bluuebunny/crossref_metadata_2025 huggingface dataset:
A Phase 2 Randomized Trial Evaluating the Antiviral Activity and Safety of the Direct-Acting Antiviral Bemnifosbuvir in Ambulatory Patients with Mild or Moderate COVID-19 (MOONSONG Study)
Authors: Boffito Marta , Dolan Eamon , Singh Karishma , Holmes William , Wildum Steffen , Horga Arantxa , Pietropaolo Keith , Zhou Xiao-Jian , Clinch Barry , Collinson Neil , Ukachukwu Vincent
Published: June 2023

COVID-19 continues to be a major global public health challenge, and there remains a need for effective and convenient direct-acting antivirals that can be administered outside health care settings. Bemnifosbuvir is an oral antiviral with a dual mechanism of action and potent
in vitro
activity against SARS-CoV-2.
Previous Antibiotic Exposure Reshapes the Population Structure of Infecting Uropathogenic Escherichia coli Strains by Selecting for Antibiotic Resistance over Urovirulence
Authors: Ballash Gregory A. , Diaz-Campos Dubraska , van Balen Joany C. , Mollenkopf Dixie F. , Wittum Thomas E.
Published: June 2023

Urinary tract infections (UTIs) are one of the most common infections of dogs and humans. While antibiotic therapy is the standard of care for UTIs and other infections, antibiotic exposure may influence the pathogenic profile of subsequent infections.
Effects of size at birth on health, growth and developmental outcomes in children up to age 18: an umbrella review
Authors: Jamaluddine Zeina , Sharara Eman , Helou Vanessa , El Rashidi Nadine , Safadi Gloria , El-Helou Nehmat , Ghattas Hala , Sato Miho , Blencowe Hannah , Campbell Oona M R
Published: June 2023

Background

Size at birth, an indicator of intrauterine growth, has been studied extensively in relation to subsequent health, growth and developmental outcomes. Our umbrella review synthesises evidence from systematic reviews and meta-analyses on the effects of size at birth on subsequent health, growth and development in children and adolescents up to age 18, and identifies gaps.

Methods

We searched five databases from inception to mid-July 2021 to identify eligible systematic reviews and meta-analyses. For each meta-analysis, we extracted data on the exposures and outcomes measured and the strength of the association.

Findings

We screened 16 641 articles and identified 302 systematic reviews. The literature operationalised size at birth (birth weight and/or gestation) in 12 ways. There were 1041 meta-analyses of associations between size at birth and 67 outcomes. Thirteen outcomes had no meta-analysis.

Small size at birth was examined for 50 outcomes and was associated with over half of these (32 of 50); continuous/post-term/large size at birth was examined for 35 outcomes and was consistently associated with 11 of the 35 outcomes. Seventy-three meta-analyses (in 11 reviews) compared risks by size for gestational age (GA), stratified by preterm and term. Prematurity mechanisms were the key aetiologies linked to mortality and cognitive development, while intrauterine growth restriction (IUGR), manifesting as small for GA, was primarily linked to underweight and stunting.

Interpretation

Future reviews should use methodologically sound comparators to further understand aetiological mechanisms linking IUGR and prematurity to subsequent outcomes. Future research should focus on understudied exposures (large size at birth and size at birth stratified by gestation), gaps in outcomes (specifically those without reviews or meta-analysis and stratified by age group of children) and neglected populations.

PROSPERO registration number

CRD42021268843.
Symptomatic aortic thrombosis in a preterm neonate
Authors: Kukreja Bhavya , Agrawal Vishnu Dutta , Singh Amandeep , Shankar Kaushaki
Published: June 2023

