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Neuropsychiatric complications such as neurocognitive impairment and depression are common in people with HIV despite viral suppression on antiretroviral therapy, but these conditions are heterogeneous in their clinical presentations and associated disability. Identifying novel biopsychosocial phenotypes that account for neurocognitive performance and depressive and functional symptoms will better reflect the complexities encountered in clinical practice and may have pathological and therapeutic implications. We classified 1580 people with HIV based on 17 features, including 7 cognitive domains, 4 subscales of the Beck depression inventory-II, 5 components of the patients assessment of own functioning inventory, and dependence in instrumental and basic activities of daily living. A two-stage clustering procedure consisting of dimension reduction with self-organizing maps and Mahalanobis distance-based k-means clustering algorithms was applied to cross-sectional data. Baseline demographic and clinical characteristics were compared between the phenotypes, and their prediction on the biopsychosocial phenotypes was evaluated using multinomial logistic regression. Four distinct phenotypes were identified. Participants in Phenotype 1 overall did well in all domains. Phenotype 2 had mild-to-moderate depressive symptoms and the most substance use disorders. Phenotype 3 had mild-to-moderate cognitive impairment, moderate depressive symptoms, and the worst daily functioning; they also had the highest proportion of females and non-HIV conditions that could affect cognition. Phenotype 4 had mild-to-moderate cognitive impairment but with relatively good mood, and daily functioning. Multivariable analysis showed that demographic characteristics, medical conditions, lifetime cocaine use disorder, triglycerides, and non-antiretroviral therapy medications were important variables associated with biopsychosocial phenotype. We found complex, multidimensional biopsychosocial profiles i

The global Sustainable Development Goals highlight the necessity for affordable and clean energy, designated as SDG7. A sustainable and feasible biorefinery concept is proposed for the carbon-negative utilization of biomass waste for affordable H2 and battery anode material production. Specifically, an innovative tandem biocarbon + NiAlO + biocarbon catalyst strategy is constructed to realize a complete reforming of biomass pyro-vapors into H2+CO (as a mixture). The solid residues from pyrolysis are upgraded into high-quality hard carbon (HCs), demonstrating potential as sodium ion battery (SIBs) anodes. The product, HC-1600-6h, exhibited great electrochemical performance when employed as (SIBs) anodes (full cell: 263 Wh/kg with ICE of 89%). Ultimately, a comprehensive process is designed, simulated, and evaluated. The process yields 75 kg H2, 169 kg HCs, and 891 kg captured CO2 per ton of biomass achieving approx. 100% carbon and hydrogen utilization efficiencies. A life cycle assessment estimates a biomass valorization process with negative-emissions (−0.81 kg CO2/kg-biomass, reliant on Sweden wind electricity). A techno-economic assessment forecasts a notably profitable process capable of co-producing affordable H2 and hard carbon battery anodes. The payback period of the process is projected to fall within two years, assuming reference prices of 13.7 €/kg for HCs and 5 €/kg for H2. The process contributes to a novel business paradigm for sustainable and commercially viable biorefinery process, achieving carbon-negative valorization of biomass waste into affordable energy and materials.

The global Sustainable Development Goals highlight the necessity for affordable and clean energy, designated as SDG7. A sustainable and feasible biorefinery concept is proposed for the carbon-negative utilization of biomass waste for affordable H2 and battery anode material production. Specifically, an innovative tandem biocarbon + NiAlO + biocarbon catalyst strategy is constructed to realize a complete reforming of biomass pyro-vapors into H2+CO (as a mixture). The solid residues from pyrolysis are upgraded into high-quality hard carbon (HCs), demonstrating potential as sodium ion battery (SIBs) anodes. The product, HC-1600-6h, exhibited great electrochemical performance when employed as (SIBs) anodes (full cell: 263 Wh/kg with ICE of 89%). Ultimately, a comprehensive process is designed, simulated, and evaluated. The process yields 75 kg H2, 169 kg HCs, and 891 kg captured CO2 per ton of biomass achieving approx. 100% carbon and hydrogen utilization efficiencies. A life cycle assessment estimates a biomass valorization process with negative-emissions (−0.81 kg CO2/kg-biomass, reliant on Sweden wind electricity). A techno-economic assessment forecasts a notably profitable process capable of co-producing affordable H2 and hard carbon battery anodes. The payback period of the process is projected to fall within two years, assuming reference prices of 13.7 €/kg for HCs and 5 €/kg for H2. The process contributes to a novel business paradigm for sustainable and commercially viable biorefinery process, achieving carbon-negative valorization of biomass waste into affordable energy and materials.

The global Sustainable Development Goals highlight the necessity for affordable and clean energy, designated as SDG7. A sustainable and feasible biorefinery concept is proposed for the carbon-negative utilization of biomass waste for affordable H2 and battery anode material production. Specifically, an innovative tandem biocarbon + NiAlO + biocarbon catalyst strategy is constructed to realize a complete reforming of biomass pyro-vapors into H2+CO (as a mixture). The solid residues from pyrolysis are upgraded into high-quality hard carbon (HCs), demonstrating potential as sodium ion battery (SIBs) anodes. The product, HC-1600-6h, exhibited great electrochemical performance when employed as (SIBs) anodes (full cell: 263 Wh/kg with ICE of 89%). Ultimately, a comprehensive process is designed, simulated, and evaluated. The process yields 75 kg H2, 169 kg HCs, and 891 kg captured CO2 per ton of biomass achieving approx. 100% carbon and hydrogen utilization efficiencies. A life cycle assessment estimates a biomass valorization process with negative-emissions (−0.81 kg CO2/kg-biomass, reliant on Sweden wind electricity). A techno-economic assessment forecasts a notably profitable process capable of co-producing affordable H2 and hard carbon battery anodes. The payback period of the process is projected to fall within two years, assuming reference prices of 13.7 €/kg for HCs and 5 €/kg for H2. The process contributes to a novel business paradigm for sustainable and commercially viable biorefinery process, achieving carbon-negative valorization of biomass waste into affordable energy and materials.

The global Sustainable Development Goals highlight the necessity for affordable and clean energy, designated as SDG7. A sustainable and feasible biorefinery concept is proposed for the carbon-negative utilization of biomass waste for affordable H2 and battery anode material production. Specifically, an innovative tandem biocarbon + NiAlO + biocarbon catalyst strategy is constructed to realize a complete reforming of biomass pyro-vapors into H2+CO (as a mixture). The solid residues from pyrolysis are upgraded into high-quality hard carbon (HCs), demonstrating potential as sodium ion battery (SIBs) anodes. The product, HC-1600-6h, exhibited great electrochemical performance when employed as (SIBs) anodes (full cell: 263 Wh/kg with ICE of 89%). Ultimately, a comprehensive process is designed, simulated, and evaluated. The process yields 75 kg H2, 169 kg HCs, and 891 kg captured CO2 per ton of biomass achieving approx. 100% carbon and hydrogen utilization efficiencies. A life cycle assessment estimates a biomass valorization process with negative-emissions (−0.81 kg CO2/kg-biomass, reliant on Sweden wind electricity). A techno-economic assessment forecasts a notably profitable process capable of co-producing affordable H2 and hard carbon battery anodes. The payback period of the process is projected to fall within two years, assuming reference prices of 13.7 €/kg for HCs and 5 €/kg for H2. The process contributes to a novel business paradigm for sustainable and commercially viable biorefinery process, achieving carbon-negative valorization of biomass waste into affordable energy and materials.

