LLukas22/scidocs huggingface dataset:
Mapping Quantitative Trait Loci Controlling High Iron and Zinc Content in Self and Open Pollinated Grains of Pearl Millet [Pennisetum glaucum (L.) R. Br.]

Pearl millet is a multipurpose grain/fodder crop of the semi-arid tropics, feeding many of the world's poorest and most undernourished people. Genetic variation among adapted pearl millet inbreds and hybrids suggests it will be possible to improve grain micronutrient concentrations by selective breeding. Using 305 loci, a linkage map was constructed to map QTLs for grain iron [Fe] and zinc [Zn] using replicated samples of 106 pearl millet RILs (F6) derived from ICMB 841-P3 × 863B-P2. The grains of the RIL population were evaluated for Fe and Zn content using atomic absorption spectrophotometer. Grain mineral concentrations ranged from 28.4 to 124.0 ppm for Fe and 28.7 to 119.8 ppm for Zn. Similarly, grain Fe and Zn in open pollinated seeds ranged between 22.4-77.4 and 21.9-73.7 ppm, respectively. Mapping with 305 (96 SSRs; 208 DArT) markers detected seven linkage groups covering 1749 cM (Haldane) with an average intermarker distance of 5.73 cM. On the basis of two environment phenotypic data, two co-localized QTLs for Fe and Zn content on linkage group (LG) 3 were identified by composite interval mapping (CIM). Fe QTL explained 19% phenotypic variation, whereas the Zn QTL explained 36% phenotypic variation. Likewise for open pollinated seeds, the QTL analysis led to the identification of two QTLs for grain Fe content on LG3 and 5, and two QTLs for grain Zn content on LG3 and 7. The total phenotypic variance for Fe and Zn QTLs in open pollinated seeds was 16 and 42%, respectively. Analysis of QTL × QTL and QTL × QTL × environment interactions indicated no major epistasis.
Knowledge, Attitudes and Motivations Among Blood Donors in São Paulo, Brazil

Recruiting safe, volunteer blood donors requires understanding motivations for donating and knowledge and attitudes about HIV. We surveyed 1,600 persons presenting for blood donation at a large blood bank in São Paulo, Brazil using a self-administered, structured questionnaire, and classified motivations into three domains as well as categorizing persons by HIV test-seeking behavior. Motivations, in descending order, and their significant associations were: “altruism”: female gender, volunteer donor and repeat donor status; “direct appeal”: female gender, repeat donor status and age 21–50 years; “self-interest”: male gender, age under 20 years, first-time donor status and lower education. HIV test-seekers were more likely to give incorrect answers regarding HIV risk behavior and blood donation and the ability of antibody testing to detect recent HIV infections. Altruism is the main motivator for blood donation in Brazil; other motivators were associated with specific demographic subgroups. HIV test-seeking might be reduced by educational interventions.
Risks and Mitigation Measures in Build-Operate-Transfer Projects

Infrastructure investments are important in developing countries, it will not only help to foster the economic growth of a nation, but it will also act as a platform in which new forms of partnership and collaboration can be developed mainly in East Asian countries. Since the last two decades, many infrastructure projects had been completed through build-operate-transfer (BOT) type of procurement. The developments of BOT have attracted participation of local and foreign private sector investor to secure funding and to deliver projects on time, within the budget and to the required specifications. Private sectors are preferred by the government in East Asia to participate in BOT projects due to lack of public funding. The finding has resulted that the private sector or promoter of the BOT projects is exposed to multiple risks which have been discussed in this paper. Effective risk management methods and good managerial skills are required in ensuring the success of the project. The review indicated that mitigation measures should be employed by the promoter throughout the concession period and support from the host government is also required in ensuring the success of the BOT project. Keywords—BOT project, risks management, concessionaire, consortium.
Crowdsourcing, collaboration and creativity

While many organizations turn to human computation labor markets for jobs with black-or-white solutions, there is vast potential in asking these workers for original thought and innovation.
An ant colony optimization algorithm for the Multiple Traveling Salesmen Problem

