Parenteral nutrition in oncologic patients]

A B16 melanoma-specific CD8+ T cell line (AB1) was established from the spleen cells of C57BL/6 mice cured of B16 melanoma with interleukin (IL)-12 treatment. The AB1 line exclusively used T cell receptor Vbeta11. The AB1 cells exhibited a cytolytic activity against both syngeneic B16 melanoma and allogeneic P815 mastocytoma, whereas a cold inhibition assay revealed specificity of the AB1 cells against B16 melanoma. Their lostability to kill a class I loss variant of B16 melanoma was restored by the transfection of H-2Kb gene. In addition, their interferon (IFN)-gamma production was significantly suppressed by the addition of anti-H-2Kb monoclonal antibody, and RT-PCR analysis showed that the AB1 line expressed the mRNA encoding IFN-gamma, but not IL-4 or IL-10. The experiment using synthetic peptides of tyrosinase-related protein-2 (TRP-2) revealed that the AB1 cells could recognize TRP-2(181-188) peptide. Moreover, the AB1 cells showed an in vivo antitumor effect against established pulmonary metastases of B16 melanoma. Overall, these results indicate that the Tc1-type Vbeta11+ AB1 cells exert an antitumor activity against syngeneic B16 melanoma through recognition of TRP-2(181-188) peptide in an H-2Kb-restricted manner.     

Implicit and hybrid methods for attribute weighting in multi-attribute decision-making: a review study

Artificial Intelligence Review - Attribute weighting is a task of paramount relevance in multi-attribute decision-making (MADM). Over the years, different approaches have been developed to face...     

Word sense disambiguation for spam filtering

Spam has become a major issue in computer security because it is a channel for threats such as computer viruses, worms, and phishing. More than 86% of received e-mails are spam. Historical approaches to combating these messages, including simple techniques such as sender blacklisting or the use of e-mail signatures, are no longer completely reliable. Many current solutions feature machine-learning algorithms trained using statistical representations of the terms that most commonly appear in such e-mails. However, these methods are merely syntactic and are unable to account for the underlying semantics of terms within messages. In this paper, we explore the use of semantics in spam filtering by introducing a pre-processing step of Word Sense Disambiguation (WSD). Based upon this disambiguated representation, we apply several well-known machine-learning models and show that the proposed method can detect the internal semantics of spam messages.     

Early-Life Development of the Bifidobacterial Community in the Infant Gut

The establishment of the gut microbiota poses implications for short and long-term health. Bifidobacterium is an important taxon in early life, being one of the most abundant genera in the infant intestinal microbiota and carrying out key functions for maintaining host-homeostasis. Recent metagenomic studies have shown that different factors, such as gestational age, delivery mode, or feeding habits, affect the gut microbiota establishment at high phylogenetic levels. However, their impact on the specific bifidobacterial populations is not yet well understood. Here we studied the impact of these factors on the different Bifidobacterium species and subspecies at both the quantitative and qualitative levels. Fecal samples were taken from 85 neonates at 2, 10, 30, 90 days of life, and the relative proportions of the different bifidobacterial populations were assessed by 16S rRNA–23S rRNA internal transcribed spacer (ITS) region sequencing. Absolute levels of the main species were determined by q-PCR. Our results showed that the bifidobacterial population establishment is affected by gestational age, delivery mode, and infant feeding, as it is evidenced by qualitative and quantitative changes. These data underline the need for understanding the impact of perinatal factors on the gut microbiota also at low taxonomic levels, especially in the case of relevant microbial populations such as Bifidobacterium. The data obtained provide indications for the selection of the species best suited for the development of bifidobacteria-based products for different groups of neonates and will help to develop rational strategies for favoring a healthy early microbiota development when this process is challenged.     

