Miracle-dz/UniFAR-FTUs huggingface dataset:
The effects of Saccharomyces cerevisiae-enriched diet on feed usage efficiency, growth performance and survival rate in Java barb (Barbonymus gonionotus) fingerlings

The study aimed to examine the effects of Saccharomyces cerevisiae-enriched diet on feed usage efficiency, growth performance and survival rate in Java barb (Barbonymus gonionotus) fingerlings. The Java barb fingerlings had an average weight of 2.53±0.58 g head. They were collected from Muntilan, Central Java, Indonesia. Experimental method using Completely Randomized Design (CRD) was implemented. The experiment had 5 (five) treatments with four repetitions in each treatment. Those treatments were by adding various doses of S. cerevisiae for every kilogram feed as follows: 0 g (treatment A), 1.5 g (treatment B), 3.0 g (treatment C), 4.5 g (treatment D) and 6.0 g (treatment E). The parameters studied were the efficiency of feed utilization (EFU), protein digestibility (ADCp), feed conversion ratio (FCR), protein efficiency (PER), relative growth rate (RGR), survival rate (SR), and water condition was also evaluated. The findings disclosed that S. cerevisiae supplemented diet has significant effect (p < 0.05) on EFU, ADCp, PER, FCR, RGR, otherwise it has insignificant effect (p > 0.05) on SR of Java barb fingerlings. The addition of S. cerevisiae 3 g kg of feed was the best dose that produced EFU, ADCp, PER, FCR, RGR values of 72.09%, 75.42%, 3.89, 1.38, and 4.75% day respectively. The parameters of water quality were still in the viable condition to cultivate Java barb.
A Multi-Stage Framework for Building Energy Optimization: Key Factors and Prototypes

In traditional building energy optimization, usually only a certain design stage is concerned, and once the optimization model is determined, it is rarely changed. However, design is a process of continuous change and improvement. As a part of the design process, optimization should evolve throughout the whole process. The goal of this research is to find the key factors affecting the sequential building energy optimization process. According to the three factors proposed (availability, dependency and sensitivity), three multistage optimization prototypes are proposed, which group variables based on different decision factors: design phase, design objects and variables’ sensitivity. Each prototype consists of three optimization models, which are computed sequentially. In the case study for optimizing the energy consumption of an office building, the performance of these three multi-stage optimization prototypes and traditional optimization methods are compared. The results illustrate that the optimization prototype based on variables’ sensitivity is superior to others. This research only used one case study to valid the effectiveness of key factors, however, it still can guide the sequential optimization for other cases since the impact of the key factors are identical. The result of this study is expected to improve the design process, by demonstrating that the integrated design process is able to produce better designs from the energy performance point of view.
A Tendon-Driven, Preloaded, Pneumatically Actuated, Soft Robotic Gripper with a Telescopic Palm

In this paper, we present a highly adaptive, 3-fingered, soft robotic gripper with a reasonably low weight (657 g) that is capable of grasping various everyday life objects. The employed soft, pneumatically actuated robotic fingers are able to grasp objects of different shapes without damaging them, and the extendable, soft, telescopic palm is able to absorb the high impact forces of the grasped objects, protecting the on-board sensor and providing adaptation to the object shape. The gripper is tendon-driven and it employs a quick-release mechanism that allows grasping of objects at high speeds. The deformability of the soft robotic fingers and the telescopic palm is evaluated by tracking their motions with an appropriate motion capture system. The proposed gripper facilitates the execution of smooth pre-contact motions. The high working volume of each finger allows for grasping of objects with a variety of shapes and sizes. The behaviour of the gripper and its performance are experimentally validated with grasping experiments that involve a plethora of everyday life objects.
LLAMA: Efficient graph analytics using Large Multiversioned Arrays

We present LLAMA, a graph storage and analysis system that supports mutability and out-of-memory execution. LLAMA performs comparably to immutable main-memory analysis systems for graphs that fit in memory and significantly outperforms existing out-of-memory analysis systems for graphs that exceed main memory. LLAMA bases its implementation on the compressed sparse row (CSR) representation, which is a read-only representation commonly used for graph analytics. We augment this representation to support mutability and persistence using a novel implementation of multi-versioned array snapshots, making it ideal for applications that receive a steady stream of new data, but need to perform whole-graph analysis on consistent views of the data. We compare LLAMA to state-of-the-art systems on representative graph analysis workloads, showing that LLAMA scales well both out-of-memory and across parallel cores. Our evaluation shows that LLAMA's mutability introduces modest overheads of 3-18% relative to immutable CSR for in-memory execution and that it outperforms state-of-the-art out-of-memory systems in most cases, with a best case improvement of 5x on breadth-first-search.
Impact of Window Operation Behaviours on Cooling Load of High-rise Residential Buildings in Hong Kong