Distal sensory polyneuropathy (DSP) is a disabling, chronic condition in people with HIV (PWH), even those with viral suppression of antiretroviral therapy (ART), and with a wide range of complications, such as reduced quality of life. Previous studies demonstrated that DSP is associated with inflammatory cytokines in PWH. Adhesion molecules, essential for normal vascular function, are perturbed in HIV and other conditions linked to DSP, but the link between adhesion molecules and DSP in PWH is unknown. This study aimed to determine whether DSP signs and symptoms were associated with a panel of plasma biomarkers of inflammation (d-dimer, sTNFRII, MCP-1, IL-6, IL-8, IP-10, sCD14) and vascular I integrity (ICAM-1, VCAM-1, uPAR, MMP-2, VEGF, uPAR, TIMP-1, TIMP-2) and differed between PWH and people without HIV (PWoH). A cross-sectional study was conducted among 143 participants (69 PWH and 74 PWoH) assessed by studies at the UC San Diego HIV Neurobehavioral Research Program. DSP signs and symptoms were clinically assessed for all participants. DSP was defined as two or more DSP signs: bilateral symmetrically reduced distal vibration, sharp sensation, and ankle reflexes. Participant-reported symptoms were neuropathic pain, paresthesias, and loss of sensation. Factor analyses reduced the dimensionality of the 15 biomarkers among all participants, yielding six factors. Logistic regression was used to assess the associations between biomarkers and DSP signs and symptoms, controlling for relevant demographic and clinical covariates. The 143 participants were 48.3% PWH, 47 (32.9%) women, and 47 (33.6%) Hispanics, with a mean age of 44.3 ± 12.9 years. Among PWH, the median (IQR) nadir and current CD4+ T-cells were 300 (178-448) and 643 (502-839), respectively. Participants with DSP were older but had similar distributions of gender and ethnicity to those without DSP. Multiple logistic regression showed that Factor 2 (sTNFRII and VCAM-1) and Factor 4 (MMP-2) were independently

The global Sustainable Development Goals highlight the necessity for affordable and clean energy, designated as SDG7. A sustainable and feasible biorefinery concept is proposed for the carbon-negative utilization of biomass waste for affordable H2 and battery anode material production. Specifically, an innovative tandem biocarbon + NiAlO + biocarbon catalyst strategy is constructed to realize a complete reforming of biomass pyro-vapors into H2+CO (as a mixture). The solid residues from pyrolysis are upgraded into high-quality hard carbon (HCs), demonstrating potential as sodium ion battery (SIBs) anodes. The product, HC-1600-6h, exhibited great electrochemical performance when employed as (SIBs) anodes (full cell: 263 Wh/kg with ICE of 89%). Ultimately, a comprehensive process is designed, simulated, and evaluated. The process yields 75 kg H2, 169 kg HCs, and 891 kg captured CO2 per ton of biomass achieving approx. 100% carbon and hydrogen utilization efficiencies. A life cycle assessment estimates a biomass valorization process with negative-emissions (−0.81 kg CO2/kg-biomass, reliant on Sweden wind electricity). A techno-economic assessment forecasts a notably profitable process capable of co-producing affordable H2 and hard carbon battery anodes. The payback period of the process is projected to fall within two years, assuming reference prices of 13.7 €/kg for HCs and 5 €/kg for H2. The process contributes to a novel business paradigm for sustainable and commercially viable biorefinery process, achieving carbon-negative valorization of biomass waste into affordable energy and materials.

Interindividual variation of human immunodeficiency virus (HIV) RNA setpoint in cerebrospinal fluid (CSF) and its determinants are poorly understood, but relevant for HIV neuropathology, brain reservoirs, viral escape, and reseeding after antiretroviral interruptions. Longitudinal multicentric study on demographic, clinical, and laboratory correlates of CSF HIV RNA in 2000 follow-up visits from 597 people with HIV (PWH) off antiretroviral therapy (ART) and with plasma HIV RNA > the lower limit of quantification (LLQ). Factors associated with CSF control (CSFC; CSF HIV RNA < LLQ while plasma HIV RNA > LLQ) and with CSF/plasma discordance (CSF > plasma HIV RNA > LLQ) were also assessed through mixed-effects models. Posthoc and sensitivity analyses were performed for persistent CSFC and ART-naïve participants, respectively. Over a median follow-up of 2.1 years, CSF HIV RNA was associated with CD4+ and CD8+ T cells, CSF leukocytes, blood-brain barrier (BBB) integrity, biomarkers of iron and lipid metabolism, serum globulins, past exposure to lamivudine, and plasma HIV RNA (model p < 0.0001). CSFC (persistent in 7.7% over 3 years) and CSF/plasma discordance (persistent in <0.01% over 1 year) were variably associated with the same parameters (model p < 0.001). Sensitivity analyses confirmed most of the previous associations in participants never exposed to ART. Persistent CSFC was associated with higher CD4+ T-cell count nadir (p < 0.001), lower serum globulins (p = 0.003), and lower CSF leukocytes (p < 0.001). Without ART, one in 13 PWH had persistently undetectable CSF HIV RNA, while persistent CSF/plasma discordance was extremely rare over years. Immune responses, inflammation, BBB permeability, and iron and lipid metabolism were all associated with HIV replication in CSF.

As a key technology of 5G, network function virtualization enables each monolithic service to be divided into microservices, facilitating their deployment and management in edge environments. One of the most critical issues in 5G is how to support dynamically arriving mission-critical services with low-latency and high-reliability requirements in distributed edge environments. However, most existing works focus on how to provide reliable services without considering latency, and their heuristics struggle to cope with high-dimensional constraints and complex environments with heterogeneous infrastructure and services. In this paper, we propose a SafeDRL algorithm to resource-efficiently support these dynamically arriving services while meeting their reliability and latency requirements. Specifically, we first formulate the problem as an integer nonlinear programming and prove its NP-hardness. To tackle this problem, our SafeDRL algorithm captures delayed rewards in dynamic environments by reinforcement learning, and corrects constraint violations with high-quality feasible solutions based on expert intervention, and prunes unnecessary backup instances for optimality. The algorithm is proved to have a bounded approximation ratio in general cases. Extensive trace-driven simulations show that, compared with the state-of-the-art solution, SafeDRL can save resource costs by up to 49.32% and improve the service acceptance ratio by up to 55% with acceptable execution time. © 2023 IEEE.

