Sampling Testing Research Articles

A rapid approach with machine learning for quantifying the relative burden of antimicrobial resistance in natural aquatic environments

The massive use and discharge of antibiotics have led to increasing concerns about antimicrobial resistance (AMR) in natural aquatic environments. Since the dose-response mechanisms of pathogens with AMR have not yet been fully understood, and the antibiotic resistance genes and bacteria-related data collection via field sampling and laboratory testing is time-consuming and expensive, designing a rapid approach to quantify the burden of AMR in the natural aquatic environment has become a challenge. To cope with such a challenge, a new approach involving an integrated machine-learning framework was developed by investigating the associations between the relative burden of AMR and easily accessible variables (i.e., relevant environmental variables and adjacent land-use patterns). The results, based on a real-world case analysis, demonstrate that the quantification speed has been reduced from 3-7 days, which is typical for traditional measurement procedures with field sampling and laboratory testing, to approximately 0.5 hours using the new approach. Moreover, all five metrics for AMR relative burden quantification exceed the threshold level of 85%, with F1-score surpassing 0.92. Compared to logistic regression, decision trees, and basic random forest, the adaptive random forest model within the framework significantly improves quantification accuracy without sacrificing model interpretability. Two environmental variables, dissolved oxygen and resistivity, along with the proportion of green areas were identified as three key feature variables for the rapid quantification. This study contributes to the enrichment of burden analyses and management practices for rapid quantification of the relative burden of AMR without dose-response information.

Analysis of The Effect of Halal Labelization, Brand Image and Prices on Consumer Purchasing Decisions With Religious As Moderating Variables on Coastal Honey in Kertasada Village, Sumenep District

The need for honey in Indonesia alone reaches an average of 150,000 tons per year. This means that Indonesia has to import around 50% of its honey from abroad to meet this demand. This could also be an opportunity for local entrepreneurs to develop their honey business. Even though it seems traditional, the honey business opportunity has undergone modernization and development, from marketing to the processed honey itself. Coastal Honey is a honey bee cultivation business located in Kertasada Village. Coastal Honey, which has been established for around 8 years, is a business that has great prospects with profits increasing almost every year, coupled with the existence of resellers in various regions of Indonesia. The purpose of this research is to research and analyze the influence of halal labeling, Brand Image and Price on Consumer Purchasing Decisions with Religiosity as Moderating Variable on Coastal Honey in Kertasada Village, Sumenep Regency. This research is a quantitative exploration, with the population being the people of Sumenep, especially people who buy Coastal Honey. The testing strategy in this review uses purposive sampling testing, specifically determining samples with certain standards, especially consumers who buy Coastal Honey. Interviews and direct observations with the owner Coastal Honey and distributed questionnaires to 100 respondents which were used to collect data. As well as using data analysis techniques, namely Descriptive Statistics Test, Validity Test, Reliability Test, Classical Assumption Test, Multiple Linear Regression Test, Coefficient of Determination Test and Hypothesis Test. The results of this research show that the Halal Labeling variable, Brand Image, Price and Religiosity have a significant effect on Purchasing Decisions partially and simultaneously. And the moderation results show that Religiosity moderates the relationship between Halal Labeling, Brand Image and Price on Purchase Decisions.

Utility of methylated DNA markers for the diagnosis of malignant biliary strictures.

Early identification of malignant biliary strictures (MBS) is challenging, with up to 20% classified as indeterminants after preliminary testing and tissue sampling with endoscopic retrograde cholangiopancreatography (ERCP). We aimed to evaluate the use of methylated DNA markers (MDM) from biliary brushings to enhance MBS detection in a prospective cohort. Candidate MDMs were evaluated for their utility in MBS diagnosis through a series of discovery and validation phases. DNA was extracted from biliary brushing samples, quantified, bisulfite-converted, and then subjected to methylation-specific Droplet Digital Polymerase Chain Reaction (ddPCR). Patients were considered to have no malignancy if the sampling was negative and there was no evidence of malignancy after 1 year or definitive negative surgical histopathology. Fourteen candidate MDMs were evaluated in the discovery phase, with top-performing and new markers evaluated in the technical validation phase. The top four MDMs were TWIST1, HOXA1, VSTM2B, and CLEC11A, which individually achieved AUC values of 0.82, 0.81, 0.83, and 0.78, respectively, with sensitivities of 59.4%, 53.1%, 62.5%, and 50.0%, respectively, at high specificities for malignancy of 95.2-95.3% for the final biologic validation phase. When combined as a panel, the AUC was 0.86, achieving 73.4% sensitivity and 92.9% specificity, which outperformed cytology and fluorescent in situ hybridization (FISH). The selected methylated DNA markers demonstrated improved performance characteristics for the detection of MBS compared to cytology and FISH. ​ Therefore, MDMs should be considered viable candidates for inclusion in diagnostic testing algorithms.​.

