bluuebunny/crossref_metadata_2025 huggingface dataset:
Beta-cell, but not autonomic nervous system, function is related to MAFLD in early stages of glucose intolerance
Authors: Dimova Rumyana , Chakarova Nevena , Serdarova Mina , Marinova Cvetelina , Popov Dimitar , Del Prato Stefano , Tankova Tsvetalina
Published: December 2024

Introduction

Previous studies have suggested an association between beta-cell and autonomic function and metabolic-associated fatty liver disease (MAFLD). We explored the association between controlled attenuated parameter (CAP) and insulin secretion and action, as well as sympathetic and parasympathetic activity in normal (NGT) and impaired (IGT) glucose tolerance.

Research design and methods

Twenty-five NGT (age 44.8±9.6 years; body mass index (BMI) 32.3±6.9 kg/m2) and 27 IGT (47.6±11.8 years; 31.0±6.5 kg/m2) subjects underwent a 75 g oral glucose tolerance test (OGTT) and a mixed meal tolerance test (MMTT) for assessment of glucose and insulin secretion. Parameters of beta-cell function and insulin sensitivity were calculated. Body composition was assessed by bioimpedance analysis (Inbody720). Autonomic function was assessed by ANX V.3.0 monitoring system. CAP was determined by Fibroscan (Echosense) and presence of MAFLD was defined as CAP >233 dB/m.

Results

A CAP >233 dB/m was found in 72% of subjects with NGT and 67% of subjects with IGT. Subjects with MAFLD, irrespective of glucose tolerance, had higher BMI and waist circumference, lower insulin secretion and action, and lower parasympathetic activity. On a matrix analysis, after adjustment for age and BMI, CAP was positively related to systolic blood pressure (SBP); insulin action was negatively related to parasympathetic activity. Regression analysis showed that AUC-insulin MMTT remained independently related to MAFLD: OR 24.4 (95% CI 2.17 to 274.77; p=0.010). A “cut-off” value of 15,620 uIU/mL-1*180 min-1provided a 75% sensitivity and 75% specificity for CAP >233 dB/m.

Conclusions

Our results do not support a role for parasympathetic activity in MAFLD. Rather, they show that stimulated hyperinsulinemia may be associated with greater risk of MAFLD irrespective of glucose tolerance in a high-risk population without diabetes.
Retrospective derivation of a causal pathway for diabetic ketoacidosis in adult patients with type 2 diabetes mellitus
Authors: Kline Jeffrey A , Wesner Nicholas A , Sharif Amina T , Griffey Richard T , Levy Phillip D , Welch Robert D , Grunberger George
Published: December 2024

Background

Type 2 ketone-prone diabetes mellitus (T2KPDM) is thought to occur in men of African descent, with obesity who experienced prolonged hyperglycemia; the role of medication non-adherence as a contributing cause remains unstudied.

Research design and methods

This was a retrospective study of unique adults (>18 years) who sought emergency care one of four hospitals in the greater Detroit area. Patients were identified on the basis of a laboratory order for a ß-hydroxybutyrate concentration. Two research coordinators abstracted 119 data fields. Patients were divided into four phenotypes: (1) no prior DM, (2) type 2 DM without prior ketosis, (3) type 2 with prior ketosis and (4) type 1 DM. A ß-hydroxybutyrate >20 mg/dL defined diabetic ketoacidosis (DKA). A directed acyclic graph was constructed to diagram a causal pathway.

Results

Of 450 patients, 326 were non-type I and 37% of these had DKA. Concentrations of ß-hydroxybutyrate, glucose, bicarbonate were not different between non-type1 versus type 1 DM patients. Admission rates to the ICU and hospital lengths of stay were similar between the four phenotypes with DKA. We found no association with sex, race or body mass index. Unadjusted odds for DKA were significant for non-adherence (odds=1.74, 95% CI 1.08 to 2.21) arrival by Emergency Medical Services (odds=0.54, 95% CI 0.33 to 0.86) and private or Medicare insurance (odds=6.80, 95% CI 4.00 to 11.60). The median HbA1C was statistically higher in patients with DKA (median 11.3%) versus those without DKA (median 9.5%, Mann-Whitney U p<0.001) and was also higher in patients with a history of non-adherence. In multivariable analysis, non-adherence was found to be a mediator of DKA with T2KPDM.

Conclusions

in Detroit, MI, prior ketosis and private or Medicare health insurance were significantly associated with new or recurrent DKA in T2KPDM. Medication non-adherence had a mediating role.
Could new records of parasitic cestode Nybelinia surmenicola in Dolly Varden (Salvelinus malma) from the Beaufort Sea indicate increased presence of salmon shark (Lamna ditropis) in the Arctic?
Authors: Gallagher Colin P. , Johnson Michael W.
Published: December 2024