Yanjun Liu,1 Zijuan Jian,1 Zhiqian Wang,1 Awen Yang,1 Peilin Liu,1 Bin Tang,1 Jiahui Wang,1,2 Qun Yan,1 Wenen Liu1,2 1Department of Clinical Laboratory, Xiangya Hospital, Central South University, Changsha, Hunan, People’s Republic of China; 2National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan, People’s Republic of ChinaCorrespondence: Wenen Liu, Department of Clinical Laboratory, Xiangya Hospital, Central South University, Changsha, Hunan, 410000, People’s Republic of China, Tel +86 13973128689, Email wenenliu@163.comPurpose: In clinical settings, CG23 Klebsiella pneumoniae (Kp) is the most virulent clonal group of Kp. Continuous fusions of hypervirulent (Hv) and highly resistant strains have been reported; however, few studies have analysed the molecular epidemiology and clinical characteristics of CG23 strains, especially MDR-sequence type ST23 strains. In this study, we investigated the molecular characteristics of ST23 Kp and analysed the clinical characteristics of ST23 Kp infections in a large teaching hospital of the third class in China.Methods: ST23 Kp isolates were screened using whole-genome sequencing data from a large single centre. We compared the clinical characteristics of ST23 strains isolated from community-acquired infections (CAI) and hospital acquired infection (HAI). In addition, the infection characteristics of MDR and poor-prognosis isolates were investigated. We analysed genetic characteristics of ST23 Kp and further investigated the evolutionary relationship based on single-nucleotide polymorphism phylogenetic trees.Results: We detected 184 ST23 strains between 2013 and July of 2018. There were no significant differences between the isolation rates of pulmonary, bloodstream, urinary tract, and cutaneous soft tissue infections in the community and hospitals, except for abscess infections. MDR strains primarily cause pulmonary infections and abscesses; infections with a poor prognosis are typica

BACKGROUND/OBJECTIVES: Diagnostic criteria for atopic dermatitis (AD) are limited in their performance and/or usability. The American Academy of Dermatology (AAD) consensus criteria include hierarchical categories of disease features to improve these metrics but have not been validated. Our objective was to create and validate a checkbox form of the AAD consensus criteria in the pediatric population. METHODS: We performed a cross-sectional study of 100 pediatric patients with AD (n = 58) and diseases in the differential diagnosis of AD (n = 42). RESULTS: Having three or more Essential, ≥2 Important, ≥1 Associated features of the AAD criteria was optimal for the diagnosis of AD in children. This combination was 91.4% (95% CI, 84.2%-98.6%) sensitive and 95.2% (88.8%-100%) specific. The UK working party criteria and the Hanifin-Rajka criteria had sensitivities of 96.6% (95% CI 91.9%-100%) and 98.3% (95% CI 94.9%-100%) and specificities of 83.3% (95% CI 72.1%-94.6%) and 71.4% (95% CI 57.8%-85.1%), respectively. The AAD criteria had significantly greater specificity than the Hanifin-Rajka criteria (p = .002). CONCLUSIONS: This study represents an important step in validating the AAD consensus criteria and formulating a useable checkbox form for diagnosing AD in the pediatric population.

The global Sustainable Development Goals highlight the necessity for affordable and clean energy, designated as SDG7. A sustainable and feasible biorefinery concept is proposed for the carbon-negative utilization of biomass waste for affordable H2 and battery anode material production. Specifically, an innovative tandem biocarbon + NiAlO + biocarbon catalyst strategy is constructed to realize a complete reforming of biomass pyro-vapors into H2+CO (as a mixture). The solid residues from pyrolysis are upgraded into high-quality hard carbon (HCs), demonstrating potential as sodium ion battery (SIBs) anodes. The product, HC-1600-6h, exhibited great electrochemical performance when employed as (SIBs) anodes (full cell: 263 Wh/kg with ICE of 89%). Ultimately, a comprehensive process is designed, simulated, and evaluated. The process yields 75 kg H2, 169 kg HCs, and 891 kg captured CO2 per ton of biomass achieving approx. 100% carbon and hydrogen utilization efficiencies. A life cycle assessment estimates a biomass valorization process with negative-emissions (−0.81 kg CO2/kg-biomass, reliant on Sweden wind electricity). A techno-economic assessment forecasts a notably profitable process capable of co-producing affordable H2 and hard carbon battery anodes. The payback period of the process is projected to fall within two years, assuming reference prices of 13.7 €/kg for HCs and 5 €/kg for H2. The process contributes to a novel business paradigm for sustainable and commercially viable biorefinery process, achieving carbon-negative valorization of biomass waste into affordable energy and materials., QC 20231106

The global Sustainable Development Goals highlight the necessity for affordable and clean energy, designated as SDG7. A sustainable and feasible biorefinery concept is proposed for the carbon-negative utilization of biomass waste for affordable H2 and battery anode material production. Specifically, an innovative tandem biocarbon + NiAlO + biocarbon catalyst strategy is constructed to realize a complete reforming of biomass pyro-vapors into H2+CO (as a mixture). The solid residues from pyrolysis are upgraded into high-quality hard carbon (HCs), demonstrating potential as sodium ion battery (SIBs) anodes. The product, HC-1600-6h, exhibited great electrochemical performance when employed as (SIBs) anodes (full cell: 263 Wh/kg with ICE of 89%). Ultimately, a comprehensive process is designed, simulated, and evaluated. The process yields 75 kg H2, 169 kg HCs, and 891 kg captured CO2 per ton of biomass achieving approx. 100% carbon and hydrogen utilization efficiencies. A life cycle assessment estimates a biomass valorization process with negative-emissions (−0.81 kg CO2/kg-biomass, reliant on Sweden wind electricity). A techno-economic assessment forecasts a notably profitable process capable of co-producing affordable H2 and hard carbon battery anodes. The payback period of the process is projected to fall within two years, assuming reference prices of 13.7 €/kg for HCs and 5 €/kg for H2. The process contributes to a novel business paradigm for sustainable and commercially viable biorefinery process, achieving carbon-negative valorization of biomass waste into affordable energy and materials., QC 20231106

Modern antiretroviral therapy (ART) has increased longevity of people with HIV and shifted the age distribution of the HIV pandemic upward toward that of the general population. This positive development has also led to concerns about premature and/or accelerated neurocognitive and physical ageing due to the combined effects of chronic HIV, accumulating comorbidities, adverse effects or possible toxicities of ART and biological ageing. Here we present results of comprehensive assessments over 12 years of 402 people with HIV in the CNS HIV ART Effects Research (CHARTER) programme, who at follow-up were composed of younger (<60 years) and older (≥60 years) subgroups. Over the 12 years, ART use and viral suppression increased in both subgroups as did systemic and psychiatric comorbidities; participants in both subgroups also evidenced neurocognitive decline beyond what is expected in typical ageing. Contrary to expectations, all these adverse effects were comparable in the younger and older CHARTER subgroups, and unrelated to chronological age. Neurocognitive decline was unrelated to HIV disease or treatment characteristics but was significantly predicted by the presence of comorbid conditions, specifically diabetes, hypertension, chronic pulmonary disease, frailty, neuropathic pain, depression and lifetime history of cannabis use disorder. These results are not consistent with premature or accelerated neurocognitive ageing due to HIV itself but suggest important indirect effects of multiple, potentially treatable comorbidities that are more common among people with HIV than in the general population. Good medical management of HIV disease did not prevent these adverse outcomes, and increased attention to a range of comorbid conditions in people with HIV may be warranted in their care.

