nils-herrmann/clean_scirepeval huggingface dataset:
Exome and genome sequencing for inborn errors of immunity.
Venue: The Journal of allergy and clinical immunology

The advent of next generation sequencing (NGS) in 2010 has transformed medicine, particularly the growing field of inborn errors of immunity. NGS has facilitated the discovery of novel disease causing genes and the genetic diagnosis of patients with monogenic inborn errors of immunity. Whole exome sequencing (WES) is presently the most cost effective approach for research and diagnostics, although whole genome sequencing offers several advantages. The scientific or diagnostic challenge consists in selecting 1 or 2 candidate variants among thousands of NGS calls. Variant and gene level computational methods, as well as immunologic hypotheses, can help narrow down this genome wide search. The key to success is a well informed genetic hypothesis on 3 key aspects: mode of inheritance, clinical penetrance, and genetic heterogeneity of the condition. This determines the search strategy and selection criteria for candidate alleles. Subsequent functional validation of the disease causing effect of the candidate variant is critical. Even the most up to date dry lab cannot clinch this validation without a seasoned wet lab. The multifariousness of variations entails an experimental rigor even greater than traditional Sanger sequencing based approaches in order not to assign a condition to an irrelevant variant. Finding the needle in the haystack takes patience, prudence, and discernment.
Law of large numbers for the many server earliest deadline first queue

A many server queue operating under the earliest deadline first discipline, where the distributions of service time and deadline are generic, is studied at the law of large numbers scale. Fluid model equations, formulated in terms of the many server transport equation and the recently introduced measure valued Skorohod map, are proposed as a means of characterizing the limit. The main results are the uniqueness of solutions to these equations, and the law of large numbers scale convergence to the solutions.
An Efficient Scheduling Scheme for OFDMA Resource Blocks with Joint User Scheduling based on Earliest Deadline First with Carrier Aggregation (CA) in LTE A System
Venue: Wirel. Pers. Commun.

This paper focuses on the resource planning within the downlink of Long Term Evolution Advanced (LTE A) in addition to Carrier Aggregation (CA) technology. Every time CA is being put to use, it is very vital to complement the LTE A system with a robust and suitable resource scheduling plan. The two basic resource scheduling schemes are Separate Random User Scheduling and Joint User Scheduling (JUS) The former scheme is simpler, but less efficient, while the latter performs optimally at the expense of higher computation complexity. As a matter of fact, LTE Advanced networks are designed to render minimal latency and additional broadcast rates, coupled with increased spectral operational performance beyond the benchmark of 3G networks. Nevertheless, concerning the insufficient radio resources, the efficient application and management of these scarce resources are most desirable. Hence, the best approach for profitable resource allocation must be of central focus to meet the Quality of Service (QoS) standard. For the purpose of enhancing the system equity and refraining from high complexity of the system, it is recommended that the JUS is based on Earliest Deadline First (EDF) to offer QoS guarantees and equitable distribution of radio resources. From the simulation results, the following improvements were made: The proposed JUS based on EDF, improved the throughput of the users by adjusting the deadline for the allocated resource blocks of the users. The JUS EDF has improved the users throughput by 10 as compared to simple JUS. It also enhanced the system fairness by adjusting the priority of each user according to Earliest Deadline compared to JUS, by 8.88 Also JUS EDF reduced packet delays by 1 s, as compared to the conventional JUS. This paper has introduced a sub optimized packet scheduling algorithm to fully utilize the new feature in LTE A downlink system.
Design of an efficient ready queue for earliest deadline first (EDF) scheduler
Venue: 2016 Design, Automation Test in Europe Conference Exhibition (DATE)

