bluuebunny/crossref_metadata_2025 huggingface dataset:
A brief psychological intervention for chronic pain in primary care: Examining long‐term effects from a pilot randomized clinical trial
Authors: Miller‐Matero Lisa R. , Gavrilova Lyubov , Hecht Leah M. , Autio Kirsti , Tobin Erin T. , Braciszewski Jordan M. , Maye Melissa , Felton Julia W. , Ahmedani Brian K.
Published: June 2022

Background

Despite the existence of evidence‐based psychological interventions for pain management, there are barriers that interfere with treatment engagement. A brief intervention integrated into primary care reduced barriers and showed promising benefits from pre‐ to post‐intervention. However, it is unknown whether a brief intervention can provide long‐term effects. The purpose of this study was to examine whether a brief psychological intervention offered benefits in pain severity, pain interference, pain catastrophizing, and depressive symptoms at 1‐ and 6‐month follow‐ups.

Methods

The majority of participants who enrolled in a pilot randomized clinical trial of a 5‐session psychological intervention for chronic pain in primary care completed the 1‐month (n = 54; 90%) and 6‐month follow‐ups (n = 50; 83.3%). Participants completed measures of pain severity, pain interference, pain catastrophizing, and depressive symptoms.

Results

From baseline to the 6‐month follow‐up, those in the intervention group had significantly better outcomes for pain severity (p = 0.01) and pain catastrophizing (p = 0.003) compared with the control group. There were no significant differences between the intervention and control groups for pain interference and depression. The percentage of patients in the intervention experiencing clinically significant improvement across all outcomes was higher than the control group.

Conclusions

Findings suggest that a brief psychological intervention for chronic pain in primary care may offer longer‐term benefits similar to that of lengthier interventions. Future studies should examine this through a randomized clinical trial with a larger sample size.
Soil VOC emissions of a Mediterranean woodland are sensitive to shrub invasion
Authors: Meischner M. , Haberstroh S. , Daber L. E. , Kreuzwieser J. , Caldeira M. C. , Schnitzler J.‐P. , Werner C.
Published: June 2022

Many belowground processes, such as soil respiration and soil–atmosphere VOC (volatile organic compounds) exchange, are closely linked to soil microbiological processes. However, little is known about how changes in plant species cover, i.e. after plant invasion, alter these soil processes. In particular, the response of soil VOC emissions to plant invasion is not well understood.

We analysed soil VOC emissions and soil respiration of a Mediterranean cork oak (Quercus suber) ecosystem, comparing soil VOC emissions from a non‐invaded Q. suber woodland to one invaded by the shrub Cistus ladanifer. Soil VOC emissions were determined under controlled conditions using online proton‐transfer time‐of‐flight mass spectrometry. Net soil VOC emissions were measured by exposing soils with or without litter to different temperature and soil moisture conditions.

Soil VOC emissions were sensitive to C. ladanifer invasion. Highest net emission rates were determined for oxygenated VOC (acetaldehyde, acetone, methanol, acetic acid), and high temperatures enhanced total VOC emissions. Invasion affected the relative contribution of various VOC. Methanol and acetaldehyde were emitted exclusively from litter and were associated with the non‐invaded sites. In contrast, acetone emissions increased in response to shrub presence. Interestingly, low soil moisture enhanced the effect of shrub invasion on VOC emissions.

Our results indicate that shrub invasion substantially influences important belowground processes in cork oak ecosystems, in particular soil VOC emissions. High soil moisture is suggested to diminish the invasion effect through a moisture‐induced increase in microbial decomposition rates of soil VOC.
Division behaviours and their effects on pre‐implantation development of pig embryos
Authors: Tao Ruixin , Bi Jiaying , Zhu Fuquan , Wang Xuguang , Jia Chao , Xu Hongxia , He Xu , Li Juan
Published: June 2022

The quality of pre‐implantation embryos could affect developmental efficiency after embryo transfer. However, the assessment of pre‐implantation embryos was unsatisfactory, especially in pig embryos to date. Therefore, this study was designed to investigate available and applicable parameters that indicate developmental potential and quality of porcine pre‐implantation embryos produced by handmade cloning (HMC), and parthenogenetic activation without zona pellucida (PAZF) and with zona pellucida (PAZI). Firstly, a common division behaviour was detected, that is the formation of uneven division with two unequal size blastomeres (UD 2‐cell), especially in HMC embryos; then, the proportion of UD 2‐cell was found to be significantly higher than that of even division with equal size blastomeres (ED 2‐cell) (72.56 ± 4.56 vs. 24.57 ± 1.92). The formation of UD 2‐cell might be due to the spindle migration along the long axis in 1‐cell stage, and the cleavage furrow was not formed in the centre of cytoplasm. In the two sister blastomeres of UD 2‐cell, uneven distribution of organelles (mitochondria and lipid droplet) was observed with lower proportion in the smaller one (p < .05). Although no difference in blastocyst rate was observed between UD and ED 2‐cell embryos, the cell number per blastocyst from UD 2‐cell embryos was lower than that from ED 2‐cell embryos (44.15 ± 2.05 vs. 51.55 ± 1.83). Besides, because of non‐synchronized division of each blastomere, the following three cleavage routes were observed in all HMC/PAZF/PAZI embryos: T1 (2‐cell → 3‐cell → 4‐cell → ≥5‐cell → morula → blastocyst), T2 (2‐cell → 3‐cell → 4‐cell → morula → blastocyst) and T3 (2‐cell → 3‐cell/4‐cell → morula → blastocyst). Therefore, in pig in vitro‐produced embryos, division behaviours of uneven volume of cytoplasm and non‐synchronized cell cycles were observed at the early embryonic developmental stage, which might be another potential factor to evaluate embryonic development.
Solar radiation leads to increased collagenase gene expression (MMP1) in HERDA (Hereditary equine regional dermal asthenia) affected horses and may explain the typical dorsal distribution of their lesions
Authors: da Cunha Neto Campo Amor Vieira , Badial Peres Ramos , de Oliveira‐Filho José Paes , de Andrade Danilo Giorgi Abranches , Araujo Jr João Pessoa , Borges Alexandre Secorun
Published: June 2022

