Post harvest loss and marketing of fruits - economic analysis of pink flesh guava in local and distant markets in India

Guava produced in Bengaluru in Karnataka is also transported to distant markets like Cochin in Kerala and Chennai in Tamil Nadu. An assessment of post harvest loss (PHL) was done in these markets. The main marketing channel followed was:Producer PHC Distant Market WS Retailer ConsumerMarketing practices followed in marketing of pink flesh guava and losses occurring at the wholesale (transit) and retailers’ level (storage) in the distant market - Kerala were studied from wholesalers and retailers. The PHL at the wholesalers’ level was observed to be 3.6 per cent mainly due to pressed and crushed fruits during transit. The retail level loss was 4.59 per cent which was mainly due to storage for more than two days resulting in decaying, rotting, yellowing etc. Average price received by the wholesaler was Rs.29.92/kg with a margin of Rs.6.21/kg (20.75%). The retailers received a price of Rs.46.54/kg with a margin of Rs.16.35/kg (35.13%). Marketing practices followed in marketing of pink flesh guava and losses occurring at the wholesale (transit) and retailers’ level (storage) in the distant market - Chennai (Tamil Nadu) were studied with wholesalers in Coimbeedu market and retailers in different parts of Chennai. The PHL at the wholesalers’ level was observed to be 4.62 per cent mainly due to pressed and crushed fruits during transit. The retail level loss was 6.09 per cent which was due to pressing of fruits during handling. The wholesaler received a margin of 22.91 percent in trading of guava fruits. The retailers received a margin of 45.72 per cent. The Karnataka farmers can take advantage of the higher prices prevalent in the distant markets and increase their income. Pathological investigation indicated that losses occurred at different stages of handling due to Styler end rot, Anthracnose, Canker, thrips attack etc., which needs to be addressed. The storage losses of pink flesh guava were estimated as 5.89 % after 4 days of storage at room temperature (24-32°C) that constituted mainly the physiological loss in weight (PLW). Spoilage started after 5 days of storage (10.5 %) and reached to 28.31 % by 6 days of storage. After 4 days of storage, guava fruits lose weight to the extent of 6 per cent and the spoilage starts after 5 days. Hence, care should be taken to dispose of the fruits within five days of harvest

Identification of Co-Existing Mutations and Gene Expression Trends Associated With K13-Mediated Artemisinin Resistance in Plasmodium falciparum

Plasmodium falciparum infects millions and kills thousands of people annually the world over. With the emergence of artemisinin and/or multidrug resistant strains of the pathogen, it has become even more challenging to control and eliminate the disease. Multiomics studies of the parasite have started to provide a glimpse into the confounding genetics and mechanisms of artemisinin resistance and identified mutations in Kelch13 (K13) as a molecular marker of resistance. Over the years, thousands of genomes and transcriptomes of artemisinin-resistant/sensitive isolates have been documented, supplementing the search for new genes/pathways to target artemisinin-resistant isolates. This meta-analysis seeks to recap the genetic landscape and the transcriptional deregulation that demarcate artemisinin resistance in the field. To explore the genetic territory of artemisinin resistance, we use genomic single-nucleotide polymorphism (SNP) datasets from 2,517 isolates from 15 countries from the MalariaGEN Network (The Pf3K project, pilot data release 4, 2015) to dissect the prevalence, geographical distribution, and co-existing patterns of genetic markers associated with/enabling artemisinin resistance. We have identified several mutations which co-exist with the established markers of artemisinin resistance. Interestingly, K13-resistant parasites harbor α-ß hydrolase and putative HECT domain–containing protein genes with the maximum number of SNPs. We have also explored the multiple, publicly available transcriptomic datasets to identify genes from key biological pathways whose consistent deregulation may be contributing to the biology of resistant parasites. Surprisingly, glycolytic and pentose phosphate pathways were consistently downregulated in artemisinin-resistant parasites. Thus, this meta-analysis highlights the genetic and transcriptomic features of resistant parasites to propel further exploratory studies in the community to tackle artemisinin resistance.</p

Recognizing recurrent neural networks (rRNN): Bayesian inference for recurrent neural networks