Parasitological investigations of anadromous Dolly Varden ( Salvelinus malma) (Walbaum, 1792) harvested along the Canadian Beaufort Sea coast in summer 2021 and 2022 revealed infections by the parasitic cestode Nybelinia surmenicola (Okada in Dollfus, 1929) (2% and 0.8% prevalence, respectively) whose only documented final host is salmon shark ( Lamna ditropis) (Hubbs and Follett, 1947), which to date has been documented only once in the Arctic. Infection rates were low as only two fish, captured in consecutive years, were infected with a single worm at the plerocercoid stage in their stomach. These infections are the first record of the parasite in the Arctic Ocean and for Dolly Varden in North America. The source of infection in both fishes was likely from consuming a euphausiid, presumably Thysanoessa raschii (M. Sars, 1863), which is an infrequent prey of Dolly Varden and a known first host of the parasite, that became infected by consuming N. surmenicola eggs expelled by salmon shark. The euphausiids presumably originated from the Bering Sea and were actively transported by currents into the Arctic Ocean yet it is unknown where their infection occurred. Given the amount of time for exogenous feeding to begin, the presumed rate of transport and time spent feeding in Arctic waters (i.e., Chukchi and Beaufort seas), we infer the infection of euphausiids most likely occurred in the Arctic, which suggests the presence of salmon shark. Additionally, the findings provide evidence that salmon shark may becoming increasingly prevalent in Arctic waters in recent years due to climate change. Our observation underscores the utility of parasitological information for surveillance for detecting climate-related change in Arctic marine biodiversity.
Effect of Oligochaete worms on the permeability of fluid fine tailings and thickened tailings under operational parameters: consequences for dewatering and strengthening
Authors: Pardo Miguel de Lucas , Sittoni Luca , van Kessel Thijs , Herman Peter , Hanssen Jill , van Rees Floris , Buffarini Lorenzo , le Galeze Simon , Kuznetsov Peter , Ulrich Ania
Published: December 2024

Oligochaete worms enhance dewatering of mature fine tailings. In this context, the research team has investigated the beneficial effects of Oligochaete worms in dewatering and strengthening of fresh samples of fluid fine tailings (FFTs) and thickened tailings (TTs), including cold temperatures. Applying Oligochaete worms to FFT and TT resulted in enhanced permeability leading to faster solid content ( Sc) increases that are twice as large as in controls, up to final Sc of 37% for FFT and 61% for TT, and shear strengths that are twice as large in their absolute value as in controls too.
Enabling precise predictions for left-right symmetry at colliders
Authors: Kriewald Jonathan , Nemevšek Miha , Nesti Fabrizio
Published: December 2024

We investigate the structure of the minimal left-right symmetric model that enables precise predictions in the gauge, scalar and neutrino sector. We revisit the complete set of mass spectra and mixings for the charged and neutral gauge bosons, would-be-Goldstones and gauge fixing, together with the ghost Lagrangian. In the scalar sector, we analytically re-derive all the massive states with mixings and devise a non-trivial physical input scheme, expressing the model couplings in terms of masses and mixing angles. Fermion couplings are also determined in closed form, including the Dirac mixing in the neutrino sector, evaluated explicitly using the Cayley–Hamilton theorem. These analytic developments are implemented in a comprehensive FeynRules model file. We calculate the one loop QCD corrections and provide a complete UFO file for NLO studies, demonstrated on relevant hadron-collider benchmarks. We provide various restricted variants of the model file with different gauges, massless states, neutrino hierarchies and parity violating

$$g_L \ne g_R$$

g
L

≠

g
R

gauge couplings.
Astrophysical insights into magnetic Penrose process around parameterized Konoplya–Rezzolla–Zhidenko black hole
Authors: Xamidov Tursunali , Shaymatov Sanjar , Sheoran Pankaj , Ahmedov Bobomurat
Published: December 2024

In this study, we investigate the parameterized Konoplya–Rezzolla–Zhidenko (KRZ) black hole (BH) spacetime in the presence of an external asymptotically uniform magnetic field. We first examine the innermost stable circular orbit (ISCO) radii for both neutral and charged test particles, demonstrating that the deformation parameters,

$$\delta _1$$

δ
1

and

$$\delta _2$$

δ
2

, reduce the ISCO values. Subsequently, we assess the energy efficiency of the magnetic Penrose process (MPP) for an axially symmetric parameterized BH, analyzing the effects of the deformation parameters and the magnetic field on the energy extraction process. Our findings indicate that the rotational deformation parameter

$$\delta _2$$

δ
2

is crucial for the efficiency of energy extraction from the BH. The synergy between the rotational deformation parameter and the magnetic field significantly boosts the energy extraction efficiency, with values exceeding

$$100\%$$

100
%

. Interestingly, for extremal BHs with negative

$$\delta _2$$

δ
2

values, the energy efficiency increases, in contrast to Kerr BHs where the MPP effect diminishes. Additionally, we explore the astrophysical implications of the MPP by deriving the maximum energy of a proton escaping from the KRZ parameterized BH due to the beta decay of a free neutron near the horizon. Our results show that negative

$$\delta _2$$

δ
2

values require stronger magnetic fields to achieve equivalent energy levels for high-energy protons, providing deeper insights into high-energy astrophysical phenomena around the parameterized BH.
Possible signal of an exotic $$I=1$$, $$J=2$$ state in the $$B \rightarrow D^{*-}D^+K^+$$ reaction
Authors: Lyu Wen-Tao , Duan Man-Yu , Xiao Chu-Wen , Wang En , Oset Eulogio
Published: December 2024

We study the

$$B^+ \rightarrow D^{*-}D^+K^+$$

B
+

→

D

∗
-

D
+

K
+

reaction, showing that a peak in the

$$D^+K^+$$

D
+

K
+

mass distribution around

$$2834 \text { MeV}$$

2834

MeV

reported by LHCb could be associated with a theoretical exotic state with that mass, a width of

$$19 \text { MeV}$$

19

MeV

and

$$J^P=2^+$$

J
P

=

2
+

, stemming from the interaction of the

$$D^{*+}K^{*+}$$

D

∗
+

K

∗
+

and

$$D^{*+}_s \rho ^+$$

D
s

∗
+

ρ
+

channels, which is a partner of the

$$0^+$$

0
+

$$T_{c{\bar{s}}}(2900)$$

T

c

s

¯

(
2900
)

