bluuebunny/crossref_metadata_2025 huggingface dataset:
ADGNN: Towards Scalable GNN Training with Aggregation-Difference Aware Sampling
Authors: Song Zhen , Gu Yu , Li Tianyi , Sun Qing , Zhang Yanfeng , Jensen Christian S. , Yu Ge
Published: December 2023

Distributed computing is promising to enable large-scale graph neural network (GNN) model training. However, care is needed to avoid excessive computational and communication overheads. Sampling is promising in terms of enabling scalability, and sampling techniques have been proposed to reduce training costs. However, online sampling introduces large overheads, and while offline sampling that is done only once can eliminate such overheads, it instead introduces information loss and accuracy degradation. Thus, existing sampling techniques are unable to improve simultaneously both efficiency and accuracy, particularly at low sampling rates. We develop a distributed system, ADGNN, for full-batch based GNN training that adopts a hybrid sampling architecture to enable a trade-off between efficiency and accuracy. Specifically, ADGNN employs sampling result reuse techniques to reduce the cost associated with sampling and thus improve training efficiency. To alleviate accuracy degradation, we introduce a new metric,Aggregation Difference (AD), that quantifies the gap between sampled and full neighbor set aggregation. We present so-called AD-Sampling that aims to minimize the Aggregation Difference with an adaptive sampling frequency tuner. Finally, ADGNN employs anAD -importance-based sampling technique for remote neighbors to further reduce communication costs. Experiments on five real datasets show that ADGNN is able to outperform the state-of-the-art by up to nearly 9 times in terms of efficiency, while achieving comparable accuracy to the non-sampling methods.
DP-starJ: A Differential Private Scheme towards Analytical Star-Join Queries
Authors: Fu Congcong , Li Hui , Lou Jian , Li Huizhen , Cui Jiangtao
Published: December 2023

Star-join query is the fundamental task in data warehouse and has wide applications in On-line Analytical Processing (olap) scenarios. Due to the large number of foreign key constraints and the asymmetric effect in the neighboring instance between the fact and dimension tables, even those latest dp efforts specifically designed for join, if directly applied to star-join query, will suffer from extremely large estimation errors and expensive computational cost. In this paper, we are thus motivated to propose DP-starJ, a novel Differentially Private framework for star-Join queries. DP-starJ consists of a series of strategies tailored to specific features of star-join, including 1) we unveil the different effects of fact and dimension tables on the neighboring database instances, and accordingly revisit the definitions tailored to different cases of star-join; 2) we propose Predicate Mechanism (PM), which utilizes predicate perturbation to inject noise into the join procedure instead of the results; 3) to further boost the robust performance, we propose a dp-compliant star-join algorithm for various types of star-join tasks based on PM. We provide both theoretical analysis and empirical study, which demonstrate the superiority of the proposed methods over the state-of-the-art solutions in terms of accuracy, efficiency, and scalability.
FACET: Robust Counterfactual Explanation Analytics
Authors: VanNostrand Peter M. , Zhang Huayi , Hofmann Dennis M. , Rundensteiner Elke A.
Published: December 2023

Machine learning systems are deployed in domains such as hiring and healthcare, where undesired classifications can have serious ramifications for the user. Thus, there is a rising demand for explainable AI systems which provide actionable steps for lay users to obtain their desired outcome. To meet this need, we propose FACET, the first explanation analytics system which supports a user in interactively refining counterfactual explanations for decisions made by tree ensembles. As FACET's foundation, we design a novel type of counterfactual explanation called the counterfactual region. Unlike traditional counterfactuals, FACET's regions concisely describe portions of the feature space where the desired outcome is guaranteed, regardless of variations in exact feature values. This property, which we coin explanation robustness, is critical for the practical application of counterfactuals. We develop a rich set of novel explanation analytics queries which empower users to identify personalized counterfactual regions that account for their real-world circumstances. To process these queries, we develop a compact high-dimensional counterfactual region index along with index-aware query processing strategies for near real-time explanation analytics. We evaluate FACET against state-of-the-art explanation techniques on eight public benchmark datasets and demonstrate that FACET generates actionable explanations of similar quality in an order of magnitude less time while providing critical robustness guarantees. Finally, we conduct a preliminary user study which suggests that FACET's regions lead to higher user understanding than traditional counterfactuals.
HongTu: Scalable Full-Graph GNN Training on Multiple GPUs
Authors: Wang Qiange , Chen Yao , Wong Weng-Fai , He Bingsheng
Published: December 2023

Full-graph training on graph neural networks (GNN) has emerged as a promising training method for its effectiveness. Full-graph training requires extensive memory and computation resources. To accelerate this training process, researchers have proposed employing multi-GPU processing. However the scalability of existing frameworks is limited as they necessitate maintaining the training data for every layer in GPU memory. To efficiently train on large graphs, we present HongTu, a scalable full-graph GNN training system running on GPU-accelerated platforms. HongTu stores vertex data in CPU memory and offloads training to GPUs. HongTu employs a memory-efficient full-graph training framework that reduces runtime memory consumption by using partition-based training and recomputation-caching-hybrid intermediate data management. To address the issue of increased host-GPU communication caused by duplicated neighbor access among partitions, HongTu employs a deduplicated communication framework that converts the redundant host-GPU communication to efficient inter/intra-GPU data access. Further, HongTu uses a cost model-guided graph reorganization method to minimize communication overhead. Experimental results on a 4XA100 GPU server show that HongTu effectively supports billion-scale full-graph GNN training while reducing host-GPU data communication by 25%-71%. Compared to the full-graph GNN system DistGNN running on 16 CPU nodes, HongTu achieves speedups ranging from 7.8X to 20.2X. For small graphs where the training data fits into the GPUs, HongTu achieves performance comparable to existing GPU-based GNN systems.
PLATON: Top-down R-tree Packing with Learned Partition Policy
Authors: Yang Jingyi , Cong Gao
Published: December 2023

