bluuebunny/crossref_metadata_2025 huggingface dataset:
Effect of sodium‐glucose cotransporter 2 inhibitor canagliflozin on interstitial glucose concentration in insulin‐treated diabetic dogs
Authors: Box Jessica R. , Oyama Mark A. , Mosenco Ariel S. , Hess Rebecka S.
Published: March 2024

Background

The utility of sodium‐glucose cotransporter 2 inhibitors (SGLT2i) has not been reported in insulin‐treated diabetic dogs.

Hypothesis

Canagliflozin, a PO‐administered SGLT2i, decreases interstitial glucose concentration (IG) in insulin‐treated diabetic dogs.

Animals

Five insulin‐treated diabetic dogs.

Methods

Uncontrolled open label longitudinal study. Canagliflozin (2‐4 mg/kg/day PO) was added to an unchanged insulin dose for 7 days. Fractional excretion of glucose was calculated by dividing the product of urine glucose and serum creatinine concentrations by the product of serum glucose and urine creatinine concentrations. Hypoglycemia was defined as IG <60 mg/dL.

Results

Median IG in 2869 measurements obtained while dogs were treated with insulin and canagliflozin was 87 mg/dL (range, 40‐500 mg/dL) and was significantly lower than median IG in 1426 measurements obtained while dogs were treated with insulin alone (212 mg/dL; range, 41‐500 mg/dL; P < .001). Median fractional excretion of glucose when dogs were treated with insulin and canagliflozin was 1.1% (range, 0.9%‐2.0%), significantly higher than when dogs were treated with insulin alone (0.3%; range, 0.01%‐1.0%; P = .04). The frequency of hypoglycemia was higher in dogs treated with insulin and canagliflozin (544 of 2869 IG measurements, 19%) compared with the frequency of hypoglycemia in dogs treated with insulin alone (52 of 1426 IG measurements, 4%; P < .001).

Conclusions and Clinical Importance

Canagliflozin may have a role in improving glycemic control in insulin‐treated diabetic dogs, but the dose of insulin should be decreased when adding canagliflozin to insulin treatment.
Non‐concordant epigenetic and transcriptional responses to acute thermal stress in western mosquitofish (Gambusia affinis)
Authors: Ren Xingyue , Zhao Junjie , Hu Juntao
Published: March 2024

Climate change is intensifying the frequency and severity of extreme temperatures. Understanding the molecular mechanisms underlying the ability to cope with acute thermal stress is key for predicting species' responses to extreme temperature events. While many studies have focused on the individual roles of gene expression, post‐transcriptional processes and epigenetic modifications in response to acute thermal stress, the relative contribution of these molecular mechanisms remains unclear. The wide range of thermal limits of western mosquitofish (Gambusia affinis) provides an opportunity to explore this interplay. Here, we quantified changes in gene expression, alternative splicing, DNA methylation and microRNA (miRNA) expression in muscle tissue dissected from mosquitofish immediately after reaching high (CTmax) or low thermal limit (CTmin). Although the numbers of genes showing expression and splicing changes in response to acute temperature stress were small, we found a possibly larger and non‐redundant role of splicing compared to gene expression, with more genes being differentially spliced (DSGs) than differentially expressed (DEGs), and little overlap between DSGs and DEGs. We also identified a small proportion of CpGs showing significant methylation change (i.e. differentially methylated cytosines, DMCs) in fish at thermal limits; however, there was no overlap between DEGs and genes annotated with DMCs in both CTmax and CTmin experiments. The weak interplay between epigenetic modifications and gene expression was further supported by our discoveries of no differentially expressed miRNAs. These findings provide novel insights into the relative role of different molecular mechanisms underlying immediate responses to extreme temperatures and demonstrate non‐concordant responses of epigenetic and transcriptional mechanisms to acute temperature stress.
Effect of photodynamic therapy with 5‐aminolevulinic acid and EDTA‐2Na against mixed infection of methicillin‐resistant Staphylococcus aureus and Pseudomonas aeruginosa
Authors: Teranishi Rie , Ozawa Toshiyuki , Katayama Bunpei , Shimojo Yu , Ito Nobuhisa , Awazu Kunio , Tsuruta Daisuke
Published: March 2024

Background

The increasing abundance of drug‐resistant bacteria is a global threat. Photodynamic therapy is an entirely new, non‐invasive method for treating infections caused by antibiotic‐resistant strains. We previously described the bactericidal effect of photodynamic therapy on infections caused by a single type of bacterium. We showed that gram‐positive and gram‐negative bacteria could be killed with 5‐aminolevulic acid and 410 nm light, respectively. However, clinically, mixed infections are common and difficult to treat.

Objective

We investigated the bactericidal effects of photodynamic therapy on mixed infections of methicillin‐resistant Staphylococcus aureus and Pseudomonas aeruginosa.

Methods

We compared bacterial growth with and without photodynamic therapy in vitro. Then, in vivo, we studied mixed infections in a mouse skin ulcer model. We evaluated the rates of ulcer area reduction and transitions to healing in treated and untreated mice. In addition, a comparison was made between PDT and existing topical drugs.

Results

We found that photodynamic therapy markedly reduced the growth of both methicillin‐resistant Staphylococcus aureus and Pseudomonas aeruginosa, in culture, and it reduced the skin ulcer areas in mice. PDT was also more effective than existing topical medicines.

