nils-herrmann/clean_scirepeval huggingface dataset:
Hierarchical Co Attention for Visual Question Answering

A number of recent works have proposed attention models for Visual Question Answering (VQA) that generate spatial maps highlighting image regions relevant to answering the question. In this paper, we argue that in addition to modeling "where to look" or visual attention, it is equally important to model "what words to listen to" or question attention. We present a novel co attention model for VQA that jointly reasons about image and question attention. In addition, our model reasons about the question and consequently the image via the co attention mechanism in a hierarchical fashion via a novel 1 dimensional convolution neural networks (CNN) model. Our final model outperforms all reported methods, improving the state of the art on the VQA dataset from 60.4% to 62.1% and from 61.6% to 65.4% on the COCO QA dataset.
Transdiagnostic Treatment of Borderline Personality Disorder and Comorbid Disorders: A Clinical Replication Series.
Venue: Journal of personality disorders

Borderline personality disorder (BPD) is a severe, difficult to treat psychiatric condition that represents a large proportion of treatment seeking individuals. BPD is characterized by high rates of co occurrence with depressive and anxiety disorders, and recently articulated conceptualizations of this comorbidity suggest that these disorders may result from common temperamental vulnerabilities and functional maintenance factors. The Unified Protocol for the Transdiagnostic Treatment of Emotional Disorders (UP) was developed to address these shared features relevant across frequently co occurring disorders. The purpose of the present study was to explore the preliminary efficacy of the UP for treatment of BPD with comorbid depressive and/or anxiety disorders in a clinical replication series consisting of five cases. For the majority of cases, the UP resulted in clinically significantly decreases in BPD, anxiety, and depressive symptoms, as well as increases in emotion regulation skills.
Population Attributable and Preventable Fractions: Cancer Risk Factor Surveillance, and Cancer Policy Projection
Venue: Current Epidemiology Reports

The proportions of new cancer cases and deaths that are caused by exposure to risk factors and that could be prevented are key statistics for public health policy and planning. This paper summarizes the methodologies for estimating, challenges in the analysis of, and utility of, population attributable and preventable fractions for cancers caused by major risk factors such as tobacco smoking, dietary factors, high body fat, physical inactivity, alcohol consumption, infectious agents, occupational exposure, air pollution, sun exposure, and insufficient breastfeeding. For population attributable and preventable fractions, evidence of a causal relationship between a risk factor and cancer, outcome (such as incidence and mortality) exposure distribution, relative risk, theoretical minimum risk, and counterfactual scenarios need to be clearly defined and congruent. Despite limitations of the methodology and the data used for estimations, the population attributable and preventable fractions are a useful tool for public health policy and planning.
MICE "Future for Business Tourism"

MICE industry is one of the fastest growing segments within the tourism industry generating millions in revenues for cities and countries across the globe. Since tourism ranks amongst the biggest economic sectors worldwide, enterprises in the travel industry carry an important place for business related travel. The prospects for the MICE industry are looking very bright as the changing trends are clearly indicating that this sector is making a steady comeback as the world economy has started picking up. With the economy improving, there is once again a renewed demand for exhibitions, meetings and events to showcase latest products or for brainstorming sessions or simply for attracting clients. Countries are promoting themselves as MICE venues to attract event organizers. The aim of the paper is highlight the importance of MICE and to look at the future prospects of this industry in India.
Linear extension operators between spaces of Lipschitz maps and optimal transport

Motivated by the notion of K {K\hskip 0.284528pt} gentle partition of unity introduced in  and the notion of K {K\kern 0.284528pt} Lipschitz retract studied in [S. I. Ohta, Extending Lipschitz and Holder maps between metric spaces, Positivity 13 (2009) no. 2, 407 425] we study a weaker notion related to the Kantorovich Rubinstein transport distance that we call K {K\kern 0.284528pt} random projection. We show that K {K\kern 0.284528pt} random projections can still be used to provide linear extension operators for Lipschitz maps. We also prove that the existence of these random projections is necessary and sufficient for the existence of weak continuous operators. Finally, we use this notion to characterize the metric spaces X d (X,d) such that the free space F X \mathcal{F}(X) has the bounded approximation propriety.
The mixed Lipschitz space and its dual for tree metrics

