Evaluation of the Predicted Particle Properties (P3) Microphysics Scheme in Simulations of Stratiform Clouds with Embedded Convection

To evaluate the ability of the Predicted Particle Properties(P3)scheme in the Weather Research and Forecasting(WRF)model,we simulated a stratiform rainfall event over northern China on 22 May 2017.WRF simulations with two P3 versions,P3-nc and P3-2ice,were evaluated against rain gauge,radar,and aircraft observations.A series of sensitivity experiments were conducted with different collection efficiencies between ice and cloud droplets.The comparison of the precipitation evolution between P3-nc and P3-2ice suggested that both P3 versions overpredicted surface precipitation along the Taihang Mountains but underpredicted precipitation in the localized region on the leeward side.P3-2ice had slightly lower peak precipitation rates and smaller total precipitation amounts than P3-nc,which were closer to the observations.P3-2ice also more realistically reproduced the overall reflectivity structures than P3-nc.A comparison of ice concentrations with observations indicated that P3-nc underestimated aggregation,whereas P3-2ice produced more active aggregation from the self-collection of ice and ice-ice collisions between categories.Efficient aggregation in P3-2ice resulted in lower ice concentrations at heights between 4 and 6 km,which was closer to the observations.In this case,the total precipitation and precipitation pattern were not sensitive to riming.Riming was important in reproducing the location and strength of the embedded convective region through its impact on ice mass flux above the melting level.

The Validity of the Thermohydrogravidynamic Theory Concerning the Predicted Dates of the Maximal Temporal Intensifications of the Global Seismotectonic Processes of the Earth during the Range 2020 - 2023 AD

We present (on the 13th International Conference on Geology and Geophysics) the convincing evidence that the strongest earthquakes (according to the U.S. Geological Survey) of the Earth (during the range 2020 - 2023 AD) occurred near the predicted (calculated in advance based on the global prediction thermohydrogravidynamic principles determining the maximal temporal intensifications of the global seismotectonic, volcanic, climatic and magnetic processes of the Earth) dates 2020.016666667 AD (Simonenko, 2020), 2021.1 AD (Simonenko, 2019, 2020), 2022.18333333 AD (Simonenko, 2021), 2023.26666666 AD (Simonenko, 2022) and 2020.55 AD, 2021.65 AD (Simonenko, 2019, 2021), 2022.716666666 AD (Simonenko, 2022), respectively, corresponding to the local maximal and to the local minimal, respectively, combined planetary and solar integral energy gravitational influences on the internal rigid core of the Earth. We present the short-term thermohydrogravidynamic technology (based on the generalized differential formulation of the first law of thermodynamics and the first global prediction thermohydrogravidynamic principle) for evaluation of the maximal magnitude of the strongest (during the March, 2023 AD) earthquake of the Earth occurred on March 16, 2023 AD (according to the U.S. Geological Survey). .

Development of a modified predicted heat strain model for hot work environments

Excessive exposure to heat can lead to injuries,illness,and death among mineworkers.The actual cost of heat-related injuries and illnesses is unknown because of underreporting and lack of symptom recognition.Multi-factorial,evidence-based,and field-ready guidelines for identifying–and predicting–physiolo gical markers of heat strain are currently unavailable.The predicted heat strain(PHS)model,is the latest attempt by mining companies to aid in the evaluation and management of occupational heat exposures.The adopted algorithm relies on worksite environmental measurements and an estimate of individual metabolic rate for mine workers to provide an estimate of the workers’core temperature during a work shift.There are several known limitations of the PHS model,including the assumption that the subject worker is hydrated and fit.A modified PHS model was presented based on eight physical parameters that are measured at different intervals during a work shift;these parameters are air temperature,relative humidity,air velocity,radiation,metabolic rate,acclimatization,clothing insulation and posture.To validate the results,the predictions from the modified PHS model were compared with direct physiological measurements obtained from ingestible pills and heat stress monitors under different environmental and working conditions.

