Influence of external nitrogen-containing donors on polymerization behavior of neodymium-based cis-1,4-polybutadiene rubber

Neodymium(Nd)-based catalyst in butadiene(Bd)polymerization has drawn interests due to its availability in affording higher cis-1,4-unit selectivity than transition metal(Ti,Co,Ni,etc.)-based catalysts[1-2].Such outstanding high cis-1,4-unit selecti-vity is hypothetically originated from the presence of 4 f orbitals,that can participate in monomer coordination and thereby govern subsequent enchainment manners.This unique characteristic also renders the active species highly susceptible to Lewis bases,and may impact the overall selectivity as well as polyme-rization behavior after coordination.Nevertheless,it is still a virgin area in such a field,and the influence of Lewis bases on Nd-based diene polymerizations is still a black box.Based on this consideration,how nitrogen-containing donors(D)impacts the overall behaviors of Nd-mediated Bd polymerizations is disclosed.

Flexible,thermal processable,self-healing,and fully bio-based starch plastics by constructing dynamic imine network

The serious environmental threat caused by petroleum-based plastics has spurred more researches in developing substitutes from renewable sources.Starch is desirable for fabricating bioplastic due to its abundance and renewable nature.However,limitations such as brittleness,hydrophilicity,and thermal properties restrict its widespread application.To overcome these issues,covalent adaptable network was constructed to fabricate a fully bio-based starch plastic with multiple advantages via Schiff base reactions.This strategy endowed starch plastic with excellent thermal processability,as evidenced by a low glass transition temperature(T_(g)=20.15℃).Through introducing Priamine with long carbon chains,the starch plastic demonstrated superior flexibility(elongation at break=45.2%)and waterproof capability(water contact angle=109.2°).Besides,it possessed a good thermal stability and self-adaptability,as well as solvent resistance and chemical degradability.This work provides a promising method to fabricate fully bio-based plastics as alternative to petroleum-based plastics.

Role of micro-Ca/In alloying in tailoring the microstructural characteristics and discharge performance of dilute Mg-Bi-Sn-based alloys as anodes for Mg-air batteries

The influence of micro-Ca/In alloying on the microstructural charac teristics,electrochemical behaviors and discharge properties of extruded dilute Mg-0.5Bi-0.5Sn-based(wt.%)alloys as anodes for Mg-air batteries are evaluated.The grain size and texture intensity of the Mg-Bi-Sn-based alloys are significantly decreased after the Ca/In alloying,particularly for the In-containing alloy.Note that,in addition to nanoscale Mg_(3)Bi_(2)phase,a new microscale Mg_(2)Bi_(2)Ca phase forms in the Ca-containing alloy.The electrochemical test results demonstrate that Ca/In micro-alloying can enhance the electrochemical activity.Using In to alloy the Mg-Bi-Sn-based alloy is effective in restricting the cathodic hydrogen evolution(CHE)kinetics,leading to a low self-corrosion rate,while severe CHE occurred after Ca alloying.The micro-alloying of Ca/In to Mg-Bi-Sn-based alloy strongly deteriorates the compactness of discharge products film and mitigates the"chunk effect"(CE),hence the cell voltage,anodic efficiency as well as discharge capacity are greatly improved.The In-containing alloy exhibits outstanding discharge performance under the combined effect of the modified microstructure and discharge products,thus making it a potential anode material for primary Mg-air battery.

Construction of coal pitch-based HA-K grafted poly condensates and their excellent anti-temperature and viscosity-reducing properties