Conclusion

This study showed that photodynamic therapy had antibacterial effects against a mixed infection of gram‐positive and gram‐negative bacteria, and it promoted skin ulcer healing. These results suggested that photodynamic therapy could be effective in both single‐ and mixed‐bacterial infections.
Interoceptive awareness mediated the effects of a 15‐minute diaphragmatic breathing on empathy for pain: A randomized controlled trial
Authors: He Yaping , Ge Likun , Yuan Jiajin , Wang Yingying , Zheng Danni , Rui An , Song Jun , Hu Li , Wei Gao‐Xia
Published: March 2024

Although empathy for pain plays an important role in positive interpersonal relationships and encourages engagement in prosocial behavior, it remains largely unknown whether empathy for pain could be effectively altered by psychophysiological techniques. This study aimed to investigate the impact of a single session of diaphragmatic breathing practice on empathy for pain and examine the potential mechanism involving interoceptive awareness. A total of 66 healthy participants were randomly assigned to the intervention group or the control group. The intervention group received a 15‐minute diaphragmatic breathing (DB) practice with real‐time biofeedback, while the control group was to gaze at a black screen at rest and not engaged in any other activities. Before and after the invention, all participants were instructed to evaluate the intensity and unpleasantness of empathy for pain while watching different pictures with pain or non‐pain conditions. The Multidimensional Assessment of Interoceptive Awareness (MAIA) was then administered to measure interoceptive awareness. The results indicated a significant interaction between group and time with regard to empathy for pain and MAIA. The DB group showed a statistically significant decrease in both pain intensity and unpleasantness during the pain picture condition, as well as a noteworthy increase in MAIA scores. The control group did not demonstrate any substantial changes. More importantly, the regulation of attention, a dimension of MAIA, had a significant mediating effect on the impact of diaphragmatic breathing on reported unpleasantness. Diaphragmatic breathing could serve as a simple, convenient, and practical strategy to optimize human empathy for pain that warrants further investigation, which has important implications not only for individuals with impaired empathy for pain but also for the improvement of interoceptive awareness.
THERMAL-INDUCED DAMAGE ON SOLDER JOINTS OF HIGH-DENSITY ADJACENT BALL GRID ARRAY COMPONENTS DURING THE REWORK PROCESS
Authors: Ismail Adlil Aizat , Abu Bakar Maria , Ehsan Abang Annuar , Zolkefli Zol Effendi
Published: March 2024

Correlation between adjacent ball grid array (BGA) components' temperature and thermal-induced damage to their solder joints on both the top and bottom printed circuit board assembly (PCBA) sides during the rework process is studied in this work. Total often adjacent BGA components from the rework area on the top (F - K) and bottom (A - E) PCBA side were observed. The dye and pull (D&P) test results, infrared thermography images, and temperature measurements were analyzed for solder joint crack induced by the thermal damage with precise temperature measurement on each adjacent BGA component. Scanning electron microscope (SEM) analysis complemented the post-D&P test solder joint crack observation. The D&P test results shows that 76 % or higher and solder joint separation locations at the copper pad on BGA occurred when the temperature of the adjacent components of the rework location exceeded 195 °C and 210 °C on the centre and corner of the component, respectively.
Cómo vivieron la pandemia los estudiantes de último año de medicina: efectos en su salud mental y mecanismos de defensa
Authors: Galeano Jaimes Natally , Pachón Blanco Nathalia , Galindo Silva Valentina , Cadena Camargo Yazmín María Lucila , Palencia Sánchez Francisco , Garciandía Imaz Jose Antonio 
Published: March 2024

Introducción: La experiencia de la enfermedad por covid-19 en 2019/2020 tuvo un impacto abrumador en los trabajadores de la salud, incluidos los estudiantes de medicina de último año, en quienes se vio afectada negativamente su experiencia de aprendizaje en el internado y en su salud mental. Métodos: Estudio de investigación cualitativa, con un abordaje fenomenológico-interpretativo. Se realizaron entrevistas grupales y se solicitó a cada participante la realización de un dibujo que representara lo que vivieron durante la pandemia por covid-19. Resultados: Se identificaron mecanismos de defensa como la negación y la escisión; los sentimientos de ansiedad, angustia, tristeza y miedo, y las percepciones positivas de la pandemia. Aparecen así mismo categorías emergentes como el síndrome de agotamiento profesional, las herramientas de afrontamiento y las barreras educativas. Discusión: Los mecanismos de defensa inmaduros que los estudiantes de medicina emplearon durante el año de internado y su relación con mayores niveles de estrés y mayor agotamiento emocional, así como el relato de situaciones que les generaron ansiedad, angustia, tristeza y miedo, además de síntomas del síndrome de burnout, muestran el impacto negativo de la pandemia por covid-19 en la salud mental de esta población.
Heat Transfer Analysis of Memory-Dependent Derivative in Biological Tissue Subjected to a Moving Heat Source
Authors: Li Xiaoya , Wang Dan
Published: March 2024