Optimizing placement of bioretention systems in the US Puget Sound region

AbstractThe Puget Sound Basin, US Pacific Northwest, is experiencing rapid population and urban growth. This growth adversely impacts local ecosystems, especially the spawning and rearing habitat for several salmonid species. Sustainable urban design strategies such as green stormwater infrastructure (GSI) are required in the region to manage stormwater onsite when new development occurs. However, the effectiveness of any GSI depends on its location relative to where stormwater is produced. This study aimed to develop a Geographic Information System (GIS)‐based framework for the optimal placement of GSI, specifically bioretention systems. We computed the Hydrologic Sensitivity Index (λHSI, indicating runoff generation potential at a landscape location) for the lower Puyallup River Watershed study area. The index and federal and state feasibility criteria were used to identify suitable sites for bioretention systems. The suitability of identified sites was verified through ground‐truthing, including soil sampling and infiltration testing. We found that 2.5% of the watershed area was suitable for bioretention, concentrated in the center and north of the study watershed. The method described in this study can be readily applied to watersheds for which spatial data (topography, soil, and land use) are available. We recommend choosing locations with high λHSI when resources are limited since these locations contribute most to runoff generation and urban flooding.

Water Quality Characteristics and Water-Rock Interaction Mechanisms of Coal Mine Underground Reservoirs.

Constructing underground reservoirs in coal mines can effectively improve the recycling of mine water. Water-rock interactions within underground reservoirs have been demonstrated to improve water quality; however, the mechanisms underlying these water-rock interactions remain unclear, hindering the widespread applications of underground reservoirs. Thus, this study focused on the underground reservoir of the Shendong Daliuta coal mine. Through on-site sampling tests and single-mineral leaching experiments, combined with X-ray diffraction, X-ray fluorescence spectrometry, and scanning electron microscopy, the water quality characteristics of the inlet and outlet water samples from the coal mine underground reservoir were analyzed. Moreover, the physical and chemical properties of the collapsed rocks in the reservoir were investigated, with the aim of clarifying the mechanism underlying the water-rock interactions in coal mine underground reservoirs. The results revealed a significant self-purification effect of the coal mine underground reservoir. Compared with the inlet water sample, the outlet water sample featured substantially reduced amounts of solid-suspended substances, turbidity, total dissolved solids, and electrical conductivity, with the average removal rates of Fe and Mn approaching 98.73 and 92.12%, respectively. Along the flow direction of the inlet and outlet water of the coal mine underground reservoir, the concentrations of Na+ and Cl- presented an increasing trend, whereas the concentrations of Ca2+, Mg2+, and HCO3 - presented a decreasing trend. The concentration of K+ changed insignificantly, while the concentration of SO4 2- fluctuated unstably. The collapsed rocks in the Daliuta coal mine underground reservoir primarily comprised mudstone and sandstone with mineral components including quartz, orthoclase, albite, illite, kaolinite, glauconite, calcite, and pyrite. Among these, kaolinite exhibited the strongest adsorption capacity for Na+, Ca2+, and Mg2+ present in the mine water, while glauconite demonstrated the strongest dissolution capacity for Mg2+. Illite presented the strongest dissolution capacity for K+, while albite presented the strongest dissolution capacity for Na+. The water-rock interactions within the coal mine underground reservoir primarily included dissolution and adsorption processes, wherein mudstone and fine sandstone both played dominant roles in the adsorption of Ca2+, as well as in the dissolution of K+, Na+, and Mg2+. In particular, mudstone exhibited a stronger adsorption capacity than fine sandstone, whereas fine sandstone presented a stronger dissolution capacity than mudstone. Thus, our results offer theoretical guidance for understanding water quality purification mechanisms in coal mine underground reservoirs.

