Miracle-dz/UniFAR-FTUs huggingface dataset:
INFRARED OCCUPANCY DETECTION TECHNOLOGIES IN BUILDING AUTOMATION-A REVIEW

Occupancy sensing, based on the use of single or sometimes on multiple technologies, is used to gather the information about human presence the building automation system requests. Infrared sensing technologies are the most widely used in occupancy detection. This paper issues occupancy detection from a building automation system, like an automatic lighting control point of view, reviews the main concepts and terminologies related to occupancy detection in buildings. Infrared occupancy sensing technologies, passive technologies such as PIR, active IR technologies, such as light barriers/gates based on the transmitter–receiver pair or transmitter-mirror pair, are discussed in detail. The main focus is on PIR sensor as it is the most common infrared technology used in motion and occupancy detection. Author’s own contribution to this subject is given in the form of a developed FEM simulation model for a typical PIR sensor. The available IR technologies and the benefits and drawbacks of each of the technologies are presented. A comparison between other occupancy sensing technologies and their combination use is presented. In order to reach higher accuracy in occupancy detection, a network of sensors spreads around a building can be used. This paper reviews some studies of occupancy detection and motion tracking based on IR sensor network technologies and the associated methods in use.
A note on the behavioural strategies used by grazing animals to alter their intake rates

A large, and often neglected, component of grazing intake is behavioural. Grazing animals may employ two strategies to increase their intake rates during grazing: increasing bite mass and decreasing handling time. These strategies are discussed in the context of fasted and non-fasted sheep grazing white ciover {Trifolium repens L. cv. Kent wild white) and p)erennial ryegrass {Lolium perenne L. cv. Parcour). It is concluded that within a forage species sheep have little flexibility for increasing their intake rates by altering their handling times but have some latitude for altering bite masses. Between forage species, differences in intake rales may be more strongly affected by the 'speciesspecific" requirement for mastication than by differences in bite masses per se. Comparisons are also made with grazing strategies of cattle.
SYMMETRIES OF HOROBALL PACKINGS RELATED TO FAMOUS 3-DIMENSIONAL HYPERBOLIC TILINGS

We discuss the symmetries of optimal packings in 3-dimensional hyperbolic space related to some famous polyhedral tilings, the Coxeter tilings with Schläfli symbols (3, 3, 6) and (4, 3, 6), as well as the Lambert-cube tilings with (p, q) = (3, 6) and (4, 4). We introduce the simplicial density function to reveal that the optimal ball packings of hyperbolic 3-space feature limiting objects called horoballs. We show that for both types of tilings there are multiple optimal packing arrangements with distinct symmetries and R. T. KOZMA AND J. SZIRMAI 2 various horoball types. Finally, we mention implications to and recent results in higher dimensional hyperbolic spaces.
Interleukin 12 Induces Stable Priming for Interferon 3' (IFN-3") Production During Differentiation of Human T Helper (Th) Cells and Transient IFN-3' Production in Established Th2 Cell Clones By Roberto Manetti,* Franca Gerosa,~ Maria Grazia Giudizi,*