The multiple traveling salesmen problem (MTSP) is a generalization of the famous traveling salesman problem (TSP), where more than one salesman is used in the solution. Though the MTSP is a typical computationally complex combinatorial optimization problem, it can be extended to a wide variety of routing and scheduling problems. The paper proposed an ant colony optimization (ACO) algorithm for the MTSP with two objectives: the objective of minimizing the maximum tour length of all the salesmen and the objective of minimizing the maximum tour length of each salesman. In the algorithm, the pheromone trail updating and limits followed the MAX-MIN Ant System (MMAS) scheme, and a local search procedure was used to improve the performance of the algorithm. We compared the results of our algorithm with genetic algorithm (GA) on some benchmark instances in literatures. Computational results show that our algorithm is competitive on both the objectives.
A randomized trial of daclatasvir with peginterferon alfa-2b and ribavirin for HCV genotype 1 infection.

BACKGROUND
Daclatasvir-containing regimens have the potential to address limitations of current regimens combining peginterferon alfa and ribavirin with first-generation protease inhibitors for treatment of chronic HCV genotype 1 infection.


METHODS
In this randomized, double-blind study, 27 Japanese treatment-naive patients received once-daily daclatasvir 10 mg or 60 mg or placebo, each combined with peginterferon alfa-2b/ribavirin; 18 prior null (n=9) or partial (n=9) responders received the same daclatasvir-containing regimens without a placebo arm. Daclatasvir recipients with protocol-defined response (HCV RNA<15 IU/ml at week 4, undetectable at week 12) were treated for 24 weeks; those without protocol-defined response and placebo recipients continued treatment to week 48.


RESULTS
Sustained virological response 24 weeks post-treatment (SVR24) was achieved by 66.7%, 90.0% and 62.5% of treatment-naive patients in the daclatasvir 10 mg, 60 mg and placebo groups, respectively. Prior non-responders had more frequent virological failure; 22.2% and 33.3% of daclatasvir 10 mg and 60 mg recipients, respectively, achieved SVR24. Adverse events were similar across groups and were typical of peginterferon alfa-2b/ribavirin. Pyrexia, headache, alopecia, decreased appetite and malaise were the most common adverse events; two daclatasvir recipients discontinued due to adverse events.


CONCLUSIONS
Daclatasvir 60 mg combined with peginterferon alfa-2b and ribavirin achieved a high rate of SVR24 in treatment-naive patients with HCV genotype 1 infection, with tolerability similar to that of peginterferon alfa-2b/ribavirin alone. However, regimens with greater antiviral potency are needed for prior non-responders.
Piggybacking Codes for Network Coding: The High/Low SNR Regime

We propose a Piggybacking scheme for Network Coding where strong source inputs piggyback the weaker ones, a scheme necessary and sufficient to achieve the cut-set upper bound at High/Low-SNR regime, a new asymptotically optimal operational regime for the multihop Amplify and Forward (AF) networks.
Vision-based Deep Reinforcement Learning

Recently, Google Deepmind showcased how Deep learning can be used in conjunction with existing Reinforcement Learning (RL) techniques to play Atari games[11], beat a world-class player [14] in the game of Go and solve complicated riddles [3]. Deep learning has been shown to be successful in extracting useful, nonlinear features from high-dimensional media such as images, text, video and audio [12]. For control tasks like playing games, researchers have traditionally used handcrafted-features which require a lot of human effort. Convolutional neural networks (CNN) can be used to extract useful visual features from the highdimensional input, such as a video game screen, to learn near-optimal value function in such control tasks. We chose the Arcade Learning environment as our testbed to examine how deep learning can be applied to a reinforcement learning setting and analyze performance of various modern algorithms. The learning is performed end-to-end with no game knowledge included in the architecture or during training. We also show how the architecture of the deep network used, can be modified to achieve superior performances and compare performances on the task of playing a complicated game Seaquest.
Chest diseases diagnosis using artificial neural networks

Chronic obstructive pulmonary, pneumonia, asthma, tuberculosis, lung cancer diseases are the most important chest diseases. These chest diseases are important health problems in the world. In this study, a comparative chest diseases diagnosis was realized by using multilayer, probabilistic, learning vector quantization, and generalized regression neural networks. The chest diseases dataset were prepared by using patient’s epicrisis reports from a chest diseases hospital’s database. 2010 Elsevier Ltd. All rights reserved.
Polymorphisms in the Hsp 70 gene locus are genetically associated with systemic lupus erythematosus

