Vector Dominance with Threshold Searchable Encryption (VDTSE) for the Internet of Things

The Internet of Medical Things(IoMT)is an application of the Internet of Things(IoT)in the medical field.It is a cutting-edge technique that connects medical sensors and their applications to healthcare systems,which is essential in smart healthcare.However,Personal Health Records(PHRs)are normally kept in public cloud servers controlled by IoMT service providers,so privacy and security incidents may be frequent.Fortunately,Searchable Encryption(SE),which can be used to execute queries on encrypted data,can address the issue above.Nevertheless,most existing SE schemes cannot solve the vector dominance threshold problem.In response to this,we present a SE scheme called Vector Dominance with Threshold Searchable Encryption(VDTSE)in this study.We use a Lagrangian polynomial technique and convert the vector dominance threshold problem into a constraint that the number of two equal-length vectors’corresponding bits excluding wildcards is not less than a threshold t.Then,we solve the problem using the proposed technique modified in Hidden Vector Encryption(HVE).This technique makes the trapdoor size linear to the number of attributes and thus much smaller than that of other similar SE schemes.A rigorous experimental analysis of a specific application for privacy-preserving diabetes demonstrates the feasibility of the proposed VDTSE scheme.

Fractal model of spontaneous imbibition in low-permeability reservoirs coupled with heterogeneity of pore seepage channels and threshold pressure

Spontaneous imbibition(SI)is an important mechanism for enhancing oil recovery in low-permeability reservoirs.Due to the strong heterogeneity,and the non-Darcy flow,the construction of SI model for lowpermeability reservoirs is extremely challenging.Commonly,traditional SI models based on single or averaged capillary tortuosity ignore the influence of heterogeneity of pore seepage channels and the threshold pressure(TP)on imbibition.Therefore,in this work,based on capillary model and fractal theory,a mathematical model of characterizing SI considering heterogeneity of pore seepage channels is established.On this basis,the threshold pressure was introduced to determine the pore radius at which the wetted phase can displace oil.The proposed new SI model was verified by imbibition experimental data.The study shows that for weakly heterogeneous cores with permeability of 0-1 m D,the traditional SI model can characterize the imbibition process relatively accurately,and the new imbibition model can increase the coefficient of determination by 1.05 times.However,traditional model has serious deviations in predicting the imbibition recovery for cores with permeability of 10-50 m D.The new SI model coupling with heterogeneity of pore seepage channels and threshold pressure effectively solves this problem,and the determination coefficient is increased from 0.344 to 0.922,which is increased by2.68 times.For low-permeability reservoirs,the production of the oil in transitional pores(0.01-0.1μm)and mesopores(0.1-1μm)significantly affects the imbibition recovery,as the research shows that when the heterogeneity of pore seepage channels is ignored,the oil recovery in transitional pores and mesopores decreases by 7.54%and 4.26%,respectively.Sensitivity analysis shows that increasing interfacial tension,decreasing contact angle,oil-water viscosity ratio and threshold pressure will increase imbibition recovery.In addition,there are critical values for the influence of these factors on the imbibition recovery,which provides theoretical support for surfactant optimization.

Chalcogenide Ovonic Threshold Switching Selector

Today’s explosion of data urgently requires memory technologies capable of storing large volumes of data in shorter time frames,a feat unattain-able with Flash or DRAM.Intel Optane,commonly referred to as three-dimensional phase change memory,stands out as one of the most promising candidates.The Optane with cross-point architecture is constructed through layering a storage element and a selector known as the ovonic threshold switch(OTS).The OTS device,which employs chalcogenide film,has thereby gathered increased attention in recent years.In this paper,we begin by providing a brief introduction to the discovery process of the OTS phenomenon.Subsequently,we summarize the key elec-trical parameters of OTS devices and delve into recent explorations of OTS materials,which are categorized as Se-based,Te-based,and S-based material systems.Furthermore,we discuss various models for the OTS switching mechanism,including field-induced nucleation model,as well as several carrier injection models.Additionally,we review the progress and innovations in OTS mechanism research.Finally,we highlight the successful application of OTS devices in three-dimensional high-density memory and offer insights into their promising performance and extensive prospects in emerging applications,such as self-selecting memory and neuromorphic computing.