. We show that the data is compatible with this assumption, but also see that the mass distribution itself cannot discriminate between the spins

$$J=0$$

J
=
0

, 1, 2 of the state. Then we evaluate the momenta of the angular mass distribution and show that they are very different for each of the spin assumptions, and that the momenta coming from interference terms have larger strength at the resonant energy than the peaks seen in the angular integrated mass distribution. We make a call for the experimental determination of these magnitudes, which has already been used by the LHCb in related decay reactions.
On the computational simulation of a temporally nonlocal and nonlinear diffusive epidemic model of disease transmission
Authors: Ahmed Nauman , Macías-Díaz Jorge E. , Shahid Naveed , Raza Ali , Rafiq Muhammad
Published: December 2024

This paper reports on a nonlocal mathematical system to model the spreading of polio among a community of human individuals. Our model consists of four compartments: susceptible, exposed, infected and vaccinated individuals. The mathematical model considers spatial diffusion, and temporal fractional derivatives of the Caputo type. We use nonnegative initial conditions and homogeneous data of the Neumann type on the boundary. We determine analytically the disease-free and the endemic equilibria along with the basic reproductive number. We establish thoroughly the nonnegativity of the solutions, and the stability of the equilibria. Computationally, we propose an implicit finite-difference method to approximate the solutions of the model. The numerical model is stable in the sense of von Neumann, it yields consistent approximations to the exact solutions of the differential problem, and it is capable of preserving unconditionally the positivity of the approximations. For the sake of illustration, we provide some computer simulations that confirm some of the theoretical results derived in the present paper.
Cosmological model in f(Q) theory of gravity
Authors: Kumar Shukla Bhupendra , Sofuoğlu Değer , Beesham A. , Mishra Preeti
Published: December 2024

In the context of symmetric teleparallel modified gravity, known as [Formula: see text] theory, we examine an accelerating cosmological model using a log-square-root form of the non-metricity function. Solving the field equations with a parametrized deceleration parameter in terms of redshift, we derive the model parameters. Our analysis utilizes data from 57 Hubble observations, 1048 Pantheon supernovae, and BAO datasets, with a Markov Chain Monte Carlo (MCMC) technique for statistical analysis. The results show that the deceleration parameter transitions from positive (early deceleration) to negative (current acceleration), aligning with observational data. Statefinder parameters indicate that the model evolves from quintessence-like behavior to convergence with the [Formula: see text]CDM model. The equation of state parameter suggests a phantom dark energy scenario, implying faster-than-expected acceleration. The matter density and cosmic pressure predictions are consistent with observational trends. We can conclude that the [Formula: see text] gravity model offers a robust framework for explaining the accelerated expansion of the universe, providing a viable alternative to the [Formula: see text]CDM model, and highlighting the potential of non-metric gravity theories to advance our understanding of dark energy and cosmic dynamics.
L∞ estimate for Maxwell–Higgs equation on Reissner–Nordström geometry
Authors: Mulyanto  , Atmaja Ardian N. , Akbar Fiki T. , Kosasih Jusak S. , Triyanta  , Gunara Bobby E.
Published: December 2024

In this paper, we obtain [Formula: see text] estimate for the Maxwell–Higgs system in the exterior region of Reissner–Nordström spacetimes. Utilizing the integrated local energy decay estimate, the Sobolev embedding theorem alongside the Gagliardo–Nirenberg–Sobolev inequality on compact Riemannian manifold, we derive the boundedness for [Formula: see text] norm of the Maxwell–Higgs system on Reissner–Nordström geometry.
Automated Human Action Recognition with Improved Graph Convolutional Network-based Pose Estimation
Authors: Baghel Amit , Kushwaha Alok Kumar Singh , Singh Roshan
Published: December 2024

The process of utilizing Artificial Intelligence (AI) to identify and label human behaviors from unprocessed activity data gathered from various sources is known as Human Activity Recognition (HAR). Because of its potential applications across multiple areas, computer vision faces a significant challenge in recognizing human actions and the accompanying interactions with objects and the environment. Investigating the temporal and geographical characteristics of the skeleton sequence is essential for this endeavor, according to recent studies. However, efficiently extracting discriminative temporal and spatial information remains a difficult task. This work proposes a novel Human Action Recognition Model exploiting improved Graph Convolutional Network (GCN)-based pose estimation with a Hybrid Classifier (IGCN-HC). The phases carried out in this model are pre-processing, pose estimation, feature extraction, and activity recognition. Initially, the input video will be pre-processed and a frame from the input video stream will be generated. Subsequently, human pose estimation exploiting improved GCN will be accomplished. Further, human skeletal joints’ coordinates in two- or three-dimensional spaces are determined via human pose estimation. Then, Shape Local Binary Texture (SLBT) and an improved hierarchy of skeleton features have been used to detect the variance in different activities. In the last phase, a hybrid classification model with the combination of Deep Maxout and customized CNN has been proposed for the recognition phase. The model utilizes two inputs pose estimation results (skeleton) and the extracted features for training purposes. Finally, the proposed trained model is evaluated for recognition on different test inputs and contrasted with the existing techniques.
A Lightweight Authenticated Encryption Algorithm Based on Compact CLEFIA Block Cipher
Authors: Liang Meiyu , Ji Tao , Yuan Yin , Cheng Xin , Zhang Zhang , Ma Lixiang
Published: December 2024

