bluuebunny/crossref_metadata_2025 huggingface dataset:
CaaS-LSM: Compaction-as-a-Service for LSM-based Key-Value Stores in Storage Disaggregated Infrastructure
Authors: Yu Qiaolin , Guo Chang , Zhuang Jay , Thakkar Viraj , Wang Jianguo , Cao Zhichao
Published: May 2024

Optimizing LSM-based Key-Value Stores (LSM-KVS) for disaggregated storage is essential to achieve better resource utilization, performance, and flexibility. Most of the existing studies focus on offloading the compaction to the storage nodes to mitigate the performance penalties caused by heavy network traffic between computing and storage. However, several critical issues are not addressed including the strong dependency between offloaded compaction and LSM-KVS, resource load-balancing, compaction scheduling, and complex transient errors.

To address the aforementioned issues and limitations, in this paper, we propose CaaS-LSM, a novel disaggregated LSM-KVS with a new idea of Compaction-as-a-Service. CaaS-LSM brings three key contributions. First, CaaS-LSM decouples the compaction from LSM-KVS and achieves stateless execution to ensure high flexibility and avoid coordination overhead with LSM-KVS. Second, CaaS-LSM introduces a performance- and resource-optimized control plane to guarantee better performance and resource utilization via an adaptive run-time scheduling and management strategy. Third, CaaS-LSM addresses different levels of transient and execution errors via sophisticated error-handling logic. We implement the prototype of CaaS-LSM based on RocksDB and evaluate it with different LSM-based distributed databases (Kvrocks and Nebula). In the storage disaggregated setup, CaaS-LSM achieves up to 8X throughput improvement and reduces the P99 latency up to 98% compared with the conventional LSM-KVS, and up to 61% of improvement compared with state-of-the-art LSM-KVS optimized for disaggregated storage.
Counterfactual Explanation at Will, with Zero Privacy Leakage
Authors: An Shuai , Cao Yang
Published: May 2024

While counterfactuals have been extensively studied as an intuitive explanation of model predictions, they still have limited adoption in practice due to two obstacles: (a) They rely on excessive access to the model for explanation that the model owner may not provide; and (b) counterfactuals carry information that adversarial users can exploit to launch model extraction attacks. To address the challenges, we propose CPC, a data-driven approach to counterfactual. CPC works at the client side and gives full control and right-to-explain to model users, even when model owners opt not to. Moreover, CPC warrants that adversarial users cannot exploit counterfactuals to extract models. We formulate properties and fundamental problems underlying CPC, study their complexity and develop effective algorithms. Using real-world datasets and user study, we verify that CPC does prevent adversaries from exploiting counterfactuals for model extraction attacks, and is orders of magnitude faster than existing explainers, while maintaining comparable and often higher quality.
DecoPa: Query Decomposition for Parallel Complex Event Processing
Authors: Akili Samira , Purtzel Steven , Weidlich Matthias
Published: May 2024

Systems for Complex Event Processing (CEP) enable the detection of predefined patterns in event streams. While the evaluation of CEP queries is computationally hard, scalability may be achieved by parallelization. Yet, existing approaches for parallel CEP are driven by static query properties, such as partitioning keys and states of the evaluation model. They largely neglect the rates with which processing units may ingest and compare events for query evaluation.

In this paper, we present an approach for parallel CEP that is based on a flexible decomposition of CEP queries. Our idea is to guide the decomposition by the sustainable throughput of each processing unit, in order to maximize the overall performance. To this end, we introduce DecoPa plans for parallel CEP, provide a cost model for them, elaborate on their correctness and optimality, and present an algorithm for their construction. Experiments using a DecoPa implementation in Flink illustrate throughput gains of up to 12 orders of magnitude compared to state-of-the-art approaches.
Graph Summarization: Compactness Meets Efficiency
Authors: Chu Deming , Zhang Fan , Zhang Wenjie , Zhang Ying , Lin Xuemin
Published: May 2024

As the volume and ubiquity of graphs increase, a compact graph representation becomes essential for enabling efficient storage, transfer, and processing of graphs. Given a graph, the graph summarization problem asks for a compact representation that consists of a summary graph and the corrections, such that we can recreate the original graph from the representation exactly. Although this problem has been studied extensively, the existing works either trade summary compactness for efficiency, or vice versa. In particular, a well-known greedy method provides the most compact summary but incurs prohibitive time cost, while the state-of-the-art algorithms with practical overheads are more than 20% behind in summary compactness in our comparison with the greedy method.

This paper presents Mags and Mags-DM, two algorithms that aim to bridge the compactness and efficiency in graph summarization. Mags adopts the existing greedy paradigm that provides state-of-the-art compactness, but significantly improves its efficiency with a novel algorithm design. Meanwhile, Mags-DM follows a different paradigm with practical efficiency and overcomes its limitations in compactness. Moreover, both algorithms can support parallel computing environments. We evaluate Mags and Mags-DM on graphs up to billion-scale and demonstrate that they achieve state-of-the-art in both compactness and efficiency, rather than in one of them. Compared with the method that offers state-of-the-art compactness, Mags and Mags-DM have a small difference (< 0.1% and < 2.1%) in compactness. For efficiency, Mags is on average 11.1x and 4.2x faster than the two state-of-the-art algorithms with practical overheads, while Mags-DM can further reduce the running time by 13.4x compared with Mags. This shows that graph summarization algorithms can be made practical while still offering a compact summary.
Historical Embedding-Guided Efficient Large-Scale Federated Graph Learning
Authors: Li Anran , Chen Yuanyuan , Zhang Jian , Cheng Mingfei , Huang Yihao , Wu Yueming , Luu Anh Tuan , Yu Han
Published: May 2024