Humic acids(HAs)are widely used as filtrate and viscosity reducers in drilling fluids.However,their practical utility is limited due to poor stability in salt resistance and high-temperature resistance.Hightemperature coal pitch(CP)is a by-product from coal pyrolysis above 650℃.The substance's molecular structure is characterized by a dense arrangement of aromatic hydrocarbon and alkyl substituents.This unique structure gives it unique chemical properties and excellent drilling performance,surpassing traditional humic acids in drilling operations.Potassium humate is prepared from CP(CP-HA-K)by thermal catalysis.A new type of high-quality humic acid temperature-resistant viscosity-reducer(Graft CP-HA-K polymer)is synthesized with CP-HA-K,hydrolyzed polyacrylonitrile sodium salt(Na-HPAN),urea,formaldehyde,phenol and acrylamide(AAM)as raw materials.The experimental results demonstrate that the most favorable conditions for the catalytic preparation of CP-HA-K are 1 wt%catalyst dosage,30 wt%KOH dosage,a reaction temperature of 250℃,and a reaction time of 2 h,resulting in a maximum yield of CP-HA-K of 39.58%.The temperature resistance of the Graft CP-HA-K polymer is measured to be 177.39℃,which is 55.39℃ higher than that of commercial HA-K.This is due to the abundant presence of amide,hydroxyl,and amine functional groups in the Graft CP-HA-K polymer,which increase the length of the carbon chains,enhance the electrostatic repulsion on the surface of solid particles.After being aged to 120℃ for a specified duration,the Graft CP-HA-K polymer demonstrates significantly higher viscosity reduction(42.12%)compared to commercial HA-K(C-HA-K).Furthermore,the Graft CP-HA-K polymer can tolerate a high salt concentration of 8000 mg.L-1,measured after the addition of optimum amount of 3 wt%Graft CP-HA-K polymer.The action mechanism of Graft CP-HA-K polymer on high-temperature drilling fluid is that the Graft CP-HA-K polymer can increase the repulsive force between solid particles and disrupt bentonite's reticulation structure.Overall,this research provides novelty insights into the synthesis of artificial humic acid materials and the development of temperature-resistant viscosity reducers,offering a new avenue for the utilization of CP resources.

Improving Satellite-Retrieved Cloud Base Height with Ground-Based Cloud Radar Measurements

Cloud base height(CBH) is a crucial parameter for cloud radiative effect estimates, climate change simulations, and aviation guidance. However, due to the limited information on cloud vertical structures included in passive satellite radiometer observations, few operational satellite CBH products are currently available. This study presents a new method for retrieving CBH from satellite radiometers. The method first uses the combined measurements of satellite radiometers and ground-based cloud radars to develop a lookup table(LUT) of effective cloud water content(ECWC), representing the vertically varying cloud water content. This LUT allows for the conversion of cloud water path to cloud geometric thickness(CGT), enabling the estimation of CBH as the difference between cloud top height and CGT. Detailed comparative analysis of CBH estimates from the state-of-the-art ECWC LUT are conducted against four ground-based millimeter-wave cloud radar(MMCR) measurements, and results show that the mean bias(correlation coefficient) is0.18±1.79 km(0.73), which is lower(higher) than 0.23±2.11 km(0.67) as derived from the combined measurements of satellite radiometers and satellite radar-lidar(i.e., Cloud Sat and CALIPSO). Furthermore, the percentages of the CBH biases within 250 m increase by 5% to 10%, which varies by location. This indicates that the CBH estimates from our algorithm are more consistent with ground-based MMCR measurements. Therefore, this algorithm shows great potential for further improvement of the CBH retrievals as ground-based MMCR are being increasingly included in global surface meteorological observing networks, and the improved CBH retrievals will contribute to better cloud radiative effect estimates.

Elastic wave insulation and propagation control based on the programmable curved-beam periodic structure

Curved-beams can be used to design modular multistable metamaterials(MMMs)with reprogrammable material properties,i.e.,programmable curved-beam periodic structure(PCBPS),which is promising for controlling the elastic wave propagation.The PCBPS is theoretically equivalent to a spring-oscillator system to investigate the mechanism of bandgap,analyze the wave propagation mechanisms,and further form its geometrical and physical criteria for tuning the elastic wave propagation.With the equivalent model,we calculate the analytical solutions of the dispersion relations to demonstrate its adjustability,and investigate the wave propagation characteristics through the PCBPS.To validate the equivalent system,the finite element method(FEM)is employed.It is revealed that the bandgaps of the PCBPS can be turned on-and-off and shifted by varying its physical and geometrical characteristics.The findings are highly promising for advancing the practical application of periodic structures in wave insulation and propagation control.