This paper presents CLEFIA-Kec, a lightweight authenticated encryption algorithm that combines CLEFIA with Keccak, for Internet of Things (IoT) applications. The compact CLEFIA circuit uses an integrated generalized Feistel network (GFN) structure that allows multiple tasks to share resources and requires only four registers for the whole GFN process by data path folding technique. All of the circuits are implemented on the Artix-7 field programmable gate array platform, and the test results show a throughput of 208[Formula: see text]Mbps with 226 slices for CLEFIA, a throughput of 4.03[Formula: see text]Gbps with 1403 slices for Keccak-512, and a throughput of 11.5[Formula: see text]Gbps with 1535 slices for CLEFIA-Kec. They achieve an optimal balance between resource utilization and throughput.
Cross varieties of aperiodic monoids with commuting idempotents
Authors: Gusev S. V.
Published: December 2024

A variety of algebras is called Cross if it is finitely based, finitely generated, and has finitely many subvarieties. In this paper, we classify all Cross varieties of aperiodic monoids with commuting idempotents.
Vlowk Renormalization group flow, vector manifestation and sound velocity in massive compact stars
Authors: Rho Mannque , Shao Long-Qi
Published: December 2024

The [Formula: see text]-renormalization group approach on the surface of Fermi liquid for nuclear matter to which Tom Kuo made a pioneering contribution at Stony Brook is found to inject the pivotal input in the formulation of the generalized nuclear effective field theory with acronym “GnEFT” applicable to superdense compact-star physics. A topology change in terms of skyrmions and half-skyrmions is shown to play the role of the “putative” hadron-quark continuity conjectured in QCD. Crucially involved are hidden local symmetry and hidden scale symmetry with the vacuum sliding with density in nuclear medium, with the nuclear tensor force emerging as a Landau Fermi-liquid fixed-point quantity. A possibly novel paradigm, a “Cheshire Catism,” in nuclear correlations is suggested.
Positively curved 10-manifolds with T3-symmetry
Authors: Krishnan Anusha M. , Wiemeler Michael
Published: December 2024

We show that closed, simply connected, positively curved 10-manifolds with effective, isometric actions of three-dimensional tori are homotopy spheres or homotopy complex projective spaces.
A Note on the Sensitivity of Permutation Entropy to Additive Noise
Authors: Jablonskaitė Kamilija , Haslhofer Eva-Maria , Landauskas Mantas
Published: December 2024

Additive noise could be encountered in various mechanical systems. It could be observed as part of ongoing system degradation and defect evolution. Here, we empirically demonstrate inherent challenges of permutation entropy (PE) in remaining useful life (RUL) analysis, the analysis of time to failure or time to unacceptable wear of the system. We perform numerical experiments by adding various amounts of additive Gaussian noise to vibrational signal and investigate how the PE changes. The data or signal are often comprised of several parts such as fundamental component, noise and other components related to perturbations out of the evolving defects. Here, we gain an additional insight on what part of the signal is related to the RUL. By joining these two problems together, we can draw a practical conclusion on how robust to additive noise the PE is to a particular dataset.
Multifractal Detrended Partial Cross-correlation and Risk Transmission of Cryptocurrencies
Authors: Xie Wenhao , Cao Guangxi
Published: December 2024

By taking Bitcoin, Ethereum, and Ripple as research objects, this paper applies the multifractal detrended partial cross-correlation analysis (MF-DPXA) to study the intrinsic cross-correlation between cryptocurrencies. Combining MF-DPXA and time-delay DCCA methods, we develop the removing factors time-delayed detrended cross-correlation analysis (R-TD-DCCA) to study the risk transmission direction between cryptocurrencies after removing the influence of common factors. The results show that after removing the influence of cryptocurrencies, the persistence of the cross-correlation between cryptocurrencies is enhanced, and the multifractal degrees of the cross-correlation between Bitcoin and Ethereum and between Ethereum and Ripple are increased, but the multifractal degree of the cross-correlation between Bitcoin and Ripple is weakened. However, after removing the influence of the S&P 500 index, the multifractal degree of the cross-correlation between cryptocurrencies has weakened. The Hurst exponent of local dynamic cross-correlation between cryptocurrencies is almost always greater than 0.5. With the increase in time delay, the risk of Bitcoin is mainly transmitted to Ethereum and Ripple, and the risk of Ripple is mainly transmitted to Ethereum. When removing the impact of the S&P 500 index, the short-term risk of Bitcoin is mainly transmitted to Ethereum and Ripple. The findings of this study have several implications for re-understanding the intrinsic interdependence structure and portfolios.
Efforts Toward Corporate Sustainability: Does ESG Performance and Technological Innovation Drive Corporate Financing Efficiency in China?
Authors: Suhrab Muhammad , Pinglu Chen , Qian Ningyu
Published: December 2024

