nils-herrmann/clean_scirepeval huggingface dataset:
Spatiotemporal simulation of urban growth patterns using agent-based modeling : The case of Tehran

0264-2751/$ see front matter Crown Copyright 2 http://dx.doi.org/10.1016/j.cities.2013.01.005 ⇑ Corresponding author.  Berlinerstrasse Heidelberg, Germany. Tel. E-mail addresses: jamaljokar@gmail.com (J. Jokar geog.uni-heidelberg.de (M. Helbich),  Rapid urban growth is becoming a serious problem in most developing countries. Tehran, the capital of Iran, stands out as a vibrant metropolitan area, facing uncontrolled urban expansion. Public authorities and decision makers require planning criteria regarding possible spatial developments. To monitor past developmental trends and to simulate emerging spatiotemporal patterns of urban growth, this research applies a geosimulation approach that couples agent-based modeling with multicriteria analysis (MCA) for the period between 1986 and 2006. To model the major determinants controlling urban development, three agent groups are defined, namely developer agents, government agents, and resident agents. The behaviors of each agent group are identified by qualitative surveys and are considered separately using multi-criteria analysis. The interactions of the agents are then combined through overlay functions within a Geographic Information System (GIS). This analysis results in the creation of a propensity surface of growth that is able to identify the most probable sites for urban development. Subsequently, a Markov Chain Model (MCM) and a concise statistical extrapolation are used to determine the amount of probable future expansion in Tehran. For validation purposes, the model is estimated using 2011 data and then validated based on actual urban expansion. Given the accurate predictions of the Markov Chain Model, further predictions were carried out for 2016 and 2026. This simulation provides strong evidence that during the next decade planning authorities will have to cope with continuous as well as heterogeneously distributed urban growth. Both the monitoring of growth and simulation revealed significant developments in the northwestern part of Tehran, continuing toward the south along the interchange networks.
An Empirical Study on Organizational Acceptance of New Information Systems in a Commercial Bank

Intranet is a term used to describe the use of Internet technologies internally within an organization rather than externally to connect to the global Internet. While the advancement and the sophistication of the intranet is progressing tremendously, research on intranet utilization is still very scant. This paper is an attempt to provide a conceptual understanding of the intranet utilization and the corresponding antecedents and impacts through the proposed conceptual model. Based on several research frameworks built through past research, the authors attempt to propose a framework for studying intranet utilization that is based on three constructs i.e. mode of utilizations, decision support and knowledge sharing. Three groups of antecedent variables namely intranet, organizational and individual characteristics are explored to determine their possible contribution to intranet utilization. In addition, the impacts of intranet utilization are also examined in terms of task productivity, task innovation and individual sense of accomplishments. Based on the proposed model, several propositions are formulated as a basis for the study that will follow.
Evaluation of Traffic Data Obtained via GPS-Enabled Mobile Phones : the Mobile Century Field Experiment

The growing need of the driving public for accurate traffic information has spurred the deployment of large scale dedicated monitoring infrastructure systems, which mainly consist in the use of inductive loop detectors and video cameras. On-board electronic devices have been proposed as an alternative traffic sensing infrastructure, as they usually provide a cost-effective way to collect traffic data, leveraging existing communication infrastructure such as the cellular phone network. A traffic monitoring system based on GPS-enabled smartphones exploits the extensive coverage provided by the cellular network, the high accuracy in position and velocity measurements provided by GPS devices, and the existing infrastructure of the communication network. This article presents a field experiment nicknamed Mobile Century, which was conceived as a proof of concept of such a system. Mobile Century included 100 vehicles carrying a GPS-enabled Nokia N95 phone driving loops on a 10-mile stretch of I-880 near Union City, California, for 8 hours. Data were collected using virtual trip lines, which are geographical markers stored in the handset that probabilistically trigger position and speed updates when the handset crosses them. The proposed prototype system provided sufficient data for traffic monitoring purposes while managing the privacy of participants. The data obtained in the experiment were processed in real-time and successfully broadcast on the internet, demonstrating the feasibility of the proposed system for real-time traffic monitoring. Results suggest that a 2-3% penetration of cell phones in the driver population is enough to provide accurate measurements of the velocity of the traffic flow.
Software Quality - Traditional vs. Agile: an Empirical Investigation