A new bioheat transfer equation is developed by introducing the memory-dependent derivative into dual-phase lag model. The heat transfer process of memory-dependent derivative in biological tissue under a moving heat source is studied. Besides, thermal conductivity is usually no longer constant at high temperature. The nonlinear temperature governing equation with considering variable thermal conductivity is formulated and the solutions are obtained by the methods of Kirchhoff and Laplace transformations. The influences of heat source velocity, variable thermal conductivity, relaxation time, and kernel function on the variation of temperature are analyzed.
Optimization of Manifold Microchannel Heat Sink Based on Design of Experiment Method
Authors: Wei Xingguo , Feng Yu , Yan Taisen , Li Wansheng , Lv Qinghang , Qin Jiang
Published: March 2024

The manifold microchannel heat sink (MMCHS) shows high potential to cope with the rapidly increasing power density of electronic devices. It is of significance to search for an optimization method to comprehensively consider multiparameter effects on the performance of microchannel. Here, we have studied the temperature and flow characteristics of the MMCHS via experimental method. Then, the effect of geometric parameters including microchannel aspect ratio (α), hydraulic diameter (Dh), and manifold block numbers (Nm) on the performance of a MMCHS were studied by numerical method. Subsequently, the design of experiment (DOE) method was proposed to optimize the geometric parameters of the MMCHS. The relation of friction coefficient and heat transfer coefficient with respect to the three geometric parameters was gained by the mathematical regression model. The statistically optimized manifold microchannel achieved a 10.0% reduction in temperature rise, 59.9% enhanced in the heat transfer coefficient, and the figure of merit (FOM) of 1.6. Our work shows a novel method to consider the effect of structure parameters on the performance of the manifold microchannel and provides a novel optimization design method for the manifold microchannel.
The influence of frequency, volume, and viscosity on the ultrasonic atomization threshold of sessile droplets
Authors: Meneses-Díaz Josué , Vargas-Hernández Yolanda , Cancino-Jaque Eduardo , Gaete-Garretón Luis
Published: March 2024

In this research, we present a study on the atomization threshold (ATh) of sessile droplets, analyzing its relationship with the excitation frequency fexc (55–48 kHz), droplet volume Vdrop (1–100 μl), and droplet viscosity μ (1–6 mPa⋅s). The investigation focused on the atomization thresholds using ultrasonic excitation of distilled water droplets and water- polyethylene glycol (PEG)-8000 mixtures deposited on vibrating surfaces. The obtained results are compared with previously reported theoretical models. A modification to the model proposed by Alzuaga et al. [Alzuaga, Manceau, and Bastien, J. Sound Vib. 282(1–2), 151–162 (2005)] is suggested to determine the atomization thresholds of sessile droplets, incorporating the atomization droplet size equation proposed by Rajan and Pandit and an empirical constant α to account for the effect of droplet volume in this process. The results show that the relationship between the atomization threshold and viscosity does not fit well with the prediction of Eisenmenger [Acta Acust united Acust. 9(4), 327–340 (1959)] and Pohlman and Stamm [Untersuchung Zum Mechanismus Der Ultraschallvernebelung an Flüssigkeitsoberflächen im Hinblick Auf Technische Anwendungen (Investigation on the Mechanism of Ultrasonic Nebulization on Liquid Surfaces Considering Technical Applications) (VS Verlag für Sozialwissenschaften, Wiesbaden, Germany, 1965)] and Pohlman et al. [Pohlman, Heisler, and Cichos, Ultrasonicc 12(1), 11–15 (1974)] (ATh∝μ). However, the data tendency aligns with the model proposed by Alzuaga (ATh ∝ μ1/2). The results obtained in this study provide a deeper understanding of the atomization thresholds of sessile droplets through ultrasonic excitation.
“You’re Too Pretty to Be a Challenge Runner”: Changing “Gamers” in an Age of Live Streaming
Authors: Garvey Kevin
Published: March 2024

Persistent misogyny in video gaming spaces has motivated calls for broader recognition of female players and the development of protective, welcoming spaces. Yet even recognition of female gamers remains elusive. By allowing individuals to broadcast themselves playing games, Twitch has greatly enhanced the visibility of players, including high-skill, hard-core female gamers developing dedicated viewer audiences. This study investigates the community management of female streamers who focus on high-skill “challenge running” and participate in hard-core challenge run communities. Regularly encountering online misogyny, these streamers have developed four distinct strategies in reply: overcoming antagonistic audiences, capturing audience emotion, anticipating antagonism, and combating misogyny through humor and recontextualization. Streamers learn to anticipate negative, misogynistic attention and, in collaboration with supportive viewers, creatively transform it into positive channel content for their benefit. By visibly challenging games and antagonistic viewers alike, these streamers provide new methods for responding to misogyny in online gaming spaces.
Laser desorption rapid evaporative ionization mass spectrometry (LD-REIMS) demonstrates a direct impact of hypochlorous acid stress on PQS-mediated quorum sensing in
Pseudomonas aeruginosa
Authors: Bradley Rob , Simon Daniel , Spiga Livia , Xiang Yuchen , Takats Zoltan , Williams Huw
Published: March 2024

