Reduction Approach Research Articles

An individual-based dynamic model to assess interventions to mitigate opioid overdose risk

BackgroundIllicit opioid overdose continues to rise in North America and is a leading cause of death. Mathematical modeling is a valuable tool to investigate the epidemiology of this public health issue, as it can characterize key features of population outcomes and quantify the broader effect of structural and interventional changes on overdose mortality. The aim of this study is to quantify and predict the impact of key harm reduction strategies at differing levels of scale-up on fatal and nonfatal overdose among a population of people engaging in unregulated opioid use in Toronto.MethodsAn individual-based model for opioid overdose was built featuring demographic and behavioural variation among members of the population. Key individual attributes known to scale the risk of fatal and nonfatal overdose were identified and incorporated into a dynamic modeling framework, wherein every member of the simulated population encompasses a set of distinct characteristics that govern demographics, intervention usage, and overdose incidence. The model was parametrized to fatal and nonfatal overdose events reported in Toronto in 2019. The interventions considered were opioid agonist therapy (OAT), supervised consumption sites (SCS), take-home naloxone (THN), drug-checking, and reducing fentanyl in the drug supply. Harm reduction scenarios were explored relative to a baseline model to examine the impact of each intervention being scaled from 0% use to 100% use on overdose events.ResultsModel simulations resulted in 3690.6 nonfatal and 295.4 fatal overdoses, coinciding with 2019 data from Toronto. From this baseline, at full scale-up, 290 deaths were averted by THN, 248 from eliminating fentanyl from the drug supply, 124 from SCS use, 173 from OAT, and 100 by drug-checking services. Drug-checking and reducing fentanyl in the drug supply were the only harm reduction strategies that reduced the number of nonfatal overdoses.ConclusionsWithin a multi-faceted harm reduction approach, scaling up take-home naloxone, and reducing fentanyl in the drug supply led to the largest reduction in opioid overdose fatality in Toronto. Detailed model simulation studies provide an additional tool to assess and inform public health policy on harm reduction.

A Novel Fabrication of Hematite Nanoparticles via Recycling of Titanium Slag by Pyrite Reduction Technology.

An enormous quantity of titanium slag has caused not merely serious environment pollution, but also a huge waste of iron and sulfur resources. Hence, recycling iron and sulfur resources from titanium slag has recently been an urgent problem. Herein, hematite nanoparticles were fabricated through a pyrite reduction approach using as-received titanium slag as the iron source and pyrite as the reducing agent in an nitrogen atmosphere. The physicochemical properties of the hematite nanoparticles were analyzed using multiple techniques such as X-ray diffraction pattern, ultraviolet-visible spectrophotometry, and scanning electron microscopy. The best synthesis conditions for hematite nanoparticles were found at 550 °C for 30 min with the mass ratio of 14:1 for titanium slag and pyrite. The results demonstrated that hematite nanoparticles with an average particle diameter of 45 nm were nearly spherical in shape. The specific surface area, pore volume, and pore size estimated according to the BET method were 19.6 m2/g, 0.117 cm3/g, and 0.89 nm, respectively. Meanwhile, the fabricated hematite nanoparticles possessed weak ferromagnetic behavior and good absorbance in the wavelength range of 200 nm-600 nm, applied as a visible light responsive catalyst. Consequently, these results show that hematite nanoparticles formed by the pyrite reduction technique have a promising application prospect for magnetic material and photocatalysis.

Exploratory factor analysis for machining error data of compressor blades based on dimensionality-reduced statistical analysis method

Abstract Various machining errors inevitably occur on aero-engine compressor blades, including leading-edge contour error, trailing-edge contour error, camber contour error, and more. The current complexity surrounding the numerous ma-chining error types and their obscure interrelationships imposes immense effort for aerodynamic analysis and hin-ders overall error control. Thus, elucidating error correlations to achieve error dimensionality reduction is imperative. This study pioneers a dimensionality reduction approach via factor analysis to conduct a comprehensive statistical analysis of 13 types of blade machining errors. The proposed technique can categorize the 13 errors into three groups, each dominated by a distinct common factor. To validate the accuracy of the extracted factors, the factor scores of the three identified latent factors are computed. Cluster analysis is then performed on the factor scores, and the clustering results are visualized by t-Distributed Stochastic Neighbor Embedding (t-SNE). Furthermore, boot-strap resampling establishes the 95% confidence intervals for the factor scores. Capitalizing on the grouping struc-ture uncovered by factor analysis, multiple linear regression models are built for the errors within each group, and then, a preliminary conjecture is made about the potential key error types for each group of errors based on the re-gression coefficients. This hypothesis is then evidenced by the statistical analysis of cross-section profile error data of 28 blades. The present work can not only optimize machining processes but also relax tolerance requirements and diminish the effort of aerodynamic analysis.