This study examines the impact of environmental, social, and governance (ESG) performance and technological innovation (TI) on corporate financing efficiency (CFE) in Chinese firms. Data from 400 companies listed in the Shanghai and Shenzhen A-share markets, alongside ESG scores, were derived from the Thomson Reuters ESG scoring system spanning 2013–2022. Fixed effects (FE) and quantile regressions were employed to explore this relationship. The findings demonstrate that ESG and TI have significant and positive effects on CFE. Furthermore, TI is a moderator that strengthens the linkage between ESG and CFE. Findings emphasize the critical importance of ESG performance in obtaining cost-effective financing for Chinese firms. This underscores the critical need for businesses and regulators to prioritize and integrate ESG practices into corporate strategies. Such integration facilitates access to lower-cost financing, enhances cost efficiency, and optimizes investments in green technology. The findings emphasize the importance of fostering a sustainable corporate culture that supports the alignment of TI with ESG principles in business operations. These outcomes carry substantial implications for the corporate sector and regulatory frameworks, highlighting the pivotal role of sustainable practices in driving financial performance and long-term prosperity.
Dual Bubble-Enriched SFEM Approaches for Locking-Free Analysis of Structures Under Cyclic Loads
Authors: Ho Phuc L. H. , Lee Changkye , Le Canh V. , Tran Dung T. , Nguyen Phuong H. , Yee Jurng-Jae
Published: December 2024

Shakedown analysis, a robust technique for assessing fatigue failure in cyclically loaded structures, may encounter volumetric locking challenges in incompressible materials under plane strain conditions, particularly with low-order approximations. This study presents dual numerical approaches that pioneer integrating the bubble-enriched edge-based smoothed finite element method (bES-FEM) with conic programming within the shakedown analysis framework. The bubble enrichment enables locking-free performance across arbitrary mesh configurations while enhancing numerical accuracy. Two distinct formulations based on Koiter’s and Melan’s theorems are presented in conic form, with the associated kinematic and static constraints satisfied over the smoothed domains, minimizing problem size. These optimization problems are efficiently solved using the highly effective primal–dual interior-point solver, Mosek. The proposed methods are validated through various benchmark numerical examples featuring diverse geometries and loading combinations, achieving accurate shakedown limits with minimal computational effort. Insights into structural failure mechanisms are derived from plastic dissipation work distributions obtained from the kinematic formulation, corroborated by limit state stress fields from its dual form — the static approach. Furthermore, the ability to predict failure modes — whether due to incremental collapse or alternating plasticity — by analyzing failure mechanisms and interaction diagrams across multiple load ranges, along with identifying transition points between these modes, represents an intriguing finding of this study.
Quality Factor Enhancement of Piezoelectric MEMS Resonators Based on Cross-Hole Fractal Phononic Crystals
Authors: Li Lixia , Gao Tianhang , Su Kun , Zhang Lei , Yan Guanhai , Yang Qian
Published: December 2024

In this paper, a cross-hole fractal phononic crystal (CHF-PnC) structure is proposed, which consists of vertical cross-holes repeating their original shapes in a certain ratio. Using the finite element method, the complex energy band curves and frequency responses of the CHF-PnC are calculated, and three complete bandgaps with strong attenuation characteristics are obtained, with bandwidths of 193.4, 55.7 and 216.8 MHz, respectively. The mechanism of the generation of the bandgap of the CHF-PnC structure is analyzed, and the sensitivities of the geometrical parameters W and [Formula: see text] to the band gap are investigated. Subsequently, applying this structure to piezoelectric microelectromechanical systems (MEMS) resonators, it is found that the anchor point loss quality factor ([Formula: see text]) of the CHF-PnC resonator is 116,951.5% higher than the conventional resonator when a 6-row × 5-column combination is used. In addition, compared to the conventional resonator, the CHF-PnC resonator has a 69.7% reduction in insertion loss and a 3.6-fold improvement in unloaded quality factor, while maintaining the same electromechanical coupling coefficient.
Submodules of pseudo semi-projective modules
Authors: Nhan Tran Hoai Ngoc
Published: December 2024

A module [Formula: see text] is called pseudo semi-projective if, for all endomorphisms [Formula: see text] of [Formula: see text] with [Formula: see text], then [Formula: see text]. In this paper, we study submodules of pseudo semi-projective modules. It is shown that if every (finitely generated) submodule of a semiprojective right [Formula: see text]-module is pseudo semi-projective, then every factor ring of [Formula: see text] is right (semi-)hereditary. Moreover, we show that if [Formula: see text] is left perfect and finitely generated submodules of pseudo semi-projective right [Formula: see text]-modules are pseudo semi-projective, then [Formula: see text] has a decomposition of abelian groups [Formula: see text], where [Formula: see text] is a semisimple subring of [Formula: see text] containing 1.
Substructures of a semigroup of tree languages
Authors: Boonsol Julaluk , Pibaljommee Bundit
Published: December 2024

The set of all terms of type [Formula: see text] is denoted by [Formula: see text] Each element of [Formula: see text] is called a tree language. A binary operation [Formula: see text] is an operation on [Formula: see text] defined from the superposition [Formula: see text] on the set of all [Formula: see text]-ary terms of type [Formula: see text] Since [Formula: see text] satisfies the superposition law, [Formula: see text] is a semigroup. In this paper, we study subsemigroups of the semigroup [Formula: see text] including constant, left-zero, right-zero subsemigroups, rectangular bands, subgroups, and inverse subsemigroups. We also study factorization and locally factorization of the semigroup [Formula: see text] and we obtain that this semigroup is neither factorizable nor locally factorizable. However, we achieve a necessary and sufficient condition for factorization of local subsemigroup [Formula: see text], where [Formula: see text] is idempotent in [Formula: see text]. Finally, we study [Formula: see text]iteration and show that with special conditions, an [Formula: see text]iteration of idempotent is idempotent.
On some new upper bounds for numerical radius
Authors: Bilal Rimsha , Hyder Javariya , Akram Muhammad Saeed , Dragomir Silvestru Sever
Published: December 2024