To establish infections in human hosts,
Pseudomonas aeruginosa
must overcome innate immune-generated oxidative stress, such as the hypochlorous acid (HOCl) produced by neutrophils. We set out to find specific biomarkers of oxidative stress through the development of a protocol for the metabolic profiling of
P. aeruginosa
cultures grown in the presence of different oxidants using a novel ionization technique for mass spectrometry, laser desorption rapid evaporative ionization mass spectrometry (LD-REIMS). We demonstrated the ability of LD-REIMS to classify samples as untreated or treated with a specific oxidant with 100% accuracy and identified a panel of 54 metabolites with significantly altered concentrations after exposure to one or more of the oxidants. Key metabolic changes were conserved in
P. aeruginosa
clinical strains isolated from patients with cystic fibrosis lung infections. These data demonstrated that HOCl stress impacted the
Pseudomonas
quinolone signal (PQS) quorum sensing system. Ten 2-alkyl-4-quinolones (AHQs) associated with the PQS system were significantly lower in concentration in HOCl-stressed
P. aeruginosa
cultures, including 2-heptyl-3-hydroxy-4(1H)-quinolone (PQS), the most active signal molecule of the PQS system. The PQS system regulates the production of virulence factors, including pyocyanin and elastase, and their levels were markedly affected by HOCl stress. No pyocyanin was detectable and elastase concentrations were reduced by more than 75% in cultures grown with sub-lethal concentrations of HOCl, suggesting that this neutrophil-derived oxidant may disrupt the ability of
P. aeruginosa
to establish infections through interference with production of PQS-associated virulence factors.

IMPORTANCE

This work demonstrates that a high-throughput ambient ionization mass spectrometry method can be used successfully to study a bacterial stress response. Its application to the opportunistic pathogen
Pseudomonas aeruginosa
led to the identification of specific oxidative stress biomarkers, and demonstrated that hypochlorous acid, an oxidant specifically produced by human neutrophils during infection, affects quorum sensing and reduces production of the virulence factors pyocyanin and elastase. No pyocyanin was detectable and elastase levels were reduced by more than 75% in bacteria grown in the presence of hypochlorous acid. This approach has the potential to be widely applicable to the characterization of the stress responses of bacteria.
Uncovering the boundaries of
Campylobacter
species through large-scale phylogenetic and nucleotide identity analyses
Authors: Wu Ruochen , Payne Michael , Zhang Li , Lan Ruiting
Published: March 2024

Campylobacter
species are typically helical shaped, Gram-negative, and non-spore-forming bacteria. Species in this genus include established foodborne and animal pathogens as well as emerging pathogens. The accumulation of genomic data from the
Campylobacter
genus has increased exponentially in recent years, accompanied by the discovery of putative new species. At present, the lack of a standardized species boundary complicates distinguishing established and novel species. We defined the
Campylobacter
genus core genome (500 loci) using publicly available
Campylobacter
complete genomes (
n
= 498) and constructed a core genome phylogeny using 2,193 publicly available
Campylobacter
genomes to examine inter-species diversity and species boundaries. Utilizing 8,440
Campylobacter
genomes representing 33 species and 8 subspecies, we found species delineation based on an average nucleotide identity (ANI) cutoff of 94.2% is consistent with the core genome phylogeny. We identified 60 ANI genomic species that delineated
Campylobacter
species in concordance with previous comparative genetic studies. All pairwise ANI genomic species pairs had
in silico
DNA-DNA hybridization scores of less than 70%, supporting their delineation as separate species. We provide the tool
Campylobacter
Genomic Species typer (CampyGStyper) that assigns ANI genomic species to query genomes based on ANI similarities to medoid genomes from each ANI genomic species with an accuracy of 99.96%. The ANI genomic species definitions proposed here allow consistent species definition in the
Campylobacter
genus and will facilitate the detection of novel species in the future.

IMPORTANCE

In recent years,
Campylobacter
has gained recognition as the leading cause of bacterial gastroenteritis worldwide, leading to a substantial rise in the collection of genomic data of the
Campylobacter
genus in public databases. Currently, a standardized
Campylobacter
species boundary at the genomic level is absent, leading to challenges in detecting emerging pathogens and defining putative novel species within this genus. We used a comprehensive representation of genomes of the
Campylobacter
genus to construct a core genome phylogenetic tree. Furthermore, we found an average nucleotide identity (ANI) of 94.2% as the optimal cutoff to define the
Campylobacter
species. Using this cutoff, we identified 60 ANI genomic species which provided a standardized species definition and nomenclature. Importantly, we have developed
Campylobacter
Genomic Species typer (CampyGStyper), which can robustly and accurately assign these ANI genomic species to
Campylobacter
genomes, thereby aiding pathogen surveillance and facilitating evolutionary and epidemiological studies of existing and emerging pathogens in the genus
Campylobacter
.
Characterization of clumpy adhesion of
Escherichia coli
to human cells and associated factors influencing antibiotic sensitivity
Authors: Khan Muhammad Moman , Sidorczuk Katarzyna , Becker Juliane , Aleksandrowicz Adrianna , Baraniewicz Karolina , Ludwig Christina , Ali Aamir , Kingsley Robert A. , Schierack Peter , Kolenda Rafał
Published: March 2024

