Prognostic and recurrent significance of SII in patients with pancreatic head cancer undergoing pancreaticoduodenectomy

BackgroundTo investigate the clinical significance of preoperative inflammatory status in patients with pancreatic head carcinoma (PHC), we performed a single-center study to assess it.MethodWe studied a total of 164 patients with PHC undergoing PD surgery (with or without allogeneic venous replacement) from January 2018 to April 2022. Systemic immune-inflammation index (SII) was the most important peripheral immune index in predicting the prognosis according to XGBoost analysis. The optimal cutoff value of SII for OS was calculated according to Youden index based on the receiver operating characteristic (ROC) curve and the cohort was divided into Low SII group and High SII group. Demographic, clinical data, laboratory data, follow-up data variables were obtained and compared between the two groups. Kaplan-Meier curves, univariable and multivariable Cox regression models were used to determine the association between preoperative inflammation index, nutritional index and TNM staging system with OS and DFS respectively.ResultsThe median follow-up time was 16 months (IQR 23), and 41.4% of recurrences occurred within 1 year. The cutoff value of SII was 563, with a sensitivity of 70.3%, and a specificity of 60.7%. Peripheral immune status was different between the two groups. Patients in High SII group had higher PAR, NLR than those in Low SII group (P <0.01, <0.01, respectively), and lower PNI (P <0.01). Kaplan–Meier analysis showed significantly poorer OS and DFS (P < 0.001, <0.001, respectively) in patients with high SII. By using the multivariable Cox regression model, high SII (HR, 2.056; 95% CI, 1.082–3.905, P=0.028) was significant predictor of OS. Of these 68 high-risk patients who recurrence within one year, patients with widespread metastasis had lower SII and worse prognosis (P <0.01).ConclusionHigh SII was significantly associated with poor prognosis in patients with PHC. However, in patients who recurrence within one year, SII was lower in patients at TNM stage III. Thus, care needs to be taken to differentiate those high-risk patients

Single-pass transformation of syngas into ethanol with high selectivity by triple tandem catalysis

乙醇既可作为替代燃料或优质汽油添加剂亦是重要基础化学品，同时也是一种理想的氢载体。乙醇需求量近年增长迅速，我国需求缺口巨大，当前合成气合成乙醇有三种方法，其中直接法因在同一催化剂上存在多种反应通道，导致产物选择性不超过60%。另一方面，多步法路线虽然较为成熟，但因反应和分离/纯化步骤多，存在成本贵、能耗高等问题。发展合成气直接制乙醇的新方法和新路线具有重大意义。王野课题组在C1化学领域率先提出以接力催化控制反应选择性的新方法，并在合成气高选择性制备液体燃料、低碳烯烃和芳烃等方面取得成功。该工作是在王野教授、张庆红教授共同指导下完成的。醇醚酯化工清洁生产国家工程实验室高工康金灿、2018级博士生何顺和2017级博士生周伟为论文共同第一作者。陈明树教授课题组在原位红外、准原位XPS等表征中给予了支持，南京大学彭路明教授课题组在固体核磁表征方面提供了帮助。Synthesis of ethanol from non-petroleum carbon resources via syngas (a mixture of H2 and CO) is an important but challenging research target. The current conversion of syngas to ethanol suffers from low selectivity or multiple processes with high energy consumption. Here, we report a high-selective conversion of syngas into ethanol by a triple tandem catalysis. An efficient trifunctional tandem system composed of potassium-modified ZnO–ZrO2, modified zeolite mordenite and Pt–Sn/SiC working compatibly in syngas stream in one reactor can afford ethanol with a selectivity of 90%. We demonstrate that the K+–ZnO–ZrO2 catalyses syngas conversion to methanol and the mordenite with eight-membered ring channels functions for methanol carbonylation to acetic acid, which is then hydrogenated to ethanol over the Pt–Sn/SiC catalyst. The present work offers an effective methodology leading to high selective conversion by decoupling a single-catalyst-based complicated and uncontrollable reaction into well-controlled multi-steps in tandem in one reactor.This work was supported by the National Key Research and Development Program of the Ministry of Science and Technology of China (No. 2017YFB0602201) and the National Natural Science Foundation of China (Nos. 91945301, 91545203, 21972116, 21433008, 21872112, 21673188 and 21690082). We acknowledge Prof. L. Peng and Y. Wen (Nanjing University, China) for performing NMR characterizations.该研究得到科技部重点研发计划(2017YFB0602201)和国家自然科学基金重大研究计划(91945301、91545203)等项目的资助

