Noise Resistant Multidimensional Data Fusion via Quasi-Cliques on Hypergraphs

Cross-matching data stored on separate files is an everyday activity in the scientific domain. However sometimes the relation between attributes may not be obvious. The discovery of foreign keys on relational databases is a similar problem. Thus techniques devised for this problem can be adapted. Nonetheless, given the different nature of the data, which can be subject to uncertainty, this adaptation is not trivial.<br>This paper firstly introduces the concept of Equally-Distributed Dependencies, which is similar to the Inclusion Dependencies from the relational domain. We describe a correspondence in order to bridge existing ideas. We then propose PresQ: a new algorithm based on the search of maximal quasi-cliques on hyper-graphs to make it more robust to the nature of uncertain numerical data. This algorithm has been tested on three public datasets, showing promising results both in its capacity to find multidimensional equally-distributed sets of attributes and in run-time.

Noise Resistant Multidimensional Data Fusion via Quasi-Cliques on Hypergraphs

Cross-matching data stored on separate files is an everyday activity in the scientific domain. However sometimes the relation between attributes may not be obvious. The discovery of foreign keys on relational databases is a similar problem. Thus techniques devised for this problem can be adapted. Nonetheless, given the different nature of the data, which can be subject to uncertainty, this adaptation is not trivial.<br>This paper firstly introduces the concept of Equally-Distributed Dependencies, which is similar to the Inclusion Dependencies from the relational domain. We describe a correspondence in order to bridge existing ideas. We then propose PresQ: a new algorithm based on the search of maximal quasi-cliques on hyper-graphs to make it more robust to the nature of uncertain numerical data. This algorithm has been tested on three public datasets, showing promising results both in its capacity to find multidimensional equally-distributed sets of attributes and in run-time.

CHILES VERDES: Radio Variability at an Unprecedented Depth and Cadence in the COSMOS Field

Although it is well established that some extragalactic radio sources are time-variable, the properties of this radio variability, and its connection with host galaxy properties, remain to be explored—particularly for faint sources. Here we present an analysis of radio variable sources from the CHILES Variable and Explosive Radio Dynamic Evolution Survey (CHILES VERDES)—a partner project of the 1.4 GHz COSMOS H i Large Extragalactic Survey. CHILES VERDES provides an unprecedented combination of survey depth, duration, and cadence, with 960 hr of 1–2 GHz continuum VLA data obtained over 209 epochs between 2013 and 2019 in a 0.44 deg2 section of the well-studied extragalactic deep field, COSMOS. We identified 18 moderate-variability sources (showing 10%–30% flux density variation) and 40 lower-variability sources (2%–10% flux density variation). They are mainly active galactic nuclei (AGNs) with radio luminosities in the range of 1022–1027 W Hz−1, based on cross-matching with COSMOS multiwavelength catalogs. The moderate-variability sources span redshifts z = 0.22–1.56, have mostly flat radio spectra (α > −0.5), and vary on timescales ranging from days to years. The lower-variability sources have similar properties, but generally have higher radio luminosities than the moderate-variability sources, extending to z = 2.8, and have steeper radio spectra (α < −0.5). No star-forming galaxy showed statistically significant variability in our analysis. The observed variability likely originates from scintillation on short (∼week) timescales, and Doppler-boosted intrinsic AGN variability on long (month–year) timescales.

Incompatible Results on Matched Cross Test Examination

Compatibility testing before blood transfusion is very crucial. This procedure to prevent transfusion reactions due to blood group incompatibility or irregular antibodies. Cross-matching to ensure that the blood safe for the recipient. There are two results in the cross-matching, namely compatible and incompatible. This study aims to determine the inappropriate results of cross-matching at Blood Transfusion Service of the Indonesian Red Cross, Kulon Progo Regency. This study used a quantitative descriptive research design with a retrospective approach. The samples used in this study were 78 incompatible samples in Blood Transfusion Service of the Indonesian Red Cross, Kulon Progo Regency. The sampling technique used was the total population. Methods of data analysis using descriptive analysis. The results show incompatibilities of most compatible cross tests found in minor and auto control (96.1%) with male gender frequency (35.9%) and women (64.1%). The most blood type that has incompatibilities is blood type O (43.3%). The most Diagnosis is anemia (76.9%), and the most components are PRC (88.4%). The most incompatible types are minor and auto control and the most commonly encountered in women, O blood type, anemia, and components of PRC.

