Efficient and Stable Perovskite Solar Cells and Modules Enabled by Tailoring Additive Distribution According to the Film Growth Dynamics

Gas quenching and vacuum quenching process are widely applied to accelerate solvent volatilization to induce nucleation of perovskites in blade-coating method.In this work,we found these two pre-crystallization processes lead to different order of crystallization dynamics within the perovskite thin film,resulting in the differences of additive distribution.We then tailor-designed an additive molecule named 1,3-bis(4-methoxyphenyl)thiourea to obtain films with fewer defects and holes at the buried interface,and prepared perovskite solar cells with a certified efficiency of 23.75%.Furthermore,this work also demonstrates an efficiency of 20.18%for the large-area perovskite solar module(PSM)with an aperture area of 60.84 cm^(2).The PSM possesses remarkable continuous operation stability for maximum power point tracking of T_(90)>1000 h in ambient air.

Differential distribution of PINK1 and Parkin in the primate brain implies distinct roles

The vast majority of in vitro studies have demonstrated that PINK1 phosphorylates Parkin to work together in mitophagy to protect against neuronal degeneration.However,it remains largely unclear how PINK1 and Parkin are expressed in mammalian brains.This has been difficult to address because of the intrinsically low levels of PINK1 and undetectable levels of phosphorylated Parkin in small animals.Understanding this issue is critical for elucidating the in vivo roles of PINK1 and Parkin.Recently,we showed that the PINK1 kinase is selectively expressed as a truncated form(PINK1–55)in the primate brain.In the present study,we used multiple antibodies,including our recently developed monoclonal anti-PINK1,to validate the selective expression of PINK1 in the primate brain.We found that PINK1 was stably expressed in the monkey brain at postnatal and adulthood stages,which is consistent with the findings that depleting PINK1 can cause neuronal loss in developing and adult monkey brains.PINK1 was enriched in the membrane-bound fractionations,whereas Parkin was soluble with a distinguishable distribution.Immunofluorescent double staining experiments showed that PINK1 and Parkin did not colocalize under physiological conditions in cultured monkey astrocytes,though they did colocalize on mitochondria when the cells were exposed to mitochondrial stress.These findings suggest that PINK1 and Parkin may have distinct roles beyond their well-known function in mitophagy during mitochondrial damage.

Pretreatment red blood cell distribution width as a predictive marker for postoperative complications after laparoscopic pancreatoduodenectomy

BACKGROUND Red blood cell distribution width(RDW)is associated with the development and progression of various diseases.AIM To explore the association between pretreatment RDW and short-term outcomes after laparoscopic pancreatoduodenectomy(LPD).METHODS A total of 804 consecutive patients who underwent LPD at our hospital between March 2017 and November 2021 were retrospectively analyzed.Correlations between pretreatment RDW and clinicopathological characteristics and short-term outcomes were investigated.RESULTS Patients with higher pretreatment RDW were older,had higher Eastern Cooperative Oncology Group scores and were associated with poorer short-term outcomes than those with normal RDW.High pretreatment RDW was an independent risk factor for postoperative complications(POCs)(hazard ratio=2.973,95%confidence interval:2.032-4.350,P<0.001)and severe POCs of grade IIIa or higher(hazard ratio=3.138,95%confidence interval:2.042-4.824,P<0.001)based on the Clavien-Dino classification system.Subgroup analysis showed that high pretreatment RDW was an independent risk factor for Clavien-Dino classi-fication grade IIIb or higher POCs,a comprehensive complication index score≥26.2,severe postoperative pancreatic fistula,severe bile leakage and severe hemorrhage.High pretreatment RDW was positively associated with the neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio and was negatively associated with albumin and the prognostic nutritional index.CONCLUSION Pretreatment RDW was a special parameter for patients who underwent LPD.It was associated with malnutrition,severe inflammatory status and poorer short-term outcomes.RDW could be a surrogate marker for nutritional and inflammatory status in identifying patients who were at high risk of developing POCs after LPD.