Mission Optimized Speed Control

Transportation underlines the vehicle industry's critical role in a country's economic future.The amount of goods moved, specically by trucks, is only expected to increase inthe near future. This work attempts to tackle the problem of optimizing fuel consumptionin Volvo trucks, when there are hard constraints on the delivery time and speed limits.Knowledge of the truck such as position, state, conguration etc., along with the completeroute information of the transport mission is used for fuel optimization.Advancements in computation, storage, and communication on cloud based systems, hasmade it possible to easily incorporate such systems in assisting modern eet. In this work,an algorithm is developed in a cloud based system to compute a speed plan for the completemission for achieving fuel minimization. This computation is decoupled from thelocal control operations on the truck such as prediction control, safety, cruise control, etc.;and serves as a guide to the truck driver to reach the destination on time by consumingminimum fuel.To achieve fuel minimization under hard constraints on delivery (or arrival) time andspeed limits, a non-linear optimization problem is formulated for the high delity modelestimated from real-time drive cycles. This optimization problem is solved using a Nonlinearprogramming solver in Matlab.The optimal policy was tested on two drive cycles provided by Volvo. The policy wascompared with two dierent scenarios, where the mission demands hard constraints ontravel time and the speed limits in addition to no trac uncertainties (deterministic). with a cruise controller running at a constant set speed throughout the mission. Itis observed that there is no signicant fuel savings. with maximum possible fuel consumption; achieved without the help of optimalspeed plan (worst case). It is seen that there is a notable improvement in fuelsaving.In a real world scenario, a transport mission is interrupted by uncertainties such as trac ow, road blocks, re-routing, etc. To this end, a stochastic optimization algorithm is proposedto deal with the uncertainties modeled using historical trac ow data. Possiblesolution methodologies are suggested to tackle this stochastic optimization problem

Mission Optimized Speed Control

Transportation underlines the vehicle industry's critical role in a country's economic future.The amount of goods moved, specically by trucks, is only expected to increase inthe near future. This work attempts to tackle the problem of optimizing fuel consumptionin Volvo trucks, when there are hard constraints on the delivery time and speed limits.Knowledge of the truck such as position, state, conguration etc., along with the completeroute information of the transport mission is used for fuel optimization.Advancements in computation, storage, and communication on cloud based systems, hasmade it possible to easily incorporate such systems in assisting modern eet. In this work,an algorithm is developed in a cloud based system to compute a speed plan for the completemission for achieving fuel minimization. This computation is decoupled from thelocal control operations on the truck such as prediction control, safety, cruise control, etc.;and serves as a guide to the truck driver to reach the destination on time by consumingminimum fuel.To achieve fuel minimization under hard constraints on delivery (or arrival) time andspeed limits, a non-linear optimization problem is formulated for the high delity modelestimated from real-time drive cycles. This optimization problem is solved using a Nonlinearprogramming solver in Matlab.The optimal policy was tested on two drive cycles provided by Volvo. The policy wascompared with two dierent scenarios, where the mission demands hard constraints ontravel time and the speed limits in addition to no trac uncertainties (deterministic). with a cruise controller running at a constant set speed throughout the mission. Itis observed that there is no signicant fuel savings. with maximum possible fuel consumption; achieved without the help of optimalspeed plan (worst case). It is seen that there is a notable improvement in fuelsaving.In a real world scenario, a transport mission is interrupted by uncertainties such as trac ow, road blocks, re-routing, etc. To this end, a stochastic optimization algorithm is proposedto deal with the uncertainties modeled using historical trac ow data. Possiblesolution methodologies are suggested to tackle this stochastic optimization problem