Although dynamic priority based EDF algorithm is known to be theoretically optimal for scheduling sporadic real time tasks on uniprocessor, fixed priority (FP) scheduling is mostly used in practice. One of the main reasons for FP scheduling being popular in the industry is its efficient implementation: operations on the ready queue can be done in constant time. On the other hand, ready queue of EDF scheduler is generally implemented as a priority queue, for example, using a binary min heap data structure in which (insertion/deletion) operation cannot be done in constant time. This paper proposes a new design of ready queue for EDF scheduler: a simple data structure for the ready queue and efficient operations to insert and remove task control blocks (TCBs) to and from the ready queue are proposed. Insertion of a TCB of a newly released job (that cannot preempt the currently executing job) is done in non constant time. However, insertion of a TCB of a preempted job or the removal of the TCB of job having the highest EDF priority from the ready queue can be done in constant time. Simulation using randomly generated task sets shows that the overhead of managing jobs in our proposed ready queue for EDF scheduler is significantly lower than that of other approaches. We believe that theoretically optimal EDF algorithm implemented based on our proposed ready queue data structure will make EDF popular in industry.
A 4fJ/bit delay hardened physically unclonable function circuit with selective bit destabilization in 14nm tri gate CMOS
Venue: 2016 IEEE Symposium on VLSI Circuits (VLSI Circuits)

A 1024 bit delay hardened physically unclonable function (PUF) array is fabricated in 14nm tri gate CMOS, targeted for on die secure generation of a full entropy 128bit key. Differential clock delay injection, selective destabilization of unstable bits and temporal majority voting (TMV) based winnowing enable 1.7x higher post burn in BER improvement, 50% reduction in dark bit induced bit errors and worst case BER of 1.46% Spectral analysis of unstable PUF bits show significant 1/f noise impacts below 500MHz. In situ field aging with write feedback improves bit stability by up to 48%
Phosphoproteomics reveals that Parkinson's disease kinase LRRK2 regulates a subset of Rab GTPases
Venue: eLife

Mutations in Park8, encoding for the multidomain Leucine rich repeat kinase 2 (LRRK2) protein, comprise the predominant genetic cause of Parkinson's disease (PD) G2019S, the most common amino acid substitution activates the kinase two to threefold. This has motivated the development of LRRK2 kinase inhibitors; however, poor consensus on physiological LRRK2 substrates has hampered clinical development of such therapeutics. We employ a combination of phosphoproteomics, genetics, and pharmacology to unambiguously identify a subset of Rab GTPases as key LRRK2 substrates. LRRK2 directly phosphorylates these both in vivo and in vitro on an evolutionary conserved residue in the switch II domain. Pathogenic LRRK2 variants mapping to different functional domains increase phosphorylation of Rabs and this strongly decreases their affinity to regulatory proteins including Rab GDP dissociation inhibitors (GDIs) Our findings uncover a key class of bona fide LRRK2 substrates and a novel regulatory mechanism of Rabs that connects them to PD. DOI: http:/dx.doi.org/10.7554/eLife.12813.001
The epidemiology of Parkinson's disease: risk factors and prevention
Venue: The Lancet Neurology

Since 2006, several longitudinal studies have assessed environmental or behavioural factors that seem to modify the risk of developing Parkinson's disease. Increased risk of Parkinson's disease has been associated with exposure to pesticides, consumption of dairy products, history of melanoma, and traumatic brain injury, whereas a reduced risk has been reported in association with smoking, caffeine consumption, higher serum urate concentrations, physical activity, and use of ibuprofen and other common medications. Randomised trials are investigating the possibility that some of the negative risk factors might be neuroprotective and thus beneficial in individuals with early Parkinson's disease, particularly with respect to smoking (nicotine) caffeine, and urate. In the future, it might be possible to identify Parkinson's disease in its prodromal phase and to promote neuroprotective interventions before the onset of motor symptoms. At this time, however, the only intervention that seems justifiable for the primary prevention of Parkinson's disease is the promotion of physical activity, which is likely to be beneficial for the prevention of several chronic diseases.
Short chain fatty acids and gut microbiota differ between patients with Parkinson's disease and age matched controls.
Venue: Parkinsonism related disorders

