Miracle-dz/UniFAR-FTUs huggingface dataset:
Editorial - Case studies of BIM in use

The use of information-rich parametric modeling 3D CAD models is increasing in the AEC industry. With this special issue we want to collect and share the benefits and challenges of using Building Information Modelling (BIM) for stakeholders in the building process, i.e. owners, architects, contractors, suppliers and others. Case studies of BIM applications are currently being presented in conferences and workshops worldwide. An example of such an initiative is the International Alliance of Interoperability initiated Building Smart forum for the industry and governments to identify, test, review, recommend and implement smart ways to deliver quality buildings and services to the facility owners using BIM technology. Another example is the annual award by the American Institute of Architects for projects that have used integrated and interoperable building information models.
Red Light Variation an Effective Alternative to Regulate Biomass and Lipid Profiles in Phaeodactylum tricornutum

Marine water diatom Phaeodactylum tricornutum is a photosynthetic organism that is known to respond to the changing light environment and adapt to different temperatures to prevent photoinhibition and maintain its metabolic functions. The objective of the present study was to test whether light shift variations in different growth phases impact the growth and lipid metabolism of P. tricornutum. Thus, we investigated R exposure in different growth phases to find the most effective light shift condition. The results showed that substituting white light (W) by red light (R) under autotrophic conditions, a condition called red shift (RS), increased biomass and lipid content compared to levels found under continuous W or R exposure alone. We observed an increase by 2-fold biomass and 2.3-fold lipid content in RS as compared to W. No significant change was observed in the morphology of lipid droplets, but the fatty acid (FA) composition was altered. Specifically, polyunsaturated FAs were increased, whereas monounsaturated FAs decreased in P. tricornutum grown in RS compared to W control. Therefore, we propose that a light shift during the beginning of the stationary phase is a low-cost cultivation strategy to boost the total biomass and lipids in P. tricornutum.
The Power of SQL Lambda Functions

This work demonstrates a wide range of applications that use lambda expressions in SQL. Such injected code snippets form a useful technique required by data mining algorithms to overcome the inflexibility of the SQL language, as the language is limited to predefined aggregations only. Following the ’move computation to the data’ paradigm, we extend SQL lambda functions—also known from common programming languages—for machinelearning tasks. As machine-learning relies mostly on gradient descent and tensor data types, we use lambda expressions for clustering and graph-mining algorithms as well as to formulate loss functions and label data. To underline the flexibility gained in SQL, this work demonstrates a main memory database system with integrated lambda expressions accessible through table functions in SQL. By reusing SQL and performing data mining and machinelearning tasks faster than can dedicated tools, this demonstration aims at convincing data scientists of the capabilities of database systems for computational tasks.
Fragmentation genetics of tropical tree species in an agro-forest landscape

Tropical trees often display long distance pollen dispersal, even in highly fragmented landscapes. Understanding how patterns of spatial isolation influence pollen dispersal and interact with background patterns of fine scale spatial genetic structure is critical for evaluating the genetic consequences of habitat fragmentation. In the endangered tropical timber tree Dysoxylum malabaricum (Meliaceae) we apply eleven microsatellite markers with paternity and parentage analysis to directly estimate historic gene flow and contemporary pollen dispersal across a large area (216 km2) in a highly fragmented agro-forest landscape. A comparison of genetic diversity and genetic structure in adult and juvenile life stages indicates an increase of differentiation and fine-scale spatial genetic structure (FSGS) over time. Paternity analysis and parentage analysis demonstrate high genetic connectivity across the landscape by pollen dispersal. A comparison between mother trees in forest patches with low and high densities of adult trees shows that the frequency of short distance mating increases, as does average kinship among mates in low density stands. This indicates that there are potentially negative genetic consequences of low population density associated with forest fragmentation. Single isolated trees, in contrast, frequently receive heterogeneous pollen from distances exceeding five kilometres. We discuss the processes leading to the observed patterns of pollen dispersal and the implications of this for conservation management of D. malabaricum and tropical trees more generally.
ERK2 mini-fragment binding

We present a novel crystallographic screening methodology (MiniFrags) that employs high-concentration aqueous soaks with a chemically diverse and ultra-low-molecular-weight library (heavy atom count 5–7) to identify ligand-binding hot and warm spots on proteins. We propose that MiniFrag screening represents a highly effective method for guiding optimisation of fragment-derived lead compounds or chemical tools and that the high screening hit rates reflect enhanced sampling of chemical space.
Responsible gambling staff training in land-based venues: a systematic review