Graph convolutional networks (GCNs) are promising for graph learning tasks. For privacy-preserving graph learning tasks involving distributed graph datasets, federated learning (FL)-based GCN (FedGCN) training is required. An important open challenge for FedGCN is scaling to large graphs, which typically incurs 1) high computation overhead for handling the explosively-increasing number of neighbors, and 2) high communication overhead of training GCNs involving multiple FL clients. Thus, neighbor sampling is being studied to enhance the scalability of FedGCNs. Existing FedGCN training techniques with neighbor sampling often produce extremely large communication and computation overhead and inaccurate node embeddings, leading to poor model performance. To bridge this gap, we propose the Federated Adaptive Attention-based Sampling (FedAAS) approach. It achieves substantial cost savings by efficiently leveraging historical embedding estimators and focusing the limited communication resources on transmitting the most influential neighbor node embeddings across FL clients. We further design an adaptive embedding synchronization scheme to optimize the efficiency and accuracy of FedAAS on large-scale datasets. Theoretical analysis shows that the approximation error induced by the staleness of historical embedding is upper bounded, and the model is guaranteed to converge in an efficient manner. Extensive experimental evaluation against four state-of-the-art baselines on six real-world graph datasets show that FedAAS achieves up to 5.12% higher test accuracy, while saving communication and computation costs by 95.11% and 94.76%, respectively.
Nexus: Correlation Discovery over Collections of Spatio-Temporal Tabular Data
Authors: Gong Yue , Galhotra Sainyam , Castro Fernandez Raul
Published: May 2024

Causal analysis is essential for gaining insights into complex real-world processes and making informed decisions. However, performing accurate causal analysis on observational data is generally infeasible, and therefore, domain experts start exploration with the identification of correlations. The increased availability of data from open government websites, organizations, and scientific studies presents an opportunity to harness observational datasets in assisting domain experts during this exploratory phase.

In this work, we introduce Nexus, a system designed to align large repositories of spatio-temporal datasets and identify correlations, facilitating the exploration of causal relationships. Nexus addresses the challenges of aligning tabular datasets across space and time, handling missing data, and identifying correlations deemed "interesting". Empirical evaluation on Chicago Open Data and United Nations datasets demonstrates the effectiveness of Nexus in exposing interesting correlations, many of which have undergone extensive scrutiny by social scientists.
On Querying Historical Connectivity in Temporal Graphs
Authors: Song Jingyi , Wen Dong , Xu Lantian , Qin Lu , Zhang Wenjie , Lin Xuemin
Published: May 2024

We study the historical connectivity query in temporal graphs where edges continuously arrive. Given an arbitrary time window, and two query vertices, the problem aims to identify if two vertices are connected by a path in the snapshot of the window. The state-of-the-art method designs an index based on the two-hop cover, and updating the index is costly when new edges arrive. In this paper, we propose a new framework and design a novel forest-based index for historical connectivity queries. The index enables us to answer queries by searching if two vertices are connected in the forest. We update the index by modifying a forest structure. Our techniques also work for connectivity query processing in a sliding window of temporal graphs. Extensive experiments have been conducted to show the considerable advantages of our approach compared with the state-of-the-art methods in both historical connectivity queries and sliding-window connectivity queries.
SchemaPile: A Large Collection of Relational Database Schemas
Authors: Döhmen Till , Geacu Radu , Hulsebos Madelon , Schelter Sebastian
Published: May 2024

Access to fine-grained schema information is crucial for understanding how relational databases are designed and used in practice, and for building systems that help users interact with them. Furthermore, such information is required as training data to leverage the potential of large language models (LLMs) for improving data preparation, data integration and natural language querying. Existing single-table corpora such as GitTables provide insights into how tables are structured in-the-wild, but lack detailed schema information about how tables relate to each other, as well as metadata like data types or integrity constraints. On the other hand, existing multi-table (or database schema) datasets are rather small and attribute-poor, leaving it unclear to what extent they actually represent typical real-world database schemas.

In order to address these challenges, we present SchemaPile, a corpus of 221,171 database schemas, extracted from SQL files on GitHub. It contains 1.7 million tables with 10 million column definitions, 700 thousand foreign key relationships, seven million integrity constraints, and data content for more than 340 thousand tables. We conduct an in-depth analysis on the millions of schema metadata properties in our corpus, as well as its highly diverse language and topic distribution. In addition, we showcase the potential of \corpus to improve a variety of data management applications, e.g., fine-tuning LLMs for schema-only foreign key detection, improving CSV header detection and evaluating multi-dialect SQL parsers. We publish the code and data for recreating SchemaPile and a permissively licensed subset SchemaPile-Perm.
Language-Model Based Informed Partition of Databases to Speed Up Pattern Mining
Authors: Bobed Lisbona Carlos , Bernad Jordi , Maillot Pierre
Published: May 2024

