Integration of MFCC Extraction and LSTM Algorithm on PYNQ-Z2 for Enhanced Audio Analysis

The need for Speech Emotion Recognition (SER) is growing since researchers have found it difficult to interpret human emotions from speech data. SER is very interesting yet very challenging   task   of human-computer interaction (HCI). The SER application can be benefitted depending on the type of feature extraction technique and model used for classification. Deep Learning has made a great impact in the field of audio, image, video, EEG and ECG classification. The speech signal characteristics and classification model affect how well the SER application performs.  The paper briefs about deploying Deep Learning Algorithm on FPGA based board i.e., PYNQ-Z2. MFCC feature extraction technique and LSTM model used for classification of human emotion is implemented on the board. Emotion can be predicted using led buttons on the board

Radiometric chronology of Changme-Khangpu glacier, Sikkim

The 32Si concentration in a sample of surface ice from the snout of Changme-Khangpu glacier is 0.36 disintegrations per minute/tonne compared to the fall-out value of 0.7 d.p.m./tonne. If this decrease is assumed to be solely due to decay of 32Si, an age of c. 100 years is estimated for the surface ice of the snout, leading to an average flow velocity of c. 40 m/year for the past century. A vertical profile of 210Pb in a core taken at an altitude of 5040 m shows two horizons where this isotope is enriched, one between 3 and 4 m and another between I I and 12 m, indicating that the primary concentration of 2l0Pb can change by physicochemical processes like adsorption on dust. None the less, a longitudinal profile along the glacier shows a systematic decrease of 2l0Pb activity with decreasing altitude, the surface ice of the snout giving a value of 0.2 d.p.m./I, corresponding to an age of 100 years which is concordant with the 32Si age. This surface flow-rate of the glacier is much larger than the average contemporary flow-rate (c. 13 m/year). The difference can be understood of the past history of advance and recession of the glacier as revealed by the geomorphic evidence

Rice Leaf Disease Detection Using Convolutional Neural Network

In the agriculture sector, the rice crops getting diseased has become a significant concern recently, especially in India, where rice is one of the primary meals. Precise and early-stage detection of various diseases observed in the rice crops can help farmers to provide proper treatment to the crops. This paper presents a Convolutional Neural Network (CNN) based approach is used to detect rice plant leaf disease. CNN is one of the deep learning algorithms that help in image processing and classification with significant accuracy. The proposed algorithm is used for an image dataset of the diseased rice plant leaves, available on Kaggle. Two types of rice leaf diseases are considered for the analysis: brown spot and bacterial leaf blight. The images of these two diseases were pre-processed, segmented, and classified to identify the caused disease. The proposed model can also be used for the detection of the diseases present in other types of crops, faces recognition system, classifying animals, and car models. The overall accuracy of the developed model is nearly 67%

How does an interacting many-body system tunnel through a potential barrier to open space?

The tunneling process in a many-body system is a phenomenon which lies at the very heart of quantum mechanics. It appears in nature in the form of alpha-decay, fusion and fission in nuclear physics, photoassociation and photodissociation in biology and chemistry. A detailed theoretical description of the decay process in these systems is a very cumbersome problem, either because of very complicated or even unknown interparticle interactions or due to a large number of constitutent particles. In this work, we theoretically study the phenomenon of quantum many-body tunneling in a more transparent and controllable physical system, in an ultracold atomic gas. We analyze a full, numerically exact many-body solution of the Schr\"odinger equation of a one-dimensional system with repulsive interactions tunneling to open space. We show how the emitted particles dissociate or fragment from the trapped and coherent source of bosons: the overall many-particle decay process is a quantum interference of single-particle tunneling processes emerging from sources with different particle numbers taking place simultaneously. The close relation to atom lasers and ionization processes allows us to unveil the great relevance of many-body correlations between the emitted and trapped fractions of the wavefunction in the respective processes.Comment: 18 pages, 4 figures (7 pages, 2 figures supplementary information

Unlocking the in vitroanti- inflammatory and antidiabetic potential of Polygonum maritimum

Context: Several Polygonum species (Polygonaceae) are used in traditional medicine in Asia, Europe and Africa to treat inflammation and diabetes. Objective: Evaluate the in vitro antioxidant, anti-inflammatory and antidiabetic potential of methanol and dichloromethane extracts of leaves and roots of the halophyte Polygonum maritimum L. Material and methods: Antioxidant activity was determined (up to 1mg/mL) as radical-scavenging activity (RSA) of 2,2-diphenyl-1-picrylhydrazyl (DPPH), 2,2'azino-bis(3-ethylbenzothiazoline-6-sulphonic acid) (ABTS), copper (CCA) and iron (ICA) chelating activities and iron reducing power (FRAP). NO production was measured in lipopolysaccharide (LPS)-stimulated macrophages for 24 h at concentrations up to 100 mu g/mL and antidiabetic potential was assessed by alpha-amylase and alpha-glucosidase inhibition (up to 10 g/mL) assays. The phytochemical composition of the extracts was determined by gas chromatography-mass spectrometry (GC-MS). Results: The methanol leaf extract had the highest activity against DPPH center dot (IC50 = 26 mu g/mL) and ABTS1(+)center dot (IC50 = 140 mu g FRAP (IC50 = 48 mu g/mL) and CCA (IC50 = 770 mu g/mL). Only the dichloromethane leaf extract (LDCM) showed anti-inflammatory activity (IC50 = 48 mu g/mL). The methanol root (IC50 = 19 mu g/mL) and leaf (IC50 = 29 mu g/mL) extracts strongly inhibited baker's yeast alpha-glucosidase, but LDCM had higher rat's alpha-glucosidase inhibition (IC50 = 2527 mu g/mL) than acarbose (IC50 = 4638 mu g/mL). GC-MS analysis identified beta-sitosterol, stigmasterol, 1-octacosanol and linolenic acid as possible molecules responsible for the observed bioactivities. Conclusions: Our findings suggest P. maritimum as a source of high-value health promoting commodities for alleviating symptoms associated with oxidative and inflammatory diseases, including diabetes.XtremeBio project - Foundation for Science and Technology (FCT) [PTDC/MAR-EST/4346/2012]; Portuguese National Budget; FCT [CCMAR/Multi/04326/ 2013, IF/00049/2012, SFRH/BPD/86071/2012, UID/Multi/00612/2013

