bluuebunny/crossref_metadata_2025_split huggingface dataset:
The Holon Approach for Simultaneously Tuning Multiple Components in a Self-Driving Database Management System with Machine Learning via Synthesized Proto-Actions
Authors: Zhang William , Lim Wan Shen , Butrovich Matthew , Pavlo Andrew 
Published: August 2024

Existing machine learning (ML) approaches to automatically optimize database management systems (DBMSs) only target a single configuration space at a time (e.g., knobs, query hints, indexes). Simultaneously tuning multiple configuration spaces is challenging due to the combined space's complexity. Previous tuning methods work around this by sequentially tuning individual spaces with a pool of tuners. However, these approaches struggle to coordinate their tuners and get stuck in local optima.
This paper presents the Proto-X framework that holistically tunes multiple configuration spaces. The key idea of Proto-X is to identify similarities across multiple spaces, encode them in a high-dimensional model, and then synthesize "proto-actions" to navigate the organized space for promising configurations. We evaluate Proto-X against state-of-the-art DBMS tuning frameworks on tuning PostgreSQL for analytical and transactional workloads. By reasoning about configuration spaces that are orders of magnitude more complex than other frameworks (both in terms of quantity and variety), Proto-X discovers configurations that improve PostgreSQL's performance by up to 53% over the next best approach.
LITS: An Optimized Learned Index for Strings
Authors: Yang Yifan , Chen Shimin 
Published: August 2024

Index is an important component in database systems. Learned indexes have been shown to outperform traditional tree-based index structures for fixed-sized integer or floating point keys. However, the application of the learned solution to variable-length string keys is under-researched. Our experiments show that existing learned indexes for strings fail to outperform traditional string indexes, such as HOT and ART. String keys are long and variable sized, and often contain skewed prefixes, which make the last-mile search expensive, and adversely impact the capability of learned models to capture the skewed distribution of string keys.
In this paper, we propose a novel learned index for string keys, LITS (Learned Index with Hash-enhanced Prefix Table and Subtries). We propose an optimized learned model, combining a global Hash-enhanced Prefix Table (HPT) and a per-node local linear model to better distinguish string keys. Moreover, LITS exploits compact leaf nodes and hybrid structures with a PMSS model for efficient point and range operations. Our experimental results using eleven string data sets show that LITS achieves up to 2.43x and 2.27x improvement over HOT and ART for point operations, and attains comparable scan performance.
Hit the Gym: Accelerating Query Execution to Efficiently Bootstrap Behavior Models for Self-Driving Database Management Systems
Authors: Lim Wan Shen , Ma Lin , Zhang William , Butrovich Matthew , Arch Samuel , Pavlo Andrew 
Published: August 2024

Autonomous database management systems (DBMSs) aim to optimize themselves automatically without human guidance. They rely on machine learning (ML) models that predict their run-time behavior to evaluate whether a candidate configuration is beneficial without the expensive execution of queries. However, the high cost of collecting the training data to build these models makes them impractical for real-world deployments. Furthermore, these models are instance-specific and thus require retraining whenever the DBMS's environment changes. State-of-the-art methods spend over 93% of their time running queries for training versus tuning.
To mitigate this problem, we present the Boot framework for automatically accelerating training data collection in DBMSs. Boot utilizes macro- and micro-acceleration (MMA) techniques that modify query execution semantics with approximate run-time telemetry and skip repetitive parts of the training process. To evaluate Boot, we integrated it into a database gym for PostgreSQL. Our experimental evaluation shows that Boot reduces training collection times by up to 268× with modest degradation in model accuracy. These results also indicate that our MMA-based approach scales with dataset size and workload complexity.
Why TPC is Not Enough: An Analysis of the Amazon Redshift Fleet
Authors: van Renen Alexander , Horn Dominik , Pfeil Pascal , Vaidya Kapil , Dong Wenjian , Narayanaswamy Murali , Liu Zhengchun , Saxena Gaurav , Kipf Andreas , Kraska Tim 
Published: August 2024

