nils-herrmann/clean_scirepeval huggingface dataset:
True Happiness in the Presence of YHWH The Literary and Theological Context for Understanding Psalm 16
Year: 2016

This article attempts to interpret Ps 16 as part of the cluster of Psalms 15 24, but also as a Torah wisdom psalm. Hossfeld and Zenger have argued that Ps 16 was added to this cluster simultaneously with Pss 19 and 23, but that this happened quite some time before Ps 1 was composed to serve (together with Ps 2) as the preface to the whole Psalter. It is proposed here that Ps 16 is a Torahwisdom composition which exemplifies true blessedness as compliance with the Torah of YHWH in contentedness with one's lot in life. It thus represents the kind of piety also portrayed in other Torahwisdom psalms such as Pss 1, 19, 23 and 73. It is consequently suggested that Ps 16 is much closer to Ps 1 in time of origin and teaching as has been accepted until now. This does have implications for its interpretation.
Energy Efficient Relay in UAV Networks Against Jamming: A Reinforcement Learning Based Approach
Venue: 2020 IEEE 91st Vehicular Technology Conference (VTC2020 Spring)
Year: 2020

Unmanned aerial vehicle (UAV) networks are vulnerable to jamming attacks because of the high mobility, limited battery and scarce spectrum resources of UAVs. In this paper, we propose a reinforcement learning based UAV relay scheme to improve the anti jamming capability and save energy consumption of the UAV network. Based on the real time channel conditions and the historical relay experiences, the proposed scheme enables UAVs to improve the policy of relay power and strategies without knowing the UAV network and channel model. Simulation results show that the proposed UAV relay scheme reduces the bit error rate of the messages and reduces the energy consumption of the UAV network compared with the state of the art benchmark.
Heart failure and self care during the COVID 19 pandemic
Year: 2020

India and many other countries are facing the challenge and threat posed by the growing pandemic of COVID 19. Patients with chronic conditions such as heart failure (HF) are at greater risk of getting the infection. Since the HF patients are at greater risk and hospital outpatient department facilities have also stopped temporarily, patients need to be prepared for self care for HF. The objective of this article is to integrate practices and recommendations for self care, in order to maintain well being and prevent patients from getting infected. HF patients are encouraged to practice preventive and protective measures to limit the risk of COVID 19. HF nurses should focus on self care education teaching also about medications, personal and environmental hygiene, mask management, social and personal distancing, psychosocial aspect, and diet in HF. All the patients are advised and encouraged to use teleconferencing, virtual, and other means of electronic communications to avoid direct contacts with others. All HF patients should be advised to stay at home and follow the government advisories.
Significant Remote Sensing Vegetation Indices: A Review of Developments and Applications
Venue: J. Sensors
Year: 2017

Vegetation Indices (VIs) obtained from remote sensing based canopies are quite simple and effective algorithms for quantitative and qualitative evaluations of vegetation cover, vigor, and growth dynamics, among other applications. These indices have been widely implemented within RS applications using different airborne and satellite platforms with recent advances using Unmanned Aerial Vehicles (UAV) Up to date, there is no unified mathematical expression that defines all VIs due to the complexity of different light spectra combinations, instrumentation, platforms, and resolutions used. Therefore, customized algorithms have been developed and tested against a variety of applications according to specific mathematical expressions that combine visible light radiation, mainly green spectra region, from vegetation, and nonvisible spectra to obtain proxy quantifications of the vegetation surface. In the real world applications, optimization VIs are usually tailored to the specific application requirements coupled with appropriate validation tools and methodologies in the ground. The present study introduces the spectral characteristics of vegetation and summarizes the development of VIs and the advantages and disadvantages from different indices developed. This paper reviews more than 100 VIs, discussing their specific applicability and representativeness according to the vegetation of interest, environment, and implementation precision. Predictably, research, and development of VIs, which are based on hyperspectral and UAV platforms, would have a wide applicability in different areas.
Prediction and Experiment of Fracture Behavior in Hot Press Forming of a TA32 Titanium Alloy Rolled Sheet
Year: 2018

In aerospace and automotive industries, hot press forming (HPF) technology is widely used for rapid and precise deformation of the complex sheet metal component, where the fracture behavior has always been a focused problem. In this study, the hot tensile test and the Nakazima test were carried out, in order to establish the Misiolek constitutive equation and determine the forming limit strain points at an elevated temperature, respectively. The microstructure evolution during the tensile test was also investigated by optical microscope. In addition, the Marciniak Kuczynski (M K) model, considering the Mises, Hill48, and Logan Hosford yield criteria, was utilized to calculate the theoretical forming limit curve (FLC) Furthermore, the fracture behavior of the TA32 alloy sheet during the HPF process was accurately predicted by inserting the predicted FLC into finite element simulation, and the qualified complex component was obtained by optimizing the shape of the sheet.
Tool testing and reliability issues in the field of digital forensics
Venue: Digit. Investig.
Year: 2019