Symptomatic aortic thrombosis is a devastating condition in the neonatal intensive care unit (NICU), which is now increasingly being diagnosed with the availability of bedside ultrasound. Early intervention can go a long way towards preventing adverse outcomes. In our case, a preterm, very low birth weight, growth-restricted baby developed aortic thrombosis with hypertensive emergency and later limb-threatening ischaemia, which usually requires thrombolysis. However, due to the parents’ reservations, he was given only therapeutic anticoagulation (with closely monitored activated partial thromboplastin time targets), which resulted in complete thrombus resolution. A multidisciplinary team approach was followed, and early detection with frequent monitoring led us to a favourable outcome.
Detecting the corneal neovascularisation area using artificial intelligence
Authors: Mergen Burak , Safi Tarek , Nadig Matthias , Bhattrai Gopal , Daas Loay , Alexandersson Jan , Seitz Berthold
Published: June 2023

Aims

To create and assess the performance of an artificial intelligence-based image analysis tool for the measurement and quantification of the corneal neovascularisation (CoNV) area.

Methods

Slit lamp images of patients with CoNV were exported from the electronic medical records and included in the study. An experienced ophthalmologist made manual annotations of the CoNV areas, which were then used to create, train and evaluate an automated image analysis tool that uses deep learning to segment and detect CoNV areas. A pretrained neural network (U-Net) was used and fine-tuned on the annotated images. Sixfold cross-validation was used to evaluate the performance of the algorithm on each subset of 20 images. The main metric for our evaluation was intersection over union (IoU).

Results

The slit lamp images of 120 eyes of 120 patients with CoNV were included in the analysis. Detections of the total corneal area achieved IoU between 90.0% and 95.5% in each fold and those of the non-vascularised area achieved IoU between 76.6% and 82.2%. The specificity for the detection was between 96.4% and 98.6% for the total corneal area and 96.6% and 98.0% for the non-vascularised area.

Conclusion

The proposed algorithm showed a high accuracy compared with the measurement made by an ophthalmologist. The study suggests that an automated tool using artificial intelligence may be used for the calculation of the CoNV area from the slit-lamp images of patients with CoNV.
Network pharmacology and biochemical experiments reveal the antiapoptotic mechanism of huperzine A for treating diabetic retinopathy
Authors: Zhang Ying , Huang Wunan , Tian Qing , Bai Guannan , Wu Wei , Yin Houfa , Hu Lidan , Chen Xiangjun
Published: June 2023

Background/aims

Diabetic retinopathy is the most common eye disease that causes blindness in the working population. Neurodegeneration is the early sign of diabetic retinopathy, but no drug has been approved for delaying or reversing retinal neurodegeneration. Huperzine A, a natural alkaloid isolated from Huperzia serrata, displays neuroprotective and antiapoptotic effects in treating neurodegenerative disorders. Our study aims to investigate the effect of huperzine A in preventing retinal neurodegeneration of diabetic retinopathy and its possible mechanism.

Methods

Diabetic retinopathy model was induced by streptozotocin. H&E staining, optical coherence tomography, immunofluorescence staining and angiogenic factors were used to determine the degree of retinal pathological injury. The possible molecular mechanism was unrevealed by network pharmacology analysis and further validated by biochemical experiments.

Results

In our study, we demonstrated that huperzine A has a protective effect on the diabetes retina in a diabetic rat model. Based on the network pharmacology analysis and biochemical studies, huperzine A may treat diabetic retinopathy via key target HSP27 and apoptosis-related pathways. Huperzine A may modulate the phosphorylation of HSP27 and activate the antiapoptotic signalling pathway.

Conclusion

Our findings revealed that huperzine A might be a potential therapeutic drug to prevent diabetic retinopathy. It is the first-time combining network pharmacology analysis with biochemical studies to explore the mechanism of huperzine A in preventing diabetic retinopathy.
Drug interventions for prevention of COVID-19 progression to severe disease in outpatients: a systematic review with meta-analyses and trial sequential analyses (The LIVING Project)
Authors: Petersen Johanne Juul , Jørgensen Caroline Kamp , Faltermeier Pascal , Siddiqui Faiza , Feinberg Joshua , Nielsen Emil Eik , Torp Kristensen Andreas , Juul Sophie , Holgersson Johan , Nielsen Niklas , Bentzer Peter , Thabane Lehana , Kwasi Korang Steven , Klingenberg Sarah , Gluud Christian , Jakobsen Janus C
Published: June 2023

Objectives

To assess the effects of interventions authorised by the European Medicines Agency (EMA) or the US Food and Drug Administration (FDA) for prevention of COVID-19 progression to severe disease in outpatients.