A Knowledge-Guided Multi-Objective Shuffled Frog Leaping Algorithm for Dynamic Multi-Depot Multi-Trip Vehicle Routing Problem

Optimization algorithms have a wide range of applications in symmetry problems, such as graphs, networks, and pattern recognition. In this paper, a dynamic periodic multi-depot multi-trip vehicle routing model for scheduling test samples is constructed, which considers the differences in testing unit price and testing capacity of various agencies and introduces a cross-depot collaborative transport method. Both the cost and the testing time are minimized by determining the optimal sampling routes and testing agencies, subjecting to the constraints of vehicle capacity, number of vehicles, and delivery time. To solve the model, a knowledge-guided multi-objective shuffled frog leaping algorithm (KMOSFLA) is proposed. KMOSFLA adopts a convertible encoding mechanism to realize the diversified search in different search spaces. Three novel strategies are designed: the population initialization with historical information reuse, the leaping rule based on the greedy crossover and genetic recombination, and the objective-driven enhanced search. Systematic experimental studies are implemented. First, feasibility analyses of the model are carried out, where effectiveness of the cross-depot collaborative transport is validated and sensitivity analyses on two parameters (vehicle capacity and proportion of the third-party testing agencies) are performed. Then, the proposed algorithm KMOSFLA is compared with five state-of-the-art algorithms. Experimental results indicate that KMOSFLA can provide a set of non-dominated schedules with lower cost and shorter testing time in each scheduling period, which provides a reference for the dispatcher to make a final decision.

Low-disturbance land remediation using vertical groundwater circulation well technology: The first commercial deployment in an operational chemical plant

Soil and groundwater contamination by organic pollutants from chemical plants presents significant risks to both environmental and human health. We report a significant field trial where a chemical plant in operation showed soil and groundwater pollution, as verified by sampling and laboratory tests. While many remediation methods are effective, they often require the temporary shutdown of plant operations to install necessary equipment. This paper introduces a novel combination of low-disturbance contaminant remediation technologies, including groundwater circulation well (GCW), pump and treat (P&T), and in-situ chemical oxidation (ISCO) technologies, that can be applied on the premises of an active plant without halting production. The groundwater with dissolved contaminants is removed through P&T and GCW, while GCW enhances ISCO that focus on eliminating the remaining hard-to-pump contaminants. Results show: (1) after two years of remediation effort, the contaminant levels in soil and groundwater were significantly reduced; (2) the average concentration reduction rate of four contaminants, including 1,2-dichloroethane, methylbenzene, ethylbenzene, and M&P-xylene, exceeds 98 %; (3) the presented remediation strategy results in the improvement of remediation efficiency. Specifically, the concentration of 1,2-dichloroethane in observation wells dropped from 40,550.7 μg/L to 44.6 μg/L. This study offers a first-of-its-kind commercial deployment of a GCW-based remediation strategy in an active plant setting. Moreover, the combined remediation approach presented here can serve as a model for designing contaminant remediation projects that require minimal operational disruption.

Two-Stage Life Test Acceptance Sampling Plans for the Weibull Distribution using Trinomial Distribution

In materials engineering applications, lifetime of product is one of the quality characteristics of interest. Lifetimes of products are inspected in life tests upto a predetermined time t0, which may observe early failure of some of the products; incorporation of this fact may not only reduce the cost of inspection, but also provide some more insight into the failure mechanism. In this paper, we consider a two-stage time censoring scheme by dividing test truncation time t0 into two parts [.. formula..] and observe the number of failures in each interval, considering the remainder items as censored at t0. The trinomial distribution has been used to develop life test acceptance sampling plans for establishing quantile life of items having Weibull lifetimes. The proposed life test sampling plan gives added advantage to producers and extra safeguard to consumers, as compared to the life test sampling plans available in the literature for the Weibull distribution. Tables of plan parameters are constructed through code written in R 4.1.2, and illustrated for some real-life industrial cases.. KEYWORDS :Quantile, Two-stage censoring, Trinomial distribution, Weibull distribution.

