nils-herrmann/clean_scirepeval huggingface dataset:
A Novel Framework for Estimating Viewer Interest by Unsupervised Multimodal Anomaly Detection
Venue: IEEE Access
Year: 2018

A reliable method to estimate viewer interest is highly sought after for human centered video information retrieval. A method that estimates viewer interest while users are watching Web videos is presented in this paper. The method uses a framework for anomaly detection based on collaborative use of facial expression and biological signals such as electroencephalogram (EEG) signals. To the best of our knowledge, there have been no studies that have taken into account two actual mechanisms of the behavior of users while they are watching Web videos. First, whereas most Web videos garner very little attention, a small number attract millions of views. Therefore, a framework for anomaly detection is newly applied to facial expression and EEG in order to model the imbalanced distribution of popularity. Second, since the number of Web videos that are labeled by users as interesting/not interesting is generally too small to estimate viewer interest by a supervised approach, the proposed method utilizes parametric techniques for anomaly detection, which estimates viewer interest in an unsupervised way. Unlike some related studies for estimating viewer interest, our method takes into account actual mechanisms of the behavior of users while they are watching Web videos by utilizing parametric techniques for anomaly detection. Then viewer interest can be estimated on the basis of an anomaly score calculated from our proposed method. Consequently, successful estimation of viewer interest based on a framework for anomaly detection, via collaborative use of facial expression and biological signals, becomes feasible.
COVID 19 among Chinese high school graduates: Psychological distress, growth, meaning in life and resilience.
Venue: Journal of health psychology
Year: 2021

This study examined perceived impact of COVID 19 (PIC) on mental health outcomes (anxiety, depression, and posttraumatic growth) and roles of resilience and meaning in life. In October 2020, 430 Chinese high school graduates completed self report measures. Results showed that 4.4% and 5.8% participants had anxiety and depression symptoms (10) respectively, while 13.3% developed posttraumatic growth (37.5) Resilience and meaning in life mediated the relationships between PIC and mental health outcomes. These findings underline psychological distress and growth coexisted in COVID 19, while resilience and meaning in life served as important protective factors of mental health.
Explicit Sentence Compression for Neural Machine Translation
Venue: AAAI
Year: 2020

State of the art Transformer based neural machine translation (NMT) systems still follow a standard encoder decoder framework, in which source sentence representation can be well done by an encoder with self attention mechanism. Though Transformer based encoder may effectively capture general information in its resulting source sentence representation, the backbone information, which stands for the gist of a sentence, is not specifically focused on. In this paper, we propose an explicit sentence compression method to enhance the source sentence representation for NMT. In practice, an explicit sentence compression goal used to learn the backbone information in a sentence. We propose three ways, including backbone source side fusion, target side fusion, and both side fusion, to integrate the compressed sentence into NMT. Our empirical tests on the WMT English to French and English to German translation tasks show that the proposed sentence compression method significantly improves the translation performances over strong baselines.
Nong Chan Pin An Quan Sheng Chan Guan Li Xi Tong Xin Kuang Jia Ajax+jQuery
Year: 2011

Wei Shi Ji Yu WebDe Nong Chan Pin An Quan Sheng Chan Guan Li Xi Tong Ju You Liang Hao De Yong Hu Jiao Hu Xing ,Zai Jie Shao AjaxYi Bu Tong Xin Ji Zhu Ji jQueryKuang Jia De Yuan Li Yu You Dian De Ji Chu Shang ,Ti Chu Li Yong AjaxHe jQueryKuang Jia Shi Xian Ji Yu WebDe Nong Chan Pin An Quan Sheng Chan Guan Li Xi Tong Wei Ci ,Xiang Xi Chan Shu Liao Xi Tong De Gong Neng Jie Gou Zheng Ti Jia Gou Chu Li Liu Cheng Yi Ji Zhu
A Review of Shariah Auditing Practices in Ensuring Governance in Islamic Financial Institution (IFIs) A Preliminary Study
Year: 2018

