Miracle-dz/UniFAR-FTUs huggingface dataset:
Intelligent Environments

Although the physical architecture is without doubt the most striking aspect of a building, from a more technical prospective it is but one of many building architectures, some of which are hidden to the human eye. One such invisible architecture is the information technology that is integrated into a building to support knowledge-based activities and to automate building services. During the last half century there have been huge advances in the use of IT to manage and control building services moving from simple service automation through to today’s so-called intelligent environments. In this chapter I will explore the nature of intelligent environments, explaining what they are and how they work. In particular, the chapter examines the autonomy continuum and presents an architecture that allows building occupants to vary the intelligence level of a building. Finally, I report on studies, conducted in the Essex iSpace, that have explored the attitudes of building occupants to intelligent technology and use these to discuss some of the consequences for designers of intelligent environments.
Protective Effect of Synbiotic Fermented Camel Milk on Non Alcoholic Fatty Liver Disease in Rats

Non-alcoholic fatty liver disease (NAFLD) is a universal epidemic that disperses among children with different ages' and adults. The current study aimed to evaluate the protective effects of fermented camel milk on progression of non-alcoholic fatty liver disease induced by a high fat diet and high fructose water in rat. Forty-two male rats were divided into seven different groups. The first group was given a standard diet to serve as a negative control group. The second group was fed on a high fat diet and high fructose in water (HFDHFr) to induce fatty liver disease, and served as a positive control group. The remaining five groups were fed on HFDHFr in addition to oral administration of camel milk (CM), fermented camel milk (FCM) containing nonencapsulated probiotic bacteria, FCM containing microencapsulated probiotic without prebiotic, FCM containing microencapsulated probiotic and 1% ginger extract or FCM containing microencapsulated probiotic and 10% beetroot extract, respectively. After 60 days, activity of liver enzymes, insulin resistance, lipid profile (TC, TG, HDL-C, and LDL-C), inflammation markers (TNF-α and NO) and oxidative stress (MDA, GSH and GSSG) were determined in serum of all rats' groups in addition to histopathological examination of liver tissue. Results revealed that oral administration of FCM containing microencapsulated probiotics with or without plant extract lowered the concentration of serum glucose, TNF-α, NO, TC, LDL-C, TG, MDA, GSSG, and the activity of liver enzymes. Furthermore, it significantly elevated HDL-C and GSH compared to positive control group. Moreover, histopathological examination showed that the group that was given FCM containing microencapsulated probiotics with beetroot extract was the nearest to negative control group followed by the group of FCM containing microencapsulated probiotics with ginger extract. It can be concluded that different tested treatments of FCM containing microencapsulated probiotics with plant extract reduced severity of fatty liver.
RANDOMIZED SUB-SAMPLED METHODS FOR MATRIX APPROXIMATION

We introduce a family of randomized iterative algorithms to approximate matrices by sub-sampling with respect to randomized input and output subspaces. These sub-sampled algorithms have several advantages over existing sample-based Quasi-Newton algorithms: the sub-sampled algorithms use significantly less data per iteration and can be tuned (by selecting input and output dimensions) for modern hardware architectures. We establish convergence rates for the algorithms and demonstrate consistent practical performance on a wide class of test matrices. An accelerated scheme is introduced and compared numerically against existing accelerated Quasi-Newton schemes.
Explainable Agency in Intelligent Agents

Explainability of intelligent agents has gained attention in recent years with their widespread utilization in society. Most work in Explainable AI (XAI) pay little attention to the humans that interact with these models, which risks resulting in unsatisfactory explanations. Theories of explainability and the nature of explanation has been widely explored in cognitive psychology and philosophy. This thesis aims to incorporate these insights to build explainable models and interfaces that can provide better and sufficient explanations to the interacting human.
Effects of various urban land-uses on the epigeic beetle communities in Bangalore city , India

