116 research outputs found

    A Data Collecting Strategy for Farmland WSNs using a Mobile Sink

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    To the characteristics of large number of sensor nodes, wide area and unbalanced energy consumption in farmland Wireless Sensor Networks, an efficient data collection strategy (GCMS) based on grid clustering and a mobile sink is proposed. Firstly, cluster is divided based on virtual grid, and the cluster head is selected by considering node position and residual energy. Then, an optimal mobile path and residence time allocation mechanism for mobile sink are proposed. Finally, GCMS is simulated and compared with LEACH and GRDG. Simulation results show that GCMS can significantly prolong the network lifetime and increase the amount of data collection, especially suitable for large-scale farmland Wireless Sensor Networks

    Delay-Dependent Stability of Single-Loop Controlled Grid-Connected Inverters with LCL Filters

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    LCL filters have been widely used for grid-connected inverters. However, the problem that how time delay affects the stability of digitally controlled grid-connected inverters with LCL filters has not been fully studied. In this paper, a systematic study is carried out on the relationship between the time delay and stability of single-loop controlled grid-connected inverters that employ inverter current feedback (ICF) or grid current feedback (GCF). The ranges of time delay for system stability are analyzed and deduced in the continuous s-domain and discrete z-domain. It is shown that in the optimal range, the existence of time delay weakens the stability of the ICF loop, whereas a proper time delay is required for the GCF loop. The present work explains, for the first time, why different conclusions on the stability of ICF loop and GCF loop have been drawn in previous studies. To improve system stability, a linear predictor-based time delay reduction method is proposed for ICF, while a time delay addition method is used for GCF. A controller design method is then presented that guarantees adequate stability margins. The delay-dependent stability study is verified by simulation and experiment

    The relationship between Comprehensive Geriatric Assessment parameters and depression in elderly patients

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    BackgroundDepression is common and serious among elderly patients. The treatment of elderly depression is often delayed owing to insufficient diagnosis, which eventually leads to adverse consequences.AimsTo explore the association between the parameters of the Comprehensive Geriatric Assessment and depression in elderly patients.MethodsA cross-sectional study of 211 outpatients and inpatients aged ≥ 65 years from the Comprehensive Geriatric Assessment database was conducted. A Comprehensive Geriatric Assessment inventory was prepared by compiling and screening general characteristics, chronic diseases (cardiovascular disease, diabetes, and peptic ulcer disease), nutritional status, daily living ability, anthropometric measurements (body mass index (BMI), upper arm circumference, and calf circumference), and blood biochemical indicators (hemoglobin, albumin, prealbumin, triglycerides, and low-density lipoprotein cholesterol). The Geriatric Depression Scale was also conducted for each elderly patient to screen for depression. A multivariable logistic regression analysis was used to determine the association between the parameters of the Comprehensive Geriatric Assessment and geriatric depression.ResultsThere were 63 patients in the depression group with a median age of 84.00 years, and 148 patients in the non-depression group with a median age of 78.50 years. After controlling for confounders, the risk of depression in elderly patients with cardiovascular diseases was 6.011 times higher than that in those without cardiovascular diseases (p < 0.001); and the risk of depression in elderly patients with peptic ulcer diseases was 4.352 times higher than that in those without peptic ulcer diseases (p < 0.001); the risk of depression in elderly patients decreased by 22.6% for each 1-point increase in the Mini Nutritional Assessment (p < 0.001). The risk of depression in elderly patients decreased by 19.9% for each 1-point increase in calf circumference (p = 0.002), and by 13.0% for each 1-point increase in albumin (p = 0.014).ConclusionOur findings suggest that Comprehensive Geriatric Assessment parameters, such as cardiovascular disease, peptic ulcer disease, Mini Nutritional Assessment score, calf circumference, and albumin, were associated with depression. The Comprehensive Geriatric Assessment can assist in the early identification of depression in the elderly population

    Kinetics and Mechanism Study of Competitive Inhibition of Jack-Bean Urease by Baicalin