Ya-Da Zhang,1,&ast; Tai-Wen He,2,&ast; Yi-Ren Chen,1 Bi-Dan Xiong,1 Zhe Zhe,1 Ping Liu,3 Bin-Qing Tang1 1Department of Pneumology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, 200071, People’s Republic of China; 2Department of Ophthalmology, Shanghai Public Health Clinical Center, Shanghai, 201500, People’s Republic of China; 3Department of Tuberculosis, Shanghai Public Health Clinical Center, Shanghai, 201500, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Bin-Qing Tang, Department of Pneumology, Shanghai Municipal Hospital of Traditional Chinese Medicine, Shanghai University of Traditional Chinese Medicine, No. 274 of ZhiJiang Middle Road, Jing’an District, Shanghai, 200071, People’s Republic of China, Tel +86 13636657240, Email tangbinqi25ng@outlook.com Ping Liu, Department of Tuberculosis, Shanghai Public Health Clinical Center, No. 2901 of Caolong Road, Jin’shan District, Shanghai, 201500, People’s Republic of China, Tel +86 18939895095, Email iupingping0517@126.comBackground: Clinical decision-making is enhanced by the development of a mathematical model for prognosis prediction. Screening criteria associated with viral shedding time and developing a prediction model facilitate clinical decision-making and are, thus, of great medical value.Methods: This study comprised 631 patients who were hospitalized with mild COVID-19 from a single center and 30 independent variables included. The data set was randomly divided into the training set (80%) and the validation set (20%). The outcome variable included viral shedding time and whether the viral shedding time > 14 days, LASSO was used to screen the influencing factors.Results: There were 321 males and 310 females among the 631 cases, with an average age of 62.1 years; the median viral shedding time was 12 days, and 68.8% of patients experienced viral shedding wit

BACKGROUND: Neurofilament light (NFL) chain concentrations, reflecting axonal damage, are seen in several polyneuropathies but have not been studied in human immunodeficiency virus (HIV) distal sensory polyneuropathy (DSP). We evaluated NFL in cerebrospinal fluid (CSF) and plasma in relation to DSP in people with HIV (PWH) from 2 independent cohorts and in people without HIV (PWoH). METHODS: Cohort 1 consisted of PWH from the CHARTER Study. Cohort 2 consisted of PWH and PWoH from the HIV Neurobehavioral Research Center (HNRC). We evaluated DSP signs and symptoms in both cohorts. Immunoassays measured NFL in CSF for all and for plasma as well in Cohort 2. RESULTS: Cohort 1 consisted of 111 PWH, mean ± SD age 56.8 ± 8.32 years, 15.3% female, 38.7% Black, 49.6% White, current CD4+ T-cells (median, interquartile range [IQR]) 532/µL (295, 785), 83.5% with plasma HIV RNA ≤50 copies/mL. Cohort 2 consisted of 233 PWH of similar demographics to PWH in Cohort 1 but also 51 PWoH, together age 58.4 ± 6.68 years, 41.2% female, 18.0% Black, Hispanic, non-Hispanic White 52.0%, 6.00% White. In both cohorts of PWH, CSF and plasma NFL were significantly higher in both PWH with DSP signs. Findings were similar, albeit not significant, for PWoH. The observed relationships were not explained by confounds. CONCLUSIONS: Both plasma and CSF NFL were elevated in PWH and PWoH with DSP. The convergence of our findings with others demonstrates that NFL is a reliable biomarker reflecting peripheral nerve injury. Biomarkers such as NFL might provide, validate, and optimize clinical trials of neuroregenerative strategies in HIV DSP.

The global Sustainable Development Goals highlight the necessity for affordable and clean energy, designated as SDG7. A sustainable and feasible biorefinery concept is proposed for the carbon-negative utilization of biomass waste for affordable H2 and battery anode material production. Specifically, an innovative tandem biocarbon + NiAlO + biocarbon catalyst strategy is constructed to realize a complete reforming of biomass pyro-vapors into H2+CO (as a mixture). The solid residues from pyrolysis are upgraded into high-quality hard carbon (HCs), demonstrating potential as sodium ion battery (SIBs) anodes. The product, HC-1600-6h, exhibited great electrochemical performance when employed as (SIBs) anodes (full cell: 263 Wh/kg with ICE of 89%). Ultimately, a comprehensive process is designed, simulated, and evaluated. The process yields 75 kg H2, 169 kg HCs, and 891 kg captured CO2 per ton of biomass achieving approx. 100% carbon and hydrogen utilization efficiencies. A life cycle assessment estimates a biomass valorization process with negative-emissions (−0.81 kg CO2/kg-biomass, reliant on Sweden wind electricity). A techno-economic assessment forecasts a notably profitable process capable of co-producing affordable H2 and hard carbon battery anodes. The payback period of the process is projected to fall within two years, assuming reference prices of 13.7 €/kg for HCs and 5 €/kg for H2. The process contributes to a novel business paradigm for sustainable and commercially viable biorefinery process, achieving carbon-negative valorization of biomass waste into affordable energy and materials., QC 20231106

The global Sustainable Development Goals highlight the necessity for affordable and clean energy, designated as SDG7. A sustainable and feasible biorefinery concept is proposed for the carbon-negative utilization of biomass waste for affordable H2 and battery anode material production. Specifically, an innovative tandem biocarbon + NiAlO + biocarbon catalyst strategy is constructed to realize a complete reforming of biomass pyro-vapors into H2+CO (as a mixture). The solid residues from pyrolysis are upgraded into high-quality hard carbon (HCs), demonstrating potential as sodium ion battery (SIBs) anodes. The product, HC-1600-6h, exhibited great electrochemical performance when employed as (SIBs) anodes (full cell: 263 Wh/kg with ICE of 89%). Ultimately, a comprehensive process is designed, simulated, and evaluated. The process yields 75 kg H2, 169 kg HCs, and 891 kg captured CO2 per ton of biomass achieving approx. 100% carbon and hydrogen utilization efficiencies. A life cycle assessment estimates a biomass valorization process with negative-emissions (−0.81 kg CO2/kg-biomass, reliant on Sweden wind electricity). A techno-economic assessment forecasts a notably profitable process capable of co-producing affordable H2 and hard carbon battery anodes. The payback period of the process is projected to fall within two years, assuming reference prices of 13.7 €/kg for HCs and 5 €/kg for H2. The process contributes to a novel business paradigm for sustainable and commercially viable biorefinery process, achieving carbon-negative valorization of biomass waste into affordable energy and materials., QC 20231106

The software-defined network (SDN) enabled mobile edge network greatly facilitates network resource management and promotes many emerging applications. However, user mobility may cause the SDN controller to set flow rules frequently, introduce additional flow setup latency, cause delay jitter, and undermine latency-sensitive services. Proactive flow setup is an effective way to eliminate flow setup latency, but existing work fails to maximize the flow setup hit ratio, a metric for evaluating the quality of proactive flow setup decisions, which is critical for latency-sensitive services. In this paper, we study how to proactively set flow rules to maximize the flow setup hit ratio under limited available network resources to eliminate the flow setup latency as much as possible. Then, we formalize the proactive flow setup problem as two integer linear programming problems under two typical routing strategies, default routing and dynamic routing. Both problems are proved to be NP-hard. To tackle these two problems, we propose a linear programming-based polynomial-time approximation algorithm for the default routing case and a greedy-based heuristic algorithm for the dynamic routing case. Extensive trace-driven experimental and simulation results verify that our algorithms can improve the flow setup hit ratio by up to 30.99% compared to existing solutions. © 1972-2012 IEEE.

We consider the multiuser detection (MUD) problem, i.e., how to separate and decode colliding data streams, in the uplink of massive Machine Type Communications (mMTC) at millimeter wave (mmWave). Operating on factor-graphs by passing messages, the sum-product algorithm and its variants are widely applied in many other scenarios. However, in this paper, we find that their performance in mMTC at mmWave could be dramatically degraded due to the ill-conditioned MUD channel gain matrix and the existence of enormous short cycles in their corresponding factor-graphs, which are caused by the limited scattering of mmWave and the sharing of a same codebook for error correction among densely located user equipments. Assuming LDPC codes are used for error correction, we further propose a novel sum-product based approach to dealing with the MUD problem in mMTC at mmWave. It first leverages the propagation characteristics of mmWave to optimize the factor-graph for MUD by removing short cycles based on node-split and node-contraction, and then takes a dynamic-programming based method to approximate the messages passing on the resulted factor-graph, which can achieve a higher decoding accuracy. Extensive simulation results show that our approach outperforms the state-of-The-Art sum-product based approaches significantly. © 2002-2012 IEEE.