ABSTRACT Multiple jurisdictions legislate responsible gambling staff training for providers of land-based gambling products or include it within the industry codes of conduct. Current training programs appear to focus on basic compliance with regulatory requirements. Although programs contain problem gambling information, staff are required to respond only when approached by individuals seeking assistance. A systematic review following PRISMA guidelines and preregistration protocols was undertaken to evaluate existing evidence of staff training program effectiveness and to assess the quality of the selected studies. 1,306 articles were identifiedbased gambling venues characterized by face-to-face contact with gambling customers. Results showed several methodological weaknesses in the studies which precluded any substantive conclusions regarding the effectiveness of training programs in reducing gambling-related fell short in providing practical skills necessary to deal with difficult situations. These findings imply that staff training programs should incorporate practical skill development for the proactive management of individuals exhibiting behavioral indicators of problem gambling Multiple jurisdictions legislate responsible gambling staff training for providers of land-based gambling products or include it within the industry codes of conduct. Current training programs appear to focus on basic compliance with regulatory requirements. Although programs contain problem gambling information, staff are required to respond only when approached by individuals seeking assistance. A systematic review following PRISMA guidelines and preregistration protocols was undertaken to evaluate existing evidence of staff training program effectiveness and to assess the quality of the selected studies. 1,306 articles were identified. 22 met the inclusion criteria of staff training programs in land-based gambling venues characterized by face-to-face contact with gambling customers. Results showed several methodological weaknesses in the studies which precluded any substantive conclusions regarding the effectiveness of training programs in reducing gambling-related harm. The findings did suggest that training programs provided some benefit to staff members overall and are reflected in the positive influence on staff confidence in assisting individuals showing signs of harm. However, programs fell short in providing practical skills necessary to deal with difficult situations. These findings imply that staff training programs should incorporate practical skill development for the management of individuals exhibiting behavioral indicators of problem gambling.
Just a small bunch of flowers: the botanical knowledge of students and the positive effects of courses in plant identification at German universities

Background In the light of the ongoing loss of species the knowledge about and the ability to identify species becomes increasingly important for effective monitoring and conservation measures. Learning about identifying biodiversity is a central task for future biologists and biology teachers and universities play an important role in educating future experts and multipliers. It builds one basis for conservation literacy. Methods We analyzed undergraduate students’ prior knowledge on plant species, identification and their knowledge gain from introductory plant identification courses at eight German universities. Using the Visual Classification Method—a combination of a presentation and standardized questionnaires—we evaluated the learning success of more than 500 students regarding (a) ‘declarative species knowledge’ of plant species names and (b) ‘taxonomic concept knowledge’, which is seen as knowledge on a higher level of complexity. From comparison of paired pre- and post-tests we calculated the individual knowledge gain. Using Linear Mixed Effects Models (LMMs) we analyzed effects of knowledge levels, learner-specific resources and learning environment on the knowledge gain. Results We found that university course instructors have to start teaching at an almost zero level with respect to undergraduates’ prior knowledge: on average 2.6 of 32 common plant species were known. Overall, the introductory courses resulted in a significant but weak knowledge gain. We detected a higher knowledge gain in ‘taxonomic concept knowledge’ than in ‘declarative species knowledge’. We showed that the learning success was influenced by learner-specific resources, such as prior knowledge or aspects of motivation towards the subject matter, and by learning environment such as teaching methodology. Discussion We discuss didactical demands and aspects of teaching methodologies that could facilitate learning the complex task of plant identification in university courses. Plant identification should be taught and supervised by experienced, highly motivated course instructors with profound expertise and outstanding didactical skills. In order to qualify future generations of biologists, biology teachers, or conservationists universities should aim at and encourage high-quality teaching.
Ofertas de forragem para novilhas nelore suplementadas no período de seca e transição seca/águas - doi: 10.4025/actascianimsci.v33i1.9112

Objetivou-se avaliar o desempenho, o consumo e o coeficiente de digestibilidade na dieta de novilhas Nelore na fase de recria suplementada em pastejo durante a seca e transicao seca/aguas, sob ofertas de forragem. Foram utilizadas 84 novilhas, com aproximadamente 146 ± 21,37 kg de peso corporal (PC) medio, dividas em tres tratamentos de acordo com as ofertas de forragem de 5, 10 e 20% do peso corporal. Os animais foram suplementados com 0,25% do PC utilizado-se o delineamento inteiramente casualizado. Os dados foram submetidos a analise de variância considerando 5% de probabilidade. Houve diferenca para a disponibilidade de forragem na primeira coleta, quarta coleta e quinta coleta (p 0,05). O melhor ganho medio diario foi para a oferta de forragem de 20% (0,37 kg dia -1 ). Os animais que receberam 10 e 5% de forragem apresentaram melhores ganhos por area, de 150,56 e 216,41 kg ha -1 , nesse contexto e recomendado o uso da oferta de forragem de 5%. Forragem; ganho de peso; pastejo; recria
Innervation of wing membrane in Japanese little horseshoe bats, Rhinolophus cornutus

