nils-herrmann/clean_scirepeval huggingface dataset:
Climate change and the Syrian civil war revisited
Year: 2017

For proponents of the view that anthropogenic climate change will become a 'threat multiplier' for instability in the decades ahead, the Syrian civil war has become a recurring reference point, providing apparently compelling evidence that such conflict effects are already with us. According to this view, human induced climatic change was a contributory factor in the extreme drought experienced within Syria prior to its civil war; this drought in turn led to large scale migration; and this migration in turn exacerbated the socio economic stresses that underpinned Syria's descent into war. This article provides a systematic interrogation of these claims, and finds little merit to them. Amongst other things it shows that there is no clear and reliable evidence that anthropogenic climate change was a factor in Syria's pre civil war drought; that this drought did not cause anywhere near the scale of migration that is often alleged; and that there exists no solid evidence that drought migration pressures in Syria contributed to civil war onset. The Syria case, the article finds, does not support 'threat multiplier' views of the impacts of climate change; to the contrary, we conclude, policymakers, commentators and scholars alike should exercise far greater caution when drawing such linkages or when securitising climate change.
Green human resource management and environmental cooperation: An ability motivation opportunity and contingency perspective
Year: 2020

This study examines the value of green human resource management (GHRM) in supporting environmental cooperation with customers and suppliers, and the moderating roles of internal green supply chain management (GSCM) A survey of 126 automobile manufacturers in China is analysed using moderated regression analysis, based on a proposed conceptual model grounded in ability motivation opportunity (AMO) theory and contingency theory (CT) The results reveal that GHRM is significantly and positively related to environmental cooperation with customers and suppliers, and that the relationships are significantly moderated by internal GSCM. HRM practitioners are advised to develop GHRM practices that provide training (ability) incentive (motivation) and conductive environment (opportunity) to help implement environmental collaboration, while SCM practitioners may improve internal GSCM to strengthen the effects of GHRM. This study clarifies key GHRM practices that contribute to GSCM, and advances related research by developing and testing an overarching model to explain such synergies and the moderating role of internal GSCM.
Advances in the application of Ontologies in the area of Digital Forensic Electronic Mail
Venue: IEEE Latin America Transactions
Year: 2019

This article presents a descriptive review of the research published in the last five years to identify areas of unavailability in the study of Digital Forensics problems. Particularly, it is important to define the state of the art related to the application of ontologies, especially in the forensics of emails. The following objectives of the review are proposed: identify and study the most up to date research contributions on Ontologies and Digital Forensics; establish the gaps in current research reltated with the application of Ontologies to Digital Forensics; and correlate these works from attributes of proximity (or distance) with the application of ontologies to the forensic analysis of emails. In addition, a systematic method is defined to select the research works that are considered of interest for this review. It is expected that it will lead to the identification of gaps in the investigation of characteristic problems in digital forensic analysis, and the definition of an updated theoretical framework linked to the forensic analysis of emails with the application of ontologies.
A Fast and Power Efficient Hardware Architecture for Non Maximum Suppression
Venue: IEEE Transactions on Circuits and Systems II: Express Briefs
Year: 2019

Non maximum suppression (NMS) is an indispensable post processing step in face detection. The vast majority of face detection methods need NMS to merge the candidate detected face boxes that belong to the same face. However, the standard NMS is a greedy and local optimization technique which suffers from several shortcomings, such as high complexity <inline formula> <tex math notation="LaTeX"{O} /tex math>/inline formula><inline formula> <tex math notation="LaTeX"{N} \boldsymbol {2} /tex math>/inline formula> high latency, and large power consumption. This brief alleviates these problems and presents an efficient hardware architecture for NMS, meanwhile, carries out the optimization for the calculation unit to achieve the reduction of area accordingly. Based on the multi thread computing, this brief utilizes sliding window to obtain parallelism and uses position based bit table technique for the enhancement of data accessing and data reusing, which greatly decreases the cost of memory access and power consumption. The proposed hardware architecture is implemented in TSMC 28 nm technology. Experiments show that the power consumption is 6.142 mW and the latency is 12.79 <inline formula> <tex math notation="LaTeX" \mu \text{s} /tex math>/inline formula> to cluster 1000 candidate boxes, whose energy efficiency is higher than those state of the art methods by <inline formula> <tex math notation="LaTeX"$3798 \times /tex math>/inline formula> and <inline formula> <tex math notation="LaTeX"$358 \times /tex math>/inline formula> respectively.
Implementing Triple Stores using NoSQL Databases
Venue: RTA CSIT
Year: 2018

