Miracle-dz/UniFAR-FTUs huggingface dataset:
Could Autodesk Revit Be Automated for Code Compliance Checking and Demonstration with A Focus on Fire Safety Regulations

Often a subject to ambiguity and interpretation, building codes and compliance with them require years of expertise to understand and to integrate into good design. Automation of code compliance through Building Information Modelling (BIM) removes the human aspect from these processes and ensures building codes are correctly adhered to. In this paper, the author reviews current code compliance systems implemented internationally and, with a focus on fire codes, compares them to the current fire certificate application in The Republic of Ireland. By conducting interviews with an Executive Fire Prevention Officer of Dublin Fire Brigade and a Fire Consultant practicing in Ireland, the author determines the process of the two professionals and attempts to automate the demonstration of compliance for 4 items from these processes. The author attempts to contain these solutions within a Revit Template File. By doing so, the solutions can be applied to any number of BIM models, demonstrating compliance for each design and, in turn, making a leaner compliance checking process for designers. By checking 4 items from the processes the author hopes to show that in theory, Revit can be automated for code compliance checking and demonstration.
Toward More Robust Graph Matching : Models and Algorithms

Graph matching refers to finding vertex correspondence among two or multiple graphs, being fundamental in many applications such as image registration, DNA alignment, and automatic software bug finding. In contrast to classic two-graph setting, recently matching multiple graphs emerge for their practical usefulness and methodological potential. Starting by a brief introduction for traditional twograph matching, we walk through the recent development of multiple graph matching methods, including details for both models and algorithms. We show how learning can be inter-played with graph matching. The hope is to prompt the up-to-date advance to readers in a concrete way. Directions for future work are also discussed.
OPTIMIZACIJE KOLONIJOM PČELA MODEL CONVERGENCE PROPERTIES OF THE CONSTRUCTIVE BEE COLONY OPTIMIZATION ALGORITHM

The Bee Colony Optimization (BCO) algorithm is a nature-inspired meta-heuristic method for dealing with hard, real-life optimization problems. It is based on the foraging habits of honeybees and was proposed by Lučić and Teodorović in 2001. Through numerous applications in transportation, location theory, scheduling and some other fields, method has evolved and underwent many transformations, modifications, even parallelization, which resulted in the increase of its efficiency. The first results of the theoretical verification of the BCO method have appeared recently. The aim of this paper is to further contribute to this topic.
Clawback Provisions

We provide a detailed analysis of 4,103 compensation clawback provisions used by S&P 1,500 firms from 2000–2013. The adoption and breadth of a clawback provision are related to the scope for executive malfeasance, compensation-related reasons to misrepresent performance; and firm governance. Executives respond to clawbacks by lowering firm risk and pursuing more conservative corporate policies, including reduced investment and R&D spending and fewer patent filings. The stock market reacts positively to the news of clawback adoption and the value increase is larger for stronger provisions and when the market can expect a more sizable reduction in firm risk. Overall, clawbacks appear to serve as more than simple window-dressing and appear to be tailored to fit firm and managerial characteristics.
Treatment Beliefs 1 Parenting Cognitions and Treatment Beliefs as Predictors of Experience Using Behavioral Parenting Strategies in Families of Children with Attention-Deficit / Hyperactivity Disorder

We tested a model of mothers’ parenting efficacy and attributions for child ADHD behaviors as predictors of experiences with behavioral treatment. The model proposed that mothers’ beliefs regarding the acceptability and effectiveness of behavioral strategies would intervene between mothers’ cognitions about parenting and child behavior and their treatment experiences. Participants were 101 mothers of 5 to 10 year old children (82% male) with ADHD. Mothers reported their parenting efficacy and attributions for child behavior, and then received a single session of treatment teaching two behavior management strategies. Then, mothers reported their beliefs regarding the acceptability and effectiveness of these strategies. A follow-up phone interview 1 week later assessed mothers’ experiences in using the behavioral strategies. The overall model fit the data. Attributions of child ADHD behavior as more pervasive, enduring, and within the child’s control were related to seeing behavioral treatment as more acceptable, but neither attributions nor treatment acceptability predicted treatment experience. However, mothers with higher parenting efficacy viewed the behavioral strategies as more likely to be effective, and this pathway significantly predicted positive treatment experience. Implications for understanding the variables that contribute to parental decision-making and treatment participation for childhood ADHD are considered.
Bots and Gender Profiling using Character Bigrams Notebook for PAN at CLEF 2019