Effects of aggregate size distribution and carbon nanotubes on the mechanical properties of cemented gangue backfill samples under true triaxial compression

The mechanical behavior of cemented gangue backfill materials(CGBMs)is closely related to particle size distribution(PSD)of aggregates and properties of cementitious materials.Consequently,the true triaxial compression tests,CT scanning,SEM,and EDS tests were conducted on cemented gangue backfill samples(CGBSs)with various carbon nanotube concentrations(P_(CNT))that satisfied fractal theory for the PSD of aggregates.The mechanical properties,energy dissipations,and failure mechanisms of the CGBSs under true triaxial compression were systematically analyzed.The results indicate that appropriate carbon nanotubes(CNTs)effectively enhance the mechanical properties and energy dissipations of CGBSs through micropore filling and microcrack bridging,and the optimal effect appears at P_(CNT)of 0.08wt%.Taking PSD fractal dimension(D)of 2.500 as an example,compared to that of CGBS without CNT,the peak strength(σ_(p)),axial peak strain(ε_(1,p)),elastic strain energy(Ue),and dissipated energy(U_(d))increased by 12.76%,29.60%,19.05%,and90.39%,respectively.However,excessive CNTs can reduce the mechanical properties of CGBSs due to CNT agglomeration,manifesting a decrease inρ_(p),ε_(1,p),and the volumetric strain increment(Δε_(v))when P_(CNT)increases from 0.08wt%to 0.12wt%.Moreover,the addition of CNTs improved the integrity of CGBS after macroscopic failure,and crack extension in CGBSs appeared in two modes:detour and pass through the aggregates.Theσ_(p)and U_(d)firstly increase and then decrease with increasing D,and porosity shows the opposite trend.Theε_(1,p)andΔε_(v)are negatively correlated with D,and CGBS with D=2.150 has the maximum deformation parameters(ε_(1,p)=0.05079,Δε_(v)=0.01990)due to the frictional slip effect caused by coarse aggregates.With increasing D,the failure modes of CGBSs are sequentially manifested as oblique shear failure,"Y-shaped"shear failure,and conjugate shear failure.

Novel Low-Carbon Optimal Operation Method for Flexible Distribution Network Based on Carbon Emission Flow

With the widespread implementation of distributed generation(DG)and the integration of soft open point(SOP)into the distribution network(DN),the latter is steadily transitioning into a flexible distribution network(FDN),the calculation of carbon flow distribution in FDN is more difficult.To this end,this study constructs a model for low-carbon optimal operations within the FDN on the basis of enhanced carbon emission flow(CEF).First,the carbon emission characteristics of FDNs are scrutinized and an improved method for calculating carbon flow within these networks is proposed.Subsequently,a model for optimizing low-carbon operations within FDNs is formulated based on the refined CEF,which merges the specificities of DG and intelligent SOP.Finally,this model is scrutinized using an upgraded IEEE 33-node distribution system,a comparative analysis of the cases reveals that when DG and SOP are operated in a coordinated manner in the FDN,with the cost of electricity generation was reduced by 40.63 percent and the cost of carbon emissions by 10.18 percent.The findings indicate that the judicious optimization of areas exhibiting higher carbon flow rates can effectively enhance the economic efficiency of DN operations and curtail the carbon emissions of the overall network.

A Case Study on Garbage Code Redistribution Methods for Heart Failure at City Level by Two Approaches

Cause of death surveillance data is most important for developing effective health policies,whose quality is crucially affected by the accuracy of the underlying cause of death(UCOD)provided in death certificates.The World Health Organization(WHO)has clearly defined a UCOD as“the disease or injury which initiated the train of morbid events leading directly to death,or the circumstance of the accident or violence which produced the fatal injuries”[1].

Some Eigenvalue Properties of Third-order Boundary Value Problems with Distributional Potentials

Several eigenvalue properties of the third-order boundary value problems with distributional potentials are investigated.Firstly,we prove that the operators associated with the problems are self-adjoint and the corresponding eigenvalues are real.Next,the continuity and differential properties of the eigenvalues of the problems are given,especially we find the differential expressions for the boundary conditions,the coefficient functions and the endpoints.Finally,we show a brief application to a kind of transmission boundary value problems of the problems studied here.