Ann Rheum Dis 2010;69:1983–1989. doi:10.1136/ard.2009.12263
Bit-Level Optimization of Adder-Trees for Multiple Constant Multiplications for Efficient FIR Filter Implementation

Multiple constant multiplication (MCM) scheme is widely used for implementing transposed direct-form FIR filters. While the research focus of MCM has been on more effective common subexpression elimination, the optimization of adder-trees, which sum up the computed sub-expressions for each coefficient, is largely omitted. In this paper, we have identified the resource minimization problem in the scheduling of adder-tree operations for the MCM block, and presented a mixed integer programming (MIP) based algorithm for more efficient MCM-based implementation of FIR filters. Experimental result shows that up to 15% reduction of area and 11.6% reduction of power (with an average of 8.46% and 5.96% respectively) can be achieved on the top of already optimized adder/subtractor network of the MCM block.
Acute systemic inflammation increases arterial stiffness and decreases wave reflections in healthy individuals.

BACKGROUND
Aortic stiffness is a marker of cardiovascular disease and an independent predictor of cardiovascular risk. Although an association between inflammatory markers and increased arterial stiffness has been suggested, the causative relationship between inflammation and arterial stiffness has not been investigated.


METHODS AND RESULTS
One hundred healthy individuals were studied according to a randomized, double-blind, sham procedure-controlled design. Each substudy consisted of 2 treatment arms, 1 with Salmonella typhi vaccination and 1 with sham vaccination. Vaccination produced a significant (P<0.01) increase in pulse wave velocity (at 8 hours by 0.43 m/s), denoting an increase in aortic stiffness. Wave reflections were reduced significantly (P<0.01) by vaccination (decrease in augmentation index of 5.0% at 8 hours and 2.5% at 32 hours) as a result of peripheral vasodilatation. These effects were associated with significant increases in inflammatory markers such as high-sensitivity C-reactive protein (P<0.001), high-sensitivity interleukin-6 (P<0.001), and matrix metalloproteinase-9 (P<0.01). With aspirin pretreatment (1200 mg PO), neither pulse wave velocity nor augmentation index changed significantly after vaccination (increase of 0.11 m/s and 0.4%, respectively; P=NS for both).


CONCLUSIONS
This is the first study to show through a cause-and-effect relationship that acute systemic inflammation leads to deterioration of large-artery stiffness and to a decrease in wave reflections. These findings have important implications, given the importance of aortic stiffness for cardiovascular function and risk and the potential of therapeutic interventions with antiinflammatory properties.
Possible effect of the local terrain on the North Carolina tower gravity experiment.

A Comment on the Letter by D. H. Eckhardt, {ital et} {ital al}., Phys. Rev. Lett. 60, 2567 (1988).
Artificial intelligence

S INCE ITS INAUGURATION in 1966, the ACM A.M. Tur-ing Award has recognized major contributions of lasting importance to computing. Through the years, it has become the most prestigious award in computing. To help celebrate 50 years of the ACM Turing Award and the visionaries who have received it, ACM has launched a campaign called " Panels in Print, " which takes the form of a collection of responses from Turing laureates, ACM award recipients and other ACM experts on a given topic or trend. ACM's celebration of 50 years of the ACM Turing Award will culminate with a conference June 23–24, 2017 at the Westin St. Francis in San Francis-co to highlight the significant impact of the contributions of ACM Turing laureates on computing and society, to look ahead to the future of technology and innovation, and to help inspire the next generation of computer scientists to invent and dream. Grace Murray Hopper recipient PEDRO FELZENSZWALB to respond to several questions about Artificial Intelligence. What have been the biggest breakthroughs in AI in recent years and what impact is it having in the real-world? RAJ REDDY: Ten years ago, I would have said it wouldn't be possible, in my lifetime, to recognize unre-hearsed spontaneous speech from an open population but that's exactly what Siri, Cortana and Alexa do. The same is happening with vision and robotics. We are by no means at the end of the activity in these areas, but we have enough working examples that society can benefit from these breakthroughs. JEFF DEAN: The biggest breakthrough in the last five or so years has been the use of deep learning, a particular kind of machine learning that uses neural networks. Stacking the network into many layers that learn increasingly abstract patterns as you go up the layers seems to be a fundamentally powerful idea, and it's been very successful in a surprisingly wide variety of applications—from speech recognition, to image recognition, to language understanding. What's interesting is we don't seem to be near the limit of what deep learning can do; we'll likely see many more powerful uses of it in the coming years. PEDRO FELZENSZWALB: Among the biggest technical advances I would include the development of scalable machine learning algorithms and the computational infrastructure to process and interact with huge data-sets. The latest example of these advances is deep learning. In computer vision deep learning has …
Tapered Transmission Lines With Dissipative Junctions