Escherichia coli
intestinal infection pathotypes are characterized by distinct adhesion patterns, including the recently described clumpy adhesion phenotype. Here, we identify and characterize the genetic factors contributing to the clumpy adhesion of
E. coli
strain 4972. In this strain, the transcriptome and proteome of adhered bacteria were found to be distinct from planktonic bacteria in the supernatant. A total of 622 genes in the transcriptome were differentially expressed in bacteria present in clumps relative to the planktonic bacteria. Seven genes targeted for disruption had variable distribution in different pathotypes and nonpathogenic
E. coli,
with the
pilV
and
spnT
genes being the least frequent or absent from most groups. Deletion (Δ) of five differentially expressed genes,
flgH
,
ffp
,
pilV
,
spnT,
and
yggT,
affected motility, adhesion, or antibiotic stress. Δ
flgH
exhibited 80% decrease and Δ
yggT
depicted 184% increase in adhesion, and upon complementation, adhesion was significantly reduced to 13%. Δ
flgH
lost motility and was regenerated when complemented, whereas Δ
ffp
had significantly increased motility, and reintroduction of the same gene reduced it to the wild-type level. The clumps produced by Δ
ffp
and Δ
spnT
were more resistant and protected the bacteria, with Δ
spnT
showing the best clump formation in terms of ampicillin stress protection. Δ
yggT
had the lowest tolerance to gentamicin, where the antibiotic stress completely eliminated the bacteria. Overall, we were able to investigate the influence of clump formation on cell surface adhesion and antimicrobial tolerance, with the contribution of several factors crucial to clump formation on susceptibility to the selected antibiotics.

IMPORTANCE

The study explores a biofilm-like clumpy adhesion phenotype in
Escherichia coli,
along with various factors and implications for antibiotic susceptibility. The phenotype permitted the bacteria to survive the onslaught of high antibiotic concentrations. Profiles of the transcriptome and proteome allowed the differentiation between adhered bacteria in clumps and planktonic bacteria in the supernatant. The deletion mutants of genes differentially expressed between adhered and planktonic bacteria, i.e.,
flgH
,
ffp
,
pilV
,
spnT
, and
yggT,
and respective complementations in
trans
cemented their roles in multiple capacities.
ffp
, an uncharacterized gene, is involved in motility and resistance to ampicillin in a clumpy state. The work also affirms for the first time the role of the
yggT
gene in adhesion and its involvement in susceptibility against another aminoglycoside antibiotic, i.e., gentamicin. Overall, the study contributes to the mechanisms of biofilm-like adhesion phenotype and understanding of the antimicrobial therapy failures and infections of
E. coli
.
How do clinicians use post-COVID syndrome diagnosis? Analysis of clinical features in a Swedish COVID-19 cohort with 18 months’ follow-up: a national observational cohort and matched cohort study
Authors: Ollila Hanna M , Fonseca-Rodríguez Osvaldo , Caspersen Ida Henriette , Kalucza Sebastian , Normark Johan , Trogstad Lill , Magnus Per Minor , Rod Naja Hulvej , Ganna Andrea , Eriksson Marie , Fors Connolly Anne-Marie
Published: March 2024

Introduction

SARS-CoV-2 infection causes acute COVID-19 and may result in post-COVID syndrome (PCS). We aimed to investigate how clinicians diagnose PCS and identify associated clinical and demographic characteristics.

Methods

We analysed multiregistry data of all SARS-CoV-2 test-positive individuals in Sweden (n=1 057 174) between 1 February 2020 and 25 May 2021. We described clinical characteristics that prompt PCS diagnosis in outpatient and inpatient settings. In total, there were 6389 individuals with a hospital inpatient or outpatient diagnosis for PCS. To understand symptomatology, we examined individuals diagnosed with PCS at least 3 months after COVID-19 onset (n=6389) and assessed factors associated with PCS diagnosis.

Results

Mechanical ventilation correlated with PCS (OR 114.7, 95% CI 105.1 to 125.3) compared with no outpatient/inpatient contact during initial COVID-19. Dyspnoea (13.4%), malaise/fatigue (8%) and abnormal pulmonary diagnostic imaging findings (4.3%) were the most common features linked to PCS. We compared clinical features of PCS with matched controls (COVID-19 negative, n=23 795) and COVID-19 severity-matched patients (COVID-19 positive, n=25 556). Hypertension associated with PCS cohort (26.61%) than in COVID-19-negative (OR 17.16, 95% CI 15.23 to 19.3) and COVID-19-positive (OR 9.25, 95% CI 8.41 to 10.16) controls, although most individuals received this diagnosis before COVID-19. Dyspnoea was the second most common feature in the PCS cohort (17.2%), and new to the majority compared with COVID-19-negative (OR 54.16, 95% CI 42.86 to 68.45) and COVID-19-positive (OR 18.7, 95% CI 16.21 to 21.57) controls.