As a kAs a key enabling technology for 5G, network function virtualization abstracts services into software-based service function chains (SFCs), facilitating mission-critical services with high-reliability requirements. However, it is challenging to cost-effectively provide reliable SFCs in dynamic environments due to delayed rewards caused by future SFC requests, limited infrastructure resources, and heterogeneity in hardware and software reliability. Although deep reinforcement learning (DRL) can effectively capture delayed rewards in dynamic environments, its trial-and-error exploration in a vast solution space with massive infeasible solutions may lead to frequent constraint violations and traps in poor local optima. To address these challenges, we propose a RuleDRL algorithm that combines the capability of DRL to capture delayed rewards and the strength of rule-based schemes to explore high-quality solutions without violating constraints. Specifically, we first formulate the reliable SFC provision problem as an integer nonlinear programming problem, which is proven to be NP-hard. Then, we jointly design DRL and rule-based schemes that are coupled to make the final decision and establish a bounded approximation ratio in general cases. Extensive trace-driven simulations show that RuleDRL can save the total cost by up to 65.67% and improve the SFC acceptance ratio by up to 82%, compared to the state-of-the-art solution.

Salient object detection segments attractive objects in scenes. RGB and thermal modalities provide complementary information and scribble annotations alleviate large amounts of human labor. Based on the above facts, we propose a scribble-supervised RGB-T salient object detection model. By a four-step solution (expansion, prediction, aggregation, and supervision), label-sparse challenge of scribble-supervised method is solved. To expand scribble annotations, we collect the superpixels that foreground scribbles pass through in RGB and thermal images, respectively. The expanded multi-modal labels provide the coarse object boundary. To further polish the expanded labels, we propose a prediction module to alleviate the sharpness of boundary. To play the complementary roles of two modalities, we combine the two into aggregated pseudo labels. Supervised by scribble annotations and pseudo labels, our model achieves the state-of-the-art performance on the relabeled RGBT-S dataset. Furthermore, the model is applied to RGB-D and video scribble-supervised applications, achieving consistently excellent performance., Comment: ICME2023

The High-Resolution Transformer (HRFormer) can maintain high-resolution representation and share global receptive fields. It is friendly towards salient object detection (SOD) in which the input and output have the same resolution. However, two critical problems need to be solved for two-modality SOD. One problem is two-modality fusion. The other problem is the HRFormer output's fusion. To address the first problem, a supplementary modality is injected into the primary modality by using global optimization and an attention mechanism to select and purify the modality at the input level. To solve the second problem, a dual-direction short connection fusion module is used to optimize the output features of HRFormer, thereby enhancing the detailed representation of objects at the output level. The proposed model, named HRTransNet, first introduces an auxiliary stream for feature extraction of supplementary modality. Then, features are injected into the primary modality at the beginning of each multi-resolution branch. Next, HRFormer is applied to achieve forwarding propagation. Finally, all the output features with different resolutions are aggregated by intra-feature and inter-feature interactive transformers. Application of the proposed model results in impressive improvement for driving two-modality SOD tasks, e.g., RGB-D, RGB-T, and light field SOD.https://github.com/liuzywen/HRTransNet

To study the mechanism and control of well deviation in air drilling, a mechanical model of bottom hole assembly (BHA) with double stabilizer is established by using the beam-column method. The mathematical model related to side force of BHA and deviating force of strata are derived by analyzing the characteristics of gravel strata in the practical engineering. The effects of weight on bit (WOB), expansion ratio of borehole diameter (ERBD), angle of well inclination, diameter of drill collar and strata bending moment on side force of BHA are explored. Then, the superposition of bit side force and deviating force of strata is obtained. The results display that side force of BHA is obviously influenced by ERBD, angle of well inclination, diameter of drill collar and strata bending moment; and the deviation force and azimuth force of gravel strata are significantly affected by comprehensive cutting anisotropy index, angle of well inclination and dip angle of strata. Finally, the variation tendency of inclination angle and azimuth angle in field measurement is consistent with the theoretical and numerical researches. The present work can provide theoretical guidance to control the well deviation in the practical air drilling.

Scene text recognition is an indispensable part of computer vision, which aims to extract text information from an image. However, effective extraction of texts following spelling rules remains a challenge for scene text recognition. We propose a cross-domain Transformer, called STR Transformer (STRT), which can not only extract texts from an image but also correct characters effectively according to their spelling rules. Specifically, we propose a Spline Transformer to extract hierarchical features of images without the convolution layers, which has the flexibility to build models with various scales and has linear computational complexity with respect to image size. Furthermore, an iterative Text Transformer is designed to predict the probability distribution of current character in the character sequence, which can effectively reduce the impact of noise. Extensive experiments demonstrate that the proposed STRT outperforms state-of-the-art methods on various benchmark datasets of scene text recognition. The qualitative and quantitative analysis proves the effectiveness and efficiency of the proposed STRT method.

Recently, learned video compression has achieved exciting performance. Following the traditional hybrid prediction coding framework, most learned methods generally adopt the motion estimation motion compensation (MEMC) method to remove inter-frame redundancy. However, inaccurate motion vector (MV) usually lead to the distortion of reconstructed frame. In addition, most approaches ignore the spatial and channel redundancy. To solve above problems, we propose a motion-aware and spatial-temporal-channel contextual coding based video compression network (MASTC-VC), which learns the latent representation and uses variational autoencoders (VAEs) to capture the characteristics of intra-frame pixels and inter-frame motion. Specifically, we design a multiscale motion-aware module (MS-MAM) to estimate spatial-temporal-channel consistent motion vector by utilizing the multiscale motion prediction information in a coarse-to-fine way. On the top of it, we further propose a spatial-temporal-channel contextual module (STCCM), which explores the correlation of latent representation to reduce the bit consumption from spatial, temporal and channel aspects respectively. Comprehensive experiments show that our proposed MASTC-VC is surprior to previous state-of-the-art (SOTA) methods on three public benchmark datasets. More specifically, our method brings average 10.15\% BD-rate savings against H.265/HEVC (HM-16.20) in PSNR metric and average 23.93\% BD-rate savings against H.266/VVC (VTM-13.2) in MS-SSIM metric., Comment: 12pages,12 figures

Most previous studies investigating sleep's association with health outcomes have relied on averaged sleep quality and laboratory-based health measures. This study examines the dynamic within-person relationships between subjective (Ecological Momentary Assessment) and objective sleep (actigraphy) on next-day cognition (subjective and objective), mood, and engagement in daily activities using linear mixed-effects regression modeling. Participants included 94 individuals (59 people with HIV, 35 HIV-) aged 50-74, assessed daily for 14 consecutive days/nights. Subjective and objective sleep were well correlated and were both associated with subjective ratings of cognition, but not objective cognition. Worse subjective sleep was associated with next-day lower happiness and higher depressed mood, and more pain, but was not related to next-day daily activities. Objective sleep was associated with next-day depressed mood and feelings of worry, and was positively associated with next-day television watching. Results provide evidence to support the utility of real-time assessment for sleep and functional outcomes that may lead to potential personalized interventions for individuals with and without HIV.

