Optimal investment based on relative performance and weighted utility

This paper studies the optimal portfolio allocation of a fund manager when he bases decisions on both the absolute level of terminal relative performance and the change value of terminal relative performance comparison to a predefined reference point. We find the optimal investment strategy by maximizing a weighted average utility of a concave utility and an Sshaped utility via a concavification technique and the martingale method. Numerical results are carried out to show the impact of the extent to which the manager pays attention to the change of relative performance related to the reference point on the optimal terminal relative performance.

EOS Utility软件在摄影理论可视化教学中的应用

可视化的理论知识更容易被识记、理解,而在摄影理论教学中,运用静态的图形图像,并不能理想地将复杂理论知识及其相互间的关系表征、可视化。运用EOS Utility软件进行摄影理论知识的辅助教学,可将各知识点内涵及其相互间的关系进行动态地表征,实现摄影参数可视化、摄影过程可视化、摄影效果可视化,使摄影知识点及其相互间的关系更容易被识记、理解,提高教学效率。

THE OPTIMAL REINSURANCE-INVESTMENT PROBLEM CONSIDERING THE JOINT INTERESTS OF AN INSURER AND A REINSURER UNDER HARA UTILITY

This paper focuses on an optimal reinsurance and investment problem for an insurance corporation which holds the shares of an insurer and a reinsurer.Assume that the insurer can purchase reinsurance from the reinsurer,and that both the insurer and the reinsurer are allowed to invest in a risk-free asset and a risky asset which are governed by the Heston model and are distinct from one another.We aim to find the optimal reinsuranceinvestment strategy by maximizing the expected Hyperbolic Absolute Risk Aversion(HARA)utility of the insurance corporation’s terminal wealth,which is the weighted sum of the insurer’s and the reinsurer’s terminal wealth.The Hamilton-Jacobi-Bellman(HJB)equation is first established.However,this equation is non-linear and is difficult to solve directly by any ordinary method found in the existing literature,because the structure of this HJB equation is more complex under HARA utility.In the present paper,the Legendre transform is applied to change this HJB equation into a linear dual one such that the explicit expressions of optimal investment-reinsurance strategies for-1≤ρi≤1 are obtained.We also discuss some special cases in a little bit more detail.Finally,numerical analyses are provided.

High Utility Periodic Frequent Pattern Mining in Multiple Sequences

Periodic patternmining has become a popular research subject in recent years;this approach involves the discoveryof frequently recurring patterns in a transaction sequence. However, previous algorithms for periodic patternmining have ignored the utility (profit, value) of patterns. Additionally, these algorithms only identify periodicpatterns in a single sequence. However, identifying patterns of high utility that are common to a set of sequencesis more valuable. In several fields, identifying high-utility periodic frequent patterns in multiple sequences isimportant. In this study, an efficient algorithm called MHUPFPS was proposed to identify such patterns. To addressexisting problems, three new measures are defined: the utility, high support, and high-utility period sequenceratios. Further, a new upper bound, upSeqRa, and two new pruning properties were proposed. MHUPFPS usesa newly defined HUPFPS-list structure to significantly accelerate the reduction of the search space and improvethe overall performance of the algorithm. Furthermore, the proposed algorithmis evaluated using several datasets.The experimental results indicate that the algorithm is accurate and effective in filtering several non-high-utilityperiodic frequent patterns.

Temporal Preferences-Based Utility Control for Smart Homes

The residential sector contributes a large part of the energy to the global energy balance.To date,housing demand has mostly been uncontrollable and inelastic to grid conditions.Analyzing the performance of a home energy manage-ment system requires the creation of various profiles of real-world residential demand,as residential demand is complex and includes multiple factors such as occupancy,climate,user preferences,and appliance types.Average Peak Ratio(A2P)is one of the most important parameters when managing an efficient and cost-effective energy system.At the household level,the larger relative magni-tudes of certain energy devices make managing this ratio critical,albeit difficult.Various Demand Response(DR)and Demand Side Management(DSM)systems have been proposed to reduce this ratio to 1.The main ways to achieve this are economic incentives,user comfort modeling and control,or preference-based.In this study,we propose a unique opportunistic social time approach called the Time Utility Based Control Feature(TUBCF),which uses the concept of a utility function from economics to model and control consumer devices.We propose a DR model for residential customers to reduce Peak-to-Average Ratio(PAR)and improve customer satisfaction by eliminating Appliance Wait Time(WTA)during peak periods.For PAR reduction and WTA,we propose a system architecture and mathematical formulation.Our proposed model automatically schedules devices based on their temporal preferences and considers six households with different device types and operational characteristics.Simulation results show that using this strategy can reduce A2P by 80%and improve user comfort during peak hours.