Valorizing polymeric wastes and biomass through optimized co-pyrolysis for upgraded pyrolysis oil: A study on TG-FTIR and fixed bed reactor

The co-pyrolysis of biomass and polymeric wastes offers a promising approach for waste reduction and valuable product recovery while decreasing fossil fuel dependence. This study aimed to investigate the synergistic effects of blending waste tire (WT) or polystyrene (PS) with sawdust (SD) at varying effective hydrogen/carbon ratio (H/Ceff) on liquid product distribution. Thermal degradation behavior was analyzed using TGA-FTIR, followed by fixed-bed reactor pyrolysis experiments at different temperatures. The devolatilization of SD primarily occurred between 185 and 390°C, while WT and PS decomposed between 250 and 500°C and 350–460°C, respectively. Results showed that SD addition to WT accelerated degradation at lower temperatures. Optimal H/Ceff ratios were 0.42 for WT/SD and 0.64 for PS/SD blends at 500°C, maximizing valued hydrocarbons, reducing pollutants, and yielding the highest liquid fraction. TGA-FTIR analysis revealed the presence of various functional groups, including C-H, CC, CO2, and O-H. The pyrolytic oil showed improved stability with significantly fewer undesired compounds. This research provides theoretical and practical insights into the control and application potential as well as the limitations of high-value energy products derived from the co-pyrolysis of SD, WT, and PS.

GWAS-Identified Loci are Associated with Obesity and Type 2 Diabetes Mellitus in Patients with Severe COVID-19.

Comorbidities such as obesity and type 2 diabetes mellitus (T2DM) have emerged as critical risk factors exacerbating the severity and mortality of COVID-19. Meanwhile, numerous genome-wide association studies (GWAS) have identified single nucleotide polymorphisms (SNPs) associated with increased susceptibility to severe COVID-19. This study investigated whether SNPs previously identified by GWAS as risk factors for severe COVID-19 also correlate with common comorbidities-obesity and T2DM-in hospitalized patients with severe COVID-19. DNA samples from 199 hospitalized COVID-19 patients were genotyped using probe-based PCR for 10 GWAS SNPs previously implicated in severe COVID-19 outcomes (rs143334143 CCHCR1, rs111837807 CCHCR1, rs17078346 SLC6A20-LZTFL1, rs17713054 SLC6A20-LZTFL1, rs7949972 ELF5, rs61882275 ELF5, rs12585036 ATP11A, rs67579710 THBS3, THBS3-AS1, rs12610495 DPP9, rs9636867 IFNAR2). The analysis revealed significant associations between certain SNPs and the increased risk of obesity and T2DM in severe COVID-19 patients. Specifically, rs17713054 SLC6A20-LZTFL1 (risk allele A; odds ratio (OR) = 2.34, 95% confidence interval (CI) = 1.24-4.4, p = 0.007) and rs7949972 ELF5 SNP (risk allele T; OR = 1.79, 95% CI = 1.11-2.91, p = 0.015) were associated with increased risk of obesity. SNP rs9636867 IFNAR2 was associated with a higher risk of T2DM (risk allele G, OR = 8.28, 95% CI = 1.69-40.64, p = 0.027). Using the model-based multifactor dimensionality reduction (MB-MDR) approach, the six most significant gene-gene interaction patterns associated with obesity in severe COVID-19 patients were identified and included five polymorphic loci: rs7949972, rs17713054, rs61882275, rs12585036, and rs143334143, participating in two or more of the most significant G-G interactions (pperm < 0.05). In total, the best models of G-G interactions associated with T2DM in patients with severe COVID-19 included eight polymorphic loci, six of which, rs7949972, rs61882275, rs12585036, rs143334143, rs67579710, and rs12610495, were involved in two or more of the most significant G-G interactions. Our study provides novel insights into the genetic associations between GWAS-identified SNPs and the risk of obesity and T2DM in patients with severe COVID-19.