A data‐driven topsoil classification framework to support soil health assessment in Minnesota

AbstractSoil health assessments aim to quantify soil health status using indicators linked to ecosystem services such as yield, nutrient cycling, water cycling, or carbon storage. Many indicators are related to soil biological processes, which can be challenging to interpret because they are sensitive not only to management, but also to nonmanagement variables such as soil inherent properties, topography, and climate. Existing studies address this challenge by grouping similar soils by taxonomy, geography, or a combination of these and other variables for soil health assessment. We investigated whether grouping soils based on multiple quantitative topsoil properties could be an alternative to taxonomic or geographic groups. We used an unsupervised classification algorithm, k‐means, to cluster publicly available soil and climate data for Minnesota. Clustering into eight conceptual groups (“clusters”) based on 10 topsoil properties was determined to be the optimal algorithm output. We evaluated the ability of our soil clusters and other grouping methods to explain variance in eight soil health indicators. We found the combination of Major Land Resource Area (MLRA) and soil cluster performed best, explaining as much or more variance than other groupings for five of the eight indicators. The clusters distinguish zones of topsoil variation at the field scale, and MLRAs account for broader scale variation in climate and other landscape factors. The approach we describe is flexible and could be applied at different locations and scales to produce conceptual soil groups and associated maps to support soil health test sampling and interpretation at the field scale.

Inhomogeneity in mechanical properties of ductile iron pipes: A comprehensive analysis

Ductile iron pipes are widely used in pipe manufacturing for water and sewage transmission and distribution. In pipeline standards such as EN545, the pipe material is assumed isotropic and its mechanical properties are determined by tensile testing of round bars extracted along the longitudinal direction. This study experimentally examined the mechanical properties of centrifugal casting ductile iron pipes, focusing on the effects of sampling orientation, location, preparation, and test methodology. A ring hoop tension test (RHTT) was designed to evaluate circumferential properties. Force analysis of RHTT was performed and theoretical equation was derived to quantify the friction coefficient that existed between the coupon specimen and the loading fixture. A numerical study was conducted to further validate the effectiveness of the proposed theory. The test results indicated that the pipe mechanical property was inhomogeneous across the wall thickness, being inferior in the internal section and superior in the middle and external sections. This inferior layer would develop crack first and lead to subsequent outward propagation. This phenomenon led to a substantial degradation in the overall mechanical performance of the entire specimens, in comparison to the material in the middle portion. The material exhibited better performance in the circumferential direction compared to the longitudinal direction in terms of its mechanical properties, such as tensile strength and ductility. Flattened specimens showed enhanced strength and reduced ductility compared to the base pipe material. Fractographic and metallographic analyses revealed the existence of casting defects of porosity and agglomerated graphite in the internal section, which were the primary cause of material inhomogeneity. The round bars suggested per EN545 tended to overestimate the actual mechanical behaviour of ductile iron pipes, and may not be a true representation of the finished product of pipes. Flattened specimens as per ASTM E8/E8M were not recommended for ductile iron pipe material assessment, as the flattening process altered the stress–strain characteristics significantly.

A Scene Unmixing Deep Learning Network for Local Climate Zone Mapping and Analysis Using Very High Resolution Remote Sensing Imagery

Abstract. With the acceleration of urbanization, the environment and climate necessary for our survival have gradually deteriorated, leading to the increasing prominence of the Urban Heat Island (UHI) effect. Local Climate Zone (LCZ) classification, as a standard of urban morphology, has become an essential tool for monitoring the UHI effect and conducting temperature studies. Deep Learning (DL) models have the ability to represent high-level semantic features. Therefore, this paper proposes amixed scene unmixing DL framework for LCZ mapping and analysis using Very High Resolution (VHR) remote sensing images. This framework consists of a two-stream deep network, including a pure scene classification network (PS-Net) and a mixed scene unmixing network (MSU-Net). We conducted random sampling tests in Wuhan, China in the experiment A. The results show that this model achieved a satisfactory accuracy with the Overall Accuracies (OAs) is 96.78% and a mixed scene unmixing Mean Absolute Error (MAE) of 0.0495. Furthermore, we applied the proposed model to generate LCZ map for five districts in Wuhan in the experiment B. The test accuracy between two experiments differs very slightly. These results demonstrate the applicability and potential of our model for LCZ mapping and urban climate analysis.

