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Mood disorders are among the most disabling and complex psychiatric conditions, affecting millions worldwide and contributing substantially to morbidity, mortality, and healthcare utilization [...].Mood disorders are among the most disabling and complex psychiatric conditions, affecting millions worldwide and contributing substantially to morbidity, mortality, and healthcare utilization [...].

Tomato is a wonder fruit fortified with health-promoting phytochemicals that are beneficial in preventing important chronic degenerative disorders. Tomato is a good source of phenolic compounds (phenolic acids and flavonoids), carotenoids (lycopene, α, and β carotene), vitamins (ascorbic acid and vitamin A) and glycoalkaloids (tomatine). Bioactive constituents present in tomato have antioxidant, anti-mutagenic, anti-proliferative, anti-inflammatory and anti-atherogenic activities. Health promoting bioactivities of tomatoes make them useful ingredient for the development of functional foods. Protective role of tomato (lycopene as a potent antioxidant) in humans against various degenerative diseases are known throughout the world. Intake of tomato is inversely related to the incidence of cancer, cardiovascular diseases, ageing and many other health problems. Bioavailability of phytoconstituents in tomato is generally not affected by routine cooking processes making it even more beneficial for human consumption. The present review provides collective information of phytochemicals in tomato along with discussing their bioactivities and possible health benefits.

The widespread use of wireless sensor devices and their advancements in terms of size, deployment cost and user-friendly interface have given rise to many applications of wireless sensor networks (WSNs). WSNs need to utilize routing techniques to forward data samples from event regions to sink via minimum cost links. Clustering is a commonly used data aggregation technique in which nodes are organized into groups in order to reduce the energy consumption. However, in clustering protocols, cluster-head (CH) has to bear an additional load for coordinating various activities within the cluster. Therefore, proper CH selection and their load balancing using efficient routing protocol is a critical aspect for the long-run operation of WSN. In this paper, genetic algorithm (GA)-based threshold-sensitive energy-efficient routing protocol (TERP) is proposed to prolong network lifetime. Multi-hop communication between CHs and base station (BS) is utilized using GA to achieve optimal link cost for load balancing of distant CHs and energy minimization. The paper also considers stability-aware model of TERP named stable TERP (STERP) so as to extend the stability period (time interval from initial time to the death of first node) of the network. In STERP, energy-aware heuristics is applied for CH selection in order to improve the stability period. Analysis and simulation results demonstrate that the proposed methodology significantly outperforms existing protocols in terms of energy consumption, system lifetime and stability period.

Nature-inspired algorithms are becoming popular among researchers due to their simplicity and flexibility. The nature-inspired metaheuristic algorithms are analysed in terms of their key features like their diversity and adaptation, exploration and exploitation, and attractions and diffusion mechanisms. The success and challenges concerning these algorithms are based on their parameter tuning and parameter control. A comparatively new algorithm motivated by the social hierarchy and hunting behavior of grey wolves is Grey Wolf Optimizer (GWO), which is a very successful algorithm for solving real mechanical and optical engineering problems. In the original GWO, half of the iterations are devoted to exploration and the other half are dedicated to exploitation, overlooking the impact of right balance between these two to guarantee an accurate approximation of global optimum. To overcome this shortcoming, a modified GWO (mGWO) is proposed, which focuses on proper balance between exploration and exploitation that leads to an optimal performance of the algorithm. Simulations based on benchmark problems and WSN clustering problem demonstrate the effectiveness, efficiency, and stability of mGWO compared with the basic GWO and some well-known algorithms.

Bipolar disorder (BD) is a chronic mental illness impacting 1-2% of the population worldwide and causing high rates of functional impairment. Patients with BD spend most of their time in depressive episodes and up to one-third of patients do not respond to adequate doses of medications. Although no consensus exists for definition of treatment-resistant bipolar depression (TRBD), failure of symptoms improvement despite an adequate trial of two therapeutic agents is a common theme of TRBD. In this paper, we review the evidence base of therapeutic interventions, challenges, and potential future directions for TRBD. We conducted a literature search for randomized controlled trials on PubMed for the treatment of TRBD and ongoing trials for the treatment of TRBD/bipolar depression on clinicaltrials.gov. Several therapeutic agents have been investigated for TRBD. Adjunctive pramipexole and modafinil have data supporting short-term efficacy in TRBD, along with limited data for racemic intravenous ketamine. Celecoxib augmentation of escitalopram and treatment with metformin in patients with insulin resistance showed promising results. Right unilateral electroconvulsive therapy displayed statistically significant response rate and improvement, but not remission compared to pharmacotherapy. Trials for transcranial magnetic stimulation (TMS) have failed to show a significant difference from sham treatment in TRBD. Pharmacological treatments with novel mechanisms of actions like brexpiprazole and vortioxetine are being investigated following successes in unipolar depression. Modified TMS protocols such as accelerated TMS are under investigation. Innovative approaches like psychedelic-assisted psychotherapy, interleukin-2, fecal microbiota transplantation and multipotent stromal cells are being studied. Evidence on current treatment modalities for TRBD is limited with low efficacy. More research is needed for successful treatment of TRBD. Effective therapies and innovative approaches to treatment are being investigated and could show promise.