Data-Driven Model for Risk Assessment of Cable Fire in Utility Tunnels Using Evidential Reasoning Approach

Cable fire is one of the most important events for operation and maintenance(O&M)safety in underground utility tunnels(UUTs).Since there are limited studies about cable fire risk assessment,a comprehensive assessment model is proposed to evaluate the cable fire risk in different UUT sections and improve O&M efficiency.Considering the uncertainties in the risk assessment,an evidential reasoning(ER)approach is used to combine quantitative sensor data and qualitative expert judgments.Meanwhile,a data transformation technique is contributed to transform continuous data into a five-grade distributed assessment.Then,a case study demonstrates how the model and the ER approach are established.The results show that in Shenzhen,China,the cable fire risk in District 8,B Road is the lowest,while more resources should be paid in District 3,C Road and District 25,C Road,which are selected as comparative roads.Based on the model,a data-driven O&M process is proposed to improve the O&M effectiveness,compared with traditional methods.This study contributes an effective ER-based cable fire evaluation model to improve the O&M efficiency of cable fire in UUTs.

Entrepreneur Education Level and Its Utility Maximization

The education level of entrepreneurs plays an important role in the decision-making process of loan financing. In this paper, the research method of optimization theory is used to study the problem of the education level and maximizing utility of entrepreneurs, and the optimal analytic solution is obtained. On this basis, the influence of the change of bank loan interest rate, the marginal effect of entrepreneur’s effort, the marginal effect of entrepreneur’s investment, the elastic coefficient of entrepreneur’s effort and the elastic coefficient of entrepreneur’s investment on the optimal solution of entrepreneur’s effort and investment amount is discussed.

SPI软件Import Utility模块在仪表数字化交付中的应用

为满足仪表数字化交付要求,基于Smart Plant Instrumentation(SPI)软件Import Utility导入模块的使用,对数字化交付这项内容采用的主要解决方法和主要流程进行了阐述,提出了在前期设计未使用SPI软件的情况下,设计院如何满足业主数字化交付的需求。

Understanding Expected Utility for Decision Making

In this paper,we present a brief version of de Finetti-Ramsey’s subjective probability theory and provide a rigorous yet intuitively plausible explanation of expected utility using elementary mathematics.In a final section,we take up the case of some“Paradoxes in Expected Utility Theory”and try to reconcile them with the help of subjective probabilities.

Utility Impact below Bridge or Culvert Soffit on Open Channel Flow

The background to this research was a flooding incident that occurred in Bridgend, Co. Donegal, Ireland in August 2017. While several properties were flooded, a flooding case study of a single dwelling house adjacent to the Bridgend River at Riverdale, Bunamayne, Co. Donegal, Ireland is used herein. For this study the flooded site shall be referred to as the “Hegarty property”. A structure in the form of a stone arched culvert is located directly adjacent to the two-storey detached dwelling house on the Hegarty Property. While the culvert is referred to locally as a bridge, within this research the word culvert will be used in connection with the structure. The culvert has a concrete surrounded utility (watermain) crossing at a gradient below the culvert soffit on the upstream face of the structure. The utility obstructed flow through the culvert and contributed to the flooding event. Given the implication of climate change and the increased probability of more extreme flooding events, it was decided to explore the case study to ascertain the factors that contribute to flooding events when utilities are positioned at culvert or bridge structures. This work was completed to assist undergraduate students, researchers, and local authorities in a relatively unknown area of flood causation.

基于Python对Intergraph Smart^(■) 3D Bulkload Utility的重新设计与实现

海克斯康的Smart 3D作为近20年来出现的先进的三维工厂设计软件,凭借其面向数据库、设计规则驱动等特点,简化了工程设计过程,深受用户喜爱,在流程行业中应用广泛。绝大多数使用过该软件进行工程设计的管理员与材料人员都对其配套工具Bulkload Utility(以下简称“Bulkload”)不陌生。作为官方提供的唯一具有图形用户界面的参考数据库(Catalog Database)导入工具,Bulkload在整个工程设计过程中都发挥着至关重要的作用。

