Miracle-dz/UniFAR-FTUs huggingface dataset:
Stochastic string motion above and below the world sheet horizon

We study the stochastic motion of a relativistic trailing string in black hole AdS5. The classical string solution develops a world-sheet horizon and we determine the associated Hawking radiation spectrum. The emitted radiation causes fluctuations on the string both above and below the world-sheet horizon. In contrast to standard black hole physics, the fluctuations below the horizon are causally connected with the boundary of AdS. We derive a bulk stochastic equation of motion for the dual string and use the AdS/CFT correspondence to determine the evolution of a fast heavy quark in the strongly coupled = 4 plasma. We find that the kinetic mass of the quark decreases by ΔM = −(γλ)1/2T/2 while the correlation time of world sheet fluctuations increases by γ1/2.
Safety of Nuclear Power Plants with Respect to the Fault Displacement Hazard

The hazard of permanent ground displacements/deformations can challenge the safety of the nuclear power plants. Increasing knowledge of the hazard and development of methods for structure–fault–displacement interaction motivates the designing of nuclear power plants for permanent ground displacement instead of abandoning the sites that could be affected by this kind of hazard. For the design basis, permanent ground displacement should be defined at the hazard level that complies with the probabilistic criteria for accounting for the natural hazards in the design that also ensure compliance with probabilistic safety criteria. In this paper, a procedure is proposed for the definition of the design basis permanent ground displacement that is based on the deaggregation of seismic design basis hazard. The definition of the displacement for the margin evaluation is also proposed. The feasibility of safe design is also demonstrated for the proposed definition of design basis hazard via qualitative judgement on the sensitivity of the structures, systems and components ensuring the fundamental safety functions with respect to the permanent ground displacement that is supported by existing case studies.
BenchPress: Analyzing Android App Vulnerability Benchmark Suites

In recent years, various efforts have designed and developed benchmark suites to evaluate the efficacy of vulnerability detection tools in Android apps. The choice of benchmark suites used in tool evaluations is often based on availability and popularity of suites instead of on the characteristics and relevance of benchmark suites relative to real world native Android apps. One of the reasons for such choice is the lack of information about characteristics and relevance of benchmarks suites relative to real world apps. In this paper, we report the findings from our effort aimed at addressing this gap. We empirically evaluated three Android specific benchmark suites – DroidBench, Ghera, and IccBench. For each suite, we report how well do these benchmark suites represent real world apps in terms of API usage: 1) coverage – how often are the APIs used in a benchmark suite used in a sample of real world native Android apps? and 2) gap – which of the APIs used in a sample of real world native Android apps are not used in any benchmark suite? Based on pairwise comparison, we also report how these suites fare relative to each other in terms of API usage. The findings in this paper can help 1) Android security analysis tool developers choose benchmark suites that are best suited to evaluate their tools (informed by coverage and pairwise comparison) and 2) Android specific benchmark creators improve API usage based representativeness of suites (informed by gaps).
The mediating effect of entrepreneurial orientation on the relationship between decision-making and firm performance in Kenya

Manufacturing firms are the single greatest contributors to industrialization and economic development. In Kenya, manufacturing firms contribute 14% of gross domestic product, train and employ 30% of the workforce, and develop the country’s industrial infrastructure. However, the sector has experienced sustained poor total factor productivity and waning competitiveness in both domestic and global markets. Manufacturing operations seem to lack the input of entrepreneurial management. The purpose of this study was to establish how entrepreneurial orientation (EO) influences the relationship between decision-making and manufacturing firm performance in Kenya. Eighty-three owners/managers of food manufacturing SMEs were surveyed using a semi-structured self-administered questionnaire, and the collected data analyzed using Statistical Package for Social Sciences (SPSS) version 20 and Smart PLS 3 software’s. The findings show that EO fully mediates the relationship between decision-making and firm performance. The paper concludes that coupling decision-making with EO forms a critical strategy for enhancing firm performance. The study recommends that manufacturing firms should develop and utilize employees’ EO capabilities through such actions as strategic delegation.
Estimation of Stress Drop for Some Large Shallow Earthquakes Using Stochastic Point Source and Finite Fault Modeling

Using stochastic point source and nite fault modeling, the stochastic stress drop is estimated for 52 large shallow earthquakes listed in the `Paci c Earthquake Engineering Research Center (PEER) Next Generation Attenuation of Ground Motions (NGA)' database. The Pseudo Spectral Acceleration (PSA) of 541 accelerograms, recorded at National Earthquake Hazards Reduction Program (NEHRP) C-class sites from 52 earthquakes are simulated and compared with the PSA listed in the PEER NGA database. The magnitude of the analyzed earthquakes ranged from M4:4 to M7:6. The stress drop is calibrated by trial and error and based on the analysis of residuals where the residual is de ned as the log of the observed PSA minus the log of the predicted PSA by stochastic methods. The symmetric distribution of residuals around the zero line is considered as an indicator of good agreement between the simulated and observed PSAs. The calculated stress drops based on stochastic point source and nite fault modeling are di erent from the static stress drops that are currently listed in the PEER NGA database. It seems that there is no clear relation between stress drop and earthquake magnitude, but there is a good linear relation between estimated stress drops based on stochastic point source and nite fault modeling. The sensitivity of the estimated stress drop values on the Kappa factor and geometric speeding factor (b value) is also investigated.
Extended Probabilistic Latent Semantic Analysis for Automatic Image Annotation

