Spanish Melon Landraces: Revealing Useful Diversity by Genomic,Morphological, and Metabolomic Analysis

Spain is a secondary centre of the diversification of the melon (Cucumis melo L.), with high diversity represented in highly appreciated landraces belonging to the Flexuosus and Ibericus groups. A collection of 47 accessions of Flexuosus, Chate, Piel de Sapo, Tendral, Amarillo, Blanco, and Rochet was analysed using a genotyping-by-sequencing (GBS) approach. A total of 66,971 quality SNPs were identified. Genetic analysis differentiated Ibericus accessions and exotic materials (Ameri, Momordica, Kachri, and Agrestis), while Flexuous accessions shared ancestry between them. Within the Ibericus group, no clear genomic distinction could be identified for the different landraces evaluated, with accessions of different landraces showing high genetic similarity. The morphological characterization confirmed that the external colour and fruit shape had been used as recognition patterns for Spanish melon landraces, but variability within a landrace exists. Differences were found in the sugars and acid and volatile profiles of the materials. Flexuosus and Chate melons at the immature commercial stage accumulated malic acid and low levels of hexoses, while Ibericus melons accumulated high contents of sucrose and citric acid. Specific trends could be identified in the Ibericus landraces. Tendral accumulated low levels of sugars and citric acid and high of malic acid, maintaining higher firmness, Rochet reached higher levels of sugars, and Amarillo tended to lower malic acid contents. Interestingly, high variability was found within landraces for the acidic profile, offering possibilities to alter taste tinges. The main volatile organic compounds (VOCs) in Flexuosus and Chate were aldehydes and alcohols, with clear differences between both groups. In the Ibericus landraces, general trends for VOC accumulation could be identified, but, again, a high level of variation exists. This situation highlights the necessity to develop depuration programs to promote on-farm in situ conservation and, at the same time, offers opportunities to establish new breeding program targets and to take advantage of these sources of variation.     

Systematic Review: Drug Repositioning for Congenital Disorders of Glycosylation (CDG)

Advances in research have boosted therapy development for congenital disorders of glycosylation (CDG), a group of rare genetic disorders affecting protein and lipid glycosylation and glycosylphosphatidylinositol anchor biosynthesis. The (re)use of known drugs for novel medical purposes, known as drug repositioning, is growing for both common and rare disorders. The latest innovation concerns the rational search for repositioned molecules which also benefits from artificial intelligence (AI). Compared to traditional methods, drug repositioning accelerates the overall drug discovery process while saving costs. This is particularly valuable for rare diseases. AI tools have proven their worth in diagnosis, in disease classification and characterization, and ultimately in therapy discovery in rare diseases. The availability of biomarkers and reliable disease models is critical for research and development of new drugs, especially for rare and heterogeneous diseases such as CDG. This work reviews the literature related to repositioned drugs for CDG, discovered by serendipity or through a systemic approach. Recent advances in biomarkers and disease models are also outlined as well as stakeholders’ views on AI for therapy discovery in CDG.     

A cost-effective heuristic to schedule local and remote memory in cluster computers

Cluster computers represent a cost-effective alternative solution to supercomputers. In these systems, it is common to constrain the memory address space of a given processor to the local motherboard. Constraining the system in this way is much cheaper than using a full-fledged shared memory implementation among motherboards. However, memory usage among motherboards can be unfairly balanced.     

Less cyber,more café: Enhancing existing small businesses across the digital divide with ICTs

About 10% of the world has access to information and communication technologies (ICTs). Telecenters and cyber cafés are one prevalent way to increase access. This paper suggests increasing access through currently existing, local businesses where people already gather and where proprietors already posses existing business relationships with suppliers and customers. This paper questions the prevailing emphasis on the “cyber'' characteristics of access, e.g., computing and internet access as is currently known, and attempts to refocus the conversation by considering computing and access in the context of the “café,” e.g., as public life in the sense of Habermas, which permits an in situ evolution of relevant access. This analysis is based on extant literature and direct ethnographic research in several public places in six countries. We offer example design perspectives based on a reflection of “third places” as inspiration for appropriate innovation in the provision of computing and communications. © 2005 Wiley Periodicals, Inc.     