Background

Hereditary equine regional dermal asthenia (HERDA) is a genetic disease that alters collagen biosynthesis. Affected horses exhibit fragile, hyperextensible skin, especially over the dorsal region. Although ultraviolet (UV) radiation seems to contribute to the regional distribution of lesions and worsening of clinical signs, the molecular mechanisms involved are largely unknown.

Objectives

To evaluate the effect of solar radiation on matrix metalloproteinase MMP1, MMP8 and MMP13 gene expression in the dorsal and ventral skin of HERDA‐affected and HERDA‐unaffected horses [wild‐type (WT) horses].

Animals

Six HERDA‐affected and six unaffected Quarter horses (WT) were paired according to age, sex and coat colour.

Materials and methods

Horses were submitted to 30 day sunlight restriction, followed by 15 day sunlight exposure. Dorsal and ventral skin biopsies were obtained at six sampling times over 45 days. The expression of MMP1, MMP8 and MMP13 genes was measured by quantitative PCR.

Results

Although solar radiation modulated MMP1, MMP8 and MMP13 expression, the effects were more pronounced on MMP1. Sun exposure for three days significantly upregulated MMP1 in the dorsal region when compared to the ventral skin in both unaffected and HERDA‐affected horses.

Conclusions and clinical relevance

This study shows that solar irradiation leads to upregulation of skin collagenase genes particularly MMP1 in the dorsal, sun‐exposed skin of horses. Furthermore, this was more marked in HERDA‐affected horses. The increased activity of collagenases on the disorganised collagen present in HERDA affected horses would explain why UV radiation leads to deterioration of clinical signs in affected individuals.
Regulation of cardiovascular health and disease by visceral adipose tissue‐derived metabolic hormones
Authors: Vasamsetti Sathish Babu , Natarajan Niranjana , Sadaf Samreen , Florentin Jonathan , Dutta Partha
Published: June 2022

Visceral adipose tissue (VAT) is a metabolic organ known to regulate fat mass, and glucose and nutrient homeostasis. VAT is an active endocrine gland that synthesizes and secretes numerous bioactive mediators called ‘adipocytokines/adipokines’ into systemic circulation. These adipocytokines act on organs of metabolic importance like the liver and skeletal muscle. Multiple preclinical and in vitro studies showed strong evidence of the roles of adipocytokines in the regulation of metabolic disorders like diabetes, obesity and insulin resistance. Adipocytokines, such as adiponectin and omentin, are anti‐inflammatory and have been shown to prevent atherogenesis by increasing nitric oxide (NO) production by the endothelium, suppressing endothelium‐derived inflammation and decreasing foam cell formation. By inhibiting differentiation of vascular smooth muscle cells (VSMC) into osteoblasts, adiponectin and omentin prevent vascular calcification. On the other hand, adipocytokines like leptin and resistin induce inflammation and endothelial dysfunction that leads to vasoconstriction. By promoting VSMC migration and proliferation, extracellular matrix degradation and inflammatory polarization of macrophages, leptin and resistin increase the risk of atherosclerotic plaque vulnerability and rupture. Additionally, the plasma concentrations of these adipocytokines alter in ageing, rendering older humans vulnerable to cardiovascular disease. The disturbances in the normal physiological concentrations of these adipocytokines secreted by VAT under pathological conditions impede the normal functions of various organs and affect cardiovascular health. These adipokines could be used for both diagnostic and therapeutic purposes in cardiovascular disease.

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La aplicación de la cláusula compromisoria a los conflictos con administradores sociales
Authors: Valencia Correa Camila , Ibarra Ibarra Gustavo , Arteta Caballero Pablo J.
Published: June 2022

El presente artículo tiene como propósito analizar el alcance del pacto arbitral en el régimen societario colombiano, específicamente, en cómo hacer extensiva la cláusula compromisoria a las controversias con administradores sociales. La naturaleza del documento es de reflexión, su objetivo es presentar los resultados de una investigación desde una perspectiva analítica e interpretativa, acerca de la aplicación de la cláusula compromisoria a los conflictos suscitados con administradores sociales. Se emplearon los siguientes recursos metodológicos: en primer lugar, se realizó una revisión de literatura con el fin de analizar desde un punto de vista doctrinal y normativo el concepto del pacto arbitral y su aplicación en el contrato social. Posteriormente, se realizó un análisis de los pronunciamientos de la Delegatura de Procedimientos Mercantiles de la Superintendencia de Sociedades sobre la extensión del pacto arbitral a los administradores. Por último, se plantearon los argumentos que justifican la imposibilidad de aplicar la cláusula compromisoria a los administradores sin su consentimiento expreso.
El rol que desempeñan las empresas: retos y oportunidades en materia de derechos humanos
Authors: Cuervo Díaz Diana Elizabeth , Cuervo Díaz Nidia
Published: June 2022