Automatic image annotation is a promising solution to enable the semantic based image retrieval via keywords. However it is still in its infancy and is not sophisticated enough to extract perfect semantic concepts according to image low-level features, often producing noisy keywords irrelevant to image semantics, which may be an obstacle to getting high-quality image retrieval. So in this paper, we propose a novel extended probabilistic latent semantic analysis (PLSA) to improve the performance of automatic image annotation. On one hand, the traditional bag-of-visual-words model is improved by integrating the contextual semantic information among visual words based on the PLSA model. Meanwhile, the approximation strategy of pseudo-likelihood in Markov random ﬁeld (MRF) is introduced to combine the feature appearance similarity in feature domain and the contextual semantic information in spatial domain. On the other hand, since the traditional expectation-maximization (EM) algorithm used to train the PLSA model is sensitive to its initialization, so a rival penalized competitive learning (RPCL) based method is employed to overcome this deﬁciency and to provide a good initial estimate of this model. Conducted experiments on the standard Corel5k image dataset demonstrate that the proposed method is signiﬁcantly more eﬀective than several state-of-the-art approaches regarding their eﬀectiveness and eﬃciency in the task of automatic image annotation.
Title Charging-induced changes in reverse current-voltagecharacteristics of Al / Al-Rich Al 2 O 3 / pSi Diodes

An Al-rich Al2O3 thin film was deposited on a p-type silicon substrate by radio frequency sputtering to form Al/Al-rich Al2O3/p-Si diodes. The current–voltage (I–V ) characteristics of the diodes were determined by carrier injection from either the Si substrate or the Al gate and by carrier transport along the tunneling paths formed by Al nanocrystals distributed in the oxide layer. The reverse I–V characteristics were greatly affected by the charge trapping in the oxide layer, i.e., the electron trapping significantly reduced the reverse current while the hole trapping enhanced the current significantly. However, the charge trapping did not produce a large change in the forward I–V characteristic.
Server Host OS Server Host OS Docker Engine Server Host OS Docker Engine Server Host OS Hypervisor

Microservices architecture has started a new trend for application development for a number of reasons: (1) to reduce complexity by using tiny services; (2) to scale, remove and deploy parts of the system easily; (3) to improve flexibility to use different frameworks and tools; (4) to increase the overall scalability; and (5) to improve the resilience of the system. Containers have empowered the usage of microservices architectures by being lightweight, providing fast start-up times, and having a low overhead. Containers can be used to develop applications based on monolithic architectures where the whole system runs inside a single container or inside a microservices architecture where one or few processes run inside the containers. Two models can be used to implement a microservices architecture using containers: master-slave, or nested-container. The goal of this work is to compare the performance of CPU and network running benchmarks in the two aforementioned models of microservices architecture hence provide a benchmark analysis guidance for system designers.
Dirichlet process mixture models made scalable and effective by means of massive distribution

Clustering with accurate results have become a topic of high interest. Dirichlet Process Mixture (DPM) is a model used for clustering with the advantage of discovering the number of clusters automatically and offering nice properties like, e.g., its potential convergence to the actual clusters in the data. These advantages come at the price of prohibitive response times, which impairs its adoption and makes centralized DPM approaches inefficient. We propose DC-DPM, a parallel clustering solution that gracefully scales to millions of data points while remaining DPM compliant, which is the challenge of distributing this process. Our experiments, on both synthetic and real world data, illustrate the high performance of our approach on millions of data points. The centralized algorithm does not scale and has its limit on 100K data points, where it needs more than 7 hours. In this case, our approach needs less than 30 seconds.
Bayes Factors via Savage-Dickey Supermodels

We outline a new method to compute the Bayes Factor for model selection which bypasses the Bayesian Evidence. Our method combines multiple models into a single, nested, Supermodel using one or more hyperparameters. Since the models are now nested the Bayes Factors between the models can be efficiently computed using the Savage-Dickey Density Ratio (SDDR). In this way model selection becomes a problem of parameter estimation. We consider two ways of constructing the supermodel in detail: one based on combined models, and a second based on combined likelihoods. We report on these two approaches for a Gaussian linear model for which the Bayesian evidence can be calculated analytically and a toy nonlinear problem. Unlike the combined model approach, where a standard Monte Carlo Markov Chain (MCMC) struggles, the combined-likelihood approach fares much better in providing a reliable estimate of the log-Bayes Factor. This scheme potentially opens the way to computationally efficient ways to compute Bayes Factors in high dimensions that exploit the good scaling properties of MCMC, as compared to methods such as nested sampling that fail for high dimensions.
Knowledge Management Tools and Academic Library Services