This paper develops a theory of harmonic analysis on spaces with tree metrics, extending previous work in this direction by Gavish, Nadler and Coifman (2010)  and Gavish and Coifman (2011, 2012)   We show how a natural system of martingales and martingale differences induced by a partition tree leads to simple and effective characterizations of the Lipschitz norm and its dual for functions on a single tree metric space. The restrictions we place on the tree metrics are far more general than those considered in previous work. As the dual norm is equal to the Earth Mover's Distance (EMD) between two probability distributions, we recover a simple formula for EMD with respect to tree distances presented by Charikar (2002)  We also consider the situation where an arbitrary metric is approximated by the average of a family of dominating tree metrics. We show that the Lipschitz norm and its dual for the tree metrics can be combined to yield an approximation to the corresponding norms for the underlying metric. The main contributions of this paper, however, are the generalizations of the aforementioned results to the setting of the product of two or more tree metric spaces. For functions on a product space, the notion of regularity we consider is not the Lipschitz condition, but rather the mixed Lipschitz condition that controls the size of a function's mixed difference quotient. This condition is extremely natural for datasets that can be described as a product of metric spaces, such as word document databases. We develop effective formulas for norms equivalent to the mixed Lipschitz norm and its dual, and extend our results on combining pairs of trees.
Opportunities for enhanced lean construction management using Internet of Things standards

Traditionally, production control on construction sites has been challenging, and still remains challenging. The ad hoc production control methods that are usually used, most of which are informal, foster uncertainty that prevents smooth production flow. Lean construction methods such as the Last Planner System have partially tackled this problem by involving site teams into the decision making process and having them report back to the production management system. However, such systems have relatively long "lookahead" planning cycles to respond to the dynamic production requirements of construction, where daily, if not hourly control is needed. New solutions have been proposed such as VisiLean, KanBIM, etc. but again these types of construction management systems require the proximity and availability of computer devices to workers. Through this paper, the authors investigate how the communication framework underlying such construction management systems can be further improved so as to fully or partially automate various communication functions across the construction project lifecycle (e.g. to enable lean and close to real time reporting of production control information) To this end, the present paper provides evidences of how the Internet of Things (IoT) and related standards can contribute to such an improvement. The paper then provides first insights through various construction scenarios into how the proposed communication framework can be beneficial for various actors and core business perspectives, from lean construction management to the management of the entire building lifecycle.
The application of case based reasoning in construction management research: An overview

Case based reasoning (CBR) has been widely adopted in construction management (CM) research due to the similar mind sets of CBR and CM problem solving. However, to date, there has been no systematic review of CBR applications in previous CM studies, raising the question of what is the current status quo of CBR applications in CM research? By using the method of content analysis, this study provides a comprehensive literature review of CM CBR articles published between 1996 and January 2015. It is found that the popularity of CBR applications in CM research is increasing, especially after 2006, with a majority emanating from South Korea. In addition, 17 CBR application fields are identified, with the primary research interests focusing on construction cost estimation, construction tendering, bidding and procurement, and environment and sustainability management. Issues in previous CBR model developments are also identified, mainly related to model hypothesis testing, reuse of case outcomes, selection of model development methods, use of derivational analogy and automated implementation, together with future research suggestions and directions. This study helps provide CM academics and practitioners with a more comprehensive understanding of the development of CBR applications and implications for future studies.
Tacit and explicit knowledge in construction management

In construction, better practice has been sought through the employment of knowledge management. Interest in tacit knowledge has grown due to its importance for raising performance at all organizational levels. Aspects of the limits which tacit knowledge places on knowledge management approaches in construction are considered with the focus being upon broad knowledge management categories rather than the details of particular methods. The distinction between knowing how and knowing that coupled with examination of whether the main mode of knowing is tacit or explicit is used to analyse the relationship between tacit and explicit knowledge in construction. There are significant general theoretical difficulties with incorporating tacit knowledge into the objectivist knowledge management approaches which predominate in construction particularly since methods for converting tacit to explicit knowledge are problematic. Improving performance requires appreciating the limitations of objectivist and practice based knowledge management within the context of construction projects as the consideration of performance management measures illustrates.
Relationship between Admission GRE Scores and Graduation GPA Scores of Construction Management Graduate Students

Graduate admission committees in some construction management graduate educational programs in the United States may sometimes require students to take and submit their GRE scores as part of the admission requirements. This is because they tend to believe that the GRE scores could predict the academic performance and success of students in graduate school. This study assessed the predictive ability of admission GRE scores on cumulative GPA scores at graduation of construction management graduate students. The hypothesis was that students who scored high in GRE at the time of admission would attain higher cumulative GPAs at graduation. The independent variables were GRE verbal score, GRE quantitative score, and total GRE score while the dependent variable was the GPA score. SPSS v21 and SAS v9.3 statistical analysis tools facilitated the analysis of the data sourced from three construction management graduate programs in the United States. The results showed weak predictive indices where GRE quantitative score was the better predictor of graduation GPA. Thus, the hypothesis of higher GPAs being associated with higher GRE scores was weakly supported. It was recommended that construction management graduate programs should re evaluate requiring GRE scores as part of their admission criteria.
Cellulose nanofibils as coating material and its effects on paper properties