This paper describes our approach to tackle the Author Profiling task at PAN 2019. The objective is to distinguish between bot and human users and for human users it is also necessary to detect their gender. We are given only Twitter messages in two languages (Spanish and English). Our preprocessing stage includes data cleaning as well as the extraction of features using character bi-grams. We experimented with several feature representations and machine learning algorithms ( Support Vector Machines (SVM) from libSVM). For both languages we use the same methods of feature extraction and classification.
Automatic Generation Of LoD 1 City Models And Building Segmentation From Single Aerial Orthographic Images Using Conditional Generative Adversarial Networks

3D city models play an important role in multiple applications, but creating them still requires effort using various possible techniques. This paper proposes a new machinelearning-based framework for generating 3D city models. With the help of conditional Generative Adversarial Networks and single orthographic images, segmentation and height estimations of buildings are achieved. The height information per pixel and the building coordinates were generalized using a histogram for heights and the DouglasPeucker algorithm. The framework was evaluated by using variations of the same dataset (for the city of Berlin) to show possible differences due to changes in the image size and representation of the heights. The evaluation reveals that it is possible to generate block models with a mean absolute height error of 5.53m per building, a mean absolute height error for the whole raster of 1.32m, and a Jaccard Index of 0.55 for the segmentation. While the proposed framework for generating LoD1 city models does not attain the accuracy of previous techniques, our work represents a step towards successfully using machine learning for the automatic generation of city models and building segmentation.
Global Scenario of Canine Parvovirus Mutants: Epidemiology, Diagnostics and Immunoprophylactic Agents

Canine parvovirus 2 (CPV-2) is one of the most important enteropathogen of dogs emerged in 1978 and manifested by two forms namely gastroenteritis and myocarditis. It is characterized by depression, loss of appetite, vomiting and leukopenia. CPV-2 is probably evolved from a very closely related virus in cats, feline panleukopenia virus (FPLV) or a closely related carnivore parvovirus. It caused high morbidity of 100% and low mortality of 10% in adult dogs and 91% in pups. Over the years a number of variants namely CPV-2a, CPV-2b, CPV-2c, New CPV-2a, New CPV-2b and Asp300 (2a/2b) have been reported from different countries in the world with varying degree of pathogenic potential. Although CPV-2 differ from FPV by 6 amino acids in the VP2 protein, subsequent variants differ from CPV-2 only in one or two places. Further, CPV-2 affects only dogs, new variants expanded their host range to cat as well. There are a number of different serological and molecular tests (PCR, nested PCR, SYBR Green based real time PCR, Taqman based real time PCR, Minor grove binding assay based PCR) available for prompt, specific and accurate diagnosis of the disease. Some molecular tests not only detect the CPV-2 but also identify the variant of CPV-2 involved in disease outbreak. Further, both live attenuated and inactivated vaccines are available to control the disease in animals. Besides, new generation vaccines namely recombinant vaccine, peptide vaccine and DNA vaccine have been developed for control of the disease in canines effectively and efficiently. However, new generation vaccines have not been issued license to be used in the field condition. Again, the presence of maternal antibodies often interferes with the active immunization with live attenuated vaccine and there always exists a window of susceptibility in spite of following proper immunization regimen. Lastly, judicious use of the vaccines in pet dogs, stray dogs and wild canids keeping in mind the new variants of the CPV-2 along with the proper sanitation and disinfection practices must be implemented for the successful control the disease.
A Method to Detect Malware Based on Behavior Using Formal Concept Analysis