Synthesis and characterization of Ag/Cu dual-metal-functionalized porous Bi2WO6 microsphere with enhanced N2 photofixation

Semiconductor photocatalytic nitrogen reduction reaction (PNRR) stands as a promising clean technique for ammonia synthesis, yet it confronts numerous challenges. In this study, Ag nanoparticle-modified Cu-doped Bi2WO6 (ACB) porous composite materials with varying mass percentages were successfully synthesized using a solvothermal reduction approach. The incorporation of transition metal Cu effectively modulates the energy band position of Bi2WO6. Furthermore, the introduction of Ag nanoparticles significantly suppresses the recombination of photogenerated carriers. Without adding sacrificial agent, the photocatalytic nitrogen fixation yield of ACB reaches an impressive 184.93 μmol·g−1·h−1, which is 5.44 times higher than that of pristine Bi2WO6. A comprehensive analysis of the experimental results reveals that the combined effect of Cu doping and Ag nanoparticle loading endows ACB with an increased exposure of active sites, thereby significantly enhancing its photocatalytic nitrogen fixation performance. This research offers a promising approach for the design of metal nanoparticle-supported catalysts for PNRR, holding significant implications for the advancement of other material systems.

Promising non-model microbial cell factories obtained by genome reduction.

The development of sustainable processes is the most important basis to realize the shift from the fossil-fuel based industry to bio-based production. Non-model microbes represent a great resource due to their advantageous traits and unique repertoire of bioproducts. However, most of these microbes require modifications to improve their growth and production capacities as well as robustness in terms of genetic stability. For this, genome reduction is a valuable and powerful approach to meet industry requirements and to design highly efficient production strains. Here, we provide an overview of various genome reduction approaches in prokaryotic microorganisms, with a focus on non-model organisms, and highlight the example of a successful genome-reduced model organism chassis. Furthermore, we discuss the advances and challenges of promising non-model microbial chassis.

Novel approach for weight reduction after Roux-en-Y gastric bypass with weight regain: a combination of Bariatric Anastomotic Reduction System with tubularization of residual gastric pouch

Novel approach for weight reduction after Roux-en-Y gastric bypass with weight regain: a combination of Bariatric Anastomotic Reduction System with tubularization of residual gastric pouch

Association between MAPK and PI3K/Akt signaling pathway-related gene polymorphisms and migraine.

The causes of migraine remain unclear. Evidence suggests that the MAPK and PI3K/Akt signaling pathways play a role in migraine pathogenesis. However, studies on genetic polymorphisms in the two pathways associated with migraine are still limited. This study included 226 migraineurs and 452 age- and sex-matched nonmigraine control individuals. Genotyping of 31 Single Nucleotide Polymorphisms (SNPs) in 21 genes was performed. The relationship between migraine and gene polymorphisms was analyzed by using logistic regression. SNP-SNP interactions were examined by a generalized multifactor dimension reduction (GMDR) approach. The possible role of SNPs was evaluated with gene expression data from the GTEx database. The RASGRP2-rs2230414 GT genotype was associated with decreased migraine risk compared with the wild-type GG genotype [ORadj (95% CI): 0.674(0.458-0.989)]. PIK3R1-rs3730089 was associated with migraine in the recessive model [ORadj (95% CI): 1.446(1.004-2.083)]. The CACNA1H-rs61734410 CT genotype was associated with migraine risk [ORadj (95% CI): 1.561(1.068-2.281)]. One significant two-way SNP-SNP interaction was found (PRKCA rs2228945-BDNF rs6265) (p = 0.0107). Significant eQTL and sQTL signals were observed for the SNP rs2230414. This is the first study to systematically reveal significant associations between MAPK and PI3K/Akt signaling pathway-related gene polymorphisms and migraine risk.

Operant ethanol self-administration behaviors do not predict sex differences in continuous access home cage drinking

Understanding sex differences in disease prevalence is critical to public health, particularly in the context of alcohol use disorder (AUD). The goal of this study was to understand sex differences in ethanol drinking behavior and define the precise conditions under which sex differences emerge. Consistent with prior work, C57BL/6J females drank more than males under continuous access two-bottle choice conditions. However, using ethanol self-administration - where an operant response results in access to an ethanol sipper for a fixed time period - we found no sex differences in operant response rates or ethanol consumption (volume per body weight consumed, as well as lick behavior). This remained true across a wide range of parameters including acquisition, when the ethanol sipper access period was manipulated, and when the concentration of the ethanol available was scaled. The only sex differences observed were in total ethanol consumption, which was explained by differences in body weight between males and females, rather than by sex differences in motivation to drink. Using dimensionality reduction approaches, we found that drinking behavior in the operant context did not cluster by sex, but rather clustered by high and low drinking phenotypes. Interestingly, these high and low drinking phenotypes in the operant context showed no correlation with those same categorizations in the home cage context within the same animals. These data underscore the complexity of sex differences in ethanol consumption, highlighting the important role that drinking conditions/context plays in the expression of these differences.