Monocytes and macrophages activation are crucial in human immunodeficiency virus (HIV) central nervous system (CNS) infection and HIV associated neurocognitive disorders (HAND) pathogenesis. The soluble form of CD14 (sCD14) is a marker of monocyte activation. We hypothesized that sCD14 levels would be lower in people with HIV-1 subtype C (HIV-1C) than in HIV-1B owing to a variant Tat cysteine dimotif (C30S31) with reduced chemotactic activity. A total of 68 paired cerebrospinal fluid (CSF) and blood samples from people with HIV (PWH); 27 samples of the HIV-1B subtype and 40 of the non-B HIV-1 subtypes (including 26,HIV-1C), and 18 HIV-negative controls were included. sCD14 levels were quantified using a high-sensitivity enzyme-linked immunosorbent assay. sCD14 increase in serum, but not in CSF, was higher in samples from HIV-1B than HIV-1C (p = 0.002; Cohen's d, 0.7). CSF or serum sCD14 values were not correlated with global deficit score or specific cognitive domains. The impact of HIV-1 on monocyte stimulation biomarkers evaluated by sCD14 in serum was subtype-dependent, higher in HIV-1B than HIV-1C, consistent with reduced chemotactic activity as hypothesized.

Most previous studies investigating sleep's association with health outcomes have relied on averaged sleep quality and laboratory-based health measures. This study examines the dynamic within-person relationships between subjective (Ecological Momentary Assessment) and objective sleep (actigraphy) on next-day cognition (subjective and objective), mood, and engagement in daily activities using linear mixed-effects regression modeling. Participants included 94 individuals (59 people with HIV, 35 HIV-) aged 50-74, assessed daily for 14 consecutive days/nights. Subjective and objective sleep were well correlated and were both associated with subjective ratings of cognition, but not objective cognition. Worse subjective sleep was associated with next-day lower happiness and higher depressed mood, and more pain, but was not related to next-day daily activities. Objective sleep was associated with next-day depressed mood and feelings of worry, and was positively associated with next-day television watching. Results provide evidence to support the utility of real-time assessment for sleep and functional outcomes that may lead to potential personalized interventions for individuals with and without HIV.

Monocytes and macrophages activation are crucial in human immunodeficiency virus (HIV) central nervous system (CNS) infection and HIV associated neurocognitive disorders (HAND) pathogenesis. The soluble form of CD14 (sCD14) is a marker of monocyte activation. We hypothesized that sCD14 levels would be lower in people with HIV-1 subtype C (HIV-1C) than in HIV-1B owing to a variant Tat cysteine dimotif (C30S31) with reduced chemotactic activity. A total of 68 paired cerebrospinal fluid (CSF) and blood samples from people with HIV (PWH); 27 samples of the HIV-1B subtype and 40 of the non-B HIV-1 subtypes (including 26,HIV-1C), and 18 HIV-negative controls were included. sCD14 levels were quantified using a high-sensitivity enzyme-linked immunosorbent assay. sCD14 increase in serum, but not in CSF, was higher in samples from HIV-1B than HIV-1C (p = 0.002; Cohen's d, 0.7). CSF or serum sCD14 values were not correlated with global deficit score or specific cognitive domains. The impact of HIV-1 on monocyte stimulation biomarkers evaluated by sCD14 in serum was subtype-dependent, higher in HIV-1B than HIV-1C, consistent with reduced chemotactic activity as hypothesized.

Positive psychological attributes are associated with better health outcomes, yet few studies have identified their underlying constructs and none have examined their temporal trajectories in clinical vs. non-clinical samples. From data collected over 4 years from people with HIV (PWH) and HIV-uninfected (HIV-) participants, we identified two latent factors (internal strengths; socioemotional support) based on responses to seven positive psychological attributes. Internal strengths increased over 4 years for PWH, but not for HIV- comparisons. Socioemotional support did not change significantly in either group. Lower internal strengths and worse socioemotional support were related to greater depressive symptoms. We speculate that improvement in internal strengths in PWH could reflect their being in care, but this requires further study to include PWH not in care. Given the apparent malleability of internal strengths and their association with improved health outcomes, these attributes can serve as promising intervention targets for PWH.

BackgroundAstrocytes become activated with certain infections, and this might alter the brain to trigger or worsen depressed mood. Indeed, astrocytes are chronically activated in people with HIV infection (PWH), who are much more frequently depressed than people without HIV (PWoH). A particularly disabling component of depression in PWH is apathy, a loss of interest, motivation, emotion, and goal-directed behavior. We tested the hypothesis that depression and apathy in PWH would be associated with higher levels of a biomarker of astrocyte activation, glial fibrillary acidic protein (GFAP), in cerebrospinal fluid (CSF).MethodsWe evaluated PWH in a prospective observational study using the Beck Depression Inventory-II (BDI-II) and additional standardized assessments, including lumbar puncture. We measured GFAP in CSF with a customized direct sandwich ELISA method. Data were analyzed using ANOVA and multivariable regression.ResultsParticipants were 212 PWH, mean (SD) age 40.9±9.14 years, median (IQR) nadir and current CD4 199 (57, 326) and 411 (259, 579), 65.1% on ART, 67.3% virally suppressed. Higher CSF GFAP correlated with worse total BDI-II total scores (Pearson correlation r=0.158, p-value=0.0211), and with worse apathy scores (r=0.205, p=0.0027). The correlation between apathy/depression and GFAP was not in fluenced by other factors such as age or HIV suppression status.ConclusionsAstrocyte activation, reflected in higher levels of CSF GFAP, was associated with worse depression and apathy in PWH. Interventions to reduce astrocyte activation -- for example, using a peptide-1 receptor (GLP-1R) agonist -- might be studied to evaluate their impact on disabling depression in PWH.

BackgroundTo examine longitudinal neurocognitive decline among Latino, non-Latino Black, and non-Latino White people with HIV (PWH) and factors that may explain ethnic/racial disparities in neurocognitive decline.MethodsFour hundred ninety nine PWH (13.8% Latino, 42.7% Black, 43.5% White; baseline age: M = 43.5) from the CNS HIV Anti-Retroviral Therapy Effects Research (CHARTER) study completed neurocognitive, neuromedical, and laboratory assessments every 6-12 months with up to 5 years of follow-up. Longitudinal neurocognitive change was determined via published regression-based norms. Survival analyses investigated the relationship between ethnicity/race and neurocognitive change, and baseline and time-dependent variables that may explain ethnic/racial disparities in neurocognitive decline, including socio-demographic, HIV-disease, medical, psychiatric, and substance use characteristics.ResultsIn Cox proportional hazard models, hazard ratios for neurocognitive decline were increased for Latino compared with White PWH (HR = 2.25, 95% CI = 1.35 to 3.73, P = 0.002), and Latino compared with Black PWH (HR = 1.86, 95% CI = 1.14 to 3.04, P = 0.013), with no significant differences between Black and White PWH (P = 0.40). Comorbidities, including cardiometabolic factors and more severe neurocognitive comorbidity classification, accounted for 33.6% of the excess hazard for Latino compared with White PWH, decreasing the hazard ratio associated with Latino ethnicity (HR = 1.83, 95% CI = 1.06 to 3.16, P = 0.03), but did not fully account for elevated risk of decline.ConclusionsLatino PWH may be at higher risk of early neurocognitive decline compared with Black and White PWH. Comorbidities accounted for some, but not all, of this increased risk among Latino PWH. Future research examining institutional, sociocultural, and biomedical factors, including structural discrimination and age-related biomarkers, may further explain the observed disparities.

