nils-herrmann/clean_scirepeval huggingface dataset:
Insulation materials for the building sector: A review and comparative analysis

The energy consumption of a building is strongly dependent on the characteristics of its envelope. The thermal performance of external walls represents a key factor to increase the energy efficiency of the construction sector and to reduce greenhouse gases emissions. Thermal insulation is undoubtedly one of the best ways to reduce the energy consumption due to both winter heating and summer cooling. Insulation materials play an important role in this scenario since the selection of the correct material, its thickness and its position, allow to obtain good indoor thermal comfort conditions and adequate energy savings. Thermal properties are extremely important, but they are not the only ones to be considered when designing a building envelope: sound insulation, resistance to fire, water vapor permeability and impact on the environment and on human health need to be carefully assessed too.
Topic Modeling of Short Texts: A Pseudo Document View
Venue: KDD

Recent years have witnessed the unprecedented growth of online social media, which empower short texts as the prevalent format for information of Internet. Given the nature of sparsity, however, short text topic modeling remains a critical yet much watched challenge in both academy and industry. Rich research efforts have been put on building different types of probabilistic topic models for short texts, among which the self aggregation methods without using auxiliary information become an emerging solution for providing informative cross text word co occurrences. However, models along this line are still rarely seen, and the representative one Self Aggregation Topic Model (SATM) is prone to overfitting and computationally expensive. In light of this, in this paper, we propose a novel probabilistic model called Pseudo document based Topic Model (PTM) for short text topic modeling. PTM introduces the concept of pseudo document to implicitly aggregate short texts against data sparsity. By modeling the topic distributions of latent pseudo documents rather than short texts, PTM is expected to gain excellent performance in both accuracy and efficiency. A Sparsity enhanced PTM (SPTM for short) is also proposed by applying Spike and Slab prior, with the purpose of eliminating undesired correlations between pseudo documents and latent topics. Extensive experiments on various real world data sets with state of the art baselines demonstrate the high quality of topics learned by PTM and its robustness with reduced training samples. It is also interesting to show that i) SPTM gains a clear edge over PTM when the number of pseudo documents is relatively small, and ii) the constraint that a short text belongs to only one pseudo document is critically important for the success of PTM. We finally take an in depth semantic analysis to unveil directly the fabulous function of pseudo documents in finding cross text word co occurrences for topic modeling.
Topic Modeling for Short Texts with Co occurrence Frequency Based Expansion
Venue: 2016 5th Brazilian Conference on Intelligent Systems (BRACIS)

Short texts are everywhere on the Web, including messages in social media, status messages, etc, and extracting semantically meaningful topics from these collections is an important and difficult task. Topic modeling methods, such as Latent Dirichlet Allocation, were designed for this purpose. However, discovering high quality topics in short text collections is a challenging task. This is because most topic modeling methods rely on information coming from the word co occurrence distribution in the collection to extract topics. As in short text this information is scarce, topic modeling methods have difficulties in this scenario, and different strategies to tackle this problem have been proposed in the literature. In this direction, this paper introduces a method for topic modeling of short texts that creates pseudo documents representations from the original documents. The method is simple, effective, and considers word co occurrence to expand documents, which can be given as input to any topic modeling algorithm. Experiments were run in four datasets and compared against state of the art methods for extracting topics from short text. Results of coherence, NPMI and clustering metrics showed to be statistically significantly better than the baselines in the majority of cases.
Oral and Maxillofacial Imaging.
Venue: Dental clinics of North America

This article provides the reader with the knowledge and skills of identification and diagnostic interpretative skills using planar images, tomographic images, CBCT, MDCT, pertinent MR images, as well as bone scans and PET images. The goal is to provide sufficient in depth knowledge of the technique, anatomy, and radiographic identifiers for the diagnosis of local and systemic pathoses. The information will train the reader to be an advocate of selection criteria as well as a follower of the "Image Gently" campaign and philosophy supported by the organized dentistry in the United States, especially in Diagnostic Radiology.
Learning to Embody Leadership Through Mindfulness and Somatics Practice