NIST is optimizing the design of a 10 V programmable Josephson voltage standard so that it uses less microwave power by employing fewer parallel-biased arrays with higher voltage per array. Increasing the voltage per array by adding more junctions is challenging because the dissipation of the over-damped Josephson junctions limits the total number that may be located in each array. If there is too much dissipation in the array, the junctions at the end receive too little microwave power compared with the junctions at the beginning of the array. To compensate for the junction attenuation, tapered impedance transmission lines were used to maintain a nearly constant microwave current along the lossy transmission line. Simulation and testing have improved the microwave uniformity of our designs for tapered impedances from 85 ohms to 5 ohms. Low-leakage bias tees for various characteristic impedances were designed so that sub-arrays could be measured within long arrays. These tapered arrays have improved the bias current margins, junction number, and bandwidth of NIST junction arrays. By measuring the microwave power from the output of these long arrays, harmonic generation and the nonlinear properties of dissipative junction arrays are studied.
Is oxycodone efficacy reflected in serum concentrations? A multicenter, cross-sectional study in 456 adult cancer patients.

CONTEXT
The relationship between oxycodone and metabolite serum concentrations and clinical effects has not previously been investigated in cancer pain patients.


OBJECTIVES
The aim of this study was to assess whether there is a relationship between oxycodone concentrations and pain intensity, cognitive functioning, nausea, or tiredness in cancer patients. Also, oxymorphone and noroxymorphone contributions to analgesia and the adverse effects of oxycodone were assessed.


METHODS
Four hundred fifty-six cancer patients receiving oxycodone for cancer pain were included. Pain was assessed using the Brief Pain Inventory. The European Organisation for Research and Treatment of Cancer Quality-of-Life Questionnaire-C30 was used to assess the symptoms of tiredness, nausea, constipation, and depression. Cognitive function was assessed using the Mini-Mental State Examination. Associations were examined by multiple linear or ordinal logistic regressions. Whether patients classified as being a "treatment success" or a "treatment failure" had different serum concentrations of oxycodone or metabolites was assessed using Mann-Whitney U-tests.


RESULTS
Serum concentrations of oxycodone and metabolites were not associated with pain intensity, nausea, tiredness, or cognitive function, with the exception that increased pain intensity was associated with higher oxymorphone concentrations. Patients with poor pain control and side effects had higher serum concentrations of the oxycodone metabolites, noroxycodone and noroxymorphone, compared with those with good pain relief and without side effects.


CONCLUSION
This study of patients receiving oxycodone for cancer pain confirms previous observations that there is most likely no association between serum concentrations of opioid analgesics and clinical effects.
New insights into the basement of the Transylvanian Depression (Romania)