Mission Optimized Speed Control

Transportation underlines the vehicle industry's critical role in a country's economic future.The amount of goods moved, specically by trucks, is only expected to increase inthe near future. This work attempts to tackle the problem of optimizing fuel consumptionin Volvo trucks, when there are hard constraints on the delivery time and speed limits.Knowledge of the truck such as position, state, conguration etc., along with the completeroute information of the transport mission is used for fuel optimization.Advancements in computation, storage, and communication on cloud based systems, hasmade it possible to easily incorporate such systems in assisting modern eet. In this work,an algorithm is developed in a cloud based system to compute a speed plan for the completemission for achieving fuel minimization. This computation is decoupled from thelocal control operations on the truck such as prediction control, safety, cruise control, etc.;and serves as a guide to the truck driver to reach the destination on time by consumingminimum fuel.To achieve fuel minimization under hard constraints on delivery (or arrival) time andspeed limits, a non-linear optimization problem is formulated for the high delity modelestimated from real-time drive cycles. This optimization problem is solved using a Nonlinearprogramming solver in Matlab.The optimal policy was tested on two drive cycles provided by Volvo. The policy wascompared with two dierent scenarios, where the mission demands hard constraints ontravel time and the speed limits in addition to no trac uncertainties (deterministic). with a cruise controller running at a constant set speed throughout the mission. Itis observed that there is no signicant fuel savings. with maximum possible fuel consumption; achieved without the help of optimalspeed plan (worst case). It is seen that there is a notable improvement in fuelsaving.In a real world scenario, a transport mission is interrupted by uncertainties such as trac ow, road blocks, re-routing, etc. To this end, a stochastic optimization algorithm is proposedto deal with the uncertainties modeled using historical trac ow data. Possiblesolution methodologies are suggested to tackle this stochastic optimization problem

Influence of quantum degeneracy on the performance of a Stirling refrigerator working with an ideal Fermi gas

The influence of quantum degeneracy on the performance of a Stirling refrigeration cycle is investigated, based on the equation of state of an ideal Fermi gas. The inherent regenerative losses and the coefficient of performance (COP) of the cycle are calculated. It is found that, under the condition of strong gas degeneracy, the COP of the cycle in the first approximation is a function only of the temperatures of the heat reservoirs, while under other conditions, the COPs of the cycle depend on the temperatures of the heat reservoirs and other parameters of the cycle. The results obtained here reveal the general performance characteristics of a Stirling refrigeration cycle having a Fermi gas as its working substance.Stirling refrigeration cycle Fermi gas Quantum degeneracy Regenerative loss Coefficient of performance

Optimization criteria for the important parameters of an irreversible Otto heat-engine

An irreversible cycle model of an Otto heat-engine is established, in which the main irreversibilities result from the non-isentropic compression and expansion processes; finite-time processes and heat loss through the cylinder wall are taken into account. The power output and efficiency of the cycle are derived. The curves of the power output and efficiency varying with the compression ratio of two isochoric processes are presented. It is found from the curves that there are optimal values of the compression ratio at which the power output and efficiency attain their maxima. Moreover, the maximum power-output and efficiency and the corresponding relevant parameters are calculated, and consequently, the optimization criteria of some important parameters such as the power output, efficiency, compression ratio, and temperatures of the working substance are obtained.Otto heat engine Irreversibility Compression ratio Power output Efficiency Optimum criterion

DESIGN AND IMPLEMENTATION OF THE REMOTE CONTROL SYSTEM OF THE DIGITAL MAGNET POWER SUPPLY OF CHINA SPALLATION NEUTRON SOURCE THE REQUIREMENT OF REMOTE CONTROL SYSTEM OF POWER SUPPLY -cc Creative Commons Attribution 3.0 (CC-BY-3.0)

Abstract The magnet power supplies of the China Spallation Neutron Source (CSNS) can be classified into three types: rapid cycling synchrotron (RCS) resonant power supplies, fast response power supplies and DC power supplies. All of the magnet power supplies are controlled by the intelligent controller called Digital Power Supply Control Module (DPSCM), which can regulate the current and voltage circuit. The DPSCM is developed by the power supply group. It has two RS-232 communication interfaces. All the command setting and reading power parameters are transmitted by Modbus protocol. Therefore, we made the communication protocol based on Modbus RTU between the remote control system and the DPSCM. This paper introduces the design of the remote control interface to the DPSCM. We developed EPICS IOC applications and real-time database on MOXA embedded serial device DA710 and OPIs using Control System Studio according to different kinds of the power supplies. We have tested the remote control system with these kinds of power supplies. The test result shows that the remote control system is stable and reliable and it can basically meet the requirements of power supply system and physicists after the continuously test for two weeks. DPSCM INTRODUCE The accelerator magnet power supplies of the CSNS can be classified into three types by working mode: the 25Hz AC source with DC bias (6 sets), corrector power supply (34 sets) and DC power supply (240 sets). Essentially, all of these power supplies are controlled by DPSCM which designed by power supply group. It just need to be burnt proper program into FPGA according to the kinds of power supply. As shown in REMOTE CONTROL SYSTEM DESIGN Remote control system needs multi-serial devices for the large number of power supplies, 280 sets in total and the interface is all the RS-232 port. We ultimately chose high performance DA710 manufactured by MOXA company. The magnet power supply remote control system design scheme is shown i