Knowledge bases empower various information retrieval systems nowadays. The usual implementation of them is through RDF based triple stores. The available toolkits that enable this are usually less mature in comparison with well established document oriented NoSQL databases. In this work we report on an alternative implementation of triple stores using NoSQL databases. In comparison with similar solutions in this regard, we decided to not use RDF at all, therefore no data or query mapping was needed. We propose the implementation of a vocabolary using a separate document collection. This would also facilitate the dynamic enlargement of it in automated fact extraction scenarios. Our results show that using a document oriented NoSQL database for storing and retrieving triples offers a considerable performance. The involved preprocessing needed because of the limitations of a non RDF based solution, did not affect this. The achieved performance was also higher in comparison with doing the same knowledge retrieval operations using a purposely built linked data toolkit.
Modified SVPWM Algorithm for Three Level VSI With Synchronized and Symmetrical Waveforms
Venue: International Journal of Scientific Research in Science and Technology
Year: 2019

To generate the required reference vector than triangle comparison based PWM techniques for three level inverters the space vector based PWM (SVPWM) strategies contain broader choice of switching sequences. This space vector based PWM technique involves in various steps. These steps are computationally exhaustive. The SVPWM has been used in three phase inverter control system. The center aligned PWM is the most effective way for the Microprocessor Control Unit implementation of the SVPWM, because it can easily generate the center aligned PWM of the multilevel inverters for generation of the signal of space vector pulse width modulation (SVPWM) this concept brings out the method. The inverter leg switching times are generated by this algorithm and middle vector switching times are centered in a sampled interval. The proposed algorithm does not require any sector identification. And it reduces the computational time as a result. The adjacent voltage space vectors are forming the small triangles it is called sectors. Multilevel converters can meet the increasing demand of power ratings and power quality associated with reduced harmonic distortion and lower electromagnetic interference. Furthermore to optimize switching waveforms, space vector pulse width modulation algorithms offer great flexibility among them. Finally the results are verified through MATLAB/SIMULINK
Synthesizing Tabular Data using Generative Adversarial Networks
Year: 2018

Generative adversarial networks (GANs) implicitly learn the probability distribution of a dataset and can draw samples from the distribution. This paper presents, Tabular GAN (TGAN) a generative adversarial network which can generate tabular data like medical or educational records. Using the power of deep neural networks, TGAN generates high quality and fully synthetic tables while simultaneously generating discrete and continuous variables. When we evaluate our model on three datasets, we find that TGAN outperforms conventional statistical generative models in both capturing the correlation between columns and scaling up for large datasets.
Urgensi Shalat dalam Pembentukan Kepribadian Muslim
Year: 2019