The primary objective of this study is to unveil new upper bounds for the numerical radius of operators in Hilbert spaces, utilizing an enhanced version of the McCarthy inequality. These newly derived estimates refine existing inequalities for bounded linear operators.
Evaluating Natural Compounds as Inhibitors of Lipopolysaccharide Biosynthesis in Acinetobacter baumannii: A Comprehensive Method Employing Molecular Docking and Dynamics Simulations
Authors: Haryini Sree , Rais Affan , Gopikrishnan Mohanraj , Elavarasu Santhosh Mudipalli , Thirumal Kumar D. , Sasikumar K. , George Priya Doss C.
Published: December 2024

The increasing prevalence of antimicrobial resistance, particularly in Gram-negative bacteria such as Acinetobacter baumannii, demands new antibiotics as existing ones become increasingly ineffective. The production of lipopolysaccharide (LPS) is vital in Gram-negative bacteria, making it a promising target for antibiotic development. This study focuses on discovering antibiotics targeting the early-stage LpxA, LpxC and LpxH enzymes. These are crucial to lipid A biosynthesis in the Raetz pathway and are vital for bacterial survival and virulence. LpxA transfers an R-3-hydroxy acyl chain during lipid A biosynthesis, crucial for bacterial growth and potential antibiotic development. Inhibiting LpxC can impede bacterial growth and increase vulnerability to other antibiotics, whereas targeting LpxH is especially lethal due to the buildup of toxic lipid A intermediates. We identified promising compounds using high-throughput virtual screening of 374 compounds from ChemDiv with Schrodinger’s Extra Precision (XP) mode, followed by MM-GBSA analysis. Molecular Dynamics Simulations (MDS) over 100 ns using GROMACS confirmed the structural stability of these proteins with novel lead compound complexes. Compounds with ChemDiv IDs N039-0003 and N002-0028 showed strong binding to LpxA, N034-0001 and N023-0006 to LpxC and N025-0038 and N039-0020 to LpxH, with binding energies between –4.85 kcal/mol and –8.41 kcal/mol and total binding energies spanning from –31.06 kcal/mol to –53.87 KJ/mol. These findings suggest that these novel lead compounds inhibit the LpxA, LpxC and LpxH proteins and serve as new antibiotics against A. baumannii. However, additional in vitro and in vivo studies are needed to confirm the efficacy of these compounds.
Experimental investigations into magnetic-assisted vacuumized abrasive finishing setup for finishing internal surfaces
Authors: Sambharia Jai Kishan , Pathri Bhargav Prajwal , Gowripathi Rao N. R. N. V. , Unune Deepak Rajendra
Published: December 2024

The surface quality of manufactured components is a primary concern for the current industries, as poor surface finishes can lead to various issues during the component’s operation and lifespan. Nonconventional finishing technologies, with or without magnetic field assistance, play a crucial role in attaining micron-level surface finishes. The present research focuses on the fabrication of a magnetic-assisted vacuum abrasive finishing (MAVAF) setup, aimed at improving the surface finish of automobile engine coupler components. A novel magnetic-assisted self-deformable abrasive finishing (MASDAF) media was synthesized, utilizing marble waste as a base material, paraffin oil and grease as additives, and silicon carbide and iron powder as abrasive particles. The MASDAF media was characterized for its viscosity and rheological behavior and the best composition of MASDAF was selected for use in the MAVAF process. The results reveal that the percentage improvement in the change of average surface roughness value ([Formula: see text]Ra) decreased with an increase in abrasive mesh size. However, the impact of abrasive concentration on [Formula: see text]Ra showed mixed effects, with [Formula: see text]Ra initially increasing with increasing abrasive concentration, before declining with further increases in concentration.
Examining how 940-nm low-power laser radiation affects female rabbits’ thyroid gland hormone levels
Authors: Al Timimi Zahra
Published: December 2024

This research evaluates whether a low-power laser modifies the levels of calcitonin, thyroxine, as well as triiodothyronine in female rabbits, and the possibility that it could help explain how this type of radiation affects these animals’ hormone levels. The objective of this study is to determine whether thyroid hormone levels would be affected by laser radiation. We used 25 female rabbits with a 940-nm CW laser. For 3 days, radiation was delivered once daily to the region surrounding the thyroid gland with a 1 W output power and a 300[Formula: see text]J/cm2 energy density at a beam spot area of 1[Formula: see text]cm2. Samples of blood were drawn from the ear vein. Samples were taken on days 1, 7, 14, 21, and 30 following the treatment. The study’s findings demonstrated a steady decline in the thyroid gland-related hormones thyroxine and triiodothyronine. However, calcitonin levels increased in tandem with the research, and 30 days later, hormone levels were back to normal. The results suggest that thyroid hormone levels may be significantly impacted by low-power laser use. To learn more about how different laser wavelengths influence glands and perhaps be used therapeutically, more research is required.
Finding Logic Bugs in Spatial Database Engines via
Affine Equivalent Inputs
Authors: Deng Wenjing , Mang Qiuyang , Zhang Chengyu , Rigger Manuel
Published: December 2024

