The effect of foliar application of methanol on productivity and fruit quality of grapevine cv. Flame Seedless

Field experiments were conducted in 2002 and 2003 on 6-year-old grapevine cv. Flame Seedless. The content of chlorophyll a and b, carotenoids and total carbohydrates increased after methanol application. Foliar application of aqueous methanol was very effective increasing the number of leaves per shoot and leaf area. Furthermore, 30 % methanol increased significantly the number of stomata of developing leaves at the first application time (shoot length: 20-30 cm) while 10, 30, 40 and 50 % methanol solutions were more effective at the second application date (prebloom). Increasing the chlorophyll content, the leaf area and the number of stomata per unit leaf area by methanol application increased net productivity of vines. There was a highly significant positive correlation between total yield, chlorophyll and carbohydrates content. Generally, all methanol treatments significantly increased length and diameter of shoots and internode length at both application dates. Application of methanol increased total soluble solids (TSS), the TSS/acid ratio and total anthocyanins in berry skins but decreased total acidity. Most significant effects were obtained by spraying 30 % methanol at the two application dates.

The Minimum Shared Edges Problem on Grid-like Graphs

We study the NP-hard Minimum Shared Edges (MSE) problem on graphs: decide whether it is possible to route $p$ paths from a start vertex to a target vertex in a given graph while using at most $k$ edges more than once. We show that MSE can be decided on bounded (i.e. finite) grids in linear time when both dimensions are either small or large compared to the number $p$ of paths. On the contrary, we show that MSE remains NP-hard on subgraphs of bounded grids. Finally, we study MSE from a parametrised complexity point of view. It is known that MSE is fixed-parameter tractable with respect to the number $p$ of paths. We show that, under standard complexity-theoretical assumptions, the problem parametrised by the combined parameter $k$, $p$, maximum degree, diameter, and treewidth does not admit a polynomial-size problem kernel, even when restricted to planar graphs

The Complexity of Routing with Few Collisions

We study the computational complexity of routing multiple objects through a network in such a way that only few collisions occur: Given a graph $G$ with two distinct terminal vertices and two positive integers $p$ and $k$, the question is whether one can connect the terminals by at least $p$ routes (e.g. paths) such that at most $k$ edges are time-wise shared among them. We study three types of routes: traverse each vertex at most once (paths), each edge at most once (trails), or no such restrictions (walks). We prove that for paths and trails the problem is NP-complete on undirected and directed graphs even if $k$ is constant or the maximum vertex degree in the input graph is constant. For walks, however, it is solvable in polynomial time on undirected graphs for arbitrary $k$ and on directed graphs if $k$ is constant. We additionally study for all route types a variant of the problem where the maximum length of a route is restricted by some given upper bound. We prove that this length-restricted variant has the same complexity classification with respect to paths and trails, but for walks it becomes NP-complete on undirected graphs

Shunt Hybrid Active Power Filter Based on Two Compensation Strategies with PI and Fuzzy Logic Controllers

Industrial designs have tremendously changed within the last decade, with its time and nonlinear variation loads in power frameworks spectrum expanding widely. This revolution has resulted in increased quality control problems such as current unbalance, current and voltage harmonics, flicker and poor power factor in control frameworks. The aim of this paper is to address this problem through the development of Synchronous Reference Frame and Reactive Power (SRF and P-Q) control methods. The DC voltage was regulated to its set reference for providing the current reference using proportional-Integral (PI) and fuzzy logic controllers. From the results, Fuzzy logic control was shown to achieve an adequate DC capacitor energy storage optimization, the sinusoidal type of the current and the change of the power factor. A low Total Harmonic Distortion (THD) that met the suggestions of IEEE- 519 standard on symphonious levels was achieved with the proposed method

Sentiment Analysis of Multilingual Dataset of Bahraini Dialects, Arabic, and English

Data Availability Statement: The dataset is openly available at: https://data.mendeley.com/datasets/5rhw2srzjj (accessed on 15 February 2023). Dataset: https://doi.org/10.17632/5rhw2srzjj.1 Dataset License: CC-BY-NC.Copyright © 2023 by the authors. Sentiment analysis is an application of natural language processing (NLP) that requires a machine learning algorithm and a dataset. In some cases, the dataset availability is scarce, particularly with Arabic dialects, precisely the Bahraini ones, which necessitates using an approach such as translation, where a rich source language is exploited to create the target language dataset. In this study, a dataset of Amazon product reviews in Bahraini dialects is presented. This dataset was generated using two cascading stages of translation—a machine translation followed by a manual one. Machine translation was applied using Google Translate to translate English Amazon product reviews into Standard Arabic. In contrast, the manual approach was applied to translate the resulting Arabic reviews into Bahraini ones by qualified native speakers utilizing constructed customized forms. The resulting parallel dataset of English, Standard Arabic, and Bahraini dialects is called English_Modern Standard Arabic_Bahraini Dialects product reviews for sentiment analysis “E_MSA_BDs-PR-SA”. The dataset is balanced, composed of 2500 positive and 2500 negative reviews. The sentiment analysis process was implemented using a stacked LSTM deep learning model. The Bahraini dialect product dataset can be utilized in the transfer learning process for sentimentally analyzing another dataset in Bahraini dialects.This research received no external funding

Biallelic mutations in valyl-tRNA synthetase gene VARS are associated with a progressive neurodevelopmental epileptic encephalopathy.