Extracting interesting patterns from data is the main objective of Data Mining. In this context, Frequent Itemset Mining has shown its usefulness in providing insights from transactional databases, which, in turn, can be used to gain insights about the structure of Knowledge Graphs. While there have been a lot of advances in the field, due to the NP-hard nature of the problem, the main approaches still struggle when they are faced with large databases with large and sparse vocabularies, such as the ones obtained from graph propositionalizations. There have been efforts to propose parallel algorithms, but, so far, the goal has not been to tackle this source of complexity (i.e., vocabulary size), thus, in this paper, we propose to parallelize frequent itemset mining algorithms by partitioning the database horizontally (i.e., transaction-wise) while not neglecting all the possible vertical information (i.e., item-wise). Instead of relying on pure item co-appearance metrics, we advocate for the adoption of a different approach: modeling databases as documents, where each transaction is a sentence, and each item a word. In this way, we can apply recent language modeling techniques (i.e., word embeddings) to obtain a continuous representation of the database, clusterize it in different partitions, and apply any mining algorithm to them. We show how our proposal leads to informed partitions with a reduced vocabulary size and a reduced entropy (i.e., disorder). This enhances the scalability, allowing us to speed up mining even in very large databases with sparse vocabularies. We have carried out a thorough experimental evaluation over both synthetic and real datasets showing the benefits of our proposal.
Vexless: A Serverless Vector Data Management System Using Cloud Functions
Authors: Su Yongye , Sun Yinqi , Zhang Minjia , Wang Jianguo
Published: May 2024

Cloud functions, exemplified by AWS Lambda and Azure Functions, are emerging as a new computing paradigm in the cloud. They provide elastic, serverless, and low-cost cloud computing, making them highly suitable for bursty and sparse workloads, which are quite common in practice. Thus, there is a new trend in designing data systems that leverage cloud functions. In this paper, we focus on vector databases, which have recently gained significant attention partly due to large language models. In particular, we investigate how to use cloud functions to build high-performance and cost-efficient vector databases. This presents significant challenges in terms of how to perform sharding, how to reduce communication overhead, and how to minimize cold-start times.

In this paper, we introduce Vexless, the first vector database system optimized for cloud functions. We present three optimizations to address the challenges. To perform sharding, we propose a global coordinator (orchestrator) that assigns workloads to Cloud function instances based on their available hardware resources. To overcome communication overhead, we propose the use of stateful cloud functions, eliminating the need for costly communications during synchronization. To minimize cold-start overhead, we introduce a workload-aware Cloud function lifetime management strategy. Vexless has been implemented using Azure Functions. Experimental results demonstrate that Vexless can significantly reduce costs, especially on bursty and sparse workloads, compared to cloud VM instances, while achieving similar or higher query performance and accuracy.
Automated Data Visualization from Natural Language via Large Language Models: An Exploratory Study
Authors: Wu Yang , Wan Yao , Zhang Hongyu , Sui Yulei , Wei Wucai , Zhao Wei , Xu Guandong , Jin Hai
Published: May 2024

The Natural Language to Visualization (NL2Vis) task aims to transform natural-language descriptions into visual representations for a grounded table, enabling users to gain insights from vast amounts of data. Recently, many deep learning-based approaches have been developed for NL2Vis. Despite the considerable efforts made by these approaches, challenges persist in visualizing data sourced from unseen databases or spanning multiple tables. Taking inspiration from the remarkable generation capabilities of Large Language Models (LLMs), this paper conducts an empirical study to evaluate their potential in generating visualizations, and explore the effectiveness of in-context learning prompts for enhancing this task. In particular, we first explore the ways of transforming structured tabular data into sequential text prompts, as to feed them into LLMs and analyze which table content contributes most to the NL2Vis. Our findings suggest that transforming structured tabular data into programs is effective, and it is essential to consider the table schema when formulating prompts. Furthermore, we evaluate two types of LLMs: finetuned models (e.g., T5-Small) and inference-only models (e.g., GPT-3.5), against state-of-the-art methods, using the NL2Vis benchmarks (i.e., nvBench). The experimental results reveal that LLMs outperform baselines, with inference-only models consistently exhibiting performance improvements, at times even surpassing fine-tuned models when provided with certain few-shot demonstrations through in-context learning. Finally, we analyze when the LLMs fail in NL2Vis, and propose to iteratively update the results using strategies such as chain-of-thought, role-playing, and code-interpreter. The experimental results confirm the efficacy of iterative updates and hold great potential for future study.
Learning-based Property Estimation with Polynomials
Authors: Li Jiajun , Lei Runlin , Wang Sibo , Wei Zhewei , Ding Bolin
Published: May 2024

The problem of estimating data properties using sampling frequency histograms has attracted extensive interest in the area of databases. The properties include the number of distinct values (NDV), entropy, and so on. In the field of databases, property estimation is fundamental to complex applications. For example, NDV estimation is the foundation of query optimization, and entropy estimation is the foundation of data compression. Among them, methods originating from statistics exhibit desirable theoretical guarantees but rely on specific assumptions about the distribution of data, resulting in poor performance in real-world applications. Learning-based methods, which use information from training data, are adaptable in the real world but often lack theoretical guarantees or explainability. In addition, a unified framework for estimating these frequency-based estimators with machine learning is lacking. Given the aforementioned challenges, it is natural to wonder if a unified framework with theoretical guarantees can be established for property estimation. The recent literature has presented theoretical studies that propose estimation frameworks based on polynomials. These studies also prove estimation errors with respect to the sample size. Motivated by the above polynomial estimation framework, we propose a learning-based estimation framework with polynomial approximation, which aims to learn the coefficients of the polynomial, providing theoretical guarantees to the learning framework. Through comprehensive experiments on both synthetic and real-world datasets for estimating various data properties like NDV, entropy, and power sum, our results show the superiority of our algorithms over previous estimators.
Structural Parameterizations for Two Bounded Degree Problems Revisited
Authors: Lampis Michael , Vasilakis Manolis
Published: May 2024