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    Baicalin (BA) is the principal component of Radix Scutellariae responsible for its pharmacological activity. In this study, kinetics and mechanism of inhibition by BA against jack-bean urease were investigated for its therapeutic potential. It was revealed that the IC50 of BA against jack-bean urease was 2.74 ± 0.51 mM, which was proved to be a competitive and concentration-dependent inhibition with slow-binding progress curves. The rapid formation of initial BA-urease complex with an inhibition constant of Ki=3.89 × 10−3 mM was followed by a slow isomerization into the final complex with an overall inhibition constant of Ki*=1.47×10-4 mM. High effectiveness of thiol protectors against BA inhibition indicated that the strategic role of the active-site sulfhydryl group of the urease was involved in the blocking process. Moreover, the inhibition of BA was proved to be reversible due to the fact that urease could be reactivated by dithiothreitol but not reactant dilution. Molecular docking assay suggested that BA made contacts with the important activating sulfhydryl group Cys-592 residues and restricted the mobility of the active-site flap. Taken together, it could be deduced that BA was a competitive inhibitor targeting thiol groups of urease in a slow-binding manner both reversibly and concentration-dependently, serving as a promising urease inhibitor for treatments on urease-related diseases

    Studies on Synthesis and Structure-Activity Relationship (SAR) of Derivatives of a New Natural Product from Marine Fungi as Inhibitors of Influenza Virus Neuraminidase

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    Based on the natural isoprenyl phenyl ether from a mangrove-derived fungus, 32 analogues were synthesized and evaluated for inhibitory activity against influenza H1N1 neuraminidase. Compound 15 (3-(allyloxy)-4-hydroxybenzaldehyde) exhibited the most potent inhibitory activity, with IC50 values of 26.96 μM for A/GuangdongSB/01/2009 (H1N1), 27.73 μM for A/Guangdong/03/2009 (H1N1), and 25.13 μM for A/Guangdong/ 05/2009 (H1N1), respectively, which is stronger than the benzoic acid derivatives (~mM level). These are a new kind of non-nitrogenous aromatic ether Neuraminidase (NA) inhibitors. Their structures are simple and the synthesis routes are not complex. The structure-activity relationship (SAR) analysis revealed that the aryl aldehyde and unsubstituted hydroxyl were important to NA inhibitory activities. Molecular docking studies were carried out to explain the SAR of the compounds, and provided valuable information for further structure modification

    HemoglobinA1c Is a Risk Factor for Changes of Bone Mineral Density: A Mendelian Randomization Study

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    BackgroundAs a valuable blood glucose measurement, HemoglobinA1c (HbA1c) is of great clinical value for diabetes. However, in previous observational studies, studies on its effect on bone mineral density (BMD) have different results. This study aimed to use Mendelian randomization (MR) to assess the effect of HbA1c on bone mineral density and fracture risk, and try to further explore whether this association was achieved through glycemic or non-glycemic factors.MethodsTake HbA1c measurement as exposure, and BMD estimated from quantitative heel ultrasounds (eBMD) and bone fractures as outcomes. Two-Sample MR Analysis was conducted to assess the causal effect of HbA1C on heel BMD and risk fracture. Then, we performed the analysis using two subsets of these variants, one related to glycemic measurement and the other to erythrocyte indices.ResultsGenetically increased HbA1C was associated with the lower heel eBMD [odds ratio (OR) 0.91 (95% CI 0.87, 0.96) per %-unit, P = 3 × 10−4(IVW)]. Higher HbA1C was associated with lower heel eBMD when using only erythrocytic variants [OR 0.87 (0.82, 0.93), P=2× 10−5(IVW)]; However, when using only glycemic variants, this casual association does not hold. In further MR analysis, we test the association of erythrocytic traits with heel eBMD.ConclusionOur study revealed the significant causal effect of HbA1c on eBMD, and this causal link might achieve through non-glycemic pathways (erythrocytic indices)

    Rankitect: Ranking Architecture Search Battling World-class Engineers at Meta Scale