Infuences of Different Admixtures on the Drying Shrinkage Characteristics of Metakaolin-based Geopolymer Mortar

To investigate the influences of different admixtures on the drying shrinkage of polymer mortar in a metakaolin base,the experiments of VAE(vinyl acetate ethylene copolymer),APAM(anionic polyacrylamide)and CPAM(cationic polyacrylamide)on the drying shrinkage properties of geopolymer mortar were designed under normal temperature curing conditions.An SP-175 mortar shrinkage dilatometer was introduced to measure the dry shrinkage of geopolymer mortar.Meanwhile,the drying shrinkage properties of geopolymer mortar are exhibited by the parameters of water loss rate,drying shrinkage rate,drying shrinkage strain and drying shrinkage coefficient.The experimental data are further fitted to obtain the prediction model of dry shrinkage of geopolymer mortar,which can better reflect the relationship between dry shrinkage rate and time.Finally,the experimental results demonstrate that the dry shrinkage of geopolymer mortar can be significantly increased by adding 4%VAE admixture,meanwhile under the condition that the polymer film formed by VAE reaction can strengthen and toughen the mortar.2.5%APAM admixture and 1.5%CPAM admixture can enhance the dry shrinkage performance of geopolymer mortar in a certain range.

Physics-Based Active Learning for Design Space Exploration and Surrogate Construction for Multiparametric Optimization

The sampling of the training data is a bottleneck in the development of artificial intelligence(AI)models due to the processing of huge amounts of data or to the difficulty of access to the data in industrial practices.Active learning(AL)approaches are useful in such a context since they maximize the performance of the trained model while minimizing the number of training samples.Such smart sampling methodologies iteratively sample the points that should be labeled and added to the training set based on their informativeness and pertinence.To judge the relevance of a data instance,query rules are defined.In this paper,we propose an AL methodology based on a physics-based query rule.Given some industrial objectives from the physical process where the AI model is implied in,the physics-based AL approach iteratively converges to the data instances fulfilling those objectives while sampling training points.Therefore,the trained surrogate model is accurate where the potentially interesting data instances from the industrial point of view are,while coarse everywhere else where the data instances are of no interest in the industrial context studied.

Preparation of palladium-based catalyst by plasma-assisted atomic layer deposition and its applications in CO_(2) hydrogenation reduction

Supported Pd catalyst is an important noble metal material in recent years due to its high catalytic performance in CO_(2)hydrogenation.A fluidized-bed plasma assisted atomic layer deposition(FP-ALD) process is reported to fabricate Pd nanoparticle catalyst over γ-Al_(2)O_(3)or Fe_(2)O_(3)/γ-Al_(2)O_(3)support,using palladium hexafluoroacetylacetonate as the Pd precursor and H_(2)plasma as counter-reactant.Scanning transmission electron microscopy exhibits that highdensity Pd nanoparticles are uniformly dispersed over Fe_(2)O_(3)/γ-Al_(2)O_(3)support with an average diameter of 4.4 nm.The deposited Pd-Fe_(2)O_(3)/γ-Al_(2)O_(3)shows excellent catalytic performance for CO_(2)hydrogenation in a dielectric barrier discharge reactor.Under a typical condition of H_(2)to CO_(2)ratio of 4 in the feed gas,the discharge power of 19.6 W,and gas hourly space velocity of10000 h^(-1),the conversion of CO_(2)is as high as 16.3% with CH_(3)OH and CH4selectivities of 26.5%and 3.9%,respectively.

Layer by Layer Self-assembly Fiber-based Flexible Electrochemical Transistor

Poly(3,4-ethylenedioxyethiophene)-polystyrene sulfonic acid(PEDOT:PSS)/polyallyl dimethyl ammonium chloride modified reduced graphene oxide(PDDA-rGO)was layer by layer self-assembled on the cotton fiber.The surface morphology and electric property was investigated.The results confirmed the dense membrane of PEDOT:PSS and the lamellar structure of PDDA-rGO on the fibers.It has excellent electrical conductivity and mechanical properties.The fiber based electrochemical transistor(FECTs)prepared by the composite conductive fiber has a maximum output current of 8.7 mA,a transconductance peak of 10 mS,an on time of 1.37 s,an off time of 1.6 s and excellent switching stability.Most importantly,the devices by layer by layer self-assembly technology opens a path for the true integration of organic electronics with traditional textile technologies and materials,laying the foundation for their later widespread application.