The main objective of shariah auditing  is to embrace the Maqasid As Shariah (Objective of Islamic Principles) as well as to uphold the shariah principles in all business processes. Shariah auditing goes beyond the usual attestation and assurance for the financial statement, internal control and governance of firms and specified by the Central Bank of Malaysia (BNM) in Shariah Governance Framework (SGF, 2010) to be conducted by internal auditors. This paper discusses current practices of shariah auditing among Islamic Financial Institutions (IFIs) in Malaysia. Data reported in this paper is obtained through 15 semi structured interviews conducted with chief internal audit, managers of internal audit department, shariah committee, external auditor and academicians. Findings indicated that the practices are still evolving where further developments and improvements are required focusing particularly on standardization of shariah audit framework and guidelines to design audit program for shariah auditing.In addition a proper design of competency framework for auditors performing shariah audit is highly recommended.  According to Shariah Governance Framework for Islamic Financial Institutions" (SGF, 2010) issued by the Central Bank of Malaysia (BNM) defined shariah audit as "the periodical assessment conducted from time to time, to provide an independent assessment and objective assurance designed to add value and improve the degree of compliance in relation to the IFI's business operations, with the main objective of ensuring a sound and effective internal control system for Shariah (Islamic) compliance"
DeepCT: Tomographic Combinatorial Testing for Deep Learning Systems
Venue: 2019 IEEE 26th International Conference on Software Analysis, Evolution and Reengineering (SANER)
Year: 2019

Deep learning (DL) has achieved remarkable progress over the past decade and has been widely applied to many industry domains. However, the robustness of DL systems recently becomes great concerns, where minor perturbation on the input might cause the DL malfunction. These robustness issues could potentially result in severe consequences when a DL system is deployed to safety critical applications and hinder the real world deployment of DL systems. Testing techniques enable the robustness evaluation and vulnerable issue detection of a DL system at an early stage. The main challenge of testing a DL system attributes to the high dimensionality of its inputs and large internal latent feature space, which makes testing each state almost impossible. For traditional software, combinatorial testing (CT) is an effective testing technique to balance the testing exploration effort and defect detection capabilities. In this paper, we perform an exploratory study of CT on DL systems. We propose a set of combinatorial testing criteria specialized for DL systems, as well as a CT coverage guided test generation technique. Our evaluation demonstrates that CT provides a promising avenue for testing DL systems.
Satellite Monitoring the Spatial Temporal Dynamics of Desertification in Response to Climate Change and Human Activities across the Ordos Plateau, China
Venue: Remote. Sens.
Year: 2017

The Ordos Plateau, a typical semi arid area in northern China, has experienced severe wind erosion events that have stripped the agriculturally important finer fraction of the topsoil and caused dust events that often impact the air quality in northern China and the surrounding regions. Both climate change and human activities have been considered key factors in the desertification process. This study used multi spectral Landsat Thematic Mapper (TM) Enhanced Thematic Mapper Plus (ETM+ and Operational Land Imager (OLI) remote sensing data collected in 2000, 2006, 2010 and 2015 to generate a temporal series of the modified soil adjusted vegetation index (MSAVI) bare soil index (BSI) and albedo products in the Ordos Plateau. Based on these satellite products and the decision tree method, we quantitatively assessed the desertification status over the past 15 years since 2000. Furthermore, a quantitative method was used to assess the roles of driving forces in desertification dynamics using net primary productivity (NPP) as a commensurable indicator. The results showed that the area of non desertification land increased from 6647 km2 in 2000 to 15,961 km2 in 2015, while the area of severe desertification land decreased from 16,161 km2 in 2000 to 8,331 km2 in 2015. During the period 2006 2015, the effect of human activities, especially the ecological recovery projects implemented in northern China, was the main cause of desertification reversion in this region. Therefore, ecological recovery projects are still required to promote harmonious development between nature and human society in ecologically fragile regions like the Ordos Plateau.
A clustering based approach for discovering interesting places in trajectories
Venue: SAC '08
Year: 2008