Early findings from a large-scale user study of CHESTNUT: Validations and implications

Towards a serendipitous recommender system with user-centred understanding, we have built CHESTNUT , an Information Theory-based Movie Recommender System, which introduced a more comprehensive understanding of the concept. Although off-line evaluations have already demonstrated that CHESTNUT has greatly improved serendip-ity performance, feedback on CHESTNUT from real-world users through online services are still unclear now. In order to evaluate how serendip-itous results could be delivered by CHESTNUT , we consequently designed , organized and conducted large-scale user study, which involved 104 participants from 10 campuses in 3 countries. Our preliminary feedback has shown that, compared with mainstream collaborative filtering techniques, though CHESTNUT limited users' feelings of unex-pectedness to some extent, it showed significant improvement in their feelings about certain metrics being both beneficial and interesting, which substantially increased users' experience of serendipity. Based on them, we have summarized three key takeaways, which would be beneficial for further designs and engineering of serendipitous recommender systems, from our perspective. All details of our large-scale user study could be found at https://github.com/unnc-idl-ucc/Early-Lessons-From-CHESTNU

Access to interpreting services in England: secondary analysis of national data

Background: Overcoming language barriers to health care is a global challenge. There is great linguistic diversity in the major cities in the UK with more than 300 languages, excluding dialects, spoken by children in London alone. However, there is dearth of data on the number of non-English speakers for planning effective interpreting services. The aim was to estimate the number of people requiring language support amongst the minority ethnic communities in England. Methods: Secondary analysis of national representative sample of subjects recruited to the Health Surveys for England 1999 and 2004. Results: 298,432 individuals from the four main minority ethnic communities (Indian, Pakistani, Bangladeshi and Chinese) who may be unable to communicate effectively with a health professional. This represents 2,520,885 general practice consultations per year where interpreting services might be required. Conclusion: Effective interpreting services are required to improve access and health outcomes of non-English speakers and thereby facilitate a reduction in health inequalities

Diterpenes from a soft coral Lobophytum pauciflorum of Indian coast

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Assessment of reporting quality of conference abstracts in sports injury prevention according to CONSORT and STROBE criteria and their subsequent publication rate as full papers

<p>Abstract</p> <p>Background</p> <p>The preliminary results of a study are usually presented as an abstract in conference meetings. The reporting quality of those abstracts and the relationship between their study designs and full paper publication rate is unknown. We hypothesized that randomized controlled trials are more likely to be published as full papers than observational studies.</p> <p>Methods</p> <p>154 oral abstracts presented at the World Congress of Sports Injury Prevention 2005 Oslo and the corresponding full paper publication were identified and analysed. The main outcome measures were frequency of publication, time to publication, impact factor, CONSORT (for Consolidated Standards of Reporting Trials) score, STROBE (for Strengthening the Reporting of Observational Studies in Epidemiology) score, and minor and major inconsistencies between the abstract and the full paper publication.</p> <p>Results</p> <p>Overall, 76 of the 154 (49%) presented abstracts were published as full papers in a peer-reviewed journal with an impact factor of 1.946 ± 0.812. No significant difference existed between the impact factor for randomized controlled trials (2.122 ± 1.015) and observational studies (1.913 ± 0.765, p = 0.469). The full papers for the randomized controlled trials were published after an average (SD) of 17 months (± 13 months); for observational studies, the average (SD) was 12 months (± 14 months) (p = 0.323). A trend was observed in this study that a higher percentage of randomized controlled trial abstracts were published as full papers (71% vs. 47%, p = 0.078) than observational trials. The reporting quality of abstracts, published as full papers, significantly increased compared to conference abstracts both in randomized control studies (CONSORT: 5.7 ± 0.7 to 7.2 ± 1.3; p = 0.018, CI -2.7 to -0.32) and in observational studies (STROBE: 8.2 ± 1.3 to 8.6 ± 1.4; p = 0.007, CI -0.63 to -0.10). All of the published abstracts had at least one minor inconsistency (title, authors, research center, outcome presentation, conclusion), while 65% had at least major inconsistencies (study objective, hypothesis, study design, primary outcome measures, sample size, statistical analysis, results, SD/CI). Comparing the results of conference and full paper; results changed in 90% vs. 68% (randomized, controlled studies versus observational studies); data were added (full paper reported more result data) in 60% vs. 30%, and deleted (full paper reported fewer result data) in 40% vs. 30%.</p> <p>Conclusions</p> <p>No significant differences with respect to type of study (randomized controlled versus observational), impact factor, and time to publication existed for the likelihood that a World Congress of Sports Injury conference abstract could be published as a full paper.</p