Database research and development is heavily influenced by benchmarks, such as the industry-standard TPC-H and TPC-DS for analytical systems. However, these twenty-year-old benchmarks neither capture how databases are deployed nor what workloads modern cloud data warehouse systems face these days.
In this paper, we summarize well-known, confirm suspected, and unearth novel discrepancies between TPC-H/DS and actual workloads using empirical data. We base our analysis on telemetrics from Amazon Redshift - one of the largest cloud data warehouse deployments. Among others, we show how write-heavy data pipelines are prominent, workloads vary over time (in both load and type), queries are repetitive, and how most properties of queries or workloads experience very long tailed distributions. We conclude that data warehouse benchmarks, just like database systems, need to become more holistic and stop focusing solely on query engine performance. Finally, we publish a dataset containing query statistics of 200 randomly selected Redshift serverless and provisioned instances (each) over a three-month period, as a basis for building more realistic benchmarks.
Medication improves velocity, reaction time, and movement time but not amplitude or error during memory‐guided reaching in Parkinson's disease
Authors: Trevarrow Michael P. , Munoz Miranda J. , Rivera Yessenia M. , Arora Rishabh , Drane Quentin H. , Pal Gian D. , Verhagen Metman Leonard , Goelz Lisa C. , Corcos Daniel M. , David Fabian J. 
Published: August 2024

AbstractThe motor impairments experienced by people with Parkinson's disease (PD) are exacerbated during memory‐guided movements. Despite this, the effect of antiparkinson medication on memory‐guided movements has not been elucidated. We evaluated the effect of antiparkinson medication on motor control during a memory‐guided reaching task with short and long retention delays in participants with PD and compared performance to age‐matched healthy control (HC) participants. Thirty‐two participants with PD completed the motor section of the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS‐UPDRS III) and performed a memory‐guided reaching task with two retention delays (0.5 s and 5 s) while on and off medication. Thirteen HC participants completed the MDS‐UPDRS III and performed the memory‐guided reaching task. In the task, medication increased movement velocity, decreased movement time, and decreased reaction time toward what was seen in the HC. However, movement amplitude and reaching error were unaffected by medication. Shorter retention delays increased movement velocity and amplitude, decreased movement time, and decreased error, but increased reaction times in the participants with PD and HC. Together, these results imply that antiparkinson medication is more effective at altering the neurophysiological mechanisms controlling movement velocity and reaction time compared with other aspects of movement control.
The analgesic effect of paeoniflorin: A focused review
Authors: Li Mingzhu , Zhu Xudong , Zhang Mingxue , Yu Jun , Jin Shengbo , Hu Xiaoli , Piao Haozhe 
Published: August 2024

Abstract
Pain has been a prominent medical concern since ancient times. Despite significant advances in the diagnosis and treatment of pain in contemporary medicine, there is no a therapeutic cure for chronic pain. Chinese herbaceous peony, a traditional Chinese analgesic herb has been in clinical use for millennia, with widespread application and substantial efficacy. Paeoniflorin (PF), the main active ingredient of Chinese herbaceous peony, has antioxidant, anti-inflammatory, anticancer, analgesic, and antispasmodic properties, among others. The analgesic effect of PF, involving multiple critical targets and pain regulatory pathways, has been a hot spot for current research. This article reviews the literature related to the analgesic effect of PF in the past decade and discusses the molecular mechanism of the analgesic effect of PF, including the protective effects of nerve cells, inhibition of inflammatory reactions, antioxidant effects, reduction of excitability in nociceptor, inhibition of the nociceptive excitatory neuroreceptor system, activation of the nociceptive inhibitory neuroreceptor system and regulation of other receptors involved in nociceptive sensitization. Thus, providing a theoretical basis for pain prevention and treatment research. Furthermore, the prospect of PF-based drug development is presented to propose new ideas for clinical analgesic therapy.
Assessment of Se, As, Cd, Cr, Hg, and Pb content status in Ankang tea plantations of China
Authors: Ji Huawei , Lin Pingxuan , Wang Hui , Chen Jiping , Ren Rui , Li Aorui 
Published: August 2024

