings" Experiencing a Therapeutic Sex Offenders Prison
Venue: International journal of offender therapy and comparative criminology

Research evidence demonstrates that sex offender treatment programmes (SOTPs) can reduce the number of sex offenders who are reconvicted. However, there has been much less empirical research exploring the experiences and perspectives of the prison environment within which treatment takes place. This is important, particularly for sexual offenders, as they often face multiple stigmas in prison. This study used a mixed methods approach to explore the experiences of prisoners and staff at a therapeutically orientated sexual offenders' prison to understand whether the prison environment was conducive to rehabilitation. The quantitative strand of the research sampled prisoners (n 112) and staff (n 48) from a therapeutically orientated sex offenders prison. This strand highlighted that both prisoners and staff had positive attitudes toward offenders and high beliefs that offenders could change. Importantly, the climate was rated positively and, in particular, participants had very high ratings of "experienced safety." The qualitative strand of the research consisted of semistructured interviews with prisoners (n 15) and a range of prison staff (n 16) The qualitative analysis revealed positive prisoner views toward staff relationships, with most participants articulating that the prison and its staff had contributed to positive change in prisoners. Crucially, the environment was perceived as safe and allowed prisoners "headspace" to work through problems and contemplate change. This research offers some support to the notion that context is important for sex offender rehabilitation.
Fast implementation of the Niblack binarization algorithm for microscope image segmentation
Venue: Pattern Recognition and Image Analysis

A fast way to implement the Niblack binarization algorithm is described. It uses not only the integral image for the local mean values calculation, but also the second order integral image for the local variance calculation. Following the proposed approach the time of segmentation has been significantly reduced providing the possibility of its use in practice. The generalization of integral image representation, called 'k order integral image' could be used for fast calculation of higher order local statistics. An example of algorithm for the segmentation of cells and Chlamydial inclusions on microscope images, containing the steps for color deconvolution and fast adaptive local binarization is presented.
AFET: Automatic Fine Grained Entity Typing by Hierarchical Partial Label Embedding
Venue: EMNLP

Distant supervision has been widely used in current systems of fine grained entity typing to automatically assign categories (entity types) to entity mentions. However, the types so obtained from knowledge bases are often incorrect for the entity mention's local context. This paper proposes a novel embedding method to separately model "clean" and "noisy" mentions, and incorporates the given type hierarchy to induce loss functions. We formulate a joint optimization problem to learn embeddings for mentions and typepaths, and develop an iterative algorithm to solve the problem. Experiments on three public datasets demonstrate the effectiveness and robustness of the proposed method, with an average 15% improvement in accuracy over the next best compared method1.
Pola Ruang Dalam Banua Tongkonan dan Banua Barung Barung di Dusun Tonga, Kelurahan Panta'nakan Lolo, Toraja Utara

Rumah Tradisional Toraja merupakan salah satu rumah tradisional yang terdapat di Indonesia, dan letaknya di Toraja, Sulawesi Selatan. Rumah tradisional Toraja ini sendiri dibagi menjadi dua jenis yaitu Banua Tongkonan dan Banua Barung barung. Banua Tongkonan adalah rumah tradisional asli Toraja, dan Barung barung merupakan rumah tambahan di samping Tongkonan yang dapat diperhitungkan sebagai rumah tradisional pula karena pola ruang dalamnya yang mengikuti pola ruang rumah Toraja. Dewasa ini sudah banyak rumah rumah tradisional Toraja baik di kota maupun di desa yang rusak, tidak terawat, bahkan beberapa sudah tidak dihuni dan tidak berupa sebuah kesatuan yang utuh. Dusun Tonga merupakan dusun di mana rumah rumah tradisional Toraja masih dihuni dan dirawat oleh para penghuninya dan dusun ini terletak di Kecamatan Kesu, sebuah kawasan yang rumah tradisionalnya masih dilestarikan dan dihuni oleh penghuninya. Penelitian yang dilakukan di Dusun Tonga ini terfokus pada pola ruang dalam yang meliputi susunan ruang, hirarki, transisi, simbol, dan aktivitas ruang di dalamnya. Penelitian ini menggunakan metode deskriptif dengan survei langsung ke lapangan, dengan objek penelitian yaitu banua Tongkonan dan banua Barung barung yang terletak di kawasan ini. Hasil studi yang didapatkan menunjukkan susunan ruang dalam pada Banua Tongkonan dan Banua Barung barung dari beberapa jenis klasifikasi yang telah dibagi berdasarkan pola ruang dalamnya.  Rumah Toraja, banua tongkonan, barung barung, rumah tradisional, pola ruang dalam
How plot shape and spatial arrangement affect plant species richness counts: implications for sampling design and rarefaction analyses