The exponential growth of spatial data poses new challenges to the performance of spatial databases. Spatial indexes like R-tree greatly accelerate the query performance and can be effectively constructed through packing, i.e., loading all data into the index at once. However, existing R-tree packing methods rely on a set of fixed heuristic rules, which may not be suitable for different data distributions and workload patterns. To address the limitations of existing R-tree packing methods, we propose PLATON, a top-down R-tree packing method with learned partition policy that explicitly optimizes the query performance with regard to the given data and workload instance. We develop a learned partition policy based on Monte Carlo Tree Search and carefully make design choices for the MCTS exploration strategy and simulation strategy to improve algorithm convergence. We propose a divide and conquer strategy and two optimization techniques, early termination and level-wise sampling, to drastically reduce the MCTS algorithm's time complexity and make it a linear-time algorithm. Experiments on both synthetic and real-world datasets demonstrate the superior performance of PLATON over existing R-tree variants and recently proposed learned/workload-aware spatial indexes.
SALI: A Scalable Adaptive Learned Index Framework based on Probability Models
Authors: Ge Jiake , Zhang Huanchen , Shi Boyu , Luo Yuanhui , Guo Yunda , Chai Yunpeng , Chen Yuxing , Pan Anqun
Published: December 2023

The growth in data storage capacity and the increasing demands for high performance have created several challenges for concurrent indexing structures. One promising solution is the learned index, which uses a learning-based approach to fit the distribution of stored data and predictively locate target keys, significantly improving lookup performance. Despite their advantages, prevailing learned indexes exhibit constraints and encounter issues of scalability on multi-core data storage.

This paper introduces SALI, the Scalable Adaptive Learned Index framework, which incorporates two strategies aimed at achieving high scalability, improving efficiency, and enhancing the robustness of the learned index. Firstly, a set of node-evolving strategies is defined to enable the learned index to adapt to various workload skews and enhance its concurrency performance in such scenarios. Secondly, a lightweight strategy is proposed to maintain statistical information within the learned index, with the goal of further improving the scalability of the index. Furthermore, to validate their effectiveness, SALI applied the two strategies mentioned above to the learned index structure that utilizes fine-grained write locks, known as LIPP. The experimental results have demonstrated that SALI significantly enhances the insertion throughput with 64 threads by an average of 2.04x compared to the second-best learned index. Furthermore, SALI accomplishes a lookup throughput similar to that of LIPP+.
TEE-based General-purpose Computational Backend for Secure Delegated Data Processing
Authors: Sha Mo , Li Jialin , Wang Sheng , Li Feifei , Tan Kian-Lee
Published: December 2023

The increasing prevalence of data breaches necessitates robust data protection measures in computational tasks. Secure computation outsourcing (SCO) presents a viable solution by safeguarding the confidentiality of inputs and outputs in data processing without disclosure. Nonetheless, this approach assumes the existence of a trustworthy coordinator to orchestrate and oversee the process, typically implying that data owners must fulfill this role themselves. In this paper, we consider secure delegated data processing (SDDP), an expanded data processing scenario wherein data owners simply delegate their data to SDDP providers for subsequent value mining or other downstream applications, eliminating the necessary involvement of data owners or trusted entities to dive into data processing deeply. However, general-purpose SDDP poses significant challenges in permitting the discretionary execution of computational tasks by SDDP providers on sensitive data while ensuring confidentiality. Existing approaches are insufficient to support SDDP in either efficiency or universality. To tackle this issue, we propose TGCB, a TEE-based General-purpose Computational Backend, designed to endow general-purpose computation with SDDP capabilities from an engineering perspective, powered by TEE-based code integrity and data confidentiality. Central to TGCB is the Encryption Programming Language (EPL) that defines computational tasks in SDDP. Specifically, SDDP providers can express arbitrary computable functions as EPL scripts, processed by TGCB's interfaces, securely interpreted and executed in TEE, ensuring data confidentiality throughout the process. As a universal computational backend, TGCB extensively bolsters data security in existing general-purpose computational tasks, allowing data owners to leverage SDDP without privacy concerns.
A Learned Cuckoo Filter for Approximate Membership Queries over Variable-sized Sliding Windows on Data Streams
Authors: Tian Yao , Yan Tingyun , Zhang Ruiyuan , Huang Kai , Zheng Bolong , Zhou Xiaofang
Published: December 2023

Designing a space-efficient data structure to answer membership queries while ensuring high accuracy and real-time response is a challenging task in the field of stream processing. Many techniques have been developed to answer these queries in a sliding windows manner. However, assuming the user will conduct the query with the presupposed window size is not always practical. In this paper, we introduce a novel data structure called Learned Cuckoo Filter (LCF). It can provide satisfactory results for the approximate membership query on data streams, regardless of the user-defined query windows. LCF operates by adaptively maintaining cuckoo filters with the assistance of a well-trained oracle that learned the frequency feature of the data within the stream. To further enhance memory utilization, we develop a compact version of LCF (denoted by LCF_C), which selectively removes redundant information to reduce space consumption without compromising query accuracy. Furthermore, we conduct a thorough theoretical analysis of query accuracy and provide detailed guidelines for optimal parameter selection (denoted by LCF_O). Extensive experimental studies on synthetic and real-world datasets demonstrate the superiority of the proposed methods in terms of both space consumption and accuracy. Compared to the state-of-the-art algorithms, LCF_O can reduce up to 61% of space cost at the same error level, and achieve up to 12× improved accuracy with the same space cost.
Proving Query Equivalence Using Linear Integer Arithmetic
Authors: Ding Haoran , Wang Zhaoguo , Yang Yicun , Zhang Dexin , Xu Zhenglin , Chen Haibo , Piskac Ruzica , Li Jinyang
Published: December 2023