We revisit two well-studied problems,
Bounded Degree Vertex Deletion
and
Defective Coloring
, where the input is a graph
G
and a target degree Δ, and we are asked either to edit or partition the graph so that the maximum degree becomes bounded by Δ. Both problems are known to be parameterized intractable for the most well-known structural parameters, such as treewidth.

We revisit the parameterization by treewidth, as well as several related parameters and present a more fine-grained picture of the complexity of both problems. In particular, we present the following:

—

Both problems admit straightforward DP algorithms with table sizes

\((\Delta +2)^\mathrm{tw}\)

and

\((\chi _\mathrm{d}(\Delta +1))^{\mathrm{tw}}\)

, respectively, where tw is the input graph’s treewidth and

\(\chi _\mathrm{d}\)

the number of available colors. We show that, under the SETH, both algorithms are essentially optimal, for any non-trivial fixed values of

\(\Delta , \chi _\mathrm{d}\)

, even if we replace treewidth by pathwidth. Along the way, we obtain an algorithm for
Defective Coloring
with complexity quasi-linear in the table size, thus settling the complexity of both problems for treewidth and pathwidth.

—

Given that the standard DP algorithm is optimal for treewidth and pathwidth, we then go on to consider the more restricted parameter tree-depth. Here, previously known lower bounds imply that, under the ETH,
Bounded Vertex Degree Deletion
and
Defective Coloring
cannot be solved in time

\(n^{o(\sqrt [4]{\mathrm{td}})}\)

and

\(n^{o(\sqrt {\mathrm{td}})}\)

, respectively, leaving some hope that a qualitatively faster algorithm than the one for treewidth may be possible. We close this gap by showing that neither problem can be solved in time

\(n^{o(\mathrm{td})}\)

, under the ETH, by employing a recursive low tree-depth construction that may be of independent interest.

—

Finally, we consider a structural parameter that is known to be restrictive enough to render both problems FPT: vertex cover. For both problems the best known algorithm in this setting has a super-exponential dependence of the form

\(\mathrm{vc}^{\mathcal {O}(\mathrm{vc})}\)

. We show that this is optimal, as an algorithm with dependence of the form

\(\mathrm{vc}^{o(\mathrm{vc})}\)

would violate the ETH. Our proof relies on a new application of the technique of
d
-detecting families introduced by Bonamy et al. [ToCT 2019].

Our results, although mostly negative in nature, paint a clear picture regarding the complexity of both problems in the landscape of parameterized complexity, since in all cases we provide essentially matching upper and lower bounds.
Temperature Variations of Spectra and Images of Photoluminescence from Heavily Cr-Doped Ruby
Authors: Hitomi Ami , Aizawa Hiroaki , Katsumata Toru
Published: May 2024

Photoluminescence (PL) spectra, intensities, and image brightness of 0.1–6.0 at% Cr-doped ruby were investigated across temperatures ranging from 24° to 600 °C. PL emissions at λ = 670, 694, 707, and 715 nm were observed in rubies doped with 0.1–1.0 at% Cr. In rubies with higher doping levels of 1.5–6.0 at% Cr, an additional PL emission at λ = 770 nm was detected. PL intensities at λ = 694, 707, 715, and 770 nm decreased with increasing temperatures from 24° to 600 °C, while the PL intensity at λ = 670 nm showed a similar temperature-dependent decrease. The variation in PL image brightness with temperature, particularly the increase observed from 24° to 200 °C, is predominantly influenced by the PL intensity variations at λ = 670 nm. Decay curves and fluorescence lifetimes of PL from ruby with various Cr concentrations were also evaluated at temperatures RT-200 °C.
Optical and Spectroscopic Features of K2B4O7-Li2B4O7 -TeO2 Glasses Modified with Cu2+ Ions
Authors: Satyanarayana T. , K. Chandra Sekhar , Hameed Abdul , Sangeetha G. , Md Shareefuddin
Published: May 2024

This work aims to analyze the structural properties of lithium and potassium tetra borate glasses that have undergone modification with tellurium oxide and Cu2+ ions with the chemical composition xK2B4O7-(80-x) Li2B4O7−19TeO2−1CuO [KLTC] (with x = 50, 60, 70 & 80 mole%). The analysis is performed by using different spectroscopic methods. The absence of sharp Braggs peaks in the X-ray diffraction spectra confirmed the amorphous nature of the processed glasses. The optical parameter values were obtained from Tauc and Urbach plots. The band gap values decreased in proportion with the content of K2B4O7 in KLTC. On these samples EPR studies were put on in order to determine the ligand field surrounded by the Cu2+ ions. The spin-Hamiltonian parameters suggest that the Cu2+ ions are located in tetragonally stretched octahedral locations. The existence of metal cations along with the characteristics borate as well as tellurite structural units were confirmed by the peaks observed in the Fourier transform infrared and Raman spectra. Among the prepared KLTC glass samples, KLTC-80 is found to be the best sample in the field of fiber optics communication.
Characterization of internal jugular vein region-specific distension and flow patterns during progressive volume shifting
Authors: Cohen Jeremy N. , Hedge Eric T. , Greaves Danielle K. , Robertson Andrew D. , Nahas Hassan , Yu Alfred C. H , Petersen Lonnie G. , Au Jason S.
Published: May 2024

