Covariance-adjusted, sparse, reduced-rank regression with adjustment for confounders

There is evidence that common genetic variation in the gene NEDD9 is associated with developing Alzheimer’s Disease (AD). In this project, we study the relationship between brain-imaging biomarkers of AD and the gene NEDD9 while adjusting for the effects of genetic population structure. The data used in this project, collected by the Alzheimer’s Disease Neuroimaging Initiative (ADNI), consists of magnetic resonance imaging (MRI) measures of 56 brain regions of interest for 200 cognitively normal people and genetic data on Single Nucleotide Polymorphisms (SNPs) obtained from 33 candidate genes for AD. The standard solution to such a multiple response problem is separate simple linear regression models. Such an approach neglects correlations between 56 brain areas and possible sparsity in the SNP effects. In this project, we review a sparse and covariance adjusted reduced-rank regression approach that can select significant predictors and estimate covariance simultaneously, and extend the approach to adjust for confounding variables. We apply the proposed algorithm to the ADNI data, and also simulated data

A review on the present situation of wastewater treatment in textile industry with membrane bioreactor and moving bed biofilm reactor

Membrane bioreactor (MBR) is one of the advanced treatment technologies used in industrial wastewater treatment due to its various advantages over conventional biological processes. Recently, the application of MBR in treatment of textile wastewater has increased significantly with an effective removal of contaminants. Moving bed bioreactor (MBBR) has been efficiently used for the treatment of different municipal and industrial wastewater during the last decades and it is a relatively novel and effective technology applied in textile wastewater treatment. This review paper presents the situation of MBR and MBBR technology for textile wastewater purification under different conditions and collates results of previous studies during the past years about MBR and MBBR treatment technologies used in textile processes. Both of these two technologies have shown their efficiency, but they still have problems in textile wastewater treatment. To this end, MBR-MBBR hybrid system could be an attractive solution for textile wastewater purification because of the high efficiency and low consumption of energy and spacePostprint (author's final draft

Reduction of Cost and Environmental Impact in the Treatment of Textile Wastewater Using a Combined MBBR-MBR System

A hybrid Moving Bed Biofilm Reactor—Membrane Bioreactor (MBBR-MBR) was developed for the treatment of wastewater from a Spanish textile company. Compared with conventional activated sludge (CAS) treatment, the feasibility of this hybrid system to reduce economic and environmental impact on an industrial scale was conducted. The results showed that, technically, the removal efficiency of COD, TSS and color reached 93%, 99% and 85%, respectively. The newly dyed fabrics performed with the treated wastewater were qualified under the standards of the textile industry. Economically, the values of Capital Expenditure (CAPEX) calculated for the hybrid MBBR-MBR system are profitable because of the reduction in Operational Expenditure (OPEX) when compared with CAS treatment, due to the lower effluent discharge tax thanks to the higher quality of the effluent and the decolorizing agent saved. The result of Net Present Value (NPV) and the Internal Rate of Return (IRR) of 18% suggested that MBBR-MBR is financially applicable for implantation into the industrial scale. The MBBR-MBR treatment also showed lower environmental impacts than the CAS process in the life cycle assessment (LCA) study, especially in the category of climate change, thanks to the avoidance of using extra decolorizing agent, a synthetic product based on a triamine.This study is co-funded by ACCIÓ (Generalitat de Catalunya, Spain) within the REGIREU Project (COMRDI16-1-0062). The preliminary results of this study were presented at the II International Congress on Water and Sustainability, 24–26 March 2021, Terrassa, Barcelona, Spain. This work was selected by the scientific committee to assume the article processing charges (APC) of publishing it in an open access journal.Peer ReviewedObjectius de Desenvolupament Sostenible::6 - Aigua Neta i SanejamentObjectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPostprint (published version

A Kind of Nanofluid Consisting of Surface-Functionalized Nanoparticles

A method of surface functionalization of silica nanoparticles was used to prepare a kind of stable nanofluid. The functionalization was achieved by grafting silanes directly to the surface of silica nanoparticles in silica solutions (both a commercial solution and a self-made silica solution were used). The functionalized nanoparticles were used to make nanofluids, in which well-dispersed nanoparticles can keep good stability. One of the unique characteristics of the nanofluids is that no deposition layer forms on the heated surface after a pool boiling process. The nanofluids have applicable prospect in thermal engineering fields with the phase-change heat transfer