Predicted 10-year Cardiovascular Disease Risk and Its Association with Sleep Duration among Adults in Beijing-Tianjin-Hebei Region,China

Objective The study aims to predict 10-year cardiovascular disease(CVD)risk and explore its association with sleep duration among Chinese urban adults.Methods We analyzed part of the baseline data of a cohort that recruited adults for health screening by cluster sampling.The simplified Pittsburgh Sleep Quality Index(PSQI)and Framingham 10-year risk score(FRS)were used to measure sleep duration and CVD risk.Demographic characteristics,personal history of chronic diseases,lifestyle factors were collected using a questionnaire.Height,weight,total cholesterol(TC),and high-density lipoprotein cholesterol(HDL-C)were also measured.Multiple logistic regression models were performed to explore the association of sleep duration with the predicted CVD risk.Results We included 31,135 participants(median age 44 years,53.02%males)free of CVD,cerebral stroke,and not taking lipid-lowering agents.Overall,14.05%,and 25.55%of participants were at medium and high predicted CVD risk,respectively.Short sleep was independently associated with increased odds of medium to high risk of predicted 10-year CVD among males(OR=1.10;95%CI:1.01–1.19)and increased odds of medium to high and high risk of predicted 10-year CVD among females(OR=1.23;95%CI:1.08–1.40;OR=1.27;95%CI:1.11–1.44).In contrast,long sleep had no association with cardiovascular risk.Conclusion A substantial number of adults free of CVD were at high 10-year CVD risk.Short sleep was associated with increased odds of predicted CVD risk.

The African Climate as Predicted by the IAP Grid-Point Nine-Layer Atmospheric General Circulation Model (IAP-9L-AGCM)

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Relationship between predicted oxygen uptake and cigarette smoking in Japanese men

The link between cigarette smoking and predicted oxygen uptake was investigated using data for 149 Japanese men not taking medication. Cigarette smoking habits were obtained through interviews by well-trained staff. The influence of cigarette smoking on predicted oxygen uptake, predicted work rate and predicted heart rate were evaluated. Predicted oxygen uptake decreased with age. Predicted oxygen uptake and predicted work rate in men who smoked cigarettes was significantly lower than in subjects who did not, after adjusting for age. The differences in parameters did not reach significant levels after adjusting for age and physical activity evaluated by Σ[metabolic equivalents × h per week (METs?h/w)] (predicted oxygen uptake: p = 0.0632, predicted work rate: p = 0.0873). Cigarette smoking might be a modifyable factor for improving the aerobic exercise level in Japanese men.

The involvement of proline-rich protein Mus musculus predicted gene 4736 in ocular surface functions

AIM: To research the two homologous predicted proline -rich protein genes, Mus musculus predicted gene 4736 (MP4) and proline-rich protein BstNI subfamily 1 (Prb1) which were significantly upregulated in cultured corneal organs when encountering fungal pathogen preparations. This study was to confirm the expression and potential functions of these two genes in ocular surface. METHODS: A Pseudomonas aeruginosa keratitis model was established in Balb/c mice. One day post infection, mRNA level of MP4 was measured using real-time polymerase chain reaction (PCR), and MP4 protein detected by immunohistochemistry (IHC) or Western blot using a customized polyclonal anti -MP4 antibody preparation. Lacrimal glands from normal mice were also subjected to IHC staining for MP4. An online bioinformatics program, BioGPS, was utilized to screen public data to determine other potential locations of MP4. RESULTS: One day after keratitis induction, MP4 was upregulated in the corneas at both mRNA level as measured using real -time PCR and protein levels as measured using Western blot and IHC. BioGPS analysis of public data suggested that the MP4 gene was most abundantly expressed in the lacrimal glands, and IHC revealed that normal murine lacrimal glands were positive for MP4 staining. CONCLUSION: MP4 and Prb1 are closely related with the physiology and pathological processes of the ocular surface. Considering the significance of ocular surface abnormalities like dry eye, we propose that MP4 and Prb1 contribute to homeostasis of ocular surface, and deserve more extensive functional and disease correlation studies.