En este mundo cambiante y lleno de retos, se hace cada vez más relevante y urgente confluir en principios y valores concretos, en busca de establecer un entendimiento común que dé fundamento sólido y ético a las acciones, donde los individuos, los Estados y las empresas deben llevar a cabo en las próximas décadas para salvaguardar y preservar nuestra existencia como sociedad y como raza. En este panorama adquieren vital relevancia los Principios Rectores sobre las Empresas y los Derechos Humanos de las Naciones Unidas (PRNU) (tablas 2, 3 y 4), los cuales son ampliamente conocidos como Principios de Ruggie, que John Ruggie, como secretario general de la ONU, logró su aceptación y posterior publicación en junio del 2011, después de años de arduo trabajo y esfuerzo conjunto. Estos principios están basados en tres pilares fundamentales: proteger, respetar y remediar; proteger los derechos humanos como obligación de los Estados; respetar los derechos humanos como responsabilidad de las empresas; y remediar los daños causados por las violaciones a los derechos humanos, mediante mecanismos eficaces y accesibles, implementados por los Estados y las empresas y son una herramienta conformada por 31 directrices. El presente artículo presenta una revisión del rol de las empresas de todos los niveles y estructuras, en materia de derechos unamos
Quantum thermodynamic methods to purify a qubit on a quantum processing unit
Authors: Solfanelli Andrea , Santini Alessandro , Campisi Michele
Published: June 2022

We report on a quantum thermodynamic method to purify a qubit on a quantum processing unit (QPU) equipped with (nearly) identical qubits. Our starting point is a three qubit design that emulates the well-known two qubit swap engine. Similar to standard fridges, the method would allow us to cool down a qubit at the expense of heating two other qubits. A minimal modification thereof leads to a more practical three qubit design that allows for enhanced refrigeration tasks, such as increasing the purity of one qubit at the expense of decreasing the purity of the other two. The method is based on the application of properly designed quantum circuits and can therefore be run on any gate model quantum computer. We implement it on a publicly available superconducting qubit based QPU and observe a purification capability down to 200 mK. We identify gate noise as the main obstacle toward practical application for quantum computing.
Immunoglobin G Sero-Dynamics Aided Host Specific Linear Epitope Identification and Differentiation of Infected from Vaccinated Hosts
Authors: Chen Xiaochun , Li Jingzhi , Yang Lan , Zhou Yuxi , Li Mengyu , Xu Wenwen , Qin Yixian , Su Jia , Zhao Wei , Gu Chaoyi , Sheng Shuixing , Pan Yongfei , Xue Qinghong , Ma Hongwei
Published: June 2022

Sudden outbreaks of pandemics caused by virus, such as SARS-CoV-2, has been determined as a public health emergency of international concern. However, the development of a DIVH-compatible vaccine is time-consuming and full of uncertainty, which is unsuitable for an emergent situation like the ongoing COVID-19 pandemic.
Isolation and Whole-Genome Sequencing of Four Antibiotic-Producing Pseudomonas Strains
Authors: Armstrong Audrey L. E. , Cole Kyle , Collins Emily , Easterday Jarret M. , Feddersen Lauren , Fleury Brianna , Johnson Lauren E. , Kecht Ankush F. , McClure Logan H. , Molinar Joselyn M. , Patel Anjali S. , Patel Ria , Rapala Jackson R. , Salomi Arunima , Stepter Amari A. , Wrobel Michal , Cozy Loralyn M.
Published: June 2022

Here, we report the isolation, whole-genome sequencing, and annotation of four novel
Pseudomonas
isolates. We also evaluate the biosynthetic potential of each genome.
The Genomic Characterization of Two Microbacterium foliorum–Specific Bacteriophages, QuadZero and AnnaLie
Authors: Cook-Easterwood Jennifer , Bethel Donovan J. , Kurikose Irene , Katsanos Joanna
Published: June 2022

The microbacteriophages QuadZero and AnnaLie were isolated from soil samples from Charlotte, NC, and were classified into EA and EB clusters, respectively. QuadZero has a 40,140 base-pair double-stranded DNA genome with 62 predicted protein coding genes, whereas AnnaLie has a 41,665-bp genome with 71 predicted protein coding genes.
Complete Genome Sequences of Two Bacillus velezensis Strains Isolated from California Raisin Vineyard Soils
Authors: Palumbo Jeffrey D. , O’Keeffe Teresa L. , Huynh Steven , Lee Bertram , Parker Craig T.
Published: June 2022

Bacillus velezensis
strains JP3042 and JP3144 were isolated from California raisin vineyard soils and were selected for further study of
in vitro
antifungal activity. Here, we present the complete genome sequences of these strains to aid in the understanding of their antifungal activity and diversity within the species.
Soil Collected in the Great Smoky Mountains National Park Yielded a Novel
Listeria sensu stricto
Species,
L. swaminathanii
Authors: Carlin Catharine R. , Liao Jingqiu , Hudson Lauren K. , Peters Tracey L. , Denes Thomas G. , Orsi Renato H. , Guo Xiaodong , Wiedmann Martin
Published: June 2022