Aminoacyl-tRNA synthetases (ARSs) function to transfer amino acids to cognate tRNA molecules, which are required for protein translation. To date, biallelic mutations in 31 ARS genes are known to cause recessive, early-onset severe multi-organ diseases. VARS encodes the only known valine cytoplasmic-localized aminoacyl-tRNA synthetase. Here, we report seven patients from five unrelated families with five different biallelic missense variants in VARS. Subjects present with a range of global developmental delay, epileptic encephalopathy and primary or progressive microcephaly. Longitudinal assessment demonstrates progressive cortical atrophy and white matter volume loss. Variants map to the VARS tRNA binding domain and adjacent to the anticodon domain, and disrupt highly conserved residues. Patient primary cells show intact VARS protein but reduced enzymatic activity, suggesting partial loss of function. The implication of VARS in pediatric neurodegeneration broadens the spectrum of human diseases due to mutations in tRNA synthetase genes

Toward an Unsteady Aerodynamic ROM for Multiple Mach Regimes

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/97065/1/AIAA2012-1708.pd

Linear, Deterministic, and Order-Invariant Initialization Methods for the K-Means Clustering Algorithm

Over the past five decades, k-means has become the clustering algorithm of choice in many application domains primarily due to its simplicity, time/space efficiency, and invariance to the ordering of the data points. Unfortunately, the algorithm's sensitivity to the initial selection of the cluster centers remains to be its most serious drawback. Numerous initialization methods have been proposed to address this drawback. Many of these methods, however, have time complexity superlinear in the number of data points, which makes them impractical for large data sets. On the other hand, linear methods are often random and/or sensitive to the ordering of the data points. These methods are generally unreliable in that the quality of their results is unpredictable. Therefore, it is common practice to perform multiple runs of such methods and take the output of the run that produces the best results. Such a practice, however, greatly increases the computational requirements of the otherwise highly efficient k-means algorithm. In this chapter, we investigate the empirical performance of six linear, deterministic (non-random), and order-invariant k-means initialization methods on a large and diverse collection of data sets from the UCI Machine Learning Repository. The results demonstrate that two relatively unknown hierarchical initialization methods due to Su and Dy outperform the remaining four methods with respect to two objective effectiveness criteria. In addition, a recent method due to Erisoglu et al. performs surprisingly poorly.Comment: 21 pages, 2 figures, 5 tables, Partitional Clustering Algorithms (Springer, 2014). arXiv admin note: substantial text overlap with arXiv:1304.7465, arXiv:1209.196

Nipple sparing versus skin sparing mastectomy: a systematic review protocol.

Introduction Breast cancer has a lifetime incidence of one in eight women. Over the past three decades there has been a move towards breast conservation and a focus on aesthetic outcomes while maintaining oncological safety. For some patients, mastectomy is the preferred option. There is growing interest in the potential use of nipple sparing mastectomy (NSM). However, oncological safety remains unproven, and the benefits and indications have not been clearly identified. The objective of this systematic review will be to determine the safety and efficacy of NSM as compared with skin sparing mastectomy (SSM).Methods and analysis All original comparative studies including; randomised controlled trials, cohort studies and case-control studies involving women undergoing either NSM or SSM for breast cancer will be included. Outcomes are primary-relating to oncological outcomes and secondary-relating to clinical, aesthetic, patient reported and quality of life outcomes. A comprehensive electronic literature search, designed by a search specialist, will be undertaken. Grey literature searches will also be conducted. Eligibility assessment will occur in two stages; title and abstract screening and then full text assessment. Each step will be conducted by two trained teams acting independently. Data will then be extracted and stored in a database with standardised extraction fields to facilitate easy and consistent data entry. Data analysis will be undertaken to explore the relationship between NSM or SSM and preselected outcomes, heterogeneity will be assessed using the Cochrane tests.Ethics and dissemination This systematic review requires no ethical approval. It will be published in a peer-reviewed journal. It will also be presented at national and international conferences. Updates of the review will be conducted to inform and guide healthcare practice and policy