Phenotypic and Genetic Characterization for Incompatible Cross-Match Cases in the Feline AB Blood Group System

The feline AB blood group system (blood types A, B, and AB) encoding the cytidine monophosphate-N-acetylneuraminic acid hydroxylase (CMAH) gene is the most significant in transfusion medicine and hemolysis of the newborn for cats. Blood typing and cross-matching in pre-transfusion testing are crucial to determining blood compatibility and thus prevent hemolytic transfusion reactions. We here performed serological and genetic investigations to characterize blood samples from cats with discordant results for card agglutination (CARD) and the alloantibody agglutination test for blood typing in two cats (subjects K and R). Subject K showed incompatible cross-matching in pre-transfusion testing. Red blood cells from subjects K and R determined blood type B from the CARD method showed blood type AB by alloanti-A and alloanti-B antibodies in agglutination testing. Genomic DNA sequencing of the coding region (exons 1a to 14) for the cat CMAH gene showed that subject K had four mutations with heterozygosity at c.139C&gt;T, c.179G&gt;T, c.327A&gt;C, and c.364C&gt;T. Similarly, the CMAH gene of subject R carried six mutations with heterozygosity at c.142G&gt;A, c.187A&gt;G, c.268T&gt;A, c.327A&gt;C, c.773G&gt;A and c.1603G&gt;A, representing a new diplotype including a novel synonymous single nucleotide polymorphism (SNP) in exon 7 (c.773 G&gt;A: Arg258Gln). The CMAH diplotype in subjects K and R was different from major diplotype in blood type B cats. This study is the first to report CMAH variants in cats with discordant blood types between CARD and TUBE methods. These results could assist in the classification of feline AB blood types for transfusion medicine to avoid blood incompatibilities.

A Cross Sectional Study to Evaluate Decision to Delivery Interval in Emergency Caeserian Section at a Tertiary Care Hospital

Background: One of the main factors affecting maternal morbidity and mortality is the decision to delivery interval (DDI) that is, the time taken from the decision to take the patient up for caesarean section to the delivery of the fetus. Method: This is a retrospective observational study conducted over a period of twelve months where 370 patients were studied. Results: No delay was seen in 49.2% cases whereas most delay was noted after decision by obstetricians to transfer patient to OT (22.2%). Conclusion: In order to get favourable maternal and fetal outcome decision to delivery interval should be within 30 minutes and this can be made possible if factors like results of blood investigations and cross matching of blood can be made available on time.

Cross-Sensor Fingerprint Matching Using Siamese Network and Adversarial Learning

The fingerprint is one of the leading biometric modalities that is used worldwide for authenticating the identity of persons. Over time, a lot of research has been conducted to develop automatic fingerprint verification techniques. However, due to different authentication needs, the use of different sensors and the fingerprint verification systems encounter cross-sensor matching or sensor interoperability challenges, where different sensors are used for the enrollment and query phases. The challenge is to develop an efficient, robust and automatic system for cross-sensor matching. This paper proposes a new cross-matching system (SiameseFinger) using the Siamese network that takes the features extracted using the Gabor-HoG descriptor. The proposed Siamese network is trained using adversarial learning. The SiameseFinger was evaluated on two benchmark public datasets FingerPass and MOLF. The results of the experiments presented in this paper indicate that SiameseFinger achieves a comparable performance with that of the state-of-the-art methods.