L. swaminathanii
is a novel
sensu stricto
species that originated from a US National Park and it will be the first
Listeria
identified to date without official standing in the nomenclature. Validation was impeded by the National Park’s requirements for strain access, ultimately deemed too restrictive by the International Committee on Systematics of Prokaryotes.
Dietary factors that affect the risk of pre-eclampsia
Authors: Perry Abigail , Stephanou Anna , Rayman Margaret P
Published: June 2022

Pre-eclampsia affects 3%–5% of pregnant women worldwide and is associated with a range of adverse maternal and fetal outcomes, including maternal and/or fetal death. It particularly affects those with chronic hypertension, pregestational diabetes mellitus or a family history of pre-eclampsia. Other than early delivery of the fetus, there is no cure for pre-eclampsia. Since diet or dietary supplements may affect the risk, we have carried out an up-to-date, narrative literature review to assess the relationship between nutrition and pre-eclampsia. Several nutrients and dietary factors previously believed to be implicated in the risk of pre-eclampsia have now been shown to have no effect on risk; these include vitamins C and E, magnesium, salt, ω-3 long-chain polyunsaturated fatty acids (fish oils) and zinc. Body mass index is proportionally correlated with pre-eclampsia risk, therefore women should aim for a healthy pre-pregnancy body weight and avoid excessive gestational and interpregnancy weight gain. The association between the risk and progression of the pathophysiology of pre-eclampsia may explain the apparent benefit of dietary modifications resulting from increased consumption of fruits and vegetables (≥400 g/day), plant-based foods and vegetable oils and a limited intake of foods high in fat, sugar and salt. Consuming a high-fibre diet (25–30 g/day) may attenuate dyslipidaemia and reduce blood pressure and inflammation. Other key nutrients that may mitigate the risk include increased calcium intake, a daily multivitamin/mineral supplement and an adequate vitamin D status. For those with a low selenium intake (such as those living in Europe), fish/seafood intake could be increased to improve selenium intake or selenium could be supplemented in the recommended multivitamin/mineral supplement. Milk-based probiotics have also been found to be beneficial in pregnant women at risk. Our recommendations are summarised in a table of guidance for women at particular risk of developing pre-eclampsia.
Effects of social determinants on children’s health in informal settlements in Bangladesh and Kenya through an intersectionality lens: a study protocol
Authors: Kibuchi Eliud , Barua Proloy , Chumo Ivy , Teixeira de Siqueira Filha Noemia , Phillips-Howard Penelope , Mithu Md Imran Hossain , Kabaria Caroline , Quayyum Zahidul , Whittaker Lana , Dean Laura , Forsyth Ross , Selim Tasmiah , Aktar Bachera , Sai Varun , Garimella Sureka , Saidu Samuel , Gandi Ibrahim , Josyula Lakshmi K , Mberu Blessing , Elsey Helen , Leyland Alastair H , Gray Linsay
Published: June 2022

Introduction

Several studies have shown that residents of urban informal settlements/slums are usually excluded and marginalised from formal social systems and structures of power leading to disproportionally worse health outcomes compared to other urban dwellers. To promote health equity for slum dwellers, requires an understanding of how their lived realities shape inequities especially for young children 0–4 years old (ie, under-fives) who tend to have a higher mortality compared with non-slum children. In these proposed studies, we aim to examine how key Social Determinants of Health (SDoH) factors at child and household levels combine to affect under-five health conditions, who live in slums in Bangladesh and Kenya through an intersectionality lens.

Methods and analysis

The protocol describes how we will analyse data from the Nairobi Cross-sectional Slum Survey (NCSS 2012) for Kenya and the Urban Health Survey (UHS 2013) for Bangladesh to explore how SDoH influence under-five health outcomes in slums within an intersectionality framework. The NCSS 2012 and UHS 2013 samples will consist of 2199 and 3173 under-fives, respectively. We will apply Multilevel Analysis of Individual Heterogeneity and Discriminatory Accuracy approach. Some of SDoH characteristics to be considered will include those of children, head of household, mothers and social structure characteristics of household. The primary outcomes will be whether a child had diarrhoea, cough, fever and acute respiratory infection (ARI) 2 weeks preceding surveys.

Ethics and dissemination

The results will be disseminated in international peer-reviewed journals and presented in events organised by the Accountability and Responsiveness in Informal Settlements for Equity consortium and international conferences. Ethical approval was not required for these studies. Access to the NCSS 2012 has been given by Africa Population and Health Center and UHS 2013 is freely available.
Managing dental unit waterlines: a quality improvement programme
Authors: Umer Fahad , Khan Madiha , Khan Farhan Raza , Tejani Karim
Published: June 2022

The presence of bacterial biofilms within dental unit waterlines (DUWLs) can cause secondary bacterial infections in immunocompromised patients. As a result, the management of biofilms within waterlines has always concerned medical and dental professionals. In February 2020, an internal audit identified the high bacterial counts within the DUWLs at the Aga Khan University Hospital, Karachi and this paper discusses a pragmatic approach to improving the water quality of DUWLs.

