The influence of dimethyl sulphide and carbon disulphide in the bouquet of wines

Sensory evaluation of DMS added to wines at very low concentrations has shown that addition of 0.022 μl · l-1 resulted in statistically more favoured wines than those with no, or 0.044 μl · l-1 added DMS. This shows that low concentrations of DMS can have a beneficial effect on the quality of some wines.The concentration of CS2 necessary to give any sensory response was higher than that observed in any commercial wine.The threshold of smell for DMS in distilled water was found tobe 7.5 x 10-5 μl · l-1 (0.08 ppb) while that for taste was 4 x 10-4 μl · l-1 (0.4 ppb).Der Einfluß von Dimethylsulfid und Schwefelkohlenstoff auf das WeinaromaBei der sensorischen Beurteilung von Weinen, denen Dimethylsulfid in sehr niedrigen Konzentrationen zugesetzt worden war, wurden jene mit 0,022 μl · l-1 vor solchen ohne oder mit 0,044 μl · l-1 Dimethylsulfid bevorzugt. Geringe DMS-Mengen können demnach die Weinqualität positiv beeinflussen.Die sensorisch wahrnehmbare Schwefelkohlenstoffkonzentration war höher als die in den Weinen gefundenen Mengen.Der Geruchsschwellenwert für Dimethylsulfid in Aqua dest. betrug 7,5 x 10-5 μl · l-1, der Geschmacksschwellenwert dagegen 4 x 10-4 μl· l-1

Using a generative adversarial network to generate synthetic MRI images for multi-class automatic segmentation of brain tumors

Challenging tasks such as lesion segmentation, classification, and analysis for the assessment of disease progression can be automatically achieved using deep learning (DL)-based algorithms. DL techniques such as 3D convolutional neural networks are trained using heterogeneous volumetric imaging data such as MRI, CT, and PET, among others. However, DL-based methods are usually only applicable in the presence of the desired number of inputs. In the absence of one of the required inputs, the method cannot be used. By implementing a generative adversarial network (GAN), we aim to apply multi-label automatic segmentation of brain tumors to synthetic images when not all inputs are present. The implemented GAN is based on the Pix2Pix architecture and has been extended to a 3D framework named Pix2PixNIfTI. For this study, 1,251 patients of the BraTS2021 dataset comprising sequences such as T1w, T2w, T1CE, and FLAIR images equipped with respective multi-label segmentation were used. This dataset was used for training the Pix2PixNIfTI model for generating synthetic MRI images of all the image contrasts. The segmentation model, namely DeepMedic, was trained in a five-fold cross-validation manner for brain tumor segmentation and tested using the original inputs as the gold standard. The inference of trained segmentation models was later applied to synthetic images replacing missing input, in combination with other original images to identify the efficacy of generated images in achieving multi-class segmentation. For the multi-class segmentation using synthetic data or lesser inputs, the dice scores were observed to be significantly reduced but remained similar in range for the whole tumor when compared with evaluated original image segmentation (e.g. mean dice of synthetic T2w prediction NC, 0.74 ± 0.30; ED, 0.81 ± 0.15; CET, 0.84 ± 0.21; WT, 0.90 ± 0.08). A standard paired t-tests with multiple comparison correction were performed to assess the difference between all regions (p < 0.05). The study concludes that the use of Pix2PixNIfTI allows us to segment brain tumors when one input image is missing

Efficient and Trustworthy Review/Opinion Spam Detection

The most common mode for consumers to express their level of satisfaction with their purchases is through online ratings, which we can refer as Online Review System. Network analysis has recently gained a lot of attention because of the arrival and the increasing attractiveness of social sites, such as blogs, social networking applications, micro blogging, or customer review sites. The reviews are used by potential customers to find opinions of existing users before purchasing the products. Online review systems plays an important part in affecting consumers' actions and decision making, and therefore attracting many spammers to insert fake feedback or reviews in order to manipulate review content and ratings. Malicious users misuse the review website and post untrustworthy, low quality, or sometimes fake opinions, which are referred as Spam Reviews. In this study, we aim at providing an efficient method to identify spam reviews and to filter out the spam content with the dataset of gsmarena.com. Experiments on the dataset collected from gsmarena.com show that the proposed system achieves higher accuracy than the standard na?ve bayes