Ground-State Structure and Physical Properties of NB_2 Predicted from First Principles

Using the newly developed particle swarm optimization algorithm on crystal structural prediction, we predict a new class of boron nitride with stoicMometry of NB2 at ambient pressure, which belongs to the tetragonal 14m2 space group. Then, its structure, elastic properties, electronic structure, and chemical bonding are investigated by first-principles calculations with the density functional theory. The phonon calculation and elastic constants confirm that the predicted NB2 is dynamically and mechanically stable, respectively. The large bulk modulus, large shear modulus, large Young＇s modulus, and small Poisson＇s ratio show that the 14m2 NB2 should be a new superhard material with a calculated theoretical Vickers hardness value of 66 GPa. Further analysis on density of states and electron localization function demonstrate that the strong B B and 13 N covalent bonds are the main reason for its high hardness in 14m2 NB2.

Predictive value of extravascular lung water indexed to predicted body weight

AIM: To investigate extravascular lung water indexed to predicted body weight(EVLWIp) and actual body weight(EVLWIa) on outcome of patients with severe sepsis.METHODS: Transpulmonary thermodilution was prospectively used to measure cardiovascular hemodynamics, EVLWIp and EVLWIa via an arterial catheter placed in each patient within 48 h of meeting the criteria for severe sepsis from a medical intensive care unit(ICU) at a university affiliated hospital. Survival was the single dependent variable. In order to examine and compare the predictive power of EVLWIp, EVLWIa and other clinically significant factors in predicting the inhospital survival status of severe sepsis patients in the medical ICU, a receiver operating characteristic(ROC) curve method to analyze the significant variables and the area under the ROC curve(AUC) of the variables, P value and 95%CI were calculated.RESULTS: In total, 33 patients were studied. In the ROC curve method analyses, EVLWIp(the AUC: 0.849; P = 0.001, 95%CI: 0.72-0.98) was as predictive for inhospital survival rate as variables with EVLWIa(AUC, 0.829; P = 0.001, 95%CI: 0.68-0.98). The proportion of patients surviving with a low EVLW(EVLWI < 10 m L/kg) was better than that of patients with a higher EVLW, whether indexed by actual(HR = 0.2; P = 0.0002, 95%CI: 0.06-0.42) or predicted body weight(HR = 0.13; P < 0.0001, 95%CI: 0.05-0.35) during their hospital stay with the Kaplan-Meier method(76% vs 12.5%, respectively).CONCLUSION: This investigation proposed that EVLWIp is as good a predictor as EVLWIa to predict inhospital survival rate among severe sepsis patients in the medical ICU.

On similarity profiles predicted in the convective marine boundary layer

On the basis of the ideal of local scale similarity theory, the profile equations of wind, temperature and humidity for the eonvective marine boundary layer have been obtained. The marine boundary layer measurements were made over the western Pacific Ocean as past of the Tropical Ocean and Global Atmosphere (TOGA) Programme during Nov. 1986-Feb. 1987. The similarity profiles predicledfor wind. temperature and humidity in the MBL are in good agreement with the observational data.

Predicted High Thermoelectric Performance of Quasi-Two-Dimensional Compound GeAs Using First-Principles Calculations

The electronic structure of binary quasi-two-dimensional GeAs is investigated using first-principles calculations, and it is found that the anisotropic structure of the layered compound GeAs brings about the anisotropy of the transport properties. Meanwhile, the band structure of GeAs exhibits a relatively large dispersion near the valence-band maximum in the Z –V direction while it is rather flat in the Z –Γ direction, which is highly desirable for good thermoelectric performance. The calculated partial charge density distribution also reveals that GeAs possesses anisotropic electrical conductivity. Based on the semi-classical Boltzmann transport theory, the anisotropic transport properties are observed, and the optimal doping concentrations are estimated. The temperature dependence transport properties of p-type GeAs are compared with the experimental data in good agreement, and the theoretical figure-of-merit ZT has been predicted as well.

Comparison of REML and MINQUE for Estimated Variance Components and Predicted Random Effects

Linear mixed model (LMM) approaches have been widely applied in many areas of research data analysis because they offer great flexibility for different data structures and linear model systems. In this study, emphasis is placed on comparing the properties of two LMM approaches: restricted maximum likelihood (REML) and minimum norm quadratic unbiased estimation (MINQUE) with and without resampling techniques being included. Bias, testing power, Type I error, and computing time were compared between REML and MINQUE approaches with and without Jackknife technique based on 500 simulated data sets. Results showed that MINQUE and REML methods performed equally regarding bias, Type I error, and power. Jackknife-based MINQUE and REML greatly improved power compared to non-Jackknife based linear mixed model approaches. Results also showed that MINQUE is more time-saving compared to REML, especially with the use of resampling techniques and large data set analysis. Results from the actual cotton data analysis were in agreement with our simulated results. Therefore, Jackknife-based MINQUE approaches could be recommended to achieve desirable power with reduced time for a large data analysis and model simulations.