Proving the equivalence between SQL queries is a fundamental problem in database research. Existing solvers model queries using algebraic representations and convert such representations into first-order logic formulas so that query equivalence can be verified by solving a satisfiability problem. The main challenge lies in "unbounded summations", which appear commonly in a query's algebraic representation in order to model common SQL features, such as projection and aggregate functions. Unfortunately, existing solvers handle unbounded summations in an ad-hoc manner based on heuristics or syntax comparison, which severely limits the set of queries that can be supported.

This paper develops a new SQL equivalence prover called SQLSolver, which can handle unbounded summations in a principled way. Our key insight is to use the theory of LIA^*, which extends linear integer arithmetic formulas with unbounded sums and provides algorithms to translate a LIA^* formula to a LIA formula that can be decided using existing SMT solvers. We augment the basic LIA^* theory to handle several complex scenarios (such as nested unbounded summations) that arise from modeling real-world queries. We evaluate SQLSolver with 359 equivalent query pairs derived from the SQL rewrite rules in Calcite and Spark SQL. SQLSolver successfully proves 346 pairs of them, which significantly outperforms existing provers.
The Online Pause and Resume Problem: Optimal Algorithms and An Application to Carbon-Aware Load Shifting
Authors: Lechowicz Adam , Christianson Nicolas , Zuo Jinhang , Bashir Noman , Hajiesmaili Mohammad , Wierman Adam , Shenoy Prashant
Published: December 2023

We introduce and study the online pause and resume problem. In this problem, a player attempts to find the k lowest (alternatively, highest) prices in a sequence of fixed length T, which is revealed sequentially. At each time step, the player is presented with a price and decides whether to accept or reject it. The player incurs aswitching cost whenever their decision changes in consecutive time steps, i.e., whenever they pause or resume purchasing. This online problem is motivated by the goal of carbon-aware load shifting, where a workload may be paused during periods of high carbon intensity and resumed during periods of low carbon intensity and incurs a cost when saving or restoring its state. It has strong connections to existing problems studied in the literature on online optimization, though it introduces unique technical challenges that prevent the direct application of existing algorithms. Extending prior work on threshold-based algorithms, we introducedouble-threshold algorithms for both the minimization and maximization variants of this problem. We further show that the competitive ratios achieved by these algorithms are the best achievable by any deterministic online algorithm. Finally, we empirically validate our proposed algorithm through case studies on the application of carbon-aware load shifting using real carbon trace data and existing baseline algorithms.
Kernel vs. User-Level Networking: Don't Throw Out the Stack with the Interrupts
Authors: Cai Peter , Karsten Martin
Published: December 2023

This paper reviews the performance characteristics of network stack processing for communication-heavy server applications. Recent literature often describes kernel-bypass and user-level networking as a silver bullet to attain substantial performance improvements, but without providing a comprehensive understanding of how exactly these improvements come about. We identify and quantify the direct and indirect costs of asynchronous hardware interrupt requests (IRQ) as a major source of overhead. While IRQs and their handling have a substantial impact on the effectiveness of the processor pipeline and thereby the overall processing efficiency, their overhead is difficult to measure directly when serving demanding workloads. This paper presents an indirect methodology to assess IRQ overhead by constructing preliminary approaches to reduce the impact of IRQs. While these approaches are not suitable for general deployment, their corresponding performance observations indirectly confirm the conjecture. Based on these findings, a small modification of a vanilla Linux system is devised that improves the efficiency and performance of traditional kernel-based networking significantly, resulting in up to 45% increased throughput without compromising tail latency. In case of server applications, such as web servers or Memcached, the resulting performance is comparable to using kernel-bypass and user-level networking when using stacks with similar functionality and flexibility.
HEAL: Performance Troubleshooting Deep inside Data Center Hosts
Authors: Pan Yicheng , Zhang Yang , Bi Tingzhu , Han Linlin , Zhang Yu , Ma Meng , Shen Xiangzhuang , Jiang Xinrui , Wang Feng , Liu Xian , Wang Ping
Published: December 2023

This study demonstrates the salient facts and challenges of host failure operations in hyperscale data centers. A host incident can involve hundreds of distinct host-level metrics, covering broad aspects. The faulting mechanism inside the host connects these heterogeneous metrics through direct and indirect correlation, making it extremely difficult to sort out the propagation procedures and the root cause from these intertwined indicators. To deeply understand the failure mechanism inside the host, we develop HEAL -- a novel host metrics analysis toolkit. HEAL synergistically discovers dynamic causality in sparse heterogeneous host metrics by combining the strengths of both time series and random variable analysis. It can also proactively extract causal directional hints from causality's asymmetry and historical knowledge. Together, these breakthroughs help HEAL produce accurate results given undesirable inputs. Extensive experiments in our production environment verify that HEAL provides significantly better result accuracy and full-process interpretability than the SOTA baselines. With these advantages, HEAL successfully serves our data center and worldwide product operations and impressively contributes to many other workflows.
Social Identities and Intersectionality: A Conversation About the What and the How of Development
Authors: Azmitia Margarita , Garcia Peraza Paulette D. , Casanova Saskias
Published: December 2023