The spinal nerves supplying the wing membranes of Japanese little horseshoe bats, Rhinolophus cornutus were studied. The wing membrane was innervated by nerve branches of the radial, ulnar, and median nerves, showing that the membrane was formed from the skin of the forelimb rather than that of the thoracolumbar skin. The radial nerve was mainly composed of the ventral rami of C7–T1, the ulnar nerve by C8–T2, and the median nerve by C8–T1. These components of R. cornutus tended to be from a narrower range of spinal nerves and to position more caudally than those of humans. In addition, the ulnar nerve showed a distribution pattern different from that of other mammals.
A high-precision heuristic model to detect home and work locations from smart card data

ABSTRACT Smart card-automated fare collection systems now routinely record large volumes of data comprising the origins and destinations of travelers. Processing and analyzing these data open new opportunities in urban modeling and travel behavior research. This study seeks to develop an accurate framework for the study of urban mobility from smart card data by developing a heuristic primary location model to identify the home and work locations. The model uses journey counts as an indicator of usage regularity, visit-frequency to identify activity locations for regular commuters, and stay-time for the classification of work and home locations and activities. London is taken as a case study, and the model results were validated against survey data from the London Travel Demand Survey and volunteer survey. Results demonstrate that the proposed model is able to detect meaningful home and work places with high precision. This study offers a new and cost-effective approach to travel behavior and demand research.
Do people communicate about their whereabouts? Investigating the relation between user-generated text messages and Foursquare check-in places

ABSTRACT The social functionality of places (e.g. school, restaurant) partly determines human behaviors and reflects a region’s functional configuration. Semantic descriptions of places are thus valuable to a range of studies of humans and geographic spaces. Assuming their potential impacts on human verbalization behaviors, one possibility is to link the functions of places to verbal representations such as users’ postings in location-based social networks (LBSNs). In this study, we examine whether the heterogeneous user-generated text snippets found in LBSNs reliably reflect the semantic concepts attached with check-in places. We investigate Foursquare because its available categorization hierarchy provides rich a-priori semantic knowledge about its check-in places, which enables a reliable verification of the semantic concepts identified from user-generated text snippets. A latent semantic analysis is conducted on a large Foursquare check-in dataset. The results confirm that attached text messages can represent semantic concepts by demonstrating their large correspondence to the official Foursquare venue categorization. To further elaborate the representativeness of text messages, this work also performs an investigation on the textual terms to quantify their abilities of representing semantic concepts (i.e., representativeness), and another investigation on semantic concepts to quantify how well they can be represented by text messages (i.e., representability). The results shed light on featured terms with strong locational characteristics, as well as on distinctive semantic concepts with potentially strong impacts on human verbalizations.
Vector-Derived Transformation Binding: An Improved Binding Operation for Deep Symbol-Like Processing in Neural Networks

Abstract We present a new binding operation, vector-derived transformation binding (VTB), for use in vector symbolic architectures (VSA). The performance of VTB is compared to circular convolution, used in holographic reduced representations (HRRs), in terms of list and stack encoding capacity. A special focus is given to the possibility of a neural implementation by the means of the Neural Engineering Framework (NEF). While the scaling of required neural resources is slightly worse for VTB, it is found to be on par with circular convolution for list encoding and better for encoding of stacks. Furthermore, VTB influences the vector length less, which also benefits a neural implementation. Consequently, we argue that VTB is an improvement over HRRs for neurally implemented VSAs.
Design and Performance Prediction of a Dual-Band Coupled-Fed Dipole Array Antenna for PCL Systems in the VHF Band

This article proposes the design of a dual-band coupled-fed dipole antenna for passive coherent location (PCL) systems in the very high frequency (VHF) band. The proposed indirect coupled feed mechanism, which is often employed in microstrip patch antennas, is first applied to VHF band dipole elements for dual-band matching. To confirm the effectiveness of the proposed design, we fabricate the coupled-fed dipole element and measure antenna characteristics, such as the voltage standing wave ratio (VSWR) and the antenna gain. The proposed antenna element is then applied to an eight-element circular array to form the reference and surveillance beams for PCL systems. Finally, the target location is estimated by constructing amplitude-range doppler (ARD) maps for one frequency modulation (FM) and two terrain digital multimedia broadcasting (T-DMB) illuminators in the Seoul-Gyunggi urban area. The results confirm that the proposed element is suitable for dual-band PCL systems in the VHF band compared to a conventional dipole antenna.
Image shadow removal using cycle generative adversarial networks

