MOSAIC: A Multi-Objective Optimization Framework for Sustainable Datacenter Management

In recent years, cloud service providers have been building and hosting datacenters across multiple geographical locations to provide robust services. However, the geographical distribution of datacenters introduces growing pressure to both local and global environments, particularly when it comes to water usage and carbon emissions. Unfortunately, efforts to reduce the environmental impact of such datacenters often lead to an increase in the cost of datacenter operations. To co-optimize the energy cost, carbon emissions, and water footprint of datacenter operation from a global perspective, we propose a novel framework for multi-objective sustainable datacenter management (MOSAIC) that integrates adaptive local search with a collaborative decomposition-based evolutionary algorithm to intelligently manage geographical workload distribution and datacenter operations. Our framework sustainably allocates workloads to datacenters while taking into account multiple geography- and time-based factors including renewable energy sources, variable energy costs, power usage efficiency, carbon factors, and water intensity in energy. Our experimental results show that, compared to the best-known prior work frameworks, MOSAIC can achieve 27.45x speedup and 1.53x improvement in Pareto Hypervolume while reducing the carbon footprint by up to 1.33x, water footprint by up to 3.09x, and energy costs by up to 1.40x. In the simultaneous three-objective co-optimization scenario, MOSAIC achieves a cumulative improvement across all objectives (carbon, water, cost) of up to 4.61x compared to the state-of-the-arts

SHIELD: Sustainable Hybrid Evolutionary Learning Framework for Carbon, Wastewater, and Energy-Aware Data Center Management

Today's cloud data centers are often distributed geographically to provide robust data services. But these geo-distributed data centers (GDDCs) have a significant associated environmental impact due to their increasing carbon emissions and water usage, which needs to be curtailed. Moreover, the energy costs of operating these data centers continue to rise. This paper proposes a novel framework to co-optimize carbon emissions, water footprint, and energy costs of GDDCs, using a hybrid workload management framework called SHIELD that integrates machine learning guided local search with a decomposition-based evolutionary algorithm. Our framework considers geographical factors and time-based differences in power generation/use, costs, and environmental impacts to intelligently manage workload distribution across GDDCs and data center operation. Experimental results show that SHIELD can realize 34.4x speedup and 2.1x improvement in Pareto Hypervolume while reducing the carbon footprint by up to 3.7x, water footprint by up to 1.8x, energy costs by up to 1.3x, and a cumulative improvement across all objectives (carbon, water, cost) of up to 4.8x compared to the state-of-the-art

Endometrial microbiota in women with and without adenomyosis: A pilot study

IntroductionThe endometrial microbiota plays an essential role in the health of the female reproductive system. However, the interactions between the microbes in the endometrium and their effects on adenomyosis remain obscure.Materials and methodsWe profile endometrial samples from 38 women with (n=21) or without (n=17) adenomyosis to characterize the composition of the microbial community and its potential function in adenomyosis using 5R 16S rRNA gene sequencing.ResultsThe microbiota profiles of patients with adenomyosis were different from the control group without adenomyosis. Furthermore, analysis identified Lactobacillus zeae, Burkholderia cepacia, Weissella confusa, Prevotella copri, and Citrobacter freundii as potential biomarkers for adenomyosis. In addition, Citrobacter freundii, Prevotella copri, and Burkholderia cepacia had the most significant diagnostic value for adenomyosis. PICRUSt results identified 30 differentially regulated pathways between the two groups of patients. In particular, we found that protein export, glycolysis/gluconeogenesis, alanine, aspartate, and glutamate metabolism were upregulated in adenomyosis. Our results clarify the relationship between the endometrial microbiota and adenomyosis.DiscussionThe endometrial microbiota of adenomyosis exhibits a unique structure and Citrobacter freundii, Prevotella copri, and Burkholderia cepacia were identified as potential pathogenic microorganisms associated with adenomyosis. Our findings suggest that changes in the endometrial microbiota of patients with adenomyosis are of potential value for determining the occurrence, progression, early of diagnosis, and treatment oadenomyosis

Factors influencing cognitive function in patients with Huntington's disease from China: A cross-sectional clinical study.