The Problem Given the unpredictable nature of organizational life, leadership development programs that rely primarily on cognitive processing and critical reflection are no longer sufficient. What is required is an integrated pedagogy that enables individuals to access and embody a "way of being," an aligned presence and purpose that spans all contexts so that the individual and leader are not separate entities but rather a fully cohesive self. To develop this capacity, reputable organizations are experimenting with holistic learning methodologies, including mindfulness and somatics practices. However, these methodologies have yet to be fully grounded in adult learning and leadership best practices, empirical research, mind body principles, and leadership performance. The Solution Through a critical review of relevant theory, practice, and empirical research, this article conceptualizes a constructive developmental learning methodology, which integrates mindfulness and somatics practices that transform a leader's relationship with behavior from the automatic to the consciously chosen realm. The article presents a practical model of embodied leadership where individuals learn ways to deepen awareness to include both the mind and body as an interdependent system to remain open, grounded, and engaged in a way that builds resilience, and resourcefulness, and improves relationships in complex environments. The Stakeholders Human resource development professionals, executive coaches, and aspiring leaders seek a holistic and practical leadership development approach, which is conceptually and empirically linked to leadership and organizational performance.
Efficient Zero Knowledge Contingent Payments in Cryptocurrencies Without Scripts
Venue: ESORICS

One of the most promising innovations offered by the cryptographic currencies (like Bitcoin) are the so called smart contracts, which can be viewed as financial agreements between mutually distrusting participants. Their execution is enforced by the mechanics of the currency, and typically has monetary consequences for the parties. The rules of these contracts are written in the form of so called "scripts" which are pieces of code in some "scripting language" Although smart contracts are believed to have a huge potential, for the moment they are not widely used in practice. In particular, most of Bitcoin miners allow only to post standard transactions (i.e. those without the non trivial scripts) on the blockchain. As a result, it is currently very hard to create non trivial smart contracts in Bitcoin.
A robust method for face recognition and face emotion detection system using support vector machines
Venue: 2016 International Conference on Electrical, Electronics, Communication, Computer and Optimization Techniques (ICEECCOT)

This research presents framework for real time face recognition and face emotion detection system based on facial features and their actions. The key elements of Face are considered for prediction of face emotions and the user. The variations in each facial feature are used to determine the different emotions of face. Machine learning algorithms are used for recognition and classification of different classes of face emotions by training of different set of images. In this context, by implementing herein algorithms would contribute in several areas of identification, psychological researches and many real world problems. The proposed algorithm is implemented using open source computer vision (OpenCV) and Machine learning with python.
A Surveillance System Using CNN for Face Recognition with Object, Human and Face Detection

Recently, surveillance system plays an important role in solving several crimes by replacing human to watch monitors. Not only many functions are complicatedly integrated to a system but also a system is evolved to capture statistical data to extract useful information. But integrating many functions should be considered to make it have reduced processing time because a system has limited processing ability. If a system considers moving objects, it could reduce processing time because surveillance system normally has static background that is useless information. People and face detection are performed in detected objects. Detected faces are recognized using CNN(Convolutional Neural Network) The processing time of the proposed system is reduced and true rate of face recognition is 72.7% under varying distance from 2m to 5m.
Face Detection and Face Recognition in Android Mobile Applications

The quality of the smartphoneaEUR(tm)s camera enables us to capture high quality pictures at a high resolution, so we can perform different types of recognition on these images. Face detection is one of these types of recognition that is very common in our society. We use it every day on Facebook to tag friends in our pictures. It is also used in video games alongside Kinect concept, or in security to allow the access to private places only to authorized persons. These are just some examples of using facial recognition, because in modern society, detection and facial recognition tend to surround us everywhere. The aim of this article is to create an appli cation for smartphones that can recognize human faces. The main goal of this application is to grant access to certain areas or rooms only to certain authorized persons. For example, we can speak here of hospitals or educational institutions where there are rooms where only certain employees can enter. Of course, this type of application can cover a wide range of uses, such as helping people suffering from Alzheimer's to recognize the people they loved, to fill gaps persons who canaEUR(tm)t remember the names of their relatives or for example to automatically capture the face of our own children when they smile.
Efficacy and safety of 3 week response guided triple direct acting antiviral therapy for chronic hepatitis C infection: a phase 2, open label, proof of concept study.
Venue: The lancet. Gastroenterology hepatology