Influence Of Shadow And Shuttle Run Exercises On Badminton Sports Footwork Aged 13 - 15 Years At Pb Jaya Raya Jakarta

This study was conducted to determine the effect of shadow and shuttle run training on badminton footwork aged 13–15 years at PB Jaya Raya Jakarta. This study uses an experimental method that utilizes a two-group pretest-posttest design. The population studied in this study were PB athletes. Jaya Raya Jakarta has a population of 30 people. A purposive sampling method was used in the study, with the following criteria: At least 75% of players were on the attendance list during the last two months of training (actively involved in training); (2) Participants are PB athletes. (3) Age 13–15 years, (4) Male gender. The sampling test in the form of a foot movement agility instrument is a circuit-based leg exercise tester. The t-test was used in the analysis of the data. The results of the research are: (1) There is an effect of shadow training on the sports footwork of children aged 13–15 years in PB. Jaya Raya Jakarta, with t count 3,289 > t table 2.26 and a significance value of 0.009 0.05, resulting in an effect of 9.55%. (2) There is an effect of the shuttle run exercise on the badminton footwork of children aged 13–15 years in PB. Jaya Raya Jakarta, with a count of 4.155 > table 2.26 and a significance value of 0.002 0.05, resulting in an effect of 10.69%. (3) The shuttle run method is more effective for badminton footwork aged 13–15 years in PB Jaya Raya Jakarta than the shadow method.

Study on the value of second‐generation sequencing technology in the clinical diagnosis of osteoarticular brucellosis

AbstractTo assess the value of next‐generation sequencing (NGS) technology in the diagnosis of osteoarticular brucellosis pathogenesis. Fifty eight patients admitted to the Department of Orthopaedics, Hebei Provincial Chest Hospital from January 2021 to January 2023 were retrospectively analyzed, and the patients were classified into 48 cases in the osteoarticular brucellosis group and 10 cases in the nonosteoarticular brucellosis group according to the final clinical diagnosis. All patients underwent serum agglutination test (SAT), CT‐guided puncture or surgical sampling of lesions for bacteriological culture and NGS after admission. The diagnostic efficacy of these three methods for osteoarticular brucellosis was compared using the final clinical diagnosis as the reference standard. Among the 58 patients with suspected osteoarticular brucellosis, 40 cases (68.97%) were positive by NGS, 33 cases (56.89%) by SAT and 10 cases (17.24%) by culture, and the differences were statistically significant (p < 0.05). Using the final clinical diagnosis as a criterion, the sensitivity of NGS, SAT, and culture for the detection of osteoarticular brucellosis was 83.33%, 62.50%, and 20.83%, respectively, the specificity was 100.00%, 70.00%, and 100.00%, the diagnostic accuracy was 86.20%, 63.79%, and 34.49%, and the κ values were 0.799, 0.590, and 0.504, respectively. NGS has a high pathogen detection rate and sensitivity in the pathogenetic diagnosis of patients with osteoarticular brucellosis and can provide clinical guidance for the diagnosis and management of patients with osteoarticular brucellosis.

Effects of puberty suppression on bone, body composition, handgrip strength and glucolipid profile in early-pubertal transgender adolescents

Introduction The effects of puberty suppression for more than 2 years before the start of gender-affirming hormones (GAH) on bone mass acquisition and body composition are understudied. Materials and methods Retrospective study on 46 transgender adolescents (20 trans boys and 26 trans girls) receiving a gonadotropin-releasing hormone analogue (GnRHa) from Tanner stage 2-3, followed by GAH around the age of 16 years. At start of GnRHa and at start of GAH, dual-energy X-ray absorptiometry (DXA) at lumbar spine (LS), femoral neck (FN) and total body (TB), handgrip strength test and fasting blood sampling were performed. Z-scores were calculated using reference values for both cis girls and cis boys. Results GnRHa were administered for a median of 3.2 years (± 0.69) in trans boys and 2.7 years (± 1.05) in trans girls. Bone mineral apparent density (BMAD)-LS Z-scores decreased significantly in both trans boys and trans girls, while BMAD-FN Z-scores decreased only in trans boys. Fat% and Fat Mass Index Z-scores significantly increased in both groups, while Lean Mass Index Z-scores significantly decreased. Handgrip strength Z-scores for the sex registered at birth (SRAB) remained stable in trans boys while they decreased in trans girls. There was no significant influence of the treatment on either insulin sensitivity or lipid profile. Discussion GnRHa administration for more than two years during the physiological time of puberty decreases bone mass acquisition, mainly at the lumbar spine and induces a general increase in fat mass. Although lean mass acquisition is undermined in both groups, handgrip strength is affected mainly in trans girls compared with age-matched peers for the SRAB.

Comparative Performance of COVID-19 Test Methods in Healthcare Workers during the Omicron Wave.