Conclusions

Our findings highlight factors Swedish physicians associate with PCS.
Coulomb effect in hybrid double quantum dot-metal nanoparticle systems considering the wetting layer
Authors: Nasser Nour A. , Al-Khursan Amin H.
Published: March 2024

Many body effects in the wetting layer (WL)-double quantum dot (DQD)-metal nanoparticle (MNP) structure have been studied by modeling the Coulomb scattering rates in this structure. The strong coupling between WL-DQD-MNPs was considered. An orthogonalized plane wave (OPW) is assumed between WL-QD transitions. The transition momenta are calculated accordingly to specify the normalized Rabi frequency on this structure, considering the strong coupling between the WL-DQD-MNP structures. This approach is important for realizing scattering rates, including in-and-out capture and relaxation rates, which are essential for specifying the type of structure used depending on the optimum value of the scattering time required to fit the application. The QD hole capture rate is the highest, and the hole capture times are the shortest. The relaxation times are less than the electron capture times by one order, while they are half of the hole capture times. The capture rates increase with increasing distance R between the DQDs and the MNP. High tunneling increases hole-capture rates and changes the relaxation rates, showing the importance of tunneling in controlling the scattering rates.
Investigation of Artificial Intelligence Algorithms in Robot Object Recognition Systems Under the Background of Big Data
Authors: Jiang Xue
Published: March 2024

In the long history of human beings, with the continuous exploration and research of natural phenomena and social life, many scientific fields have emerged, and robots are the product of this technological development to a certain stage. At present, there are hundreds of different types of robots applied in production and daily life in the world, which have achieved significant economic benefits. However, its technical issues have gradually emerged. For example, the shortcomings in visual perception and other aspects cannot be effectively addressed. Object recognition is not precise enough, and information resources cannot be effectively utilized to achieve control functions. These are the main factors that constrain the further progress and improvement of robots. The emergence of big data and Artificial Intelligence (AI) has brought unprecedented opportunities to robots. Especially, the application of big data analysis in intelligent manufacturing and smart city construction is becoming increasingly widespread, thus providing new solutions for robot services. They not only enable people to quickly and accurately grasp a large amount of valuable knowledge, but also better tap into the enormous potential contained in human intelligence, which largely drives the robot industry towards intelligence. By summarizing the existing research results, this paper explored the development trend of robot object recognition systems, and focused on its key technologies, the feature matching-based pattern recognition and acceleration strategy-based detection efficiency improvement. In response to the current problems, corresponding solutions were proposed and comparative experiments were designed. This proved that the anti-interference detection accuracy of the robot object recognition system based on big data and AI algorithm improved by about 12.48%, thus hoping to provide reference for future robot system development.
PACMMOD Volume 2 Issue 1: Editorial
Authors: Agrawal Divy , Meliou Alexandra , Sudarshan S.
Published: March 2024

Welcome to Issue 1 of Volume 2 of the Proceedings of the ACM on Management of Data, which has papers from the third round of submissions to the SIGMOD research track.

Out of 230 submissions in this round, whose submission deadline was July 15, 2023, a total of 71 articles were accepted and are presented in this issue.
High-performance Effective Scientific Error-bounded Lossy Compression with Auto-tuned Multi-component Interpolation
Authors: Liu Jinyang , Di Sheng , Zhao Kai , Liang Xin , Jin Sian , Jian Zizhe , Huang Jiajun , Wu Shixun , Chen Zizhong , Cappello Franck
Published: March 2024

Error-bounded lossy compression has been identified as a promising solution for significantly reducing scientific data volumes upon users' requirements on data distortion. For the existing scientific error-bounded lossy compressors, some of them (such as SPERR and FAZ) can reach fairly high compression ratios and some others (such as SZx, SZ, and ZFP) feature high compression speeds, but they rarely exhibit both high ratio and high speed meanwhile. In this paper, we propose HPEZ with newly-designed interpolations and quality-metric-driven auto-tuning, which features significantly improved compression quality upon the existing high-performance compressors, meanwhile being exceedingly faster than high-ratio compressors. The key contributions lie as follows: (1) We develop a series of advanced techniques such as interpolation re-ordering, multi-dimensional interpolation, and natural cubic splines to significantly improve compression qualities with interpolation-based data prediction. (2) The auto-tuning module in HPEZ has been carefully designed with novel strategies, including but not limited to block-wise interpolation tuning, dynamic dimension freezing, and Lorenzo tuning. (3) We thoroughly evaluate HPEZ compared with many other compressors on six real-world scientific datasets. Experiments show that HPEZ outperforms other high-performance error-bounded lossy compressors in compression ratio by up to 140% under the same error bound, and by up to 360% under the same PSNR. In parallel data transfer experiments on the distributed database, HPEZ achieves a significant performance gain with up to 40% time cost reduction over the second-best compressor.
MWP: Multi-Window Parallel Evaluation of Regular Path Queries on Streaming Graphs
Authors: Zhang Siyuan , He Zhenying , Jing Yinan , Zhang Kai , Wang X. Sean
Published: March 2024

A persistent Regular Path Query (RPQ) on a streaming graph is to continuously find every pair of vertices that are connected by a path in the graph within a sliding window, such that the edge label sequence of this path matches a given regular expression. The existing RPQ evaluation algorithm in the literature incrementally maintains a set of spanning-tree-like data structures to quickly form query results and to avoid reprocessing edges that are shared by multiple sliding windows. This approach allows parallel processing of the graph edges within a sliding window but requires a blocking expiration phase between sliding windows to remove the old edges. This blocking phase can significantly degrade the query performance, especially when the edges arrive quickly and the sliding windows overlap significantly.

