IDENTIFICATION OF ERRORS IN COTTON FIBER DATA SETS USING BAYESIAN NETWORKS

Cotton fiber is graded on a series of parameters based on physiological factors (strength, length, and thickness), lint color, and presence of non-lint matter such as leaves, stems or other foreign materials. Cotton lint is graded by the USDA-AMS after harvest and ginning, and the grade determines the price of the lint. Given the importance of cotton fiber quality to the value of the crop, the spatial variability of cotton fiber properties is of particular interest to researchers and producers in developing management scenarios for optimal profitability. Previous research studies have relied on hand-harvesting the cotton at intervals throughout the field to obtain a measure of the cotton fiber quality and the extent of spatial variability. However, hand-harvested cotton has different qualities than that harvested by machine and ginned in the large-scale production gins. Part of this arises from the difference in efficiency of harvest between machine and humans, and part results from the different gins used for the smaller sample sizes. While these studies have demonstrated the extent of spatial variability of fiber properties, handharvesting is not amenable to large-scale or production research efforts. Moreover, the differences in fiber properties limit the extension of the results to the production setting. We have developed a mechanism of sampling cotton from the cotton chute during mechanical harvest. The samples are then ginned on a research gin. This study was undertaken to develop a method of translating these small-scale researcher level results to full-scale production level results. The research reported here is the first step in that effort, and demonstrates the use of Bayesian networks to detect erroneous entries in cotton fiber data sets

Advances of new drugs bedaquiline and delamanid in the treatment of multi-drug resistant tuberculosis in children

Tuberculosis (TB) is a major public health problem, with nearly 10 million new cases and millions of deaths each year. Around 10% of these cases are in children, but only a fraction receive proper diagnosis and treatment. The spread of drug-resistant (DR) strain of TB has made it difficult to control, with only 60% of patients responding to treatment. Multi-drug resistant TB (MDR-TB) is often undiagnosed in children due to lack of awareness or under-diagnosis, and the target for children’s DR-TB treatment has only been met in 15% of goals. New medications such as bedaquiline and delamanid have been approved for treating DR-TB. However, due to age and weight differences, adults and children require different dosages. The availability of child-friendly formulations is limited by a lack of clinical data in children. This paper reviews the development history of these drugs, their mechanism of action, efficacy, safety potential problems and current use in treating DR-TB in children

Parallelizing an Immune-Inspired Algorithm for Efficient Pattern Recognition

mammalian immune system as a source of inspiration and metaphor for computational tasks. One avenue of this investigation has been the exploration of the learning capabilities demonstrated by these biological systems. A second appealing aspect of biological immune systems is their inherent distributedness

Modeling and Experimental Investigation of the Anode Inlet Relative Humidity Effect on a PEM Fuel Cell

External humidification has been used as a flexible water management strategy for the proton exchange membrane fuel cell (PEMFC). To study the anode inlet relative humidity (ARH) effect on the performance of PEMFC, the anode inlet water content (AIWC) model is established, including condensation rates and water activity. A comparable analysis between the AIWC model, Fluent model and experiment is conducted at 60 °C operating temperature, four different anode relative humidities (25%, 50%, 75% and 100%), and 100% cathode relative humidity (CRH). The species distributions of water content and hydrogen concentration are presented and analyzed. The results show the relative error of the voltage results derived from the AIWC model has been reduced by 3.2% (the original is 4.6% in the Fluent model) especially at 240 mA·cm−2 for 50% ARH. An increase in hydrogen humidity can improve the PEMFC output at low ARH (25% and 50%). Meanwhile, at high ARH (100%), the excess water produced does not play a positive role. At 50% ARH, the water content and hydrogen distribution are more uniform all over the anode channels

Modeling and Experimental Investigation of the Anode Inlet Relative Humidity Effect on a PEM Fuel Cell

External humidification has been used as a flexible water management strategy for the proton exchange membrane fuel cell (PEMFC). To study the anode inlet relative humidity (ARH) effect on the performance of PEMFC, the anode inlet water content (AIWC) model is established, including condensation rates and water activity. A comparable analysis between the AIWC model, Fluent model and experiment is conducted at 60 °C operating temperature, four different anode relative humidities (25%, 50%, 75% and 100%), and 100% cathode relative humidity (CRH). The species distributions of water content and hydrogen concentration are presented and analyzed. The results show the relative error of the voltage results derived from the AIWC model has been reduced by 3.2% (the original is 4.6% in the Fluent model) especially at 240 mA·cm−2 for 50% ARH. An increase in hydrogen humidity can improve the PEMFC output at low ARH (25% and 50%). Meanwhile, at high ARH (100%), the excess water produced does not play a positive role. At 50% ARH, the water content and hydrogen distribution are more uniform all over the anode channels

Identifying circRNA–miRNA–mRNA Regulatory Networks in Chemotherapy-Induced Peripheral Neuropathy

Chemotherapy-induced peripheral neuropathy (CIPN) is a frequent and severe side effect of first-line chemotherapeutic agents. The association between circular RNAs (circRNAs) and CIPN remains unclear. In this study, CIPN models were constructed with Taxol, while 134 differentially expressed circRNAs, 353 differentially expressed long non-coding RNAs, and 86 differentially expressed messenger RNAs (mRNAs) were identified utilizing RNA sequencing. CircRNA-targeted microRNAs (miRNAs) were predicted using miRanda, and miRNA-targeted mRNAs were predicted using TargetScan and miRDB. The intersection of sequencing and mRNA prediction results was selected to establish the circRNA–miRNA–mRNA networks, which include 15 circRNAs, 18 miRNAs, and 11 mRNAs. Functional enrichment pathway analyses and immune infiltration analyses revealed that differentially expressed mRNAs were enriched in the immune system, especially in T cells, monocytes, and macrophages. Cdh1, Satb2, Fas, P2ry2, and Zfhx2 were further identified as hub genes and validated by RT-qPCR, correlating with macrophages, plasmacytoid dendritic cells, and central memory CD4 T cells in CIPN. Additionally, we predicted the associated diseases, 36 potential transcription factors (TFs), and 30 putative drugs for hub genes using the DisGeNET, TRRUST, and DGIdb databases, respectively. Our results indicated the crucial role of circRNAs, and the immune microenvironment played in CIPN, providing novel insights for further research