Malware threats have recently become a real concern. To solve this problem, we propose a new approach in this paper. The method analyzes the apps’ used history and constructs a Formal Concept Lattice based on the permissions which the app is used. The concepts of Formal concept Lattice are used to be compared with the permissions which a new application required before installed. So we can find an optimal concept and identify malwares and inform users about the risk of apps which are about to be installed. An experiment illustrates that our method can effectively identify malicious apps and to protect the user's information security.
Indirect search for color octet electron at PWFA-LC

Indirect search for color octet electron at Plasma Wake Field AcceleratorLinear Collider (PWFA-LC) has been considered. It is shown that color octet electron masses can be probed up to 17.7 TeV at PWFA-LC with three years integrated luminosity. In addition, the compositeness scale can be probed up to 38.5 TeV.
Deep proteomic analysis of Dnmt1 mutant/hypomorphic colorectal cancer cells reveals dys-regulation of Epithelial-Mesenchymal Transition and subcellular re-localization of Beta-Catenin

Background DNA methyltransferase I is the primary eukaryotic DNA methyltransferase engaged in maintenance of CpG DNA methylation patterns across the genome. Alteration of CpG methylation patterns and levels is a frequent and significant occurrence across many cancers, and targeted inhibition of Dnmt1 has become an approach of choice for select malignancies. There has been significant interest both in the methyltransferase activity as well as methylation-independent functions of Dnmt1. A previously generated hypomorphic allele of Dnmt1 in HCT116 colorectal cancer cells has become an important tool for understanding Dnmt1 function and how CpG methylation patterns are modulated across the genome. Colorectal cancer cells with the Dnmt1 hypomorphic allele carry a homozygous deletion of exons 3 to 5 of Dnmt1, resulting in greatly reduced Dnmt1 protein expression whilst still exhibiting a limited functional activity and methyltransferase ability. Although this cell model of reduced Dnmt1 levels and function have been used to study the downstream effects on the epigenome and transcriptome, the broader effects of the Dnmt1 hypomorph on the proteome and wider cell signalling are largely unknown. Results In this study, we used quantitative proteomic analysis of nuclear-enriched samples of HCT116 Dnmt1 hypomorph cells to identify signalling pathways and processes dysregulated in the hypomorph cells as compared to wild-type HCT116 cells. Unexpectedly, we observed a clear signature of increased expression of Epithelial-to-Mesenchymal (EMT) in Dnmt1 hypomorph cells. We also observed reduced expression and sub-cellular re-localization of Beta-Catenin in Dnmt1 hypomorph cells. Expression of wild-type Dnmt1 in hypomorph cells or knock-down of wild-type Dnmt1 did not recapitulate or rescue the observed protein profiles in Dnmt1 hypomorph cells suggesting that hypomorphic Dnmt1 causes changes not solely attributable Conclusions In summary we present the first comprehensive proteomic analysis of the widely studied Dnmt1 hypomorph colorectal cancer cells and identify redistribution of Dnmt1 and its interaction partner Beta-Catenin as well as the dysregulation of EMT related processes and signalling pathways related to the development of a cancer stem cell phenotype.
Relating Word Embedding Gender Biases to Gender Gaps: A Cross-Cultural Analysis

Modern models for common NLP tasks often employ machine learning techniques and train on journalistic, social media, or other culturally-derived text. These have recently been scrutinized for racial and gender biases, rooting from inherent bias in their training text. These biases are often sub-optimal and recent work poses methods to rectify them; however, these biases may shed light on actual racial or gender gaps in the culture(s) that produced the training text, thereby helping us understand cultural context through big data. This paper presents an approach for quantifying gender bias in word embeddings, and then using them to characterize statistical gender gaps in education, politics, economics, and health. We validate these metrics on 2018 Twitter data spanning 51 U.S. regions and 99 countries. We correlate state and country word embedding biases with 18 international and 5 U.S.-based statistical gender gaps, characterizing regularities and predictive strength.
LIPID NANOSTRUCTURES AS OPTIMAL CARRIERS FOR ENCAPSULATION OF BIOACTIVE COMPOUNDS