Abstract
Selenium (Se) is an essential trace element for humans. The Ankang tea plantation area in China is the best place for producing high-quality and Se-enriched organic tea. However, accumulation of potentially toxic elements (PTEs) in soil and tea leaves has attracted a lot of attention. Therefore, in this research, the content status of Se and five PTEs (As, Cd, Cr, Hg, and Pb) in soil and tea leaf samples collected from 88 Ankang tea plantations was studied. Results showed that the average Se content was 0.17 mg kg
−1 and the Se-enrichment rate was 25% for the 88 tea leaf samples, and As, Cd, Cr, Hg, and Pb contents in all tea leaf samples met the Chinese standard for pollution-free tea except for 11.2% excess Cr in only one sample. Cd concentrations in 56.82% soil samples exceeded the Chinese risk screening value for soil contamination of the agricultural land, and therefore the pollution degree of Cd is high in these soil samples. Moreover, the Hakanson potential ecological risk assessment of soil As, Cd, Cr, Hg, and Pb indicated that the Ankang tea plantation area was at a medium potential ecological risk level. These results will provide theoretical support for ecological risk management and safe production of Se-enriched tea in Ankang Se-enriched tea plantations.
Artificial neural network infused quasi oppositional learning partial reinforcement algorithm for structural design optimization of vehicle suspension components
Authors: Sait Sadiq M. , Mehta Pranav , Pholdee Nantiwat , Yıldız Betül Sultan , Yıldız Ali Rıza 
Published: August 2024

Abstract
This paper introduces and investigates an enhanced Partial Reinforcement Optimization Algorithm (E-PROA), a novel evolutionary algorithm inspired by partial reinforcement theory to efficiently solve complex engineering optimization problems. The proposed algorithm combines the Partial Reinforcement Optimization Algorithm (PROA) with a quasi-oppositional learning approach to improve the performance of the pure PROA. The E-PROA was applied to five distinct engineering design components: speed reducer design, step-cone pulley weight optimization, economic optimization of cantilever beams, coupling with bolted rim optimization, and vehicle suspension arm optimization problems. An artificial neural network as a metamodeling approach is used to obtain equations for shape optimization. Comparative analyses with other benchmark algorithms, such as the ship rescue optimization algorithm, mountain gazelle optimizer, and cheetah optimization algorithm, demonstrated the superior performance of E-PROA in terms of convergence rate, solution quality, and computational efficiency. The results indicate that E-PROA holds excellent promise as a technique for addressing complex engineering optimization problems.
Policy Actors’ Struggle for Attention: The Role of Peer Networks in the Migration Discourse on Twitter (X)
Authors: Hanke Sara , Sicakkan Hakan G. , Van Wolleghem Pierre Georges , Heiberger Raphael Heiko 
Published: August 2024

Abstract
Policy actors (PAs) like nongovernmental organizations, political parties or governmental institutions strategically communicate on social media to gain attention and thus influence the public agenda. We argue that networks of PAs engaged in the same issues (i.e., a PA’s peer network) are crucial to attracting the interest of a broad audience. Drawing on network theory, we posit that (i) ideological homophily, and (ii) the centrality and embeddedness in a PA’s peer network increase the attention received from all Twitter (now X) users. We investigate these premises by analyzing the European migration discourse on Twitter (2014–2020). The results of our study reveal that the centrality of PAs in their peer networks and ideologically similar relations considerably increase attention from the whole Twittersphere. These findings provide strong evidence that a PA’s role in its organizational peer network on social media governs the attention received in the overall discourse.
Influence mechanism of paper mechanical properties: numerical simulation and experimental verification based on a fiber network
Authors: Sun Hao , Wang Yaling , Li Haojin , Wei Lingjun , Zhu Yunfeng , Zhang Wanlu , Wang Wei 
Published: August 2024