Summary Interleukin 12 (IL-12) facilitates the generation of a T helper type 1 (Thl) response, with high interferon 3' (IFN-3') production, while inhibiting the generation of IL-4-producing Th2 calls in polyclonal cultures of both human and murine T cells and in vivo in the mouse. In this study, we analyzed the effect of IL-12, present during cloning of human T cells, on the cytokine profile of the clones. The culture system used allows growth of clones from virtually every T cell, and thus excludes the possibility that selection of precommitted Th cell precursors plays a role in determining characteristics of the clones. IL-12 present during the cloning procedures endowed both CD4 + and CD8 + clones with the ability to produce IFN-3" at levels severalfold higher than those observed in clones generated in the absence of IL-12. This priming was stable because the high levels of IFN-3' production were maintained when the clones were cultured in the absence of IL-12 for 11 d. The CD4 + and some of the CD8 + clones produced variable amounts of IL-4. Unlike IFN-3', IL-4 production was not significantly different in clones generated in the presence or absence of IL-12. These data suggest that IL-12 primes the done progenitors, inducing their differentiation to high IFN-3'-producing clones. The suppression of IL-4-producing cells observed in polyclonally generated T cells in vivo and in vitro in the presence of IL-12 is not observed in this donal model, suggesting that the suppression depends more on positive selection of nonIL-4-producing cells than on differentiation of individual clones. However, antigen-specific established Th2 clones that were unable to produce IFN-3, with any other inducer did produce IFN-3" at low but significant levels when stimulated with IL-12 in combination with specific antigen or insoluble anti-CD3 antibodies. This induction of IFN-3' gene expression was transient, because culture of the established clones with IL-12 for up to 1 wk did not convert them into IFN-3" producers when stimulated in the absence of IL-12. These results suggest that Th clones respond to IL-12 treatment either with a stable priming for IFN-3' production or with only a transient low level expression of the IFN-3" gene, depending on their stage of differentiation.
ON THE PRIVACY AND UTILITY PROPERTIES OF TRIPLE MATRIX-MASKING

Privacy protection is an important requirement in many statistical studies. A recently proposed data collection method, triple matrix-masking, retains exact summary statistics without exposing the raw data at any point in the process. In this paper, we provide theoretical formulation and proofs showing that a modified version of the procedure is strong collection obfuscating: no party in the data collection process is able to gain knowledge of the individual level data, even with some partially masked data information in addition to the publicly published data. This provides a theoretical foundation for the usage of such a procedure to collect masked data that allows exact statistical inference for linear models, while preserving a well-defined notion of privacy protection for each individual participant in the study. This paper fits into a line of work tackling the problem of how to create useful synthetic data without having a trustworthy data aggregator. We achieve this by splitting the trust between two parties, the “masking service provider” and the “data collector. ”
A Technology for Evaluating Relations between Response Frequency and Academic Performance Outcomes*

Since the 1970ts, proponents of Precision Teaching have cited the relation between fluent performance and various long-term academic performance outcomes. Unfortunately, clinical work has mainly been used to demonstrate the importance of high correct response frequencies in education. The current paper describes a technology currently being used in a university-based Precision Teaching center to systematically evaluate relations between response frequency and academic performance outcomes with school children. Specifically, three studies are reported which evaluate retention, endurance, and application as a function of response rate during training. Results indicate that higher rates of responding during training yielded better performance during tests of retention, endurance, and application. The studies are discussed in terms of technological innovations for educational reform and directions for future research.
Comparative Study of Breast Cancer Diagnosis using Data Mining Classification

—Breast Cancer is often suffered by women and it is an enemy to millions of women all over the world. The most important strategy to prevent death is to do early detection of the breast cancer and provide modern treatments. Along with the development of medical technology and information technology, various methods have been developed to detect the presence of breast cancer, one of which is the machine learning classification technique. In this study, performance comparison is conducted on three machine learning algorithm i.e. Multilayer Perception (MLP), Random Forest (RF) and Support Vector Machine (SVM). The dataset is sourced from Wisconsin Breast Cancer Diagnostic (WBCD). The performance comparison is evaluated by measuring accuracy, precision and recall values. Result of this study confirm that, using the k-fold cross validation technique, the MLP algorithm has the highest performance.
Riverine macroinvertebrate responses to chlorine and chlorinated sewage effluents - Acute chlorine tolerances of Baetis harrisoni (Ephemeroptera) from two rivers in KwaZulu-Natal, South Africa

Chlorine is widely used in South African sewage treatment works, and despite its volatility is likely to have a considerable impact on riverine ecosystems. This paper considers the results of acute (96 h) toxicity responses to chlorine of riverine mayfly nymphs Baetis harrisoni collected from the small, relatively uncontaminated suburban Westville Stream, KwaZulu-Natal and from the more severely impacted Umbilo River, which flows through the industrial area of Pinetown, KwaZulu-Natal, South Africa. The 96 h LC50 value for total residual chlorine for nymphs from Westville Stream was 4.1 µg/l and from the Umbilo River 4.8 µg/l. This value is well below the general effluent standard of 100 µg/l (General and Special Standards, Regulation 991, 1984), but correlates with the acute effect value guideline of 5 µg/l (South African Water Quality Guidelines, No 7. 1996).
Voice Conversion Strategies for Parallel and Nonparallel Data Cases