How does the spatial configuration of sampling units influence recorded plant species richness values at small spatial scales? What are the consequences of these findings for sampling methodology and rarefaction analyses?  Six semi natural grasslands in Western Eurasia (France, Germany, Bulgaria, Hungary, Italy, Turkey)  In each site we established six blocks of 40 cm x 280 cm, subdivided into 5 cm x 5 cm micro quadrats, on which we recorded vascular plant species presence with the rooted (all sites) and shoot (four sites) presence method. Data of these micro quadrats were then combined to achieve larger sampling units of 0.01, 0.04 and 0.16 m2 grain size with six different spatial configurations (square, 4:1 rectangle, 16:1 rectangle, three variants of discontiguous randomly placed micro quadrats) The effect of the spatial configurations on species richness was quantified as relative richness compared to the mean richness of the square of the same surface area.  Square sampling units had significantly lower species richness than other spatial configurations in all countries. For 4:1 and 16:1 rectangles, the increase of rooted richness was on average about 2% and 8% respectively. In contrast, the average richness increase for discontiguous configurations was 7% 17% and 40% In general, increases were higher with shoot presence than with rooted presence. Overall, the patterns of richness increase were highly consistent across six countries, three grain sizes and two recording methods.  Our findings suggest that the shape of sampling units has negligible effects on species richness values when the length width ratio is up to 4:1, and the effects remain small even for more elongated contiguous configurations. In contrast, results from discontiguous sampling units are not directly comparable with those of contiguous sampling units, and are strongly confounded by spatial extent. This is particularly problematic for rarefaction studies where spatial extent is often not controlled for. We suggest that the concept of effective area is a useful tool to report effects of spatial configuration on richness values, and introduce species extent relationships (SERs) to describe richness increases of different spatial configurations of sampling units.
Variational Inference for Monte Carlo Objectives
Venue: ICML

Recent progress in deep latent variable models has largely been driven by the development of flexible and scalable variational inference methods. Variational training of this type involves maximizing a lower bound on the log likelihood, using samples from the variational posterior to compute the required gradients. Recently, Burda et al. (2016) have derived a tighter lower bound using a multi sample importance sampling estimate of the likelihood and showed that optimizing it yields models that use more of their capacity and achieve higher likelihoods. This development showed the importance of such multi sample objectives and explained the success of several related approaches. We extend the multi sample approach to discrete latent variables and analyze the difficulty encountered when estimating the gradients involved. We then develop the first unbiased gradient estimator designed for importance sampled objectives and evaluate it at training generative and structured output prediction models. The resulting estimator, which is based on low variance per sample learning signals, is both simpler and more effective than the NVIL estimator proposed for the single sample variational objective, and is competitive with the currently used biased estimators.
Cell free DNA (cfDNA) Clinical Significance and Utility in Cancer Shaped By Emerging Technologies
Venue: Molecular Cancer Research

Precision oncology is predicated upon the ability to detect specific actionable genomic alterations and to monitor their adaptive evolution during treatment to counter resistance. Because of spatial and temporal heterogeneity and comorbidities associated with obtaining tumor tissues, especially in the case of metastatic disease, traditional methods for tumor sampling are impractical for this application. Known to be present in the blood of cancer patients for decades, cell free DNA (cfDNA) is beginning to inform on tumor genetics, tumor burden, and mechanisms of progression and drug resistance. This substrate is amenable for inexpensive noninvasive testing and thus presents a viable approach to serial sampling for screening and monitoring tumor progression. The fragmentation, low yield, and variable admixture of normal DNA present formidable technical challenges for realization of this potential. This review summarizes the history of cfDNA discovery, its biological properties, and explores emerging technologies for clinically relevant sequence based analysis of cfDNA in cancer patients. Molecular barcoding (or Unique Molecular Identifier, UMI) based methods currently appear to offer an optimal balance between sensitivity, flexibility, and cost and constitute a promising approach for clinically relevant assays for near real time monitoring of treatment induced mutational adaptations to guide evidence based precision oncology.
New Ocean Winds Satellite Mission to Probe Hurricanes and Tropical Convection

AbstractThe Cyclone Global Navigation Satellite System (CYGNSS) is a new NASA earth science mission scheduled to be launched in 2016 that focuses on tropical cyclones (TCs) and tropical convection. The mission's two primary objectives are the measurement of ocean surface wind speed with sufficient temporal resolution to resolve short time scale processes such as the rapid intensification phase of TC development and the ability of the surface measurements to penetrate through the extremely high precipitation rates typically encountered in the TC inner core. The mission's goal is to support significant improvements in our ability to forecast TC track, intensity, and storm surge through better observations and, ultimately, better understanding of inner core processes. CYGNSS meets its temporal sampling objective by deploying a constellation of eight satellites. Its ability to see through heavy precipitation is enabled by its operation as a bistatic radar using low frequency GPS signals. The mission will depl.
Aberrations in Peripheral Inflammatory Cytokine Levels in Parkinson Disease: A Systematic Review and Meta analysis.
Venue: JAMA neurology