Abstract. A shadow-removal algorithm based on cycle generative adversarial network is proposed. There are two networks in the proposed method. To increase the diversity of shadow images for improving the robustness in the shadow-removal process, the first network is used to add shadows in nonshadow images to increase the variation of training data. Then, the second network is trained for the shadow-removal task. Six different losses are calculated and combined in the loss function to increase the performance. Ablation experiments show that the resulting images suffer from some artifacts without any of the six losses in the loss function. The proposed method presents lower value of root-mean-squared error and the superior visual quality compared to the state-of-the-art image removal algorithms.
Adaptive prescribed performance servo control of an automotive electronicthrottle system with actuator constraint

To further improve the transient and steady-state performance of automotive electronic throttle position tracking, in this paper an adaptive prescribed performance servo control strategy is designed and applied to a real electronic throttle control system. In view of the possible high gain of the prescribed performance controller in practice, the actuator constraint is also considered in the controller design. The designed servo controller can ensure the transient and steady-state responses of tracking error are limited in the range prescribed by the performance function, and converge with the prescribed convergence rate and have no overshoot. The incorporated adaptive updating law can enhance the robustness of the transient and steady-state performance against uncertainty from the product tolerance, the operating conditions, and the aging of components. Both Matlab/Simulink simulation and dSPACE-based hardware-in-the-loop experimental verification show the effectiveness and applicability of the proposed control strategy.
Brain Morphometry Methods for Feature Extraction in Random Subspace Ensemble Neural Network Classification of First-Episode Schizophrenia

Abstract Machine learning (ML) is a growing field that provides tools for automatic pattern recognition. The neuroimaging community currently tries to take advantage of ML in order to develop an auxiliary diagnostic tool for schizophrenia diagnostics. In this letter, we present a classification framework based on features extracted from magnetic resonance imaging (MRI) data using two automatic whole-brain morphometry methods: voxel-based (VBM) and deformation-based morphometry (DBM). The framework employs a random subspace ensemble-based artificial neural network classifier—in particular, a multilayer perceptron (MLP). The framework was tested on data from first-episode schizophrenia patients and healthy controls. The experiments differed in terms of feature extraction methods, using VBM, DBM, and a combination of both morphometry methods. Thus, features of different types were available for model adaptation. As we expected, the combination of features increased the MLP classification accuracy up to 73.12%—an improvement of 5% versus MLP-based only on VBM or DBM features. To further verify the findings, other comparisons using support vector machines in place of MLPs were made within the framework. However, it cannot be concluded that any classifier was better than another.
Snapshot Isolation for Transactional Stream Processing

Transactional database systems and data stream management systems have been thoroughly investigated over the past decades. While both systems follow completely different data processing models, the combined concept of transactional stream processing promises to be the future data processing model. So far, however, it has not been investigated how well-known concepts found in DBMS or DSMS regarding multi-user support can be transferred to this model or how they need to be redesigned. In this paper, we propose a transaction model combining streaming and stored data as well as continuous and ad-hoc queries. Based on this, we present appropriate protocols for concurrency control of such queries guaranteeing snapshot isolation as well as for consistency of transactions comprising several shared states. In our evaluation, we show that our protocols represent a resilient and scalable solution meeting all requirements for such a model.
Analytical Model Analysis of Reflection/Transmission Characteristics of Long-Period Fiber Bragg Grating (LPFBG) by Using Coupled Mode Theory

This study presents an analytical model analysis of reflection/transmission characteristics of long-period fiber Bragg grating (LPFBG) by using coupled mode theory. Reflected signal power is deeply studied against grating length at the optimum operating signal wavelength of 1550 nm for the proposed and previous models. Reflectivity and transmission coefficient are also clarified versus operating wavelength for the previous model and proposed a model with a central wavelength of 1550 nm, Δn = 0.003 and optimum grating length of 30 mm. In the same way, the reflectivity and transmission coefficient are outlined against relative refractive grating difference step at the optimum wavelength of 1550 nm and optimum grating length of 30 mm. The optimum LPFBG can be achieved with the optimum grating length of 30 mm, operating wavelength of 1550 nm and relative refractive grating difference step of 0.3 %.