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Herein, we demonstrate strongly enhanced visible light photoelectrocatalytic hydrogen evolution reaction (HER) in few-layer MoS2 grown on a mesoporous TiO2(B) nanobelt (NB) by selective decoration of platinum (Pt) nanoparticles (NPs) on the edge/defect sites of the MoS2 layer. Three catalytically active components are anchored together to increase the photoelectrocatalytic HER activity synergistically, beyond that of commercial Pt/C electrodes (20 wt% Pt). An extremely low concentration of Pt NPs (1.4 wt%) with average size ∼3.8 nm was decorated over the preferentially edge-site-exposed few-layer MoS2, with lateral sizes 130–350 nm, as evidenced from high-angle annular dark-field STEM imaging. During the heterojunction formation, S is doped in the TiO2 layer causing a high density of electrons in TiO2 that migrate to the MoS2 layer inducing n-type doping in it and thus TiO2 acts as an efficient photocathode in photoelectrocatalysis. Quantitative XPS analysis reveals that the catalytically active bridging S22−/apical S2− increases up to ∼72% after the formation of the ternary system Pt@MoS2/TiO2(B). S-enriched MoS2/TiO2(B) selectively loaded with Pt NPs on the edge sites of MoS2 exhibits a giant enhancement in the HER activity in an acidic medium under light. We record a nearly 16 fold higher exchange current density (0.296 mA cm−2) for the ternary system as compared to that of the MoS2/TiO2 binary system under visible light excitation. The marginally Pt loaded ternary system exhibits an extremely low charge transfer resistance (14 Ω) and a low overpotential as well as Tafel slope (−74 mV and 30 mV dec−1, respectively) boosting the overall HER performance under visible light. Chronopotentiometric measurements reveal the high stability of binary and ternary systems to sustain a 10 mA cm−2 cathodic current up to 12 hours. The results show that the marginally loaded Pt NPs activate the inert basal plane, edge sites of MoS2 and porous sites of TiO2, forming an integrated network where the photogenerated electrons can easily be injected from the TiO2 to MoS2 and then to Pt NPs, presenting a feasible approach to boost the HER activity under visible light. [ABSTRACT FROM AUTHOR]

Purpose of the Review: The prevalence of mental and substance use disorders is three to five times higher than that of the general population. Psychosocial interventions are effective in identifying and managing mental health and substance use disorders. This article aims to review the randomized control studies which have used nonpharmacological interventions alone or in combination with pharmacological interventions for managing mental and substance use disorders in prison/correctional settings. Collection and Analysis of Data: Studies included were randomized control trials and pilot randomized studies that assessed the impact of psychosocial interventions for prisoners with mental disorders and substance use disorders. A comprehensive search for articles was done by the primary author (Sreekanth Nair Thekkumkara) in the following databases: PubMed, ProQuest, PsychArticles, and Google Scholar (search engine), for the period June 1, 2000, to December 31, 2020. Results and Conclusions: The 21 studies included in the review had a sample size of 34 to 759. The settings of all the interventions were the prison and different types of psychosocial interventions were provided across the studies. The average duration of intervention ranged between 10 min and 120 min with the frequency of one to six sessions per week for 1 to 36 months. All the 21 Randomized Control Trials (RCTs) were nonIndian studies. Overall, the results of the included studies showed significant improvement postintervention (motivational intervention, interpersonal therapy, cognitive behavior therapy, positive psychology intervention, music therapy, and acceptance and commitment therapy) on primary outcome measures such as symptom severity of depression, anxiety, and substance abuse prisoners. Positive effects were observed on secondary outcome measures such as motivation, aggression, follow up rates, and recidivism. A limited number of studies have focused on evaluating psychosocial interventions in prison settings. Most of the interventions were tested in prisoners with substance use disorder alone or in those with dual diagnoses and in high-income countries.

This paper reports the enhancing of isolated word speech recognition system using audio visual features which are extracted from the context speech. Hand gestures captured which are co-expressive with speech are extracted from the context of speech. Both static and dynamic gestures are experimented as part of this study. The extracted gestural features are considered as augmenting features for improving the accuracy of isolated word speech recognition system. The performance of the system are measured under different noise conditions. The experimental results are tabulated under different signal to noise ratio conditions. [ABSTRACT FROM AUTHOR]

The long-sought-after “magic bullet” in systemic therapy remains unrealized for disease targets existing inside most tissues, theoretically because vascular endothelium impedes passive tissue entry and full target engagement. We engineered the first “dual precision” bispecific antibody with one arm pair to precisely bind to lung endothelium and drive active delivery and the other to precisely block TGF-β effector function inside lung tissue. Targeting caveolae for transendothelial pumping proved essential for delivering most of the injected intravenous dose precisely into lungs within one hour and for enhancing therapeutic potency by >1000-fold in a rat pneumonitis model. Ultra-low doses (μg/kg) inhibited inflammatory cell infiltration, edema, lung tissue damage, disease biomarker expression and TGF-β signaling. The prodigious benefit of active vs passive transvascular delivery of a precision therapeutic unveils a new promising drug design, delivery and therapy paradigm ripe for expansion and clinical testing.

The popularity and rapid growth of the internet have reemphasized the importance of intrusion detection systems (IDS) significance in the network security. IDS decreases hacking, data theft risk, privacy intrusion, and others. To save the system from external and internal intruders, the primary approaches of IDS are used. Many techniques[13], like genetic algorithms, artificial neural networks, and artificial immune systems, have been applied to IDS. This paper describes an Ensemble Framework of Artificial Immune System (AIS) based on Network Intrusion Detection System. Without placing a significant additional load on networks and monitoring systems, the large volume of data is analysed by a network-based Intrusion Detection System (NIDS). For determining the connection type, data from KDD Cup 99 competitions is utilized. To differentiate between attacks and valid connections, IDS can be utilized. Optimized feature selection is used to speed up the time-consuming rough set. The results obtained from the IDS system indicate that it can effectively identify the attacking connections with a high success rate.