Miracle-dz/UniFAR-FTUs huggingface dataset:
Effect of Air Gap width on the Performance of a Stacked Square Electronic Band Gap Antenna

A Stacked Square Microstrip Antenna with shorting post is designed which is backed with electromagnetic band gap (EBG) structure on the other side of the substrate, acting as ground plane. One such EBG Microstrip Antenna is discussed with square holes in the ground plane. A reflector plane is used at a distance of 8.5mm. The air gap between this reflector and EBG ground plane is varied and its effect on the antenna parameters is studied.
Secure and Efficient Federated Transfer Learning

Machine Learning models require a vast amount of data for accurate training. In reality, most data is scattered across different organizations and cannot be easily integrated under many legal and practical constraints. Federated Transfer Learning (FTL) was introduced in [1] to improve statistical models under a data federation that allow knowledge to be shared without compromising user privacy, and enable complementary knowledge to be transferred in the network. As a result, a target-domain party can build more flexible and powerful models by leveraging rich labels from a source-domain party. However, the excessive computational overhead of the security protocol involved in this model rendered it impractical. In this work, we aim towards enhancing the efficiency and security of existing models for practical collaborative training under a data federation by incorporating Secret Sharing (SS). In literature, only the semi-honest model for Federated Transfer Learning has been considered. In this paper, we improve upon the previous solution, and also allow malicious players who can arbitrarily deviate from the protocol in our FTL model. This is much stronger than the semi-honest model where we assume that parties follow the protocol precisely. We do so using the one of the practical MPC protocol called SPDZ, thus our model can be efficiently extended to any number of parties even in the case of a dishonest majority. In addition, the models evaluated in our setting significantly outperform the previous work, in terms of both runtime and communication cost. A single iteration in our model executes in 0.8 seconds for the semi-honest case and 1.4 seconds for the malicious case for 500 samples, as compared to 35 seconds taken by the previous implementation.
Scattering diagrams of quivers with potentials and mutations

For a quiver with non-degenerate potential, we study the associated stability scattering diagram and how it changes under mutations. We show that under mutations the stability scattering diagram behaves like the cluster scattering diagram associated to the same quiver, which gives them identical cluster chamber structures. As an application, we prove if the quiver has a green-to-red sequence, these two scattering diagrams are identical and if the quiver comes from a once-punctured torus, they differ by a central wall-crossing. This verifies in those cases a conjecture of Kontsevich-Soibelman that a particular set of initial data given by a quiver determines the Donaldson-Thomas series of the quiver with a non-degenerate potential.
Global Food Consumption and Impacts on Trade Patterns

Driven primarily by per capita income growth, the composition of world agricultural trade has substantially changed in the past two decades. For developing countries, consumption and trade are shifting from basic staples towards higher value livestock products. In high-income countries, demand for foreign brands are expanding intra-industry trade in processed consumer-ready products. 1 Agricultural economists with the Market and Trade Economics Division, Economic Research Service, USDA.
Cambios en la mortalidad y en las causas de defunción en las personas con diagnóstico de infección por el VIH, 1985-2004

OBJECTIVE. To describe the changes in causes of death among persons with HIV infection. METHODS. An analysis of mortality according to cause was performed in persons diagnosed with HIV infection and residing in the province of Navarre (Spain) from 1985 to 2004. RESULTS. Among 1,649 persons diagnosed with HIV infection up to 2004, 709 (43.0%) had died. Mortality reached the maximum in 1993-1996 with 83.1 deaths per 1,000 person-years (PY). Since that time and up to 2001-2004, mortality due to AIDS decreased from 68.3 to 14.1 per 1,000 PY (p 0.0001). From 1989-1992 period to the 2001-2004 period, mortality due to drug overdose dropped from 9.2 to 3.6 per 1,000 PY (p 0.0035) and mortality due to hepatic disease rose from 1.6 to 6.6 per 1000 PY (p 0.0061), with no significant changes in all other causes. In 2001-2004, AIDS continued to be the first cause of death (44.4%) in this population, followed by hepatic disease (20.9%) and drug overdose (11.3%). In the era of potent antiretroviral therapy (1997-2004), death caused by AIDS (rate ratio 0.63; p 0.0344) and by all other causes (RR 0.59; p 0.0232) was lower among women. In addition, mortality due to causes other than AIDS was higher in persons 40 years of age and older (RR 1.77; P 0.0050) and mortality was lower in homosexual men (RR 0.22; p 0.0360). A simultaneous diagnosis of HIV infection and AIDS was associated with higher mortality by AIDS (RR, 3.39; p < 0.0001). CONCLUSIONS. AIDS continues to be the primary cause of death in HIV-infected people, and mortality due to hepatic diseases and drug overdose is high. Early diagnosis of HIV-infection would reduce the incidence of deaths due to AIDS.
Angular Momentum and Morphological Sequence of Massive Galaxies through Dark Sage

