430 research outputs found

    The feasibility and microbial community dynamics of using down flow hanging sponges (DHS) reactor in treating high strength soft drink wastewater

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    The feasibility of using a standalone down-flow hanging sponge (DHS) reactor to treat high organic strength soft drink wastewater was investigated by operation over 700 days. At the same time, the microbial compositions were characterized and related to reactor performance. Synthetic wastewater at a concentration of 3000 mg/L chemical oxygen demand (COD) was directly fed to two identical DHS reactors operated in parallel. The effluent from these two reactors was then combined and fed to a third DHS reactor identical as the first two in physical scale. The first two DHS reactors were operated with a hydraulic retention time (HRT) of 15.3 hours and an organic loading rate of 4.9 kg COD/m3 sponge volume/day, and achieved > 90% organic matters removal efficiency. The third reactor consistently achieved a final effluent COD 60% of organic and nitrogen species contents were removed at the upper part of the reactor. The microbial community analyses together with redundancy analysis revealed that the community structures could be distinguished based on the locations of individual sponges taken along the reactor. Also, microbial community structures were continuously shifted during the entire operation period and a feeding accident influenced the community structures significantly. In general, at the end of the operation period, OTUs in phylum Proteobacteria were more abundant in the reactor with good organic removal efficiency (>90%) than that with poor efficiency (<50%). In contract, OTUs related to Bacteroidetes was observed to be more abundant in the reactor with poor organic removal efficiency. OTUs closely related to Tolumonas auensis, and Rivicola pingtungensis had higher abundance in the upper part communities than middle and lower part of the reactor with good organic removal efficiency and these OTUs were likely targeting the major components in the feeding substrate. In addition, the lower abundance of these OTUs in the upper part of the reactor with poor organic removal efficiency than that with good efficiency might also indicate the importance of these OTUs in treating the soft drink wastewater tested in this study

    TKwinFormer: Top k Window Attention in Vision Transformers for Feature Matching

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    Local feature matching remains a challenging task, primarily due to difficulties in matching sparse keypoints and low-texture regions. The key to solving this problem lies in effectively and accurately integrating global and local information. To achieve this goal, we introduce an innovative local feature matching method called TKwinFormer. Our approach employs a multi-stage matching strategy to optimize the efficiency of information interaction. Furthermore, we propose a novel attention mechanism called Top K Window Attention, which facilitates global information interaction through window tokens prior to patch-level matching, resulting in improved matching accuracy. Additionally, we design an attention block to enhance attention between channels. Experimental results demonstrate that TKwinFormer outperforms state-of-the-art methods on various benchmarks. Code is available at: https://github.com/LiaoYun0x0/TKwinFormer.Comment: 11 pages, 7 figure

    DAMIC at SNOLAB

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    We introduce the fully-depleted charge-coupled device (CCD) as a particle detector. We demonstrate its low energy threshold operation, capable of detecting ionizing energy depositions in a single pixel down to 50 eVee. We present results of energy calibrations from 0.3 keVee to 60 keVee, showing that the CCD is a fully active detector with uniform energy response throughout the silicon target, good resolution (Fano ~0.16), and remarkable linear response to electron energy depositions. We show the capability of the CCD to localize the depth of particle interactions within the silicon target. We discuss the mode of operation and unique imaging capabilities of the CCD, and how they may be exploited to characterize and suppress backgrounds. We present the first results from the deployment of 250 um thick CCDs in SNOLAB, a prototype for the upcoming DAMIC100. DAMIC100 will have a target mass of 0.1 kg and should be able to directly test the CDMS-Si signal within a year of operation.Comment: 13 pages, 12 figures, proceedings prepared for 13th International Conference on Topics in Astroparticle and Underground Physics (TAUP2013

    Conceptual design and progress of transmitting \sim MV DC HV into 4 K LHe detectors