This study investigates the effects of cellulose nanofibril (CNF) coating on the physical, mechanical and barrier properties of paper. CNF is currently of limited use in wet end applications because of its low retention and inefficient application within the paper fibre network, as well as its relatively high cost. Different CNF concentrations and number of coating layers were therefore evaluated to determine the most efficient conditions for CNF coating. For this purpose, handsheets were coated on one side with 1.5 wt% or 3 wt% CNF as a single or double layer. SEM micrographs of CNF coated surfaces indicated that paper surface porosity decreased considerably with increasing CNF concentration and more coating layers. These micrographs also showed that the surface of paper coated with a double layer of 1.5 wt% CNF is more uniform and continuous compared to that of paper coated with a single layer of 3 wt% CNF. The results revealed that the air resistance, surface strength, stiffness and tensile strength were also higher when a higher CNF concentration or greater number of layers was applied, while the Cobb index and roughness were lower. Finally, it was found that a double layer of 1.5 wt% CNF resulted in better mechanical and barrier properties compared to a single layer of 3 wt% CNF, even though the total amount of applied CNF was the same.
Zwitterionic Cellulose Carbamate with Regioselective Substitution Pattern: A Coating Material Possessing Antimicrobial Activity.
Venue: Macromolecular bioscience

A polyzwitterion is synthesized by regioselective functionalization of cellulose possessing a uniform charge distribution. The positively charged ammonium group is present at position 6, while the negative charge of carboxylate is located at positions 2 and 3 of the repeating unit. The molecular structure of the biopolymer derivative is proved by NMR spectroscopy. This cellulose based zwitterion is applied to several support materials by spin coating and characterized by means of atomic force microscope, contact angle measurements, ellipsometry, and X ray photoelectron spectroscopy. The coatings possess antimicrobial activity depending on the support materials (glass, titanium, tissue culture poly(styrene) as revealed by confocal laser scanning microscopy and live/dead staining.
Preparation and application of modified carboxymethyl cellulose Si/polyacrylate protective coating material for paper relics
Venue: Chemical Papers

There are large numbers of paper cultural relics in China, the country where paper making was invented. However, the paper relics have not been adequately protected so they are at risk of ageing, damage and disappearance. In order to better protect the paper relics, modified carboxymethyl cellulose/Si/polyacrylate protective materials were prepared with acrylicresin and modified carboxymethyl cellulose which has a good affinity with the paper and modified silica, improving the mechanical strength and ability to withstand weathering. The modified CMC/Si/polyacrylate protective material was analysed using infrared spectroscopy, transmission electron microscopy, differential scanning calorimetry and other performance testing devices. The surface morphology of the paper samples was analysed using scanning electron microscopy. The protective material so prepared was evaluated by subjection to accelerated ageing (dry heat treatment) The results showed the protective material films to have good hydrophobicity, acid/alkali resistance and mechanical strength. When the content of SiO2 is 6 mass the protective material has an excellent comprehensive performance. The results of the ageing test reveal that the prepared material can effectively slow down the ageing rate. The prepared material is suited to the protection of paper cultural relics.
PAT Based Control of Fluid Bed Coating Process Using NIR Spectroscopy to Monitor the Cellulose Coating on Pharmaceutical Pellets
Venue: AAPS PharmSciTech

Current endeavor was aimed towards monitoring percent weight build up during functional coating process on drug layered pellets. Near infrared (NIR) spectroscopy is an emerging process analytical technology (PAT) tool which was employed here within quality by design (QbD) framework. Samples were withdrawn after spraying every 15 Kg cellulosic coating material during Wurster coating process of drug loaded pellets. NIR spectra of these samples were acquired using cup spinner assembly of Thermoscientific Antaris II, followed by multivariate analysis using partial least squares (PLS) calibration model. PLS model was built by selecting various absorption regions of NIR spectra for Ethyl cellulose, drug and correlating the absorption values with actual percent weight build up determined by HPLC. The spectral regions of 8971.04 to 8250.77 cm 1, 7515.24 to 7108.33 cm 1, and 5257.00 to 5098.87 cm 1 were found to be specific to cellulose, where as the spectral region of 6004.45 to 5844.14 cm 1was found to be specific to drug. The final model gave superb correlation co efficient value of 0.9994 for calibration and 0.9984 for validation with low root mean square of error (RMSE) values of 0.147 for calibration and 0.371 for validation using 6 factors. The developed correlation between the NIR spectra and cellulose content is useful in precise at line prediction of functional coat value and can be used for monitoring the Wurster coating process.
Democratic Business Ethics: Volkswagen's Emissions Scandal and the Disruption of Corporate Sovereignty

