Stony Brook’s High-Pressure Laboratory Collaborations with French Scientists

For more than a half century, my colleagues and I in the Stony Brook High Pressure Laboratory have profited from collaborations with French scientists in their laboratories in Orsay, Paris, Toulouse, Lille, Lyon, Strasbourg and Rennes. These interactions have included postdoctoral appointments of French colleagues in our laboratory as well as two année sabbatique by me;in 1983-84, in the Laboratoire de Géophysique et Géodynamique Interne at the Université Paris XI in Orsay and in 2020-2003 in the Laboratoire des Méchanismes et Transfert en Géologie at the Université Paul Sabatier in Toulouse. The objective of this report is to relate this history and to illustrate the scientific advances which resulted from these collaborations.

Stony Brook’s Collaborations with Czech Scientists

For the past half-century, I have been fortunate in maintaining collaborations with Czech scientists in the Czech Republic [formerly Czechoslovakia] from the Geofyzikální ústav-GFU [Institute of Geophysics] of the ?eskoslovenská Akademie Věd-?SAV [Czechoslovak Academy of Sciences]. These collaborations have included exchange visits by me to Prague [Praha] and convening international workshops in 1976, 1986 and 1996 in castles used by the ?SAV as well as visits by Czech colleagues to Stony Brook University. The objective of this report is to relate this history. This paper is dedicated to the memory of Vladislav Babu?ka.

Virtual Power Plants for Grid Resilience: A Concise Overview of Research and Applications

The power grid is undergoing a transformation from synchronous generators(SGs) toward inverter-based resources(IBRs). The stochasticity, asynchronicity, and limited-inertia characteristics of IBRs bring about challenges to grid resilience. Virtual power plants(VPPs) are emerging technologies to improve the grid resilience and advance the transformation. By judiciously aggregating geographically distributed energy resources(DERs) as individual electrical entities, VPPs can provide capacity and ancillary services to grid operations and participate in electricity wholesale markets. This paper aims to provide a concise overview of the concept and development of VPPs and the latest progresses in VPP operation, with the focus on VPP scheduling and control. Based on this overview, we identify a few potential challenges in VPP operation and discuss the opportunities of integrating the multi-agent system(MAS)-based strategy into the VPP operation to enhance its scalability, performance and resilience.

CAS-ESM2.0 Successfully Reproduces Historical Atmospheric CO_(2) in a Coupled Carbon−Climate Simulation

The atmospheric carbon dioxide(CO_(2))concentration has been increasing rapidly since the Industrial Revolution,which has led to unequivocal global warming and crucial environmental change.It is extremely important to investigate the interactions among atmospheric CO_(2),the physical climate system,and the carbon cycle of the underlying surface for a better understanding of the Earth system.Earth system models are widely used to investigate these interactions via coupled carbon-climate simulations.The Chinese Academy of Sciences Earth System Model version 2(CAS-ESM2.0)has successfully fixed a two-way coupling of atmospheric CO_(2)with the climate and carbon cycle on land and in the ocean.Using CAS-ESM2.0,we conducted a coupled carbon-climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment.This paper examines the modeled CO_(2)by comparison with observed CO_(2)at the sites of Mauna Loa and Barrow,and the Greenhouse Gases Observing Satellite(GOSAT)CO_(2)product.The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO_(2)during the period 1850-2014,and in capturing the seasonal cycle of CO_(2)at the two baseline sites,as well as over northern high latitudes.These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon-climate interactions,even though uncertainties remain in the processes involved.This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate,which will provide significant scientific support for climate research and China’s goal of carbon neutrality.

API Development Increases Access to Shared Computing Resources at Boston University

Within the last few decades, increases in computational resources have contributed enormously to the progress of science and engineering (S & E). To continue making rapid advancements, the S & E community must be able to access computing resources. One way to provide such resources is through High-Performance Computing (HPC) centers. Many academic research institutions offer their own HPC Centers but struggle to make the computing resources easily accessible and user-friendly. Here we present SHABU, a RESTful Web API framework that enables S & E communities to access resources from Boston University’s Shared Computing Center (SCC). The SHABU requirements are derived from the use cases described in this work.