The COVID-19 pandemic presents unique requirements for accessible, reliable testing, and many testing platforms and sampling techniques have been developed over the course of the pandemic. Not all test methods have been systematically compared to each other or a common gold standard, and the performance of tests developed in the early epidemic have not been consistently re-evaluated in the context of new variants. We conducted a repeated measures study with adult healthcare workers presenting for SARS-CoV-2 testing. Participants were tested using seven testing modalities. Test sensitivity was compared using any positive PCR test as the gold standard. A total of 325 individuals participated in the study. PCR tests were the most sensitive (saliva PCR 0.957 ± 0.048, nasopharyngeal PCR 0.877 ± 0.075, oropharyngeal PCR 0.849 ± 0.082). Standard nasal rapid antigen tests were less sensitive but roughly equivalent (BinaxNOW 0.613 ± 0.110, iHealth 0.627 ± 0.109). Oropharyngeal rapid antigen tests were the least sensitive (BinaxNOW 0.400 ± 0.111, iHealth brands 0.311 ± 0.105). PCR remains the most sensitive testing modality for the diagnosis of COVID-19 and saliva PCR is significantly more sensitive than oropharyngeal PCR and equivalent to nasopharyngeal PCR. Nasal AgRDTs are less sensitive than PCR but have benefits in convenience and accessibility. Saliva-based PCR testing is a viable alternative to traditional swab-based PCR testing for the diagnosis of COVID-19.

292 Effects of feeding mycotoxins-contaminated feed with a mitigation strategy on growth performance and health status in weaned pigs

Abstract Various types and levels of mycotoxins are present in feed ingredients, thus negatively impacting swine health and productivity. Appropriate sampling and frequent testing of feed ingredients are recommended to assess the risk of mycotoxins in feed and to determine mitigation strategies for mycotoxin control. However, monitoring plans do not guarantee feed will be free of mycotoxins, so in-feed mitigation strategies are implemented to minimize production losses. The objective of this study was to investigate the efficacy of a mycotoxin mitigation product (MultiSHIELD, modified clinoptilolite-based product) on growth performance and health status of weaned pigs under dietary challenges with various types and levels of mycotoxins commonly found in feed. The presence of mycotoxins was confirmed in the ground corn, which was obtained from the Midwestern United States and then used in a standard corn and soybean meal-based diet for three dietary treatments. Treatments were as follows: 1) control diet containing mycotoxins without mitigation (fumonisins B1 at 390, 454, and 527 ppb; zearalenone at 727, 846, and 982 ppb; deoxynivalenol at 671, 781, and 907 ppb in N1, N2, and N3 diets, respectively), 2) control diet with 0.15% of MultiSHIELD as mitigation level 1, and 3) control diet with 0.3% of MultiSHIELD as mitigation level 2. A total of 912 weaned pigs were allotted to 1 of 3 dietary treatments (19 pigs per pen and 16 replicates per treatment) in a randomized complete block design with the initial body weight (as blocking. The results revealed that mycotoxin mitigation, regardless of the mitigation levels, had decreased removal rate (P < 0.01), incidence of injectable medication treatments (P = 0.01), ear necrosis (P = 0.27), and scours (P = 0.18) compared with control. Overall, pigs fed mycotoxin mitigation treatment diets had heavier pen weight (P = 0.06) than those fed the control diet due to fewer removals. The results also demonstrated a significant improvement of economic parameters (i.e., income over feed cost per pen; P = 0.01) for pigs fed diets with MultiSHIELD, regardless of the inclusion level, than pigs fed control diet. In conclusion, poor swine productivity was observed due to the presence of mycotoxins in feed, and the inclusion of MultiSHIELD in feed under the mycotoxin challenge delivers a positive impact on health and economic performance of nursery pigs.

Widespread White Matter Abnormalities in Concussed Athletes Detected by 7T Diffusion Magnetic Resonance Imaging.