Predicted Employment Situation from 1996 to 2000

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Tissue factor in predicted severe acute pancreatitis

AIM: To study tissue factor (TF) in acute pancreatitis and evaluate the role of TF as a predictive marker of severity. METHODS: Forty-nine consecutive patients admitted to Lund University Hospital, fulfilling the criteria of predicted severe acute pancreatitis (AP), were recruited prospectively between 2002 and 2004. Blood samples for TF analyses were drawn at inclusion in the study and 12 h, 1 d and 3 d later. RESULTS: Twenty-seven patients developed mild AP, and 22 patients severe AP. At inclusion in the study, the groups were comparable with respect to gender, aetiology, Acute Physiology and Chronic Health Evaluation Ⅱ score, and duration of pain. At inclusion in the study and at 12 h, TF was higher in the severe AP group (P = 0.035 and P = 0.049, respectively). After 1 and 3 d, no differences in TF levels were noted. Interleukin (IL)-6 was significantly higher in the severe AP group at all of the studied time points. C-reactive protein (CRP) was significantly higher in the AP group at 1 and 3 d. In receiver operating characteristic-curves, the area under the curve (AUC) for TF was 0.679 (P = 0.035) at inclusion in the study, and a cut off level for TF of 40 pg/mL showed a sensitivity of 71% and a specificity of 67%, whereas corresponding AUC for IL-6 was 0.775, P = 0.001, and for CRP was 0.653. IL-6 showed better AUC-values than TF at all time points studied. CONCLUSION: TF-levels are raised early in severe AP. TF as an early predictive marker of severe AP is superior to CRP, but inferior to IL-6.

Wavelet analysis of quasi-3-year temperature oscillations in China in last 50 years, and predicted changes in the next 20 years

The wavelet analysis method is used to analyze the annual and winter temperature data of 98 observation stations in China in eight climate zones during the last 50 years （1961-2009）. The periodicities of temperature changes are investigated, and the possible temperature change trends in China in the next 20 years （2012-2029） are also predicted. Our results show that in the inter-annual temperature variability there are pervasive quasi-3- to quasi-4-year cycles, and these cycle changes are relatively steady. The periodic characteristics of the annual temperature changes are clearly different between northern and southern China, and our period superimposition extrapolation shows that both annual and winter temperatures in China will continue to increase in the next 20 years, more so in northern China and in the Qinghai-Xizang Plateau （QXP） than in the southern region, except in the southwest. If temperatures follow historic increasing linear trends, the overall temper- ature is expected to increase by 1℃ between 2010 and 2029.

Basal Energy Expenditure of Chinese Healthy Adults:Comparison of Measured and Predicted Values

Objective This study aimed to measure the basal energy expenditure(BEE)of Chinese healthy adults and establish an accurate predictive equation for this population.Methods In total,470 Chinese healthy adults had their BEE measured using the Cosmed K4b2 portable metabolic system.Multiple linear regression analysis was applied to develop new optimal equations for predicting BEE.The bias,accuracy rate,concordance correlation coefficient(CCC),and root mean square error(RMSE)were used to evaluate the accuracy of the predictive equations.Results There was a significant difference in BEE between males and females,with 5,954 kJ/d and 5,089 kJ/d,respectively.People living in rural areas expended significantly higher BEE(5,885 kJ/d)than those in urban areas(5,279 kJ/d).Previous equations developed by Henry,Schofield,Harris-Benedict(HB),and Liu overestimated the BEE of Chinese healthy adults.The new equations derived from the present study displayed the smallest average bias and RMSE from the measured basal energy expenditure(mBEE).The CCC of the new equations was higher than other predictive equations,but it was lower than 0.8.There was no significant difference in the accuracy rate among all predictive equations.Conclusions Sex and regional differences in BEE were observed in Chinese healthy adults.Neither the widely used previous predictive equations nor the one derived in the present study were accurate enough for estimating the BEE of Chinese healthy adults.Further study is required to develop more accurate equations for predicting the BEE of Chinese healthy adults aged between 20–45 years.