Advancements in biomass gasification research utilizing iron-based oxygen carriers in chemical looping:A review

Biomass,recognized as renewable green coal,is pivotal for energy conservation,emission reduction,and dualcarbon objectives.Chemical looping gasification,an innovative technology,aims to enhance biomass utilization efficiency.Using metal oxides as oxygen carriers regulates the oxygen-to-fuel ratio to optimize synthesis product yields.This review examines various oxygen carriers and their roles in chemical looping biomass gasification,including natural iron ore types,industrial by-products,cerium oxide-based carriers,and core-shell structures.The catalytic,kinetic,and phase transfer properties of iron-based oxygen carriers are analyzed,and their catalytic cracking capabilities are explored.Molecular interactions are elucidated and system performance is optimized by providing insights into chemical looping reaction mechanisms and strategies to improve carrier efficiency,along with discussing advanced techniques such as density functional theory(DFT)and reactive force field(ReaxFF)molecular dynamics(MD).This paper serves as a roadmap for advancing chemical looping gasification towards sustainable energy goals.

An Improved Bounded Conflict-Based Search for Multi-AGV Pathfinding in Automated Container Terminals

As the number of automated guided vehicles(AGVs)within automated container terminals(ACT)continues to rise,conflicts have becomemore frequent.Addressing point and edge conflicts ofAGVs,amulti-AGVconflict-free path planning model has been formulated to minimize the total path length of AGVs between shore bridges and yards.For larger terminalmaps and complex environments,the grid method is employed to model AGVs’road networks.An improved bounded conflict-based search(IBCBS)algorithmtailored to ACT is proposed,leveraging the binary tree principle to resolve conflicts and employing focal search to expand the search range.Comparative experiments involving 60 AGVs indicate a reduction in computing time by 37.397%to 64.06%while maintaining the over cost within 1.019%.Numerical experiments validate the proposed algorithm’s efficacy in enhancing efficiency and ensuring solution quality.

A Study on the Explainability of Thyroid Cancer Prediction:SHAP Values and Association-Rule Based Feature Integration Framework

In the era of advanced machine learning techniques,the development of accurate predictive models for complex medical conditions,such as thyroid cancer,has shown remarkable progress.Accurate predictivemodels for thyroid cancer enhance early detection,improve resource allocation,and reduce overtreatment.However,the widespread adoption of these models in clinical practice demands predictive performance along with interpretability and transparency.This paper proposes a novel association-rule based feature-integratedmachine learning model which shows better classification and prediction accuracy than present state-of-the-artmodels.Our study also focuses on the application of SHapley Additive exPlanations(SHAP)values as a powerful tool for explaining thyroid cancer prediction models.In the proposed method,the association-rule based feature integration framework identifies frequently occurring attribute combinations in the dataset.The original dataset is used in trainingmachine learning models,and further used in generating SHAP values fromthesemodels.In the next phase,the dataset is integrated with the dominant feature sets identified through association-rule based analysis.This new integrated dataset is used in re-training the machine learning models.The new SHAP values generated from these models help in validating the contributions of feature sets in predicting malignancy.The conventional machine learning models lack interpretability,which can hinder their integration into clinical decision-making systems.In this study,the SHAP values are introduced along with association-rule based feature integration as a comprehensive framework for understanding the contributions of feature sets inmodelling the predictions.The study discusses the importance of reliable predictive models for early diagnosis of thyroid cancer,and a validation framework of explainability.The proposed model shows an accuracy of 93.48%.Performance metrics such as precision,recall,F1-score,and the area under the receiver operating characteristic(AUROC)are also higher than the baseline models.The results of the proposed model help us identify the dominant feature sets that impact thyroid cancer classification and prediction.The features{calcification}and{shape}consistently emerged as the top-ranked features associated with thyroid malignancy,in both association-rule based interestingnessmetric values and SHAPmethods.The paper highlights the potential of the rule-based integrated models with SHAP in bridging the gap between the machine learning predictions and the interpretability of this prediction which is required for real-world medical applications.

Investigating the Correlation between Patient Education on Web-Based Portal Functionality and the Reduction in 30-Day Hospital Readmission Rates