We study the present-day connection between galaxy morphology and angular momentum using the Dark Sage semi-analytic model of galaxy formation. For a given stellar mass in the range 1010–1012 M ⊙, the model predicts that galaxies with more prominent disks exhibit higher stellar disk specific angular momentum (j stellar,disk). However, when we include the gas in the disk, bulge-dominated galaxies have the highest total disk specific angular momentum (j total,disk). We attribute this to a large contribution from an extended disk of cold gas in typical bulge-dominated galaxies. Note that while the specific angular momenta (j = J/M) of these disks are large, their masses (M) are negligible. Thus, the contribution of these disks to the total angular momentum of the galaxy is small. We also find the relationship between the specific angular momentum of the dark matter (j dark matter) and morphology to be counterintuitive. Surprisingly, in this stellar mass range, not only do bulge-dominated galaxies tend to live in halos with higher j dark matter than disk-dominated galaxies, but intermediate galaxies (those with roughly equal fractions of bulge and disk mass) have the lowest j dark matter of all. Yet, when controlling for halo mass, rather than stellar mass, the relationship between j dark matter and morphology vanishes. Based on these results, we find that halo mass—rather than angular momentum—is the main driver of the predicted morphology sequence in this high mass range. In fact, in our stellar mass range, disk-dominated galaxies live in dark matter halos that are roughly one-fifth the mass of their bulge-dominated counterparts.
Neural View-Interpolation for Sparse LightField Video

We suggest representing light field (LF) videos as "one-off" neural networks (NN), i.e., a learned mapping from view-plus-time coordinates to high-resolution color values, trained on sparse views. Initially, this sounds like a bad idea for three main reasons: First, a NN LF will likely have less quality than a same-sized pixel basis representation. Second, only few training data, e.g., 9 exemplars per frame are available for sparse LF videos. Third, there is no generalization across LFs, but across view and time instead. Consequently, a network needs to be trained for each LF video. Surprisingly, these problems can turn into substantial advantages: Other than the linear pixel basis, a NN has to come up with a compact, non-linear i.e., more intelligent, explanation of color, conditioned on the sparse view and time coordinates. As observed for many NN however, this representation now is interpolatable: if the image output for sparse view coordinates is plausible, it is for all intermediate, continuous coordinates as well. Our specific network architecture involves a differentiable occlusion-aware warping step, which leads to a compact set of trainable parameters and consequently fast learning and fast execution.
Implementation of SWOT Analysis in Determining Competitive Strategy On Catering and Conference Services in Hotels

The objectives of this research are To find out the internal conditions related to Strengths and Weaknesses and to find out the external conditions related to Opportunities and Threats to Catering and Conference Services, The Ritz-Carlton Jakarta, Pacific Place and to determine the competitive strategy of the SWOT analysis at the Catering and Conference Services, The Ritz-Carlton Jakarta, Pacific Place. The type of this research is descriptive research, while the time horizon that is applied is Cross Sectional Data. Data collection techniques used in this study are observations and interviews. Samples from this study were 18 respondents using purposive sampling. Based on the results of the research Implementation of SWOT Analysis in Determining Competitive Strategies, where divisions that enter cells I, II, and IV can be described as grow and build. Intensive strategies (market penetration, market development, and product development) or integrative strategies (backward integration, forward integration, and horizontal integration) can be the most suitable strategy for divisions within this cell.
CEREBRAL CIRCULATION: II. REACTION OF PIAL ARTERIES TO INCREASE IN BLOOD PRESSURE

Investigations by Fog1and Forbes, Nason and Wortman2have demonstrated that the pial arteries react to a fall in blood pressure by dilatation. This reaction was shown to be independent of the way in which the fall in pressure was produced. It was noted also by these authors that the same arteries react to a rise in blood pressure by constriction, but no detailed description of the latter reaction was given. During recent experiments with epinephrine,3I have made observations which confirmed these earlier findings, but in view of the various conclusions reached by other investigators, it seemed desirable to carry out further experiments, using the method of direct observation. Heretofore, conclusions as to cerebral vascular reactions have been drawn largely from data obtained by indirect methods. By all such methods the changes in caliber of the vessels are inferred, not observed. Therefore, even if data were
HISTOLOGICAL STUDY OF THE EFFECT OF ESTROGEN ON ASTHMATIC MALE MICE