Abstract In the Transylvanian Depression (Romania) a number of deep wells were drilled to investigate and exploit methane gas fields. From these, only a few penetrated the Middle to Upper Jurassic volcanics in the basement. From three boreholes (Deleni, Cenade and Zoreni) rock samples were available for investigations. Deleni and Cenade show calc-alkaline basalts to andesites which are similar to the island arc volcanics of the Southern Apuseni Mountains. Zoreni basalts and basaltic andesites show a boninitic affinity, which was not found up to now in outcrops. The distribution of the volcanics in the basement of the Transylvanian Depression, which correlates with a geomagnetic anomaly, can be explained by the presence of a magnetite-rich ophiolite layer beneath the island arc volcanics. Comparable oceanic crust rocks are found further west, in the Southern Apuseni Mountains. They are considered to be remnants of a marginal or back-arc basin, in which a volcanic arc including boninites developed. Upon the westward-directed subduction of an open ocean, the island arc and part of the back-arc basin were overthrusted eastwards onto continental crust during the Late Jurassic or Early Cretaceous. A flip in the subduction direction caused late Early Cretaceous westward thrusting of the back-arc basin and island arc rocks onto the crystalline basement of the Tisia continent.
The New Era of Interferon-Free Treatment of Chronic Hepatitis C

BACKGROUND
Within the development and approval of several new direct-acting antivirals (DAA) against hepatitis C virus (HCV), a new era of hepatitis C therapy has begun. Even more treatment options are likely to become available during the next 1-2 years.


METHODS
A summary of the current phase II and III trials investigating DAA and a review of the recent HCV guidelines was conducted.


RESULTS
With the development of new potent DAA and the approval of different DAA combinations, cure rates of HCV infection of >90% are achievable for almost all HCV genotypes and stages of liver disease. Currently available DAA target different steps in the HCV replication cycle, in particular the NS3/4A protease, the NS5B polymerase, and the NS5A replication complex. Treatment duration varies between 8 and 24 weeks depending on the stage of fibrosis, prior treatment, HCV viral load, and HCV genotype. Ribavirin is required only for some treatment regimens and may be particularly beneficial in patients with cirrhosis. DAA resistance influences treatment outcome only marginally; thus, drug resistance testing is not routinely recommended before treatment. In the case of treatment failure, however, resistance testing should be performed before re-treatment with other DAA is initiated.


CONCLUSION
With the new, almost side effect-free DAA treatment options chronic HCV infection became a curable disease. The clinical benefit of DAA combination therapies in patients with advanced cirrhosis and the effects on incidence rates of hepatocellular carcinoma remain to be determined.
The effects of soccer training and timing of balance training on balance ability

The purpose of the present study was to investigate the effects of a soccer training session on the balance ability of the players and assess whether the effectiveness of a balance program is affected by its performance before or after the regular soccer training. Thirty-nine soccer players were randomly divided into three subject groups (n=13 each), one control group (C group), one training group that followed a balance program (12 weeks, 3 times per week, 20 min per session) before the regular soccer training (TxB group), and one training group that performed the same balance program after the soccer training (TxA group). Standard testing balance boards and the Biodex Stability System were used to assess balance ability in the C, TxB, and TxA groups at baseline (T0) and after completing the balance program (T12). The same tests and additional isokinetic knee joint moment measurements were carried out in the TxB and TxA groups pre- and post-soccer training. Two main results were obtained: (1) No differences (p>0.05) were found in balance ability and knee joint moment production between pre- and post-soccer training. (2) The balance program increased (p<0.01) the balance ability in the TxB and TxA groups, and the improvement in the TxA group was greater (p<0.05) than that in the TxB group post-soccer training. Result (1) is in contrast to the notion of a link between fatigue induced by a soccer training session or game and injury caused by impaired balance, and result (2) has implications for athletic training and rehabilitation.
Effects of Cutting Parameters on Surface Roughness during End Milling of Aluminium under Minimum Quantity Lubrication (MQL)

In this study an experimental investigation of effects of cutting parameters on surface roughness during end milling of aluminium 6061 under minimum quantity lubrication (MQL) condition was carried out. The experiments were carried out to investigate surface quality of the machined parameters and to developed mathematical models using least square techniques. Spindle speed (N), feed rate (f), axial depth of cut (a) and radial depth of cut (r) has been chosen as input variables in order to predict surface roughness. The experiment was designed by using central composite design (CCD) in which 30 samples were run in a CNC milling machine. Each of the experimental result was measured using Mitutoyo surface tester. After the predicted surface roughness values have been obtained the average percentage errors were calculated. The mathematical model developed by using least square method shows accuracy of 89.5% which is reasonably reliable for surface roughness prediction. With the obtained optimum input parameters for surface roughness, production operations will be enhanced.