It is well known that the software process impacts the quality of the resulting product. There are also anecdotal claims that agile processes result in higher level of quality than traditional methodologies. However, still solid evidence of this is missing. This work reports in an empirical analysis of the correlation between software process and software quality with specific reference to agile and traditional processes. More than 100 software developers and engineers from 21 countries have been surveyed with an online questionnaire. We have used the percentage of satisfied customers estimated by the software developers and engineers as the main dependent variable. The results evidence some interesting patterns: architectural styles may not have a significant influence on quality, agile methodologies might result in happier customers, larger companies and shorter projects seems to produce better products.
iCrawl: Improving the Freshness of Web Collections by Integrating Social Web and Focused Web Crawling

Researchers in the Digital Humanities and journalists need to monitor, collect and analyze fresh online content regarding current events such as the Ebola outbreak or the Ukraine crisis on demand. However, existing focused crawling approaches only consider topical aspects while ignoring temporal aspects and therefore cannot achieve thematically coherent and fresh Web collections. Especially Social Media provide a rich source of fresh content, which is not used by state-of-the-art focused crawlers. In this paper we address the issues of enabling the collection of fresh and relevant Web and Social Web content for a topic of interest through seamless integration of Web and Social Media in a novel integrated focused crawler. The crawler collects Web and Social Media content in a single system and exploits the stream of fresh Social Media content for guiding the crawler.
MoFIS: a mobile user interface for semi-automatic extraction of food product ingredient lists

The availability of food ingredient information in digital form is a major factor in modern information systems related to diet management and health issues. Although ingredient information is printed on food product labels, corresponding digital data is rarely available for the public. In this demo, we present the Mobile Food Information Scanner (MoFIS), a mobile user interface designed to enable users to semi-automatically extract ingredient lists from food product packaging.
On the Near Impossibility of Measuring the Returns to Advertising

Classical theories of the firm assume access to reliable signals to measure the causal impact of choice variables on profit. For advertising expenditure we show, using twenty-five online field experiments (representing $2.8 million) with major U.S. retailers and brokerages, that this assumption typically does not hold. Statistical evidence from the randomized trials is very weak because individual-level sales are incredibly volatile relative to the per capita cost of a campaign—a “small” impact on a noisy dependent variable can generate positive returns. A concise statistical argument shows that the required sample size for an experiment to generate sufficiently informative confidence intervals is typically in excess of ten million person-weeks. This also implies that heterogeneity bias (or model misspecification) unaccounted for by observational methods only needs to explain a tiny fraction of the variation in sales to severely bias estimates. The weak informational feedback means most firms cannot even approach profit maximization.
Fast-food habits, weight gain, and insulin resistance (the CARDIA study): 15-year prospective analysis

Fast-food consumption has increased greatly in the USA during the past three decades. However, the effect of fast food on risk of obesity and type 2 diabetes has received little attention. We aimed to investigate the association between reported fast-food habits and changes in bodyweight and insulin resistance over a 15-year period in the USA.



Participants for the CARDIA study included 3031 young (age 18-30 years in 1985-86) black and white adults who were followed up with repeated dietary assessment. We used multiple linear regression models to investigate the association of frequency of fast-food restaurant visits (fast-food frequency) at baseline and follow-up with 15-year changes in bodyweight and the homoeostasis model (HOMA) for insulin resistance.



Fast-food frequency was lowest for white women (about 1.3 times per week) compared with the other ethnic-sex groups (about twice a week). After adjustment for lifestyle factors, baseline fast-food frequency was directly associated with changes in bodyweight in both black (p=0.0050) and white people (p=0.0013). Change in fast-food frequency over 15 years was directly associated with changes in bodyweight in white individuals (p<0.0001), with a weaker association recorded in black people (p=0.1004). Changes were also directly associated with insulin resistance in both ethnic groups (p=0.0015 in black people, p<0.0001 in white people). By comparison with the average 15-year weight gain in participants with infrequent (less than once a week) fast-food restaurant use at baseline and follow-up (n=203), those with frequent (more than twice a week) visits to fast-food restaurants at baseline and follow-up (n=87) gained an extra 4.5 kg of bodyweight (p=0.0054) and had a two-fold greater increase in insulin resistance (p=0.0083).



Fast-food consumption has strong positive associations with weight gain and insulin resistance, suggesting that fast food increases the risk of obesity and type 2 diabetes.
Deep Neural Network Approximation for Custom Hardware: Where We've Been, Where We're Going

Deep neural networks have proven to be particularly eective in visual and audio recognition tasks. Existing models tend to be computationally expensive and memory intensive, however, and so methods for hardwareoriented approximation have become a hot topic. Research has shown that custom hardware-based neural network accelerators can surpass their general-purpose processor equivalents in terms of both throughput and energy eciency. Application-tailored accelerators, when co-designed with approximation-based network training methods, transform large, dense and computationally expensive networks into small, sparse and hardware-ecient alternatives, increasing the feasibility of network deployment. In this article, we provide a comprehensive evaluation of approximation methods for high-performance network inference along with in-depth discussion of their eectiveness for custom hardware implementation. We also include proposals for future research based on a thorough analysis of current trends. is article represents the rst survey providing detailed comparisons of custom hardware accelerators featuring approximation for both convolutional and recurrent neural networks, through which we hope to inspire exciting new developments in the eld.
Evolution of the cancer stem cell model.