Energy saving can be achieved with proper natural ventilation from window opening. Window operation behaviours affect the cooling load by introducing fresh air and interacting with the operation of air conditioners. However, there is limited knowledge on how window operation behaviours influence the cooling load in highrise buildings. This paper thus examines quantitatively the impact of window operation on cooling load. The research was conducted through building simulation compared with a post-occupancy evaluation survey with a 40-storey typical high-rise residential building in Hong Kong. The results reveal up to 11% variance of cooling load among the residential flats with different window operation behaviours.
Tempering the temporary: Improving thermal safety and comfort in relief shelters

Despite guidelines encouraging climate responsive designs, post-disaster/conflict temporary shelters are frequently deployed across substantially different climates, resulting in anecdotes of unbearable interior temperatures. Therefore, in order to test their climateappropriateness, we performed thermal simulations of fourteen of the most common shelter types, testing these designs in thirteen different climate zones. Evaluating these shelters based on adaptive thermal comfort threshold temperatures proved inadequate as interior operative temperatures frequently far exceeded this threshold. Therefore, we proposed using 35°C [95°F] and 12°C [54°F] for the upper and lower health-risk temperature thresholds to evaluate thermal safety. In several cases, the simulations identified interior conditions outside these limits, which could pose health risks to occupants, especially to vulnerable populations, e.g. the elderly, sick and children. We then used thermal simulation to test improvements to temporary shelter design and synthesize new designs, and to suggest quantitative guidelines to improve thermal safety.
Insight Into Predictive models: On The Joint Use Of Clustering And Classiﬁcation By Association (CBA) On Building Time Series

Data-driven, black box machine learning models have received a lot of attention in the ﬁeld of building control. They have been used successfully to predict building behaviour given information like weather forecasts and real time sensor information. In these models, the occupant behaviour is considered to act exogenously on the building. We consider the users as active elements of the building operation control loop. To make educated control decisions they have to be informed about how the building will behave. Therefore, we propose a prediction model which explains to occupants the day-ahead building behaviour using a clustering and clas-siﬁcation by association model. We benchmark this approach to a neural network regression model and only observed a small loss of accuracy. Knowing the upcoming building behaviour, occupants can adjust their behaviour (e.g. putting on clothes) or the building systems settings (e.g. set points) accordingly. The proposed method is a promising way to decode complex regression models into readable rules, which in future may be useful in conjunction with for example voice-based virtual assistants.
On Formulation and Training of Grey-box Thermal Model for Low-rise Residential Buildings

This paper details the methodologies for creating and training grey-box thermal models for low-rise residential buildings. This paper covers different aspects of model development such as model vectorization, cost function definition and parameter estimation. Different computing strategies such as GPU accelerated calculation are also explored. This paper also briefly demonstrates the possibility of rearranging the model equation for predictive control purposes. The performance of an example grey-box model is tested against common data-driven machine learning models using a dataset of over 500 dwellings. Overall the grey-box model achieved good temperature prediction accuracy at a 4-hour forecast horizon and produced meaningful insights from the estimated parameters. The possibilities of using grey-box models for more advanced applications, such as model predictive control and remote auditing are also discussed.
Effect of Façade Thickness on Daylight Performance in a Reference Office Building

Current daylighting simulation practice often ignores the importance of façade thickness, despite its real influence on the total building performance. This research therefore aims to determine the effect of various facade thickness on daylight performance in a simulated reference office. An isolated reference office with an unglazed opening on one of the short façade was taken as case study, modelled and simulated in Radiance and Daysim, using weather data of Bandung, Indonesia. The thickness of the window façade was varied within 0.05~0.50 m, and the following daylight metrics were determined: average daylight factor, spatial daylight autonomy, spatial useful daylight illuminance, simplified daylight glare probability on selected viewpoints, and annual lighting energy demand. Results suggest that variation of façade thickness yields different impacts, which is largely significant on the average daylight factor, but is subtler on the climate-based daylight metrics and lighting energy demand.
A Machine Learning Based Framework for the Smart Healthcare Monitoring

In this paper, we propose a novel framework for the smart healthcare system, where we employ the compressed sensing (CS) and the combination of the state-of-the-art machine learning based denoiser as well as the alternating direction of method of multipliers (ADMM) structure. This integration significantly simplifies the software implementation for the lowcomplexity encoder, thanks to the modular structure of ADMM. Furthermore, we focus on detecting fall down actions from image streams. Thus, teh primary purpose of thus study is to reconstruct the image as visibly clear as possible and hence it helps the detection step at the trained classifier. For this efficient smart health monitoring framework, we employ the trained binary convolutional neural network (CNN) classifier for the fall-action classifier, because this scheme is a part of surveillance scenario. In this scenario, we deal with the fallimages, thus, we compress, transmit and reconstruct the fallimages. Experimental results demonstrate the impacts of network parameters and the significant performance gain of the proposal compared to traditional methods.
Context Sensitive Access Control in Smart Home Environments