Spatial Database Management Systems (SDBMSs) aim to store, manipulate, and retrieve
spatial data
. SDBMSs are employed in various modern applications, such as geographic information systems, computer-aided design tools, and location-based services. However, the presence of logic bugs in SDBMSs can lead to incorrect results, substantially undermining the reliability of these applications. Detecting logic bugs in SDBMSs is challenging due to the lack of ground truth for identifying incorrect results. In this paper, we propose an automated
geometry-aware generator
to generate high-quality SQL statements for SDBMSs and a novel concept named
Affine Equivalent Inputs (AEI)
to validate the results of SDBMSs. We implemented them as a tool named Spatter (
Spat
ial DBMS Tes
ter
) for finding logic bugs in four popular SDBMSs: PostGIS, DuckDB Spatial, MySQL, and SQL Server. Our testing campaign detected 34 previously unknown and unique bugs in these SDBMSs, of which 30 have been confirmed, and 18 have already been fixed. Our testing efforts have been well appreciated by the developers. Experimental results demonstrate that the
geometry-aware generator
significantly outperforms a naive random-shape generator in detecting unique bugs, and
AEI
can identify 14 logic bugs in SDBMSs that were totally overlooked by previous methodologies.
High-Performance Query Processing with NVMe Arrays: Spilling without Killing Performance
Authors: Kuschewski Maximilian , Giceva Jana , Neumann Thomas , Leis Viktor
Published: December 2024

This paper aims to bridge the gap between fast in-memory query engines and slow but robust engines that can utilize external storage. We find that current systems have to choose between fast in-memory operators and slower out-of-memory operators. We present a solution that leverages two independent but complementary techniques: First, we propose adaptive materialization, which can turn any hash-based in-memory operator into an out-of-memory operator without reducing in-memory performance. Second, we introduce self-regulating compression, which optimizes the throughput of spilling operators based on the current workload and available hardware. We evaluate these techniques using the prototype query engine Spilly, which matches the performance of state-of-the-art in-memory systems, but also efficiently executes large out-of-memory workloads by spilling to NVMe arrays.
iRangeGraph: Improvising Range-dedicated Graphs for Range-filtering Nearest Neighbor Search
Authors: Xu Yuexuan , Gao Jianyang , Gou Yutong , Long Cheng , Jensen Christian S.
Published: December 2024

Range-filtering approximate nearest neighbor (RFANN) search is attracting increasing attention in academia and industry. Given a set of data objects, each being a pair of a high-dimensional vector and a numeric value, an RFANN query with a vector and a numeric range as parameters returns the data object whose numeric value is in the query range and whose vector is nearest to the query vector. To process this query, a recent study proposes to build
O(n
2
) dedicated graph-based indexes for all possible query ranges to enable efficient processing on a database of
n
objects. As storing all these indexes is prohibitively expensive, the study constructs compressed indexes instead, which reduces the memory consumption considerably. However, this incurs suboptimal performance because the compression is lossy. In this study, instead of materializing a compressed index for every possible query range in preparation for querying, we materialize graph-based indexes, called elemental graphs, for a moderate number of ranges. We then provide an effective and efficient algorithm that during querying can construct an index for any query range using the elemental graphs. We prove that the time needed to construct such an index is low. We also cover an experimental study on real-world datasets that provides evidence that the materialized elemental graphs only consume moderate space and that the proposed method is capable of superior and stable query performance across different query workloads.
Live Patching for Distributed In-Memory Key-Value Stores
Authors: Fruth Michael , Scherzinger Stefanie
Published: December 2024

Providers of high-availability data stores need to roll out software updates without causing noticeable downtimes. For distributed data stores like Redis Cluster, the state-of-the-art is a rolling update, where the nodes are restarted in sequence. This requires preserving, restoring, and resynchronizing the database state, which can significantly prolong updates for larger memory states, and thus delay critical security fixes. In this article, we propose applying software updates directly in memory without restarting any nodes. We present the first fully operational live patching solution for Redis Cluster on Linux. We support both push- and pull-based distribution of patches, trading dissemination speed against cluster elasticity, the ability to allow nodes to dynamically join or leave the cluster. Our integration is very lightweight, as it piggybacks on the cluster-internal gossip protocol. Our experiments benchmark live patching against state-of-the-art rolling updates. In one scenario, live patching updates the entire cluster orders of magnitude faster, without unfavorable trade-offs regarding throughput, tail latencies, or network consumption. To showcase generalizability, we provide general guidelines on integrating live patching for distributed database systems and successfully apply them to a primary-replica PostgreSQL setup. Given our overall promising results, we discuss the opportunities of live patching in database DevOps.
LSMGraph: A High-Performance Dynamic Graph Storage System with Multi-Level CSR
Authors: Yu Song , Gong Shufeng , Tao Qian , Shen Sijie , Zhang Yanfeng , Yu Wenyuan , Liu Pengxi , Zhang Zhixin , Li Hongfu , Luo Xiaojian , Yu Ge , Zhou Jingren
Published: December 2024

The growing volume of graph data may exhaust the main memory. It is crucial to design a disk-based graph storage system to ingest updates and analyze graphs efficiently. However, existing dynamic graph storage systems suffer from read or write amplification and face the challenge of optimizing both read and write performance simultaneously. To address this challenge, we propose LSMGraph, a novel dynamic graph storage system that combines the write-friendly LSM-tree and the read-friendly CSR. It leverages the multi-level structure of LSM-trees to optimize write performance while utilizing the compact CSR structures embedded in the LSM-trees to boost read performance. LSMGraph uses a new memory structure, MemGraph, to efficiently cache graph updates and uses a multi-level index to speed up reads within the multi-level structure. Furthermore, LSMGraph incorporates a vertex-grained version control mechanism to mitigate the impact of LSM-tree compaction on read performance and ensure the correctness of concurrent read and write operations. Our evaluation shows that LSMGraph significantly outperforms state-of-the-art (graph) storage systems on both graph update and graph analytical workloads.
Memento Filter: A Fast, Dynamic, and Robust Range Filter
Authors: Eslami Navid , Dayan Niv
Published: December 2024