The internal jugular vein (IJV) facilitates cerebral outflow and is sensitive to volume shifts. Concerns about IJV expansion and fluid flow behavior in astronauts have surfaced following thromboembolism reports. Our study explored regional volume distension and blood flow complexity in the IJV during progressive volume shifting. We observed stepwise volume distension and increasing flow dispersion with head-down tilting across all regions. Flow dispersion may pose a risk of future thromboembolism during prolonged volume shifts.
Socioeconomic status as a potential mediator of arterial aging in marginalized ethnic and racial groups: current understandings and future directions
Authors: Darvish Sanna , Mahoney Sophia A. , Venkatasubramanian Ravinandan , Rossman Matthew J. , Clayton Zachary S. , Murray Kevin O.
Published: May 2024

Cardiovascular diseases (CVDs) are the leading cause of death in the United States. However, disparities in CVD-related morbidity and mortality exist as marginalized racial and ethnic groups are generally at higher risk for CVDs (Black Americans, Indigenous People, South and Southeast Asians, Native Hawaiians, and Pacific Islanders) and/or development of traditional CVD risk factors (groups above plus Hispanics/Latinos) relative to non-Hispanic Whites (NHW). In this comprehensive review, we outline emerging evidence suggesting these groups experience accelerated arterial dysfunction, including vascular endothelial dysfunction and large elastic artery stiffening, a nontraditional CVD risk factor that may predict risk of CVDs in these groups with advancing age. Adverse exposures to social determinants of health (SDOH), specifically lower socioeconomic status (SES), are exacerbated in most of these groups (except South Asians—higher SES) and may be a potential mediator of accelerated arterial aging. SES negatively influences the ability of marginalized racial and ethnic groups to meet aerobic exercise guidelines, the first-line strategy to improve arterial function, due to increased barriers, such as time and financial constraints, lack of motivation, facility access, and health education, to performing conventional aerobic exercise. Thus, identifying alternative interventions to conventional aerobic exercise that 1) overcome these common barriers and 2) target the biological mechanisms of aging to improve arterial function may be an effective, alternative method to aerobic exercise to ameliorate accelerated arterial aging and reduce CVD risk. Importantly, dedicated efforts are needed to assess these strategies in randomized-controlled clinical trials in these marginalized racial and ethnic groups.
Fixed Bed Column Adsorption System for the Removal of 2,4‐Dichlorophenoxyacetic Acid Herbicide from an Aqueous Solution
Authors: Debebe Yalemtsehay , Worku Zemene , Alemayehu Esayas
Published: May 2024

The intensive use of 2,4‐dichlorophenoxyacetic acid (2,4‐D) herbicide has resulted in the presence of its residues in the environment, which leads to contamination of surface and groundwater. In this study, a fixed‐bed column experiment was conducted for the removal of 2,4‐D from an aqueous solution using termite mound soil (TMS). Scanning electron microscopy (SEM), Fourier transform infrared (FTIR), atomic absorption spectrometry (AAS), and Brunauer–Emmett–Teller (BET) techniques were used to characterize the adsorbent. The effect of significant variables, such as the initial 2,4‐D concentration (50 mg/L and 75 mg/L), flow rate (2.5 ml/min and 5 ml/min), solution pH (2, 4, and 6), and bed height (3, 6, and 9 cm), on the breakthrough characteristics of the adsorption system was assessed. In addition, the Thomas and Yoon–Nelson models were applied to predict the breakthrough curves and to determine the characteristic parameters of the column that are useful for process design. The findings showed that at a lower pH (2), a lower flow rate (2.5 ml/min), a lower 2,4‐D concentration (50 mg/L), a higher bed depth (9 cm), and 840 min breakthrough time, a higher removal percentage (80.2%) of 2,4‐D was achieved. The experimental data were in good agreement with the Thomas and Yoon–Nelson models. For the Yoon–Nelson model, the rate constant increased with an increase in the flow rate, initial ion concentration, and bed height. The time required for a 50% breakthrough decreased with an increase in the flow rate, bed height, and initial ion concentration. For the Thomas model, the rate constant increased with an increase in the flow rate but decreased with an increase in bed height and initial concentration. Overall, the study showed that termite mound soil in a fixed‐bed column adsorption system presents an excellent potential for removing 2,4‐D from aqueous solutions.
Characteristic of Premixed Hydrogen/Air Tubular Flames in Microcombustor: Effects of Stimulated and Unstimulated Inlet Conditions on Flame Dynamics
Authors: Alipoor Alireza , Abbaspour Pouyan
Published: May 2024