The digital forensic discipline is wholly reliant upon software applications and tools designed and marketed for the acquisition, display and interpretation of digital data. The results of any subsequent investigation using such tools must be reliable and repeatable whilst supporting the establishment of fact, allowing criminal justice proceedings the ability to digest any findings during the process of determining guilt or innocence. Errors present at any stage of an examination can undermine an entire investigation, compromising any potentially evidential results. Despite a clear dependence on digital forensic tools, arguably, the field currently lacks sufficient testing standards and procedures to effectively validate their usage during an investigation. Digital forensics is a discipline which provides decision makers with a reliable understanding of digital traces on any device under investigation, however, it cannot say with 100% certainty that the tools used to undertake this process produce factually accurate results in all cases. This is an increasing concern given the push for digital forensic organisations to now acquire ISO 17025 accreditation. This article examines the current state of digital forensic tool testing in 2018 along with the difficulties of sufficiently testing applications for use in this discipline. The results of a practitioner survey are offered, providing an insight into industry consensus surrounding tool testing and reliability.
Imitation Learning with Recurrent Neural Networks
Venue: ArXiv
Year: 2016

We present a novel view that unifies two frameworks that aim to solve sequential prediction problems: learning to search (L2S) and recurrent neural networks (RNN) We point out equivalences between elements of the two frameworks. By complementing what is missing from one framework comparing to the other, we introduce a more advanced imitation learning framework that, on one hand, augments L2S s notion of search space and, on the other hand, enhances RNNs training procedure to be more robust to compounding errors arising from training on highly correlated examples.
Political realism and international relations
Year: 2017

In this article, I explore recent work on realist political theory and international politics. I discuss how scholarship on the topic emanates from two different fields International Relations and political philosophy and argue that there is a good case for greater engagement between them. I open by delineating various kinds of realism, showing that the term covers a wide variety of methodological and political approaches. In particular, I suggest, it is important to recognize the difference between liberal and radical approaches. The remainder of the essay examines assorted examples of realist international political theorizing, work that ranges from attempts to rewrite the canon of 20th century political thought to contributions to the vibrant global justice debates.
A Smart Virtual Assistant Answering Questions About COVID 19
Venue: 2020 4th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)
Year: 2020

Numerous information and news put forward by different sources during the COVID 19 pandemic have caused many questions about the epidemic in people's minds. In this study, a smart virtual assistant was developed in order to eliminate this information pollution about COVID 19 and to give correct answers to people's questions with information obtained from reliable sources. Intelligent virtual assistants are question answering system software that enable people to get answers easily and quickly to their questions curious about. The use of these virtual assistants is becoming widespread all over the world in many fields, especially in education, e commerce, tourism, finance and health. However, the number of question answering system studies on Turkish is very few and insufficient. In fact, no question answering study was found in the field of health that is presented for Turkish in the literature. The smart virtual assistant presented within the scope of this study is a first in this respect. This smart virtual assistant answers two different types of questions. The first of these is frequently asked information questions about COVID 19 among the people. The second is the questions about numerical data such as number of COVID 19 cases, number of deaths, number of tests, etc. of countries in the world. It has been observed that the developed virtual assistant can answer the vast majority of users' questions about COVID 19. It is thought that this smart virtual assistant could be useful in fighting the COVID 19 pandemic.
Valuation of Volunteer Work in Satellite Account of Non Profit Institutions
Year: 2017

Volunteer work constitutes an important input into the activities of non profit institutions. However, in the core system of national accounts, volunteering falls outside the production boundary even if it leads to the production of services. By doing so, national accounts inevitably underestimates the contribution of non profit institutions to the well being. This shortcoming is overcome by the Satellite Account of Non profit Institutions complementing and extending the concept of national accounts chiefly by incorporation of the value of volunteering and by full coverage of non profit institutions classified in a number of economic sectors. This paper is an attempt to address the key issue that is the way of volunteer work's valuation for analytical purposes. We will discuss different approaches to the valuation and their impact on key macroeconomic aggregates.
Discussion: A review on the behaviour of helical piles as a potential offshore foundation system
Year: 2020