The association of nonmotor features and Parkinson disease (PD) is increasingly recognized. Evidence suggests that inflammation may play a role in PD pathologic features and symptoms.  To quantitatively summarize the peripheral inflammatory cytokine data available for patients with PD.  A systematic search of peer reviewed English language articles from PubMed, PsycINFO, and the Cochrane Library without year limitation was performed from December 7, 2015, to March 23, 2016. The search terms included inflammation or cytokine or chemokine or tumor necrosis factor or interleukin or interferon or C reactive protein AND Parkinson disease. Study Selection Studies were included if they provided data on peripheral blood cytokine concentrations in patients with PD and a healthy control group. Studies were excluded if they contained in vitro analysis of stimulated or unstimulated levels of cytokines, samples that overlapped with other studies, patients not diagnosed with PD at blood sampling, or if the cytokine analyzed was assessed in fewer than 3 studies. Data Extraction and Synthesis Data were extracted from the 25 included studies encompassing 1547 unique patients with PD and 1107 unique controls by 2 independent investigators. Data were pooled using a random effects model with the Comprehensive Meta analysis software. Effect sizes were generated as standardized mean differences of cytokine concentrations between patients with PD and healthy controls and converted to the Hedges g statistic.  Blood cytokine concentrations in patients with PD compared with controls. Aberrations in peripheral cytokine levels were hypothesized to be related to PD.  Among the 2654 study participants, concentrations of interleukin 6 (IL 6) (Hedges g, 0.325; 95% CI, 0.007 0.643; P .045) in 13 studies, tumor necrosis factor (Hedges g, 0.354; 95% CI, 0.144 0.563; P .001) in 9 studies, IL 1b (Hedges g, 0.382; 95% CI, 0.142 0.621; P .002) in 6 studies, C reactive protein (Hedges g, 0.323; 95% CI, 0.052 0.593; P .02) in 6 studies, IL 10 (Hedges g, 0.329; 95% CI, 0.051 0.607; P .02) in 5 studies, RANTES (regulated on activation, normal T expressed, and presumably secreted) (Hedges g, 0.605; 95% CI, 0.111 1.099; P .02) in 5 studies, and IL 2 (Hedges g, 0.789; 95% CI, 0.105 1.472; P .02) in 3 studies were significantly higher in patients with PD compared with healthy controls. No differences were found between patients with PD and healthy controls for concentrations of interferon g (Hedges g, 0.745; 95% CI, 0.192 to 1.682; P .12) in 5 studies, IL 4 (Hedges g, 0.031; 95% CI, 0.191 to 0.253; P .79) in 3 studies, and IL 8 (Hedges g, 0.072; 95% CI, 0.136 to 0.279; P .50) in 3 studies.  The findings of the meta analysis demonstrated higher peripheral concentrations of IL 6, tumor necrosis factor, IL 1b, IL 2, IL 10, C reactive protein, and RANTES in patients with PD, strengthening the clinical evidence that PD is accompanied by an inflammatory response.
Non invasive Analyte Access and Sensing through Eccrine Sweat: Challenges and Outlook circa 2016

Despite the many ergonomic advantages of eccrine perspiration (sweat) compared to other possible biofluids (particularly in "wearable" devices) sweat remains an underrepresented source of biomarker analytes compared to the established biofluids blood, urine, and saliva. Upon closer comparison to other non invasive biofluids, the advantages may even extend beyond ergonomics: sweat might provide superior analyte information. A number of challenges, however, have historically kept sweat from its place in the pantheon of clinical samples. These challenges include very low sample volumes (nL to uL) unknown concentration due to evaporation, filtration and dilution of large analytes, mixing of old and new sweat, and the potential for contamination from the skin surface. More recently, rapid progress in "wearable" sweat sampling and sensing devices has resolved several of the historical challenges. However, this recent progress has also been limited to high concentration analytes (uM to mM) sampled at high sweat rates >1 nL/min/gland, e.g. athletics) Progress will be much more challenging as sweat biosensing moves towards use with sedentary users (low sweat rates or not sweating at all) and/or towards low concentration analytes (pM to nM) Addressing these unresolved challenges will require significant advances in sweat stimulation, sample collection efficiency, compact sensors, and likely more. Fortunately, none of the remaining challenges appear to be fundamentally blocking, and scientific and engineering innovations have the opportunity to enable broader application of sweat biosensing technology.