The rise in popularity of Internet of Things (IoT) devices has opened doors for privacy and security breaches in Cyber-Physical systems like smart homes, smart vehicles, and smart grids that affect our daily existence. IoT systems are also a source of big data that gets shared via cloud. IoT systems in a smart home environment have sensitive access control issues since they are deployed in a personal space. The collected data can also be of highly personal nature. Therefore, it is critical to build access control models that govern who, under what circumstances, can access which sensed data or actuate a physical system. Traditional access control mechanisms are not expressive enough to handle such complex access control needs, warranting the incorporation of new methodologies for privacy and security. In this paper, we propose the creation of the PALS system, that builds upon existing work in attribute based access control model, captures physical context collected from sensed data (attributes), and performs dynamic reasoning over these attributes and context driven policies using Semantic Web technologies to execute access control decisions. Reasoning over user context, details of information collected by cloud service provider and device type our mechanism generates as a consequent access control decisions. Our system’s access control decisions are supplemented by another sub-system that detects intrusions into smart home systems based on both network and behavioral data. The combined approach serves to determine indicators that a smart home system is under attack, as well as limit what data breach such attacks can achieve.
Sequence analysis PPNID: a reference database and molecular identification pipeline for plant-parasitic nematodes

Motivation: The phylum Nematoda comprises the most cosmopolitan and abundant metazoans on Earth and plant-parasitic nematodes represent one of the most significant nematode groups, causing severe losses in agriculture. Practically, the demands for accurate nematode identification are high for ecological, agricultural, taxonomic and phylogenetic researches. Despite their importance, the morphological diagnosis is often a difficult task due to phenotypic plasticity and the absence of clear diagnostic characters while molecular identification is very difficult due to the problematic database and complex genetic background. Results: The present study attempts to make up for currently available databases by creating a manually-curated database including all up-to-date authentic barcoding sequences. To facilitate the laborious process associated with the interpretation and identification of a given query sequence, we developed an automatic software pipeline for rapid species identification. The incorporated alignment function facilitates the examination of mutation distribution and therefore also reveals nucleotide autapomorphies, which are important in species delimitation. The implementation of genetic distance, plot and maximum likelihood phylogeny analysis provides more powerful optimality criteria than similarity searching and facilitates species delimitation using evolutionary or phylogeny species concepts. The pipeline streamlines several functions to facilitate more precise data analyses, and the subsequent interpretation is easy and straightforward. Availability: The pipeline was written in vb.net, developed on Microsoft Visual Studio 2017 and designed to work in any Windows environment. The PPNID is distributed under the GNU General Public License (GPL). The executable file along with tutorials is available at https://github.com/xueqing4083/PPNID. Contact: xueqing4083@gmail.com; sigalhor@volcani.agri. gov.il
Identifying Genes Associated With Obesity

530 NCMJ vol. 74, no. 6 ncmedicaljournal.com Obesity is a multifactorial disease resulting from the interaction between genetic factors and lifestyle. Identification of rare genetic variations with strong effects on obesity has been useful in diagnosing and designing personalized therapy for early-onset or syndromic obesity. However, common variants identified in recent genome-wide association studies have limited clinical value.
On periodic points of Hamiltonian diffeomorphisms of $\mathbb{C} \mathrm{P}^d$ via generating functions

Inspired by the techniques of Givental and Theret, we provide a proof with generating functions of a recent result of Ginzburg-Gurel concerning the periodic points of Hamiltonian diffeomorphisms of $\mathbb{C}\text{P}^d$. For instance, we are able to prove that fixed points of pseudo-rotations are isolated as invariant sets or that a Hamiltonian diffeomorphism with a hyperbolic fixed point has infinitely many periodic points.
The Qualitative Evaluation of Urban Spacecs Application of the Holistic Landscape Approach in the Evaluation of Mashhad Shohada Square Project*

