Evaluation of short-term initial performance of a “Molekule Air” portable air cleaner

The aim of this project was to evaluate and characterize the performance of a MOLEKULE AIR air cleaner unit. The testing protocol comprised the evaluation of an unused Molekule Air unit operating at maximum (“boost” setting) fan speed setting. The device was tested over initial short-term periods of 70-80 h of continuous operation. The tested air cleaner was challenged in separate experiments with a well-characterized mixture of volatile organic compounds (VOCs), and with ozone. All tests were performed at realistic pollutant levels in a 20-m3 environmental stainless-steel chamber. Variables controlled and measured in this study included the chamber temperature, relative humidity, the composition and concentration of the challenge VOCs, and the concentrations of ozone. Potential formation of byproducts was also investigated to assess the overall performance

Transcriptome analysis reveals the important roles of a two-component system, flagellar assembly, active efflux system and outer membrane proteins in the anti-quinolone ability of Vibrio harveyi from orange-spotted grouper (<em>Epinephelus coioides</em>)

The drug resistance of Vibrio harveyi in aquaculture became more severe because the control of Vibriosis depends majorly on the current antibiotics. Transcriptomes of a wild-type strain (VS) and its quinolone-resistant mutants (VR) of V. harveyi were respectively sequenced by RNA-seq technology. A total of 2,082 unigenes were obtained after de novo splicing and assembly. 129 genes were identified with significant differential expression in strain VR compared to strain VS, among which 65 were up-regulated and 64 down-regulated. Then, functional annotation and enrichment analysis of these differentially expressed genes (DEGs) were performed. GO enrichment results showed that DEGs focused mainly on cell structure, substance metabolism, and transporter. COG classification of the DEGs mainly focused on amino acid transport and metabolism, cell wall/membrane biosynthesis, carbohydrate transport and metabolism, ribosomal structure, and biosynthesis. KEGG pathways related to a two-component system, ABC transport system and flagellar assembly (ko02040) were enriched significantly, and 9 genes associated with quinolone-resistance ability, including genes for resistance-related transport proteins, outer membrane proteins, and DNA repair-related proteins were discovered through analysis of the drug-resistance related genes. Ten DEGs (including the above part genes of 9 drug resistance-related genes) in the transcriptome data were taken to analyze their expression with real-time qPCR. The results were the same as the changes of the above transcriptome analysis, further confirming the reliability of the transcriptome sequencing and data analysis. In a word, genes from a two-component system, flagellar assembly, active efflux system and outer membrane proteins take great roles in the quinolone-resistance of V. harveyi. These results provide enough information for further study on the molecular mechanism of quinolone-resistance and give a helpful transcriptomic resource to unravel the contact between quinolone-resistance and metabolic pathways in Vibrios

Stochastic dividers for low latency neural networks

Due to the low complexity in arithmetic unit design, stochastic computing (SC) has attracted considerable interest to implement Artificial Neural Networks (ANNs) for resources-limited applications, because ANNs must usually perform a large number of arithmetic operations. To attain a high computation accuracy in an SC-based ANN, extended stochastic logic is utilized together with standard SC units and thus, a stochastic divider is required to perform the conversion between these logic representations. However, the conventional divider incurs in a large computation latency, so limits an SC implementation for ANNs used in applications needing high performance. Therefore, there is a need to design fast stochastic dividers for SC-based ANNs. Recent works (e.g., a binary searching and triple modular redundancy (BS-TMR) based stochastic divider) are targeting a reduction in computation latency, while keeping the same accuracy compared with the traditional design. However, this divider still requires $N$ iterations to deal with $2^{N}$ -bit stochastic sequences, and thus the latency increases in proportion to the sequence length. In this paper, a decimal searching and TMR (DS-TMR) based stochastic divider is initially proposed to further reduce the computation latency; it only requires two iterations to calculate the quotient, so regardless of the sequence length. Moreover, a trade-off design between accuracy and hardware is also presented. An SC-based Multi-Layer Perceptron (MLP) is then considered to show the effectiveness of the proposed dividers over current designs. Results show that when utilizing the proposed dividers, the MLP achieves the lowest computation latency while keeping the same classification accuracy; although incurring in an area increase, the overhead due to the proposed dividers is low over the entire MLP. When using as combined metric for both hardware design and computation complexity the product of the implementation area, latency, power and number of clock cycles, the proposed designs are also shown to be superior to the SC-based MLPs (at the same level of accuracy) employing other dividers found in the technical literature as well as the commonly used 32-bit floating point implementation.The work of Shanshan Liu, Farzad Niknia, and Fabrizio Lombardi was supported by the NSF Grant CCF-1953961 and Grant 1812467. The work of Pedro Reviriego was supported in part by the Spanish Ministry of Science and Innovation under project ACHILLES (Grant PID2019-104207RB-I00) and the Go2Edge Network (Grant RED2018-102585-T), and in part by the Madrid Community Research Agency under Grant TAPIR-CM P2018/TCS-4496. The work of Weiqiang Liu was supported by the NSFC under Grant 62022041 and Grant 61871216. The work of Ahmed Louri was supported by the NSF Grant CCF-1812495 and Grant 1953980