Fecal microbiota transplantation for the treatment of irritable bowel syndrome:A systematic review and meta-analysis

BACKGROUND Irritable bowel syndrome(IBS)is the most prevalent gastrointestinal disorder in developed countries and reduces patients’quality of life,hinders their ability to work,and increases health care costs.A growing number of trials have demonstrated an aberrant gut microbiota composition in IBS,also known as‘gut dysbiosis’.Fecal microbiota transplantation(FMT)has been suggested as a treatment for IBS.AIM To assess the efficacy and safety of FMT for the treatment of IBS.METHODS We searched Cochrane Central,MEDLINE,EMBASE and Web of Science up to 24 October 2022 for randomised controlled trials(RCTs)investigating the effectiveness of FMT compared to placebo(including autologous FMT)in treating IBS.The primary outcome was the number of patients with improvements of symptoms measured using a validated,global IBS symptoms score.Secondary outcomes were changes in quality-of-life scores,non-serious and serious adverse events.Risk ratios(RR)and corresponding 95%CI were calculated for dichotomous outcomes,as were the mean differences(MD)and 95%CI for continuous outcomes.The Cochrane risk of bias tool was used to assess the quality of the trials.GRADE criteria were used to assess the overall quality of the evidence.RESULTS Eight RCTs(484 participants)were included in the review.FMT resulted in no significant benefit in IBS symptoms three months after treatment compared to placebo(RR 1.19,95%CI:0.68-2.10).Adverse events were reported in 97 participants in the FMT group and in 45 participants in the placebo group(RR 1.17,95%CI:0.63-2.15).One serious adverse event occurred in the FMT group and two in the placebo group(RR 0.42,95%CI:0.07-2.60).Endoscopic FMT delivery resulted in a significant improvement in symptoms,while capsules did not.FMT did not improve the quality of life of IBS patients but,instead,appeared to reduce it,albeit non significantly(MD-6.30,95%CI:-13.39-0.79).The overall quality of the evidence was low due to moderate-high inconsistency,the small number of patients in the studies,and imprecision.CONCLUSION We found insufficient evidence to support or refute the use of FMT for IBS.Larger trials are needed.

Machine learning-based stiffness optimization of digital composite metamaterials with desired positive or negative Poisson's ratio

Mechanical metamaterials such as auxetic materials have attracted great interest due to their unusual properties that are dictated by their architectures.However,these architected materials usually have low stiffness because of the bending or rotation deformation mechanisms in the microstructures.In this work,a convolutional neural network(CNN)based self-learning multi-objective optimization is performed to design digital composite materials.The CNN models have undergone rigorous training using randomly generated two-phase digital composite materials,along with their corresponding Poisson's ratios and stiffness values.Then the CNN models are used for designing composite material structures with the minimum Poisson's ratio at a given volume fraction constraint.Furthermore,we have designed composite materials with optimized stiffness while exhibiting a desired Poisson's ratio(negative,zero,or positive).The optimized designs have been successfully and efficiently obtained,and their validity has been confirmed through finite element analysis results.This self-learning multi-objective optimization model offers a promising approach for achieving comprehensive multi-objective optimization.

A data-driven machine learning approach for yaw control applications of wind farms

This study proposes a cost-effective machine-learning based model for predicting velocity and turbulence kineticenergy fields in the wake of wind turbines for yaw control applications.The model consists of an auto-encoderconvolutional neural network(ACNN)trained to extract the features of turbine wakes using instantaneous datafrom large-eddy simulation(LES).The proposed framework is demonstrated by applying it to the Sandia NationalLaboratory Scaled Wind Farm Technology facility consisting of three 225 kW turbines.LES of this site is performedfor different wind speeds and yaw angles to generate datasets for training and validating the proposed ACNN.It is shown that the ACNN accurately predicts turbine wake characteristics for cases with turbine yaw angleand wind speed that were not part of the training process.Specifically,the ACNN is shown to reproduce thewake redirection of the upstream turbine and the secondary wake steering of the downstream turbine accurately.Compared to the brute-force LES,the ACNN developed herein is shown to reduce the overall computational costrequired to obtain the steady state first and second-order statistics of the wind farm by about 85%.