| The organization and renovation of Shohada square in Mashhad, entitled as the urban regeneration project has been in progress for the last two decades and now this project has been almost completed. However, it has failed to achieve its goals as it has witnessed the absence and involvement of people. This failure is caused by the perspective in which urban space is considered merely an object. Previous studies on urban regeneration and related projects show that the focus has just been on the functional and physical aspects of urban spaces rather than meaning. The negligence of the meaning could be the main barrier to developing a sense of place in cities. To address this gap, the current study employed a qualitative and holistic approach to evaluating the Shohada square landscape. The study included three phases: The first phase involved a detailed field study and data collection on the physical attributes, activities, and meaning of space by the researcher. In the second phase, data about Shohada square was collected from available research papers, newspapers, reports,etc.and were further analyzed. Using the content analysis the role of the square was scrutinized from the citizens’ perspectives. To this end, in-depth interviews were conducted with urban users. The findings revealed that the people’s perceptions of Shohada square fall into five categories: “city center”, “shrine threshold”, “public urban space”, “cold and soulless” and “identityless”. These factors reflect the meanings of Shohada square in the citizen’s minds. The study further drew upon the data from three phases to evaluate Shohada square through the lens of its citizens and then attempted to identify the factors threatening the role of this square. Based on the findings, the study concludes that for the revitalization of Shohada Square, three main aims and relatively policies and strategies must be taken into account namely: increasing the space vitality and its transformation to a civil space, reproducing and adding meaning and keeping the identity of space as well as the spatial reorganization of space for bringing people to space.
Modeling oil paint network formation for characterization of the molecular topology

Oil paintings and their degradation is a popular topic of research. However, cured, or polymerized, oil paint is a strongly cross-linked polymer and analysis of the structure of the network is practically impossible because of this. Insight in the structure is necessary to explain several degradation processes, such as the migration of metal ions, that are not fully understood thus far. In this study the only option to obtain structural information about the molecular topology of an oil paint network after polymerization is employed; an advanced model is developed that simulates the formation of an oil paint network. Because this challenge has not been addressed until now, we looked for the methodology to other fields of research. We employed a kind of Gillespie Monte Carlo method in combination with graph theory, a mathematical approach to describe the connectivity of a network. The monomers of an oil paint polymer are triacylglycerides (TAG-units), which contain double bonds that are responsible for the formation of the cross-links. The starting point of the model is the assumption that the reactivity of these monomers only depends on their number of double bonds, or their functionality. This is the main assumption from polymer reaction engineering and the application to oil paint is already a novelty. Oil paint monomers can have a functionality up to 9, which is considerably more than most industrial monomers. Because of this and when no other effects that influence the reactivity of the monomers are taken into account, the network becomes too dense. Therefore, we added three novel advanced routines to approach a realistic chemical system more accurately. Preferential coupling, the first effect, ensures that monomers that are close together will connect with a high probability. Secondly, intramolecular bonds within a TAG-unit are allowed. The third effect is steric hindrance and implies that shielded monomers have a low probability of connecting. The final part of this research is about the validation of the model. An experiment is designed within the research group and we wrote an algorithm to simulate this experiment. The goal of the experiment is to break the network into pieces by hydrolyzing the TAG-units. The original cross-links are retained in these fragments that can be analyzed. The experimental results can be coupled to the model to find the original network and all its structural information.
Technological Mediation in Participatory Design

This chapter engages with the idea that instead of trying to satisfy the users ’ elusive particularities, designers should offer them tools to create their own designs. From the 1970s speculations on computational techniques for user participation in design, to current design for design empowerment endeavors, technological renderings of this idea do not escape controversy around the delivery of their empowering claims. The question remains: Who designs? The “ empowered ” users? The tools and/or techniques that facilitate the process? The designer of the tools and/or techniques? I propose that technological mediation, construed here as the mode of agency distribution among users, technologies, and their designers, provides a productive viewpoint from which to analyze and critique techno-centric proposals of design for user empowerment. With this hypothesis as point of departure, I offer a parallel reading of proposals for technologically mediated user participation in design, presented in the 1971 “ Design Participation ” conference of the Design Research Society, and recent theorizations of technological mediation in science and technology studies (STS) and the philosophy of technology.
Identification of Dwelling-specific Energy Saving Benchmarks from Building Stock Models

The evaluation of benchmarks for building energy savings for a specific dwelling usually requires the generation of an individually calibrated model (ICM). The development of such models requires specialist knowledge, has time and cost implications, and may require the deployment of field devices to obtain data for the calibration process. The project reported here compared the outcomes from the simulation of detailed ICMs and corresponding (simpler) models selected from a pre-constructed collection of models comprising a building stock. The results demonstrated a reasonable agreement between benchmarks derived from ICM and stock model simulations in ~29% of cases. In the other cases, the stock model tended to over-predict the potential savings. This was attributed to lack of diversity in parameters defining heating system time-of-use and set-point temperatures. The paper discusses how a future collection of stock models can better incorporate these aspects.