Recurrent neural networks (RNNs) are widely used in computational neuroscience and machine learning applications. In an RNN, each neuron computes its output as a nonlinear function of its integrated input. While the importance of RNNs, especially as models of brain processing, is undisputed, it is also widely acknowledged that the computations in standard RNN models may be an over-simplification of what real neuronal networks compute. Here, we suggest that the RNN approach may be made both neurobiologically more plausible and computationally more powerful by its fusion with Bayesian inference techniques for nonlinear dynamical systems. In this scheme, we use an RNN as a generative model of dynamic input caused by the environment, e.g. of speech or kinematics. Given this generative RNN model, we derive Bayesian update equations that can decode its output. Critically, these updates define a 'recognizing RNN' (rRNN), in which neurons compute and exchange prediction and prediction error messages. The rRNN has several desirable features that a conventional RNN does not have, for example, fast decoding of dynamic stimuli and robustness to initial conditions and noise. Furthermore, it implements a predictive coding scheme for dynamic inputs. We suggest that the Bayesian inversion of recurrent neural networks may be useful both as a model of brain function and as a machine learning tool. We illustrate the use of the rRNN by an application to the online decoding (i.e. recognition) of human kinematics

Minimizing material consumption of 3d printing with stress-guided optimization

3D printing has been widely used in daily life, industry, architecture, aerospace, crafts, art, etc. Minimizing 3D printing material consumption can greatly reduce the costs. Therefore, how to design 3D printed objects with less materials while maintain structural soundness is an important problem. The current treatment is to use thin shells. However, thin shells have low strength. In this paper, we use stiffeners to stiffen 3D thin-shell objects for increasing the strength of the objects and propose a stress guided optimization framework to achieve minimum material consumption. First, we carry out finite element calculations to determine stress distribution in 3D objects and use the stress distribution to guide random generation of some points called seeds. Then we map the 3D objects and seeds to a 2D space and create a Voronoi Diagram from the seeds. The stiffeners are taken to be the edges of the Voronoi Diagram whose intersections with the edges of each of the triangles used to represent the polygon models of the 3D objects are used to define stiffeners. The obtained intersections are mapped back to 3D polygon models and the cross-section size of stiffeners is minimized under the constraint of the required strength. Monte-Carlo simulation is finally introduced to repeat the process from random seed generation to cross-section size optimization of stiffeners. Many experiments are presented to demonstrate the proposed framework and its advantages

Treatment outcomes of new tuberculosis patients hospitalized in Kampala, Uganda: a prospective cohort study.

BACKGROUND: In most resource limited settings, new tuberculosis (TB) patients are usually treated as outpatients. We sought to investigate the reasons for hospitalisation and the predictors of poor treatment outcomes and mortality in a cohort of hospitalized new TB patients in Kampala, Uganda. METHODS AND FINDINGS: Ninety-six new TB patients hospitalised between 2003 and 2006 were enrolled and followed for two years. Thirty two were HIV-uninfected and 64 were HIV-infected. Among the HIV-uninfected, the commonest reasons for hospitalization were low Karnofsky score (47%) and need for diagnostic evaluation (25%). HIV-infected patients were commonly hospitalized due to low Karnofsky score (72%), concurrent illness (16%) and diagnostic evaluation (14%). Eleven HIV uninfected patients died (mortality rate 19.7 per 100 person-years) while 41 deaths occurred among the HIV-infected patients (mortality rate 46.9 per 100 person years). In all patients an unsuccessful treatment outcome (treatment failure, death during the treatment period or an unknown outcome) was associated with duration of TB symptoms, with the odds of an unsuccessful outcome decreasing with increasing duration. Among HIV-infected patients, an unsuccessful treatment outcome was also associated with male sex (P = 0.004) and age (P = 0.034). Low Karnofsky score (aHR = 8.93, 95% CI 1.88 - 42.40, P = 0.001) was the only factor significantly associated with mortality among the HIV-uninfected. Mortality among the HIV-infected was associated with the composite variable of CD4 and ART use, with patients with baseline CD4 below 200 cells/µL who were not on ART at a greater risk of death than those who were on ART, and low Karnofsky score (aHR = 2.02, 95% CI 1.02 - 4.01, P = 0.045). CONCLUSION: Poor health status is a common cause of hospitalisation for new TB patients. Mortality in this study was very high and associated with advanced HIV Disease and no use of ART

Reinforcement learning or active inference?