To shorten the course of direct acting antiviral agents for chronic hepatitis C virus (HCV) infection, we examined the antiviral efficacy and safety of 3 weeks of response guided therapy with an NS3 protease inhibitor and dual NS5A inhibitor NS5B nucleotide analogue.  In this open label, phase 2a, single centre study, Chinese patients with chronic HCV genotype 1b infection without cirrhosis were randomly allocated by a computer program to one of three treatment groups (sofosbuvir, ledipasvir, and asunaprevir; sofosbuvir, daclatasvir, and simeprevir; or sofosbuvir, daclatasvir, and asunaprevir) until six patients in each group (1:1:1) achieved an ultrarapid virological response (plasma HCV RNA <500 IU/mL by day 2, measured by COBAS TaqMan HCV test, version 2.0) Patients with an ultrarapid virological response received 3 weeks of therapy. Patients who did not achieve an ultrarapid response were switched to sofosbuvir and ledipasvir for either 8 weeks or 12 weeks. The primary endpoint was the proportion of patients with a sustained virological response at 12 weeks (SVR12) after treatment completion, analysed in the intention to treat population. All patients who achieved an ultrarapid virological response were included in the safety analysis.  Between April 5, 2015, and April 15, 2015, 26 eligible patients were recruited. 12 patients were assigned to sofosbuvir, ledipasvir, and asunaprevir; six to sofosbuvir, daclatasvir, and simeprevir; and eight to sofosbuvir, daclatasvir, and asunaprevir. Six patients in each group achieved an ultrarapid virological response (18 [69% All patients with an ultrarapid virological response who were given 3 weeks of triple therapy achieved SVR12. The most common adverse events were fatigue (one [17% of six patients receiving sofosbuvir, ledipasvir, and asunaprevir; one [17% of six patients receiving sofosbuvir, daclatasvir, and simeprevir; and two [33% of six patients receiving sofosbuvir, daclatasvir, and asunaprevir) and headache (one [17% patient in each group) No patients experienced any serious adverse events.  In this proof of concept study, all patients with chronic HCV without cirrhosis who achieved an ultrarapid virological response on triple direct acting antiviral regimens by day 2 and received 3 weeks of treatment were cured, with excellent tolerability. By shortening the duration of therapy from the currently recommended 12 weeks to 3 weeks, we could drastically reduce the cost of therapy and the rate of adverse events. Further large scale studies should be done to confirm our findings.
Environmental Issues in Central Africa

The Central African forests, the planet's second largest rainforest block, are key to global environmental health. They influence climate change through their crucial role in carbon sinking and storage, affect weather patterns across Africa, and safeguard unique species and biodiverse communities. Their fate is important to everyone, not just today's inhabitants. The forests cover seven countries, and the differing socioeconomic histories and trajectories of these nations determine divergent fates for people, trees, and wildlife across the region. We review current knowledge of how the Central African forests have been shaped by climate and human activity within the region and assess how they may evolve under future climate change, population growth, and the Anthropocene race for wealth and energy. We highlight three different environmental trajectories for the countries of the region, identify key current regional issues that have an international dimension, and highlight five new points of future concern.
Tourism in Austria: biodiversity, environmental sustainability, and growth issues
Venue: Environmental Science and Pollution Research

This study examined the long run and causal relationships between international tourism, biodiversity loss, environmental sustainability, and specific growth factors under the premises of sustainable tourism in Austria, by using a consistent time series data from 1975 to 2015. The results reveal that inbound tourism, per capita income, and population density affected the potential habitat area while population density largely affected the food production in a country. Inbound tourism and population density both deteriorate the environmental quality in a form of increasing carbon dioxide (CO2) emissions and fossil fuel energy consumption while per capita income reduces the fossil fuel energy consumption. Food exports increase per capita income, while food imports and population density both decrease economic growth. Inbound tourism and economic growth advance population density while forest area and food exports decrease the population density. The study supports growth led tourism and growth led food production in a country.
Natural Resources and Environmental Issues

Natural resources and environmental concerns have been prevalent not only in India, but in other countries of the world as well, but in most cases, India has been the major country that has experienced the depletion of natural resources and environmental degradation. In this research manuscript, main focus has been laid upon India; India is the most populous country in the world and with the impact of population explosion, there is exhaustion of natural resources and environmental degradation. The main areas that have been highlighted are rural poverty and environmental degradation, effects of disasters and natural hazards, assessing risks, impacts and opportunities from natural resources and the environment, precise insinuations for environment, sustainability and green development, greening rural development and economic growth and environmental sustainability. The issues have been taken into account and the measures also have been underscored that are essential in order to lead to preservation and sustenance of natural resources and the environment.
Military Geosciences and Desert Warfare: Past Lessons and Modern Challenges

Gallipoli continues to be a cause celebre for those seeking to assign blame for this ill fated military campaign fought against the Ottoman Empire from April to December 1915. Variously blamed are weak generals, poor planning and preparation and even inadequate topographical mapping. Intended to assist the Allied naval fleet in breaking through the Dardanelles Straits, thereby threatening the Ottoman Capital of Constantinople (and, it was hoped, forcing the Ottomans out of the war) the military campaign was certainly hastily conceived and underresourced. Commencing on 25 April 1915 as an amphibious landing, the campaign soon degenerated into a desperate struggle, as the Allies attempted in vain to break out of tightly constrained beachheads. This study investigates the role of terrain in the warfare of the ANZAC (Australian and New Zealand Army Corps) Sector, from initial landings in April, to attempted breakout in August. At ANZAC, an 'unfortunate accident of geography' brought, dry, mostly fine grained Pliocene sediments to the coast. An upland area created by the North Anatolian Fault System, the fine sediments were (and are) quickly weathered and eroded to form topographically complex gullied surfaces. This would be the almost hopeless battleground of the Australians and New Zealanders in April December 1915. With the Ottomans holding a firm grip on the ridge top, the ANZAC troops were constrained to a small, deeply dissected and mostly waterless sector of the scarp slope of the Sari Bair Plateau and ridge system. The war here would be hard fought and bloody, with geology having a major impact on its outcome; the withdrawal of ANZAC troops in December 1915.
Geothermal Energy as a Major Source of Renewable Energy Learning from Asian Neighbours