Range filters are probabilistic data structures that answer approximate range emptiness queries. They aid in avoiding processing empty range queries and have use cases in many application domains such as key-value stores and social web analytics. However, current range filters do not support dynamically changing and growing datasets. Moreover, several of these designs also exhibit impractically high false positive rates under correlated workloads, which are common in practice. These impediments restrict the applicability of range filters across a wide range of use cases.

We introduce Memento filter, the first range filter to simultaneously offer dynamicity, fast operations, and a robust false positive rate for any workload. Memento filter partitions the key universe and clusters its keys according to this partitioning. For each cluster, it stores a fingerprint and a list of key suffixes contiguously. The encoding of these lists makes them amenable to existing dynamic filter structures. Due to the one-to-one mapping from keys to suffixes, Memento filter supports inserts and deletes and can even expand to accommodate a growing dataset.

We implement Memento filter on top of a Rank-and-Select Quotient filter and InfiniFilter and demonstrate that it achieves a competitive false positive rate and performance with the state of the art while also providing dynamicity. Due to its dynamicity, Memento filter is the first range filter applicable to B-Trees. We showcase this by integrating Memento filter into WiredTiger, a B-Tree-based key-value store, significantly boosting its performance for mixed workloads.
Multivariate Time Series Cleaning under Speed Constraints
Authors: Zhang Aoqian , Wu Zexue , Gong Yifeng , Yuan Ye , Wang Guoren
Published: December 2024

Errors are common in time series due to unreliable sensor measurements. Existing methods focus on univariate data but do not utilize the correlation between dimensions. Cleaning each dimension separately may lead to a less accurate result, as some errors can only be identified in the multivariate case. We also point out that the widely used minimum change principle is not always the best choice. Instead, we try to change the smallest number of data to avoid a significant change in the data distribution. In this paper, we propose MTCSC, the constraint-based method for cleaning multivariate time series. We formalize the repair problem, propose a linear-time method to employ online computing, and improve it by exploiting data trends. We also support adaptive speed constraint capturing. We analyze the properties of our proposals and compare them with SOTA methods in terms of effectiveness, efficiency versus error rates, data sizes, and applications such as classification. Experiments on real datasets show that MTCSC can have higher repair accuracy with less time consumption. Interestingly, it can be effective even when there are only weak or no correlations between the dimensions.
Navigating Labels and Vectors: A Unified Approach to Filtered Approximate Nearest Neighbor Search
Authors: Cai Yuzheng , Shi Jiayang , Chen Yizhuo , Zheng Weiguo
Published: December 2024

Given a query vector, approximate nearest neighbor search (ANNS) aims to retrieve similar vectors from a set of high-dimensional base vectors. However, many real-world applications jointly query both vector data and structured data, imposing label constraints such as attributes and keywords on the search, known as filtered ANNS. Effectively incorporating filtering conditions with vector similarity presents significant challenges, including index for dynamically filtered search space, agnostic query labels, computational overhead for label-irrelevant vectors, and potential inadequacy in returning results. To tackle these challenges, we introduce a novel approach called the
Label Navigating Graph,
which encodes the containment relationships of label sets for all vectors. Built upon graph-based ANNS methods, we develop a general framework termed
Unified Navigating Graph (UNG)
to bridge the gap between label set containment and vector proximity relations. UNG offers several advantages, including
versatility
in supporting any query label size and specificity,
fidelity
in exclusively searching filtered vectors,
completeness
in providing sufficient answers, and
adaptability
in integration with most graph-based ANNS algorithms. Extensive experiments on real datasets demonstrate that the proposed framework outperforms all baselines, achieving 10x speedups at the same accuracy.
Pasta: A Cost-Based Optimizer for Generating Pipelining Schedules for Dataflow DAGs
Authors: Liu Xiaozhen , Huang Yicong , Lin Xinyuan , Kumar Avinash , Alsudais Sadeem , Li Chen
Published: December 2024

Data analytics tasks are often formulated as data workflows represented as directed acyclic graphs (DAGs) of operators. The recent trend of adopting machine learning (ML) techniques in workflows results in increasingly complicated DAGs with many operators and edges. Compared to the operator-at-a-time execution paradigm, pipelined execution has benefits of reducing the materialization cost of intermediate results and allowing operators to produce results early, which are critical in iterative analysis on large data volumes. Correctly scheduling a workflow DAG for pipelined execution is non-trivial due to the richer semantics of operators and the increasing complexity of DAGs. Several existing data systems adopt simple heuristics to solve the problem without considering costs such as materialization sizes. In this paper, we systematically study the problem of scheduling a workflow DAG for pipelined execution, and develop a novel cost-based optimizer called Pasta for generating a high-quality schedule. The Pasta optimizer is not only general and applicable to a wide variety of cost functions, but also capable of utilizing properties inherent in a broad class of cost functions to improve its performance significantly. We conducted a thorough evaluation of developed techniques on real-world workflows and show the efficiency and efficacy of these solutions.