Research on the development of social identities in early and middle childhood has largely focused on gender; increasingly, however, theory and research have addressed the development of ethnic/racial, social class, sexual, and immigrant identities. Moreover, it is assumed that individuals’ thinking about and articulating of the intersectionality between their social identities emerge in adolescence and young adulthood, but a growing body of work has shown that minoritized children conceptualize their intersectional identities by middle childhood. This article reviews that work and addresses how interdisciplinary scholarship and quantitative and qualitative methodologies can deepen our understanding of the development of social identities and intersectionality. We take a contextual approach to investigate how relational and cultural contexts contour the socialization of social and intersectional identities. Most of our review focuses on theory and research in the United States; however, because we aim to consider immigrant identity, we also include theory and research on how immigrant families and communities help minoritized children and youth navigate their identities in schools and communities and cope with discrimination.
Establishment of a Lithium-Ion Battery Model Considering Environmental Temperature for Battery State of Charge Estimation
Authors: Wang Jiabin , Du Jianhua , Tan Birong , Cao Xin , Qu Chang , Ou Yingjie , He Xingfeng , Xiong Leji , Tu Ran
Published: December 2023

Accurate estimation of the state-of-charge (SOC) is essential to prevent overcharging and over-discharging of lithium-ion batteries. However, traditional SOC estimation methods exhibit significant errors under large temperature variations due to the strong temperature dependence of battery characteristics. To enhance the accuracy of SOC estimation, this study proposes a second-order RC equivalent circuit model with temperature correction. By considering the influence of temperature on model parameters, the model’s accuracy is improved by adjusting the estimated parameters. A polynomial coefficient data table for model parameters is established to expedite the computation time of the SOC estimation process. Finally, the temperature-corrected model is combined with an Adaptive Extended Kalman Filter (AEKF) algorithm for SOC estimation. The results of the Dynamic Stress Test (DST) condition experiments show that the temperature correction model can improve the accuracy of SOC estimation under different temperature conditions. It has a more lower SOC estimation error than the model without temperature correction.
g-C3N4 Boosting the Interfacial Compatibility of Solid-State Lithium-Sulfur Battery
Authors: Wang Peng-Qin , Shao Wen-Wen , Zhong Liang , Wu Heng-Fei , Li Jing-Xuan , Liu Ming-Quan , Mei Yong , Zhang Gang , Liu Hai-Xia , Shen Xiang-Qian , Jing Mao-Xiang
Published: December 2023

The poor interfacial compatibility between solid electrolyte and lithium metal anode is one of the main obstacles to the development of solid lithium metal battery. Herein, the poly (1,3-dioxolane) (PDOL) polymer is combined with g-C3N4 powders to form a flexible and dense composite solid electrolyte film, which not only possesses high ionic conductivity of 3.7 × 10−4 S·cm−1, high ion migration number up to 0.86, and wide electrochemical stability window of 5.0 V, but also is helpful for inhibiting the growth of lithium dendrites to improve the interfacial stability of the lithium anode and close contact with cathode. The prepared S/g-C3N4-PDOL/Li battery exhibits good rate and cycle performances with a capacity of 550 mAh g−1 at 1 C, and 1150 mAh g−1 at 0.1 C with a capacity retention rate of 83% after 100 cycles. The dense Li3N layer generated by the reaction between g-C3N4 and Li gives g-C3N4/PDOL composite electrolyte a high inhibition ability of lithium dendrites. This composite solid electrolyte film with an interface modification function has good practical application prospects in lithium-sulfur batteries.
Expression and function of transient receptor potential melastatin 3 in the spinal afferent innervation of the mouse colon
Authors: King James W. , Bennett Aidan S. W. , Wood Hannah M. , Baker Corey C. , Alsaadi Hanin , Topley Max , Vanner Stephen A. , Reed David E. , Lomax Alan E.
Published: December 2023

This is the first study to characterize TRPM3 protein expression and function in colon-projecting DRG neurons. A TRPM3 agonist excited DRG neurons and colonic afferent nerves from healthy mice. TRPM3 agonist responses in DRG neurons were elevated during colitis. Inhibiting TRPM3 reduced the firing of wide dynamic range afferent nerves from mice with colitis but had no effect in control mice.
Diesel exhaust particles induce polarization state-dependent functional and transcriptional changes in human monocyte-derived macrophages
Authors: Smyth Timothy , Jaspers Ilona
Published: December 2023

We determined that reprogramming M2 macrophages in the presence of diesel exhaust particles (DEP) results in a highly inflammatory mixed M1/M2 phenotype. We also demonstrated that M1 macrophages are particularly vulnerable to particulate matter (PM) exposure as seen by dampened phagocytic function and modified bioenergetics. Our study suggests that PM causes reprogrammed M2 macrophages to become a highly energetic, highly secretory subpopulation of macrophages that may contribute to negative health outcomes observed in humans after PM exposure.
In Silico, SwissADME, and DFT Studies of Newly Synthesized Oxindole Derivatives Followed by Antioxidant Studies
Authors: Rauf Abdur , Khan Haroon , Khan Momin , Abusharha Ali , Serdaroğlu Goncagül , Daglia Maria
Published: December 2023