The paper aims at obtaining lipid nanostructures based on basil oil to be used in the encapsulation process of some bioactive compounds. In order to assure a high degree of homogenization, two adequate techniques have been successively applied: high shear homogenization (HSH) and high pressure homogenization (HPH). The synthesis procedure has been optimized by following four consecutive stages in which a series of relevant parameters have been monitored: working pressure and number of HPH cycles, HSH time exposure, concentration of surfactant, induction period for pre-emulsion formation, and proportion of lipids within lipid mixture. The lipid nanostructures thus obtained will be further used as efficient carriers to encapsulate various ingredients with antifungal action.
Online balanced truncation for linear time-varying systems using continuously differentiable interpolation on Grassmann manifold

We consider model order reduction of linear time-varying systems on a finite time interval using balanced truncation. A standard way to perform MOR is to first numerically integrate the associated pair of differential Lyapunov equations for the two gramians, then compute projection matrices using the square root method, and finally formulate the reduced systems at each time instant of a chosen grid. This approach is well-known for delivering good approximation, but rather costly in computation and storage requirement. Furthermore, if one needs to compute the reduced system for any new time instant that is not included in the chosen grid, the mentioned procedure must be performed again without explicitly making use of the already computed data. For dealing with such a situation, we propose to store the projection matrices corresponding to a simplified sparse time grid and to use them to recover the projection subspaces at any other time instant via curve interpolation on the Grassmann manifold. By doing this, we can avoid the repetition of solving the differential Lyapunov equations which is the most expensive step in the procedure and therefore, as shown in a numerical example, accelerate the online reduction process.
Horizontal linear vibrating actuator to reduce smart phone thickness

Smart phones have numerous features and large display. In result, the smart phone is less portable than before due to its large size. In order to improve the portability of a smart phone, the thickness of the smart phone should be reduced. This is one of the important issues in today's smart phone hardware industry. The vibrating actuator is the thickest component in a smart phone. A thinner electric vibration actuator could make smart phones slimmer. Currently, a vertical linear vibrating actuator is used in smart phones, and it vibrates in the thickness direction of the phone. This imposes a restriction on the sliming of smart phones. Also, a vertical actuator has a thickness of approximately 3.0 to 3.6 mm. We develop a horizontal linear vibrating actuator that can be used to reduce the thickness of a smart phone. Mathematical vibration modeling is used to calculate the magnetic force, and a finite element analysis using the commercial electromagnetic analysis software MAXWELL is performed to determine the specifications of a permanent magnet and electromagnetic coil. The guide spring is designed by modal and harmonic response analysis using ANSYS. A horizontal linear vibrating actuator is designed, and a prototype is manufactured for use in experiments. Its thickness is reduced by 30 % compared to a vertical linear vibrating actuator. In addition, the actuator can vibrate with an acceleration of up to 2.10 Gravity (G), which represents an improvement of at least 40 % compared to a vertical linear vibrating actuator.
PaGeS : Design and Compilations of a Bilingual Parallel Corpus German Spanish Compilation of bilingual corpora for linguistic research

In this paper it will reflect on the specific needs of the linguistic research regarding the construction of bilingual parallel corpora and primarily on the conclusions to be drawn for their design, compilation and domains. A research group of the university in Santiago is currently building a bilingual parallel corpus (Corpus PaGeS) consisting of original texts in German and Spanish together with their translations into the other language, as well as German and Spanish translations from a third language. This corpus was originally intended for linguistic research purposes, specifically, the analysis of the expression of the spatial relations. Initially a brief survey of some significant existing related corpora is performed, and their limitations for linguistic studies are outlined. The different issues that were taken into account for the design of the corpus will be explained, such as type of texts, domains, regional language variety or quality and direction of translations. After describing the manual preparation process of the texts to make the documents suitable for further processing it is explained the manual and automatic annotation procedure: the metadata, and the automatically linguistic annotation. Then the process of sentence alignment and the manual review of the alignment are described and finally the next steps of future work are outlined
Understanding Expectations of a Robot ' s Identity Through Multi-User Interactions