Biogeography of the Japanese Gourmet Fungus, Tricholoma matsutake: A Review of the Distribution and Functional Ecology of Matsutake

Tricholoma matsutake (S. Ito & S. Imai) Singer is an ectomycorrhizal basidiomycete that produces highly prized mushrooms known as ‘true matsutake’. Recent research has shown that T. matsutake has a wide but patchy distribution in temperate and boreal forests of Eurasia and subtropical China in association with Pinus, Picea, Tsuga, Abies and even fagaceous broadleaves. Molecular analyses of the microbial communities living in shiro soil have been made in certain locations, but their generality has yet to be determined systematically and across the entire range. Variation in fruiting in relation to climate and geography has improved our understanding of matsutake phenology, and important in-roads have been made into its ecology over the past 15 years. T. matsutake is a commercially-important fungal species that plays a significant role in the functional diversity of forests in the Northern Hemisphere, but much remains to be learned about this enigmatic taxon.Peer reviewe

A design of resonant inelastic X-ray scattering (RIXS) spectrometer for spatial- and time-resolved spectroscopy.

The optical design of a Hettrick-Underwood-style soft X-ray spectrometer with Wolter type 1 mirrors is presented. The spectrometer with a nominal length of 3.1 m can achieve a high resolving power (resolving power higher than 10000) in the soft X-ray regime when a small source beam (<3 µm in the grating dispersion direction) and small pixel detector (5 µm effective pixel size) are used. Adding Wolter mirrors to the spectrometer before its dispersive elements can realize the spatial imaging capability, which finds applications in the spectroscopic studies of spatially dependent electronic structures in tandem catalysts, heterostructures, etc. In the pump-probe experiments where the pump beam perturbs the materials followed by the time-delayed probe beam to reveal the transient evolution of electronic structures, the imaging capability of the Wolter mirrors can offer the pixel-equivalent femtosecond time delay between the pump and probe beams when their wavefronts are not collinear. In combination with some special sample handing systems, such as liquid jets and droplets, the imaging capability can also be used to study the time-dependent electronic structure of chemical transformation spanning multiple time domains from microseconds to nanoseconds. The proposed Wolter mirrors can also be adopted to the existing soft X-ray spectrometers that use the Hettrick-Underwood optical scheme, expanding their capabilities in materials research

Steric trapping reveals a cooperativity network in the intramembrane protease GlpG.

Membrane proteins are assembled through balanced interactions among proteins, lipids and water. Studying their folding while maintaining the native lipid environment is necessary but challenging. Here we present methods for analyzing key elements of membrane protein folding including thermodynamic stability, compactness of the unfolded state and folding cooperativity under native conditions. The methods are based on steric trapping, which couples the unfolding of a doubly biotinylated protein to the binding of monovalent streptavidin (mSA). We further advanced this technology for general application by developing versatile biotin probes possessing spectroscopic reporters that are sensitized by mSA binding or protein unfolding. By applying these methods to the Escherichia coli intramembrane protease GlpG, we elucidated a widely unraveled unfolded state, subglobal unfolding of the region encompassing the active site, and a network of cooperative and localized interactions to maintain stability. These findings provide crucial insights into the folding energy landscape of membrane proteins

Skeleton-of-Thought: Large Language Models Can Do Parallel Decoding

This work aims at decreasing the end-to-end generation latency of large language models (LLMs). One of the major causes of the high generation latency is the sequential decoding approach adopted by almost all state-of-the-art LLMs. In this work, motivated by the thinking and writing process of humans, we propose "Skeleton-of-Thought" (SoT), which guides LLMs to first generate the skeleton of the answer, and then conducts parallel API calls or batched decoding to complete the contents of each skeleton point in parallel. Not only does SoT provide considerable speed-up (up to 2.39x across 11 different LLMs), but it can also potentially improve the answer quality on several question categories in terms of diversity and relevance. SoT is an initial attempt at data-centric optimization for efficiency, and reveal the potential of pushing LLMs to think more like a human for answer quality.Comment: Technical report, work in progres