NUTRITIONAL AND SENSORY EVALUATION OF CONVECTIVE DRIED FRUTI

Most vegetables and fruits are highly perishable due to a high water content, which makes it difficult to trade, since seasonality and distance between markets demand costly refrigerated storage and transportation. Increasing shelf life and availability throughout the year by processing reduces losses by marketing of fresh foods. The drying or dehydration is a technique used from the antiquity for the conservation of foods, once the water affects in a decisive way the time of preservation of the products, influencing his/her quality and durability directly. The objectives of the present work were to assess the nutritional quality and conduct consumer sensory evaluation testing of convective dried fruits. They were processed apple, bananas, papaya, melon, kiwi and pear. Convective drying was carried out in the dryer a tray cabinet at 60 C and 1.25 m.s-1 to obtain a product with 15% moisture content.  Dehydrated fruits were evaluated for their physicochemical and microbiological characteristics. The sensorial attributes were appraised for 30 consumers using climbs hedonic of five points. The results showed that the convective drying maintained the nutritional quality of the fruit when compared to the fresh product. Sensory analysis showed that the product obtained high acceptance rate, corresponding to the second and third levels of hedonic scale (liked and enjoyed regularly). The feature that predominantly influenced acceptance of the product was the appearance, flavor and aroma. The texture was the attribute that less influenced the acceptance

Rapid antidepressant effects of the psychedelic ayahuasca in treatment-resistant depression: a randomized placebo-controlled trial

Background Recent open-label trials show that psychedelics, such as ayahuasca, hold promise as fast-onset antidepressants in treatment-resistant depression. Methods To test the antidepressant effects of ayahuasca, we conducted a parallel-arm, double-blind randomized placebo-controlled trial in 29 patients with treatment-resistant depression. Patients received a single dose of either ayahuasca or placebo. We assessed changes in depression severity with the Montgomery-Åsberg Depression Rating Scale (MADRS) and the Hamilton Depression Rating scale at baseline, and at 1 (D1), 2 (D2), and 7 (D7) days after dosing. Results We observed significant antidepressant effects of ayahuasca when compared with placebo at all-time points. MADRS scores were significantly lower in the ayahuasca group compared with placebo at D1 and D2 (p = 0.04), and at D7 (p < 0.0001). Between-group effect sizes increased from D1 to D7 (D1: Cohen's d = 0.84; D2: Cohen's d = 0.84; D7: Cohen's d = 1.49). Response rates were high for both groups at D1 and D2, and significantly higher in the ayahuasca group at D7 (64% v. 27%; p = 0.04). Remission rate showed a trend toward significance at D7 (36% v. 7%, p = 0.054). Conclusions To our knowledge, this is the first controlled trial to test a psychedelic substance in treatment-resistant depression. Overall, this study brings new evidence supporting the safety and therapeutic value of ayahuasca, dosed within an appropriate setting, to help treat depression. This study is registered at http://clinicaltrials.gov (NCT02914769)

SoK: A Consensus Taxonomy in the Blockchain Era

Consensus (a.k.a. Byzantine agreement) is arguably one of the most fundamental problems in distributed systems, playing also an important role in the area of cryptographic protocols as the enabler of a (secure) broadcast functionality. While the problem has a long and rich history and has been analyzed from many different perspectives, recently, with the advent of blockchain protocols like Bitcoin, it has experienced renewed interest from a much wider community of researchers and has seen its application expand to various novel settings. One of the main issues in consensus research is the many different variants of the problem that exist as well as the various ways the problem behaves when different setup, computational assumptions and network models are considered. In this work we perform a systematization of knowledge in the landscape of consensus research starting with the original formulation in the early 1980s up to the present blockchain-based new class of consensus protocols. Our work is a roadmap for studying the consensus problem under its many guises, classifying the way it operates in many settings and highlighting the exciting new applications that have emerged in the blockchain era