Sports-related concussions may cause white matter injuries and persistent post-concussive symptoms (PPCS). We hypothesized that athletes with PPCS would have neurocognitive impairments and white matter abnormalities that could be revealed by advanced neuroimaging using ultra-high field strength diffusion tensor (DTI) and diffusion kurtosis (DKI) imaging metrics and cerebrospinal fluid (CSF) biomarkers. A cohort of athletes with PPCS severity limiting the ability to work/study and participate in sport school and/or social activities for ≥6 months completed 7T magnetic resonance imaging (MRI) (morphological T1-weighed volumetry, DTI and DKI), extensive neuropsychological testing, symptom rating, and CSF biomarker sampling. Twenty-two athletes with PPCS and 22 controls were included. Concussed athletes performed below norms and significantly lower than controls on all but one of the psychometric neuropsychology tests. Supratentorial white and gray matter, as well as hippocampal volumes did not differ between concussed athletes and controls. However, of the 72 examined white matter tracts, 16% of DTI and 35% of DKI metrics (in total 28%) were significantly different between concussed athletes and controls. DKI fractional anisotropy and axial kurtosis were increased, and DKI radial diffusivity and radial kurtosis decreased in concussed athletes when compared with controls. CSF neurofilament light (NfL; an axonal injury marker), although not glial fibrillary acidic protein, correlated with several diffusion metrics. In this first 7T DTI and DKI study investigating PPCS, widespread microstructural alterations were observed in the white matter, correlating with CSF markers of axonal injury. More white matter changes were observed using DKI than using DTI. These white matter alterations may indicate persistent pathophysiological processes following concussion in sport.

Weak signal detection technique based on Durbin-Watson test and one-bit sampling.

Correlation-based detection techniques are widely used in the weak periodic signal detection field. Traditionally, they are based on extracting the correlation of a weak signal from noise. Considering the impact of a weak signal on the randomness of background noise, this article takes the opposite approach and proposes a weak signal detection technique based on the Durbin-Watson (DW) test and one-bit sampling, detecting the weak signal due to the extent to which the randomness of noise is affected. The randomness of noise is analyzed through the DW test, which is a method for detecting the randomness of data sequences through first-order autocorrelation. One-bit sampling is adopted to reduce the complexity of the sampling circuit and data processing algorithm. The effectiveness of the DW test in the situation of one-bit sampling is demonstrated through simulation and analysis. Simulation results show that the proposed technique is capable of detecting weak sinusoidal and square-wave signals with a signal-to-noise ratio (SNR) above -30 dB, and the frequency or SNR of a weak signal can be further estimated based on mutual constraints. The measured results confirm the capability. In addition, the factors of coherent sampling, noise bandwidth, and comparator threshold that influence the performance of the proposed technique are simulated and discussed in detail.

Evaluation of germicidal ultraviolet-C disinfection in a real-world outpatient health care environment

The coronavirus disease 2019 pandemic has highlighted the need for effective infection control in outpatient healthcare settings. Germicidal ultraviolet-C (GUV) light, known for inactivating microorganisms by damaging their deoxyribonucleic acid or ribonucleic acid, offers a potential solution. This study examines the efficacy of GUV air disinfection systems in real-world outpatient environments. We deployed upper-room and far-UV GUV fixtures in 3 outpatient facilities, assessing their impact on bacterial loads through air and surface sampling and bioindicator tests. Occupancy was also monitored. While manual air and surface sampling did not show a significant difference in bacterial loads between control and Ultraviolet C-treated groups, bioindicator tests demonstrated a high level of spore inactivation (up to 99.7% for upper-room GUV and 96.26% for far-UV). Occupancy levels did not significantly influence these outcomes. The discrepancy between bioindicator efficacy and environmental sampling results suggests limitations in the latter's ability to accurately capture environmental bioburden. Bioindicators proved to be reliable for in-situ validation of Ultraviolet C surface disinfection. Bioindicators are effective for validating GUV surface disinfection efficacy in healthcare settings, though further research is needed to optimize environmental sampling methods for assessing GUV's impact on real-world bacterial loads.

CPTU-based permeability evaluation of clays

The piezocone penetration test (CPTU) is an efficient in-situ testing method for delineating subsurface stratigraphy and interpreting geoparameters continuously with depth. However, owing to the regional sensitivity and geological diversity, the applicability of CPTU-based geotechnical parameter evaluation methods is limited when applied to specific sites. This requires further scrutiny considering the different geological histories and local soil conditions. In this study, a database that included a collection of CPTU test sites in Jiangsu Province, China, was compiled containing high-quality sampling and laboratory testing performed to characterize the permeability of clay soils. Several published CPTU correlations for determining soil permeability were summarized and compared with laboratory-measured soil permeability as a benchmark reference. The evaluation results indicated that the I c-based correlations can provide a reasonably good determination of the permeability for the investigated soils with root mean squared error of 0.89 and mean absolute error of 0.77. Finally, a modified approach was presented to evaluate the permeability coefficient of Jiangsu clay soils, which was calibrated using two additional case studies.