Background: The growing use of web-based patient portals offers patients valuable tools for accessing health information, communicating with healthcare providers, and engaging in self-management. However, the influence of educating patients on these portals’ functionality on clinical outcomes, such as all-cause readmission rates, remains underexplored. Objective: This research proposal tested the hypothesis that educating a subset of patients with Chronic Obstructive Pulmonary Disease (COPD) and Congestive Heart Failure (CHF), on how to effectively access and utilize the functionality of web-based patient portals can reduce all-cause readmission rates. Methods: We performed a prospective, quasi-experimental study at Bon Secours St. Mary’s Hospital in Richmond, Virginia, USA;dividing participants into an intervention group, receiving education about accessing and navigating “My Chart”, the Bon Secours Web based portal, and a control group, receiving standard care. We then compared 30-day readmission rates, patient engagement, and self-management behaviors between the groups. Data was analyzed using statistical tests to assess the intervention’s impact. Results: We projected that educated patients will exhibit lower readmission rates, improved engagement, and better self-management. The results of the study showed that there was a significant decrease in 30-day readmissions in the intervention group in comparison with the control group (22.7% and 40.9%, respectively). This reduction of 18. 2% of readmissions evaluated here for a trial of meaningful clinical effect is statistically insignificant (p = 0. 184). The practical significance of the intervention is considered small-to-moderate (Cramer V = 0. 20) suggesting that the observed difference has a potential clinical importance even though the difference was not statistically significant. Conclusion: These results imply that the proposed educational intervention might have a positive impact on readmissions;nonetheless, the patient’s characteristics that make him or her capable of readmission cannot be changed and are assessed by the RoR (Risk of Readmission) score. The potential impact of the intervention may be offset, in part, by these baseline risk factors. The study’s power may be limited by sample size, potentially affecting the detection of significant differences. Future studies with larger, multi-center samples and longer follow-up periods are recommended to confirm these findings.

Preceptors'experiences in guiding nursing students to use research findings and to implement evidence-based practice

Objective:Evidence-based practices(EBPs)have been taught to students by identifying the best evidence/evidence from research results.However,the experiences of Indonesian nurse preceptors in helping students implement research findings have not been explored thoroughly.This study aimed to explore Indonesian nurse preceptors in guiding nursing students to use research findings.Methods:This study used interpretive phenomenology analysis that involves 9 nurse preceptors from hospitals in West Kalimantan,Indonesia.Semi-structured in-depth interviews were recorded and then transcribed verbatim.Results:Three themes were generated during the analysis:“types of student supervision,”“issues during supervision,”and“the need for research literacy and supervision.”Conclusions:Nurse preceptors need support to supervise the nursing students to use research findings.In addition to upgrading nursing skills,nurse preceptors must receive training in research and its utilization.Developing an appropriate strategy to assist students in using research findings will enhance the promotion of evidence-based nursing practices on a daily basis.

Effects of Al_(2)O_(3)-SiO_(2) Raw Material Types on Properties of Anorthite Based Insulation Refractories

To optimize their Al_(2)O_(3)-SiO_(2) raw materials,anorthite based insulation refractories were prepared by the in-situ sintering process combined with the foaming method after sintering at 1350℃for 3 h,using green and pollution-free kaolin,kyanite,andalusite and sillimanite as Al_(2)O_(3)-SiO_(2) raw materials,respectively,and industrial CaCO_(3) as the CaO source.Effects of Al_(2)O_(3)-SiO_(2) raw material types on the physical properties,phase composition and microstructure were investigated.The results are as follows.All samples prepared by different Al_(2)O_(3)-SiO_(2) raw materials have hexagonal flake anorthite and a small amount of mullite and corundum.Their bulk density and thermal conductivity decrease in the order of using kaolin,andalusite,kyanite and sillimanite as the Al_(2)O_(3)-SiO_(2) raw material,but their apparent porosity increases.Moreover,in the sample with kaolin,the bonding between anorthite crystals on the pore walls is closer than that of the other samples,which is conducive to increasing the cold crushing strength.The bonding between anorthite crystals on pore walls gradually decreases in the order of using kyanite,andalusite and sillimanite as the Al_(2)O_(3)-SiO_(2) raw material,thus their cold crushing strength decreases accordingly.In comprehensive consideration,the properties of the sample from kyanite are the optimal.Its apparent porosity,thermal conductivity and cold crushing strength are 84.6%,0.141 W·m^(-1)·K^(-1) and 1.89 MPa,respectively.