Because of the large amount of trajectory data produced by mobile devices, there is an increasing need for mechanisms to extract knowledge from this data. Most existing works have focused on the geometric properties of trajectories, but recently emerged the concept of semantic trajectories, in which the background geographic information is integrated to trajectory sample points. In this new concept, trajectories are observed as a set of stops and moves, where stops are the most important parts of the trajectory. Stops and moves have been computed by testing the intersections of trajectories with a set of geographic objects given by the user. In this paper we present an alternative solution with the capability of finding interesting places that are not expected by the user. The proposed solution is a spatio temporal clustering method, based on speed, to work with single trajectories. We compare the two different approaches with experiments on real data and show that the computation of stops using the concept of speed can be interesting for several applications.
Characterization of Particulate Matter and Gaseous Emissions of a C 130H Aircraft
Venue: Journal of the Air Waste Management Association
Year: 2008

The gaseous and nonvolatile particulate matter (PM) emissions of two T56 A 15 turboprop engines of a C 130H aircraft stationed at the 123rd Airlift Wing in the Kentucky Air National Guard were characterized. The emissions campaign supports the Strategic Environmental Research and Development Program (SERDP) project WP 1401 to determine emissions factors from military aircraft. The purpose of the project is to develop a comprehensive emissions measurement program using both conventional and advanced techniques to determine emissions factors of pollutants, and to investigate the spatial and temporal evolutions of the exhaust plumes from fixed and rotating wing military aircraft. Standard practices for the measurement of gaseous emissions from aircraft have been well established; however, there is no certified methodology for the measurement of aircraft PM emissions. In this study, several conventional instruments were used to physically characterize and quantify the PM emissions from the two turboprop engines. Emissions samples were extracted from the engine exit plane and transported to the analytical instrumentation via heated lines. Multiple sampling probes were used to assess the spatial variation and obtain a representative average of the engine emissions. Particle concentrations, size distributions, and mass emissions were measured using commercially available aerosol instruments. Engine smoke numbers were determined using established Society of Automotive Engineers (SAE) practices, and gaseous species were quantified via a Fourier transform infrared based gas analyzer. The engines were tested at five power settings, from idle to take off power, to cover a wide range of operating conditions. Average corrected particle numbers (PNs) of (6.4 14.3) x 107 particles per cm3 and PN emission indices (EI) from 3.5 x 1015 to 10.0 x 1015 particles per kg fuel were observed. The highest PN EI were observed for the idle power conditions. The mean particle diameter varied between 50 nm at idle to 70 nm at maximum engine power. PM mass EI ranged from 1.6 to 3.5 g/kg fuel for the conditions tested, which are in agreement with previous T56 engine measurements using other techniques. Additional PM data, smoke numbers, and gaseous emissions will be presented and discussed.
Spontaneous imbibition in shale: A review of recent advances
Venue: Capillarity
Year: 2019

Spontaneous imbibition in shale is commonly observed during and after hydraulic fracturing. This mechanism greatly influences hydrocarbon recovery in shale plays, therefore attracting increasing attention from researchers. The number of related publications is increasing. In this review, we summarize the recent advances in shale spontaneous imbibition from three aspects, namely, conventional spontaneous imbibition models, common experimental methods, and key mechanisms that need to be focused on. The major influencing factors on the shale imbibition process are discussed, and promising future works are presented on the basis of the merits and demerits of the recent studies. This study discusses the mechanisms of shaleliquid interaction, the complexity of multiphase flow in shale plays, and highlights the achievements and challenges in shale imbibition research. Cited as Li, C. Singh, H. Cai, J. Spontaneous imbibition in shale: A review of recent advances. Capillarity, 2019, 2(2) 17 32, doi: 10.26804/capi.2019.02.01.
Pengaruh Kitosan Udang Secara Topikal Terhadap Kepadatan Kolagen dalam Penyembuhan Luka Eksisi pada Tikus Putih
Year: 2020