The present study investigates the characteristics and periodic behavior of H2/air tubular flames in a 1 mm diameter microtube under exciting and nonexciting inlet conditions. Under unstimulated inlet conditions, increasing inlet velocity positively impacted flow stratification and self‐sustaining of the tubular flames, leading to higher maximum temperatures within the flame kernel due to reduced flow temperature gradients near the wall. Conversely, under stimulated conditions, varying excitation amplitudes resulted in two flame propagation modes: flame with semi‐repetitive extinction/ignition (FSREI) and pulsating flame, observed across different exciting amplitude ranges. It was found that the formation of recirculation fields generated by negative propagation speed temporarily stored the released heat of combustion and prevented it from extinguishing in the flowing phase. From the kinetics point of view, the maximum reaction rate during the pulsating mode belongs to H + O2 = HO2, while competition between H + O2 = HO2 and H2 + OH = H2O + H occurred in the FSREI mode. Results revealed that in the pulsating mode, fluctuations in mass fractions of the heavier species are more considerable near the outlets. However, radical mass fraction fluctuations were significant near the inlet slot in pulsating mode.
N‐Acetylcysteine Treats Spinal Cord Injury by Inhibiting Astrocyte Proliferation
Authors: Zhang Dong , Qin Chaoxi , Meng Fei , Han Xiaopeng , Guo Xing
Published: May 2024

Astrocyte proliferation commonly occurs after spinal cord injury (SCI). N‐Acetylcysteine (NAC) has a regulatory effect on many diseases. In this study, we investigated the effect and underlying mechanism of NAC on astrocytes in SCI. We isolated rat primary astrocytes and stimulated with lipopolysaccharide to induce cell proliferation and degeneration. A rat model of SCI was also established, and the Basso–Beattie–Bresnahan score was determined. The localization of glial fibrillary acidic protein in the cells and tissues was determined using TUNEL staining and immunofluorescence, while that of connexin 43 was assessed via immunofluorescence. Pathological changes associated with SCI were detected using hematoxylin and eosin staining, and inflammatory factors were detected using enzyme‐linked immunosorbent assay. Additionally, JAK/STAT expression was evaluated using western blotting and quantitative reverse transcription polymerase chain reaction. NAC downregulated the glial fibrillary acidic protein abundance and connexin 43 in reactive astrocytes and SCI rat models while inhibiting the abundance of secreted proteins DSPG, HSPG, KSPG, tenascin C, vimentin, CSPG, ephrin‐B2, and nestin. NAC also regulated the JAK/STAT signaling pathway by downregulating the expression of JAK2, STAT5, STAT3, STAT1, PIM1, NFATc1, COL1, COL3, TGF‐β, SMAD1, CTGF, CyCD1, and CDK4, thus alleviating SCI. Finally, NAC exhibited durable effects, with no SCI recurrence within 60 days. Therefore, NAC relieves SCI by inhibiting the proliferation of reactive astrocytes and suppressing the expression of secretory and JAK/STAT pathway proteins.
Effects of Ambient Air Pollution on Brain Cortical Thickness and Subcortical Volume: A Longitudinal Neuroimaging Study
Authors: Ko Juyeon , Sohn Jungwoo , Noh Young , Koh Sang-Baek , Lee Seung-Koo , Kim Sun-Young , Cho Jaelim , Kim Changsoo
Published: May 2024

Introduction: Several cross-sectional studies have shown that long-term exposures to air pollutants are associated with smaller brain cortical volume or thickness. Here, we investigated longitudinal associations of long-term air pollution exposures with cortical thickness and subcortical volume. Methods: In this longitudinal study, we included a prospective cohort of 361 adults residing in four cities in the Republic of Korea. Long-term concentrations of particulate matter with aerodynamic diameters of ≤10 μm (PM10) and ≤2.5 μm (PM2.5) and nitrogen dioxide (NO2) at residential addresses were estimated. Neuroimaging markers (cortical thickness and subcortical volume) were obtained from brain magnetic resonance images at baseline (August 2014 to March 2017) and at the 3-year follow-up (until September 2020). Linear mixed-effects models were used, adjusting for covariates. Results: A 10-μg/m3 increase in PM10 was associated with reduced whole-brain mean (β = −0.45, standard error [SE] = 0.10; p < 0.001), frontal (β = −0.53, SE = 0.11; p < 0.001) and temporal thicknesses (β = −0.37, SE = 0.12; p = 0.002). A 10-ppb increase in NO2 was associated with a decline in the whole-brain mean cortical thickness (β = −0.23, SE = 0.05; p < 0.001), frontal (β = −0.25, SE = 0.05; p < 0.001), parietal (β = −0.12, SE = 0.05; p = 0.025), and temporal thicknesses (β = −0.19, SE = 0.06; p = 0.001). Subcortical structures associated with air pollutants included the thalamus. Conclusions: Long-term exposures to PM10 and NO2 may lead to cortical thinning in adults.
Karyotypic Reshuffling in the Genus Rhipidomys (Rodentia: Cricetidae: Sigmodontinae) Revealed by Zoo-FISH
Authors: Moreira Camila N. , Pricoli Fernanda G. , Ferguson-Smith Malcolm A. , Yonenaga-Yassuda Yatiyo , Ventura Karen
Published: May 2024