The present study was conducted to evaluate the influence of estrogen (a female sex hormone) on the experimentally induced asthma in male mice. The animals were divided into 4 groups; 20 mice each: group I received no treatment and represents control mice, group II were injected intraperitoneally with estrogen (0.25 mg/kg B.W., twice on the day 28 of the experiment), group III injected intraperitoneally with two doses of ovalbumin (OVA) (2 μg of OVA mixed with 100 μg of alum) on day 1 and day 14 of the experiment, then challenged intranasaly with a single dose of OVA (50 μg dissolved in 0.05 ml PBS) on day 28 of the experiment and represents asthmatic mice, and f inally group IV included asthma model male mice received the estrogen (0.5 mg/kg B.W. in 40 ml PBS), twice on the day 28 of the experiment and represents asthmatic mice treated with estrogen. Many histopathological changes in the structural integrity were demonstrated in the lung tissues of asthma model mice. The lesions included inf il tration of inflammatory cells around and inside terminal bronchioles, loss of the normal alveolar structure and collapse of the majority of alveolar sacs, while others were distended due to ruptured interalveolar septa. Severe congestion in pulmonary blood vessels and increased thickness in smooth muscle layers of terminal bronchioles were also seen. The collagen fibres (by using azan stain) increased severely at the basement membrane of airways and in the alveolar and respiratory bronchiole walls. The treatment of asthmatic male mice with estrogen improved the histological architecture of the lung tissues, reduced the inflammatory cells and restored the thickness of collagen fibres. For this reason, the present findings support the benefit role of estrogen in modulating the inf lammatory effects caused by asthma in male mice and it may be helpful to recover the histology of asthmatic lung progressions.
Generalized Portrait Quality Assessment

El trabajo en el grupo MICROWINE en esta linea de trabajo ha sido financiado por proyectos y contratos de formacion del Ministerio de Ciencia Innovacion y Universidades que se detallan a continuacion: AGL2012-32064, RTC2014-2186-2, AGL2015-63629-R, y PCI2018-092949 (CoolWine: ERACoBiotech), asi como el contrato predoctoral de Alda J. Rodrigues, y postdoctoral de Jose A. Curiel. J. Tronchoni esta actualmente financiado por el programa COMFUTURO de la FGCSIC
Newly discovered dwarf galaxies in the MATLAS low density fields

We present the photometric properties of 2210 newly identified dwarf galaxy candidates in the MATLAS fields. The Mass Assembly of early Type gaLAxies with their fine Structures (MATLAS) deep imaging survey mapped $\sim$142 deg$^2$ of the sky around nearby isolated early type galaxies using MegaCam on the Canada-France-Hawaii Telescope, reaching surface brightnesses of $\sim$ 28.5 - 29 in the g-band. The dwarf candidates were identified through a direct visual inspection of the images and by visually cleaning a sample selected using a partially automated approach, and were morphologically classified at the time of identification. Approximately 75% of our candidates are dEs, indicating that a large number of early type dwarfs also populate low density environments, and 23.2% are nucleated. Distances were determined for 13.5% of our sample using pre-existing $z_{spec}$ measurements and HI detections. We confirm the dwarf nature for 99% of this sub-sample based on a magnitude cut $M_g$ = -18. Additionally, most of these ($\sim$90%) have relative velocities suggesting that they form a satellite population around nearby massive galaxies rather than an isolated field sample. Assuming that the candidates over the whole survey are satellites of the nearby galaxies, we demonstrate that the MATLAS dwarfs follow the same scaling relations as dwarfs in the Local Group as well as the Virgo and Fornax clusters. We also find that the nucleated fraction increases with $M_g$, and find evidence of a morphology-density relation for dwarfs around isolated massive galaxies.
On Privacy of Dynamical Systems: An Optimal Probabilistic Mapping Approach

We address the problem of maximizing privacy of stochastic dynamical systems whose state information is released through quantized sensor data. In particular, we consider the setting where information about the system state is obtained using noisy sensor measurements. This data is quantized and transmitted to a (possibly untrustworthy) remote station through a public/unsecured communication network. We aim at keeping (part of) the state of the system private; however, because the network (and/or the remote station) might be unsecure, adversaries might have access to sensor data, which can be used to estimate the system state. To prevent such adversaries from obtaining an accurate state estimate, before transmission, we randomize quantized sensor data using additive random vectors, and send the corrupted data to the remote station instead. We design the joint probability distribution of these additive vectors (over a time window) to minimize the mutual information (our privacy metric) between some linear function of the system state (a desired private output) and the randomized sensor data for a desired level of distortion–how different quantized sensor measurements and distorted data are allowed to be. We pose the problem of synthesising the joint probability distribution of the additive vectors as a convex program subject to linear constraints. Simulation experiments are presented to illustrate our privacy scheme.
The Reduced Tensor Product of Braided Tensor Categories Containing a Symmetric Fusion Category