Modeling the potential distribution of Argentine shortfin squid in the southwest Atlantic Ocean

The Argentine shortfin squid Illex argentinus is an economically important short-lived species widely distributed in the southwest Atlantic Ocean.The abundance and distribution of I.argentinus are associated with climate change and environmental fluctuations.The potential distribution of I.argentinus was modeled with various environmental variables including sea surface temperature(SST),sea surface height(SSH),chlorophyll a,sea surface salinity(SSS),net primary productivity(NPP),mixed layer depth(MLD),eddy kinetic energy(EKE),and photosynthetically active radiation(PAR)using the maximum entropy(MaxEnt)approach during the peak fishing seasons(January–April).The habitat suitability index(HSI)was defined as the probability of species emergence from the MaxEnt model and the area of HSI≥0.6 was regarded as suitable.Results indicate that the predicted habitat correlated with the actual fishing position,with similar trends in the percentages of suitable habitats and catch per unit effort(CPUE)of I.argentinus from January to April.Moreover,SST,SSH,PAR,and MLD were identified critical environmental variables for the distribution of I.argentinus.In addition,the median of preferred ranges of the critical environmental variables were concentrated within the suitable habitats of I.argentinus.The Area under the Receiver Operating Characteristic Curve(AUC)was greater than 0.96 for all four months.Variations in latitudinal and longitudinal gravity centers(LATG and LONG)of fishing effort were consistent with latitudinal and longitudinal gravity centers(LATG_H and LONG_H)of the HSI.Our findings suggest that the MaxEnt model is an effective tool to predict the potential distribution of I.argentinus.Meanwhile,SST,SSH,PAR,and MLD should be given with more extensive attention in predicting the potential distribution of I.argentinus,as they are important environmental indicators that can help decision-makers search for the fishing ground of I.argentinus in the Southwest Atlantic.

Numerical Simulation of Flow and Temperature Distribution in a Bottom-Blown Copper Bath

Smelting with oxygen bottom blowing is one of the main methods used in the frame of copper pyrometallurgy.With this approach,feed materials and oxygen-enriched air are introduced in reversed order to enhance multiphaseflow within the furnace.Understanding the flow structure and temperature distribution in this setup is crucial foroptimizing production.In this study,gas-liquid interactions,and temperature profiles under varying air-injectionconditions are examined by means of numerical simulation for a 3.2 m×20 m furnace.The results indicate that thehigh-velocity regions are essentially distributed near the lance within the reaction region and the flue gas outlet,while low-velocity regions are located close to the furnace walls on both side of the reaction region.Dead regionsappear in the sedimentation region,with gas velocities surpassing those of the molten phase.As the injection rateincreases from 0.50 to 0.80 Nm3/s,the stabilization time of the average liquid surface velocity decreases from 2.6 sto 1.9 s,exhibiting a similar trend to the gas holdup.During stabilization,the average liquid surface velocity risesfrom 0.505 to 0.702 m/s.The average turbulent kinetic energy(TKE)of the fluid in the molten bath increases from0.095 to 0.162 m^(2)/s^(2).The proportion of the area distribution with TKE greater than 0.10 m^(2)/s^(2) and the gas holdupat steady state both rise with an increase in the injection quantity.The maximum splashing height of the melt growsfrom approximately 0.756 to 1.154 m,with the affected area expanding from 14.239 to 20.498 m^(2).Under differentworking conditions with varying injection quantities,the average temperature changes in melt zone and flue gaszone of the furnace are small.The temperature in the melt and in the flue-gas zone spans the interval 1200℃–1257℃,and 1073℃–1121℃,respectively.The temperature distribution of the melt and flue gas reveals a patterncharacterized by elevated temperatures in the reaction zone,gradually transitioning to lower temperatures in thesedimentation region.

Data driven prediction of fragment velocity distribution under explosive loading conditions

This study presents a machine learning-based method for predicting fragment velocity distribution in warhead fragmentation under explosive loading condition.The fragment resultant velocities are correlated with key design parameters including casing dimensions and detonation positions.The paper details the finite element analysis for fragmentation,the characterizations of the dynamic hardening and fracture models,the generation of comprehensive datasets,and the training of the ANN model.The results show the influence of casing dimensions on fragment velocity distributions,with the tendencies indicating increased resultant velocity with reduced thickness,increased length and diameter.The model's predictive capability is demonstrated through the accurate predictions for both training and testing datasets,showing its potential for the real-time prediction of fragmentation performance.