Introduction: Rhipidomys is the second most specious and the most widespread genus of the tribe Thomasomyini. Chromosomal data have been an important tool in the taxonomy of the group that presents low variability of diploid number (2n) and highly variable fundamental numbers (FNs). Despite such diversity, the genus has been studied mainly by classical and banding cytogenetic techniques. Methods: This study performed a comparative study between R. emiliae (2n = 44, FN = 52), R. macrurus (2n = 44, FN = 49), R. nitela (2n = 50, FN = 71), and R. mastacalis (2n = 44, FN = 72) using chromosome painting probes of two Oryzomyini species. Results: Our analysis revealed pericentric inversion as the main rearrangement involved in the karyotype evolution of the group, although tandem fusions/fissions were also detected. In addition, we detected eight syntenic associations exclusive of the genus Rhipidomys, and three syntenic associations shared between species of the tribe Thomasomyini and Oryzomyini. Conclusion: Comparative cytogenetic analysis by ZOO-FISH on genus Rhipidomys supports a pattern of chromosomal rearrangement already suggested by comparative G-banding. However, the results suggest that karyotype variability in the genus could also involve the occurrence of an evolutionary new centromere.
Short and intermediate-term price performance of unseasoned issues
Authors: Mumtaz Muhammad Zubair , Smith Zachary Alexander
Published: May 2024

Avaliamos o desempenho de preços no curto e médio prazo de ofertas públicas iniciais no período de 1995 a 2014. Encontramos que as novas emissões, em média, são subavaliadas no dia de listagem e obtêm retornos anormais significativos até os quinze dias de negociação. No caso do desempenho a médio prazo, os investidores obtêm retornos positivos anormais para, no máximo, dois meses de negociação. Utilizamos análise de limites extremos, regressão lasso e regressão passo a passo para selecionar os fatores determinantes do desempenho a curto e médio prazo. Cada método econométrico possui suas próprias especificações e características para identificar os melhores parâmetros
Políticas econômicas e estabilização no Plano Real
Authors: Toledo Joaquim Elói Cirne de
Published: May 2024

O objetivo deste artigo e esboçar, sem a pretensão de originalidade, um referencial simples de análise e um conjunto de dados sobre o desempenho recente de certos indicadores macroeconômicos da economia brasileira. Argumentar-se-á, assim, que a política cambial do Plano Real - tão criticada - pode ser considerada como integralmente adequada. Por outro lado, a política fiscal deve ser julgada como fortemente inadequada. Finalmente, a política monetária - de juros - deve ser avaliada como inadequada - e, até mesmo, um verdadeiro desastre, pela herança que deixa, na forma de uma elevada dívida pública interna.
Observações sobre o Plano Real
Authors: Arida Persio
Published: May 2024

O artigo inicia-se com uma breve descrição da proposta Larida dando ênfase tanto para a fase de denominada de 'transição' como para a fase referida como 'âncora e estabilidade de preços’. Especula-se sobre as possíveis razões para a não adoção da proposta Larida nos planos de estabilização brasileiros. Após questionar as ambiguidades da palavra 'fundamentos’, o texto termina com uma elaboração sobre as dificuldades que poderiam ser encontradas na fixação de uma âncora nominal.
Impacto inicial del COVID-19 en la situación económico-financiera de las familias de Santiago de Cali, Colombia
Authors: Oliveira Nadja Simone Menezes Nery de , Correa Fonnegra Juan Byron , Arias Arbeláez Fabio Alberto
Published: May 2024

The study aims to evaluate the initial impact of the COVID-19 pandemic on the economic-financial situation of families in Cali, Colombia through a multinomial Logit model. The data comes from a direct investigation through the application of a survey. The results revealed that there is an economic-financial vulnerability of these families to the pandemic. Men with an average age of 36 years who present levels of education higher than professional can resist the financial impact. As the age of men increases, the negative financial impact grows stronger.
As manipulações das etnicidades como forma de controle, exploração e alienação em Hibisco Roxo de Chimamanda Ngozi Adichie.
Authors: Campos Juliana Sant'Ana Campos
Published: May 2024

Este estudo analise a obra Hibisco Roxo (2011) de Chimamanda Ngozie Adichie observando às tensões culturais, sociais e econômicas entre os explorados e os exploradores tendo como ponto central as manipulações que alteram e expandem os processos de construções identitárias dos protagonistas e suas esferas de dominação.
Autoposição e autodestruição na filosofia de Schelling
Authors: Pacheco Marília Cota
Published: May 2024

Falar da possibilidade ou não de aniquilação da natureza, pelo próprio homem, é no limite uma polêmica infindável se considerarmos que a não sustentabilidade dos recursos naturais implica a aniquilação da própria humanidade. O tema por si mesmo expõe uma contradição, porquanto todo imaginário individual, enquanto um ideal, contém a noção de autopreservação. Mas o fato é que em nossos dias tal possibilidade atingiu um alto grau de probabilidade. Então podemos nos perguntar: como isso aconteceu? Neste trabalho, iremos falar sobre a possibilidade, ou não, de aniquilação da natureza, através da noção de Schelling de autoposição do espírito como liberdade incondicionada. Primeiramente, buscaremos esclarecer as razões pelas quais chegamos ao impasse de nossos dias apresentando a dificuldade com a qual Schelling se depara ao considerar o Eu como princípio no texto Sistema do Idealismo Transcendental.Em seguida, a passagem para sua filosofia da identidade como uma tentativa de mostrar como o indivíduo da consciência empírica pode ser livre e, ao mesmo tempo, estabelece uma relação histórico-universal válida para o todo da diversidade de consciências finitas. Num terceiro momento apresentaremos a sua noção de Abfall (“Filosofia e Religião”) através da qual o autor demonstra como o universal é intuído pelo particular. Por fim, considerando a dialética da imaginação implícita na noção de Abfall, tentaremos indicar uma direção norteadora sobre a questão da preservação da natureza e, por conseguinte, do homem.
Teenagers’ perceptions of Mexican primates: A participatory environmental education program for the conservation of mantled howler monkeys (Alouatta palliata) in Los Tuxtlas, Mexico
Authors: Hernández-Cortés Alejandra , Silva-Rivera Evodia , Rangel-Negrín Ariadna , Franquesa-Soler Montserrat
Published: May 2024