This paper presents a new RPQ evaluation strategy called Multi-Window Parallel (MWP) method leveraging a new data structure called Timestamped Rooted Digraph (TRD). The novel idea is to incrementally maintain TRDs for the quick formulation of query results, like the aforementioned spanning trees, but simultaneously contain needed information for multiple sliding windows. MWP eliminates the forced blocking expiration phase. Only when memory runs low, a quick "dirty garbage collection" (DGC) process is done to remove some unneeded edges and nodes on TRDs, without incurring large costs. Extensive experiments on real graph datasets show that MWP significantly outperforms the existing algorithm in terms of throughput, tail latency, and scalability, and that DGC provides an effective solution for releasing memory with minimum impact.
Proximity Queries on Point Clouds using Rapid Construction Path Oracle
Authors: Yan Yinzhao , Wong Raymond Chi-Wing
Published: March 2024

The prevalence of computer graphics technology boosts the developments of point clouds in recent years, which offer advantages over terrain surfaces (represented by Triangular Irregular Networks, i.e., TINs) in proximity queries, including the shortest path query, the k-Nearest Neighbor (kNN) query and the range query. Since (1) all existing on-the-fly and oracle-based shortest path query algorithms on a TIN are very expensive, (2) all existing on-the-fly shortest path query algorithms on a point cloud are still not efficient, and (3) there are no oracle-based shortest path query algorithms on a point cloud, we propose an efficient (1+ε)-approximate shortest path oracle that answers the shortest path query for a set of Points-Of-Interests (POIs) on the point cloud, which has a good performance (in terms of the oracle construction time, oracle size and shortest path query time) due to the concise information about the pairwise shortest paths between any pair of POIs stored in the oracle. Our oracle can be easily adapted to answering the shortest path query for any points on the point cloud if POIs are not given as input, and also achieve a good performance. Then, we propose efficient algorithms for answering the (1+ε)-approximate kNN and range query with the assistance of our oracle. Our experimental results show that when POIs are given (resp. not given) as input, our oracle is up to 390 times, 30 times and 6 times (resp. 500 times, 140 times and 50 times) better than the best-known oracle on a TIN in terms of the oracle construction time, oracle size and shortest path query time, respectively. Our algorithms for the other two proximity queries are both up to 100 times faster than the best-known algorithms.
Starling: An I/O-Efficient Disk-Resident Graph Index Framework for High-Dimensional Vector Similarity Search on Data Segment
Authors: Wang Mengzhao , Xu Weizhi , Yi Xiaomeng , Wu Songlin , Peng Zhangyang , Ke Xiangyu , Gao Yunjun , Xu Xiaoliang , Guo Rentong , Xie Charles
Published: March 2024

High-dimensional vector similarity search (HVSS) is gaining prominence as a powerful tool for various data science and AI applications. As vector data scales up, in-memory indexes pose a significant challenge due to the substantial increase in main memory requirements. A potential solution involves leveraging disk-based implementation, which stores and searches vector data on high-performance devices like NVMe SSDs. However, implementing HVSS for data segments proves to be intricate in vector databases where a single machine comprises multiple segments for system scalability. In this context, each segment operates with limited memory and disk space, necessitating a delicate balance between accuracy, efficiency, and space cost. Existing disk-based methods fall short as they do not holistically address all these requirements simultaneously. In this paper, we present Starling, an I/O-efficient disk-resident graph index framework that optimizes data layout and search strategy within the segment. It has two primary components: (1) a data layout incorporating an in-memory navigation graph and a reordered disk-based graph with enhanced locality, reducing the search path length and minimizing disk bandwidth wastage; and (2) a block search strategy designed to minimize costly disk I/O operations during vector query execution. Through extensive experiments, we validate the effectiveness, efficiency, and scalability of Starling. On a data segment with 2GB memory and 10GB disk capacity, Starling can accommodate up to 33 million vectors in 128 dimensions, offering HVSS with over 0.9 average precision and top-10 recall rate, and latency under 1 millisecond. The results showcase Starling's superior performance, exhibiting 43.9x higher throughput with 98% lower query latency compared to state-of-the-art methods while maintaining the same level of accuracy.
Optimizing Nested Recursive Queries
Authors: Shaikhha Amir , Suciu Dan , Schleich Maximilian , Ngo Hung
Published: March 2024

Datalog is a declarative programming language that has gained popularity in various domains due to its simplicity, expressiveness, and efficiency. But "pure" Datalog is limited to monotone queries, and cannot be used in most practical applications. For that reason, newer systems are relaxing the language by allowing non-monotone queries to be freely combined with recursion. But by departing from the elegant fixpoint semantics of pure datalog, these systems often result in inefficient query execution, for example they perform redundant computations, or use redundant storage. In this paper, we propose Temporel, a system that allows recursion to be freely combined with non-monotone operators. Temporel optimizes the program by compiling it into a novel intermediate representation that we call TempoDL. Our experimental results show that our system outperforms a state-of-the-art Datalog engine as well as a vectorized and a compiled in-memory database system for a wide range of applications from machine learning to graph processing.
Efficient Distributed Hop-Constrained Path Enumeration on Large-Scale Graphs
Authors: Zeng Yuanyuan , Fang Yixiang , Ma Chenhao , Zhou Xu , Li Kenli
Published: March 2024