A three-person committee was developed and the area for improvement was identified as the contaminated DUWLs. Distilled water samples from two dental units were first assessed as baseline in July 2020. The process changes were then implemented which included daily flushing of the dental unit waterlines and ‘shock treatment’ using A-dec ICX capsules. Subsequently, the units were tested after intervention on 24 August 2020 and water from all 16 dental units assessed on 20 November 2020 and again on 22 April 2021.

The samples from all the dental units assessed showed marked reduction in bacterial counts and compliance with the Centers for Disease Control guidelines after intervention. All the dental units showed minimal bacterial counts; however, a slightly low pH was noted in the final round of water testing.

DUWLs are heavily contaminated with microbes and pose potential risk both to the patient as well as the DHCPs. This study suggests that chemical disinfection using A-dec ICX tablets and flushing as an effective method of reducing the bacterial load in DUWLs.
Defining case management success: a qualitative study of case manager perspectives from a large-scale health and social needs support program
Authors: Knox Margae , Esteban Emily E , Hernandez Elizabeth A , Fleming Mark D , Safaeinilli Nadia , Brewster Amanda L
Published: June 2022

Objective

Health systems are expanding efforts to address health and social risks, although the heterogeneity of early evidence indicates need for more nuanced exploration of how such programs work and how to holistically assess program success. This qualitative study aims to identify characteristics of success in a large-scale, health and social needs case management program from the perspective of interdisciplinary case managers.

Setting

Case management program for high-risk, complex patients run by an integrated, county-based public health system.

Participants

30 out of 70 case managers, purposively sampled to represent their interdisciplinary health and social work backgrounds. Interviews took place in March–November 2019.

Primary and secondary outcome measures

The analysis intended to identify characteristics of success working with patients.

Results

Case managers described three characteristics of success working with patients: (1) establishing trust; (2) observing change in patients’ mindset or initiative and (3) promoting stability and independence. Cross-cutting these characteristics, case managers emphasised the importance of patients defining their own success, often demonstrated through individualised, incremental progress. Thus, moments of success commonly contrasted with external perceptions and operational or productivity metrics.

Conclusions

Themes emphasise the importance of compassion for complexity in patients’ lives, and success as a step-by-step process that is built over longitudinal relationships.
A road modulus test method based on rigid spherical indentation
Authors: Zhang Yining , Sun Lijun
Published: June 2022

Currently, the modulus test method such as falling weight deflectometer has an inevitable problem of stress concentration, which may lead to a negative impact on the results. This paper attempted to apply the spherical indentation test equipment into road detection to solve this problem. Firstly, by following the displacement boundary conditions, a general expression of modulus, force, and displacement under the semi-infinite system was established. Compared with the Sneddon’s formula (a classic formula in materials industry), this expression was consistent with it under the small deformation situations, which verified the rationality of this method. Moreover, this expression can also be utilized in the larger deformation situations, which was more in line with the pavement environment. Then, by further improving the method, this paper established the method of calculating the structure modulus of new pavement layers. Finally, a specific test method for modulus detection based on the spherical indentation was proposed.
Transverse Goldstone mode in holographic fluids with broken translations
Authors: Zhong Yuan-Yuan , Li Wei-Jia
Published: June 2022

In this paper we investigate the low energy shear modes in fluid systems with spontaneously broken translations by a specific holographic model. In absence of momentum relaxation, we find that there exist two decoupled gapless modes in the transverse channel, one of which is purely diffusive and the other corresponds to vortex like excitations. The diffusive mode is associated with the conservation of momentum and the vortex mode can be viewed as the Goldstone mode of the spontaneous symmetry breaking. Switching on an external source which breaks the translations explicitly but weakly, the would-be gapless modes both get relaxed and acquire a tiny mass gap. Finally, in the strong momentum relaxation regime, we find a (pseudo-)diffusive-to-sound crossover that is set by a momentum gap.
Semi-empirical relation to understand matter properties at neutron star interiors
Authors: Mallick Ritam , Kuzur Debojoti , Nandi Rana
Published: June 2022

The occurrence of quark matter at the center of neutron stars is still in debate. This study defines some semi-empirical parameters that try to quantify the presence and the amount of quark matter at star interiors. We find that one needs unusually accurate measurement to qualitatively deduce the occurrence of quark core at the center of stars by studying the compactness of a fast rotating star as a function of angular momentum. Nevertheless one can deduce the quark content of a static 1.4 solar mass star and extend it for a rotating star. The quark fractions in a star depend on the stiffness of the equation of state and the critical density for phase transition. As the phase transition from the neutron star to a hybrid star happens, the star shrinks, releasing significant energy. A massive neutron star usually collapses into a black hole if the phase transition happens at constant baryonic mass. Given a hadronic EoS, we have shown how one can have a critical mass of the neutron star and the corresponding maximum mass of the hybrid star for a given equation of state.
Transfer Learning-based Hybrid Approach for Bayesian Network Structure Learning
Authors: Jose Sonu , Louis Sushil , Dascalu Sergiu , Liu Siming
Published: June 2022