Voice Conversion (VC) is a technique that converts the perceived speaker identity in a given speech signal from a source speaker to a target speaker without affecting the linguistic content of the utterance [1]. The basic framework of VC first extracts speaker-specific information (namely, spectral and prosodic features (especially speaking style)) from both the source and the target speakers. Learn the mapping function between corresponding feature pairs and predict the converted features. These features are again converted back to the speech signal using VOCODER. VC broadly can be categorized into parallel (if both the speakers have spoken the same utterances) and non-parallel cases (if both the speakers have spoken different utterances from a same language or different language) (for non-parallel corpus) [2]. Even if both the speakers have spoken the same utterances, the spectral features from both the source and the target speakers need to be aligned during training due to a speaking rate variation across the speakers (i.e., interspeaker variations) and a speech rate variations within the speaker (i.e., intraspeaker variations) [3, 4]. So is the case for non-parallel VC. One of the major focuses of this thesis is to identify issues related to the alignment on the quality of converted voices [5, 6]. In addition, we also identified the impact of outliers and hence, their removal on the quality of converted voices [7, 8]. Furthermore, we also proposed convergence theorem for one of the popular alignement techniques for non-parallel VC case, namely, Iterative combination of Nearest Neighbor search step and Conversion step Alignment (INCA) algorithm and its extension in the form of dynamic INCA algorithm [9, 10]. Moreover, we also proposed to use Vocal Tract Length Normalization-based warped features for avoiding the need of alignment stage in the case of nonparallel VC [11]. Apart from this, we proposed novel Amplitude Scaling (AS)-based method for BiLinear Frequency Warping (BLFW)based mapping techniques for the VC [12]. Furthermore, novel Generative Adversarial Network (GAN)-based model with Minimum Mean Square Error (MMSE) Regularizer has also been proposed, which is used for the VC as well as NonAudible Murmur-to-WHispered SPeech (NAM2WHSP) conversion task [13]. In my thesis, issues related to the objective evaluations were also identified and novel objective measure, based on acoustic-to-articulatory inversion technique was also proposed [14].
Present status of HLA typing for haematopoietic stem cell transplantation in Lithuania

The present paper summarizes development of donor search for allot-ransplantation of haematopoietic stem cells (HSC) in Lithuania during a periodof seven years (1998–2005). This paper considers the topics of strategy and met-hods of histocompatibility typing and creating a legal and organizational frame ofthe functioning of the Lithuanian National Bone Marrow Donor Registry.
Genetic Variation of the Chinese Mudskipper, Periophthalmus cantonensis (Osbeck, 1762) (Pisces; Perciformes, Gobiidae) from Taiwan'

An average Nei's genetic identity of T= 0.996 (0.993-0.999) indicated highly homogenous protein structure. The proportion of polymorphic loci (0.95 level) varied from 0.0909 to 0.2727 with a mean of 0.1742; ex­ pected heterozygosity ranged from 0.028 to 0.065 with a mean of 0.051. The mean Fst differentiation among populations was only 0.0235. However, observed population phenotype numbers partly disagreed with Hardy-Weinberg equilibrium; this is probably due to some factors that affect the disequilibrium.
Formulation and characterization of gentamicin-loaded albumin microspheres as a potential drug carrier for the treatment of E. coli K88 infections