Genetic analyses have shaped much of our understanding of cancer. However, it is becoming increasingly clear that cancer cells display features of normal tissue organization, where cancer stem cells (CSCs) can drive tumor growth. Although often considered as mutually exclusive models to describe tumor heterogeneity, we propose that the genetic and CSC models of cancer can be harmonized by considering the role of genetic diversity and nongenetic influences in contributing to tumor heterogeneity. We offer an approach to integrating CSCs and cancer genetic data that will guide the field in interpreting past observations and designing future studies.
Management of external genital warts.

Genital warts affect 1% of the sexually active U.S. population and are commonly seen in primary care. Human papillomavirus types 6 and 11 are responsible for most genital warts. Warts vary from small, flat-topped papules to large, cauliflower-like lesions on the anogenital mucosa and surrounding skin. Diagnosis is clinical, but atypical lesions should be confirmed by histology. Treatments may be applied by patients, or by a clinician in the office. Patient-applied treatments include topical imiquimod, podofilox, and sinecatechins, whereas clinician-applied treatments include podophyllin, bichloroacetic acid, and trichloroacetic acid. Surgical treatments include excision, cryotherapy, and electrosurgery. The quadrivalent human papillomavirus vaccine is active against virus subtypes that cause genital warts in men and women. Additionally, male circumcision may be effective in decreasing the transmission of human immunodeficiency virus, human papillomavirus, and herpes simplex virus.
Implementing Evidence-Based Neonatal Skin Care With Parent-Performed, Delayed Immersion Baths.

There has been a recent trend toward delaying newborn baths because of mounting evidence that delayed bathing promotes breastfeeding, decreases hypothermia, and allows for more parental involvement with newborn care. A multidisciplinary team from a maternal-new-born unit at a military medical center designed and implemented an evidence-based practice change from infant sponge baths shortly after birth to delayed immersion baths. An analysis of newborn temperature data showed that newborns who received delayed immersion baths were less likely to be hypothermic than those who received a sponge bath shortly after birth. Furthermore, parents reported that they liked participating in bathing their newborns and that they felt prepared to bathe them at home.
SafeDispatch: Securing C++ Virtual Calls from Memory Corruption Attacks

Several defenses have increased the cost of traditional, low-level attacks that corrupt control data, e.g. return addresses saved on the stack, to compromise program execution. In response, creative adversaries have begun circumventing these defenses by exploiting programming errors to manipulate pointers to virtual tables, or vtables, of C++ objects. These attacks can hijack program control flow whenever a virtual method of a corrupted object is called, potentially allowing the attacker to gain complete control of the underlying system. In this paper we present SAFEDISPATCH, a novel defense to prevent such vtable hijacking by statically analyzing C++ programs and inserting sufficient runtime checks to ensure that control flow at virtual method call sites cannot be arbitrarily influenced by an attacker. We implemented SAFEDISPATCH as a Clang++/LLVM extension, used our enhanced compiler to build a vtable-safe version of the Google Chromium browser, and measured the performance overhead of our approach on popular browser benchmark suites. By carefully crafting a handful of optimizations, we were able to reduce average runtime overhead to just 2.1%.
Recognition of persisting emotional valence from EEG using convolutional neural networks

Recently there has been considerable interest in EEG-based emotion recognition (EEG-ER), which is one of the utilization of BCI. However, it is not easy to realize the EEG-ER system which can recognize emotions with high accuracy because of the tendency for important information in EEG signals to be concealed by noises. Deep learning is the golden tool to grasp the features concealed in EEG data and enable highly accurate EEG-ER because deep neural networks (DNNs) may have higher recognition capability than humans'. The publicly available dataset named DEAP, which is for emotion analysis using EEG, was used in the experiment. The CNN and a conventional model used for comparison are evaluated by the tests according to 11-fold cross validation scheme. EEG raw data obtained from 16 electrodes without general preprocesses were used as input data. The models classify and recognize EEG signals according to the emotional states "positive" or "negative" which were caused by watching music videos. The results show that the more training data are, the much higher the accuracies of CNNs are (by over 20%). It also suggests that the increased training data need not to belong to the same person's EEG data as the test data so as to get the CNN recognizing emotions accurately. The results indicate that there are not only the considerable amount of the interpersonal difference but also commonality of EEG properties.
Integrative single-cell analysis of transcriptional and epigenetic states in the human adult brain