BACKGROUND AND AIM Huntington's disease (HD) is an autosomal dominant inherited neurodegenerative disorder caused by CAG repeats expansion. Cognitive decline contributes to the loss of daily activity in manifest HD. We aimed to examine the cognition status in a Chinese HD cohort and explore factors influencing the diverse cognitive domains. METHODS A total of 205 participants were recruited in the study with the assessment by neuropsychological batteries, including the mini-mental state examination (MMSE), Stroop test, symbol digit modalities test (SDMT), trail making test (TMT), verbal fluency test (VFT), and Hopkins verbal learning test-revised, as well as motor and psychiatric assessment. Pearson correlation and multiple linear regression models were applied to investigate the correlation. RESULTS Only 41.46% of patients had normal global function first come to our center. There was a significantly difference in MMSE, Stroop test, SDMT, TMT, and VFT across each stage of HD patients (p < .05). Apathy of PBA-s was correlated to MMSE, animal VFT and Stroop-interference tests performance. Severity of motor symptoms, functional capacity, age, and age of motor symptom onset were correlated to all neuropsychological scores, whereas education attainment and diagnostic delay were correlated to most neuropsychological scores except TMT. Severity of motor symptoms, functional capacity, and education attainment showed independent predicting effect (p < .05) in diverse cognitive domains. CONCLUSION Cognitive impairment was very common in Chinese HD patients at the first visit and worse in the patients in advanced phase. The severity of motor symptoms and functional capacity were correlated to the diverse cognitive domains

An Adaptive Visible Watermark Embedding Method based on Region Selection

Aiming at the problem that the robustness, visibility, and transparency of the existing visible watermarking technologies are difficult to achieve a balance, this paper proposes an adaptive embedding method for visible watermarking. Firstly, the salient region of the host image is detected based on superpixel detection. Secondly, the flat region with relatively low complexity is selected as the embedding region in the nonsalient region of the host image. Then, the watermarking strength is adaptively calculated by considering the gray distribution and image texture complexity of the embedding region. Finally, the visible watermark image is adaptively embedded into the host image with slight adjustment by just noticeable difference (JND) coefficient. The experimental results show that our proposed method improves the robustness of visible watermarking technology and greatly reduces the risk of malicious removal of visible watermark image. Meanwhile, a good balance between the visibility and transparency of the visible watermark image is achieved, which has the advantages of high security and ideal visual effect

RNA-seq reveals co-dysregulated circular RNAs in the adenomyosis eutopic endometrium and endometrial–myometrial interface

Abstract Background Uterine adenomyosis is associated with chronic pelvic pain, abnormal uterine bleeding, and infertility. The pathogenesis of adenomyosis is still unclear. Circular RNAs (circRNAs) have been implicated in several benign diseases and malignant tumors. We aimed to explore the co-dysregulated circular RNA profile in the eutopic endometrium and endometrial–myometrial interface (EMI) of adenomyosis. Methods Total RNA was extracted from the eutopic endometrium and EMI of 5 patients with adenomyosis and 3 patients without adenomyosis. Next-generation sequencing was performed to identify the circRNA expression profile of the two tissue types. Bioinformatics analysis was performed to predict circRNA-binding miRNAs and miRNA-binding mRNAs and construct ceRNA networks, and functional enrichment analysis was performed to predict the biological functions of circRNAs. Results Among the adenomyosis patients, 760 circRNAs were significantly upregulated and 119 circRNAs were significantly downregulated in the EMI of adenomyosis, while 47 circRNAs were significantly upregulated and 17 circRNAs were significantly downregulated in the eutopic endometrium of adenomyosis. We identified hsa_circ_0002144 and hsa_circ_0005806 as co-upregulated and hsa_circ_0079536 and hsa_circ_0024766 as co-downregulated in the eutopic endometrium and EMI. Bioinformatics analysis was performed to construct a ceRNA network of codifferentially expressed circRNAs. The MAPK signaling pathway is the most important signaling pathway involved in the function of the ceRNA network. Conclusions Co-dysregulated circRNAs were present in the eutopic endometrium and EMI of adenomyosis. MiRNA binding sites were observed for all of these circRNAs and found to regulate gene expression. Co-dysregulated circRNAs may induce the eutopic endometrial invagination process through the MAPK signaling pathway and promote the progression of adenomyosis

Selection of Aptamers Specific for DEHP Based on ssDNA Library Immobilized SELEX and Development of Electrochemical Impedance Spectroscopy Aptasensor