Evaluation of rainfall threshold models for debris flow initiation in the Jiangjia Gully,Yunnan Province,China

Systematically determining the discriminatory power of various rainfall properties and their combinations in identifying debris flow occurrence is crucial for early warning systems.In this study,we evaluated the discriminatory power of different univariate and multivariate rainfall threshold models in identifying triggering conditions of debris flow in the Jiangjia Gully,Yunnan Province,China.The univariate models used single rainfall properties as indicators,including total rainfall(R_(tot)),rainfall duration(D),mean intensity(I_(mean)),absolute energy(Eabs),storm kinetic energy(E_(s)),antecedent rainfall(R_(a)),and maximum rainfall intensity over various durations(I_(max_dur)).The evaluation reveals that the I_(max_dur)and Eabs models have the best performance,followed by the E_(s),R_(tot),and I_(mean)models,while the D and R_(a)models have poor performances.Specifically,the I_(max_dur)model has the highest performance metrics at a 40-min duration.We used logistic regression to combine at least two rainfall properties to establish multivariate threshold models.The results show that adding D or R_(a)to the models dominated by Eabs,E_(s),R_(tot),or I_(mean)generally improve their performances,specifically when D is combined with I_(mean)or when R_(a)is combined with Eabs or E_(s).Including R_(a)in the I_(max_dur)model,it performs better than the univariate I_(max_dur)model.A power-law relationship between I_(max_dur)and R_(a)or between Eabs and R_(a)has better performance than the traditional I_(mean)–D model,while the performance of the E_(s)–R_(a)model is moderate.Our evaluation reemphasizes the important role of the maximum intensity over short durations in debris flow occurrence.It also highlights the importance of systematically investigating the role of R_(a)in establishing rainfall thresholds for triggering debris flow.Given the regional variations in rainfall patterns worldwide,it is necessary to evaluate the findings of this study across diverse watersheds.

A study of the soil water potential threshold values to trigger irrigation of ‘Shimizu Hakuto’ peach at pivotal fruit developmental stages

Water management is an important practice that affects fruit size and quality.Effective implementation of irrigation scheduling requires knowledge of the appropriate indicators and thresholds,which are established manly based on the effects of water deficits on final fruit quality.Few studies have focused on the real-time effects of water status on fruit and shoot growth.To establish soil water potential (ψ_(soil)) thresholds to trigger irrigation of peach at pivotal fruit developmental stages,photogrammetry,^(13)C labelling,and other techniques were used in this study to investigate real-time changes in stem diameter,fruit projected area,net leaf photosynthetic rate (P_(n)),and allocation of photoassimilates to fruit under soil water potential conditions ranging from saturation to stress in 6-year-old Shimizu hakuto’peach.Stem growth,fruit growth,and P_n exhibited gradually decreasing sensitivity to water deficits during fruit developmental stages I,II,and III.Stem diameter growth was significantly inhibited whenψ_(soil)dropped to-8.5,-7.6,and-5.4 k Pa,respectively.Fruit growth rate was low,reaching zero when theψ_(soil)was-9.0 to-23.1,-14.9 to-21.4,and-16.5 to-23.3 k Pa,respectively,and P_ndecreased significantly when theψ_(soil)reached-24.2,-22.7,and-20.4 kPa,respectively.In addition,more photoassimilates were allocated to fruit under moderateψ_(soil)conditions (-10.1 to-17.0 k Pa) than under otherψ_(soil)values.Our results revealed threeψ_(soil)thresholds,-10.0,-15.0,and-15.0 kPa,suitable for triggering irrigation during stages I,II,and III,respectively.These thresholds can be helpful for controlling excessive tree vigor,maintaining rapid fruit growth and leaf photosynthesis,and promoting the allocation of more photoassimilates to fruit.

Epidemic threshold influenced by non-pharmaceutical interventions in residential university environments

The control of highly contagious disease spreading in campuses is a critical challenge.In residential universities,students attend classes according to a curriculum schedule,and mainly pack into classrooms,dining halls and dorms.They move from one place to another.To simulate such environments,we propose an agent-based susceptible–infected–recovered model with time-varying heterogeneous contact networks.In close environments,maintaining physical distancing is the most widely recommended and encouraged non-pharmaceutical intervention.It can be easily realized by using larger classrooms,adopting staggered dining hours,decreasing the number of students per dorm and so on.Their real-world influence remains uncertain.With numerical simulations,we obtain epidemic thresholds.The effect of such countermeasures on reducing the number of disease cases is also quantitatively evaluated.