Skripsi berjudul Urgensi Shalat dalam Pembentukan Kepribadian Muslim. Rumusan masalah dalam penelitian ini urgensi shalat dalam pembentukan kepribadian Muslim, dan upaya shalat agar dapat membentuk kepribadian Muslim. Adapun penelitian ini bertujuan untuk mengetahui urgensi shalat dalam pembentukan kepribadian Muslim dan untuk mengetahui upaya shalat agar dapat membentuk kepribadian Muslim. Untuk menjawab penelitian tersebut, penulis menggunakan metode penelitian kualitatif jenis Library Research (kajian pustaka) data yang dikumpulkan dari perpustakaan dengan mengutip, memilah, menyusun dan menganalisis isi (content analysis) terhadap literatur yang representatif dengan menggunakan pendekatan tafsir tematik, yaitu tafsir Al Misbah oleh Quraisy Shihab. Dari hasil penelitian menunjukkan bahwa shalat sebagai ibadah yang paling sempurna dalam memenuhi kebutuhan spiritual seorang Muslim, kekuatan spiritual tersebut akan menghasilkan refleksi dalam diri dan kemudian diwujudkan dalam bentuk aksi sehingga dari aksi tersebut tampaklah dalam kepribadian Muslim.
Cation ordering, valence states, and symmetry breaking in the crystal chemically complex mineral chevkinite (Ce) X ray diffraction and photoelectron spectroscopy studies and mechanisms of Nb enrichment
Venue: American Mineralogist
Year: 2019

The crystal structures of natural Nb rich chevkinite (Ce) from the Biraya rare metal deposit, Russia, crystallizing in space groups C2/m and P21/a, were solved and refined to R1 0.03 and R1= 0.07, respectively, from data collected with a single crystal diffractometer. X ray photoelectron spectroscopy was used to determine the oxidation states of the following ions: Ce3+ Fe2+ Fe3+ Ti4+ and Ti3+ Typically, Nb rich chevkinite (Ce) has space group C2/m, but specimens with space group P21/a were also identified. While XPS shows that both C2/m and P21/a crystal structures contain Ti4+ and Ti3+ it also indicates that Ti2+ may occur in the P21/a phases. The general formula for the Nb rich chevkinite (Ce) having space group C2/m is (Ce3+,La3+,Nd3+,Pr3+,Ca2+,Na+)4Fe2+(Fe3+,Nb5+,Al3+)2 (Ti4+,Ti3+,Nb5+,Mg2+)2(Si2O7)2O8 and with P21/a is (Ce3+,La3+,Nd3+,Pr3+,Ca2+,Na+)4(Fe2+,Mg2+,Ti2+)1 (Fe3+,Nb5+,Al3+)2(Ti4+,Ti3+,Nb5+)2(Si2O7)2O8. It is proposed that, in addition to the substitution CFe3+ DTi4+ CFe2+ DNb5+ niobium can also be incorporated into chevkinite (Ce) by the substitution 2DTi4+ DNb5+ DTi3+ leading to substantial Nb enrichment. The study has revealed that the distribution of cations between the various structural sites is considerably more complex than that envisaged in standard models of the chevkinite group, and that cations such as Ti can have more than one valency in the structure. Lighter elements with larger ionic radii (Mg2+ tend to occupy the D site in the C2/m crystal structure, whereas in the P21/a structure these elements (Mg2+ Ti2+ tend to enter the B site. Niobium is distributed between the C and D sites. The techniques employed provide a comprehensive representation of the distribution of cations and can be used to examine similar complexity in other mineral groups. The present study has shown that Nb can also be fractionated from residual melts.
Effect of immediate and delayed dentin sealing on the fracture strength, failure type and Weilbull characteristics of lithiumdisilicate laminate veneers.
Venue: Dental materials official publication of the Academy of Dental Materials
Year: 2016