How Social Workers Can Be Deployed to Assist with the Ongoing Opioid Crisis.

The opioid epidemic has claimed more than 1 million lives in the United States over the past two decades. The persistent increase in deaths indicates that current strategies intended to decrease the negative consequences of opioid use are inadequate. Harm reduction strategies are designed to promote safer substance usage and reduce overdose mortality rates, yet the implementation of harm reduction programs is inhibited by community- and provider-level stigma against people who use opioids, coupled with limited understanding and insufficient education about harm reduction approaches. Despite ongoing research, engagement in opioid treatment programs remains a challenge, and the opioid crisis continues to disproportionately harm marginalized populations. This article describes how social workers are prepared to play a larger role in opioid use treatment because they are trained with the skill set and values necessary to facilitate access to harm reduction programs, promote engagement in substance use treatment, and create and advocate for interventions to address problematic substance use, especially in high-need communities.

SnS/C nanostructures endowed by low-temperature in-situ carbothermal reduction of sustainable lignin for stable lithium- and sodium-ion storage

SnS emerges as a promising anode candidate for high-energy–density lithium/sodium-ion batteries, attributed to its substantial theoretical capacity of 1022 mAh/g. However, its practical application faces challenges stemming from intrinsic low conductivity and substantial volume variation during lithium/sodium intercalation and deintercalation processes. To address these limitations, we present a cost-effective hydrothermal synthesis combined with an in-situ carbothermal reduction approach for fabricating a nanoflower-like porous carbon-wrapped SnS (SnS/C NFs) anode. The porous carbon shell mitigates the volume expansion of SnS and enhances electronic/ionic conductivity, owing to the porous structure and formation of C-S-C bonds. The SnS/C NFs anode delivered excellent rate performance and long-term cycling stability with high specific capacity both in LIBs (1120 mAh/g after 1000 cycles at 1 A/g) and SIBs (399.3 mAh/g after 500 cycles at 1 A/g). This work provides a safe and low-cost approach for next-generation advanced LIBs and SIBs anodes.

Evanescent field engineering to reduce cross-talk in pattern-free suspended graphene-based plasmonic waveguides using nano-strips

Suppression of the cross-talk between neighboring photonic components has been considered one of the most efficient methods for increasing the packing density of photonic integrated circuits. In this study, an effective cross-talk reduction approach is developed for plasmonic waveguides. Firstly, the mode characteristics of the waveguide are investigated, and then two silicon strips are placed beside the two adjacent waveguides. The mechanism of the cross-talk suppression method highly relies on the evanescent waves. The designed strips in this study manipulate the wave vectors of surface plasmon polaritons. The tangential component of the wave vector is conserved along the interface, while the perpendicular component in the surroundings can be equal to zero or imaginary, leading to evanescent waves. Placing the strips increases the perpendicular component of the wave vector in the surroundings, resulting in less cross-talk. So, the coupling length of the waveguide with the strips at the wavelength of 10 μm increases up to 345 μm which is 25 times longer than that in its non-strip counterpart. Also, the figure-of-merit and loss of the designed structure are up to 1000 and 0.13 dB/μm at a chemical potential of 0.8 eV and a wavelength of 10 μm, respectively. So, high figure-of-merit and low loss along with long coupling length are the interesting features of the designed plasmonic waveguide which propose promising structures with high performance in the near-infrared.