Urban landscapes harbor diverse man-made land-uses ranging from highly modified residential and industrial areas to semi-natural habitats with their associated biotic communities. Understanding the ecological patterns and processes of urban landscapes is required for the maintenance of urban biodiversity and planning in the face of expanding cities and increasing populations. Therefore, we studied the epigeic beetle communities in Bangalore city (India) to examine their responses to different types of urban land-uses. They were systematically sampled using pitfall traps from four land-use types (remnant forest patches, campuses, public parks and vacant residential plots). Different taxonomic groups within the epigeic beetle communities dominated different land-use types. In general, the alpha diversity was higher in residential plots and remnant forest patches than parks and campuses, indicating their differential responses to habitat disturbance. The overall beta diversity was high, with moderate levels of similarity between the sampled locations indicating spatial heterogeneity of urban environments. Among trophic guilds, predators and detrivores dominated residential plots and remnant forest patches, respectively. Finally, we conclude that future urban planning in Bangalore should include even small patches of natural vegetation for conservation of native flora and fauna, as these small patches can provide refuge to native biotic communities, including insects.
TMAC: A Toolbox of Modern Async-Parallel, Coordinate, Splitting, and Stochastic Methods

TMAC is a toolbox written in C++11 that implements algorithms based on a set of modern methods for large-scale optimization. It covers a variety of optimization problems, which can be both smooth and nonsmooth, convex and nonconvex, as well as constrained and unconstrained. The algorithms implemented in TMAC, such as the coordinate up- date method and operator splitting method, are scalable as they decompose a problem into simple subproblems. These algorithms can run in a multi-threaded fashion, either synchronously or asynchronously, to take advantages of all the cores available. TMAC architecture mimics how a scientist writes down an optimization algorithm. Therefore, it is easy for one to obtain a new algorithm by making simple modifications such as adding a new operator and adding a new splitting, while maintaining the multicore parallelism and other features. The package is available at this https URL
Sevoflurane induces cortical neurons apoptosis in mice via microRNA-21 / PTEN / AKT pathway

Previous reports have shown that neonatal exposure to sevoflurane is neurotoxic, causing severe cortical neurons injury, which results in learning and memory deficits. However, the precise molecular mechanism has not yet been elucidated. Recent studies have demonstrated that microRNAs (miRNAs) serve a regulatory function in many injury models including the neurons injury. The aim of present study is to investigate whether the miRNAs are involved in sevoflurane-induced cortical neurons injury. Here, we established a mice model of neurons injury through exposure to sevoflurane and performed the miRNA microarray to analyze miRNAs expression in cortical tissues. The apoptosis of cortical neurons was detected by Western Blot and terminal deoxynucleotidyl transferase dUTP nick end labelling (TUNEL) assay. Validation analysis of microRNA-21 (miR-21) level in serum and cortical tissues was performed using quantitative reverse transcription PCR (qRT-PCR). The primary mice cortical neurons isolated from neonatal mice were used as cellular model in our study. Then, the effect of miR-21 on cell viability and apoptosis was determined using the cell counting kit-8 (CCK-8), Western Blot, caspase-3 activity kit and flow cytometry, respectively. Furthermore, the target gene of miR-21 and the downstream signaling pathway were also investigated. Our results showed that sevoflurane significantly increased the numbers of TUNEL positive cells and sevoflurane exposure led to a significant elevation in levels of cleaved caspase-3, cleaved-PARP and Bax whereas marked decrease in expression of Bcl-2. Microarray data revealed that 15 miRNAs were upregulated and 25 miRNAs were downregulated, and miR-21 was one of the miRNAs being most significantly downregulated after sevoflurane treatment. Subsequently, overexpression of miR-21 protected primary mice cortical neurons injury by inhibiting sevoflurane induced apoptosis. Moreover, phosphatase and tensin homolog deleted on chromosome ten (PTEN) was proved to be a direct and functional target of miR-21 by the dual luciferase reporter assay. Furthermore, we also found that the anti-apoptotic effects of miR-21 are dependent on the activation of PTEN/Akt pathway. Our results suggest that sevoflurane induced cortical neurons injury by downregulating the expression of miR-21, which induces apoptosis through inactivating the PTEN/AKT/mTOR signaling pathway.
IN PIG BREEDING , 1 , 2007 ( 1 ) COMPOSITION OF SOW ́ S MILK AND SELECTED METABOLIC INDICES AFTER ADMINISTRATION OF PROBIOTICS