Impacts of proppant distribution on development of tight oil reservoirs with threshold pressure gradient

Field evidence indicates that proppant distribution and threshold pressure gradient have great impacts on well productivity.Aiming at the development of unconventional oil reservoirs in Triassic Chang-7 Unit,Ordos Basin of China,we presented an integrated workflow to investigate how(1)proppant placement in induced fracture and(2)non-linear flow in reservoir matrix would affect well productivity and fluid flow in the reservoir.Compared with our research before(Yue et al.,2020),here we extended this study into the development of multi-stage fractured horizontal wells(MFHWs)with large-scale complicated fracture geometry.The integrated workflow is based on the finite element method and consists of simulation models for proppant-laden fluid flow,fracture flow,and non-linear seepage flow,respectively.Simulation results indicate that the distribution of proppant inside the induced cracks significantly affects the productivity of the MFHW.When we assign an idealized proppant distribution instead of the real distribution,there will be an overestimation of 44.98%in daily oil rate and 30.63%in cumulative oil production after continuous development of 1000 days.Besides,threshold pressure gradient(TPG)also significantly affects the well performance in tight oil reservoirs.If we simply apply linear Darcy’s law to the reservoir matrix,the overall cumulative oil production can be overrated by 77%after 1000 days of development.In general,this research provides new insights into the development of tight oil reservoirs with TPG and meanwhile reveals the significance of proppant distribution and non-linear fluid flow in the production scenario design.

Vehicle Abnormal Behavior Detection Based on Dense Block and Soft Thresholding

With the rapid advancement of social economies,intelligent transportation systems are gaining increasing atten-tion.Central to these systems is the detection of abnormal vehicle behavior,which remains a critical challenge due to the complexity of urban roadways and the variability of external conditions.Current research on detecting abnormal traffic behaviors is still nascent,with significant room for improvement in recognition accuracy.To address this,this research has developed a new model for recognizing abnormal traffic behaviors.This model employs the R3D network as its core architecture,incorporating a dense block to facilitate feature reuse.This approach not only enhances performance with fewer parameters and reduced computational demands but also allows for the acquisition of new features while simplifying the overall network structure.Additionally,this research integrates a self-attentive method that dynamically adjusts to the prevailing traffic conditions,optimizing the relevance of features for the task at hand.For temporal analysis,a Bi-LSTM layer is utilized to extract and learn from time-based data nuances.This research conducted a series of comparative experiments using the UCF-Crime dataset,achieving a notable accuracy of 89.30%on our test set.Our results demonstrate that our model not only operates with fewer parameters but also achieves superior recognition accuracy compared to previous models.

The Toxic Effects of Strong Chlorin Disinfectant on Mangroves and Emission Thresholds

In this study, based on the simulated discharge results of chemical disinfectants, hypocotyl germination concentration gradient pre-test and concentration gradient determination experiment were set up respectively. Laboratory cultivation was conducted to compare and analyze the root germination and germination indexes, three mangrove hypocotyls of Kandelia candel (Linn.) Druce, Ceriopstagal C.B. Rob. and Bruguiera sexangula var. Rhynchopetalas’ efficiency of cumulative root germination, cumulative germination and the cumulative expansion of the second pair of leaves, one-way analysis of variance was used to obtain the tolerance threshold of three mangrove hypocotyls to strong chlorin disinfectant. The study determined that the by-products of strong chlorin disinfectant, the toxic threshold concentrations of Kandelia candel (Linn.) Druce, Ceriopstagal C.B. Rob. and Bruguiera sexangula var. rhynchopetala are close to 0.55 mg/L, 0.55 mg/L and 0.25 mg/L, respectively. This concentration range is lower than the average concentration of 1.183 mg/L of active chlorine emitted from strong chlorine concentrate during pond clearing in high-level shrimp ponds, indicating that transient emissions of strong chlorine concentrate during pond clearing can have a toxic effect on mangrove plants. The strength of tolerance of the embryonic axes of the three mangrove species to effective chlorine contamination was, Ceriopstagal C.B. Rob. stronger than Bruguiera sexangula var. rhynchopetala, and Kandelia candel (Linn.) Druce is the weakest.