Luka eksisi adalah luka yang permukaan kulit dan lapisan bawahnya akan terpotong sampai kedalaman yang bervariasi dapat terjadi secara sengaja atau tidak sengaja. Tujuan dari penelitian ini adalah untuk mengetahui pengaruh chitosan kulit udang terhadap kepadatan kolagen dalam proses penyembuhan luka eksisi pada tikus putih. Sebanyak dua puluh ekor tikus putih Rattus norvegicus) jantan dibagi ke dalam lima kelompok perlakuan yaitu K luka eksisi dengan pemberian basis salep, K+ (luka eksisi+10% povidone iodine P1 (luka eksisi+salep chitosan kulit udang 1.5% P2 (luka eksisi+udang salep kulit kitosan 2.5% dan P3 (luka eksisi+kitosan kulit udang 5% Hasil perhitungan persentase kepadatan kolagen dianalisis oleh Kruskal Wallis yang menunjukkan perbedaan signifikan (p<0.05) dan dilanjutkan dengan uji Mann Whitney U. Kelompok K+ K dan P1 memiliki perbedaan signifikan dalam kepadatan kolagen pada P2, dan kelompok P3 (p<0.05) Kesimpulan dari penelitian ini kitosan berpengaruh terhadap kepadatan kolagen dengan dosis 5%
Empirical equations for the prediction of third phase formation limits in the extraction of thorium nitrate by tri iso amyl phosphate (TiAP)
Venue: Journal of Radioanalytical and Nuclear Chemistry
Year: 2015

Third phase formation in the extraction of Th(IV) by TiAP in various n alkane diluents was investigated under different conditions. The limiting organic concentrations (LOC) for third phase formation for TiAP/n alkane/thorium nitrate systems were measured as a function of various parameters for deriving empirical equations with respect to extractant concentration, equilibrium aqueous phase nitric acid concentration [HNO3]aq,eq) temperature and number of carbon atoms per diluent for the prediction of LOC. Our results show a very good agreement between the LOC values calculated with empirical equations derived from two different approaches.
Telecommunication band InAs quantum dots and dashes embedded in different barrier materials
Year: 2012

We investigate the long wavelength (1.2 to 1.55 micro m) photoluminescence of high density InAs quantum dots and dashes, which were grown on InP substrates. We analyze the temperature dependence of the recombination and carrier distribution on the alloy composition of the barrier materials, InGaAlAs, and on the existence of a wetting layer. Carrier escape and transfer are discussed based on temperature dependent photoluminescence measurements and theoretical considerations about the heterostructures' confinement energies and band structure. We propose two different contributions to the thermal quenching, which can explain the observations for both the quantum dot and dash samples. Among these one is a unique phenomenon for high density quantum dot/dash ensembles which is related to significant inter dot/dash coupling. With the goal ahead to use these dots and dashes for quantum optical applications on the single dot/dash level in the telecommunication C band as well as at elevated temperatures we present first steps towards the realization of such devices.
Title Analysis of the impact degree distribution in metabolicnetworks using branching process approximation
Year: 2019

Theoretical frameworks to estimate the tolerance of metabolic networks to various failures are important to evaluate the robustness of biological complex systems in systems biology. In this paper, we focus on a measure for robustness in metabolic networks, namely, the impact degree, and propose an approximation method to predict the probability distribution of impact degrees from metabolic network structures using the theory of branching process. We demonstrate the relevance of this method by testing it on real world metabolic networks. Although the approximation method possesses a few limitations, it may be a powerful tool for evaluating metabolic robustness.
A Selected Core Microbiome Drives the Early Stages of Three Popular Italian Cheese Manufactures
Venue: PloS one
Year: 2014

Mozzarella (M) Grana Padano (GP) and Parmigiano Reggiano (PR) are three of the most important traditional Italian cheeses. In the three cheese manufactures the initial fermentation is carried out by adding natural whey cultures (NWCs) according to a back slopping procedure. In this study, NWCs and the corresponding curds from M, GP and PR manufactures were analyzed by culture independent pyrosequencing of the amplified V1 V3 regions of the 16S rRNA gene, in order to provide insights into the microbiota involved in the curd acidification. Moreover, culture independent high throughput sequencing of lacS gene amplicons was carried out to evaluate the biodiversity occurring within the S. thermophilus species. Beta diversity analysis showed a species based differentiation between GP PR and M manufactures indicating differences between the preparations. Nevertheless, all the samples shared a naturally selected core microbiome, that is involved in the curd acidification. Type level variability within S. thermophilus species was also found and twenty eight lacS gene sequence types were identified. Although lacS gene did not prove variable enough within S. thermophilus species to be used for quantitative biotype monitoring, the possibility of using non rRNA targets for quantitative biotype identification in food was highlighted.
Description of a new species of the genus Zodarion Walckenaer, 1826 (Araneae, Zodariidae) from Algeria.
Venue: Zootaxa
Year: 2021