The aim of this study was to formulate and characterize gentamicin-loaded albumin microspheres for their potential therapeutic use in E. coli K88 infections. Based on in vitro assays, it is proposed that microspheres may serve as a carrier of gentamicin and may provide localized antibacterial activity in the treatment of porcine colibacillosis. Gentamicin-albumin microspheres (GAM) were obtained using a water/oil (W/O) emulsion followed by cross-linking with different concentrations of glutaraldehyde. Electron microscopy showed spherical particles with indentations. The average size of the GAM was 10.5-12.3 µm. At pH 7.2, the release kinetics of gentamicin from the GAM was successfully described as an initial burst defined by a first order equation. Gentamicin release was unaffected by the glutaraldehyde concentrations used but was affected by acidic conditions. The behavior of gentamicin release from the GAM was not altered by digestion with trypsin and chymotrypsin at pH 7.2. Additionally, the concentration of gentamicin released from GAM to reach antibacterial activity was similar to that of free gentamicin against E. coli K88. This work shows the potential use of GAM as therapeutic vehicles of gentamicin to counteract intestinal infections in pigs
Rapid Response Crop Maps in Data Sparse Regions

Spatial information on cropland distribution, often called cropland or crop maps, are critical inputs for a wide range of agriculture and food security analyses and decisions. However, high-resolution cropland maps are not readily available for most countries, especially in regions dominated by smallholder farming (e.g., sub-Saharan Africa). These maps are especially critical in times of crisis when decision makers need to rapidly design and enact agriculture-related policies and mitigation strategies, including providing humanitarian assistance, dispersing targeted aid, or boosting productivity for farmers. A major challenge for developing crop maps is that many regions do not have readily accessible ground truth data on croplands necessary for training and validating predictive models, and field campaigns are not feasible for collecting labels for rapid response. We present a method for rapid mapping of croplands in regions where little to no ground data is available. We present results for this method in Togo, where we delivered a high-resolution (10 m) cropland map in under 10 days to facilitate rapid response to the COVID-19 pandemic by the Togolese government. This demonstrated a successful transition of machine learning applications research to operational rapid response in a real humanitarian crisis. All maps, data, and code are publicly available to enable future research and operational systems in data-sparse regions.
VAE-KRnet and its applications to variational Bayes

In this work, we have proposed a generative model for density estimation, called VAE-KRnet, which combines the canonical variational autoencoder (VAE) with our recently developed flow-based generative model, called KRnet. VAE is used as a dimension reduction technique to capture the latent space, and KRnet is used to model the distribution of the latent variables. Using a linear model between the data and the latent variables, we show that VAE-KRnet can be more effective and robust than the canonical VAE. As an application, we apply VAE-KRnet to variational Bayes to approximate the posterior. The variational Bayes approaches are usually based on the minimization of the Kullback-Leibler (KL) divergence between the model and the posterior, which often underestimates the variance if the model capability is not sufficiently strong. However, for high-dimensional distributions, it is very challenging to construct an accurate model since extra assumptions are often needed for efficiency, e.g., the mean-field approach assumes mutual independence between dimensions. When the number of dimensions is relatively small, KRnet can be used to approximate the posterior effectively with respect to the original random variable. For high-dimensional cases, we consider VAE-KRnet to incorporate with the dimension reduction. To alleviate the underestimation of the variance, we include the maximization of the mutual information between the latent random variable and the original one when seeking an approximate distribution with respect to the KL divergence. Numerical experiments have been presented to demonstrate the effectiveness of our model.
Patterns of stable isotope signatures in willow warbler Phylloscopus trochilus feathers collected in Africa

We conducted stable isotope analyses of nitrogen and carbon on feathers obtained from willow warblers in Africa to find an explanation for a previously observed pattern of different delta N-15 and delta C-13 values across a migratory divide in central Scandinavia. A new data set confirms that north Scandinavian birds of the subspecies P. t. acredula have higher delta N-15 values than south Scandinavian birds of the subspecies P. t. trochilus. In Africa, we found significant differences for both delta N-15 and delta C-13 values among feathers collected from major geographical regions as well as between countries within regions. Isotope signatures of delta N-15 and delta C-13 in Scandinavian acredula matched well with those of willow warblers sampled in southern parts of Africa, but differed from samples obtained in East and West Africa. Isotope signatures in Scandinavian trochilus did not agree with the pattern in any of the three African regions (West, East or South). However, a more detailed analysis of the isotopic data in feathers from countries within West Africa, which is the wintering region of Swedish trochilus based on ringing recoveries, revealed a correspondence with samples from Liberia, the Ivory Coast and Nigeria. (Less)
Accelerating Reinforcement Learning Agent with EEG-based Implicit Human Feedback