The Utility of Land-Surface Model Simulations to Provide Drought Information in a Water Management Context Using Global and Local Forcing Datasets

Drought diagnosis and forecasting are fundamental issues regarding hydrological management in Spain, where recurrent water scarcity periods are normal. Land-surface models (LSMs) could provide relevant information for water managers on how drought conditions evolve. Here, we explore the usefulness of LSMs driven by atmospheric analyses with different resolutions and accuracies in simulating drought and its propagation to precipitation, soil moisture and streamflow through the system. We perform simulations for the 1980-2014 period with SASER (5 km resolution) and LEAFHYDRO (2.5 km resolution), which are forced by the Spanish SAFRAN dataset (at 5km and 30km resolutions), and the global eartH2Observe datasets at 0.25 degrees (including the MSWEP precipitation dataset). We produce standardized indices for precipitation (SPI), soil moisture (SSMI) and streamflow (SSI). The results show that the model structure uncertainty remains an important issue in current generation large-scale hydrological simulations based on LSMs. This is true for both the SSMI and SSI. The differences between the simulated SSMI and SSI are large, and the propagation scales for drought regarding both soil moisture and streamflow are overly dependent on the model structure. Forcing datasets have an impact on the uncertainty of the results but, in general, this impact is not as large as the uncertainty due to model formulation. Concerning the global products, the precipitation product that includes satellite observations (MSWEP) represents a large improvement compared with the product that does not.

     

Designing biomass supply chains within planetary boundaries

The design of sustainable supply chains, which recently emerged as an active area of research in process systems engineering, is vital to ensure sustainable development. Despite past and ongoing efforts, the available methods often overlook impacts beyond climate change or incorporate them via standard life cycle assessment metrics that are hard to interpret from an absolute sustainability viewpoint. We here address the design of biomass supply chains considering critical ecological limits of the Earth—planetary boundaries—which should never be surpassed by anthropogenic activities. Our method relies on a mixed-integer linear program that incorporates a planetary boundaries-based damage model to quantify absolute sustainability precisely. We apply this approach to the sugarcane-to-ethanol industry in Argentina, identifying the optimal combination of technologies and network layout that minimize the impact on these ecological boundaries. Our framework can find applications in a wide range of supply chain problems related to chemicals and fuels production, energy systems, and agriculture planning.     

Mechanochemical tuning of molecular weight distribution of styrene homopolymers as postpolymerization modification in solvent-free solid-state

Mechanochemical degradation by planetary ball milling (PM) is used for postpolymerization modification of styrene homopolymers (PS). A complete factorial design was chosen to study the effect of radical scavengers, milling time, initial molecular weight, and revolution radius (R_p), on the shape of molecular weight distributions (MWDs) of PS. Size-exclusion chromatography analysis shows the feasibility of fine-tuning MWD of PS at up to 40% conversion. Distributions ranged from unimodal to bimodal in a PM with R_p = 150 mm at different stage of milling, whereas in a PM with R_p of 60.8 mm the adjustment of unimodal distributions is achieved. Initial polydispersity is more important to develop bimodal distributions when compared with initial molecular weight. Fourier transform infrared and X-ray electron spectrometry analysis show some suppression of PS degradation and complete oxidation inhibition of macromolecular radicals with the incorporation of radical scavengers, which we considered as additional aids when adjusting the MWDs.     

A Robust Controller for A 3‐DOF Flexible Robot with a Time Variant Payload

This article describes a new control scheme designed for a three degree of freedom (3‐DOF) flexible robot. The control scheme consists of two multi variable control loops. The inner loop is the motor's position control system, while the outer loop controls the robot tip's position, thus canceling vibrations which are originated by the structural flexibility of the manipulator during movement. As it will be shown, the outer control loop is robust to payload variations. The outer loop performance is based on a perfect cancelation of the inner loop dynamics. The effects of not achieving such perfect cancelation are also studied, and rules for designing a robust controller in this case are developed. Simulations assuming different payloads have been carried out with successful results for trajectory tracking. Trajectory tracking with a variable payload is also achieved.     

Long short-term cognitive networks

Neural Computing and Applications - In this paper, we present a recurrent neural system named long short-term cognitive networks (LSTCNs) as a generalization of the short-term cognitive network...