Precision Tests of the Nonlinear Mode Coupling of Anisotropic Flow via High-Energy Collisions of Isobars

Valuable information on dynamics of expanding fluids can be inferred from the response of such systems to perturbations in their initial geometry.We apply this technique in high-energy^(96)Ru+^(96)Ru and^(96)Zr+^(96)Zr collisions to scrutinize the expansion dynamics of the quark-gluon plasma,where the initial geometry perturbations are sourced by the differences in deformations and radial profiles between^(96)Ru and^(96)Zr,and the collective response is captured by the change in anisotropic flow Vn between the two collision systems.Using a transport model,we analyze how the nonlinear coupling between lower-order flow harmonics V_(2)and V_(3)to the higher-order flow harmonics V_(4)and V_(5),expected to scale as V_(4)NL= χ_(4)V_(2)2and V_(5)NL= χ_(5)V_(2)V_(3),gets modified as one moves from^(96)Ru+^(96)Ru to^(96)Zr+^(96)Zr systems.We find that these scaling relations are valid to high precision:variations of order 20% in V_(4)NLand V_(5)NLdue to differences in quadrupole deformation,octupole deformation,and nuclear skin modify χ_(4)and χ_(5)by about 1–2%.Percent-level deviations are however larger than the expected experimental uncertainties and could be measured.Therefore,collisions of isobars with different nuclear structures are a unique tool to isolate subtle nonlinear effects in the expansion of the quark-gluon plasma that would be otherwise impossible to access in a single collision system.

Adaptive Reversible Visible Watermarking Based on Total Variation for BTC-Compressed Images

Few previous Reversible Visible Watermarking(RVW)schemes have both good transparency and watermark visibility.An adaptive RVW scheme that integrates Total Variation and visual perception in Block Truncation Coding(BTC)compressed domain,called TVB-RVW is proposed in this paper.A new mean image estimation method for BTC-compressed images is first developed with the help of Total Variation.Then,a visual perception factor computation model is devised by fusing texture and luminance characteristics.An adaptive watermark embedding strategy is used to embed the visible watermark with the effect of the visual perception factor in the BTC domain.Moreover,a lossless embedding method of the encrypted visible watermark is exploited to deter illegal watermark removal.The visible watermark can be removed since the visual perception factor and the estimated mean image remain unchanged before and after watermark embedding.Extensive experiments validate the superiority of the proposed algorithm over previous RVW schemes in BTC in terms of the visual quality of watermarked images and watermark visibility,and it can achieve a good balance between transparency and watermark visibility.

慢性心理社会应激触发小胶质细胞/巨噬细胞诱导的炎症反应,导致神经元功能障碍和抑郁相关行为

慢性环境压力和创伤性社会经历会导致不良行为变化,是主要抑郁症(MDD)和各种焦虑相关精神障碍的危险因素。临床研究和慢性压力的动物模型研究结果显示,症状严重程度与先天免疫反应和情绪调节相关脑区(mPFC:内侧前额叶皮质)中神经炎症细胞因子信号上调有关。尽管越来越多的证据表明神经可塑性受损和突触信号传导缺陷是与应激相关精神障碍的病理生理学的一部分,但小胶质细胞如何调节神经元稳态以应对慢性压力尚未明确。本研究使用反复社交挫败应激(RSDS)小鼠模型证明小胶质细胞诱导的炎症反应可以调节与心理社会压力相关的神经元可塑性。具体来说,我们发现慢性压力会迅速激活并增殖mPFC中的小胶质细胞以及巨噬细胞浸润,并且这些过程与神经元激活的空间位置相关。此外,我们研究还发现小胶质细胞炎症反应与对慢性压力的敏感性或抗性之间存在显著关联;暴露于慢性压力会加剧突触成分的吞噬作用和神经元可塑性的缺陷。通过使用2种不同的CSF1R抑制剂(脑渗透性的PLX5622和非渗透性的PLX73086),我们证实了小胶质细胞(其次为巨噬细胞)在催化mPFC中与心理社会压力相关的病理表现以及在与抑郁症相关的常见行为缺陷方面的关键作用。

PartLabeling:A label management framework in 3D space

Background In this work,we focus on the label layout problem:specifying the positions of overlaid virtual annotations in Virtual/Augmented Reality scenarios.Methods Designing a layout of labels that does not violate domain-specific design requirements,while at the same time satisfying aesthetic and functional principles of good design,can be a daunting task even for skilled visual designers.Presenting the annotations in 3D object space instead of projection space,allows for the preservation of spatial and depth cues.This results in stable layouts in dynamic environments,since the annotations are anchored in 3D space.Results In this paper we make two major contributions.First,we propose a technique for managing the layout and rendering of annotations in Virtual/Augmented Reality scenarios by manipulating the annotations directly in 3D space.For this,we make use of Artificial Potential Fields and use 3D geometric constraints to adapt them in 3D space.Second,we introduce PartLabeling:an open source platform in the form of a web application that acts as a much-needed generic framework allowing to easily add labeling algorithms and 3D models.This serves as a catalyst for researchers in this field to make their algorithms and implementations publicly available,as well as ensure research reproducibility.The PartLabeling framework relies on a dataset that we generate as a subset of the original PartNet dataset consisting of models suitable for the label management task.The dataset consists of 10003D models with part annotations.