The compounds were synthesized by refluxing 6-chlorooxindole with 2,3-dichlorobenzaldehyde and 2,6-dichlorobenzaldehyde in the presence of piperidine as a catalyst and characterized by spectroscopic analysis using 1H NMR, 13C NMR, and mass spectrometry as (E)-3-(2,3-dichlorobenzylidene)-6-chloroindolin-2-one (C-1) and (E)-3-(2,6-dichlorobenzylidene)-6-chloroindolin-2-one (C-2). Additionally, in silico ADME studies indicated that C-1 and C-2 with 1,1 rotatable bonds could have moderate water solubility and therefore could have the potential ability to cross the blood-brain barrier. Both showed high GI absorption, indicating that they are suitable for intestinal absorption while the compounds showed CYP1A2, CYP2C19, and CYP2C9 inhibition. The five drug-likeness criteria, which were Lipinski, Muegge, Ghose, Veber, and Egan, and the principles of drug-likeness are not violated by compounds C-1 and C-2. Also, the DFT computations were performed at the B3LYP level and at 6-311++G

∗
∗

basis set to evaluate and support the obtained results from the experiment. The FMO results revealed that C-1 could likely prefer the intramolecular interactions rather than the intermolecular interactions, and vice versa for C-2. In addition, the NBO results indicated that the resonance interaction, especially the shift of electron to empty orbitals from lone pair electrons of nitrogen, would contribute to the stabilization of both compounds greatly. In DPPH assay, the compounds showed IC50 values of 37.390 and 34.676 μM, respectively. Similarly, in ABTS assay, the calculated IC50 values for the compounds were 25.381 and 33.706 μM, respectively. In short, these results provided a solid ground for further preclinical studies in quest of new effective therapeutic agents.
Comparative Analysis of Energy Storage Technologies for Microgrids
Authors: Chehab Mohamed Haikel , Ben Salah Chokri , Falama Ruben Zieba , Tlija Mehdi , Rabhi Abdelhamid
Published: December 2023

Nowadays, microgrids (MGs) are receiving a lot of attention. In an economical MG, the battery energy storage system (BESS) plays an important role. One of the biggest challenges in MGs is the optimal choice of the BESS that can lead to better performance of the MG, which will be more flexible, efficient, and effective than traditional power systems. In this paper, we present the modeling and simulation of different energy storage systems including Li-ion, lead-acid, nickel cadmium (Ni-Cd), nickel-metal hybrid (Ni-Mh), and supercapacitor (SC), for renewable energy applications, and more specifically for MGs. The results of simulation show that Li-ion batteries have a better response time than lead-acid batteries, Ni-Cd batteries, and Ni-Mh batteries and thus are more suitable for combination with supercapacitors. Li-ion batteries are the best option for fast-charging applications in MGs. The discharge phase ends with SOC ≤ ±94%, SOC ≤ ±95%, SOC = 95%, SOC < 95%, and SOC < 60%, respectively, for Li-ion, lead-acid, Ni-Cd, Ni-Mh, and supercapacitor. Moreover, the use of the battery management system (BMS) can significantly improve the performance of BESS, leading to higher levels of SOC and longer life span. The obtained results have shown that with an optimization algorithm for energy storage systems, more specifically for the battery-charging mode, the response time of BESSs can be further improved. The effect of ambient temperature has also been investigated on the functional capacities of the batteries. The obtained results demonstrated that extreme temperatures (80°C to −80°C) have a significant impact on battery performance and capacity, especially for Li-ion batteries, with a drop in capacity of up to 50% at −40°C. This highlights the importance of considering the ambient temperature in the design and operation of MGs. Overall, our study provides valuable insights into the optimal selection of BESS and the impact of ambient temperature on their performance, which can help in the development of more efficient and reliable MGs.
Forecasting the Friction Coefficient of Rubbing Zirconia Ceramics by Titanium Alloy
Authors: Salah Ahmad , Fathalla Ahmed , Eldesouky Esraa , Li Wei , Mahmoud Ibrahim Ahmed Mohamed
Published: December 2023

The thermal issues generated from friction are the key obstacle in the high‐performance machining of titanium alloys. The friction between the workpiece being cut and the cutting tool is the dominant parameter that affects the heat generation during the machining processes, i.e., the temperature inside the cutting zone and the consumed cutting energy. Besides, the complexity is associated with the nature of the friction phenomenon. However, there are limited efforts to forecast the friction coefficient during the machining operations. In this work, the friction coefficients between the titanium alloy against zirconia ceramics lubricated by minimum quantity lubrication were recorded and measured using a universal mechanical tester pin‐on‐disc tribometer. Then, we proposed two models for forecasting the friction coefficient which are trained and tested on the recorded data. The two predictive models are based on autoregressive integrated moving average and gated recurrent unit deep neural network methods. The proposed models are evaluated through a set of exhaustive experiments. These experiments demonstrated that the proposed models can efficiently be used to reduce power consumption dedicated to monitoring the friction coefficients. Besides, they can reduce or avoid surface thermal damage by predicting the high level of friction coefficients in advance, which can be used as an alert to enable or readjust the lubrication parameters (fluid pressure, fluid flow rate, etc.) to maintain lower ranges of friction coefficients and power consumption.
Acute and Subchronic Toxicity Assessment of Conventional Soxhlet Cymbopogon citratus Leaves Extracts in Sprague–Dawley Rats
Authors: Ayembilla Jacob Apibilla , Khalid Abdul Raouf , Abubakari Sharif Buari , Adams Abdul Rashid , Botchway Felix Abekah , Antwi Stephen , Otu Phyllis Naa Yarley , Appiah Michael , Osei-Adjei George , Kottoh Kwame Owen , Ahiabenu-Williams Peace , Quasie Olga
Published: December 2023