Bayesian network is a graphical model that is widely used to perform probabilistic reasoning. However, learning the structure of Bayesian network is a complex task. In this paper, we propose a hybrid structure learning algorithm that has two phases: a constraint-based phase to reduce the search space and a score-and-search phase that employs case-injected genetic algorithms for determining the optimal structure from the reduced space of structures. We use a case-injected genetic algorithm-based hybrid approach for the structure learning in order to improve the learning accuracy over similar problems. A case-injected genetic algorithm is the augmentation of a case-based memory with the Genetic Algorithm (GA). Thereby, it finds near-optimal solutions in fewer generations compared to GA. Our method stores relevant or partial solutions in a case-base while solving the problems and utilizes those stored solutions on new similar problems. We use small-to-very large networks for assessing our viability of our approach. In this paper, a series of experiments are conducted on datasets generated from four benchmark Bayesian networks. We compare our method against GA-based hybrid approach and a state-of-the-art algorithm, Max-Min Hill Climbing (MMHC). Presented results indicate an enhanced improvement of our approach over GA and MMHC in learning the Bayesian network structures.
POMACS V6, N2, June 2022 Editorial
Authors: Carlsson Niklas , Cohen Edith , Robert Philippe
Published: June 2022

The ACM Proceedings of the ACM on Measurement and Analysis of Computing Systems (POMACS) focuses on the measurement and performance evaluation of computer systems and operates in close collaboration with the ACM Special Interest Group SIGMETRICS. All papers in this issue of POMACS will be presented during the ACM SIGMETRICS/Performance 2022 conference. The issue contains papers selected by the editorial board via a rigorous review process that follows a hybrid conference and journal model, with reviews conducted by the 101 members of our POMACS editorial board. Each paper was either conditionally accepted (and shepherded), allowed a "one-shot" revision (to be resubmitted to one of the subsequent two deadlines), or rejected (with resubmission allowed after a year). For this issue, which represents the winter deadline, we accepted 17 papers out of 126 submissions (including 4 papers that had been given a "one-shot" revision opportunity). All submitted papers received at least 3 reviews and we held an online TPC meeting. Based on the indicated primary track, roughly 31% of the submissions were in the Measurement & Applied Modeling track, 25% were in the Systems track, 23% were in the Theory track, and 21% were in the Learning track. Many people contributed to the success of this issue of POMACS. First, we would like to thank the authors, who submitted their work to SIGMETRICS/POMACS. Second, we would like to thank the TPC members for their work: constructive feedback in their reviews to authors, participation to online discussions and also to TPC meetings. We also thank several external reviewers who provided their expert opinion on specific submissions that required additional input. We are also grateful to the SIGMETRICS Board Chair, Giuliano Casale, and to past TPC Chairs. Finally, we are grateful to the Organization Committee and to the SIGMETRICS Board for their ongoing efforts and initiatives for creating an exciting program for ACM SIGMETRICS/Performance 2022.
Learning To Maximize Welfare with a Reusable Resource
Authors: Faw Matthew , Papadigenopoulos Orestis , Caramanis Constantine , Shakkottai Sanjay
Published: June 2022

Considerable work has focused on optimal stopping problems where random IID offers arrive sequentially for a single available resource which is controlled by the decision-maker. After viewing the realization of the offer, the decision-maker irrevocably rejects it, or accepts it, collecting the reward and ending the game. We consider an important extension of this model to a dynamic setting where the resource is "renewable'' (a rental, a work assignment, or a temporary position) and can be allocated again after a delay period d. In the case where the reward distribution is known a priori, we design an (asymptotically optimal) 1/2-competitive Prophet Inequality, namely, a policy that collects in expectation at least half of the expected reward collected by a prophet who a priori knows all the realizations. This policy has a particularly simple characterization as a thresholding rule which depends on the reward distribution and the blocking period d, and arises naturally from an LP-relaxation of the prophet's optimal solution. Moreover, it gives the key for extending to the case of unknown distributions; here, we construct a dynamic threshold rule using the reward samples collected when the resource is not blocked. We provide a regret guarantee for our algorithm against the best policy in hindsight, and prove a complementing minimax lower bound on the best achievable regret, establishing that our policy achieves, up to poly-logarithmic factors, the best possible regret in this setting.
Prediction of the Resource Consumption of Distributed Deep Learning Systems
Authors: Yang Gyeongsik , Shin Changyong , Lee Jeunghwan , Yoo Yeonho , Yoo Chuck
Published: June 2022

The prediction of the resource consumption for the distributed training of deep learning models is of paramount importance, as it can inform a priori users how long their training would take and also enable users to manage the cost of training. Yet, no such prediction is available for users because the resource consumption itself varies significantly according to "settings" such as GPU types and also by "workloads" like deep learning models. Previous studies have aimed to derive or model such a prediction, but they fall short of accommodating the various combinations of settings and workloads together. This study presents Driple that designs graph neural networks to predict the resource consumption of diverse workloads. Driple also designs transfer learning to extend the graph neural networks to adapt to differences in settings. The evaluation results show that Driple can effectively predict a wide range of workloads and settings. At the same time, Driple can efficiently reduce the time required to tailor the prediction for different settings by up to 7.3×.
An Enterprise-Grade Open-Source Data Reduction Architecture for All-Flash Storage Systems
Authors: Ajdari Mohammadamin , Raaf Patrick , Kishani Mostafa , Salkhordeh Reza , Asadi Hossein , Brinkmann André
Published: June 2022