CT Thresholds for Spinal Bone Mineral Attenuation to Prioritize Eligible Older Women for Osteoporosis Screening

Introduction: Computed tomography (CT) measurements of bone mineral attenuation may be a useful means to identify older women who should be prioritized for bone mineral density screening. Methods: We compared bone mineral attenuation as measured in the L1 vertebra of CT studies to the results of dual-energy x-ray absorptiometry (DEXA) studies to determine what CT attenuation thresholds might yield a reasonable combination of sensitivity and specificity for the detection of osteoporosis. The study was limited to women between the ages of 65 and 75 years who had a DEXA study and a CT that included the L1 or adjacent vertebra performed within 3 years of the DEXA study. Results: There were 1226 women in this study, of whom 452 (38%) had osteoporosis based on a T-score ≤ −2.5 by DEXA. There were 830 CT studies performed with contrast and 396 studies which were performed without contrast. There was a statistically significant difference in the mean HU of those studies performed without contrast compared to those with contrast (unenhanced mean 103 HU versus 125 HU, p < 0.001). Different CT attenuation thresholds provided the most appropriate combination of sensitivity and specificity for the detection of osteoporosis when comparing CT studies performed without or with IV contrast and when all the CT data were used in aggregate. Conclusion: Different thresholds appear necessary when using the mean CT vertebral attenuation to identify older women for preferential referral for DEXA studies.

Impact of digital economy development on carbon productivity:An empirical analysis based on threshold effect and spatial spillover effect

Utilizing provincial panel data from 2014 to 2020,this study employs a fixed effect model,a threshold effect model,and a spatial lag model to empirically examine the correlation between digital economic development and carbon productivity.The findings indicate that digital economic development significantly contributes to the enhancement of carbon productivity in the long term.Furthermore,through instrumental variable method,replacement of explanatory variables and other methods to test its endogeneity and stability,the results remain robust.In terms of regional heterogeneity,the impact of digital economic development on carbon productivity is less pronounced in the central and western regions compared to the eastern region.Additionally,further investigation reveals that industrial structure upgrading and science and technology investment level exhibit different threshold effects on the influence of digital economy development level on carbon productivity.Moreover,there is a significant spatial spillover effect of digital economy development on carbon productivity with H-H and L-L agglomeration spatial correlation.

Research on the Impact of China’s Foreign Trade Technology Spillover on Green Total Factor Productivity of Countries Along the“Belt and Road”:Based on the Institutional Quality Threshold Effect

China’s growing trade with countries along the“Belt and Road”Initiative is accompanied by a focus on green development.Based on the panel data from 2007 to 2018,this paper establishes a threshold regression model to empirically analyze the institutional quality threshold effect of China’s foreign trade technology spillover on the GTFP of countries along the“Belt and Road.”The results show that China’s foreign trade technology spillover has a significant institutional quality double threshold effect on the green total factor productivity of the countries along the“Belt and Road.”As the institutional quality of the countries along the“Belt and Road”crosses a specific threshold value,the impact of China’s foreign trade technology spillover on the green total factor productivity of the countries along the“Belt and Road”has a significant positive promoting effect,and corresponding suggestions are put forward.

An Information Entropy-Based Methodology to Construct the Avulsion Threshold in the Tail Reach of the Estuarine Alluvial Plain

Channel avulsion is a natural phenomenon that occurs abruptly on alluvial river deltas,which can affect the channel stability.The causes for avulsion could be generally categorized as topography-and flood-driven factors.However,previous studies on avulsion thresholds usually focused on topography-driven factors due to the centurial or millennial avulsion timescales of the world’s most deltas,but neglected the impacts of flood-driven factors.In the current study,a novel demarcation equation including the two driven factors was proposed,with the decadal timescale of avulsion being considered in the Yellow River Estuary(YRE).In order to quantify the contributions of different factors in each category,an entropy-based methodology was used to calculate the contributing weights of these factors.The factor with the highest weight in each category was then used to construct the demarcation equation,based on avulsion datasets associated with the YRE.An avulsion threshold was deduced according to the demarcation equation.This avulsion threshold was then applied to conduct the risk assessment of avulsion in the YRE.The results show that:two dominant factors cover respectively geomorphic coefficient representing the topography-driven factor and fluvial erosion intensity representing the flood-driven factor,which were thus employed to define a two dimensional mathematical space in which the demarcation equation can be obtained;the avulsion threshold derived from the equation was also applied in the risk assessment of avulsion;and the avulsion threshold proposed in this study is more accurate,as compared with the existing thresholds.