Spatial distribution of shallow landslides caused by Typhoon Lekima in 2019 in Zhejiang Province, China

In recent years, the coastal region of Southeast China has witnessed a significant increase in the frequency and intensity of extreme rainfall events associated with landfalling typhoons. The hilly and mountainous terrain of this area, combined with rapid rainfall accumulation, has led to a surge in flash floods and severe geological hazards. On August 10, 2019, Typhoon Lekima made landfall in Zhejiang Province, China, and its torrential rainfall triggered extensive landslides, resulting in substantial damage and economic losses. Utilizing high-resolution satellite images, we compiled a landslide inventory of the affected area, which comprises a total of 2,774 rainfallinduced landslides over an area of 2965 km2. The majority of these landslides were small to mediumsized and exhibited elongated, clustered patterns. Some landslides displayed characteristics of high-level initiation, obstructing or partially blocking rivers, leading to the formation of debris dams. We used the inventory to analyze the distribution pattern of the landslides and their relationship with topographical, geological, and hydrological factors. The results showed that landslide abundance was closely related to elevation, slope angle, faults, and road density. The landslides were predominantly located in hilly and low mountainous areas, with elevations ranging from 150 to 300 m, slopes of 20 to 30 degrees, and a NE-SE aspect. Notably, we observed the highest Landslide Number Density(LND) and Landslide Area Percentage(LAP) in the rhyolite region. Landslides were concentrated within approximately 4 km on either side of fault zones, with their size and frequency negatively correlated with distances to faults, roads, and river systems. Furthermore, under the influence of typhoons, regions with denser vegetation cover exhibited higher landslide density, reaching maximum values in shrubland areas. In areas experiencing significantly increased concentrated rainfall, landslide density also showed a corresponding rise. In terms of spatial distribution, the rainfall-triggered landslides primarily occurred in the northeastern part of the study area, particularly in regions characterized by complex topography such as Shanzao Village in Yantan Town, Xixia Township, and Shangzhang Township. The research findings offer crucial data on the rainfallinduced landslides triggered by Typhoon Lekima, shedding light on their spatial distribution patterns. These findings provide valuable references for mitigating risks and planning reconstruction in typhoon-affected area.

Red cell distribution width-to-albumin ratio is a simple promising prognostic marker in acute cholangitis requiring biliary drainage

Background: It is crucial to assess the severity of acute cholangitis(AC). There are currently several prognostic markers. However, the accuracies of these markers are not satisfied. The present study aimed to investigate the predictive value of the red cell distribution width(RDW)-to-albumin ratio(RAR) for the prognosis of AC. Methods: We retrospectively evaluated consecutive patients diagnosed with AC between May 2019 and March 2022. RAR was calculated, and its predictive ability for in-hospital mortality, intensive care unit(ICU) admission, bacteremia, and the length of hospitalization were analyzed. Results: Out of 438 patients, 34(7.8%) died. Multivariate analysis showed that malignant etiology [odds ratio(OR) = 4.816, 95% confidence interval(CI): 1.936-11.980], creatinine(OR = 1.649, 95% CI: 1.095-2.484), and RAR(OR = 2.064, 95% CI: 1.494-2.851) were independent risk factors for mortality. When adjusted for relevant covariates, including age, sex, malignant etiology, Tokyo severity grading(TSG), Charlson comorbidity index, and creatinine, RAR significantly predicted mortality(adjusted OR = 1.833, 95% CI: 1.280-2.624). When the cut-off of RAR was set to 3.8, its sensitivity and specificity for mortality were 94.1% and 56.7%, respectively. Patients with an RAR of > 3.8 had a 20.9-fold(OR = 20.9, 95% CI: 4.9-88.6) greater risk of mortality than the remaining patients. The area under the curve value of RAR for mortality was 0.835(95% CI: 0.770-0.901), which was significantly higher than that of TSG and the other prognostic markers, such as C-reactive protein-to-albumin ratio, and procalcitonin-to-albumin ratio. Lastly, RAR was not inferior to TSG in predicting ICU admission, bacteremia, and the length of hospitalization. Conclusions: RAR successfully predicted the in-hospital mortality, ICU admission, bacteremia, and the length of hospitalization of patients with AC, especially in-hospital mortality. RAR is a promising marker that is more convenient than TSG and other prognostic markers for predicting the prognosis of patients with AC.