The enumeration of hop-constrained simple paths is a building block in many graph-based areas. Due to the enormous search spaces in large-scale graphs, a single machine can hardly satisfy the requirements of both efficiency and memory, which causes an urgent need for efficient distributed methods. In practice, it is inevitable to produce plenty of intermediate results when directly extending centralized methods to the distributed environment, thereby causing a memory crisis and weakening the query performance. The state-of-the-art distributed method HybridEnum designed a hybrid search paradigm to enumerate simple paths. However, it makes massive exploration for the redundant vertices not located in any simple path, thereby resulting in poor query performance. To alleviate this problem, we design a distributed approach DistriEnum to optimize query performance and scalability with well-bound memory consumption. Firstly, DistriEnum adopts a graph reduction strategy to rule out the redundant vertices without satisfying the constraint of hop number. Then, a core search paradigm is designed to simultaneously reduce the traversal of shared subpaths and the storage of intermediate results. Moreover, DistriEnum is equipped with a task division strategy to theoretically achieve workload balance. Finally, a vertex migration strategy is devised to reduce the communication cost during the enumeration. The comprehensive experimental results on 10 real-world graphs demonstrate that DistriEnum achieves up to 3 orders of magnitude speedup than HybridEnum in query performance and exhibits superior performances on scalability, communication cost, and memory consumption.
Spruce: a Fast yet Space-saving Structure for Dynamic Graph Storage
Authors: Shi Jifan , Wang Biao , Xu Yun
Published: March 2024

Dynamic graphs have been gaining increasing popularity across various application domains. With the growing size of these graphs, the update performance as well as space occupancy is becoming a crucial aspect of dynamic graph storage. Although existing dynamic graph systems can handle massive streaming updates (e.g., insertions and deletions), they cannot achieve both high throughput and low memory footprint. Drawing inspiration from the basic operations of the van Emde Boas (vEB) tree in double-logarithmic time, we designed Spruce, a high-performance yet space-saving in-memory structure to store dynamic graphs. Spruce uses a compact representation to construct the tree-like multilevel structure, which shares the common prefixes of vertices and has no merging or splitting of nodes to achieve the requirements of low memory consumption and high-efficiency dynamic operations. Furthermore, Spruce incorporates a read-optimized concurrency protocol, which refines ROWEX and Optimistic Locking, to facilitate efficient simultaneous read/write operations. Our experiment demonstrates that compared to Sortledton (the best of competitors), Spruce is up to 2.4X faster in ingesting graph updates, while saving up to 38.5% of memory space. As for graph analytics, Spruce shows high adaptability to different analytical workloads, and achieves comparable performance to other state-of-the-art dynamic graph structures.
Parallel Algorithms for Hierarchical Nucleus Decomposition
Authors: Shi Jessica , Dhulipala Laxman , Shun Julian
Published: March 2024

Nucleus decompositions have been shown to be a useful tool for finding dense subgraphs. The coreness value of a clique represents its density based on the number of other cliques it is adjacent to. One useful output of nucleus decomposition is to generate a hierarchy among dense subgraphs at different resolutions. However, existing parallel algorithms for nucleus decomposition do not generate this hierarchy, and only compute the coreness values. This paper presents a scalable parallel algorithm for hierarchy construction, with practical optimizations, such as interleaving the coreness computation with hierarchy construction and using a concurrent union-find data structure in an innovative way to generate the hierarchy. We also introduce a parallel approximation algorithm for nucleus decomposition, which achieves much lower span in theory and better performance in practice. We prove strong theoretical bounds on the work and span (parallel time) of our algorithms.

On a 30-core machine with two-way hyper-threading, our parallel hierarchy construction algorithm achieves up to a 58.84x speedup over the state-of-the-art sequential hierarchy construction algorithm by Sariyuce et al. and up to a 30.96x self-relative parallel speedup. On the same machine, our approximation algorithm achieves a 3.3x speedup over our exact algorithm, while generating coreness estimates with a multiplicative error of 1.33x on average.
Time Series Representation for Visualization in Apache IoTDB
Authors: Rui Lei , Huang Xiangdong , Song Shaoxu , Kang Yuyuan , Wang Chen , Wang Jianmin
Published: March 2024

When analyzing time series, often interactively, the analysts frequently demand to visualize instantly large-scale data stored in databases. M4 visualization selects the first, last, bottom and top data points in each pixel column to ensure pixel-perfectness of the two-color line chart visualization. While M4 already shows its preciseness of encasing time series in different scales into a fixed size of pixels, how to efficiently support M4 representation in a time series native database is still absent. It is worth noting that, to enable fast writes, the commodity time series database systems, such as Apache IoTDB or InfluxDB, employ LSM-Tree based storage. That is, a time series is segmented and stored in a number of chunks, with possibly out-of-order arrivals, i.e., disordered on timestamps. To implement M4, a natural idea is to merge online the chunks as a whole series, with costly merge sort on timestamps, and then perform M4 representation as in relational databases. In this study, we propose a novel chunk merge free approach called M4-LSM to accelerate M4 representation and visualization. In particular, we utilize the metadata of chunks to prune and avoid the costly merging of any chunk. Moreover, intra-chunk indexing and pruning are enabled for efficiently accessing the representation points, referring to the special properties of time series. Remarkably, the time series database native operator M4-LSM has been implemented in Apache IoTDB, an open-source time series database, and deployed in companies across various industries. In the experiments over real-world datasets, the proposed M4-LSM operator demonstrates high efficiency without sacrificing preciseness.