Evolution of information and knowledge has impacted all organizations, including academic libraries. Knowledge management has drawn the attention of LIS professionals for the past decade. Initially the knowledge management was a feature of the corporate sector; later it started a role in academic libraries too. This paper discusses the various components of knowledge management process, identifies Intranet as one of the tools of KM, its contents, resources required and advantages as a tool for KM. The study explores the feasibility of services offered through Intranet services in University libraries in the state of Karnataka and Jammu& Kashmir.
Zebrafish in Education Zebrafish Embryology and Cartilage Staining Protocols for High School Students

The Life Sciences–Howard Hughes Medical Institute Outreach Program at Harvard University supports high school science education by offering an on-campus program for students and their teachers to participate in investigative, hands-on laboratory sessions. The outreach program has recently designed and launched a successful zebrafish embryology protocol that we present here. The main objectives of this protocol are to introduce students to zebrafish as a model research organism and to provide students with direct experience with current techniques used in embryological research. The content of the lab is designed to generate discussions on embryology, genetics, fertilization, natural selection, and animal adaptation. The protocol produces reliable results in a time-efficient manner using a minimum of reagents. The protocol presented here consists of three sections: observations of live zebrafish larvae at different developmental stages, cartilage staining of zebrafish larvae, and a mutant hunt involving identification of two zebrafish mutants (nacre and chokh). Here, we describe the protocol, show the results obtained for each section, and suggest possible alternatives for different lab settings.
Trial in progress: A phase Ib study of AMG 510, a specific and irreversible KRASG12C inhibitor, in combination with other anticancer therapies in patients with advanced solid tumors harboring KRAS p.G12C mutation (CodeBreak 101).

TPS3661 Background: Kirsten rat sarcoma viral oncogene homolog (KRAS) p.G12C mutation has been identified as a driver oncogenic mutation in several solid tumors (eg, non-small cell lung cancer [NSCLC], colorectal cancer [CRC]). Development of therapies targeting KRASG12C has been unsuccessful. AMG 510 is a specific and irreversible small molecule inhibitor of KRASG12C. A first-in-human clinical trial of AMG 510 monotherapy in patients with KRAS p.G12C mutant solid tumors is currently ongoing. AMG 510 in combination with additional anticancer therapies may lead to enhanced antitumor efficacy. This study is a master protocol designed to evaluate multiple investigational regimens of AMG 510 in patients with KRAS p.G12C mutant solid tumors. Here, we present two combination cohorts of AMG 510 with a mitogen-activated protein kinase kinase (MEK) inhibitor and an investigational anti-programmed cell death protein-1 (PD-1) therapy, respectively. Additional combination cohorts will be presented at the meeting. Methods: This is a phase 1b, open-label study evaluating AMG 510 in combination with a MEK inhibitor or an investigational anti-PD-1 therapy in pts with KRAS p.G12C mutant solid tumors. The dose exploration phase (part 1; n=20) will evaluate the safety and tolerability of AMG 510 in combination with the MEK inhibitor or anti-PD-1 therapy; this will be followed by a dose expansion phase (part 2; n=40) to verify the safety and tolerability profile of AMG 510 combination therapies and assess antitumor efficacy. Key eligibility criteria include locally-advanced or metastatic malignancy with KRAS p.G12C mutation identified through molecular testing and at least one or multiple lines of prior systemic therapy (eg, ≥2 for advanced/metastatic colorectal cancer). Primary endpoints include dose-limiting toxicities, treatment-emergent or -related adverse events. Secondary endpoints include pharmacokinetic parameters of combination regimens, disease control rate, duration of response, progression-free survival, and duration of stable disease (measured by computed tomography or magnetic resonance imaging and assessed per RECIST 1.1). The study began enrolling pts in December 2019 and is ongoing. For more information, please contact Amgen Medical Information: medinfo@amgen.com . Clinical trial information: NCT04185883 .
Symptoms of Depression and Associated Risk Factors in Patients with Epilepsy in Burkina Faso