Evaluating content quality and helpfulness of online product reviews: The interplay of review helpfulness vs. review content

Online reviews have received much attention recently in the literature, as their visibility has been proven to play an important role during the purchase process. Furthermore, recent theoretical insight argue that the votes casted on how helpful an online review is (review helpfulness) are of particular importance, since they constitute a focal point for examining consumer decision making during the purchase process. In this paper, we explore the interplay between online review helpfulness, rating score and the qualitative characteristics of the review text as measured by readability tests. We construct a theoretical model based on three elements: conformity, understandability and expressiveness and we investigate the directional relationship between the qualitative characteristics of the review text, review helpfulness and the impact of review helpfulness on the review score. Furthermore, we examine whether this relation holds for extreme and moderate review scores. To validate this model we applied four basic readability measures to a dataset containing 37,221 reviews collected from Amazon UK, in order to determine the relationship between the percentage of helpful votes awarded to a review and the review text’s stylistic elements. We also investigated the interrelationships between extremely helpful and unhelpful reviews, as well as absolutely positive and negative reviews using intergroup comparisons. We found that review readability had a greater effect on the helpfulness ratio of a review than its length; in addition, extremely helpful reviews received a higher score than those considered less helpful. The present study contributes to the ever growing literature on on-line reviews by showing that readability tests demonstrate a directional relationship with average length reviews and their helpfulness and that this relationship holds both for moderate and extreme review scores.     

Deforming Time in a Nonadditive Discount Function

The aim of this paper is to present a methodology to generate a partially subadditive (respectively superadditive) discount function starting from an entirely subadditive (respectively superadditive) discount model. To do this, we are going to use the concept of deformation of time in a discount function, focusing on Stevens' power law. A deformation of time is a function that mathematically represents the perception from an individual or a group of individuals about how the calendar time evolves. This approach will be important when describing the treatment of addictions and other diseases in patients who show a certain degree of impulsivity in their intertemporal choice.     

Determination of Thermoelectric Module Efficiency: A Survey

The development of thermoelectrics (TE) for energy conversion is in the transition phase from laboratory research to device development. There is an increasing demand to accurately determine the module efficiency, especially for the power generation mode. For many TE, the figure of merit, ZT, of the material sometimes cannot be fully realized at the device level. Reliable efficiency testing of thermoelectric modules is important to assess the device ZT and provide end-users with realistic values for how much power can be generated under specific conditions. We conducted a general survey of efficiency testing devices and their performance. The results indicated a lack of industry standards and test procedures. This study included a commercial test system and several laboratory systems. Most systems are based on the heat flow meter method, and some are based on the Harman method. They are usually reproducible in evaluating thermoelectric modules. However, different systems often showed large differences that are likely caused by uncertain heat loss and thermal resistance. Efficiency testing is an important capability for the thermoelectric community to improve. A follow-up international standardization effort is planned.     

Higher-Order Adaptive Finite Difference Methods for Fully Nonlinear Elliptic Equations

We introduce generalised finite difference methods for solving fully nonlinear elliptic partial differential equations. Methods are based on piecewise Cartesian meshes augmented by additional points along the boundary. This allows for adaptive meshes and complicated geometries, while still ensuring consistency, monotonicity, and convergence. We describe an algorithm for efficiently computing the non-traditional finite difference stencils. We also present a strategy for computing formally higher-order convergent methods. Computational examples demonstrate the efficiency, accuracy, and flexibility of the methods.     

STATISTICAL LINGUISTIC LAWS IN ECOLOGICAL MODELS

This paper gives the theoretical setup so that an ecological model, as a particular mathematical model, can be considered a text written in a formal language (mathematics), and therefore, statistical linguistic laws can be applied to obtain information parameters in different semantic levels of the same model. The statistical laws will be useful to: a) compare semantic levels, submodels, and different models mutually; b) prove that information temperature parameter is an indirect measure of meaning: the significance or semantic component of information, opposed to significant, or comprehension, on the part of the observer (modeller) of the model text. We will apply these ideas in two practical examples.