Background. In Ghana, Cymbopogon citratus leaves together with guava, pawpaw, and lime are processed into a decoction to treat fever. To encourage its usage, preclinical validation of the safety profile of the plant is required. The acute and subchronic toxicities of the conventional Soxhlet ethanolic Cymbopogon citratus leaves extract in Sprague–Dawley rats were investigated. Methods. Pulverized Cymbopogon citratus leaves were extracted with 98% ethanol using the conventional Soxhlet extraction (CSE) method and dried. In the acute toxicity study, a single dose of 5000 mg/kg body weight was administered to six female Sprague–Dawley rats and 1 ml/100 g body weight normal saline to control (6) once, and signs of toxicity were observed every hour for the first 12 hr, 24 hr, and 48 hr through to 14 days. In the subchronic study, the treatment groups were administered 200 mg/kg, 600 mg/kg, and 1200 mg/kg, respectively, of the CSE C. citratus leaves extract for six weeks. Analyses were conducted on the blood, urine, and serum samples of the rats. Histopathological examination of the liver, heart, kidney, spleen, and lungs was carried out at termination. Analysis of variance (ANOVA) was performed to determine statistically significant differences between the test and control rats at

P
 
<
 
0.05

. Results. The results revealed that there were no statistically significant differences (

p
 
>
 
0.05

) in the urinalysis and haematological analysis between control and test rats over the treatment period. Similarly, CSE C. citratus leaves extract did not induce any significant biochemical changes in the treatment group; however, there was a weight loss effect on the treated rats. There were no noticeable morphological changes in the heart, liver, spleen, lung, and kidney of the test rats compared to the control. Conclusion. CSE ethanolic C. citratus leaves extract has a weight loss effect, and long-term administration of the extract may not cause any organ-specific toxicity to the consumers.
Preferences of Caregivers of People with Dementia for Respite Care: A Discrete Choice Experiment
Authors: Gao Weijie , Zhang Tieling , Wang Hongyun , Wang Shanshan , Ye Xin , Pang Xiaoli , Hu Yan
Published: December 2023

Taking care of people with dementia is stressful for informal caregivers. Respite care can provide a break for them. But it is often underused, and its acceptability can be low in China. One reason is that it fails to meet their needs. This study aimed to explore the preference of caregivers of people with dementia for respite care services. A discrete choice experiment was used. Attributes and levels of respite care were informed by a literature review and expert consultations. A fractional factorial design was used to reduce the number of choice sets. A questionnaire survey was conducted in Tianjin, China. A mixed logit model was used to compute coefficients for attributes and levels. Respite care packages differed in five attributes, which were content, provider, duration, frequency, and cost. 322 caregivers completed valid discrete choice experiment questionnaires. All five attributes were statistically significant. Two most preferred attributes were “providers” (coefficient 1.297,

p
<
0.001

) and “frequency” (coefficient 1.169,

p
<
0.001

). Caregivers prefer highly qualified service providers and frequent respite care. The desirable respite care for caregivers would be assistance with personal care for people with dementia which was provided by an experienced worker with attitudes of understanding and respect towards people with dementia more than 3 times per week regularly and more than 4 h every time with a lower cost. This study offered new information on Chinese dementia caregivers’ preferences for respite care. Policymakers should pay attention to the frequency and quality of providers when designing respite care to improve service uptake and ultimately lighten the burden on caregivers of people with dementia.
Schistosomiasis Involving the Central Nervous System: Case Report of a Rare Complication
Authors: Alanazi Rahaf F. , Al Karawi Maryam , Almalki Abdulrahman , Sufiani Fahd , Al Karawi Sarmad
Published: December 2023

Introduction. Schistosomiasis is a parasitic infection caused by schistosome invasion of blood circulation. Neuroschistosomiasis is a severe cerebral complication that accounts for less than 2.3% of reported cases. Patients present with progressive encephalitis, seizures, or both. Management includes antiparasitic medications, steroids, and surgical intervention. Case Presentation. We report a case of a 44-year-old female who presented to the ER with a history of transient loss of consciousness (LOC) and seizure. Radiological investigations revealed a right frontal brain lesion. Histopathological results confirmed the diagnosis of schistosomiasis. Conclusion. Schistosomiasis is a parasitic infection commonly diagnosed in patients who live in tropical areas. Early diagnosis with radiological and histopathological evaluation is required to identify patients at risk of developing severe neurological complications.
Supplementary Table S3 from Oncogenic KRAS Drives Lipofibrogenesis to Promote Angiogenesis and Colon Cancer Progression
Authors: Hsu Wen-Hao , LaBella Kyle A. , Lin Yiyun , Xu Ping , Lee Rumi , Hsieh Cheng-En , Yang Lei , Zhou Ashley , Blecher Jonathan M. , Wu Chang-Jiun , Lin Kangyu , Shang Xiaoying , Jiang Shan , Spring Denise J. , Xia Yan , Chen Peiwen , Shen John Paul , Kopetz Scott , DePinho Ronald A.
Published: December 2023

Supplementary Table S3 contains the predicted TFs on pro-adipogenic cytokines' promoter
Supplementary Figure 7 from Formate Supplementation Enhances Antitumor CD8+ T-cell Fitness and Efficacy of PD-1 Blockade
Authors: Rowe Jared H. , Elia Ilaria , Shahid Osmaan , Gaudiano Emily F. , Sifnugel Natalia E. , Johnson Sheila , Reynolds Amy G. , Fung Megan E. , Joshi Shakchhi , LaFleur Martin W. , Park Joon Seok , Pauken Kristen E. , Rabinowitz Joshua D. , Freeman Gordon J. , Haigis Marcia C. , Sharpe Arlene H.
Published: December 2023