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    Neural Architecture Search (NAS) has demonstrated its efficacy in computer vision and potential for ranking systems. However, prior work focused on academic problems, which are evaluated at small scale under well-controlled fixed baselines. In industry system, such as ranking system in Meta, it is unclear whether NAS algorithms from the literature can outperform production baselines because of: (1) scale - Meta ranking systems serve billions of users, (2) strong baselines - the baselines are production models optimized by hundreds to thousands of world-class engineers for years since the rise of deep learning, (3) dynamic baselines - engineers may have established new and stronger baselines during NAS search, and (4) efficiency - the search pipeline must yield results quickly in alignment with the productionization life cycle. In this paper, we present Rankitect, a NAS software framework for ranking systems at Meta. Rankitect seeks to build brand new architectures by composing low level building blocks from scratch. Rankitect implements and improves state-of-the-art (SOTA) NAS methods for comprehensive and fair comparison under the same search space, including sampling-based NAS, one-shot NAS, and Differentiable NAS (DNAS). We evaluate Rankitect by comparing to multiple production ranking models at Meta. We find that Rankitect can discover new models from scratch achieving competitive tradeoff between Normalized Entropy loss and FLOPs. When utilizing search space designed by engineers, Rankitect can generate better models than engineers, achieving positive offline evaluation and online A/B test at Meta scale.Comment: Wei Wen and Kuang-Hung Liu contribute equall

    Software-Hardware Co-design for Fast and Scalable Training of Deep Learning Recommendation Models

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    Deep learning recommendation models (DLRMs) are used across many business-critical services at Facebook and are the single largest AI application in terms of infrastructure demand in its data-centers. In this paper we discuss the SW/HW co-designed solution for high-performance distributed training of large-scale DLRMs. We introduce a high-performance scalable software stack based on PyTorch and pair it with the new evolution of Zion platform, namely ZionEX. We demonstrate the capability to train very large DLRMs with up to 12 Trillion parameters and show that we can attain 40X speedup in terms of time to solution over previous systems. We achieve this by (i) designing the ZionEX platform with dedicated scale-out network, provisioned with high bandwidth, optimal topology and efficient transport (ii) implementing an optimized PyTorch-based training stack supporting both model and data parallelism (iii) developing sharding algorithms capable of hierarchical partitioning of the embedding tables along row, column dimensions and load balancing them across multiple workers; (iv) adding high-performance core operators while retaining flexibility to support optimizers with fully deterministic updates (v) leveraging reduced precision communications, multi-level memory hierarchy (HBM+DDR+SSD) and pipelining. Furthermore, we develop and briefly comment on distributed data ingestion and other supporting services that are required for the robust and efficient end-to-end training in production environments

    The Effect of Plasma Triglyceride-Lowering Therapy on the Evolution of Organ Function in Early Hypertriglyceridemia-Induced Acute Pancreatitis Patients With Worrisome Features (PERFORM Study): Rationale and Design of a Multicenter, Prospective, Observational, Cohort Study

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    Background: Acute pancreatitis (AP) is a potentially life-threatening inflammatory disease with multiple etiologies. The prevalence of hypertriglyceridemia-induced acute pancreatitis (HTG-AP) has been increasing in recent years. It is reported that early triglyceride (TG) levels were associated with the severity of the disease, and TG- lowering therapies, including medical treatment and blood purification, may impact the clinical outcomes. However, there is no consensus regarding the optimal TG-lowering therapy, and clinical practice varies greatly among different centers. Our objective is to evaluate the TG-lowering effects of different therapies and their impact on clinical outcomes in HTG-AP patients with worrisome features. Methods: This is a multicenter, observational, prospective cohort study. A total of approximately 300 patients with HTG-AP with worrisome features are planned to be enrolled. The primary objective of the study is to evaluate the relationship between TG decline and the evolution of organ failure, and patients will be dichotomized depending on the rate of TG decline. The primary outcome is organ failure (OF) free days to 14 days after enrollment. Secondary outcomes include new-onset organ failure, new-onset multiple-organ failure (MOF), new-onset persistent organ failure (POF), new receipt of organ support, requirement of ICU admission, ICU free days to day 14, hospital free days to day 14, 60-day mortality, AP severity grade (Based on the Revised Atlanta Classification), and incidence of systemic and local complications. Generalized linear model (GLM), Fine and Gray competing risk regression, and propensity score matching will be used for statistical analysis. Discussion: Results of this study will reveal the current practice of TG-lowering therapy in HTG-AP and provide necessary data for future trials
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