A selection of aptamers specific for di(2-ethylhexyl) phthalate (DEHP) and development of electrochemical impedance spectroscopy (EIS) aptasensor are described in this paper. The aptamers were selected from an immobilized ssDNA library using the systematic evolution of ligands by exponential enrichment (SELEX). The enrichment was monitored using real-time quantitative PCR (Q-PCR), and the aptamers were identified by high-throughput sequencing (HTS), gold nanoparticles (AuNPs) colorimetric assay, and localized surface plasmon resonance (LSPR). The EIS aptasensor was developed to detect DEHP in water samples. After eight rounds of enrichment, HTS, AuNPs colorimetric assay, and LSPR analysis indicated that four aptamers had higher binding activity, and aptamer 31 had the highest affinity (Kd = 2.26 &plusmn; 0.06 nM). The EIS aptasensor had a limit of detection (LOD) of 0.103 pg/mL with no cross-reactivity to DEHP analogs and a mean recovery of 76.07% to 141.32% for detection of DEHP in water samples. This aptamer is novel with the highest affinity and sensitivity

Effect of dietary inclusion of antioxidants and organic trace minerals on growth performance, carcass characteristics, and meat quality of finishing pigs with pre-slaughter transportation

A total of 320 pigs (body weight = 98 ± 4 kg) were assigned to four treatments, with eight replicates (pens) per treatment. Pigs were fed the following diets: a control diet (CON), the CON diet plus antioxidant blends (AOX), organic trace minerals (OTM), or both (AOX + OTM). After the feeding trial, two pigs from each pen were selected for slaughtering right away or after transportation. The inclusion of AOX, OTM, or AOX + OTM had no significant effect on feed intake, average daily gain, and feed efficiency compared with CON (P > 0.05). The pre-transportation significantly reduced the pH value of loin meat at 24 h post mortem and leg meat at 45 min post mortem (P < 0.05). The pigs in the AOX, OTM, and AOX + OTM group had significantly lower plasma malondialdehyde (MDA) content than the CON group (P < 0.05). Pre-transportation resulted in significantly higher meat MDA contents (P < 0.05), clearly influencing the oxidative stress of pigs. The inclusion of antioxidant blends or organic trace minerals had no significant effect on the growth performance and antioxidant capacity of finishing pigs.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Measuring Web Feature Impacts in BitTorrent-like Systems

In Peer-to-Peer (P2P) file sharing systems, the attributes of resource description can influence the user behavior, especially on resource selection. However, this has been only qualitatively speculated but lacks of quantitative analysis. In this paper, we carry out a systematically quantitative study on the impact of these attributes presented in the form of web features, by measuring the largest BitTorrent website in CERNET. The measurement lasts for 31 days, and there are 168,610 records containing 11,228 distinct resources collected. The result is twofold. On one hand, it confirms the above qualitative speculation; on the other hand, it shows more significant findings: (1) with the highlight feature on popular items, the downloads of each resource yield to a long-tail distribution however deviating from Zipf Law; (2) publications with attracting titles disseminate 1.9 times faster than others; (3) publisher authority feature does not evidently help the system escaping from malicious resources' pervasion; (4) other features such as taxonomy and size also influence users' choice. We further demonstrate the implications of the web feature impact for system designers and potential attackers. © Copyright 2008 ICST

Measuring web feature impacts in Peer-to-Peer file sharing systems

In Peer-to-Peer (P2P) file sharing systems, the presentation of resource attributes organized in different web features can influence users' selection. However, this has been only qualitatively speculated without concrete analysis. In this paper, we conduct extensive quantitative measurements on the impacts of these attributes by crawling web pages of a BitTorrent site, "5QZone". The measurement lasts for 31 days, and 168,610 records containing 11,228 distinct resources have been collected. We further compare it with one-day commercial measurement data from a hybrid file sharing site, "Xunlei", which contains 5,473,283 resources for 5,156,696 participating users. The finding is twofold. On one hand. it confirms the above qualitative speculation; on the other hand, it shows more significant results: (1) with the highlight feature on popular items, the downloads of each resource yield to a long-tail distribution, deviated from Zipf Law: (2) publications with attracting titles disseminate substantially faster than others; (3) publisher authority feature has limited influence on depressing low quality resources; (4) other features such as presenting resource categories and sizes also affect user behavior. We further demonstrate the implications of the web feature impact for system design and potential attackers. (C) 2009 Elsevier B.V. All rights reserved