Research on the Current State of Global Poverty and Directions for Improvement

In today's increasingly complex global poverty landscape, effectively reducing poverty remains one of the core issues for global sustainable development. The current state of poverty has transitioned from relatively simple single factors such as natural disasters, extreme weather, and conflicts to multidimensional poverty caused by the interaction of multiple factors. Due to the complexity and diversity of contributing factors, multidimensional poverty varies in severity, making it challenging to reduce effectively and resulting in a prolonged global poverty problem. Compounded by limited global resources and funds, as well as slowing economic growth, addressing multidimensional poverty requires sustained long-term efforts, posing challenges in resource allocation. This leads to a cyclical pattern of multidimensional poverty, wasting resources and affecting people's confidence and attention to poverty reduction efforts, thus hindering progress. This paper analyzes the current state, challenge and existing problems of global poverty, and explores effective and sustainable approaches for poverty reduction considering the methods currently employed and their shortcomings. Through analysis, it is found that effective poverty reduction could focus on coordinating resources, adopting a combination of natural and artificial approaches, updating technologies, strengthening local improvements, and analyzing cross-regional impacts to prevent factors leading to poverty and mitigate present and future poverty issues.

Genetic variations in the antioxidant genes and their role in modulating susceptibility towards chronic obstructive pulmonary disease in the North Indian population

BackgroundChronic Obstructive Pulmonary Disease (COPD) is a persistent inflammatory lung condition characterized by an obstruction in removing oxygen from the lungs. Oxidant and antioxidant imbalance have long been hallmarks of COPD development, where the amount of antioxidants produced is less than that of oxidants. Here, polymorphism in the antioxidant enzymes like Catalase, Superoxide dismutase and Glutathione peroxidase plays an essential role in regulating the levels of oxidants. Methods1000 subjects, including 500 COPD cases and 500 controls, have been recruited and genotyped to assess the correlation between COPD and the particular SNPS of antioxidant genes. Logistic regression was used to compute odds ratios (ORs) and 95 % confidence intervals (CIs) to assess the association between SNPs and COPD risk. The relationship between spirometry value and COPD for all SNPs has been analyzed using Kruskal Wallis's. Haplotype analysis has also been performed. The effect of SNP interactions on COPD risk was assessed through the Multifactor Dimensionality Reduction (MDR) approach, a nonparametric test for overcoming some of the limitations of the logistic regression for detecting and characterizing SNP interactions. ResultsOur findings indicated a strong association between COPD and the variations in the CAT rs7943316 (OR = 0.61, Pc = 0.0001), SOD2 rs4880 (OR = 2.07, Pc = 0.0006), and GPx rs1050450 (OR = 0.60, Pc = 0.0018). Furthermore, SOD2 rs4880 was associated with forced vital capacity (FVC) and forced expiratory volume in 1 s (FEV1) of COPD patients. Our study found that the triple combination of SOD1 (rs2234694), SOD1 (rs36232792) and SOD2 (rs4880) was found to be elevating the risk of COPD (OR = 2.83, Pc = 0.006). SOD2 rs4880 and GPx rs1050450 are also linked to cough and mucus production. The Haplotype study reveals a substantial relationship between CAT (rs7943316 and rs1001179) and SOD (rs2234694 and rs4880), which increases the risk of COPD. The three-locus model (CAT rs794331, CAT rs1101179, and GPx rs1050450) was the most effective for COPD risk assessment based on the MDR findings, which were statistically significant (p < 0.0001). ConclusionThis study shows that rs7943316, rs4880, and rs1050450 are associated with the risk of COPD in the north Indian population and have the potential to enhance our knowledge of COPD at the molecular level, which in turn might pave the way for earlier detection, treatment, and preventive efforts.

Integrative, high-resolution analysis of single cells across experimental conditions with PARAFAC2.

Effective tools for exploration and analysis are needed to extract insights from large-scale single-cell measurement data. However, current techniques for handling single-cell studies performed across experimental conditions (e.g., samples, perturbations, or patients) require restrictive assumptions, lack flexibility, or do not adequately deconvolute condition-to-condition variation from cell-to-cell variation. Here, we report that the tensor decomposition method PARAFAC2 (Pf2) enables the dimensionality reduction of single-cell data across conditions. We demonstrate these benefits across two distinct contexts of single-cell RNA-sequencing (scRNA-seq) experiments of peripheral immune cells: pharmacologic drug perturbations and systemic lupus erythematosus (SLE) patient samples. By isolating relevant gene modules across cells and conditions, Pf2 enables straightforward associations of gene variation patterns across specific patients or perturbations while connecting each coordinated change to certain cells without pre-defining cell types. The theoretical grounding of Pf2 suggests a unified framework for many modeling tasks associated with single-cell data. Thus, Pf2 provides an intuitive universal dimensionality reduction approach for multi-sample single-cell studies across diverse biological contexts.