Abstract
Paper is a kind of renewable material that exists widely and has important application prospects. However, previous studies have mostly focused on the macromechanical properties of paper but lack micro theory based on paper fiber networks. We present a comprehensive experimental and computational study on the mechanical properties of fibers and fiber networks under the influence of microstructure. A beam-spring model was established based on a beam-fiber network to simulate the behavior of fiber networks. Simulations were performed to demonstrate the influence of fiber microstructural parameters such as fiber bond strength, stiffness, failure strength, size, and network density on mechanical features. Mechanical experiments verified that the fiber bond strength had a greater influence on the paper properties than did the fiber strength. This result is highly consistent with that of the model. All the simulations were validated by experimental measurements. Finally, we provided computational insights into the interfiber bond damage pattern with respect to different fiber microlevels and demonstrated that the proposed beam-spring model can be used to predict the response of fiber networks of paper materials. The above research can be used to optimize the formulation, process, and treatment of paper to meet specific application needs.
Spilled Wine, Spilled Blood: Spilling the Secrets of the Covered Cup from the Chungul Kurgan
Authors: Woodfin Warren T. 
Published: August 2024

Abstract
The covered cup, discovered in 1981 during the salvage excavation of a burial mound in southern Ukraine, is an impressive example of secular metalwork from around 1200. The cup’s interior contains a cast silver-gilt lion and a hitherto undetected siphon mechanism, making it one of the first preserved automata from Europe and the earliest known Western medieval example of this type of trick vessel. The cup from the Chungul Kurgan helps to clarify the probable operation of the chantepleure illustrated in the sketchbook of Villard de Honnecourt and sheds light on possible other medieval automata. The cup’s presence in the same burial with other works from the same approximate date and region suggests historical circumstances that might have resulted in its burial with a nomadic leader in the steppe.
Iodine supply and thyroid function in women with gestational diabetes mellitus: a cohort study
Authors: Vítková Hana , Anderlová Kateřina , Krátký Jan , Bílek Radovan , Springer Drahomíra , Votava Felix , Brutvan Tomáš , Krausová Adéla , Žabková Kristýna , Potluková Eliška , Jiskra Jan 
Published: August 2024

Introduction
Maternal urinary iodine concentration and blood neonatal thyroid-stimulating hormone (TSH) concentration reflect iodine status in pregnancy and serve as markers of iodine deficiency. As dietary measures in gestational diabetes mellitus (GDM) could affect iodine intake, our study aimed to investigate iodine supply in women with GDM compared to healthy pregnant women and to evaluate its relationship to maternal and neonatal thyroid function.

Methods
Urinary iodine concentration (UIC) and serum TSH, free thyroxine (FT4), and autoantibodies against thyroid peroxidase (TPOAb) were analyzed in 195 women with GDM and 88 healthy pregnant women in the second trimester. Subsequently, neonatal TSH concentrations measured 72 h after delivery in a subgroup of 154 newborns (115 of mothers with GDM and 39 controls) from the national register were analyzed.

Results
Median UIC was significantly lower in women with GDM compared to controls (89.50 µg/L vs. 150.05 µg/L; P < 0.001). Optimal iodine intake was found only in nine women with GDM (4.6%) and 33 healthy pregnant women (37.5%) (P < 0.001). Most pregnant women with GDM (88.7%) compared to one half of controls (50%) had iodine deficiency (P < 0.001). Although serum TSH and the prevalence of hypothyroidism (TSH > 4.0 mIU/L) were not different in both groups, hypothyroxinaemia was more prevalent in GDM compared to controls (12.3% vs 3.4%, P = 0.032). Consistently, neonatal TSH > 5.0 mIU/L indicating iodine deficiency, was found in 6 (5.2%) newborns of women with GDM as compared to none in controls. In women with GDM, the prevalence of perinatal complications was significantly lower in those who were taking dietary iodine supplements compared to those who were not (3/39 (7.69%) vs 46/156 (28.85%), P <0.001). In the multiple logistic and linear regression models in women with GDM, hypothyroxinaemia was associated with preterm births, and a negative association of serum FT4 and HbA1c was found.