All-flash storage (AFS) systems have become an essential infrastructure component to support enterprise applications, where sub-millisecond latency and very high throughput are required. Nevertheless, the price per capacity ofsolid-state drives (SSDs) is relatively high, which has encouraged system architects to adoptdata reduction techniques, mainlydeduplication andcompression, in enterprise storage solutions. To provide higher reliability and performance, SSDs are typically grouped usingredundant array of independent disk (RAID) configurations. Data reduction on top of RAID arrays, however, adds I/O overheads and also complicates the I/O patterns redirected to the underlying backend SSDs, which invalidates the best-practice configurations used in AFS. Unfortunately, existing works on the performance of data reduction do not consider its interaction and I/O overheads with other enterprise storage components including SSD arrays and RAID controllers. In this paper, using a real setup with enterprise-grade components and based on the open-source data reduction module RedHat VDO, we reveal novel observations on the performance gap between the state-of-the-art and the optimal all-flash storage stack with integrated data reduction. We therefore explore the I/O patterns at the storage entry point and compare them with those at the disk subsystem. Our analysis shows a significant amount of I/O overheads for guaranteeing consistency and avoiding data loss through data journaling, frequent small-sized metadata updates, and duplicate content verification. We accompany these observations with cross-layer optimizations to enhance the performance of AFS, which range from deriving new optimal hardware RAID configurations up to introducing changes to the enterprise storage stack. By analyzing the characteristics of I/O types and their overheads, we propose three techniques: (a) application-aware lazy persistence, (b) a fast, read-only I/O cache for duplicate verification, and (c) disaggregation of block maps and data by offloading block maps to a very fast persistent memory device. By consolidating all proposed optimizations and implementing them in an enterprise AFS, we show 1.3× to 12.5× speedup over the baseline AFS with 90% data reduction, and from 7.8× up to 57× performance/cost improvement over an optimized AFS (with no data reduction) running applications ranging from 100% read-only to 100% write-only accesses.
Monetizing Spare Bandwidth
Authors: Xiao Yunming , Varvello Matteo , Kuzmanovic Aleksandar
Published: June 2022

Residential Internet speeds have been rapidly increasing, reaching averages of ~100 Mbps in most developed countries. Several studies have shown that users have way more bandwidth than they need, only using about 20-30% on a regular day. Several systems exploit this trend by enabling users to monetize their spare bandwidth, e.g., by sharing their WiFi connection or by participating in distributed proxy or VPN (dVPN) services. Despite the proliferation of such systems, little is known on how such marketplaces operate, what are the key factors that determine the price of the spare bandwidth, and how such prices differ worldwide. In this work, we shed some light on this topic using dVPNs as a use-case. We start by formalizing the problem of bandwidth monetization as an optimization between a buyer's cost and seller's income. Next, we explore three popular dVPNs (Mysterium, Sentinel, and Tachyon) using both active and passive measurements. We find that dVPNs have a large and growing footprint, and offer comparable performance to their centralized counterpart. We identify Mysterium (in the US) as the most concrete realization of a bandwidth marketplace, for which we derive a value of spare Internet bandwidth ranging between 11 and 14 cents per GB. We also show that both buyers and sellers utilize ad-hoc "rules-of-thumb" when choosing their prices, which results in a sub-optimal marketplace. By applying our optimization, a seller's income can be tripled by setting a price lower than the default one which allows to attract more buyers. These observations motivate us to create RING, a first and concrete system which helps sellers to automatically adjust their prices and traffic volumes across multiple marketplaces.
Hierarchical Learning Algorithms for Multi-scale Expert Problems
Authors: Yang Lin , Chen Yu-Zhen Janice , Hajiesmaili Mohammad H. , Herbster Mark , Towsley Don
Published: June 2022

In this paper, we study the multi-scale expert problem, where the rewards of different experts vary in different reward ranges. The performance of existing algorithms for the multi-scale expert problem degrades linearly proportional to the maximum reward range of any expert or the best expert and does not capture the non-uniform heterogeneity in the reward ranges among experts. In this work, we propose learning algorithms that construct a hierarchical tree structure based on the heterogeneity of the reward range of experts and then determine differentiated learning rates based on the reward upper bounds and cumulative empirical feedback over time. We then characterize the regret of the proposed algorithms as a function of non-uniform reward ranges and show that their regrets outperform prior algorithms when the rewards of experts exhibit non-uniform heterogeneity in different ranges. Last, our numerical experiments verify our algorithms' efficiency compared to previous algorithms.
Toxicity in the Decentralized Web and the Potential for Model Sharing
Authors: Bin Zia Haris , Raman Aravindh , Castro Ignacio , Hassan Anaobi Ishaku , De Cristofaro Emiliano , Sastry Nishanth , Tyson Gareth
Published: June 2022

The "Decentralised Web" (DW) is an evolving concept, which encompasses technologies aimed at providing greater transparency and openness on the web. The DW relies on independent servers (aka instances) that mesh together in a peer-to-peer fashion to deliver a range of services (e.g. micro-blogs, image sharing, video streaming). However, toxic content moderation in this decentralised context is challenging. This is because there is no central entity that can define toxicity, nor a large central pool of data that can be used to build universal classifiers. It is therefore unsurprising that there have been several high-profile cases of the DW being misused to coordinate and disseminate harmful material. Using a dataset of 9.9M posts from 117K users on Pleroma (a popular DW microblogging service), we quantify the presence of toxic content. We find that toxic content is prevalent and spreads rapidly between instances. We show that automating per-instance content moderation is challenging due to the lack of sufficient training data available and the effort required in labelling. We therefore propose and evaluate ModPair, a model sharing system that effectively detects toxic content, gaining an average per-instance macro-F1 score 0.89.
Tensor Completion with Nearly Linear Samples Given Weak Side Information
Authors: Yu Christina Lee , Xi Xumei
Published: June 2022