There were 2 x 16 hybrid sows included into the trial. The trial lasted from 2 weeks before farrowing until weaning at 4 weeks after farrowing. Control group was fed with standard feed for lactating sows, experimental one was fed with control feed (same as that of the control group) with 400 g BioPlus 2B/t feed which equals 1.28x10 CFU/g feed. Milk-samples of all sows were collected on the 3rd and 14th day of lactation. Milk-samples were analyzed for cholesterol, total lipids, protein, lactose and total solids. Blood samples for determination of parameters of protein and lipid profile was taken on day 1 and 15 after parturition.The experimental group had higher content of lipids and cholesterol in milk compared with control group on day 3 and also on day 14 of lactation. No significant differences between groups were observed in total solids and lactose concentration in sow’s milk. Level of cholesterol in blood of experimental group increased. As a result, significant higher cholesterol level was found in experimental group compared to control group on day 15 (P=0,038). Similar to cholesterol, total lipids in blood of experimental group was significantly higher in comparison to control group on day 15 (P=0.007). Results of our experiment indicate that the probiotics based on representatives of the genus Bacillus are able to affect the nutrient composition, e.g. total lipids and cholesterol, of sow ́s milk and consequently improve performance and average daily gains of suckling piglets.
CLASSIFICATION USING ENSEMBLES OF CONVOLUTIONAL NEURAL NETWORKS AND SPECTROGRAM DECOMPOSITIONS Technical Report

This technical report proposes ensembles of convolutional neural networks (CNNs) for the task 1 / subtask B of the DACSE 2019 challenge, with emphasis on using different spectrogram decompositions. The harmonic percussive source separation (HPSS), nearest neighbor filter (NNF), and vocal separation are applied to the monaural samples. Head-related transfer function (HRTF) is also proposed to transform monaural samples to binaural ones with augmented spatial information. Finally, 16 neural networks are trained and put together. The classification accuracy of the proposed system achieves 0.70166 on the public leaderboard.
Spatial Fading Emulator using Cavity-Excited Circular Array based on ESPAR Antenna エスパアンテナの原理を用いたラジアルキャビティ給電空間フェジングエミュレータ 朴 哲均

Field emulator using electronically steerable passive array radiator (ESPAR) antenna was proposed[1][2]. It works well as a spatial fading emulator with low cost and simple structure but only a small angular spread (AS) could be generated under specific condition. A cavity-exited circular array (CECA) based on ESPAR antenna as a spatial fading emulator therefore is proposed to overcome small AS and severe conditions[3].
Implementasi Data Mining dengan Seleksi Fitur untuk Klasifikasi Serangan pada Intrusion Detection System ( IDS )

System and network security with only firewall device installed is not enough to prevent the attack. Increased attacks has caused very large data to be analyzed , existing Internet network security system has limitations on the ability to adapt large amounts of data and types of new various attacks. The use of Intrusion Detection System (IDS) combined with a firewall installation has become a standard security system and network. Research on Intrusion Detection System (IDS) currently is still continuing to look for new good intrusion detection methods to overcome the problem of the limitations in detecting new types of attacks that increase fastly. Data mining is one of solution to solve the problem of IDS. This paper use KDDCUP'99 dataset as an initial test for analyzing data mining algorithms in attack classification. The proposed data mining algorithm is Naïve Bayes Classifier, Random Forest and SVM. Feature selection methods aimed to improve the accuracy and performance of the proposed model. Based on test results the build time of model is significantly reduced that means affected in reduction both computational size and computational complexity . Keywords-IDS; Classification; Feature selection; Data
The Risk of Successive Disasters: A Blow-by-Blow Network Vulnerability Analysis