This study explores the perceptions that high school students have about mantled howler monkeys in the Mexican community of Balzapote, Veracruz. We systematized the learning process derived from a Primate Conservation Education Program (PCEP) based on participatory action research (PAR) and arts-based education. Our results indicate a decrease in students’ fear of monkeys, the recovery of myths and legends about this species, as well as a complex knowledge about monkeys and their habitat. The inclusion of local knowledge enriched the learning experience and reinforced primate conservation concepts. The PAR and arts-based approaches allowed students to internalize and apply acquired knowledge and fostered empathy. In addition to learning, the approach helped develop teamwork, critical thinking, and creative skills. Quantitative indicators showed shifts in emotions and knowledge post-program, and qualitative data revealed a deep articulation of learned content. We also identified migration and mining activities as socio-political factors impacting local people’s livelihoods and wildlife conservation in this region.
Leaf-footed Bugs (Hemiptera: Heteroptera: Coreidae) of Colombia: Annotated checklist, distribution, and description of a new species
Authors: SERNA-MUÑOZ SEBASTIAN , WOLFF MARTA
Published: May 2024

Coreidae is a family of phytophagous hemipterans known as leaf-footed bugs, which can become important pests for various crops. Information on this family in Colombia is scarce, and it is necessary to address its diversity and distribution for adequate management of potential pest species, as well as for the knowledge and conservation of the whole group. To contribute to the knowledge of the family Coreidae in the country, a catalog was carried out based on a review of the bibliography, eleven national biological collections and the citizen science platform iNaturalist. A total of 300 species were found, 115 of which are new records for the country. A key for the genera of Hypselonotini is included, as well as photographs of the habitus of most of the species and distributional maps. Also, a new species of the genus Sundarellus Brailovsky & Barrera from the departments of Guaviare and Meta is described.
Checklist of the Odonata (Insecta) of Sundaland and Wallacea (Malaysia, Singapore, Brunei, Indonesia and Timor Leste)
Authors: DOW R.A. , CHOONG C.Y. , GRINANG J. , LUPIYANINGDYAH P. , NGIAM R.W.J. , KALKMAN V.J.
Published: May 2024

A checklist, based on a database containing published data, of the Odonata (dragonflies and damselflies) occurring in Sundaland and Wallacea is presented. The presence of (sub)species is indicated for eight main regions (Singapore & Peninsular Malaysia, South China Sea (islands in the South China Sea that are not sensibly treated as satellites of larger landmasses), Borneo, Sumatra, Java & Bali, Lesser Sunda, Sulawesi, Moluccas), 22 subregions and 80 smaller islands and island groups. In total 743 full species are recorded from the entire area with 549 species known from Sundaland and 270 from Wallacea. Of these 482 are not found outside Sundaland and Wallacea, 385 (ca. 52% of the fauna) of which are single region endemics; the majority of these are actually single island endemics. Notes are provided on taxonomic problems or indicating problematic distribution records. Prodasineura lansbergei is considered to be a nomen nudum (stat nov.). For each of the eight main regions the history of the study of odonates is briefly discussed, information is provided on the coverage of the available data and the faunal composition is described. An overview is given of genera for which no larvae have been described. A brief comparison is made between the faunas of Sundaland and Wallacea showing that they only share 10% of the species between them (76 of 743).
4. Semantic Roles and Decomposition of Agency
Authors: Canu Højgaard Christian
Published: May 2024

Social network analysis relies on a mapping of relationships or interactions among persons or groups. Often a particular relationship is assumed (e.g., marriage or trade ties), but all sorts of relationships can be taken into account. One way to deal with social network analysis of texts is to extract all event structures consisting of an actor, undergoer, and event, grammatically realized as subject, (in)direct object, and verbal predicate. Leviticus 17–26 contains 181 different verbs resulting in a complex social network. This prompts the question of how to differentiate between various verbal events in a quantifiable way.

The question is addressed by invoking linguistic theories of agency since all events presuppose a certain amount of effort on behalf of the agents. By implication, verbs can be measured according to agency required, that is, amount of force and volition. This chapter develops a framework for capturing agency from verbal events on the basis of the Role and Reference Grammar theory for deriving semantic roles from the lexical aspect of verbs, also known as Aktionsart. It is argued that dynamicity and causation are the two most important verbal features for decoding agency.
5. Dynamicity
Authors: Canu Højgaard Christian
Published: May 2024

Dynamicity is one of the most important verbal features with respect to agency. Essentially, dynamic or active events presuppose an active agent in contrast to stative situations. In practice, it is complicated to analyse verbal semantics, especially for ancient languages given the lack of native language users to consult.

The chapter investigates previous approaches to the analysis of the Hebrew verbal system and concludes that new quantitative methods are needed to provide more objective measures of verbal semantics. In particular, it is demonstrated how collostructional analysis can help to differentiate between semantic roles, most importantly between dynamic and static verbs but also between goal and source.