Physics Potential of a 2540 Km Baseline Superbeam Experiment

We study the physics potential of a neutrino superbeam experiment with a 2540 km baseline. We assume a neutrino beam similar to the NuMI beam in medium energy configuration. We consider a 100 kton totally active scintillator detector at a 7 mr off-axis location. We find that such a configuration has outstanding hierarchy discriminating capability. In conjunction with the data from the present reactor neutrino experiments, it can determine the neutrino mass hierarchy at 3 sigma level in less than 5 years, if sin^2(2*theta13) > 0.01, running in the neutrino mode alone. As a stand alone experiment, with a 5 year neutrino run and a 5 year anti-neutrino run, it can determine non-zero theta13 at 3 sigma level if sin^2(2*theta13) > 7*10^{-3} and hierarchy at 3 sigma level if sin^2(2*theta13) > 8*10^{-3}. This data can also distinguish deltaCP = pi/2 from the CP conserving values of 0 and pi, for sin^2(2*theta13) > 0.02.Comment: 16 pages, 7 figures and 1 table: Published versio

Role of Higher Education Institutions in Environmental Conservation and Sustainable Development: A case study of Shivaji University, Maharashtra, India.

The ever increasing population and changing lifestyles are making the environmental problems more critical. Higher educational institutions can be the best solution to solve this situation. Higher education can play a crucial role in sustainable development of any nation. As environmental sustainability is becoming an increasingly important issue for the world, the role of higher educational institutions in relation to environmental sustainability is more prevalent. Universities are the apex bodies in higher education system and can provide environmental education through its curricular design, research and collaborative efforts with NGO’s working in those areas. They can provide trained manpower and knowledgeable expertise to solve critical environmental problems. They can also act as a good networking system and data collector. Shivaji University is one of the significant higher education institution located in heart of Western Ghats working with the same goal of environmental sustainability through various activities. The paper examines the efforts taken by higher education in environmental development in the areas of creating healthy environment and conservation of resources. Key words: Role of Higher education, Environmental protection, Universities, sustainable developmen

Neutrino mass hierarchy and octant determination with atmospheric neutrinos

The recent discovery by the Daya-Bay and RENO experiments, that \theta_{13} is nonzero and relatively large, significantly impacts existing experiments and the planning of future facilities. In many scenarios, the nonzero value of \theta_{13} implies that \theta_{23} is likely to be different from \pi/4. Additionally, large detectors will be sensitive to matter effects on the oscillations of atmospheric neutrinos, making it possible to determine the neutrino mass hierarchy and the octant of \theta_{23}. We show that a 50 kT magnetized liquid argon neutrino detector can ascertain the mass hierarchy with a significance larger than 4 sigma with moderate exposure times, and the octant at the level of 2-3 sigma with greater exposure.Comment: 4 pages, 4 figures. Version published in Phys. Rev. Let

Truth Discovery in Big Data Social Media Application

In this system first one is “misinformation spread” where a significant number of sources are contributing to false claims, making the identification of truthful claims difficult. For example, on, Instagram, rumors, Twitter scams, and influence bots are common examples of sources colluding, either intentionally or unintentionally, to spread misinformation and obscure the truth. The challenge is “data sparsity” or the “long-tail phenomenon” where a majority of sources only contribute a small number of claims, providing insufficient evidence to determine those sources’ trustworthiness. For example, in the Twitter datasets that we collected during real-world events, more than 90only contributed to a single claim. Third, many current solutions are not scalable to large-scale social sensing events because of the centralized nature of their truth discovery algorithms. We are going develop a Scalable and Robust Truth Discovery (SRTD) scheme to address the above all challenges. In this, the SRTD scheme jointly quantifies both the reliability of sources and the credibility of claims using a principled approach