Energy is one of the fundamental necessities for economic growth, increased social equity, and an environment that allows livelihoods to thrive. Development is not possible without energy, and sustainable development is not possible without sustainable energy. Renewable Energy (RE) is a key to sustainable development and offers an opportunity to improve access to modern energy services for the impoverished segments of society, which is essential for sustainable community development. In Asia, Indonesia and the Philippines are rich in Geothermal (GT) energy. Being a renewable, sustainable, and indigenous energy resource, GT is reliable because its supply is independent of season and global energy market dynamics. Japan has a huge potential for GT and wants to expand renewable energy resources after the Fukushima Nuclear Power Accident. In the near future, GT is set to lay a major role in national energy supply in Japan. Therefore, the objective of this study is to look at various challenges and opportunities in GT energy policies of Indonesia and the Philippines to adopt them to meet Japanese needs in the future.
Success factors for Taiwanese contractors collaborating with local Chinese contractors in construction projects

Regional trade cooperation has become an important component of construction industry due to the Free Trade Agreement. This segment of the market presents many challenges for construction firms. Establishing suitable international partnering relations is an effective strategy for adapting to the additional unpredictability of international markets. This research integrates the Balanced Scorecard system with Fuzzy Analytic Hierarchy Process for comprehensive and quantitative evaluation of the relevant bilateral cooperation. Commercial cooperation across the Taiwan Strait is selected as a case study for determining the evaluating methodology. After examining data from Chinese firms, 12 factors for partner selection are identified. The factors are compared with practical conditions of worldwide and local markets to establish their viability. The methodology provides a framework for evaluating potential partners when attempting to enter foreign markets. Additionally, it identifies critical factors for developing optimal market entrance strategies, contracts, and risk management; results can also be golcally (globally and locally) tailored to promote the efficiency of international cooperation.
Metric online monocular SLAM by using a known reference
Venue: 2016 12th World Congress on Intelligent Control and Automation (WCICA)

A metric direct (feature less) online monocular SLAM algorithm is proposed, which, different from the traditional monocular SLAM algorithm, can obtain the absolute scale of the world. A calibrate object is used to calculate the relative pose of the first key frame and initialize the depth map, introducing the metric scale into the reconstruction meanwhile. Highly accurate pose estimation is achieved by direct image alignment, and the depth of image points is obtained by filtering over a large number of pixel wise small baseline stereo comparisons. With those, the environment is reconstructed in real time as pose graph of key frames with associated semi dense depth maps. Also an explicitly scale drift aware formulation is proposed to align the scale between key frames. The algorithm is tested online, and is proved to run in real time on a CPU.
Effects of an ecological conservation and restoration project in the Three River Source Region, China
Venue: Journal of Geographical Sciences

The first stage of an ecological conservation and restoration project in the Three River Source Region (TRSR) China, has been in progress for eight years. However, because the ecological effects of this project remain unknown, decision making for future project implementation is hindered. Thus, in this study, we developed an index system to evaluate the effects of the ecological restoration project, by integrating field observations, remote sensing, and process based models. Effects were assessed using trend analyses of ecosystem structures and services. Results showed positive trends in the TRSR since the beginning of the project, but not yet a return to the optima of the 1970s. Specifically, while continued degradation in grassland has been initially contained, results are still far from the desired objective, 'grassland coverage increasing by an average of 20% 40% In contrast, wetlands and water bodies have generally been restored, while the water conservation and water supply capacity of watersheds have increased. Indeed, the volume of water conservation achieved in the project meets the objective of a 1.32 billion m3 increase. The effects of ecological restoration inside project regions was more significant than outside, and, in addition to climate change projects, we concluded that the implementation of ecological conservation and restoration projects has substantially contributed to vegetation restoration. Nevertheless, the degradation of grasslands has not been fundamentally reversed, and to date the project has not prevented increasing soil erosion. In sum, the effects and challenges of this first stage project highlight the necessity of continuous and long term ecosystem conservation efforts in this region.