Xuan Liu,1,&ast; Xin Li,1,&ast; A-wen Yang,1 Bin Tang,1 Zi-juan Jian,1 Yi-ming Zhong,1 Hong-ling Li,1 Yan-ming Li,1 Qun Yan,1 Xiang-hui Liang,1,2 Wen-en Liu1,2 1Department of Clinical Laboratory, Xiangya Hospital, Central South University, Changsha, Hunan Province, People’s Republic of China; 2National Clinical Research Center for Geriatric Disorders, Xiangya Hospital, Changsha, Hunan, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Wen-en Liu; Xiang-hui Liang, Department of Clinical Laboratory, Xiangya Hospital, Central South University, Changsha, 410008, Hunan Province, People’s Republic of China, Tel +86-731-84327437, Fax +86-731-84327332, Email wenenliu@163.com; 1677344146@qq.comBackground: Fecal carriage of extended-spectrum β-lactamase-producing Escherichia coli (ESBL-EC) and carbapenemase-producing E. coli (CP-EC) is well reported among hospitalized adults and children. However, there are few studies on the carriage prevalence and ESBL-EC and CP-EC genotypes among healthy children in China.Patients and Methods: Stool samples were collected from 330 students in 2021 from three randomly selected primary schools in Changsha, China. ESBL-EC and CP-EC were screened using CHROMagarTM chromogenic plates. ESBL and carbapenemase production was confirmed using the double-disc synergy test and a modified carbapenem inactivation method, respectively. Antimicrobial susceptibility was tested using the broth microdilution method. Resistance determinants, virulence factors, and phylogenetic groups were determined by PCR and sequencing. Multi-locus sequence typing (MLST) was performed (seven housekeeping genes were amplified and sequenced) on the phylogenic group B2 E. coli to detect high-risk clonal strains such as ST131 E. coli. Then, ST131 E. coli were characterized based on ST131 clades, O-type, and fimH alleles.Results: In total, 118 (35.8%) ESBL-EC and 3 (0.9%) CP-EC were isolated. blaCTX-M was the most com

Li Zhang,1,&ast; Jing Xu,1,&ast; Xiaoling Qi,1 Zheying Tao,1 Zhitao Yang,2 Wei Chen,3 Xiaoli Wang,1 Tingting Pan,1 Yunqi Dai,1 Rui Tian,1 Yang Chen,1 Bin Tang,1 Zhaojun Liu,1 Ruoming Tan,1 Hongping Qu,1 Yue Yu,1 Jialin Liu1 1Department of Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, People’s Republic of China; 2Emergency Department, Ruijin Hospital affiliate to Shanghai Jiaotong University School of Medicine, Shanghai, People’s Republic of China; 3Department of Pulmonary and Critical Care Medicine, Ruijin Hospital Affiliate to Shanghai Jiaotong University School of Medicine, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jialin Liu; Yue Yu, Department of Critical Care Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200020, People’s Republic of China, Email ljl11243@rjh.com.cn; yy12356@rjh.com.cnBackground: Since the outbreak of coronavirus disease (COVID-19) in December 2019 in Wuhan, it has spread rapidly worldwide. We aimed to establish and validate a nomogram that predicts the probability of coronavirus-associated acute respiratory distress syndrome (CARDS).Methods: In this single-centre, retrospective study, 261 patients with COVID-19 were recruited using positive reverse transcription–polymerase chain reaction tests for severe acute respiratory syndrome coronavirus 2 in Tongji Hospital at Huazhong University of Science and Technology (Wuhan, China). These patients were randomly distributed into the training cohort (75%) and the validation cohort (25%). The factors included in the nomogram were determined using univariate and multivariate logistic regression analyses based on the training cohort. The area under the receiver operating characteristic curve (AUC), consistency index (C-index), calibration curve, and decision curve analysis (DCA) were used to evaluate the efficiency of the nomogra

Federated Learning (FL) is a promising machine learning paradigm to cooperatively train a global model with highly distributed data located on mobile devices. Aiming to optimize the communication efficiency for gradient aggregation and model synchronization among large-scale devices, we propose a relay-assisted FL framework. By breaking the traditional transmission-order constraint and exploiting the broadcast characteristic of relay nodes, we design a novel synchronization scheme named Partial Synchronization Parallel (PSP), in which models and gradients are transmitted simultaneously and aggregated at relay nodes, resulting in traffic reduction. We prove that PSP has the same convergence rate as the sequential synchronization approaches via rigorous analysis. To further accelerate the training process, we integrate PSP with any unbiased and error-bounded compression technologies and prove that the convergence properties of the resulting scheme still hold. Extensive experiments are conducted in a distributed cluster environment with real-world datasets and the results demonstrate that our proposed approach reduces the training time up to 37 percent compared to state-of-the-art methods. © 2002-2012 IEEE.

Distributed gradient descent has been widely adopted in the machine learning field because considerable computing resources are available when facing the huge volume of data. Specifically, the gradient over the whole data is cooperatively computed by multiple workers. However, its performance can be severely affected by slow workers, namely stragglers. Recently, coding-based approaches have been introduced to mitigate the straggler problem, but they could hardly deal with the heterogeneity among workers. Besides, they always discard the results of stragglers causing huge resource waste. In this article, we first investigate how to tolerate stragglers by discarding their results and then seek to leverage the stragglers. For tolerating stragglers, we propose a heterogeneity-aware coding scheme that encodes gradients adaptive to the computing capability of workers. Theoretically, this scheme is optimal for stragglers tolerance. Relying on the scheme, we further propose an algorithm called DHeter-aware to exploit the gradients of stragglers which we called delayed gradients. Moreover, theoretical results characterized for DHeter-aware exhibits the same convergence rate as the gradient descent without delayed gradients. Experiments on various tasks and clusters demonstrate that our coding scheme outperforms all the state-of-the-art methods and the DHeter-aware further accelerates the coding scheme by achieving 25 percent time savings. © 1968-2012 IEEE.

Text editing, such as grammatical error correction, arises naturally from imperfect textual data. Recent works frame text editing as a multi-round sequence tagging task, where operations -- such as insertion and substitution -- are represented as a sequence of tags. While achieving good results, this encoding is limited in flexibility as all actions are bound to token-level tags. In this work, we reformulate text editing as an imitation game using behavioral cloning. Specifically, we convert conventional sequence-to-sequence data into state-to-action demonstrations, where the action space can be as flexible as needed. Instead of generating the actions one at a time, we introduce a dual decoders structure to parallel the decoding while retaining the dependencies between action tokens, coupled with trajectory augmentation to alleviate the distribution shift that imitation learning often suffers. In experiments on a suite of Arithmetic Equation benchmarks, our model consistently outperforms the autoregressive baselines in terms of performance, efficiency, and robustness. We hope our findings will shed light on future studies in reinforcement learning applying sequence-level action generation to natural language processing., Comment: Accepted to Findings of EMNLP 2022

Methamphetamine (METH) use disorder is highly prevalent among people with HIV (PWH) and is a significant public health problem. HIV and METH use are each associated with immune system dysfunction; however, the combined effects on the immune system are poorly understood. This cross-sectional project measured soluble immune biomarkers in plasma and cerebrospinal fluid (CSF) collected from a control group, people with a history of a METH use disorder (METH+), PWH with no history of METH use disorder (HIV+), and PWH with a history of METH use disorder (HIV+/METH+). HIV, METH, and immune dysfunction can also be associated with affective and cognitive deficits, so we characterized mood and cognition in our participants. Two factor analyses were performed for the plasma and CSF biomarkers. Plasma IL-8, Ccl2, VEGF, and 8-isoprostane loaded onto one factor that was highest in the HIV+/METH+ group (p < 0.047) reflecting worse inflammation, vascular injury, and oxidative stress. This plasma factor was also negatively correlated with delayed recall (R = -0.49, p = 0.010), which was worst in the HIV+/METH+ group (p = 0.030 compared to the control group). Overall, these data implicate that combined HIV-1 infection and METH use may exacerbate inflammation, leading to worse cognition.