Patients with Parkinson's disease (PD) frequently have gastrointestinal symptoms (e.g. constipation) and exhibit the PD typical pathohistology in the enteric nervous system (ENS) Both, clinical symptoms and pathohistological changes in the ENS occur at early stages and can precede the motor manifestations of PD. Two recent studies reported an association between changes in gut microbiota composition and PD. We hypothesized that alterations in gut microbiota might be accompanied by altered concentrations of short chain fatty acids (SCFA) one main metabolic product of gut bacteria.  We quantitatively analyzed SCFA concentrations (using gas chromatography) and microbiota composition (using quantitative PCR) in fecal samples of 34 PD patients and 34 age matched controls.  Fecal SCFA concentrations were significantly reduced in PD patients compared to controls. The bacterial phylum Bacteroidetes and the bacterial family Prevotellaceae were reduced, Enterobacteriaceae were more abundant in fecal samples from PD patients compared to matched controls.  Our study confirms the recently reported association between PD and the abundance of certain gut microbiota and shows a reduction in fecal SCFA concentrations (one main metabolic product of certain gut bacteria) The reduction in SCFA might, theoretically, induce alterations in the ENS and contribute to gastrointestinal dysmotility in PD. Prospective longitudinal studies in subjects at risk for PD are required to further elucidate the causal role of gut microbiota and microbial products in the development of PD and PD associated dysmotility.
The glucagon like peptide 1 (GLP) receptor as a therapeutic target in Parkinson's disease: mechanisms of action.
Venue: Drug discovery today

Growing evidence suggests that agonists of the glucagon like peptide 1 (GLP 1) receptor provide neuroprotection across a range of experimental models of Parkinson's disease (PD) and, recently, a small proof of concept, open label human trial of exenatide in the treatment moderate severity PD appeared to show persistent improvements in motor and cognitive function. The underlying mechanisms of action remain unclear, but as evidence for the potential use of GLP 1 agonists in treating several neurodegenerative disease mounts, and with several clinical trials of GLP 1 analogues in PD and Alzheimer's disease (AD) currently underway, here we review the molecular mechanisms underlying the neuroprotective effects of GLP 1 analogues in the laboratory and their potential therapeutic utility with particular relevance to PD and PD dementia (PDD)
Google Analytics Breakthrough: From Zero to Business Impact

Google Analytics Breakthrough is a much needed comprehensive resource for the world's most widely adopted analytics tool. Designed to provide a complete, best practices foundation in measurement strategy, implementation, reporting, and optimization, this book systematically demystifies the broad range of Google Analytics features and configurations. Throughout the end to end learning experience, you'll sharpen your core competencies, discover hidden functionality, learn to avoid common pitfalls, and develop nextgeneration tracking and analysis strategies so you can understand what is helping or hindering your digital performance and begin driving more success.
Wacana Puja Bhakti Dalam Kakawin Raja Patni Mokta

This study analyzes the tribute discourse in Kakawin Raja Patni Mokta. The composition of this kakawin is dominated by the theme of tribute for first lady, Tien Soeharto. The focus of this research are to reveal the form of puja bhakti (tribute) its function, and its meaning in Kakawin Raja Patni Mokta. Semiotic theory from Pierce is used to intreprete the text, while sociological theory of literature by Wellek and Werren is used to analyze the function of tribute discourse in Kakawin Raja Patni Mokta. Puja Bhakti in Kakawin Raja Patni Mokta can be considered as a special offering to the nation
Study on Applying the Neural Network in Computer Network Security Assessment
Venue: 2016 Eighth International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