Primary adrenal Ewing sarcoma:A systematic review of the literature

BACKGROUND Ewing sarcoma(ES)is a malignant neoplasm of neuroectodermal origin and is commonly observed in children and young adults.The musculoskeletal system is the main body system impacted and ES is rarely seen in the visceral organs particularly the adrenal gland.AIM To present a comprehensive review of primary adrenal ES,with emphasis on diagnosis,therapy and oncological outcomes.METHODS A systematic review of the literature was performed according to the Preferred Reporting Items for Systematic reviews and Meta-Analyses 2020.PubMed/MEDLINE,EMBASE and Google Scholar bibliographic databases were searched to identify articles from 1989 to 2022 and included patients with ES/primitive neuroectodermal tumor(PNET)of the adrenal gland.PubMed,Google Scholar and EMBASE medical databases were searched,combining the terms“adrenal”,“ES”and“PNET”.Demographic,clinical,pathological and oncological data of patients were analyzed by SPSS version 29.0.RESULTS A total of 52 studies were included for review(47 case reports and 5 case series)with 66 patients reported to have primary adrenal ES.Mean age at diagnosis was 26.4±15.4 years(37.9%males,57.6%females,sex not reported in 3 cases).The most frequent complaint was abdominal/flank pain or discomfort(46.4%)followed by a palpable mass(25.0%),and the average duration of symptoms was 2.6±3.1 mo.The imaging modality of choice was computed tomography scan(81.5%),followed by magnetic resonance imaging(20.4%).Preoperative staging revealed that 17 tumors(27.9%)were metastatic and 14 patients had inferior vena cava or renal vein neoplastic thrombus at initial diagnosis.Open adrenalectomy was performed in the majority of cases(80.0%),of which 27.9%required more extensive resection.Minimally invasive surgery was attempted in 8.2%of tumors.Complete surgical resection was achieved in 89.4%of the patients.Adjuvant therapy was administered to 32 patients,in the form of chemotherapy(62.5%),radiotherapy(3.1%)or combination(34.4%).Median overall survival was 15 mo and 24-mo overall survival was 40.5%.Median disease-free survival was 10 mo and 24-mo disease-free survival was 33.3%.CONCLUSION The significant progress in molecular biology and genetics of ES does not reflect on patient outcomes.ES remains an aggressive tumor with a poor prognosis and high mortality.

气候变化约束下中国电力系统低碳转型路径及策略

为理清应对气候变化约束下推动电力系统转型中面临的挑战和潜力,形成有效精准抓手,研究从气候变化约束对电力需求的影响出发,系统梳理温升目标下电力系统转型路径相关研究,并通过综述在低碳转型过程中与电力系统密切相关的煤电退出问题、可再生能源并网问题以及电网优化问题提出相应政策建议。研究发现,温升约束下煤电规模需快速下降,可再生能源发电大规模并网及远距离输送将成为最显著的特征,气电将承担比现在更重大的责任,核电需抛开争议加速发展。加快完善市场化机制、严控煤电规模、着力提升能效、统筹加强灵活性资源管理以及优化跨区负荷管理应成为监管部门重点推进的方向。

三峡库区消落带土壤有机碳氧化稳定性特征

土壤有机碳氧化的难易对土壤质量和碳沉降具有显著的影响。选取三峡库区消落带的3个海拔梯度的土壤,以从未淹没的样地作为对照,研究消落带湿地不同海拔梯度土壤有机碳氧化难易各组分（F1：高氧化活性有机碳组分;F2：中氧化活性有机碳组分;F3：低氧化活性有机碳组分;F4：难氧化有机碳组分）的特征。结果表明：土壤F1组分含量和其所占有机碳的比例在所有样地的各组分中最高。土壤易氧化有机碳总量及其F2,F3和F4组分都是消落带区域小于从未淹没的对照样地,但是高氧化有机碳组分F1在海拔155～165m的消落带区域与从未淹没的对照样地之间并无显著的差异。在消落带区域,155～165m区域土壤易氧化有机碳及其F1组分显著大于144～155m及其165～175m区域的,而F2,F3和F4组分之间都无显著性差异。相关性分析表明,土壤易氧化有机碳及其氧化有机碳组分与土壤总有机碳之间都具有显著的正相关性,而氧化有机碳F3和F4组分只与土壤全氮之间具有显著的正相关性。消落带土壤易氧化碳活性系数的大小顺序为是155～165m〉145～165m〉165～175m,这意味着消落带土壤有机碳不稳定性高低的顺序为155～165m〉145～165m〉165～175m。

