Class Anchor Margin Loss for Content-Based Image Retrieval

The performance of neural networks in content-based image retrieval (CBIR) is highly influenced by the chosen loss (objective) function. The majority of objective functions for neural models can be divided into metric learning and statistical learning. Metric learning approaches require a pair mining strategy that often lacks efficiency, while statistical learning approaches are not generating highly compact features due to their indirect feature optimization. To this end, we propose a novel repeller-attractor loss that falls in the metric learning paradigm, yet directly optimizes for the L2 metric without the need of generating pairs. Our loss is formed of three components. One leading objective ensures that the learned features are attracted to each designated learnable class anchor. The second loss component regulates the anchors and forces them to be separable by a margin, while the third objective ensures that the anchors do not collapse to zero. Furthermore, we develop a more efficient two-stage retrieval system by harnessing the learned class anchors during the first stage of the retrieval process, eliminating the need of comparing the query with every image in the database. We establish a set of four datasets (CIFAR-100, Food-101, SVHN, and Tiny ImageNet) and evaluate the proposed objective in the context of few-shot and full-set training on the CBIR task, by using both convolutional and transformer architectures. Compared to existing objective functions, our empirical evidence shows that the proposed objective is generating superior and more consistent results

Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector

A search for weakly interacting massive particle dark matter produced in association with bottom or top quarks is presented. Final states containing third-generation quarks and miss- ing transverse momentum are considered. The analysis uses 36.1 fb−1 of proton–proton collision data recorded by the ATLAS experiment at √s = 13 TeV in 2015 and 2016. No significant excess of events above the estimated backgrounds is observed. The results are in- terpreted in the framework of simplified models of spin-0 dark-matter mediators. For colour- neutral spin-0 mediators produced in association with top quarks and decaying into a pair of dark-matter particles, mediator masses below 50 GeV are excluded assuming a dark-matter candidate mass of 1 GeV and unitary couplings. For scalar and pseudoscalar mediators produced in association with bottom quarks, the search sets limits on the production cross- section of 300 times the predicted rate for mediators with masses between 10 and 50 GeV and assuming a dark-matter mass of 1 GeV and unitary coupling. Constraints on colour- charged scalar simplified models are also presented. Assuming a dark-matter particle mass of 35 GeV, mediator particles with mass below 1.1 TeV are excluded for couplings yielding a dark-matter relic density consistent with measurements

Ganglion Cell Complex Analysis: Correlations with Retinal Nerve Fiber Layer on Optical Coherence Tomography

The aim of this review is to analyze the correlations between the changes in the ganglion cell complex (GCC) and the retinal nerve fiber layer (RNFL) on optical coherence tomography in different possible situations, especially in eyes with glaucoma. For glaucoma evaluation, several studies have suggested that in the early stages, GCC analysis, especially the thickness of the infero and that of the inferotemporal GCC layers, is a more sensitive examination than circumpapillary RNFL (pRNFL). In the moderate stages of glaucoma, inferior pRNFL thinning is better correlated with the disease than in advanced cases. Another strategy for glaucoma detection is to find any asymmetry of the ganglion cell–inner plexiform layers (GCIPL) between the two macular hemifields, because this finding is a valuable indicator for preperimetric glaucoma, better than the RNFL thickness or the absolute thickness parameters of GCIPL. In preperimetric and suspected glaucoma, GCC and pRNFL have better specificity and are superior to the visual field. In advanced stages, pRNFL and later, GCC reach the floor effect. Therefore, in this stage, it is more useful to evaluate the visual field for monitoring the progression of glaucoma. In conclusion, GCC and pRNFL are parameters that can be used for glaucoma diagnosis and monitoring of the progression of the disease, with each having a higher accuracy depending on the stage of the disease

Survey and Measurements of Indoor Environmental Quality in Urban/Rural Schools Located in Romania