In silico analysis reveals the prospects of renal anisotropy in improving chronic kidney disease detection using ultrasound shear wave elastography.

Renal anisotropy is a complex property of the kidney and often poses a challenge in obtaining consistent measurements when using shear wave elastography to detect chronic kidney disease. To circumvent the challenge posed by renal anisotropy in clinical settings, a dimensionless biomarker termed the 'anisotropic ratio' was introduced to establish a correlation between changes in degree of renal anisotropy and progression of chronic kidney disease through an in silico perspective. To achieve this, an efficient model reduction approach was developed to model the anisotropic property of kidneys. Good agreement between the numerical and experimental data were obtained, as percentage errors of less than 5.5% were reported when compared against experimental phantom measurement from the literature. To demonstrate the applicability of the model to clinical measurements, the anisotropic ratio of sheep kidneys was quantified, with both numerical and derived experimental results reporting a value of .667. Analysis of the anisotropic ratio with progression of chronic kidney disease demonstrated that patients with normal kidneys would have a lower anisotropic ratio of .872 as opposed to patients suffering from renal impairment, in which the anisotropic ratio may increase to .904, as determined from this study. The findings demonstrate the potential of the anisotropic ratio in improving the detection of chronic kidney disease using shear wave elastography.

In-situ enrichment of ARGs and their carriers in soil by hydroxamate siderophore: A promising biocontrol approach for source reduction

Pathogenic microorganisms with antibiotic resistance genes (ARGs) pose a serious threat to public health and soil ecology. Although new drugs and available antibacterial materials can kill ARG carriers but accidentally kill beneficial microorganisms. Therefore, the rapid enrichment and separation of ARGs and their carriers from soil is becoming an important strategy for controlling the diffusion of ARGs. Hydroxamate siderophore (HDS) has gained widespread attentions for its involvement in trace element transfer among microorganisms in the soil environment, we thus explored an in-situ trapping-enrichment method for ARGs and their carriers via a small molecular HDS secreted by Pseudomonas fluorescens HMP01. In this study, we demonstrate that HDS significantly in-situ traps and enriches certain ARGs, including chloramphenicol, MLS, rifamycin, and tetracycline resistance genes in the soil environment. The enrichment efficiencies were 1473-fold, 38-fold, 17-fold, and 5-fold, respectively, higher than those in the control group. Specifically, the primary enriched ARGs were rpoB, mphL, catB2, and tetA(60), and Bacillus, Rhizobium, Rossellomorea, and Agrobacterium were hosts for these ARGs. This enrichment was caused by the upregulation of chemotaxis genes (e.g., cheW, cheC, and cheD) and rapid biofilm formation within the enriched bacterial population. Notably, representative ARGs such as cat, macB, and rpoB were significantly reduced by 36%, 85.7%, and 72%, respectively, in the paddy soil after HDS enrichment. Our research sheds light on the potential application of siderophore as a rapping agent for the eco-friendly reduction of ARGs and their carriers in soil environments.

Advanced Neural Network-Based Equalization in Intensity-Modulated Direct-Detection Optical Systems: Current Status and Future Trends

Intensity-modulated direct-detection (IM/DD) optical systems are most widely employed in short-reach optical interconnects due to their simple structure and cost-effectiveness. However, IM/DD systems face mixed linear and nonlinear channel impairments, mainly induced by the combination of square-law detection and chromatic dispersion, as well as the utilization of low-cost non-ideal transceivers. To solve this issue, recent years have witnessed a growing trend of introducing machine learning technologies such as neural networks (NNs) into IM/DD systems for channel equalization. NNs usually present better system performance than traditional approaches, and various types of NNs have been investigated. Despite the excellent system performance, the associated high computational complexity is a major drawback that hinders the practical application of NN-based equalizers. This paper focuses on the performance and complexity trade-off of NNs employed in IM/DD systems, presenting a systematic review of the current status of NN-based equalizers as well as a number of effective complexity reduction approaches. The future trends of leveraging advanced NN in IM/DD links are also discussed.

Novel Co-treatment of Cooling Blowdown Water and Produced Water: A Regional Approach for Resource Recovery and Treatment Footprint Reduction

Novel Co-treatment of Cooling Blowdown Water and Produced Water: A Regional Approach for Resource Recovery and Treatment Footprint Reduction