Tensor completion exhibits an interesting computational-statistical gap in terms of the number of samples needed to perform tensor estimation. While there are only Θ(tn) degrees of freedom in a t-order tensor with n^t entries, the best known polynomial time algorithm requires O(n^t/2 ) samples in order to guarantee consistent estimation. In this paper, we show that weak side information is sufficient to reduce the sample complexity to O(n). The side information consists of a weight vector for each of the modes which is not orthogonal to any of the latent factors along that mode; this is significantly weaker than assuming noisy knowledge of the subspaces. We provide an algorithm that utilizes this side information to produce a consistent estimator with O(n^1+κ ) samples for any small constant κ > 0. We also provide experiments on both synthetic and real-world datasets that validate our theoretical insights.
TauSSA
Authors: Sheldon Matthew , Casale Giuliano
Published: June 2022

In this paper, we present TauSSA, a discrete-event simulation tool for stochastic queueing networks integrated in the LINE solver. TauSSA combines Gillespie's stochastic simulation algorithm with tau leaping, a methodology for optimistic simulation acceleration. Although tau leaping is frequently used in chemical reaction network simulation, it has so far found limited application in queueing theory. TauSSA offers one of the very first attempts to make this method broadly applicable to analyze extended queueing network models, which include class switching, fork-join, and non-exponential service and arrival distributions. We conceptualize various strategies for handling ordering and illegal states in tau leaping that arise specifically within queueing network models, and compare their performance through numerical experiments. Our main finding is that strategies that sort events based on the network topological order incur a better trade-off between speedup and approximation error.
PIPE 2.7 overview A Petri net tool for performance modeling and evaluation
Authors: Llado Catalina M.
Published: June 2022

The Petri net modeling formalism allows for the convenient graphical visualization of system models, as well as the modeling and performance analysis of complex stochastic systems. PIPE is an open source, platform independent tool for creating and analysing Petri nets including GSPNs (Generalized Stochastic Petri Nets). It is implemented entirely in Java and provides an easy-to-use graphical user interface that allows creating, saving and loading of Petri as well as its qualitative and quantitative analysis. This paper describes PIPE 2.7, its main features, including its GUI, modeling power, and analysis functionality.
The ORIS tool
Authors: Carnevali Laura , Paolieri Marco , Vicario Enrico
Published: June 2022

ORIS is a tool for quantitative modeling and evaluation of concurrent systems with non-Markovian durations. It provides a Graphical User Interface (GUI) for model specification as Stochastic Time Petri Nets (STPNs), validation by interactive simulation, and evaluation by several techniques, computing instantaneous and cumulative rewards. It also provides an open-source Java Application Programming Interface (API) to automate the workflow, and it can be used as a toolkit for derivation and evaluation of STPNs in model driven engineering. As distinguishing features, ORIS implements transient and steady-state analysis of STPNs with underlying Markov Regenerative Process (MRP), and transient analysis of STPNs with underlying Generalized Semi- Markov Process (GSMP). It also implements nondeterministic analysis of Time Petri Nets (TPNs), simulation of STPNs, and solution methods for Continuous-Time Markov Chains (CTMCs) and MRPs with at most one non-exponential timer in each state. The well-engineered software architecture of ORIS supports agile implementation of new STPN features, new modeling formalisms, and new analysis methods.
Stochastic modelling and evaluation using GreatSPN
Authors: Amparore Elvio G.
Published: June 2022

GreatSPN is a tool that supports model-based (stochastic) analysis of Discrete Event Dynamic Systems (DEDS) modeled as Generalized Stochastic Petri Nets or one of its extensions like StochasticWell-formed Nets, Deterministic and Stochastic Petri Nets among the other. Performance evaluation of the timed and stochastic properties of the modeled systems was the initial reason for the tool development, and it is today a large and flexible framework that incorporates several analysis techniques, performance index types, variegated transition timing specifications, etc. In this paper we report the current status of the GreatSPN framework, with a focus on the modularity, the types of stochastic analysis, the specification and evaluation functionalities, and its role for the performance evaluation.
The Genomics of Auditory Function and Disease
Authors: Taiber Shahar , Gwilliam Kathleen , Hertzano Ronna , Avraham Karen B.
Published: June 2022

Current estimates suggest that nearly half a billion people worldwide are affected by hearing loss. Because of the major psychological, social, economic, and health ramifications, considerable efforts have been invested in identifying the genes and molecular pathways involved in hearing loss, whether genetic or environmental, to promote prevention, improve rehabilitation, and develop therapeutics. Genomic sequencing technologies have led to the discovery of genes associated with hearing loss. Studies of the transcriptome and epigenome of the inner ear have characterized key regulators and pathways involved in the development of the inner ear and have paved the way for their use in regenerative medicine. In parallel, the immense preclinical success of using viral vectors for gene delivery in animal models of hearing loss has motivated the industry to work on translating such approaches into the clinic. Here, we review the recent advances in the genomics of auditory function and dysfunction, from patient diagnostics to epigenetics and gene therapy.