We conducted two experiments looking at how to read user expectations of a robot's identity within multi-user environments. Multi-user environments are unpredictable and fast-paced, which can become a challenge for roboticists to interpret. However, they also present a rich landscape of data, and we propose methodologies to retrieve user reactions to the robot through sensor data. We also emphasize the necessity of using the results from these methodologies to define a robot's identity based on user expectations. In Experiment 1, we found that sensor data taken from a handshake with the robot can be used to find differences in the views of different demographic groups towards interaction with our robot. In Experiment 2, we expand the subject pool and reaffirm the usefulness of sensor data in multiuser environments, while also using questionnaire data to create an identity for our robot. I.2. 9 [Robotics]: Operator interfaces – methods to research user expectations and intuitive interaction, multi-user environments, robot identity, biofeedback
Properties and Peculiarities of Ceramic Coatings on the Al 2 O 3 and ZrSiO 4 Basis Formed by a New Multi-chamber Gas-dynamic Accelerator

Al2O3/xZrSiO4 (where x = 0, 3, 25 wt.%) composite coatings were deposited onto corrosion-resistant steel substrates by a new multi-chamber gas-dynamic accelerator of mixed the cheap raw materials (alumina and zircon). X-Ray diffraction (XRD) was used to characterize the phase composition and scanning electron microscopy (SEM) examined the morphology of the polished cross-sections. The coatings were investigated using Vickers microhardness tester at a test load 200 g. The wear behaviour of coatings was carried out by the ball-on-disk tests. Microstructural investigation showed that the coatings were well-adhered onto corrosion-resistant steel substrate. The results show that the Al2O3/xZrSiO4 coatings consist of both fully melted regions and partially melted regions, and the fully melted region has a lamellar-like structure. The effect of ZrSiO4 addition on the properties of coatings was investigated in terms of microhardness and wear behavior. It was found that ZrSiO4 improved the microhardness and reduced wear rate of the coatings.
WORKING PAPER SERIES International Ecotourism and Economic Development in Central America and the Caribbean

Using annual data for the period 1995–2012 for seven Central American and Caribbean countries, six different open-economy growth models that allow for internatio nal (eco-) tourism are estimated using panel-data estimation techniques. The main result of the investigation is that not only international tourist arrivals per capita have a highly significant impact on real GDP per capita but also that five different sustainability indicators interacted with internat ional tourism have a positive impact on economic development in addition to international tourism . Furthermore, quantile regression shows that lower and medium income deciles in particular benefit mo st fr m international (eco-) tourism. The results are complemented by very similar estimation res ults for a set of 12 Central American and Caribbean countries using two sustainability indicato rs only, thus corroborating the validity of the specification. In addition, control variables are also g enerally significant and feature the algebraic signs as expected from economic theory.
Pay-gap pays : The effect of CEO ’ s industry tournament on corporate social responsibility

We examine the impact of a CEO’s pay compare to other CEOs in the same industry (termed as industry tournament incentive) on firm-level corporate social responsibility (CSR) engagements. We find that firms with high CEO industry tournament incentive (CITI) involve in fewer CSR activities. This result adds to the CITI literature in that CEOs shift resources to more visible outcomes as valued by the external labour market to win industry tournament. Accordingly, our results also demonstrate that firms with high CITI invest more in firm specific projects, improve cost efficiency, and increase firm productivity and performance when their investment in CSR decreases. We establish a causal link between CITI and CSR by designing a quasi-natural experiment using a change in the enforceability of the non-competition agreement in three states as an exogenous shock to CITI. Further, we show that the relation between CITI and CSR weakens in industries with more internally hired CEOs. Finally, we observe that the relation strengthens with high local density of the firms in the same industry, high managerial ability, overconfident CEOs, strong corporate governance, and with high CEO demand.