We detail a construction of a symmetric monoidal structure, called the reduced tensor product on the 2-category of braided tensor categories $\mathbf{BTC}(\mathcal{A})$ containing a fixed symmetric fusion subcategory $\mathcal{A}$. The construction only depends on the braiding and monoidal structure of the categories involved. The main tool in the construction is an enriching procedure that is shown to give an equivalence between $\mathbf{BTC}(\mathcal{A})$ and a 2-category of so-called Drinfeld centre crossed braided tensor categories. As an application of the reduced tensor product, we show that it gives a pairing between minimal modular extensions of braided tensor categories containing $\mathcal{A}$ as their transparent subcategory.
Indian EmoSpeech Command Dataset: A dataset for emotion based speech recognition in the wild

Speech emotion analysis is an important task which further enables several application use cases. The non-verbal sounds within speech utterances also play a pivotal role in emotion analysis in speech. Due to the widespread use of smartphones, it becomes viable to analyze speech commands captured using microphones for emotion understanding by utilizing on-device machine learning models. The non-verbal information includes the environment background sounds describing the type of surroundings, current situation and activities being performed. In this work, we consider both verbal (speech commands) and non-verbal sounds (background noises) within an utterance for emotion analysis in real-life scenarios. We create an indigenous dataset for this task namely "Indian EmoSpeech Command Dataset". It contains keywords with diverse emotions and background sounds, presented to explore new challenges in audio analysis. We exhaustively compare with various baseline models for emotion analysis on speech commands on several performance metrics. We demonstrate that we achieve a significant average gain of 3.3% in top-one score over a subset of speech command dataset for keyword spotting.
Human-Like Hybrid Caching in Software-Defined Edge Cloud

With the development of Internet of Things (IoT) and communication technology, the number of next-generation IoT devices has increased explosively, and the delay requirement for content requests is becoming progressively higher. Fortunately, the edge-caching scheme can satisfy users’ demands for low latency of content. However, the existing caching schemes are not smart enough. To address these challenges, we propose a human-like hybrid caching architecture based on the software-defined edge cloud, which simultaneously considers the content popularity and the fine-grained user characteristics. Then, an optimization problem with a caching hit ratio as an optimization objective is formulated. To solve this problem, using reinforcement learning, we design a human-like hybrid caching algorithm. The extensive experiments show that compared with popular caching schemes, human-like hybrid caching schemes can improve the cache hit ratio by 20%.
Genotype Extraction and False Relative Attacks: Security Risks to Third-Party Genetic Genealogy Services Beyond Identity Inference

—Customers of direct-to-consumer (DTC) genetic testing services routinely download their raw genetic data and give it to third-party companies that support additional features. One type of analysis, called genetic genealogy, uses genetic data and genealogical methods to ﬁnd new relatives. While genetic genealogy is quite popular, it has raised new privacy concerns. Genetic genealogy services can be leveraged to ﬁnd the person corresponding to anonymous genetic data and have been used dozens of times by law enforcement to solve crimes. We hypothesized that the open design and broad API offered by some genetic genealogy services raise other signiﬁcant security and privacy issues. To test this hypothesis, we analyzed the security practices of GEDmatch, the largest third-party genetic genealogy service. Here, we experimentally show how the GEDmatch API is vulnerable to a number of attacks from an adversary that only uploads normally formatted genetic data ﬁles and runs standard queries. Using a small number of speciﬁcally designed ﬁles and queries, an attacker can extract a large percentage of the genetic markers from other users; 92% of markers can be extracted with 98% accuracy, including hundreds of medically sensitive markers. We also ﬁnd that an adversary can construct genetic data ﬁles that falsely appear like relatives to other samples in the database; in certain situations, these false relatives can be used to make the re-identiﬁcation of genetic data more difﬁcult. These attacks are possible because of the rich set of features supported by the API, including detailed visualizations, that are meant to enhance usability. We conclude with security recommendations for genetic genealogy services.
Overlapped speech recognition from a jointly learned multi-channel neural speech extraction and representation.

We propose an end-to-end joint optimization framework of a multi-channel neural speech extraction and deep acoustic model without mel-filterbank (FBANK) extraction for overlapped speech recognition. First, based on a multi-channel convolutional TasNet with STFT kernel, we unify the multi-channel target speech enhancement front-end network and a convolutional, long short-term memory and fully connected deep neural network (CLDNN) based acoustic model (AM) with the FBANK extraction layer to build a hybrid neural network, which is thus jointly updated only by the recognition loss. The proposed framework achieves 28% word error rate reduction (WERR) over a separately optimized system on AISHELL-1 and shows consistent robustness to signal to interference ratio (SIR) and angle difference between overlapping speakers. Next, a further exploration shows that the speech recognition is improved with a simplified structure by replacing the FBANK extraction layer in the joint model with a learnable feature projection. Finally, we also perform the objective measurement of speech quality on the reconstructed waveform from the enhancement network in the joint model.