This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain

Investigation of attentional bias in obsessive compulsive disorder with and without depression in visual search

Copyright: © 2013 Morein-Zamir et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are creditedWhether Obsessive Compulsive Disorder (OCD) is associated with an increased attentional bias to emotive stimuli remains controversial. Additionally, it is unclear whether comorbid depression modulates abnormal emotional processing in OCD. This study examined attentional bias to OC-relevant scenes using a visual search task. Controls, non-depressed and depressed OCD patients searched for their personally selected positive images amongst their negative distractors, and vice versa. Whilst the OCD groups were slower than healthy individuals in rating the images, there were no group differences in the magnitude of negative bias to concern-related scenes. A second experiment employing a common set of images replicated the results on an additional sample of OCD patients. Although there was a larger bias to negative OC-related images without pre-exposure overall, no group differences in attentional bias were observed. However, OCD patients subsequently rated the images more slowly and more negatively, again suggesting post-attentional processing abnormalities. The results argue against a robust attentional bias in OCD patients, regardless of their depression status and speak to generalized difficulties disengaging from negative valence stimuli. Rather, post-attentional processing abnormalities may account for differences in emotional processing in OCD.Peer reviewedFinal Published versio

Medulloblastomas overexpress the p53-inactivating oncogene WIP1/PPM1D

Medulloblastoma is the most common malignant brain tumor of childhood. Despite numerous advances, clinical challenges range from recurrent and progressive disease to long-term toxicities in survivors. The lack of more effective, less toxic therapies results from our limited understanding of medulloblastoma growth. Although TP53 is the most commonly altered gene in cancers, it is rarely mutated in medulloblastoma. Accumulating evidence, however, indicates that TP53 pathways are disrupted in medulloblastoma. Wild-typep53-induced phosphatase 1 (WIP1 or PPM1D) encodes a negative regulator of p53. WIP1 amplification (17q22-q23) and its overexpression have been reported in diverse cancer types. We examined primary medulloblastoma specimens and cell lines, and detected WIP1 copy gain and amplification prevalent among but not exclusively in the tumors with 17q gain and isochromosome 17q (i17q), which are among the most common cytogenetic lesions in medulloblastoma. WIP1 RNA levels were significantly higher in the tumors with 17q gain or i17q. Immunoblots confirmed significant WIP1 protein in primary tumors, generally higher in those with 17q gain or i17q. Under basal growth conditions and in response to the chemotherapeutic agent, etoposide, WIP1 antagonized p53-mediated apoptosis in medulloblastoma cell lines. These results indicate that medulloblastoma express significant levels of WIP1 that modulate genotoxic responsiveness by negatively regulating p53

Phase III study of 5FU, etoposide and leucovorin (FELV) compared to epirubicin, cisplatin and 5FU (ECF) in previously untreated patients with advanced biliary cancer

The purpose of this study was to determine whether epirubicin, cisplatin and infused 5FU (ECF) improves overall survival (OS) compared to 5FU, etoposide and leucovorin (FELV) in patients with previously untreated advanced biliary cancer in a prospective randomised study. Patients were randomly assigned to receive epirubicin, cisplatin and infused 5FU ECF or bolus 5FU etoposide and leucovorin (FELV). The primary end point was OS with secondary end points of objective response rate (ORR), failure-free survival (FFS), quality of life (QOL) and toxicity. In all, 54 patients were recruited with 27 randomly assigned to each arm. The median OS for ECF was 9.02 months (95% confidence interval (CI): 6.46–11.51) and FELV 12.03 months (95% CI: 9.3–14.7), P=0.2059. Objective response rates were similar for both arms: ECF 19.2% (95% CI: 6.55–39.3); FELV 15% (95% CI: 3.2–37.9), P=0.72. There was significantly increased grade 3/4 neutropenia with FELV vs ECF (53.8 vs 29.5%, respectively, P=0.020). Symptom resolution was impressive for both regimens. This is the largest reported randomised study to date in this setting. ECF did not improve OS compared to FELV, but was associated with less acute toxicity. These data suggest that chemotherapy can prolong OS and achieve good symptomatic relief in advanced biliary cancer