In this paper, we aim to solve the problem of neural network in computer network security assessment, which is very important for computer network's popularization. Our proposed computer network security assessment system contains client and server. The client module includes: 1) scanning configuration model, 2) assessment model, 3) scanning result database model and 4) output model. Furthermore, server is made up of 1) scanning engine, 2) vulnerability database, 3) rules database. To promote the performance of artificial neural network, we choose the back propagation neural network, and particle swarm optimization is utilized to optimize parameters. Finally, experimental results demonstrate the effectiveness of our proposed approach.
Computer Network Security and Defense Technology Research
Venue: 2016 Eighth International Conference on Measuring Technology and Mechatronics Automation (ICMTMA)

Computer network in work and life bring convenience for people at the same time, also inevitable has brought some safe hidden trouble. To bring the positive role of efficient use of computer network, you need to effectively safeguard the security of computer network information. This article mainly analyzes the present situation of computer network security problems, analyzes the main source of computer security threats, and puts forward some effective network security defense technology, to maximize the guarantee the safety of computer network information to provide reliable guarantee.
A threat risk estimation model for computer network security
Venue: 2016 6th International Conference on Computer and Knowledge Engineering (ICCKE)

Risk analysis of security threats in computer networks is one of the most challenging fields in network management. Security risk analysis is usually done by security experts. Although they utilize analysis tools such as scanners and analyzers, the need for expert is still inevitable. To reduce the need of security expertise for network administrator, yet performing security risk management, this paper proposes UML models to represent expert's security information. We propose a UML class diagram which is built up of necessary classes for security analysis of networks. These classes are the building blocks needed for estimation of probability and effects of security threats. This model is created once and represents the security information needed for analysis. To analyze any network, the needed objects should be instantiated from the provided classes. These objects form the security model of the network with all the threats and their risks specified in. To instantiate the objects of network security model, its information is needed. This information is usually available in documents of a network or is obtainable via automated scanners. We show the applicability of the proposed model on a test network. As the result, the security model of the network which contains its security threats and also their risks are obtained.
Pine wilt disease alters soil properties and root associated fungal communities in Pinus tabulaeformis forest
Venue: Plant and Soil

AimsThe objective was to elucidate how pine wilt disease impacts soil properties and root associated fungi in Pinus tabulaeformis forest.MethodsSoil responses to pine wilt disease were studied in three kinds of damaged (undisturbed, middle disturbed and high disturbed) stands. The responses of root associated fungal community structure and diversity were examined through Illumina MiSeq sequencing of tagged amplicons of the 18S rDNA region. Soil nutrient properties were compared among stands using standard techniques.ResultsStands disturbed by pine wilt disease had lower soil hyphal density, pH, P and K content, higher organic matter and higher total N (P 0.05) compared with undisturbed stands. With the increasing of disease damage, the root ergosterol content, the colonization rates of ectomycorrhizal fungi and total hyphae were significantly decreased (P 0.05) Dark septate endopasitic fungi decreased firstly and then increased again with the increased severity of disease. The composition of root associated fungi differed among three kinds of disturbed stands. Basidiomycota and Ascomycota were the dominant root associated fungi of P. tabulaeformis. Tuber, as the most abundant fungal taxa, predominated in the undisturbed stand, while Russula in high disturbed stand. The community richness and diversity of root associated fungi were significantly lower (P 0.01) in high disturbed stand than that of undisturbed stand.ConclusionsPine wilt disease alters soil biotic and nutrient properties. Our study revealed clear differences in the biomass, abundance, diversity and community structure of root associated fungi among three pure P. tabulaeformis stands. Analysis of dominated RAF abundance provides one of methods to predict the damage degree of pine wilt disease to some extent.
A Survey on Various Approaches for Taxonomy Construction