Wireless sensor network (WSN) consists of densely distributed nodes that are deployed to observe and react to events within the sensor field. In WSNs, energy management and network lifetime optimization are major issues in the designing of cluster-based routing protocols. Clustering is an efficient data gathering technique that effectively reduces the energy consumption by organizing nodes into groups. However, in clustering protocols, cluster heads (CHs) bear additional load for coordinating various activities within the cluster. Improper selection of CHs causes increased energy consumption and also degrades the performance of WSN. Therefore, proper CH selection and their load balancing using efficient routing protocol is a critical aspect for long run operation of WSN. Clustering a network with proper load balancing is an NP-hard problem. To solve such problems having vast search area, optimization algorithm is the preeminent possible solution. Spider monkey optimization (SMO) is a relatively new nature inspired evolutionary algorithm based on the foraging behaviour of spider monkeys. It has proved its worth for benchmark functions optimization and antenna design problems. In this paper, SMO based threshold-sensitive energy-efficient clustering protocol is proposed to prolong network lifetime with an intend to extend the stability period of the network. Dual-hop communication between CHs and BS is utilized to achieve load balancing of distant CHs and energy minimization. The results demonstrate that the proposed protocol significantly outperforms existing protocols in terms of energy consumption, system lifetime and stability period.

The incidence and clinical correlates of acute in-hospital mortality of takotsubo cardiomyopathy (TTC) are not clear. We performed a systematic review and meta-analysis to consolidate the current evidence on acute mortality in TTC. We then assessed the impact of “secondary” TTC, male gender, advancing age, and catecholamine use on mortality. A comprehensive search of 4 major databases (EMBASE, Ovid MEDLINE, PubMed, and Google Scholar) was performed from their inception to the first week of July 2013. We included original research studies, recruiting ≥10 participants, published in English language, and those that reported data on mortality and cause of death in patients with TTC. Of 382 citations, 37 studies (2,120 patients with TTC) from 11 different countries were included in the analyses. The mean age of the cohort was 68 years (95% confidence interval [CI] 67 to 69) with female predominance (87%). The in-hospital mortality rate among patients with TTC was 4.5% (95% CI 3.1 to 6.2, I2 = 60.8%). Among all deaths, 38% were directly related to TTC complications and rest to underlying noncardiac conditions. Male gender was associated with higher TTC mortality rate (odds ratio 2.6, 95% CI 1.5 to 4.6, p = 0.0008, I2 = 0%) so was “secondary” TTC (risk difference −0.11, 95% CI −0.18 to −0.04, p = 0.003, I2 = 84%). The mean age of patients dying tended to be greater than that in the whole cohort (72 ± 7 vs 65 ± 7 years). In conclusion, TTC is not as benign as once thought. To reduce the mortality rate, greater efforts need to be directed to the diagnosis, treatment, and ultimately prevention of “secondary” TTC.

India relies on groundwater irrigation to produce staple grain crops that provide over half of the calories consumed by its over 1.3 billion people. While groundwater has helped India achieve grain self-sufficiency, aquifers have been overexploited across much of the country and its implications for crop production are unclear. To understand how groundwater depletion affects staple grain (wheat, rice, maize, pearl millet, and sorghum) production in India, we ran district-level panel regressions using agricultural census, groundwater observation, and gridded weather datasets over a ten-year study period (2004–2013). We find that nationally, declining groundwater levels are associated with significant reductions in yield, cropped area, and production for wheat, rice, and maize in the winter season. Despite the negative impacts of groundwater depletion on crop production, we find little evidence that farmers are switching from planting more water-intensive to less water-intensive grains. Using profit-based decision modeling, we further investigated the effects of agricultural energy prices on crop choice in the monsoon season across Haryana and Punjab, which are responsible for over 60% of India’s grain production, have high electricity subsidies, and have rapidly depleting water tables. We find that eliminating energy subsidies for groundwater pumping would likely not encourage farmers to switch to planting less water-intensive crops, though sensitivity analyses suggest that it could encourage the adoption of increased water conservation efforts. In summary, our analyses reveal a discernable impact of groundwater depletion on crop production in India and suggest that reducing or removing energy subsidies may largely affect water use but not crop choice.

Food packaging reinforced with Zn-doped TiO 2 nanoparticles with enhanced prerequisite film-forming and biodegradable traits was prepared to augment fresh food storage. Pure and tailored metal (Zinc, Copper, and Selenium) doped TiO 2 nanoparticles were synthesized and analyzed through multiple characterization techniques (optical spectra, XRD patterns (X-Ray Diffraction), Dynamic Light Scattering, and Scanning Electron Microscopy). The synthesized nanoparticles were tested for their Minimum Inhibitory Concentrations, antimicrobial potential against common lethal food pathogens, and cytotoxicity. Compared to Cu- and Se-doped nanoparticles, Zn-doped TiO 2 nanoparticles displayed the most potent antimicrobial activity with insignificant cytotoxicity and were incorporated into the food packaging materials. The developed nano-reinforced food packaging efficaciously augmented the freshness of plums ( Oemleria cerasiformis ) for 16 days (42 ± 2 °C). The physicomechanical characterization of the nano-reinforced packaging establishes its utility in food packaging applications. The developed biodegradable packaging undergoes complete decomposition within 12 days of storage in natural soil.

Wireless sensor network (WSN) is a cost-effective networking solution for information updating in the coverage radius or in the sensing region. To record a real-time event, a large number of sensor nodes (SNs) need to be arranged systematically, such that information collection is possible for a longer span of time. But, the hurdle faced by WSN is the limited resources of SNs. Hence, there is a high demand to design and implement an energy-efficient scheme to prolong the performance parameters of WSN. Clustering-based routing is the most suitable approach to support for load balancing, fault tolerance, and reliable communication to prolong performance parameters of WSN. These performance parameters are achieved at the cost of reduced lifetime of cluster head (CH). To overcome such limitations in clustering based hierarchical approach, efficient CH selection algorithm, and optimized routing algorithm are essential to design efficient solution for larger scale networks. In this paper, fuzzy extended grey wolf optimization algorithm based threshold-sensitive energy-efficient clustering protocol is proposed to prolong the stability period of the network. Analysis and simulation results show that the proposed algorithm significantly outperforms competitive clustering algorithms in the context of energy consumption, stability period and system lifetime.