A new species of the genus Zodarion Walckenaer, 1826 is described based on material collected in different regions in Algeria. Morphological, diagnostic characters and illustrations of the genitalia of both sexes are presented. The samples reveal different phenological activities for males and females, and that the species occurs in agro ecosystem habitats.
PLANT DISEASE DETECTION AND CLASSIFICATION USING IMAGE PROCESSING AND ARTIFICIAL NEURAL NETWORKS
Year: 2018

Agricultural productivity is something on which Indian economy highly depends. This is one of the reasons that disease detection in plants plays an important role in agricultural field, as having disease in plants is quite natural. If proper care is not taken in this area then it causes serious effects on plants and due to which respective product quality, quantity or productivity is deteriorated. Detection of plant disease through some automatic technique is beneficial as it reduces a large work of monitoring in big farms of crops, and at very early stage itself it detects the symptoms of diseases i.e. when they appear on plant leaves .Visually identifying plant diseases is inefficient, difficult, time consuming, requires expertise in plant diseases and continuous monitoring which might be expensive in large farms. Therefore; a fast, automatic and accurate method to detect plant disease is of great importance. Hence, image processing technique is employed for the detection of plant diseases. The implementation of these technologies will lead to improved productivity.
Haemodynamic management of patients with left ventricular assist devices using echocardiography: the essentials
Venue: European heart journal cardiovascular Imaging
Year: 2019

Mechanical circulatory support with continuous flow left ventricular assist devices (LVADs) has emerged as a viable treatment modality for patients with advanced heart failure. LVAD support results in unique haemodynamic and echocardiographic alterations that must be understood to provide optimal care for these patients. In this review, we propose essential echocardiographic and haemodynamic elements for the assessment of optimal LVAD function based on the literature and the use of simulation software. A key element of LVAD physiology remains the interaction between an unloaded left ventricle and a loaded right ventricle. The echocardiographic assessment and treatment of the pathophysiology of the right sided part of the heart remains critical to maintaining optimal LVAD support.
Menge: A Modular Framework for Simulating Crowd Movement
Year: 2016

We present Menge, a cross platform, extensible, modular framework for simulating pedestrian movement in a crowd. Menge's architecture is inspired by an implicit decomposition of the problem of simulating crowds into component subproblems. These subproblems can typically be solved in many ways; different combinations of subproblem solutions yield crowd simulators with likewise varying properties. Menge creates abstractions for those subproblems and provides a plug in architecture so that a novel simulator can be dynamically configured by connecting built in and bespoke implementations of solutions to the various subproblems. Use of this type of framework could facilitate crowd simulation research, evaluation, and applications by reducing the cost of entering the domain, facilitating collaboration, and making comparisons between algorithms simpler. We show how the Menge framework is compatible with many prior models and algorithms used in crowd simulation and illustrate its flexibility via a varied set of scenarios and applications.
Extending FreeSurfer to estimate sulcal morphology
Year: 2018

While it is well established that cortical morphology differs in relation to a variety of inter individual factors, it is often characterized using estimates of volume, thickness, surface area, or gyrification. Here I developed a computational approach for estimating sulcal width and depth that relies on cortical surface reconstructions output by FreeSurfer. While other approaches for estimating sulcal morphology exist, studies often are require the use of multiple brain morphology programs that have been shown to differ in their approaches to localize sulcal landmarks, yielding morphological estimates based on inconsistent boundaries. To demonstrate the approach, sulcal morphology was estimated in three large sample of adults across the lifespan, in relation to aging. A fourth sample is additionally used to estimate test retest reliability of the approach. This toolbox is now made freely available as supplemental to this paper: https:/cmadan.github.io/calcSulc/