It is often assumed that a network will not be struck by multiple disasters in a relatively short period of time; that is, a subsequent disaster will not strike within the recovery phase of a previous disaster. However, recent events have shown that combinations of disasters are not implausible. This realization calls for a new perspective on how we assess the vulnerability of our networks and shows a need for a framework to assess the vulnerability of networks to successive independent disasters. We propose a network and disaster model capable of modeling a sequence of disasters in time, while taking into account recovery operations. Based on that model, we develop both an exact and a Monte Carlo method to compute the vulnerability of a network to successive disasters. By applying our approach to real empirical disaster data, we show that the probability of a second disaster striking the network during recovery can be significant even for short repair times. Our framework is a first step towards determining the vulnerability of networks to such successive disasters.
Indoor Navigation with Model Vehicles

This paper describes a vision-based approach to miniature robot vehicle position estimation and navigation, that integrates data from on-board camera, tachometers and steering servo. The goal is to navigate a miniature vehicle on an indoor track using visual data from lane markings and dead reckoning from odometry. Then the estimated position of the miniature vehicle will be visualized in real-time and overlayed on a photo of the actual track. This will be used to evaluate how well this estimation performs and what its limitations are.
Design of edge detection algorithm for image sobel based on FPGA

With the development of embedded technology, digital image processing technology is widely used in various fields. A real-time image processing system based on FPGA is studied, which is composed of two parts, the basic algorithm of image acquisition and image processing. The QuartusII9.1 and Modelsim6.5b are used to develop the simulation environment. The structure system of the traditional line is completed by using the modular design method. Simulation results show that the system meets the real-time data acquisition and processing, and can reach 50 frames /S.
Performance research on mobile IP handoff

Mobile IP gives a simple and scalable global mobility solution. This paper studies the costs of the Mobile IP handoff that occurs when a mobile host moves between subnetworks. Experiments were carried out with Mobile IP and TCP over varying network conditions to observe the effect of handoffs on the transmission. The result shows that although Mobile IP may be appropriate for macro mobility applications, its long handoff periods make it unsuitable for micro mobility support.
Application of Geophysical Methods on Geothermal Resource Exploration : A Case of Shores of Lake Malawi Fabiano

East African Rift System (EARS) is one of the major tectonic structures of the earth where thermal energy of the interior of the earth escapes to the near surface. Estimated Geothermal energy resource potential in the EARS is more than 14,500 MW. Currently, other countries such as Malawi, Zambia, and Mozambique have not gone beyond the systematic inventory work of the resource potential exploration. There is a possibility of geophysical, geo-chemical and geological surveying methods to be used for geothermal energy investigations in Malawi. For each of these methodologies, there is a typical physical/chemical property to which the technique is sensitive to. The concept of the paper is to detail the applications of geophysics in the location of geothermal reservoir rocks with precise depth by use of seismic velocity through its electrical conductivity, magnetic or/and gravitative methods along the shores of Lake Malawi. The integration modern geophysics (Seismology) methods and its data is key in order to obtain a better understanding of the thermal rock as a whole, which is the ultimate goal of exploration in the paper. In absence of detailed drilling in Malawi, this methodology provides a perfectly general and internally consistent approach to estimating at least the upper limit of thermal rocks in terms of temperature and exact depth. Index Term-Geothermal, Thermal rock, Renewable energy, Climate change, Seismology, Malawi.
GDGT Thermometry: Lipid Tools for Reconstructing Paleotemperatures