Taken as a whole, the indoor environmental quality (IEQ) is a concept that deals not only with thermal conditions, but it also goes much further, because it includes indoor air quality (IAQ), illuminance or acoustic comfort. Among the different categories of buildings, schools are one of the most important in society especially because future generations are spending more than 6 h/day and ensuring them a healthy and comfortable environment must be top priority. The purposes of this research were to better understand school children’s IEQ preferences and needs in classrooms and to compare these among rural versus urban respondents. To reach this goal, a simple yet complete survey was proposed and, along with measurements, multiple conclusions were made. The methodology proposed was to reach a large sample of respondents to give more credibility and precision to the analysis. The results are based on the responses of 790 occupants both from urban and rural environments. Lack of ventilation, cooling, low or too high temperatures during winter/summer periods and a misappropriate sizing or piloting of the heating system are some of the issues found during the survey. The paper tackles several issues at once, helping to paint a more holistic image of the problems encountered in school classrooms. Optimal thermal comfort is not met during the cold season in any of the schools under investigation. The old rural schools were found to be the worst performing buildings compared to urban schools where due to recent investments in refurbishment the winter thermal comfort was enhanced. During the study, it was observed that one of the major IAQ problems consisted in elevated levels of CO2 or particulate matter especially for the schools situated in the city. Noise was reported as an issue only for the schools situated next to national roads while visual comfort was found to be acceptable for more than 94% of respondents from all regions

Identification of IGF-1 gene polymorphism using PCR-RFLP for improving goat meat evaluation in Carpatina breed

The objective of this study was to identify insulin growth factor (IGF-1) gene polymorphism using PCR RFLP technique in order to improve goat meat evaluation. Insulin like growth factor -1 play an important stimulator role in skeletal growth, cell differentiation and metabolism. Also it has an important role in control of hair cycles and it is involved in development of wool fiber. Therefore, it is considered as an appropriate candidate gene for meat quality evaluation. Blood samples were collected from 12 Carpatina kids and DNA was extracted using, Wizard Genomic DNA Purification Kit. Polymorphism of IGF-1 was determined by PCR amplification followed by RFLP method using restriction enzyme Hae III. In the present study homozygous individuals were identified by RFLP with enzyme Hae III which cuts the amplicon in two places obtaining genotype BC with three migration bands at 363, 264 and 99 bp. Restriction enzyme doesn’t cut the amplicon of the homozygous individuals for the genotype BB, and there is no restriction site, so amplified DNA fragment migration can be visualized in one band of 363 bp.  Based on results, two genotypes BB and BC were identified. It was identified homozygous genotype BB with 75% and heterozygous genotype BC with 25%. B allele frequency was 0.87 and for allele C was 0.13. Observed and expected values of IGF-1 genotypes were found in Hardy Weinberg equilibrium, after χ2 test was calculated. Further investigation are necessary to be carried out on a high number of animals in order to discover other mutations correlated with meat quality in Carpatina goat

Improvement of meat quality evaluation by ultrasound in Carpathian goat breed

In goat, the evaluation of carcass quality was mainly done by using the classical method of animal slaughtering. This paper proposes a non-invasive method for goat carcass estimation, very efficient and easy to use, without sacrificing and able to keep the animals for reproduction: ultrasound method. In the present study, the following parameters were measured by ultrasound method: fat layer, muscle depth, eye muscle area, eye muscle perimeter in Longissimus Dorssi, between two measurements point (12th rib and between 3rd and 4th lumbar vertebra). Young goats (33.65kg, BW), 9 months of age, and adult female goats (35.99 kg BW), were used. In young goat, fat layer (1.86, 1.94 mm), muscle depth (18.97, 17.34 mm), eye muscle area (8.18, 8.25 cm2) and eye muscle perimeter (123.93, 125.06 mm) was similar with those founded in other goat breeds. Very high correlations were found between body weight and ultrasound parameters for muscle depth (0.81, 0.61) and eye muscle area (0.74, 0.67) in young goats. In adults, the ultrasound measurements showed 1.99, 2.04 mm for fat, 19.96, 19.26 mm for muscle depth and 9.02 and 9.17 cm2 for eye muscle area. High correlations were found also for adult goats for the same parameters, body weight and ultrasound for muscle depth (0.61, 0.63) and eye muscle area (0.45, 0.41). In the second phase of this study correlations with carcass derived from slaughtered animals will be carried out