Enhancement of nitrate removal at the sediment-water interface by carbon addition plus vertical mixing

Author Posting. © The Author(s), 2014. This is the author's version of the work. It is posted here by permission of Elsevier for personal use, not for redistribution. The definitive version was published in Chemosphere 136 (2015): 305-310, doi:10.1016/j.chemosphere.2014.12.010.Wetlands and ponds are frequently used to remove nitrate from effluents or runoffs. However, the efficiency of this approach is limited. Based on the assumption that introducing vertical mixing to water column plus carbon addition would benefit the diffusion across the sediment–water interface, we conducted simulation experiments to identify a method for enhancing nitrate removal. The results suggested that the sediment-water interface has a great potential for nitrate removal, and the potential can be activated after several days of acclimation. Adding additional carbon plus mixing significantly increases the nitrate removal capacity, and the removal of total nitrogen (TN) and nitrate-nitrogen (NO3--N) is well fitted to a first-order reaction model. Adding Hydrilla verticillata debris as a carbon source increased nitrate removal, whereas adding Eichhornia crassipe decreased it. Adding ethanol plus mixing greatly improved the removal performance, with the removal rate of NO3--N and TN reaching 15.0-16.5 g m-2 d-1. The feasibility of this enhancement method was further confirmed with a wetland microcosm, and the NO3--N removal rate maintained at 10.0-12.0 g m-2 d-1 at a hydraulic loading rate of 0.5 m d-1.The present work was supported by the State Oceanic Administration of China (Demonstration project of coastal wetland restoration, north coast of Hangzhou Wan bay), the National Science Foundation of China under Grant No. 51378306 and 41471393, and Science and Technology Planning Project of Zhejiang Province No.2014F50003

Performance of a CO2 sorbent for indoor air cleaning applications: Effects of environmental conditions, sorbent aging, and adsorption of co-occurring formaldehyde.

Indoor air cleaning systems that incorporate CO2 sorbent materials enable HVAC load shifting and efficiency improvements. This study developed a bench-scale experimental system to evaluate the performance of a sorbent under controlled operation conditions. A thermostatic holder containing 3.15&nbsp;g sorbent was connected to a manifold that delivered CO2 -enriched air at a known temperature and relative humidity (RH). The air stream was also enriched with 0.8-2.1&nbsp;ppm formaldehyde. The CO2 concentration was monitored in real-time upstream and downstream of the sorbent, and integrated formaldehyde samples were collected at different times using DNPH-coated silica cartridges. Sorbent regeneration was carried out by circulating clean air in countercurrent. Almost 200 loading/regeneration cycles were performed in the span of 17&nbsp;months, from which 104 were carried out at reference test conditions defined by loading with air at 25°C, 38% RH, and 1000&nbsp;ppm CO2 , and regenerating with air at 80°C, 3% RH and 400&nbsp;ppm CO2 . The working capacity decreased slightly from 43-44&nbsp;mg CO2 per g sorbent to 39-40&nbsp;mg per g over the 17&nbsp;months. The capacity increased with lower loading temperature (in the range 15-35°C) and higher regeneration temperature, between 40 and 80°C. The CO2 capacity was not sensitive to the moisture content in the range 6-9&nbsp;g/m3 , and decreased slightly when dry air was used. Loading isothermal breakthrough curves were fitted to three simple adsorption models, verifying that pseudo-first-order kinetics appropriately describes the adsorption process. The model predicted that equilibrium capacities decreased with increasing temperature from 15 to 35°C, while adsorption rate constants slightly increased. The formaldehyde adsorption efficiency was 80%-99% in different cycles, corresponding to an average capacity of 86&nbsp;±&nbsp;36&nbsp;µg/g. Formaldehyde was not quantitatively released during regeneration, but its accumulation on the sorbent did not affect CO2 adsorption

Application of generalized equivalent uniform dose optimization in the treatment of nasopharyngeal carcinoma with intensity-modulated radiotherapy

Background and purpose: In the design of intensity-modulated radiotherapy (IMRT) for nasopharyngeal carcinoma, the traditional dose-volume (DV) physical optimization method is compared with the combined use of the DV physical optimization method and the generalized equivalent uniform dose (gEUD) optimization. This study aimed to investigate dosimetry differences in radiotherapy planning for nasopharyngeal carcinoma using gEUD method, to explore the effect of different optimization methods on the protection of organ at risk (OAR) in IMRT planning. Methods: Fifty patients with nasopharyngeal carcinoma in Eye &amp; ENT Hospital of Fudan University from 2019 to 2021 were randomly selected, and two optimization plans were used for each case at the same time for optimization calculation. Group A used the traditional DV physical optimization method, while group B combined DV optimization and gEUD optimization methods adopted, in which gEUD was selected as a=1, 2, 5, 10 and 20. We evaluated the results of OAR dose data obtained by using different optimization schemes and different a values. Results: The planned data of the two plans were compared and analyzed, and there was no statistically significant difference in the dosimetry index of the target area between groups (P&gt;0.05). However, in terms of the protection of the parotid gland and oral cavity, the results of the optimization plan of group B were significantly better compared with group A. The a value of gEUD had more obvious influence on the average dose of the parotid gland and the oral cavity. Conclusion: In the radiotherapy plan for nasopharyngeal carcinoma, the combined use of physical optimization and biological optimization can not only meet the target dose requirements but also better protect the parotid gland, oral cavity and other endangered OAR