Detailed characterization of the cell types in the human brain requires scalable experimental approaches to examine multiple aspects of the molecular state of individual cells, as well as computational integration of the data to produce unified cell-state annotations. Here we report improved high-throughput methods for single-nucleus droplet-based sequencing (snDrop-seq) and single-cell transposome hypersensitive site sequencing (scTHS-seq). We used each method to acquire nuclear transcriptomic and DNA accessibility maps for >60,000 single cells from human adult visual cortex, frontal cortex, and cerebellum. Integration of these data revealed regulatory elements and transcription factors that underlie cell-type distinctions, providing a basis for the study of complex processes in the brain, such as genetic programs that coordinate adult remyelination. We also mapped disease-associated risk variants to specific cellular populations, which provided insights into normal and pathogenic cellular processes in the human brain. This integrative multi-omics approach permits more detailed single-cell interrogation of complex organs and tissues.
Rank conditioned rank selection filters for signal restoration

A class of nonlinear filters called rank conditioned rank selection (RCRS) filters is developed and analyzed in this paper. The RCRS filters are developed within the general framework of rank selection (RS) filters, which are filters constrained to output an order statistic from the observation set. Many previously proposed rank order based filters can be formulated as RS filters. The only difference between such filters is in the information used in deciding which order statistic to output. The information used by RCRS filters is the ranks of selected input samples, hence the name rank conditioned rank selection filters. The number of input sample ranks used is referred to as the order of the RCRS filter. The order can range from zero to the number of samples in the observation window, giving the filters valuable flexibility. Low-order filters can give good performance and are relatively simple to optimize and implement. If improved performance is demanded, the order can be increased but at the expense of filter simplicity. In this paper, many statistical and deterministic properties of the RCRS filters are presented. A procedure for optimizing over the class of RCRS filters is also presented. Finally, extensive computer simulation results that illustrate the performance of RCRS filters in comparison with other techniques in image restoration applications are presented.
Enjoyment of Mediated Fright and Violence : A Meta-Analysis

In this meta-analysis, we synthesized data from published journal articles that investigated viewers’ enjoyment of fright and violence. Given the limited research on this topic, this analysis was primarily a way of summarizing the current state of knowledge and developing directions for future research. The studies selected (a) examined frightening or violent media content; (b) used self-report measures of enjoyment or preference for such content (the dependent variable); and (c) included independent variables that were given theoretical consideration in the literature. The independent variables examined were negative affect and arousal during viewing, empathy, sensation seeking, aggressiveness, and the respondents’ gender and age. The analysis confirmed that male viewers, individuals lower in empathy, and those higher in sensation seeking and aggressiveness reported more enjoyment of fright and violence. Some support emerged for Zillmann’s (1980, 1996) model of suspense enjoyment. Overall, the results demonstrate the importance of considering how viewers interpret or appraise their reactions to fright and violence. However, the studies were so diverse in design and measurement methods that it was difficult to identify the underlying processes. Suggestions are proposed for future research that will move toward the integration of separate lines of inquiry in a unified approach to understanding entertainment. MEDIA PSYCHOLOGY, 7, 207–237
Unroofing and Curettage for the Treatment of Acute and Chronic Pilonidal Disease

Various surgical techniques are available in the management of pilonidal sinus, but controversy concerning the optimal surgical approach persists. The present study analyzes the outcome of unroofing and curettage as the primary intervention for acute and chronic pilonidal disease. A total of 297 consecutive patients presenting with chronic disease, acute abscess, or recurrent disease were treated with unroofing and curettage. The wound was left open to heal by secondary intention. Hospitalization, time required to resume daily activities and return to work, healing time, and recurrence rates were recorded. All patients were discharged within the first 24 h after operation. The median period before returning to work was 3.2 ± 1.2 days, and the mean time for wound healing was 5.4 ± 1.1 weeks. Six patients were readmitted with recurrence of the disease within the first six postoperative months. All recurrences were in patients who did not follow the wound care advice and who did not come to regular weekly appointments. Patients with recurrence underwent repeat surgery by the same technique with good results. Unroofing and curettage for pilonidal sinus disease is an easy and effective technique. The vast majority of the patients, including those with abscess as well as those with chronic disease, will heal with this simple procedure, after which even recurrences can be managed successfully with the same procedure. Relying on these results, we advocate unroofing and curettage as the procedure of choice in the management of pilonidal disease.