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    A dual-phase TPC (Time Projection Chamber) is more advanced in characterizing an event than a single-phase one because it can, in principle, reconstruct the 3D (X-Y-Z) image of the event, while a single-phase detector can only show a 2D (X-Y) picture. As a result, more enriched physics is expected for a dual-phase detector than a single-phase one. However, to build such a detector, DC HV (High Voltage) must be delivered into the chamber (to have a static electric field), which is a challenging task, especially for an LHe detector due to the extremely low temperature, \sim 4 K, and the very high voltage, \sim MV (Million Volts). This article introduces a convincing design for transmitting \sim MV DC into a 4 K LHe detector. We also report the progress of manufacturing a 100 kV DC feedthrough capable of working at 4 K. Surprisingly, we realized that the technology we developed here might be a valuable reference to the scientists and engineers aiming to build residential bases on the Moon or Mars

    Searching for ER and/or NR-like dark matter signals with the especially low background liquid helium TPCs

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    In the Dark Matter (DM) direct detection community, the absence of convincing signals has become a ``new normal'' for decades. Among other possibilities, the ``new normal'' might indicate that DM-matter interactions could generate not only the hypothetical NR (Nuclear Recoil) events but also the ER (Electron Recoil) ones, which have often been tagged as backgrounds historically. Further, we argue that ER and NR-like DM signals could co-exist in a DM detector's same dataset. So in total, there would be three scenarios we can search for DM signals: (i) ER excess only, (ii) NR excess only, and (iii) ER and NR excesses combined. To effectively identify any possible DM signal under the three scenarios, a DM detector should (a) have the minimum ER and NR backgrounds and (b) be capable of discriminating ER events from NR ones. Accordingly, we introduce the newly established project, ALETHEIA, which implements liquid helium-filled TPCs (Time Projection Chamber) in hunting for DM. Thanks to the nearly single-digit number of ER and NR backgrounds on 1 ton*yr exposure, presumably, the ALETHEIA detectors should be able to identify any form of DM-induced excess in its ROI (Research Of Interest). As far as we know, ALETHEIA is the first DM direct detection experiment claiming such an inclusive search; conventional detectors search DM mainly on the ``ER excess only'' and/or the ``NR excess only'' channel, not the ``ER and NR excesses combined'' channel. In addition, we introduce a preliminary scheme to one of the most challenging R\&D tasks, transmitting 500+ kV into a 4 K LHe detector

    Bacillus cereus Isolated From Vegetables in China: Incidence, Genetic Diversity, Virulence Genes, and Antimicrobial Resistance

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    Bacillus cereus is a food-borne opportunistic pathogen that can induce diarrheal and emetic symptoms. It is widely distributed in different environments and can be found in various foods, including fresh vegetables. As their popularity grows worldwide, the risk of bacterial contamination in fresh vegetables should be fully evaluated, particularly in vegetables that are consumed raw or processed minimally, which are not commonly sterilized by enough heat treatment. Thereby, it is necessary to perform potential risk evaluation of B. cereus in vegetables. In this study, 294 B. cereus strains were isolated from vegetables in different cities in China to analyze incidence, genetic polymorphism, presence of virulence genes, and antimicrobial resistance. B. cereus was detected in 50% of all the samples, and 21/211 (9.95%) of all the samples had contamination levels of more than 1,100 MPN/g. Virulence gene detection revealed that 95 and 82% of the isolates harbored nheABC and hblACD gene clusters, respectively. Additionally, 87% of the isolates harbored cytK gene, and 3% of the isolates possessed cesB. Most strains were resistant to rifampicin and β-lactam antimicrobials but were sensitive to imipenem, gentamicin, ciprofloxacin, kanamycin, telithromycin, ciprofloxacin, and chloramphenicol. In addition, more than 95.6% of the isolates displayed resistance to three kinds of antibiotics. Based on multilocus sequence typing, all strains were classified into 210 different sequence types (STs), of which 145 isolates were assigned to 137 new STs. The most prevalent ST was ST770, but it included only eight isolates. Taken together, our research provides the first reference for the incidence and characteristics of B. cereus in vegetables collected throughout China, indicating a potential hazard of B. cereus when consuming vegetables without proper handling