Predictive value of red blood cell distribution width and hematocrit for short-term outcomes and prognosis in colorectal cancer patients undergoing radical surgery

BACKGROUND Previous studies have reported that low hematocrit levels indicate poor survival in patients with ovarian cancer and cervical cancer,the prognostic value of hematocrit for colorectal cancer(CRC)patients has not been determined.The prognostic value of red blood cell distribution width(RDW)for CRC patients was controversial.AIM To investigate the impact of RDW and hematocrit on the short-term outcomes and long-term prognosis of CRC patients who underwent radical surgery.METHODS Patients who were diagnosed with CRC and underwent radical CRC resection between January 2011 and January 2020 at a single clinical center were included.The short-term outcomes,overall survival(OS)and disease-free survival(DFS)were compared among the different groups.Cox analysis was also conducted to identify independent risk factors for OS and DFS.RESULTS There were 4258 CRC patients who underwent radical surgery included in our study.A total of 1573 patients were in the lower RDW group and 2685 patients were in the higher RDW group.There were 2166 and 2092 patients in the higher hematocrit group and lower hematocrit group,respectively.Patients in the higher RDW group had more intraoperative blood loss(P<0.01)and more overall complications(P<0.01)than did those in the lower RDW group.Similarly,patients in the lower hematocrit group had more intraoperative blood loss(P=0.012),longer hospital stay(P=0.016)and overall complications(P<0.01)than did those in the higher hematocrit group.The higher RDW group had a worse OS and DFS than did the lower RDW group for tumor node metastasis(TNM)stage I(OS,P<0.05;DFS,P=0.001)and stage II(OS,P=0.004;DFS,P=0.01)than the lower RDW group;the lower hematocrit group had worse OS and DFS for TNM stage II(OS,P<0.05;DFS,P=0.001)and stage III(OS,P=0.001;DFS,P=0.001)than did the higher hematocrit group.Preoperative hematocrit was an independent risk factor for OS[P=0.017,hazard ratio(HR)=1.256,95%confidence interval(CI):1.041-1.515]and DFS(P=0.035,HR=1.194,95%CI:1.013-1.408).CONCLUSION A higher preoperative RDW and lower hematocrit were associated with more postoperative complications.However,only hematocrit was an independent risk factor for OS and DFS in CRC patients who underwent radical surgery,while RDW was not.

Red cell distribution width/platelet ratio estimates the 3-year risk of decompensation in Metabolic Dysfunction-Associated Steatotic Liver Disease-induced cirrhosis

BACKGROUND For compensated advanced chronic liver disease(cACLD)patients,the first decompensation represents a dramatically worsening prognostic event.Based on the first decompensation event(DE),the transition to decompensated advanced chronic liver disease(dACLD)can occur through two modalities referred to as acute decompensation(AD)and non-AD(NAD),respectively.Clinically Significant Portal Hypertension(CSPH)is considered the strongest predictor of decompensation in these patients.However,due to its invasiveness and costs,CSPH is almost never evaluated in clinical practice.Therefore,recognizing noninvasively predicting tools still have more appeal across healthcare systems.The red cell distribution width to platelet ratio(RPR)has been reported to be an indicator of hepatic fibrosis in Metabolic Dysfunction-Associated Steatotic Liver Disease(MASLD).However,its predictive role for the decompensation has never been explored.AIM In this observational study,we investigated the clinical usage of RPR in predicting DEs in MASLD-related cACLD patients.METHODS Fourty controls and 150 MASLD-cACLD patients were consecutively enrolled and followed up(FUP)semiannually for 3 years.At baseline,biochemical,clinical,and Liver Stiffness Measurement(LSM),Child-Pugh(CP),Model for End-Stage Liver Disease(MELD),aspartate aminotransferase/platelet count ratio index(APRI),Fibrosis-4(FIB-4),Albumin-Bilirubin(ALBI),ALBI-FIB-4,and RPR were collected.During FUP,DEs(timing and modaities)were recorded.CSPH was assessed at the baseline and on DE occurrence according to the available Clinical Practice Guidelines.RESULTS Of 150 MASLD-related cACLD patients,43(28.6%)progressed to dACLD at a median time of 28.9 months(29 NAD and 14 AD).Baseline RPR values were significantly higher in cACLD in comparison to controls,as well as MELD,CP,APRI,FIB-4,ALBI,ALBI-FIB-4,and LSM in dACLD-progressing compared to cACLD individuals[all P<0.0001,except for FIB-4(P:0.007)and ALBI(P:0.011)].Receiving operator curve analysis revealed RPR>0.472 and>0.894 as the best cut-offs in the prediction respectively of 3-year first DE,as well as its superiority compared to the other non-invasive tools examined.RPR(P:0.02)and the presence of baseline-CSPH(P:0.04)were significantly and independently associated with the DE.Patients presenting baseline-CSPH and RPR>0.472 showed higher risk of decompensation(P:0.0023).CONCLUSION Altogether these findings suggest the RPR as a valid and potentially applicable non-invasive tool in the prediction of timing and modalities of decompensation in MASLD-related cACLD patients.

