We present a data driven approach to classify ictal (epileptic seizure) and non-ictal EEG signals using the multivariate empirical mode decomposition (MEMD) algorithm. MEMD is a multivariate extension of empirical mode decomposition (EMD), which is an established method to perform the decomposition and time-frequency (T-F) analysis of non-stationary data sets. We select suitable feature sets based on the multiscale T-F representation of the EEG data via MEMD for the classification purposes. The classification is achieved using the artificial neural networks. The efficacy of the proposed method is verified on extensive publicly available EEG datasets.

ABSTRACT. Five novel sulfonamides derivatives HR5-HR8 and HR14 were synthesized by sulfonylation of primary or secondary amine in the presence of base through nucleophilic substitution reaction. Structural elucidation was carried out through FT-IR, UV, 1 H NMR, MS and elemental analysis. Prepared compounds were evaluated against pathogenic strains of bacteria (S. aureus and E. coli) and fungi (A. flavous and A. nyger). Results were compared against standard antifungal and bacterial drug already available in market (isoconazole and sulfmethoxazole). It was found that compound HR14 showed good activity with MIC 1.5 µg/mL and 2.0 µg/mL for S. aurues and E. coli, respectively. While HR5 showed best antifungal activity with zone of inhibition 27.2+0.12 mm (MIC: 5.25 µg/mL) and 18.1+0.12 mm (MIC: 12.5 µg/mL) against A. flavous and A. nyger, respectively. Synthesized compounds were also tested for their in vitro antioxidant activity by using DDPH. Amongst all compounds HR5 was found to have potential activity with 15.60% antioxidant activity at 6 mM concentration.

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Person re-identification (Re-ID) is one of the primary components of an automated visual surveillance system. It aims to automatically identify/search persons in a multi-camera network having non-overlapping field-of-views. Owing to its potential in various applications and research significance, a plethora of deep learning based re-Id approaches have been proposed in the recent years. However, there exist several vision related challenges, e.g., occlusion, pose scale & viewpoint variance, background clutter, person misalignment and cross-domain generalization across camera modalities, which makes the problem of re-Id still far from being solved. Majority of the proposed approaches directly or indirectly aim to solve one or multiple of these existing challenges. In this context, a comprehensive review of current re-ID approaches in solving theses challenges is needed to analyze and focus on particular aspects for further advancements. At present, such a focused review does not exist and henceforth in this paper, we have presented a systematic challenge-specific literature survey of 230+ papers between the years of 2015-21. For the first time a survey of this type have been presented where the person re-Id approaches are reviewed in such solution-oriented perspective. Moreover, we have presented several diversified prominent developing trends in the respective research domain which will provide a visionary perspective regarding ongoing person re-Id research and eventually help to develop practical real world solutions. Scope/Objective of the ReviewIn this paper, we have targeted the most popular challenges in person re-id to perform systematic challenge-wise review of the published approaches. In this context, we have collected papers from top conferences and journals for the years from 2015 to 2021. The progress in papers addressing each challenge and its influence on published results is

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Heavy metals are considered as most important contaminations due to industrialization of countries and an influence on its existence in soil, plant and milk. A study was carried out to check manganese content in soil, forage and milk at three sites of city Jhang, Punjab, Pakistan. All samples (milk, soil, water, fodder plants and ground water) were analyzed for manganese by Atomic Absorption Spectrophotometer. Different health indices were also studied to check Mn flow in food chain. Level of Mn in samples was found within acceptable limits. Manganese level was higher in soil samples collected from Site-III than other sites. Manganese showed higher value (2.595 to 10.402 mg/kg) in soil than other samples. Fodders were found to accumulate manganese from 0.008 to 0.022 mg/kg. Manganese concentration was found to be 0.1482 to 1.241 mg/L, 0.164 to 0.9708 mg/L in water and milk, respectively. BCF and PLI values for manganese were also found to be less than 1. Estimated daily intake (EDI) and THQ of manganese are found within permissible limits in milk of cows feeding on fodders irrigated with wastewater and ground water. So, use of wastewater for irrigation purpose should be properly checked due to possible toxic effects.