Adhesion on dentin is less reliable than on enamel, which could affect the durability of laminate veneers (LV) Immediate dentin sealing (IDS) is suggested instead of delayed dentin sealing (DDS) to overcome hypersensitivity and prevent debonding from dentin. This study evaluated the effect of IDS and DDS on the durability of Li2Si2O5 laminate veneers in vitro.  Window preparations were made on the labial surfaces of sound maxillary central incisors (N=50) They were randomly divided into five groups: Group 1: Enamel only+H3PO4+Adhesive (control) Group 2: <1/4 dentin+H3PO4+DDS (2 weeks later) Group 3: Complete dentin+H3PO4+DDS (2 weeks later) Group 4: <1/4 dentin+H3PO4+IDS; Group 5: Complete dentin+H3PO4+IDS. Li2Si2O5 laminate veneers (e.max Press) were bonded to the labial surfaces of the teeth with adhesive resin cement (Variolink Veneer) IDS layers were silicacoated (CoJet System) and silanized (ESPE Sil) The teeth with their bonded laminates were thermocycled (10.000x cycles) and then subjected to static loading (1mm/min) Failure type and location after debonding were classified. Data were analyzed using ANOVA and Tukey's post hoc test (a=0.05) Two parameter Weibull distribution values including the Weibull modulus, scale (m) and shape (0) values were calculated.  Mean fracture strength (N) per group in descending order was as follows: Group 5 (576+ 254) Group 4 (478+ 216) Group 1 (473+ 159) Group 2 (465+ 186) and Group 3 (314+ 137) The presence of complete dentin exposure sealed with DDS after 2 weeks on the bonded surface (Group 3) resulted in significantly lower fracture strength results than those in group 5 with IDS (p=0.034) Weibull distribution presented higher shape (0) for Group 1 (3.67) than those of other groups (2.51 2.89) Failure types were predominantly adhesive failure between the cement and the laminate veneer in Groups 1, 2, 4 whereas Group 3 presented more often complete adhesive failures between the cement and dentin. In Group 5, failures showed some IDS and cement with or without ceramic fracture attached on the tooth.  When laminate veneers are bonded to a large dentin substrate, application of immediate dentin sealing improves adhesion and thereby, the fracture strength of Li2Si2O5 laminate veneers.
Optimizing Gaussian Process Regression for Image Time Series Gap Filling and Crop Monitoring
Year: 2020

Image processing entered the era of artificial intelligence, and machine learning algorithms emerged as attractive alternatives for time series data processing. Satellite image time series processing enables crop phenology monitoring, such as the calculation of start and end of season. Among the promising algorithms, Gaussian process regression (GPR) proved to be a competitive time series gap filling algorithm with the advantage of, as developed within a Bayesian framework, providing associated uncertainty estimates. Nevertheless, the processing of time series images becomes computationally inefficient in its standard per pixel usage, mainly for GPR training rather than the fitting step. To mitigate this computational burden, we propose to substitute the per pixel optimization step with the creation of a cropland based precalculations for the GPR hyperparameters th To demonstrate our approach hardly affects the accuracy in fitting, we used Sentinel 2 LAI time series over an agricultural region in Castile and Leon, North West Spain. The performance of image reconstructions were compared against the standard per pixel GPR time series processing. Results showed that accuracies were on the same order (RMSE 0.1767 vs. 0.1564 m 2 m 2 12% RMSE degradation) whereas processing time accelerated about 90 times. We further evaluated the alternative option of using the same hyperparameters for all the pixels within the complete scene. It led to similar overall accuracies over crop areas and computational performance. Crop phenology indicators were also calculated for the three different approaches and compared. Results showed analogous crop temporal patterns, with differences in start and end of growing season of no more than five days. To the benefit of crop monitoring applications, all the gap filling and phenology indicators retrieval techniques have been implemented into the freely downloadable GUI toolbox DATimeS.
The Nature of the Relationship Between Anxiety and the Error Related Negativity Across Development
Venue: Current Behavioral Neuroscience Reports
Year: 2017

the literature on the relationship between anxiety and the error related negativity (ERN) a neurophysiological marker of performance monitoring, across development. I cover the development of the ERN, its functional significance, and its different relationship with anxiety in young children compared to adolescents and adults.Recent FindingsContemporary research indicates that the ERN becomes larger with age and shows primary sources in cingulate, frontal, and motor cortices. Functional accounts of the ERN and its relationship with anxiety emphasize either cognitive control or affective mechanisms. Converging evidence across development suggests a reduced ERN characterizes anxious young children whereas an enlarged ERN characterizes older children, adolescents, and adults.SummaryThe mechanisms involved in the developmental change in the relationship between the ERN and anxiety have important implications for better understanding interactions between cognitive control, anxiety, and motivation across the life span. Further research is needed to address extant methodological limitations and make stronger links to related neuroscience findings and theory on the development of anxiety and self control.
PROteolysis TArgeting Chimeras (PROTACs) as emerging anticancer therapeutics
Venue: Oncogene
Year: 2020