Study on Gas Explosion Characteristics in Urban Utility Tunnels

In order to study the effects of three factors,namely,premixed gas concentration,number of pressure relief ports and number of obstacles,on the overpressure characteristics of gas explosion and flame structure of gas chambers in utility tunnels,in this paper,a small and narrow experimental platform for gas explosion was constructed to study the evolution mechanism and law of the kinetic characteristics and flame behavior of gas explosion in utility tunnels,with a view to revealing the special influencing mechanism of the overpressure characteristics and flame behavior of gas explosion in utility tunnels.The results show that in the methane concentration of 9.5%when the explosion overpressure reaches its peak,and at the same time by the utility tunnel long and narrow restricted space,the explosion generated by the precursor shock wave along with the flame compression wave were superimposed on both ends of the pipeline back and forth for many times so that the overpressure waveforms are cyclic oscillatory trend,increasing the explosion hazards;compared with the closed conditions,the relief port on the overpressure characteristics of the significant impact of the maximum decrease of 57.7%,when the frequency of overpressure oscillation is reduced,the gas explosion generated by the overpressure damage is reduced;the presence of obstacles significantly affects the flow field,accelerates the flame propagation and leads to greater overpressure peaks and overpressure oscillations.The conclusions of the study can provide a basis for the safety of natural gas in utility tunnels.

Structural properties of residual carbon in coal gasification fine slag and their influence on flotation separation and resource utilization:A review

Coal gasification fine slag(FS)is a typical solid waste generated in coal gasification.Its current disposal methods of stockpil-ing and landfilling have caused serious soil and ecological hazards.Separation recovery and the high-value utilization of residual carbon(RC)in FS are the keys to realizing the win-win situation of the coal chemical industry in terms of economic and environmental benefits.The structural properties,such as pore,surface functional group,and microcrystalline structures,of RC in FS(FS-RC)not only affect the flotation recovery efficiency of FS-RC but also form the basis for the high-value utilization of FS-RC.In this paper,the characteristics of FS-RC in terms of pore structure,surface functional groups,and microcrystalline structure are sorted out in accordance with gasification type and FS particle size.The reasons for the formation of the special structural properties of FS-RC are analyzed,and their influence on the flotation separation and high-value utilization of FS-RC is summarized.Separation methods based on the pore structural characterist-ics of FS-RC,such as ultrasonic pretreatment-pore-blocking flotation and pore breaking-flocculation flotation,are proposed to be the key development technologies for improving FS-RC recovery in the future.The design of low-cost,low-dose collectors containing polar bonds based on the surface and microcrystalline structures of FS-RC is proposed to be an important breakthrough point for strengthening the flotation efficiency of FS-RC in the future.The high-value utilization of FS should be based on the physicochemical structural proper-ties of FS-RC and should focus on the environmental impact of hazardous elements and the recyclability of chemical waste liquid to es-tablish an environmentally friendly utilization method.This review is of great theoretical importance for the comprehensive understand-ing of the unique structural properties of FS-RC,the breakthrough of the technological bottleneck in the efficient flotation separation of FS,and the expansion of the field of the high value-added utilization of FS-RC.

From prediction to prevention:Machine learning revolutionizes hepatocellular carcinoma recurrence monitoring

In this editorial,we comment on the article by Zhang et al entitled Development of a machine learning-based model for predicting the risk of early postoperative recurrence of hepatocellular carcinoma.Hepatocellular carcinoma(HCC),which is characterized by high incidence and mortality rates,remains a major global health challenge primarily due to the critical issue of postoperative recurrence.Early recurrence,defined as recurrence that occurs within 2 years posttreatment,is linked to the hidden spread of the primary tumor and significantly impacts patient survival.Traditional predictive factors,including both patient-and treatment-related factors,have limited predictive ability with respect to HCC recurrence.The integration of machine learning algorithms is fueled by the exponential growth of computational power and has revolutionized HCC research.The study by Zhang et al demonstrated the use of a groundbreaking preoperative prediction model for early postoperative HCC recurrence.Challenges persist,including sample size constraints,issues with handling data,and the need for further validation and interpretability.This study emphasizes the need for collaborative efforts,multicenter studies and comparative analyses to validate and refine the model.Overcoming these challenges and exploring innovative approaches,such as multi-omics integration,will enhance personalized oncology care.This study marks a significant stride toward precise,efficient,and personalized oncology practices,thus offering hope for improved patient outcomes in the field of HCC treatment.

Differentially Private Support Vector Machines with Knowledge Aggregation

With the widespread data collection and processing,privacy-preserving machine learning has become increasingly important in addressing privacy risks related to individuals.Support vector machine(SVM)is one of the most elementary learning models of machine learning.Privacy issues surrounding SVM classifier training have attracted increasing attention.In this paper,we investigate Differential Privacy-compliant Federated Machine Learning with Dimensionality Reduction,called FedDPDR-DPML,which greatly improves data utility while providing strong privacy guarantees.Considering in distributed learning scenarios,multiple participants usually hold unbalanced or small amounts of data.Therefore,FedDPDR-DPML enables multiple participants to collaboratively learn a global model based on weighted model averaging and knowledge aggregation and then the server distributes the global model to each participant to improve local data utility.Aiming at high-dimensional data,we adopt differential privacy in both the principal component analysis(PCA)-based dimensionality reduction phase and SVM classifiers training phase,which improves model accuracy while achieving strict differential privacy protection.Besides,we train Differential privacy(DP)-compliant SVM classifiers by adding noise to the objective function itself,thus leading to better data utility.Extensive experiments on three high-dimensional datasets demonstrate that FedDPDR-DPML can achieve high accuracy while ensuring strong privacy protection.