FPGA-based position reconstruction method for neutron beam flux spatial distribution measurement in BNCT

A new measurement method for the spatial distribution of neutron beam flux in boron neutron capture therapy(BNCT)is being developed based on the two-dimensional Micromegas detector.To address the issue of long processing times in traditional offline position reconstruction methods,this paper proposes a field programmable gate array based online position reconstruction method utilizing the micro-time projection chamber principle.This method encapsulates key technical aspects:a self-adaptive serial link technique built upon the dynamical adjustment of the delay chain length,fast sorting,a coordinate-matching technique based on the mapping between signal timestamps and random access memory(RAM)addresses,and a precise start point-merging technique utilizing a circular combined RAM.The performance test of the selfadaptive serial link shows that the bit error rate of the link is better than 10-12 at a confidence level of 99%,ensuring reliable data transmission.The experiment utilizing the readout electronics and Micromegas detector shows a spatial resolution of approximately 1.4 mm,surpassing the current method’s resolution level of 5 mm.The beam experiment confirms that the readout electronics system can obtain the flux spatial distribution of neutron beams online,thus validating the feasibility of the position reconstruction method.The online position reconstruction method avoids traditional methods,such as bubble sorting and traversal searching,simplifies the design of the logic firmware,and reduces the time complexity from O(n2)to O(n).This study contributes to the advancement in measuring neutron beam flux for BNCT.

Application of DSAPSO Algorithm in Distribution Network Reconfiguration with Distributed Generation

With the current integration of distributed energy resources into the grid,the structure of distribution networks is becoming more complex.This complexity significantly expands the solution space in the optimization process for network reconstruction using intelligent algorithms.Consequently,traditional intelligent algorithms frequently encounter insufficient search accuracy and become trapped in local optima.To tackle this issue,a more advanced particle swarm optimization algorithm is proposed.To address the varying emphases at different stages of the optimization process,a dynamic strategy is implemented to regulate the social and self-learning factors.The Metropolis criterion is introduced into the simulated annealing algorithm to occasionally accept suboptimal solutions,thereby mitigating premature convergence in the population optimization process.The inertia weight is adjusted using the logistic mapping technique to maintain a balance between the algorithm’s global and local search abilities.The incorporation of the Pareto principle involves the consideration of network losses and voltage deviations as objective functions.A fuzzy membership function is employed for selecting the results.Simulation analysis is carried out on the restructuring of the distribution network,using the IEEE-33 node system and the IEEE-69 node system as examples,in conjunction with the integration of distributed energy resources.The findings demonstrate that,in comparison to other intelligent optimization algorithms,the proposed enhanced algorithm demonstrates a shorter convergence time and effectively reduces active power losses within the network.Furthermore,it enhances the amplitude of node voltages,thereby improving the stability of distribution network operations and power supply quality.Additionally,the algorithm exhibits a high level of generality and applicability.

Federated Learning Model for Auto Insurance Rate Setting Based on Tweedie Distribution

In the assessment of car insurance claims,the claim rate for car insurance presents a highly skewed probability distribution,which is typically modeled using Tweedie distribution.The traditional approach to obtaining the Tweedie regression model involves training on a centralized dataset,when the data is provided by multiple parties,training a privacy-preserving Tweedie regression model without exchanging raw data becomes a challenge.To address this issue,this study introduces a novel vertical federated learning-based Tweedie regression algorithm for multi-party auto insurance rate setting in data silos.The algorithm can keep sensitive data locally and uses privacy-preserving techniques to achieve intersection operations between the two parties holding the data.After determining which entities are shared,the participants train the model locally using the shared entity data to obtain the local generalized linear model intermediate parameters.The homomorphic encryption algorithms are introduced to interact with and update the model intermediate parameters to collaboratively complete the joint training of the car insurance rate-setting model.Performance tests on two publicly available datasets show that the proposed federated Tweedie regression algorithm can effectively generate Tweedie regression models that leverage the value of data fromboth partieswithout exchanging data.The assessment results of the scheme approach those of the Tweedie regressionmodel learned fromcentralized data,and outperformthe Tweedie regressionmodel learned independently by a single party.