Improved quantum(t,n)threshold group signature

Threshold signature is an important branch of the digital signature scheme,which can distribute signature rights and avoid the abuse of signature rights.With the continuous development of quantum computation and quantum information,quantum threshold signatures are gradually becoming more popular.Recently,a quantum(t,n)threshold group signature scheme was analyzed that uses techniques such as quantum-controlled-not operation and quantum teleportation.However,this scheme cannot resist forgery attack and does not conform to the design of a threshold signature in the signing phase.Based on the original scheme,we propose an improved quantum(t,n)threshold signature scheme using quantum(t,n)threshold secret sharing technology.The analysis proves that the improved scheme can resist forgery attack and collusion attack,and it is undeniable.At the same time,this scheme reduces the level of trust in the arbitrator during the signature phase.

Volatile threshold switching memristor:An emerging enabler in the AIoT era

With rapid advancement and deep integration of artificial intelligence and the internet-of-things,artificial intelligence of things has emerged as a promising technology changing people’s daily life.Massive growth of data generated from the devices challenges the AIoT systems from information collection,storage,processing and communication.In the review,we introduce volatile threshold switching memristors,which can be roughly classified into three types:metallic conductive filament-based TS devices,amorphous chalcogenide-based ovonic threshold switching devices,and metal-insulator transition based TS devices.They play important roles in high-density storage,energy efficient computing and hardware security for AIoT systems.Firstly,a brief introduction is exhibited to describe the categories(materials and characteristics)of volatile TS devices.And then,switching mechanisms of the three types of TS devices are discussed and systematically summarized.After that,attention is focused on the applications in 3D cross-point memory technology with high storage-density,efficient neuromorphic computing,hardware security(true random number generators and physical unclonable functions),and others(steep subthreshold slope transistor,logic devices,etc.).Finally,the major challenges and future outlook of volatile threshold switching memristors are presented.

Chest computed tomography findings of the Omicron variants of SARS-CoV-2 with different cycle threshold values

BACKGROUND The Omicron variant of severe acute respiratory syndrome coronavirus 2(SARSCoV-2)mainly infects the upper respiratory tract.This study aimed to determine whether the probability of pulmonary infection and the cycle threshold(Ct)measured using the fluorescent polymerase chain reaction(PCR)method were related to pulmonary infections diagnosed via computed tomography(CT).AIM To analyze the chest CT signs of SARS-CoV-2 Omicron variant infections with different Ct values,as determined via PCR.METHODS The chest CT images and PCR Ct values of 331 patients with SARS-CoV-2Omicron variant infections were retrospectively collected and categorized into low(<25),medium(25.00-34.99),and high(≥35)Ct groups.The characteristics of chest CT images in each group were statistically analyzed.RESULTS The PCR Ct values ranged from 13.36 to 39.81,with 99 patients in the low,155 in the medium,and 77 in the high Ct groups.Six abnormal chest CT signs were detected,namely,focal infection,patchy consolidation shadows,patchy groundglass shadows,mixed consolidation ground-glass shadows,subpleural interstitial changes,and pleural changes.Focal infections were less frequent in the low Ct group than in the medium and high Ct groups;these infections were the most common sign in the medium and high Ct groups.Patchy consolidation shadows and pleural changes were more frequent in the low Ct group than in the other two groups.The number of patients with two or more signs was greater in the low Ct group than in the medium and high Ct groups.CONCLUSION The chest CT signs of patients with pulmonary infection caused by the Omicron variants of SARSCoV-2 varied depending on the Ct values.Identification of the characteristics of Omicron variant infection can help subsequent planning of clinical treatment.