OsNPF3.1,a nitrate,abscisic acid and gibberellin transporter gene,is essential for rice tillering and nitrogen utilization efficiency

Low-affinity nitrate transporter genes have been identified in subfamilies 4-8 of the rice nitrate transporter 1(NRT1)/peptide transporter family(NPF),but the OsNPF3 subfamily responsible for nitrate and phytohormone transport and rice growth and development remains unknown.In this study,we described OsNPF3.1 as an essential nitrate and phytohormone transporter gene for rice tillering and nitrogen utilization efficiency(NUtE).OsNPF3.1 possesses four major haplotypes of its promoter sequence in 517 cultivars,and its expression is positively associated with tiller number.Its expression was higher in the basal part,culm,and leaf blade than in other parts of the plant,and was strongly induced by nitrate,abscisic acid(ABA)and gibberellin 3(GA_3)in the root and shoot of rice.Electrophysiological experiments demonstrated that OsNPF3.1 is a pH-dependent low-affinity nitrate transporter,with rice protoplast uptake assays showing it to be an ABA and GA_3 transporter.OsNPF3.1 overexpression significantly promoted ABA accumulation in the roots and GA accumulation in the basal part of the plant which inhibited axillary bud outgrowth and rice tillering,especially at high nitrate concentrations.The NUtE of OsNPF3.1-overexpressing plants was enhanced under low and medium nitrate concentrations,whereas the NUtE of OsNPF3.1 clustered regularly interspaced short palindromic repeats(CRISPR)plants was increased under high nitrate concentrations.The results indicate that OsNPF3.1 transports nitrate and phytohormones in different rice tissues under different nitrate concentrations.The altered OsNPF3.1 expression improves NUtE in the OsNPF3.1-overexpressing and CRISPR lines at low and high nitrate concentrations,respectively.

The 2024 Compendium of Physical Activities and its expansion

First developed 30 years ago,the Compendium of Physical Activities(Compendium)was created to provide a standardized way of measuring and classifying specific physical activities(PAs),allowing researchers and health professionals to assess the energy expenditure and health benefits associated with different PA.1Since its inception,the Compendium has been widely utilized and recognized as a fundamental PA and health resource.

Spinal intradural electrodes: opportunities, challenges and translation to the clinic

Damage to the spinal cord disrupts the electrically active nerve cells which normally transmit afferent and efferent signals,resulting in loss of motor,sensory,and autonomic functions.Potential treatments for spinal cord injury utilizing implanted spinal electrodes can be broadly classified into three different categories.The first of these approaches is“spinal stimulation”where electrodes,usually positioned above the level of injury,provide electrical stimulation to target and disrupt pain signals before they reach the brain.The second approach uses“activity-dependent neuro-technologies”,in which electrodes positioned below the level of injury initiate a complex spatiotemporal pattern of stimulation at the lumbar spinal cord to generate a walking gait in the limbs(Minev et al.,2015;Wagner et al.,2018).

New Second-Level-Discrete Zeroing Neural Network for Solving Dynamic Linear System

Dear Editor,This letter deals with a new second-level-discretization method with higher precision than the traditional first-level-discretization method.Specifically,the traditional discretization method utilizes the first-order time derivative information,and it is termed first-level-discretization method.By contrast,the new discretization method not only utilizes the first-order time derivative information,but also makes use of the second-order derivative information.By combining the new second-level-discretization method with zeroing neural network(ZNN),the second-level-discrete ZNN(SLDZNN)model is proposed to solve dynamic(i.e.,time-variant or time-dependent)linear system.Numerical experiments and application to angle-of-arrival(AoA)localization show the effectiveness and superiority of the SLDZNN model.

Could near infrared spectroscopy be the new weapon in our understanding of the cerebral and muscle microvascular oxygen demand during exercise?

Near-infrared spectroscopy(NIRS)has been increasingly utilized in both sport and health sciences to assess various physiological parameters related to exercise performance.1 NIRS methods coupled with the recent development of portable and wearable devices suitable for field-based measurements have revolutionized the study of exercise physiology and the determinants of exercise performance by providing real-time,non-invasive,and spatially localized measurements of tissue oxygenation dynamics.