Providing Reinforcement Learning (RL) agents with human feedback can dramatically improve various aspects of learning. However, previous methods require human observer to give inputs explicitly (e.g., press buttons, voice interface), burdening the human in the loop of RL agent's learning process. Further, it is sometimes difficult or impossible to obtain the explicit human advise (feedback), e.g., autonomous driving, disabled rehabilitation, etc. In this work, we investigate capturing human's intrinsic reactions as implicit (and natural) feedback through EEG in the form of error-related potentials (ErrP), providing a natural and direct way for humans to improve the RL agent learning. As such, the human intelligence can be integrated via implicit feedback with RL algorithms to accelerate the learning of RL agent. We develop three reasonably complex 2D discrete navigational games to experimentally evaluate the overall performance of the proposed work. Major contributions of our work are as follows, (i) we propose and experimentally validate the zero-shot learning of ErrPs, where the ErrPs can be learned for one game, and transferred to other unseen games, (ii) we propose a novel RL framework for integrating implicit human feedbacks via ErrPs with RL agent, improving the label efficiency and robustness to human mistakes, and (iii) compared to prior works, we scale the application of ErrPs to reasonably complex environments, and demonstrate the significance of our approach for accelerated learning through real user experiments.
No Redshift Evolution in the Broad-line-region Metallicity up to z = 7.54: Deep Near-infrared Spectroscopy of ULAS J1342+0928

We present deep (9 hr) Gemini-N/Gemini Near-InfraRed Spectrograph near-infrared spectroscopic observations of ULAS J1342+0928, a luminous quasar at z = 7.54. Various broad emission lines were detected, as well as the underlying continuum and iron forests over the rest-frame wavelength 970–2930 Å. There is a clear trend that higher-ionization emission lines show larger blueshifts with C iv exhibiting km s−1 blueshift with respect to the systematic redshift from the far-infrared [C ii] emission line. Those high-ionization lines have wide profiles with FWHM more than 10,000 km s−1. A modest blueshift of km s−1 is also seen in Mg ii, the lowest-ionization line identified in the spectrum. The updated Mg ii-based black hole mass of and the Eddington ratio of confirm that ULAS J1342+0928 is powered by a massive and actively accreting black hole. There is no significant difference in the emission-line ratios such as Si iv/C iv and Al iii/C iv when compared to lower-redshift quasars in a similar luminosity range, which suggests early metal pollution of the broad-line-region clouds. This trend also holds for the Fe ii/Mg ii line ratio, known as a cosmic clock that traces the iron enrichment in the early universe. Different iron templates and continuum fitting ranges were used to explore how the Fe ii/Mg ii measurement changes as a function of spectral modeling. Quasars at even higher redshift or at fainter luminosity range ( erg s−1) are needed to probe the sites of early metal enrichment and a corresponding change in the Fe ii/Mg ii ratio.
ANA at SemEval-2020 Task 4: MUlti-task learNIng for cOmmonsense reasoNing (UNION)

In this paper, we describe our mUlti-task learNIng for cOmmonsense reasoNing (UNION) system submitted for Task C of the SemEval2020 Task 4, which is to generate a reason explaining why a given false statement is non-sensical. However, we found in the early experiments that simple adaptations such as fine-tuning GPT2 often yield dull and non-informative generations (e.g. simple negations). In order to generate more meaningful explanations, we propose UNION, a unified end-to-end framework, to utilize several existing commonsense datasets so that it allows a model to learn more dynamics under the scope of commonsense reasoning. In order to perform model selection efficiently, accurately, and promptly, we also propose a couple of auxiliary automatic evaluation metrics so that we can extensively compare the models from different perspectives. Our submitted system not only results in a good performance in the proposed metrics but also outperforms its competitors with the highest achieved score of 2.10 for human evaluation while remaining a BLEU score of 15.7. Our code is made publicly available.