To analysis different approaches for taxonomy construction to improve the knowledge classification, information retrieval and other data mining process.  Taxonomies learning keep getting more important process for knowledge sharing about a domain. It is also used for application development such as knowledge searching, information retrieval. The taxonomy can be build manually but it is a complex process when the data are so large and it also produce some errors while taxonomy construction. There is various automatic taxonomy construction techniques are used to learn taxonomy based on keyword phrases, text corpus and from domain specific concepts etc. So it is required to build taxonomy with less human effort and with less error rate. This paper provides detailed information about those techniques.  The methods such as lexico syntatic pattern, semi supervised methods, graph based methods, ontoplus, TaxoLearn, Bayesian approach, two step method, ontolearn and Automatic Taxonomy Construction from Text are analyzed in this paper.  The findings of this work prove that the TaxoFinder approach provides better result than other approaches.
A phase IIb randomized, double blind, placebo controlled trial of ubrogepant for the acute treatment of migraine
Venue: Cephalalgia an international journal of headache

The aim of this trial was to evaluate the efficacy and tolerability of ubrogepant (MK 1602) a calcitonin gene related peptide receptor antagonist (CGRP RA) for the acute treatment of migraine.  This double blind, placebo controlled study randomized 834 participants to treat one migraine attack with ubrogepant 1 mg, 10 mg, 25 mg, 50 mg, 100 mg, or placebo in a 1:1 ratio. The co primary endpoints were pain freedom and headache response at two hours. The first primary hypothesis tested the dose response trend for two hour pain freedom using a logistic regression model. Subsequent hypotheses tested the effects of each dose on the co primary endpoints, using a closed sequential testing procedure to control for multiplicity.  A total of 527 participants received ubrogepant and 113 received placebo. A positive response trend in the proportion of participants achieving two hour pain freedom was demonstrated (p 0.001) Ubrogepant 100 mg was significantly superior to placebo for two hour pain freedom (25.5% vs 8.9% but not for two hour headache response. Per the prespecified multiplicity strategy, this nonsignificant result precluded further formal hypothesis testing, although the 50 mg and 25 mg doses demonstrated nominal significance over placebo for two hour pain freedom (unadjusted p 0.05) Overall, adverse events were similar between ubrogepant and placebo.  This trial supports ubrogepant's efficacy and provides further evidence that CGRP RAs are viable options for the acute treatment of migraine.
Combined study of the effect of deposition temperature and post deposition annealing on the photoluminescence of silicon quantum dots embedded in chlorinated silicon nitride thin films

Chlorinated silicon nitride (SiNx:Cl) thin films with embedded silicon quantum dots (Si QDs) were grown by remote plasma enhanced chemical vapor deposition using SiH2Cl2, H2, NH3 and Ar at different deposition temperatures (DT) in the range of 50 to 350 degC and using steps of 50 degC. After that, each sample was subjected to annealing treatments at temperatures (AT) of 400, 700 and 1000 degC. The evolution of the optical properties, composition and structure as a function of DT and AT were investigated by Null Ellipsometry, photoluminescence (PL) measurements, UV Vis spectroscopy, X ray Photoelectron Spectroscopy (XPS) Fourier Transform Infrared Spectroscopy (FTIR) scanning electron microscopy with energy dispersive X ray spectroscopy (SEM) with (EDS) and High Resolution Transmission Electron Microscopy (HRTEM) A red shift in the PL peak and an increment in the PL integrated intensity of the films was found on increasing DT from 150 to 350 degC; such changes can be explained by modifications of the matrix chemical composition and by the quantum confinement effect due to an increase in the size and density of Si QDs respectively. A chemical analysis revealed that films deposited below 150 degC suffer a post deposition oxidation process leading to the formation of silicon oxide; this process is accelerated by the temperature of the annealing treatment. Meanwhile films deposited between 150 and 350 degC are mainly composed of silicon nitride that diminishes the mentioned oxidation due to the thermal treatments and promotes the splitting of Si QDs into two populations with different average diameter. The annealed films deposited below 150 degC show a clearly decrement in the PL intensity, meanwhile the maximum emission PL peak from annealed films grown from 150 to 350 degC shifts to high emission energies. This post thermal annealing blue shift can be mainly related to the nucleation of new small Si QDs. We concluded that temperature is one of the most important mainstays to achieve good luminescence from Si QDs.