Comparison of aroma and taste profiles of kiwi wine fermented with/without peel by combining intelligent sensory, gas chromatography-mass spectrometry, and proton nuclear magnetic resonance

Kiwi wine (KW) is tipically made by fermenting juice from peeled kiwifruit, resulting in the disposal of peel and pomace as by-products. However, the peel contains various beneficial compounds, like phenols and flavonoids. Since the peel is edible and rich in these compounds, incorporating it into the fermentation process of KW presents a potential solution to minimize by-product waste. This study compared the aroma and taste profiles of KW from peeled (PKW) and unpeeled (UKW) kiwifruits by combining intelligent sensory technology, GC-MS, and 1H-NMR. Focusing on aroma profiles, 75 volatile organic compounds (VOCs) were identified in KW fermented with peel, and 73 VOCs in KW without peel, with 62 VOCs common to both. Among these compounds, rose oxide, D-citronellol, and bornylene were more abundant in UKW, while hexyl acetate, isoamyl acetate, and 2,4,5-trichlorobenzene were significantly higher in PKW. For taste profiles, E-tongue analysis revealed differences in the taste profiles of KW from the two sources. A total of 74 molecules were characterized using 1H-NMR. UKW exhibited significantly higher levels of tartrate, galactarate, N-acetylserotonin, 4-hydroxy-3-methoxymandelate, fumarate, and N-acetylglycine, along with a significantly lower level of oxypurinol compared to PKW. This study seeks to develop the theoretical understanding of the fermentation of kiwifruit with peel in sight of the utilization of the whole fruit for KW production, to increase the economic value of kiwifruit production

Evaluation of a village-based digital health kiosks program: A protocol for a cluster randomized clinical trial

Background To address disparities in healthcare quality and access between rural and urban areas in China, reforms emphasize strengthening primary care and digital health utilization. Yet, evidence on digital health approaches in rural areas is lacking. Objective This study will evaluate the effectiveness of Guangdong Second Provincial General Hospital's Digital Health Kiosk program, which uses the Dingbei telemedicine platform to connect rural clinicians to physicians in upper-level health facilities and provide access to artificial intelligence-enabled diagnostic support. We hypothesize that our interventions will increase healthcare utilization and patient satisfaction, decrease out-of-pocket costs, and improve health outcomes. Methods This cluster randomized control trial will enroll clinics according to a partial factorial design. Clinics will be randomized to either a control arm with clinician medical training, a second arm additionally receiving Dingbei telemedicine training, or a third arm with monetary incentives for patient visits conducted through Dingbei plus all prior interventions. Clinics in the second and third arm will then be orthogonally randomized to a social marketing arm that targets villager awareness of the kiosk program. We will use surveys and Dingbei administrative data to evaluate clinic utilization, revenue, and clinician competency, as well as patient satisfaction and expenses. Results We have received ethical approval from Guangdong Second Provincial General Hospital (IRB approval number: GD2H-KY IRB-AF-SC.07-01.1), Peking University (IRB00001052-21007), and the University of North Carolina at Chapel Hill (323385). Study enrollment began April 2022. Conclusions This study has the potential to inform future telemedicine approaches and assess telemedicine as a method to address disparities in healthcare access. Trial registration number: ChiCTR210005387

Advances of hafnium based nanomaterials for cancer theranostics

Hafnium-based nanomaterials (Hf-NMs) have attracted the interest of numerous biomedical researchers by their unique properties. Recent years have witnessed significant advancements in the field of Hafnium-based nanomaterials, particularly in the context of cancer diagnosis and treatment. However, research in this area, especially concerning the clinical application of Hafnium-based nanomaterials, has not been thoroughly reviewed. This review will cover: 1) Classification and synthesis of Hafnium-based nanomaterials including Hafnium oxide nanomaterials, Hafnium Metal-Organic Frameworks/nanoscale coordination polymers (MOFs/NCPs); 2) Hafnium-based nanomaterials act as contrast enhancement agent for cancer imaging, and hafnium-based nanomaterials used for diagnosis in cancer liquid biopsy; 3) hafnium-based nanomaterials for cancer therapy, including hafnium-based nanomaterials for radiotherapy, hafnium-based nanomaterials for photodynamic therapy, hafnium-based nanomaterials for various combined therapy; and 4) Translation, toxicity, and safety for Hf-NMs in human and preclinical animal models. More attention will be given to the clinical translation of Hf-NMs in cancer