Predicting the probability distribution of Martian rocks mechanical property based on microscale rock mechanical experiments and accurate grain-based modeling

The exploration of Mars would heavily rely on Martian rocks mechanics and engineering technology.As the mechanical property of Martian rocks is uncertain,it is of utmost importance to predict the probability distribution of Martian rocks mechanical property for the success of Mars exploration.In this paper,a fast and accurate probability distribution method for predicting the macroscale elastic modulus of Martian rocks was proposed by integrating the microscale rock mechanical experiments(micro-RME),accurate grain-based modeling(AGBM)and upscaling methods based on reliability principles.Firstly,the microstructure of NWA12564 Martian sample and elastic modulus of each mineral were obtained by micro-RME with TESCAN integrated mineral analyzer(TIMA)and nanoindentation.The best probability distribution function of the minerals was determined by Kolmogorov-Smirnov(K-S)test.Secondly,based on best distribution function of each mineral,the Monte Carlo simulations(MCS)and upscaling methods were implemented to obtain the probability distribution of upscaled elastic modulus.Thirdly,the correlation between the upscaled elastic modulus and macroscale elastic modulus obtained by AGBM was established.The accurate probability distribution of the macroscale elastic modulus was obtained by this correlation relationship.The proposed method can predict the probability distribution of Martian rocks mechanical property with any size and shape samples.

The abundance,distribution,and enrichment mechanism of harmful trace elements in coals from Guizhou,Southwestern China

Coal seams can enrich a variety of harmful trace elements under specific geological conditions.The spatial distribution of harmful trace elements in coal is extremely uneven,and the distribution characteristics of each element content are different.The harmful elements released in the process of coal mining and utilization will cause serious harm to the environment and the human body.It is of great resource significance to study the geochemistry of coal that affects the enrichment and distribution characteristics of harmful trace elements.Based on the domestic and foreign literature on coal geochemistry in Guizhou published by previous investigators,this study counted 1097 sample data from 23 major coal-producing counties in Guizhou Province,systematically summarized the relevant research results of harmful trace elements in the coal of Guizhou,and revealed the overall distribution and enrichment characteristics of harmful trace elements in the coal of Guizhou.The results show that the average contents of Cd,Pb,Se,Cu,Mo,U,V,As,Hg,and Cr in coal of Guizhou are higher than those in Chinese coal and world coal.A variety of harmful trace elements in the coal of Guizhou have high background values,especially in Liupanshui,Xingyi and Qianbei coalfield.The enrichment of various harmful trace elements in the Late Permian coal in Guizhou is mainly related to the combined action of various geological and geochemical factors.The supply of terrigenous debris and sedimentary environment may be the basic background of the enrichment of harmful elements in western Guizhou,while low-temperature hydrothermal activity and volcanic ash deposition may be the main reasons for the enrichment of harmful elements in southwestern Guizhou.

A possible probe to neutron-skin thickness by fragment parallel momentum distribution in projectile fragmentation reactions

Neutron-skin thickness is a key parameter for a neutron-rich nucleus;however,it is difficult to determine.In the framework of the Lanzhou Quantum Molecular Dynamics(LQMD)model,a possible probe for the neutron-skin thickness(δ_(np))of neutron-rich ^(48)Ca was studied in the 140A MeV ^(48)Ca+^(9)Be projectile fragmentation reaction based on the parallel momentum distribution(p∥)of the residual fragments.A Fermi-type density distribution was employed to initiate the neutron density distributions in the LQMD simulations.A combined Gaussian function with different width parameters for the left side(Γ_(L))and the right side(Γ_(R))in the distribution was used to describe the p∥of the residual fragments.Taking neutron-rich sulfur isotopes as examples,Γ_(L) shows a sensitive correlation withδ_(np) of ^(48)Ca,and is proposed as a probe for determining the neutron skin thickness of the projectile nucleus.