Supplementary Figure 7 shows individual mouse growth curves from those depicted in main Figure 4.
Supplementary Figure 11 from Formate Supplementation Enhances Antitumor CD8+ T-cell Fitness and Efficacy of PD-1 Blockade
Authors: Rowe Jared H. , Elia Ilaria , Shahid Osmaan , Gaudiano Emily F. , Sifnugel Natalia E. , Johnson Sheila , Reynolds Amy G. , Fung Megan E. , Joshi Shakchhi , LaFleur Martin W. , Park Joon Seok , Pauken Kristen E. , Rabinowitz Joshua D. , Freeman Gordon J. , Haigis Marcia C. , Sharpe Arlene H.
Published: December 2023

Supplementary Figure 11 shows single cell RNA sequencing analysis for tumor infiltrating CD8+ T cells following formate and/or anti-PD-1 antibody treatment.
Supplementary Figure S5 from p53 Gain-of-Function Mutation Induces Metastasis via BRD4-Dependent CSF-1 Expression
Authors: Efe Gizem , Dunbar Karen J. , Sugiura Kensuke , Cunningham Katherine , Carcamo Saul , Karaiskos Spyros , Tang Qiaosi , Cruz-Acuña Ricardo , Resnick-Silverman Lois , Peura Jessica , Lu Chao , Hasson Dan , Klein-Szanto Andres J. , Taylor Alison M. , Manfredi James J. , Prives Carol , Rustgi Anil K.
Published: December 2023

Supplementary Figure S5. CSF-1/CSF-1R signaling associates positively with clinical outcomes, and leukocyte infiltration ESCC.
Supplementary Figure S1 from p53 Gain-of-Function Mutation Induces Metastasis via BRD4-Dependent CSF-1 Expression
Authors: Efe Gizem , Dunbar Karen J. , Sugiura Kensuke , Cunningham Katherine , Carcamo Saul , Karaiskos Spyros , Tang Qiaosi , Cruz-Acuña Ricardo , Resnick-Silverman Lois , Peura Jessica , Lu Chao , Hasson Dan , Klein-Szanto Andres J. , Taylor Alison M. , Manfredi James J. , Prives Carol , Rustgi Anil K.
Published: December 2023

Supplementary Figure S1. Characterization of the primary and metastatic mouse ESCC cell lines.
Re-“Formate” T-cell Antitumor Responses
Authors: Lin Mei-Chun , Moller Sofie Hedlund , Ho Ping-Chih
Published: December 2023

Rowe and colleagues discover that one-carbon (1C) metabolism rewiring occurs upon T-cell activation to support proliferation and cytolytic activity in CD8+ T cells and that supplementation of 1C donor formate rescues the dysfunctional T cells and their responsiveness to anti–PD-1 in selective tumor-infiltrated T-cell subsets. This finding represents an attractive strategy to overcome a metabolic vulnerability in the tumor microenvironment and improve the efficacy of immune checkpoint blockade.

See related article by Rowe et al., p. 2566 (8).
Noninvasive and Multicancer Biomarkers: The Promise of LINE-1 Retrotransposons
Authors: Doucet Aurelien J. , Cristofari Gael
Published: December 2023

LINE-1 retrotransposons are frequently active in epithelial tumors. In a new study, Taylor, Wu and colleagues now describe that one of the proteins encoded by LINE-1 elements, ORF1p, is detected in the bloodstream of patients with cancer, and can be used as a noninvasive and multicancer biomarker for diagnosis or treatment monitoring.

See related article by Taylor, Wu et al., p. 2532 (7).
Supplementary Figure 18 from Activating Transcription Factor 5 Promotes Neuroblastoma Metastasis by Inducing Anoikis Resistance
Authors: Banerjee Debarshi , Boboila Shuobo , Okochi Shunpei , Angelastro James M. , Kadenhe-Chiweshe Angela V. , Lopez Gonzalo , Califano Andrea , Connolly Eileen P. , Greene Lloyd A. , Yamashiro Darrell J.
Published: December 2023

Supplementary Figure 18 shows that CP-d/n-ATF5 treatment decreased viability and induced anoikis of SK-N-DZ CTCs
Supplementary Figure 12 from Activating Transcription Factor 5 Promotes Neuroblastoma Metastasis by Inducing Anoikis Resistance
Authors: Banerjee Debarshi , Boboila Shuobo , Okochi Shunpei , Angelastro James M. , Kadenhe-Chiweshe Angela V. , Lopez Gonzalo , Califano Andrea , Connolly Eileen P. , Greene Lloyd A. , Yamashiro Darrell J.
Published: December 2023

Supplementary Figure 12 shows that CP-d/n-ATF5 inhibits the growth of MYCN-amplified and MYCN-non-amplified cell lines in a dose-dependent manner
FIGURE 1 from Activating Transcription Factor 5 Promotes Neuroblastoma Metastasis by Inducing Anoikis Resistance
Authors: Banerjee Debarshi , Boboila Shuobo , Okochi Shunpei , Angelastro James M. , Kadenhe-Chiweshe Angela V. , Lopez Gonzalo , Califano Andrea , Connolly Eileen P. , Greene Lloyd A. , Yamashiro Darrell J.
Published: December 2023