Remaining useful life prediction of aero-engines based on random-coefficient regression model considering random failure threshold

Remaining useful life(RUL)prediction is one of the most crucial components in prognostics and health management(PHM)of aero-engines.This paper proposes an RUL prediction method of aero-engines considering the randomness of failure threshold.Firstly,a random-coefficient regression(RCR)model is used to model the degradation process of aeroengines.Then,the RUL distribution based on fixed failure threshold is derived.The prior parameters of the degradation model are calculated by a two-step maximum likelihood estimation(MLE)method and the random coefficient is updated in real time under the Bayesian framework.The failure threshold in this paper is defined by the actual degradation process of aeroengines.After that,a expectation maximization(EM)algorithm is proposed to estimate the underlying failure threshold of aeroengines.In addition,the conditional probability is used to satisfy the limitation of failure threshold.Then,based on above results,an analytical expression of RUL distribution of aero-engines based on the RCR model considering random failure threshold(RFT)is derived in a closed-form.Finally,a case study of turbofan engine is used to demonstrate the effectiveness and superiority of the RUL prediction method and the parameters estimation method of failure threshold proposed.

Critical thresholds for stage division of water erosion process in different ridge systems in mollisol region of Northeast China

Extreme rainfall events on a slope under ridge tillage systems cause concentrated stream soil loss.To analyse the critical thresholds for different stages of water erosion process of ridge systems,simulated rainfall-erosion experiments for the contour wide ridge(CWR),contour narrow ridge(CNR),longitudinal wide ridge(LWR),and longitudinal narrow ridge(LNR)were conducted under four rainfall intensities,with slope gradients of 3°and 5°.For the runoff event,the runoff depth order was LNR>LWR>CWR>CNR;the soil loss order was CNR>LNR>CWR>LWR.The product of slope factor(S)and rainfall erosivity(R)or runoff depth(D),can be adopted as critical thresholds for different stages of runoff and soil erosion process.For the longitudinal ridge systems,R values were provided for LWR and LNR and were the beginning of sheet flow,whereas the product of rainfall erosivity and slope factor(RS)values were provided for LWR and LNR as the beginning of the accelerated concentrated flow.For the contour ridge systems,R values were provided for CWR and CNR as critical thresholds for the beginning of overflow.The product of runoff depth and slope factor(DS)values were 9.98 and 7.73 mm for CWR and CNR,respectively,and were critical thresholds for the beginning of ridge failure;the DS values were 18.45 and 12.75 mm for CWR and CNR,respectively,and were critical thresholds for the beginning of the formation of ephemeral gully erosion.The critical thresholds can distinguish different stages of soil erosion process modelling.

Threshold-type memristor-based crossbar array design and its application in handwritten digit recognition

Neuromorphic computing simulates the operation of biological brain function for information processing and can potentially solve the bottleneck of the Von Neumann architecture.Inspired by the real characteristics of physical memristive devices,we propose a threshold-type nonlinear voltage-controlled memristor mathematical model which is used to design a novel memristor-based crossbar array.The presented crossbar array can simulate the synaptic weight in real number field rather than only positive number field.Theoretical analysis and simulation results of a 2×2 image inversion operation validate the feasibility of the proposed crossbar array and the necessary training and inference functions.Finally,the presented crossbar array is used to construct the neural network and then applied in the handwritten digit recognition.The Mixed National Institute of Standards and Technology(MNIST)database is adopted to train this neural network and it achieves a satisfactory accuracy.

Deformation critical threshold estimation of Xiaowan ultrahigh arch dam with time-varying grey model

The structural behavior of the Xiaowan ultrahigh arch dam is primarily influenced by external loads and time-varying characteristics of dam concrete and foundation rock mass during long-term operation. According to overload testing with a geological model and the measured time series of installed perpendicular lines, the space and time evolution characteristics of the arch dam structure were analyzed, and its mechanical performance was evaluated. Subsequently, the deformation centroid of the deflective curve was suggested to indicate the magnitude and unique distribution rules for a typical dam section using the measured deformation values at multi-monitoring points. The ellipse equations of the critical ellipsoid for the centroid were derived from the historical measured time series. Hydrostatic and seasonal components were extracted from the measured deformation values with a traditional statistical model, and residuals were adopted as a grey component. A time-varying grey model was developed to accurately predict the evolution of the deformation behavior of the ultrahigh arch dam during future operation. In the developed model, constant coefficients were modified so as to be time-dependent functions, and the prediction accuracy was significantly improved through introduction of a forgetting factor. Finally, the critical threshold was estimated, and predicted ellipsoids were derived for the Xiaowan arch dam. The findings of this study can provide technical support for safety evaluation of the actual operation of ultrahigh arch dams and help to provide early warning of abnormal changes.