There is an established body of politically informed scholarly work that offers a sustained critique of how corporate business ethics is a form of organizing that acts as a subterfuge to facilitate the expansion of corporate sovereignty. This paper contributes to that work by using its critique as the basis for theorizing an alternative form of ethics for corporations. Using the case of the 2015 Volkswagen emissions scandal as an illustrative example, the paper theorizes an ethics that locates corporations in the democratic sphere so as to defy their professed ability to organize ethics in a self sufficient and autonomous manner. The Volkswagen scandal shows how established organizational practices of corporate business ethics are no barrier to, and can even serve to enable, the rampant pursuit of business self interest through well orchestrated and large scale conspiracies involving lying, cheating, fraud and lawlessness. The case also shows how society, represented by individuals and institutions, is able to effectively resist such corporate malfeasance. The 'democratic business ethics' that this epitomizes is one where civil society holds corporations to account for their actions, and in so doing disrupts corporate sovereignty. This ethics finds practical purchase in forms of dissent that redirect power away from centres of organized wealth and capital, returning it to its democratically rightful place with the people, with society.
The evolution of business ethics research in the realm of tourism and hospitality: A bibliometric analysis

This paper aims to illustrate how business ethics research is progressing in the tourism and hospitality (T/H) industries and suggest a research agenda.  This study applies bibliometric analysis to articles related to business ethics topics in the T/H fields published between 1995 and 2014 in six, nine and five leading hospitality tourism and business ethics oriented journals, respectively.  This study provides a broad view on business ethics research in the T/H fields based on leading authors, institutions, themes and methods used over the past two decades.  This study assesses the progress of business ethics research in the hospitality and tourism fields. Only articles published in select, prominent Social Sciences Citation Index journals were analyzed.  This analysis focuses on published articles related to business ethics in the T/H fields. As such, it facilitates researchers, academic scholars and professionals in contributing to the field more effectively and advancing scientific progress in the literature. It aids practitioners by evaluating the extent to which scholars have investigated key issues in the field.  This study is the first to utilize bibliometric analysis to assess business ethics research focusing on T/H activities published in leading tourism, hospitality and business ethics journals.
Wind speed forecasting for wind farms: A method based on support vector regression

In this paper, a hybrid methodology based on Support Vector Regression for wind speed forecasting is proposed. Using the autoregressive model called Time Delay Coordinates, feature selection is performed by the Phase Space Reconstruction procedure. Then, a Support Vector Regression model is trained using univariate wind speed time series. Parameters of Support Vector Regression are tuned by a genetic algorithm. The proposed method is compared against the persistence model, and autoregressive models (AR, ARMA, and ARIMA) tuned by Akaike's Information Criterion and Ordinary Least Squares method. The stationary transformation of time series is also evaluated for the proposed method. Using historical wind speed data from the Mexican Wind Energy Technology Center (CERTE) located at La Ventosa, Oaxaca, Mexico, the accuracy of the proposed forecasting method is evaluated for a whole range of short termforecasting horizons (from 1 to 24 h ahead) Results show that, forecasts made with our method are more accurate for medium (5 23 h ahead) short term WSF and WPF than those made with persistence and autoregressive models.
Time series analytics using sliding window metaheuristic optimization based machine learning system for identifying building energy consumption patterns

Smart grids are a promising solution to the rapidly growing power demand because they can considerably increase building energy efficiency. This study developed a novel time series sliding window metaheuristic optimization based machine learning system for predicting real time building energy consumption data collected by a smart grid. The proposed system integrates a seasonal autoregressive integrated moving average (SARIMA) model and metaheuristic firefly algorithm based least squares support vector regression (MetaFA LSSVR) model. Specifically, the proposed system fits the SARIMA model to linear data components in the first stage, and the MetaFA LSSVR model captures nonlinear data components in the second stage. Real time data retrieved from an experimental smart grid installed in a building were used to evaluate the efficacy and effectiveness of the proposed system. A k week sliding window approach is proposed for employing historical data as input for the novel time series forecasting system. The prediction system yielded high and reliable accuracy rates in 1 day ahead predictions of building energy consumption, with a total error rate of 1.181% and mean absolute error of 0.026kWh. Notably, the system demonstrates an improved accuracy rate in the range of 36.8 113.2% relative to those of the linear forecasting model (i.e. SARIMA) and nonlinear forecasting models (i.e. LSSVR and MetaFA LSSVR) Therefore, end users can further apply the forecasted information to enhance efficiency of energy usage in their buildings, especially during peak times. In particular, the system can potentially be scaled up for using big data framework to predict building energy consumption.