Planning of Modular Fixtures in a Robotic Assembly System

AbstractIncreasing product varieties is beneficial for companies in terms of expanding the market and harmful in terms of increasing manufacturing costs. Designing and fabricating different fixtures for producing different products with different geometries is a significant portion of the manufacturing costs. To overcome to this problem in a mid-volume mid-variety robotic assembly system, an optimization model is developed to minimize hole-pattern modular fixtures’ preparation time and efforts. Using this model, the best locations for placing different products and jigging-pins are determined, considering all possible part's translations and rotations on the holder. The model is solved by GAMS using the BARON solver for different examples to prove the efficacy of the proposed model

Improving named entity recognition accuracy for gene and protein in biomedical text literature

The task of recognising biomedical named entities in natural language documents called biomedical Named Entity Recognition (NER) is the focus of many researchers due to complex nature of such texts. This complexity includes the issues of character-level, word-level and word order variations. In this study, an approach for recognising gene and protein names that handles the above issues is proposed. Similar to the previous related works, our approach is based on the assumption that a named entity occurs within a noun group. The strength of our proposed approach lies on a Statistical Character-based Syntax Similarity (SCSS) algorithm which measures similarity between the extracted candidates and the well-known biomedical named entities from the GENIA V3.0 corpus. The proposed approach is evaluated and results are satisfied. For recognitions of both gene and protein names, we achieved 97.2% for precision (P), 95.2% for recall (R), and 96.1 for F-measure. While for protein names recognition we gained 98.1% for P, 97.5% for R and 97.7 for F-measure

Effect of cattle manure and zeolite applications on physiological and biochemical changes in soybean [Glycine max (L.) Merr.] grown under water deficit stress | Efecto de la aplicación de estiércol de ganado y zeolita sobre los cambios fisiológicos y bioquímicos en soya [Glycine max (L.) Merr.] cultivada bajo estrés por déficit hídrico

In order to study the effects of cattle manure and zeolite applications on physiological and biochemical changes in soybean grown under conditions of water stress, an experiment was conducted at Varamin, Iran during 2011 growing season. The experimental design was carried out in a randomized complete blocks with a split factorial arrangement of treatments in three replications. Main factor was water stress (normal irrigation and irrigation withholding after 50% flowering) and sub factors were included cattle manure (0, 15 and 30 ton per hectare) and zeolite application (with and without). The results showed that water stress significantly decreased relative water content and electrolyte leakage while increased antioxidant enzyme activity. By contrast, zeolite and cattle manure application had positive effect on relative water content and improve of electrolyte leakage. These treatments alleviate enzyme activity and lipid or protein peroxidation. In general, we concluded that zeolite and manure application can ameliorate growth conditions for soybean plants grown under water deficit stress. Key words: Soybean, cattle manure, zeolite, water stress, enzyme activity RESUMEN Con el fin de estudiar los efectos de la aplicación de estiércol de ganado y zeolita sobre los cambios fisiológicos y bioquímicos de soya cultivada bajo condiciones de estrés hídrico se realizó un experimento de campo en Varamin, Irán durante la temporada de cultivo del 2011. El diseño experimental fue bloques completos al azar en parcelas divididas con tres repeticiones. El factor principal fue el estrés hídrico (riego normal y la supresión de riego después del 50% de floración) y los sub factores fueron estiércol de ganado (0, 15 y 30 t/ha) y la aplicación de zeolita (con y sin). Los resultados mostraron que el estrés hídrico disminuyó significativamente el contenido relativo de agua y la estabilidad de la membrana mientras que incrementó la actividad enzimática. Por el contrario, la aplicación de zeolita y estiércol de ganado tuvieron un efecto positivo sobre el contenido relativo de agua y mejoraron la estabilidad de la membrana. Estos tratamientos aliviaron la actividad enzimática y la peroxidación de lípidos o proteínas. En general, se concluye que la aplicación de zeolita y estiércol puede mejorar las condiciones de crecimiento de las plantas de soya cultivadas bajo estrés por déficit hídrico. Palabras clave: Soya, estiércol de ganado, zeolita, estrés hídrico, actividad enzimátic

The effects of foliar application of ascorbic acid (vitamin C) on physiological and biochemical changes of corn (Zea mays L) under irrigation withholding in different growth stages

To study the effects of ascorbic acid foliar application and limited irrigation in different growth stages on physiological and biochemical changes of corn, an experiment was conducted in Varamin, Iran during the growing season of 2012. The experimental design was randomized complete blocks in split plots arrangement with three replications. Main plots included four different levels of irrigation (complete irrigation, irrigation withholding at 8-leaf stage, irrigation withholding at silks appearance stage and irrigation withholding at both 8-leaf stage and silks appearance stages) and different concentration of foliar application of ascorbic acid (vitamin C) (0, 75, and 150 ppm) were allocated to subplots. The results showed that irrigation withholding conditions in different growth stages significantly decreased seed yield, RWC and total chlorophyll but by contrast increased proline content, antioxidant enzymes activity. Ascorbic acid foliar application in irrigation with holding in different growth stages had positive effect on all attributes in this experiment. In general, the results of the present study indicate that usage of AsA reduces the harmful effects of water deficit stress and increases resistance to drought stress in corn plant

Effect of humic acid foliar application on growth and quantity of corn in irrigation withholding at different growth stages