Classification analysis of prediction skill among ensemble members in MJO subseasonal predictions——based on the results of the CAMS-CSM subseasonal prediction system

由于模式误差和初始误差所致,次季节-季节预报技巧整体偏低.国际上多数模式都采用集合预报的方式来提高次季节预报的准确率.热带大气季节内振荡(MJO)作为次季节尺度可预报性的重要来源,其预测水平取决于模式性能和MJO事件本身的物理特性.根据中国气象科学研究院气候系统模式次季节预测系统的回报结果,结合不同类型MJO事件的特征,对模式集合成员间的预报技巧进行了分类和比较.在集合成员预报技巧普遍较高的一类MJO事件中,对流异常信号持续时间较长,强度较大,强对流异常中心主要位于印度洋区域,并逐渐东传至西太平洋.在集合成员预报技巧多数较差的MJO事件中,对流异常信号的强度最弱,维持时间最短.在集合成员预报技巧优劣参半的类别中,MJO往往持续时间较短,强度较低,在后续传播过程中,对流异常中心多停驻在海洋性大陆区域.

Short Communication: Enhancing the Drying Process of Microbial-Based Products with a Dehumidifier

The development of microbial-based products requires certain criteria for them to be successfully commercialized. The product must meet the following desirable criteria: effectiveness, contamination free, stability, cost-effectiveness, and a prolonged shelf life. Controlling the drying process is crucial for ensuring the stability and durability of the product. The traditional approach, which involved mechanical and natural drying, led to decreased productivity and quality. The objective of this research endeavour was to achieve a dry process enhancement while preserving the microbial quality of Trichoderma asperellum (M103). The temperature and relative humidity during the drying period were monitored under two conditions: with and without a dehumidifier. The results demonstrate that the dehumidifier increases drying period efficiency by up to 63%.

Fuzzy-Model-Based Finite Frequency Fault Detection Filtering Design for Two-Dimensional Nonlinear Systems

This article studies the fault detection filtering design problem for Roesser type two-dimensional(2-D)nonlinear systems described by uncertain 2-D Takagi-Sugeno(T-S)fuzzy models.Firstly,fuzzy Lyapunov functions are constructed and the 2-D Fourier transform is exploited,based on which a finite frequency fault detection filtering design method is proposed such that a residual signal is generated with robustness to external disturbances and sensitivity to faults.It has been shown that the utilization of available frequency spectrum information of faults and disturbances makes the proposed filtering design method more general and less conservative compared with a conventional nonfrequency based filtering design approach.Then,with the proposed evaluation function and its threshold,a novel mixed finite frequency H_(∞)/H_(-)fault detection algorithm is developed,based on which the fault can be immediately detected once the evaluation function exceeds the threshold.Finally,it is verified with simulation studies that the proposed method is effective and less conservative than conventional non-frequency and/or common Lyapunov function based filtering design methods.

Effectiveness of Wastewater-Based Epidemiology as an Early Warning Tool to Detect SARS-CoV-2 (COVID-19)

Medical diagnostic tests to detect Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) for individuals in the United States were initially limited to people who were traveling or symptomatic to track disease incidence due to the cost of providing testing for all people in a community on a routine basis. As an alternative to randomly sampling large groups of people to track disease incidence at significant cost, wastewater-based epidemiology (WBE) is a well-established and cost-effective technique to passively measure the prevalence of disease in communities without requiring invasive testing. WBE can also be used as a forecasting tool since the virus is shed in individuals prior to developing symptoms that might otherwise prompt testing. This study applied the WBE approach to understand its effectiveness as a possible forecasting tool by monitoring the SARS-CoV-2 levels in raw wastewater sampled from sewer lift stations at a large public university campus setting including dormitories, academic buildings, and athletic facilities. The WBE analysis was conducted by sampling from building-specific lift stations and enumerating target viral copies using RT-qPCR analysis. The WBE results were compared with the 7-day rolling averages of confirmed infected individuals for the following week after the wastewater sample analysis. In most cases, changes in the WBE outcomes were followed by similar trends in the clinical data. The positive predictive value of the applied WBE approach was 86% for the following week of the sample collection. In contrast, positive correlations between the two data with Spearmen correlation (rs) ranged from 0.16 to 0.36. A stronger correlation (rs = 0.18 to 0.51) was observed when WBE results were compared with COVID-19 cases identified on the next day of the sampling events. The P value of 0.007 for Dorm A suggests high significance, while moderate significance was observed for the other dormitories (B, C, and D). The outcomes of this investigation demonstrate that WBE can be a valuable tool to track the progression of diseases like COVID-19 seven days before diagnostic cases are confirmed, allowing authorities to take necessary measures in advance and also enable authorities to decide to reopen a facility after a quarantine.