Elevated ATF5 expression correlates with poor outcomes in patients with neuroblastoma, and ATF5 silencing prolongs survival and inhibits metastatic progression in neuroblastoma-bearing mice. A, Violin plots of ATF5 expression in high-risk MYCN-amplified (MNA, red), high-risk MYCN-non-amplified (HR_NA, yellow), and low-risk stage 1 (LR_S1, green) patients. For SEQC, MNA = 92, HR_NA = 83, LR_S1 = 118. For TARGET, MNA = 68, HR_NA = 145, LR_S1 = 30. Expression data: SEQC (from GEO: GSE49711): https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49711; ref. 28); TARGET: HumanExon arrays (29). B, Kaplan–Meier curve depicting the corresponding increase in poor outcome with increasing ATF5 expression. The P value was calculated using a Cox proportional hazards model after removing stage 1 patient samples, Wald test, P = 1.57E-14. C, Bioluminescent images at day 10 and day 23 of mice bearing Dox-inducible BE(2)-C-shATF5-2 renal xenograft tumors and treated with or without Dox. D, Kaplan–Meier plot of mice bearing Dox-inducible BE(2)-C-shATF5-2 renal xenograft tumors with ATF5 knocked down (+ Dox, n = 10) or not (− Dox, n = 11). P = 0.0083, log-rank (Mantel–Cox). E,Ex vivo bioluminescent images of the liver at the time of euthanasia. F, Quantification of total flux (photons/second) by ex vivo liver bioluminescence at the time of euthanasia. G, Quantification of bone marrow metastases from bioluminescence of bone marrow homogenate (RLU/# BM cells) at the time of euthanasia. RLU: relative luciferase unit. H, Quantification of bioluminescence from blood representing the number of CTCs at the time of euthanasia. *, P < 0.05.
Entrectinib Response to ROS1-Fusion-Positive Non-Small-Cell Lung Cancer That Progressed on Crizotinib with Leptomeningeal Metastasis: A Case Report
Authors: Sawada Hiromune , Taniguchi Yuri , Iizuka Shin , Ikeda Toshiki , Aga Masaharu , Hamakawa Yusuke , Miyazaki Kazuhito , Misumi Yuki , Agemi Yoko , Nakamura Yukiko , Maeda Koki , Shimokawa Tsuneo , Okamoto Hiroaki
Published: December 2023

Introduction: C-ros oncogene 1 (ROS1) translocation is an oncogenic driver-mutation identified in 1–2% of non-small-cell lung cancer (NSCLC) cases. Although crizotinib, a tyrosine kinase inhibitor (TKI) against ALK/ROS1, is known to be effective against ROS1-fusion-positive NSCLC, such cases sometimes progress with brain metastases. The most frequently reported crizotinib-resistance mutation is ROS1 G2032R, and some studies have found that even newly developed ROS1 TKIs, such as entrectinib and lorlatinib, show a decreased efficacy against it. The optimal therapies for ROS1-fusion-positive NSCLC and how such cases can be sequenced have not yet been established. Case Presentation: We herein report a patient with ROS1-fusion-positive NSCLC diagnosed at 34 years old. Crizotinib was started at the diagnosis and switched after 25 months to cisplatin/pemetrexed/bevacizumab once the disease progressed with multiple brain metastases that were resistant to stereotactic radiation therapy. The cytotoxic chemotherapy stabilized the patient’s condition for 17 months until he developed leptomeningeal metastasis (LM). He underwent lumboperitoneal shunting and whole-brain radiotherapy, followed by crizotinib re-administration. Despite crizotinib treatment, his neurological symptoms, such as double vision, headache, weakness in the legs, and walking difficulties, progressed. Eventually, subsequent entrectinib treatment was initiated, which resolved all of the symptoms mentioned above. Regrettably, liquid next-generation sequencing had failed to detect the resistance mechanism due to minimal ctDNA in this case. Conclusion: These findings imply that sequential entrectinib administration may be effective in patients with disease progression limited to central nervous system metastases during crizotinib administration.
Compromised Accuracy of Stereotactic Target Delineation Associated with Computed Tomography-Based Frame Registration: A Comparative Analysis of Magnetic Resonance Imaging-Computed Tomography Fusion
Authors: Kim Junhyung , Jang Sunwoo , Hong Seok Ho , Jeon Sang Ryong
Published: December 2023

Introduction: Recent advancements in stereotactic neurosurgical techniques have become increasingly reliant on image-based target planning. We devised a case-phantom comparative analysis to evaluate the target registration errors arising during the magnetic resonance imaging (MRI)-computed tomography (CT) image fusion process. Methods: For subjects whose preoperative MRI and CT images both contained fiducial frame localizers, we investigated discrepancies in target coordinates derived from frame registration based on either MRI or CT. We generated a phantom target through an image fusion process, merging the framed CT images with their corresponding reference MRIs after masking their fiducial indicators. This phantom target was then compared with the original during each instance of target planning. Results: In our investigative study with 26 frame registrations, a systematic error in the y-axis was observed as −0.89 ± 0.42 mm across cases using either conventional CT and/or cone-beam CT (O-arm). For the z-axis, errors varied on a case-by-case basis, recording at +0.64 ± 1.09 mm with a predominant occurrence in those merged with cone-beam CT. Collectively, these errors resulted in an average Euclidean error of 1.33 ± 0.93 mm. Conclusion: Our findings suggest that the accuracy of frame-based stereotactic planning is potentially compromised during MRI-CT fusion process. Practitioners should recognize this issue, underscoring a pressing need for strategies and advancements to optimize the process.