Helical piles have emerged as an attractive foundation system for offshore applications with renewed interest from the offshore community. Significant research gap currently exists in transferring this technology offshore and this paper discusses how existing and emerging knowledge can be successfully used to bridge some of the gaps. We focus on the Coupled Eulerian Lagrangian (CEL) large deformation finite element (LDFE) modelling technique that is commercially available and can be used to model the three dimensional installation process with consideration of strain rate and softening effects in soft offshore clays. A helical pile of L 7.5 m long is modelled with one or two large diameter helices (D 2 m) attached to a central shaft of d 0.5 m in diameter.The net effect of strain rate and softening is to increase the installation torque. The measured torque is within the range of 200 400 kN.m for the offshore clay and the pile geometry studied. Additional helices increase the uplift force but to a lesser degree than that of the measured torque. Remoulding induced strength reduction is found to be within the range of 25 33% of the intact clay strength. Issues of extracting and reusing offshore helical pile foundations are discussed.
A Project Guide to UX Design: For User Experience Designers in the Field or in the Making
Year: 2009

User experience design is the discipline of creating a useful and usable Web site or application thats easily navigated and meets the needs of the site owner and its users. Theres a lot more to successful UX design than knowing the latest Web technologies or design trends: It takes diplomacy, management skills, and business savvy. Thats where the updated edition of this important book comes in. With new information on design principles, mobile and gestural interactions, content strategy, remote research tools and more, youll learn to:Recognize the various roles in UX design, identify stakeholders, and enlist their supportObtain consensus from your team on project objectivesUnderstand approaches such as Waterfall, Agile, and Lean UXDefine the scope of your project and avoid mission creepConduct user research in person or remotely, and document your findingsUnderstand and communicate user behavior with personasDesign and prototype your application or sitePlan for development, product rollout, and ongoing quality assurance
Three new graphical models for statistical language modelling
Venue: ICML '07
Year: 2007

The supremacy of n gram models in statistical language modelling has recently been challenged by parametric models that use distributed representations to counteract the difficulties caused by data sparsity. We propose three new probabilistic language models that define the distribution of the next word in a sequence given several preceding words by using distributed representations of those words. We show how real valued distributed representations for words can be learned at the same time as learning a large set of stochastic binary hidden features that are used to predict the distributed representation of the next word from previous distributed representations. Adding connections from the previous states of the binary hidden features improves performance as does adding direct connections between the real valued distributed representations. One of our models significantly outperforms the very best n gram models.
Energy Management for Smart Multi Energy Complementary Micro Grid in the Presence of Demand Response
Year: 2018

With the application and the rapid advancement of smart grid technology, the practical application and operation status of multi energy complementary microgrids have been widely investigated. In the paper presented, the optimal operation of a solar unit, a storage battery and combined cooling, heating and power is studied via an economic optimization model implemented in General Algebraic Modeling Systems (GAMS) The model represents an optimization strategy for the economic operation of a microgrid considering demand response programs in different scenarios, and it is intended for the targets of minimizing the operating cost of the microgrid and maximizing the efficiency of renewable energy utilization. In addition, a multi time electricity price response model based on user behavior and satisfaction is established, and the core value of the model is to describe the mechanism and effect of participation in electricity price demand response. In order to verify the accuracy of the model proposed, we design the dispatch strategy of a microgrid under different states considering demand response, and use genetic algorithm to solve the optimization problems. On the other hand, the application of methodology to a real case study in Suzhou demonstrates the effectiveness of this model to solve the economic dispatch of the microgrid's renewable energy park.
RNA regulons in Hox 5'UTRs confer ribosome specificity to gene regulation
Venue: Nature
Year: 2015

Emerging evidence suggests that the ribosome has a regulatory function in directing how the genome is translated in time and space. However, how this regulation is encoded in the messenger RNA sequence remains largely unknown. Here we uncover unique RNA regulons embedded in homeobox (Hox) 5' untranslated regions (UTRs) that confer ribosome mediated control of gene expression. These structured RNA elements, resembling viral internal ribosome entry sites (IRESs) are found in subsets of Hox mRNAs. They facilitate ribosome recruitment and require the ribosomal protein RPL38 for their activity. Despite numerous layers of Hox gene regulation, these IRES elements are essential for converting Hox transcripts into proteins to pattern the mammalian body plan. This specialized mode of IRES dependent translation is enabled by an additional regulatory element that we term the translation inhibitory element (TIE) which blocks cap dependent translation of transcripts. Together, these data uncover a new paradigm for ribosome mediated control of gene expression and organismal development.
Trauma symptoms and personality traits in adolescents with experience of child maltreatment
Year: 2019