In order to study effect of humic acid foliar application and limited irrigation on growth and quantitative character¬istics of corn an experiment was conducted in research field of Varamin in Iran during 2012 growing season. The experimental design was laid out in a randomized complete block with a split plots arrangement of treatments in three replications. Main plots included three different levels of irrigation (complete irrigation, irrigation withhold¬ing at 8-leaf stage and irrigation withholding at staminate inflorescence) and four different concentration of humic acid foliar application (0, 150,300 and 450 ppm) was allocated to subplots were. The results showed that irrigation withholding conditions in different growth stages significantly decreased plant height, yield components, seed yield, biological yield and harvest index. Humic acid foliar application in irrigation with holding in different growth stages had positive effect on all attributes in this experiment. In general, the results of the present study indicate that usage of humic acid reduces the harmful effects of water deficit stress and increases resistance to drought stress in corn plant

Influence of Bulk and Nanoparticles Titanium Foliar Application on some Agronomic Traits, Seed Gluten and Starch Contents of Wheat Subjected to Water Deficit Stress

Titanium (Ti) is a very interesting chemical element, especially physiologically. Although Ti is not toxic for animals and humans, its effects on plants show remarkable concentration dependence. Whereas for plants, it shows beneficial effects on various physiological parameters at low doses. This study was conducted to evaluate the effect of bulk and nanoparticles titanium foliar. Application on some agronomic traits, seed gluten and starch contents of wheat under water deficit stress conditions during 2010-2011 growing seasons. The experimental design was randomized in complete blocks arranged in split-split plots with four replications. The factors included normal irrigation, water deficit stress (irrigation withholding at two growing stages of stem elongation and flowering), two growing stages for water deficit stress induction and titanium applications, five titanium concentrations, sources including control of titanium oxide (bulk), and three concentrations of 0.01%, 0.02%, and 0.03% of titanium dioxide nanoparticles. Plant height, ear weight, ear number, seed number, 1000-seed weight, final yield, biomass, harvest index, gluten, and starch contents were assayed. The results showed that water deficit stress caused significant decrease in plant growth, yield and yield components. In addition, among the different titanium treatments, titanium dioxide nanoparticles at 0.02% increased almost all agronomic traits including gluten and starch content. Thus, the application of titanium dioxide nanoparticles under conditions of water deficit stress is recommended. </p

Global, regional, and national prevalence of depression among cancer patients:A systematic review and meta-analysis

This systematic review and meta-analysis aimed to provide a summary of the existing evidence on the prevalence of depression among cancer patients worldwide to assist health policymakers in adopting appropriate measures to prevent and control depression in these patients. EMBASE, Google Scholar, Scopus, PubMed, and Web of Science databases were searched for original studies published in English from January 2000 to July 2019. The studies were screened on the basis of quality and relevance criteria. The statistical analyses were conducted in the R software. Out of 182,521 cancer patients examined in 183 studies, 49,280 (~27%) had depression (95% confidence interval [CI] = 24%-30%). The highest prevalence of depression was among patients with colorectal cancer with 32% (95% CI = 20%-47%). Among countries, Pakistan with 43% (95% CI = 26%-64%), and among continents, Africa with 36% (95% CI = 29%-43%) had the highest prevalence of reported depression in cancer patients. Adjusting for sample size, the prevalence of depression among female cancer patients, 31% (95% CI = 26%-36%), was higher than men, 26% (95% CI = 21%-31%). The prevalence of depression among cancer patients is increasing by an average of 0.6% per year. The findings show higher prevalence of depression among cancer patients in underdeveloped and developing countries compared to the developed nations and the global average

Improving named entity recognition accuracy of gene and protein in biomedical text

The plethora of biomedical material on the WWW is one of the factors that have sustained interest in automatic methods for extracting information from biomedical document, which can help biologists in their research. To extract useful knowledge from the biomedical literature, we must be able to recognize names of biomedical entities, such as genes, proteins, cells, and diseases which are called Named Entity. The task of recognizing entity-denoting expressions, or named entities (NE), in natural language documents is called Named Entity Recognition (NER). Among the biomedical types such as gene, protein, virus, cells, and etc, the most important biomedical types for recognition are gene and protein, which is the scope of this research. The most important reason why most researchers focus on the gene and protein named entities is due to the complexity nature of such types. This complexity includes the issues of character-level variation, word-level variation, and word order variation in biomedical text literature. Typically there are four approaches for Named Entity Recognition, namely: Dictionary-Based, Rule-Based, Statistical and Machine Learning, and Hybrid approaches. In this study, to handle the above issues in recognizing gene and protein names, a statistical similarity measurement as a pattern matching function is proposed. Our approach is based on an assumption that a named entity occurs among a noun group which is extracted using Brill Part of Speech tagger. The strength of our proposed approach for recognizing biomedical named entity is based on a Statistical Character-Based Syntax Similarity (SCSS) algorithm which measured similarity between all extracted candidates and the well-known biomedical named entities from a corpus. For this study, we have used the GENIA V3.0 corpus, which is the largest annotated corpus in the molecular and biology domain. The proposed approach is evaluated based on two measures: recall and precision which are used to calculate a balanced F-test. We have compared our pattern matching function with the other methods and result is satisfied as precision is 98.5% and recall is 96.4%, while the F-test is 97.5 for both gene and protein names recognizing and precision is 99.3% and recall is 99.1%, while the F-test is 99.1 for protein names recognizing