    Utilization of multiple genetic methods for prenatal diagnosis of rare thalassemia variants

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    Background: Thalassemia is the most prevalent monogenic disorder caused by an imbalance between the α- and β-globin chains as a result of pathogenic variants in the α- or β-globin genes. Novel or complex structural changes in globin genes are major hurdles for genetic consulting and prenatal diagnosis.Methods: From 2020 to 2022, genetic analysis was performed on 1,316 families suspected of having children with thalassemia major, including 42 pregnant couples suspected of being thalassemia carriers with rare variants. Multiple techniques including multiplex ligation-dependent probe amplification (MLPA), Sanger sequencing, targeted next-generation sequencing, and single-molecule real-time (SMRT) sequencing were used to diagnose rare thalassemia.Results: The rate of prenatal diagnosis for rare thalassemia variants was 3.19% (42/1,316). The most prevalent alleles of α- and β-thalassemia are Chinese Gγ(Aγδβ)0and -- THAI deletion. In addition, ten rare complex genotypes include one Chinese Gγ(Aγδβ)0 deletion combined with HBG1-HBG2 fusion, two rare deletions at HBB gene (hg38, Chr11: 5224211-5232470, hg38, Chr11: 5224303-5227790), one complete 7,412 bp fusion gene for anti-Lepore Hong Kong, two complex rearrangements of the α-globin gene cluster, two novel duplications, and two rare large deletions in the α-globin gene cluster.Conclusion: Accurate gene diagnosis for probands with combined molecular biology techniques is the key to prenatal diagnosis of rare thalassemia

    Search for supersymmetry in events with opposite-sign dileptons and missing transverse energy using an artificial neural network

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    In this paper, a search for supersymmetry (SUSY) is presented in events with two opposite-sign isolated leptons in the final state, accompanied by hadronic jets and missing transverse energy. An artificial neural network is employed to discriminate possible SUSY signals from a standard model background. The analysis uses a data sample collected with the CMS detector during the 2011 LHC run, corresponding to an integrated luminosity of 4.98  fb-1 of proton-proton collisions at the center-of-mass energy of 7 TeV. Compared to other CMS analyses, this one uses relaxed criteria on missing transverse energy (E̸T>40  GeV) and total hadronic transverse energy (HT>120  GeV), thus probing different regions of parameter space. Agreement is found between standard model expectation and observations, yielding limits in the context of the constrained minimal supersymmetric standard model and on a set of simplified model

    CMS distributed computing workflow experience

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    The vast majority of the CMS Computing capacity, which is organized in a tiered hierarchy, is located away from CERN. The 7 Tier-1 sites archive the LHC proton-proton collision data that is initially processed at CERN. These sites provide access to all recorded and simulated data for the Tier-2 sites, via wide-area network (WAN) transfers. All central data processing workflows are executed at the Tier-1 level, which contain re-reconstruction and skimming workflows of collision data as well as reprocessing of simulated data to adapt to changing detector conditions. This paper describes the operation of the CMS processing infrastructure at the Tier-1 level. The Tier-1 workflows are described in detail. The operational optimization of resource usage is described. In particular, the variation of different workflows during the data taking period of 2010, their efficiencies and latencies as well as their impact on the delivery of physics results is discussed and lessons are drawn from this experience. The simulation of proton-proton collisions for the CMS experiment is primarily carried out at the second tier of the CMS computing infrastructure. Half of the Tier-2 sites of CMS are reserved for central Monte Carlo (MC) production while the other half is available for user analysis. This paper summarizes the large throughput of the MC production operation during the data taking period of 2010 and discusses the latencies and efficiencies of the various types of MC production workflows. We present the operational procedures to optimize the usage of available resources and we the operational model of CMS for including opportunistic resources, such as the larger Tier-3 sites, into the central production operation
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