Child abuse and neglect is a general problem all around the world. It may result in the physical, psychological and social dysfunction of the child and it may cause serious consequences in the adult life. The aim of this study was to examine trauma symptoms and personality traits in adolescents with experiences of child maltreatment.  60 participants of both genders aged from 12 to 18 years were divided into two groups (group of abused children and adolescents group A and control group group C) Five questionnaires were used: General Questionnaire, Wechsler Abbreviated Scale of Intelligence, Trauma Symptom Checklist for Children Alternative (TSCC A) Childhood Trauma Questionnaire (CTQ) and Adolescent TRAUMA SYMPTOMS AND PERSONALITY TRAITS IN ADOLESCENTS WITH EXPERIENCE OF CHILD MALTREATMENT
High catalytic activity for formaldehyde oxidation of an interconnected network structure composed of d MnO2 nanosheets and g MnOOH nanowires
Year: 2020

Among the transition metal oxide catalysts, manganese oxides have great potential for formaldehyde (HCHO) oxidation at ambient temperature because of their high activity, nontoxicity, low cost, and polybasic morphologies. In this work, a MnO2 based catalyst (M MnO2) with an interconnected network structure was successfully synthesized by a one step hydrothermal method. The M MnO2 catalyst was composed of the main catalytic agent, d MnO2 nanosheets, dispersed in a nonactive framework material of g MnOOH nanowires. The catalytic activity of M MnO2 for HCHO oxidation at room temperature was much higher than that of the pure d MnO2 nanosheets. This is attributed to the special interconnected network structure. The special interconnected network structure has high dispersion and specific surface area, which can provide more surface active oxygen species and higher surface hydroxyl groups to realize rapid decomposition of HCHO.
Progesterone levels on pregnancy test day after hormone replacement therapy cryopreserved embryo transfer cycles and related reproductive outcomes.
Venue: Reproductive biomedicine online
Year: 2018

Do serum progesterone levels determine ongoing pregnancy rates (OPR) in hormone replacement therapy frozen thawed embryo transfer (HRT FET) cycles?  A cohort study of 244 HRT FET cycles from a Danish public fertility centre. Data from patients undergoing HRT FET from January 2016 to December 2017 were extracted from a clinical database. All patients had transfer in HRT cycles of autologous embryos frozen on day 5 or 6. Endometrial preparation was performed using 6 mg oestradiol valerate daily from the second day of the cycle followed by vaginal micronized progesterone (90 mg/8 h) All patients had serum progesterone measurement during the artificial luteal phase.  The optimal cut off for ongoing pregnancy was 35 nmol/l based on sensitivity analysis of different progesterone levels as a factor variable and its association with ongoing pregnancy. No significant differences regarding number of embryos transferred, embryo quality, age, body mass index (BMI) or smoking were found in the two groups of progesterone 35 nmol/l and 35 nmol/l, respectively. A total of 51% of patients had a serum progesterone 35 nmol/l. The range of all measurements was 0.3 to 110 nmol/l. The unadjusted OPR was significantly lower in the 35 nmol/l group compared with the 35 nmol/l group (38% versus 51%;P 0.04) A logistic regression analysis, adjusting for smoking, age, BMI, number of embryos transferred and blastocyst age showed a significant decrease in OPR when progesterone was 35 nmol/l of 44% (95% confidence interval [CI] 35 54% compared with 35 nmol/l of 58% (95% CI 48 68% risk difference of 14% (95% CI 2 26%,P 0.02)  Serum progesterone levels 35 nmol/l decrease the chance of OPR in HRT FET cycles.
Fatigue of natural fiber thermoplastic composites
Year: 2014

The fatigue behavior of hemp fiber reinforced High Density Polyethylene (HDPE) composites is investigated using fatigue life (S N) curves at different fiber volume fractions. For this purpose, a new modified stress level is proposed to normalize the developed S N curves into one normalized S N curve. A generalized fatigue behavior model is developed to simulate the fatigue life response of these composites. It is demonstrated that the developed model is capable of predicting the fatigue behavior of the natural fiber composites at different fiber fractions and fatigue stress ratios, and is also capable of accounting for the effect of moisture absorption.
CNN Based Subject Independent Driver Emotion Recognition System Involving Physiological Signals for ADAS
Year: 2016

Supporting drivers by Advanced Driver Assistance Systems (ADAS) significantly increases road safety. Driver's emotions recognition is a building block of advanced systems for monitoring the driver's comfort and driving ergonomics additionally to driver's fatigue and drowsiness forecasting. This paper presents an approach for driver emotions recognition involving a set of three physiological signals (Electrodermal Activity, Skin Temperature and the Electrocardiogram) Additionally, we propose a CNN (cellular neural network) based classifier to classify each signal into four emotional states. Moreover, the subject independent classification results of all signals are fused using Dempster Shafer evidence theory in order to obtain a more robust detection of the true emotional state. The new system is tested using the benchmarked MAHNOB HCI dataset and the results show a relatively high performance compared to existing competing algorithms from the recent relevant literature.