An immunoglobulin Y that specifically binds to an in silico-predicted unique epitope of Zika virus non-structural 1 antigen

Objective:To identify unique immunogenic epitopes of Zika virus non-structural 1(NS1)antigen and produce immunoglobulin Y(IgY)for potential use in he diagnosis of of Zika virus infection.Methods:Immunogenic epitopes were identified using in silico B-cell epitope prediction.A synthetic peptide analog of the predicted epitope was used to induce antipeptide IgY production in hens which was purified using affinity chromatography.Presence of purified IgY and its binding specificity were performed by gel electrophoresis and ELISA,respectively.Results:Out of the nine continuous epitopes identified,the sequence at position 193-208(LKVREDYSLECDPAVI)was selected and used to produce anti-peptide IgY.The produced IgY was found to bind to the synthetic analog of the Zika virus NS1 immunogenic epitope but not to other flaviviruses and random peptides from other pathogens.Conclusions:In this study,we identified an immunogenic epitope unique to Zika virus that can be used to develop a serodiagnostic tool that specifically detect Zika virus infection.

High-pressure structures of InBi predicted by particle swarm optimization algorithm

We extensively explore the high-pressure structures of InBi by using a newly developed particle swarm optimization algorithm. An orthorhombic Imma structure is discovered to be stable from 43.7 GPa to 107.9 GPa, ruling out the previously speculated cubic structure. Further increasing the pressure, we find a tetragonal P4/nmm structure which is energetically more favourable from 107.9 CPa to 200 GPa. Especially, the tetragonal P4/nmm structure is known to occur at high pressure in the structures of ZnO and MgTe. We also predict this structure to be a high-pressure structure of ZnTe. Thus the tetragonal P4/nmm structure may be a universal high-pressure structure of the Ⅱ-Ⅵ and the Ⅲ-Ⅴ compounds.

Web-GIS Based Visualization System of Predicted Ground Vibration Induced by Blasting in Urban Quarry Sites

Blasting is routinely carried out at various resource extraction sites, even in urban areas. As a consequence of this, residents around urban quarry sites are affected by ground vibration induced by blasting on a regular basis. In this study, a prediction and visualization system for ground vibrations is developed for the purpose of reducing the adverse psychological effects of blasting. The system consists of predicting ground vibration using an Artificial Neural Network (ANN) and visualizing it on an online map using Web-GIS. A prediction model using ANN that learned the optimum weight by taking 50 sets of data indicated a regression value of 0.859 and a Mean Square Error (MSE) of 0.0228. Compared with previous researches, these values are not bad results. Peak Particle Velocity (PPV) was used as a metric to measure ground vibration intensity. A color contour is generated using GIS tools based on the PPV value of each prediction point. The system is completed by overlaying the contour onto a basic map in a website. The basic map shows the surrounding area through the use of Google Maps data. This system can be used by anyone with access to the internet and a browser, requiring no special software or hardware. In addition, mining operations can utilize the data to modify blasting design and planning to minimize ground vibration. In conclusion, this system has the potential to alleviate the worries of surrounding residents caused by ground vibrations from blasting due to the fact that they can personally check the predicted vibration around their locale. Furthermore, since this data will be publicly available on the internet, it is also possible that this system can contribute to research in other fields.

Robust Predictive Control of Uncertain Systems with Time-delay Using Tight Sets of Predicted States

A robust model predictive control (MPC) algorithm for discrete time linear systems with time-delay (RPC-TDS) subjected to constrained input control is presented, where the polytopic uncertainties exist in state matrices and input matrices. In the algorithm the standard optimization of quadratic objective function has been transformed into optimization of sum of N+1 upper bounds of the quadratic objective function with respect to N control moves and a state feedback control law, where N is the control horizon. The feasibility of the optimization problem guarantees that the algorithm is robustly stable. The simulation results verify the effectiveness of the proposed algorithm.