智能车位锁管理系统设计

为了解决广大市民停车难、停车贵等问题,将ZigBee与WiFi无线通信技术相结合,并引入实时时钟模块和继电器模块,通过软、硬件开发设计了智能车位锁管理系统。当有取车或停车需求时,手机用户通过WiFi接入网络并发送需求指令,ZigBee协调器收到通信请求后发送无线数据到指定终端,从而控制车位锁的升降。此外,该系统利用RTC实时时钟模块可计算停车时间并扣取费用。通过实验验证了该车位锁管理系统的有效性。本管理系统的设计为全市停车场进行联网提供了一种新方案。

肿瘤基因突变组学在肿瘤免疫治疗中的意义

肿瘤基因突变的研究为转化医学研究提供了重要手段,对基因突变的深入探索改变了肿瘤的诊断、分类和预后评估方式,显著提高了肿瘤的临床治疗效果,同时也为个体化肿瘤免疫治疗的发展奠定基础并提供了新策略。本文对近年来这些领域的研究和肿瘤免疫治疗的临床应用进展予以介绍,并提出"突变组学(mutanome)"的概念,就基因突变组学与肿瘤的发生、与肿瘤疫苗治疗和过继免疫治疗的关系研究进展等方面作一综述。

青藏高原调控区域能量过程和全球气候的机理

本文总结了中国国家自然科学基金委重点项目“青藏高原调控区域能量过程及其影响机理”的研究进展。着重阐明了春夏季伊朗高原和青藏高原(TIP)地表热通量特征及变化原因、TIP上空独特的水汽、云宏观和微观垂直结构,以及降水和云辐射效应;在夏季两个高原地区的感热加热存在相互影响和反馈,形成观测到的加热与大气垂直环流之间的准平衡耦合系统,由此提出了TIP系统(TIPS)的概念;项目还从天文和水文的角度佐证了TIPS对亚洲夏季风的影响,揭示TIPS导致上对流层暖、下平流层冷的南亚高压的形成机理及TIPS影响北半球环流和印度洋海气相互作用的物理过程;揭示TIPS系统对南亚高压年际变化的影响,提出高原位涡强迫激发中国东部激烈天气过程的一种新机制。此外还揭示了CMIP5模式对高原表面温度模拟存在冷偏差的原因和其中的物理过程,这是大气环流与冰雪反照率的动力耦合的结果。

玉米叶片物理建模与参数确定的运动学分析方法

基于物理的方法是解决植物动态建模与仿真的有效途径,而模型参数的确定是基于物理方法所面临的重要问题.为实现基于生物物理属性特征的玉米叶片高精度、高真实感动态建模与仿真,提出一种基于运动学分析的玉米叶片物理建模与参数确定方法.首先利用运动捕捉技术获取玉米叶片的运动数据;然后根据运动捕捉特征点构建基于质点-弹簧系统的物理模型;最后基于运动学分析建立物理模型参数解析方程组,利用最小二乘法计算物理模型的参数.以此参数构建物理模型实现玉米叶片的动态模拟,并给出2种模型构造方式的玉米叶片虚拟仿真.结果表明,该方法以一种数据驱动的机制有效估算出对应的物理模型参数,生成的玉米叶片动态虚拟仿真过程具有与实际情况较为接近的真实感效果,为虚拟植物建模与应用提供了一种可行的物理建模及参数确定方法.

激光工作模式对苯氰S1电子态高分辨光谱的影响

本文研究了不同激光工作模式对苯氰分子高分辨光谱的影响,高分辨的激光为Ar^+泵浦的cw环形染料激光经过Nd:YAG激光三步脉冲放大后倍频产生的UV光.实验发现当Nd:YAG激光的振荡级有种子光注入时,光谱呈现转动分辨的谱线,可以很好地标识为苯氰分子S_1←S_0 0_0~0跃迁的转动结构;而当Nd:YAG激光工作于多个模式(无种子光注入)时,光谱则为连续的毫无结构的谱带.由于苯氰分子S_1电子态具有较大的偶极矩,工作于多个模式下激光脉冲的峰值功率的增强产生AC Stark效应,是导致谱线加宽从而无法观测到转动分辨光谱的可能原因.