—Microbial communities adjust the chemical structure of their cell membranes in response to environmental temperature. This enables the development of lipid-based paleothermometers such as the glycerol dialkyl glycerol tetraether (GDGT) proxies described here. Surface-sediment calibrations establish a strong empirical relationship between the relative distribution of GDGTs and temperature. GDGT proxies can be used in marine, lacustrine, and paleosol sequences as long as the organic material is not thermally mature. Thus far, GDGT proxies have been applied to sediments dating back to the middle Jurassic. Many of the key uncertainties of these proxies are related to our emerging understanding of archaeal (and for the branched GDGTs, bacterial) ecology.
Illumination-Invariant Road Detection for Monocular Camera via Patch Propagation

Road detection is one of the most crucial problems for advanced driving assistance system. In this paper, we propose an efficient illumination-invariant road area detection method via a vision-based approach using an onboard monocular camera on a vehicle. Accurately identifying road areas is challenging due to the road variability caused by illumination changes. To address this problem, we propose to use PCA based illumination invariant grayscale image computed from an input RGB image. We assume that road areas in the grayscale images have the similar texture appearance, and those areas are connected to each other. Based on these assumptions, we develop an efficient, yet robust patch based techniques for identifying seed road patches and propagating them to find the road area. We have tested our method with the KITTI benchmark, and compared the performance against three state-of-the-art techniques. We found that our method shows higher accuracy in a range of 7% to 23% points over the tested methods. Moreover, our method runs two orders of magnitude faster than other tested methods. These results are mainly achieved thanks to the usage of the illumination invariant grayscale images and our patch based approach, which is efficient and robust to various noise.
Learning to Be : Developing and Understanding Digital Competence

In the present article, a study of the use of a virtual lab in environmental science teaching is reported. The lab was used as part of regular instruction; the idea was to provide a context to learn about experimentation as a research method. The study builds on a sample of 80 of 511 students, and uses preand post-test data of students’ insights about concepts and procedures relevant for designing an experiment in environmental science. The results show that students discovered some principles of how to organize an experiment. A majority of the students appropriated some of the relevant terminology and procedures relevant for organizing experiments. However, the findings also pointed to limitations in how students were able to reason about experimentation. A major problem for the students was to understand the role an experiment plays in resolving an issue. Such insights do not emerge from using the virtual lab per se, but rather from realizing the role an experiment plays as part of a scientific study of a problem.
WP 1066 prevents retinoblastoma cell growth in vitro and in vivo

The compound WP1066, a novel small molecule STAT3 inhibitor, was originally synthesized by modifying the structure of AG490, which inhibits the activation of signal transducer and activator of transcription 3 (STAT3) by directly targeting Janus kinases (JAKs). WP1066 exhibits stronger anti-cancer activity than AG490 against malignant glioma and other cancer cells and is regarded as a promising therapeutic agent. Whether WP1066 has antitumor effect by targeting STAT3 signaling in retinoblastoma (RB) cells is unclear. In the present study, we found that WP1066 inhibited persistent STAT3 phosphorylation and induced apoptosis in human RB Y79 cell lines. In addition, WP1066 also inhibited colony formation and decreased the viability of Y79 cells. Furthermore,WP1066 suppressed RB tumor growth in a mouse model in vivo and suggested that WP1066 is a promising therapeutic drug candidate for RB by inhibiting persistent STAT3 activity.
Extending Pruning Techniques to Polymorphic Second Order ~-Calculus

Type theory and constructive logics allow us, from a proof of a formula, to extract a program that satisfies the specification expressed by this formula. Normally, programs extracted in this way are inefficient. Optimization algorithms for these programs have been developed. In this paper we show an algorithm to optimize programs represented by second order typed k-terms. We prove also that the simplified programs are observational equivalent to the original ones.
Comparing Bayesian Models for Production Efficiency

In this paper we use Markov chain Monte Carlo (MCMC) methods in order to estimate and compare stochastic production frontier models from a Bayesian perspective. We consider a number of competing models in terms of different production functions and the distribution of the asymetric error term. All MCMC simulations are done using the package JAGS (Just Another Gibbs Sampler), a clone of the classic BUGS package which works closely with the R package where all the statistical computations and graphics are done.