Background: Depression is the most common psychiatric disorder in patients with epilepsy. The aim of this study was to determine the prevalence of depressive symptoms and its factors associated in patients with epilepsy at the Yalgado Ouedraogo University Teaching Hospital (Burkina Faso). Methods: This was a prospective 6-month study carried out in Neurology Department from February to July 2017. This study included all the patients with epilepsy aged over 18 years. Sampling was non-random with systematic recruitment. The informed consent of the patient was required. All included patients were assessed using the Hamilton Depression Scale and Gererd questionnaire. The analysis of the data was performed by the software Epi Info version 7. Results: One hundred two patients with epilepsy with a mean age of 41.47 ± 16.67 years were included. The symptoms of depression were present in 67.3% of patients with epilepsy with a mean age of 42.59 ± 17 years, and 78 years (19 - 88 years). Depression was mild in 35%, moderate in 34% and severe in 31%. The prevalence of depressive symptoms was respectively 57.6% in male patients and 79% in female gender. The mean score of HDRS for depression was 15.62 ± 4.26. Hypochondriasis (97%), work and interest (95.5%) and anxiety-somatic (94.1%) were the most symptoms of HDRS-17. Higher scores were found for work and interests, anxiety-psychic and hypochondriasis. There was a significant association between perceived stigma, female gender, seizure frequency and presence of depression among patients with epilepsy (p < 0.05). Conclusion: Our study had found a high prevalence of depression among patients with epilepsy. High perceived stigma, female gender and seizure frequency were the most associated factors with depressive symptoms.
Factors Effecting In Vitro Microrhizome Formation and Growth in Curcuma longa L. and Improved Field Performance of Micropropagated Plants

Microrhizomes were successfully produced from tissue culture derived shoots of Curcuma longa by transferring them to the liquid medium of Murashige and Skoog (MS) supplemented with 13.3mM BA (6- benzyladenine) and 6% sucrose, and culturing with a reduced photoperiod of 4 hours daily. Microrhizomes were formed at the base of the shoots grown on the medium after 30 days of incubation at 25 ± 1 o C. The number of buds per microrhizome varied from 1-4 and the weight varied from 50 mg to 580 mg. Factors such as concentration of sucrose and BA in the medium, as well as photoperiod and their interaction, were found to have a significant effect in the induction of microrhizomes. Sucrose was most effective in rhizome formation, followed by photoperiod and BA in the medium. Microrhizomes were harvested after 120 days of culture. These microrhizomes could be stored in MS media with a low concentration of BA (0.04mM) and in moist sand at room temperature. Microrhizomes were produced in vitro independent of seasonal fluctuation, and sprouted with roots and shoots in the potting soil and were then transferred to the field. Rate of sprouting of microrhizomes was not affected by the amount of sucrose and BA in induction medium, but only by duration of photoperiod in culture. Comparison of field performance of conventionally seed propagated and micropropagated plants revealed relative improvement in rhizome yield of micropropagated plants of Curcuma longa through in vitro induction of microrhizome.
COMPARISON WITH JAPANESE VOWEL ACOUSTICS – A LIKELIHOOD RATIO-BASED APPROACH USING SEGMENTAL

The suitability of vowel cepstral spectra for forensic voice comparison is explored within a likelihood ratio-based framework. Noncontemporaneous landline telephone recordings of 297 male Japanese speakers are compared using only two replicates each of their five vowels. 14 cepstrally-mean-subtracted LPC CCs from dc to 5 kHz are used as features. Multivariate likelihood ratios estimated for the 297 targetand 43956 nontarget trials give good results: an equal error rate of 0.28% and log likelihood ratio cost of 0.013. It is concluded that the approach has some merit.
Finite-temperature structure of theMAPbI3perovskite: Comparing density functional approximations and force fields to experiment

Determining the finite temperature structure of the hybrid perovskite MAPbI3 is a challenge for both experimental and theoretical methods. A very powerful computational method that can resolve the atomic structure is molecular dynamics (MD). The resulting structure depends on the density functional approximation (DFA) in the case of ab initio MD and the force field in classical MD. We compare the structure between 250K and 400K obtained with different DFAs and force fields in one consistent manner. The symmetry of the PbI3 framework is analyzed as well as the relative ordering of the neighboring organic molecules inside the framework. The distribution function of the molecules is used to map out an effective energy surface for the rotation of a single molecule. This surface is accurately modeled by a pair of cubic harmonics. Available experimental data in literature are discussed and compared to the structure obtained with the different methods. The spread in these data is still too large to uniquely determine the method that 'best' describes the perovskite, however promising candidates and outliers have been identified.
Biomarkers of diseases in medicine

Biomarkers have gained immense scientific and clinical value and interest in the practise of medicine. Biomarkers are potentially useful along the whole spectrum of the disease process. Before diagnosis, markers could be used for screening and risk assessment. During diagnosis, markers can determine staging, grading, and selection of initial therapy. During treatment, they can be used to monitor therapy, select additional therapy, or monitor recurrent diseases. Advances in genomics, proteomics and molecular pathology have generated many candidate biomarkers with potential clinical value. In the future, integration of biomarkers, identified using emerging high-throughput technologies, into medical practise will be necessary to achieve ‘personalization’ of treatment and disease prevention.