Conclusion
Iodine deficiency in pregnancy was more prevalent among women with GDM compared to healthy pregnant controls. Serum FT4 negatively correlated with HbA1c, and hypothyroxinaemia was associated with preterm births in women with GDM. Conversely, women with GDM who used dietary iodine supplements had a lower risk of perinatal complications.
Linking the natural man to the res publica in the works of Marcus Tullius Cicero
Authors: Hamza Gábor 
Published: August 2024

AbstractThere is no consensus on the importance of Cicero's doctrine of the state (res publica) among the prominent figures and scholars of political theory. In our view, the main reason for this is that the discussion of the political theoretical insights of the corpus Ciceronianum is too often reduced to a repetition of stereotypes. Cicero's key works on political doctrine, such as the De oratore, the De re publica and the De officiis, are mostly analysed from a philosophical point of view, with historical and legal aspects being put to one side. The characteristics of the mixed constitution (mikte politeia), which is at the heart of Cicero's theory of the res publica, are only superficially examined. What is also mostly overlooked is the extremely significant fact that in the De re publica Cicero (unlike Plato, for example) not only develops a philosophically grounded theory of the state, the res publica, but also applies his theory to finding the state, and in particular its ideal form, the optimus status civitatis, in the historical reality of Rome, that is, his own state. In this way, Cicero connects ratio and res, thus establishing the harmony and, indeed, unity of idea and history. The value of this important idea is not in the least affected by the fact that Cicero was undoubtedly an eclectic thinker rather than a consistent exponent of the views of any school or current. That, it seems to us, helped him greatly to lay the foundations of a doctrine of the state that could influence political thought centuries, even millennia, later, up to the political thought of the first decades of the 21st century.
Quality Management In Ready-Mix Concrete Production In Zambia
Authors: Bweupe Arthur S. , Mwiya Balimu 
Published: August 2024

The construction industry, a significant contributor to global economies, is projected to yield substantial economic output by 2030 of around $135 trillion. Central to construction is concrete, a widely used material. Ready-mix concrete (RMC), a specialised form of concrete, is gaining prominence due to its rapid setting and superior quality. In Zambia, the increasing demand for RMC highlights the need for stringent quality management to hedge potential structural risks. This study aimed to determine the quality management in ready-mix concrete production in Zambia. Employing a parallel convergent mixed-methods research design to achieve the objectives, qualitative data was collected through semi-structured interviews and desk study and quantitative data was gathered through a structured questionnaire and an observation checklist. The findings of the study reveal that while guidelines exist, adherence varies. Regulatory bodies for standards, engineering and construction play pivotal roles in overseeing RMC quality. However, their execution faces inconsistencies and challenges due to limited resources and a lack of sense of responsibility. Quality control practices were investigated unveiling variations in forward, immediate, and retrospective control phases. Notable trends in proper storage and equipment calibration showed a commitment to precision. Immediate control practices, encompassing sampling and non-compliance management, demonstrated both positive aspects and areas for improvement. Retrospective control showed commitment to comprehensive strength testing and minimal towards split cylinder testing and on-site slump evaluation. In the realm of quality assurance (QA), RMC facilities show substantial adherence to documented QA standard operating procedures and thorough raw material inspections. However, deficiencies in batching and mixing practices and limited adoption of modern weighing systems require improvement. The study recommends creating an industry association for collaboration, enhancing standardised practices, introducing third-party quality audits, and proposing compulsory RMC standards to boost progress in the Zambian RMC industry.
Key Words: Quality Management, Ready Mix Concrete, Observation, Desk Study, Zambia.
Shaping the Digital Fashion Industry with Generation Z’s Buying Behavior
Authors: Susanto Prayataneswara Dwiputri , Pangaribuan Christian Haposan , Tjhin Santo 
Published: August 2024

Abstract: Marketing forms have evolved over time, and as the world transitions into a new generation of audiences and consumption behaviors, marketing has gone from the traditional to the more essential digital form, with the use of social media technology such as Instagram and Facebook. The main objective of this study is to empirically examine how hedonic motives, emotional response, and involvement in fashion can impact impulsive buying in the fashion industry within Generation Z. In this context, data were collected from 100 respondents in the age range of 16 to 23 years in the greater areas of Jakarta and Surabaya through an online survey. The data were then tested and finally analyzed. The most influential determinants affecting impulse buying are involvement in fashion, followed by hedonic motives, and emotional response. Even though the scarcity factor fills the gap created by prior studies’ inconsistencies, it fails to moderate the link between emotional response and impulse buying. Keywords: Impulse buying, Hedonic behavior, Emotional response, Involvement in fashion, Scarcity