Using PROteolysis TArgeting Chimeras (PROTACs) to degrade proteins that are important for tumorigenesis has emerged as a potential therapeutic strategy for cancer. PROTACs are heterobifunctional molecules consisting of one ligand for binding to a protein of interest (POI) and another to an E3 ubiquitin (E3) ligase, connected via a linker. PROTACs recruit the E3 ligase to the POI and cause proximity induced ubiquitination and degradation of the POI by the ubiquitin proteasome system (UPS) PROTACs have been developed to degrade a variety of cancer targets with unprecedented efficacy against a multitude of tumor types. To date, most of the PROTACs developed have utilized ligands to recruit E3 ligases that are ubiquitously expressed in both tumor and normal tissues. These PROTACs can cause on target toxicities if the POIs are not tumor specific. Therefore, identifying and recruiting the E3 ligases that are enriched in tumors with minimal expression in normal tissues holds the potential to develop tumor specific/selective PROTACs. In this review, we will discuss the potential of PROTACs to become anticancer therapeutics, chemical and bioinformatics approaches for PROTAC design, and safety concerns with a special focus on the development of tumor specific/selective PROTACs. In addition, the identification of tumor types in terms of solid versus hematological malignancies that can be best targeted with PROTAC approach will be briefly discussed.
SACPC: A framework based on probabilistic linguistic terms for short text sentiment analysis
Venue: Knowl. Based Syst.
Year: 2020

Short text sentiment analysis is challenging because short texts are limited in length and lack context. Short texts are usually rather ambiguous because of polysemy and the typos these texts contain. Polysemy is the coexistence of multiple word meanings and commonly appears in every language. Various uses of a word may assign the word both positive and negative meanings. In previous studies, the variability of words is often ignored, which may cause analysis errors. In this study, to resolve this problem, we proposed a novel text representation model named Word2PLTS for short text sentiment analysis by introducing probabilistic linguistic terms sets (PLTSs) and the relevant theory. In this model, every word is represented as a PLTS that fully describes the possibilities for the sentiment polarity of the word. Then, by using support vector machines (SVM) a novel sentiment analysis and polarity classification framework named SACPC is obtained. This framework is a technique that combines supervised learning and unsupervised learning. We compare SAPCP to lexicon based approaches and machine learning approaches on three benchmark datasets. A noticeable improvement in performance is achieved. To further verify the superiority of SAPCP, state of the art performance comparisons are conducted, and the results are impressive.
Mean Landslide geometries inferred from a global database of earthquake and non earthquake triggered landslides
Year: 2017

Ranging in size from very small to tremendous, landslides often cause loss of life and damage to infrastructure, property and the environment. They are triggered by a variety and combinations of causes among which the role of water and seismic shaking have the most serious consequences. In this regard, seismic wave amplification due to topography as well as to the impedance contrast between the landslide mass and its underlying bedrock are of particular interest. Therefore, high resolution reconstruction of the lateral confinement of the landslide mass and the exact measurement of the mechanical properties are a necessity. A global chronological database was created to study and compare 2D and 3D geometries of landslides, i.e. of landslides properly sliding on a rupture surface. It contains 277 seismically and non seismically induced landslides whose rupture masses were measured in all available details allowing for statistical analyses of their shapes and to create numerical models thereupon based. Detailed studies reveal that values of distinct geometrical parameters have different statistical behaviors. As for dimension related parameters, occurrence frequencies follow decreasing exponential distributions and mean values progressively increase with landslide magnitude. In contrast, occurrence frequencies of shape related parameters follow normal distributions and mean values are constant throughout different landslide magnitudes. Dimensions and shapes of landslides are thus to be regarded in a precise and distinctive manner when analyzing seismically induced slope displacements.