BackgroundThe association between long-term cannabis use and balance disturbances has not been investigated in people living with HIV (PWH). We hypothesized that long-term cannabis use in PWH might be associated with more deleterious effects on balance than in HIV seronegative individuals due to potential neurotoxic interactions between HIV and cannabis.MethodsThree thousand six-hundred and forty-eight participants with and without HIV completed an interviewer-administered timeline follow-back assessment to assess lifetime days and quantity of cannabis use and other cannabis use characteristics. A structured clinical interview was used to collect any history of balance disturbance. Comparisons between HIV+ vs the HIV- groups and moderate-severe vs. no or minimal imbalance in participant characteristics (demographics, cannabis use, medication currently used, and neurological disease) were performed using Student t tests for continuous variables and Fisher's exact test for binary and categorical variables. Multivariate logistic regression was applied to determine the interaction effect of total quantity of cannabis use with HIV status on balance disturbance. Age, gender, cDSPN symptoms, gait ataxia, opioid medications, and sedatives were included as covariates in the adjusted model after variable selection. The effect sizes are presented as Cohen's d or odds ratios.ResultsOn average, participants were 45.4 years old (SD = 11 years), primarily male (77.7%), and non-Hispanic white (48.1%). A majority of participants were HIV+ (79.1%). Four hundred thirty (11.9%) of the participants reported balance disturbances within the past 10 years. PWH were more likely to have balance disturbances than demographically matched HIV-uninfected participants (odds ratio [OR] 2.66, 95% CI 1.91-3.7). Participants with moderate-severe balance disturbances did not differ from those with no or minimal imbalance in the proportion who had ever used cannabis (73.8% vs. 74.4%; p = 0.8) (OR

In this paper, cumulant approach is used in MQAM modulated signal recognition. This method uses the characteristics of higher-order cumulants and higher-order statistics to identify different kinds of MQAM signals. We focus on the modulation identification using statistical properties of MQAM signals. The reason of using this method is the ability of higher-order statistics to reflect the distribution characteristics of the constellation diagram.Thereare many benefits of using this method. This method needs only small amount of computations. It can effectively inhibit the effects of White Gaussian Noise. In many applications,the cumulants are applicable to distinguish between different amplitude or phase modulated signals like MQAM, MPSK,MASK. Differentmodulated signals have different cumulant values. Whenever we use higher order cumulants, we will get higher degree to distinguish the type of modulation scheme; the higher order cumulants require a large amount of data. A good characteristic of this method is that: the value of higher order cumulants (more than two orders), for the Gaussian noise is zero, so the use of higher-order cumulants characteristics can effectively remove the impact of the Gaussian noise.Simulation results reflectthe validity of proposed algorithm.

In this paper, cumulant approach is used in MQAM modulated signal recognition. This method uses the characteristics of higher-order cumulants and higher-order statistics to identify different kinds of MQAM signals. We focus on the modulation identification using statistical properties of MQAM signals. The reason of using this method is the ability of higher-order statistics to reflect the distribution characteristics of the constellation diagram.Thereare many benefits of using this method. This method needs only small amount of computations. It can effectively inhibit the effects of White Gaussian Noise. In many applications,the cumulants are applicable to distinguish between different amplitude or phase modulated signals like MQAM, MPSK,MASK. Differentmodulated signals have different cumulant values. Whenever we use higher order cumulants, we will get higher degree to distinguish the type of modulation scheme; the higher order cumulants require a large amount of data. A good characteristic of this method is that: the value of higher order cumulants (more than two orders), for the Gaussian noise is zero, so the use of higher-order cumulants characteristics can effectively remove the impact of the Gaussian noise.Simulation results reflectthe validity of proposed algorithm.

In this paper, cumulant approach is used in MQAM modulated signal recognition. This method uses the characteristics of higher-order cumulants and higher-order statistics to identify different kinds of MQAM signals. We focus on the modulation identification using statistical properties of MQAM signals. The reason of using this method is the ability of higher-order statistics to reflect the distribution characteristics of the constellation diagram.Thereare many benefits of using this method. This method needs only small amount of computations. It can effectively inhibit the effects of White Gaussian Noise. In many applications,the cumulants are applicable to distinguish between different amplitude or phase modulated signals like MQAM, MPSK,MASK. Differentmodulated signals have different cumulant values. Whenever we use higher order cumulants, we will get higher degree to distinguish the type of modulation scheme; the higher order cumulants require a large amount of data. A good characteristic of this method is that: the value of higher order cumulants (more than two orders), for the Gaussian noise is zero, so the use of higher-order cumulants characteristics can effectively remove the impact of the Gaussian noise.Simulation results reflectthe validity of proposed algorithm.

In this paper, cumulant approach is used in MQAM modulated signal recognition. This method uses the characteristics of higher-order cumulants and higher-order statistics to identify different kinds of MQAM signals. We focus on the modulation identification using statistical properties of MQAM signals. The reason of using this method is the ability of higher-order statistics to reflect the distribution characteristics of the constellation diagram.Thereare many benefits of using this method. This method needs only small amount of computations. It can effectively inhibit the effects of White Gaussian Noise. In many applications,the cumulants are applicable to distinguish between different amplitude or phase modulated signals like MQAM, MPSK,MASK. Differentmodulated signals have different cumulant values. Whenever we use higher order cumulants, we will get higher degree to distinguish the type of modulation scheme; the higher order cumulants require a large amount of data. A good characteristic of this method is that: the value of higher order cumulants (more than two orders), for the Gaussian noise is zero, so the use of higher-order cumulants characteristics can effectively remove the impact of the Gaussian noise.Simulation results reflectthe validity of proposed algorithm.

In this paper, cumulant approach is used in MQAM modulated signal recognition. This method uses the characteristics of higher-order cumulants and higher-order statistics to identify different kinds of MQAM signals. We focus on the modulation identification using statistical properties of MQAM signals. The reason of using this method is the ability of higher-order statistics to reflect the distribution characteristics of the constellation diagram.Thereare many benefits of using this method. This method needs only small amount of computations. It can effectively inhibit the effects of White Gaussian Noise. In many applications,the cumulants are applicable to distinguish between different amplitude or phase modulated signals like MQAM, MPSK,MASK. Differentmodulated signals have different cumulant values. Whenever we use higher order cumulants, we will get higher degree to distinguish the type of modulation scheme; the higher order cumulants require a large amount of data. A good characteristic of this method is that: the value of higher order cumulants (more than two orders), for the Gaussian noise is zero, so the use of higher-order cumulants characteristics can effectively remove the impact of the Gaussian noise.Simulation results reflectthe validity of proposed algorithm.