Setting

Outpatient treatment.

Participants

Participants with a diagnosis of COVID-19 and the associated SARS-CoV-2 virus irrespective of age, sex and comorbidities.

Interventions

Drug interventions authorised by EMA or FDA.

Primary outcome measures

Primary outcomes were all-cause mortality and serious adverse events.

Results

We included 17 clinical trials randomising 16 257 participants to 8 different interventions authorised by EMA or FDA. 15/17 of the included trials (88.2%) were assessed at high risk of bias. Only molnupiravir and ritonavir-boosted nirmatrelvir seemed to improve both our primary outcomes. Meta-analyses showed that molnupiravir reduced the risk of death (relative risk (RR) 0.11, 95% CI 0.02 to 0.64; p=0.0145, 2 trials; very low certainty of evidence) and serious adverse events (RR 0.63, 95% CI 0.47 to 0.84; p=0.0018, 5 trials; very low certainty of evidence). Fisher’s exact test showed that ritonavir-boosted nirmatrelvir reduced the risk of death (p=0.0002, 1 trial; very low certainty of evidence) and serious adverse events (p<0.0001, 1 trial; very low certainty of evidence) in 1 trial including 2246 patients, while another trial including 1140 patients reported 0 deaths in both groups.

Conclusions

The certainty of the evidence was very low, but, from the results of this study, molnupiravir showed the most consistent benefit and ranked highest among the approved interventions for prevention of COVID-19 progression to severe disease in outpatients. The lack of certain evidence should be considered when treating patients with COVID-19 for prevention of disease progression.

PROSPERO registration number

CRD42020178787.
Risk of myocarditis and pericarditis in mRNA COVID-19-vaccinated and unvaccinated populations: a systematic review and meta-analysis
Authors: Alami Abdallah , Krewski Daniel , Farhat Nawal , Mattison Donald , Wilson Kumanan , Gravel Christopher A , Farrell Patrick J , Crispo James A G , Haddad Nisrine , Perez-Lloret Santiago , Villeneuve Paul J
Published: June 2023

Objective

To summarise the available evidence on the risk of myocarditis and/or pericarditis following mRNA COVID-19 vaccination, compared with the risk among unvaccinated individuals in the absence of COVID-19 infection.

Design

Systematic review and meta-analysis.

Data sources

Electronic databases (Medline, Embase, Web of Science and WHO Global Literature on Coronavirus Disease), preprint repositories (medRxiv and bioRxiv), reference lists and grey literature were searched from 1 December 2020 until 31 October 2022.

Study selection

Epidemiological studies of individuals of any age who received at least one dose of an mRNA COVID-19 vaccine, reported a risk of myo/pericarditis and compared the risk of myo/pericarditis to individuals who did not receive any dose of an mRNA COVID-19 vaccine.

Data extraction and synthesis

Two reviewers independently conducted screening and data extraction. The rate of myo/pericarditis among vaccinated and unvaccinated groups was recorded, and the rate ratios were calculated. Additionally, the total number of individuals, case ascertainment criteria, percentage of males and history of SARS-CoV-2 infection were extracted for each study. Meta-analysis was done using a random-effects model.

Results

Seven studies met the inclusion criteria, of which six were included in the quantitative synthesis. Our meta-analysis indicates that within 30-day follow-up period, vaccinated individuals were twice as likely to develop myo/pericarditis in the absence of SARS-CoV-2 infection compared to unvaccinated individuals, with a rate ratio of 2.05 (95% CI 1.49–2.82).

Conclusion

Although the absolute number of observed myo/pericarditis cases remains quite low, a higher risk was detected in those who received mRNA COVID-19 vaccinations compared with unvaccinated individuals in the absence of SARS-CoV-2 infection. Given the effectiveness of mRNA COVID-19 vaccines in preventing severe illnesses, hospitalisations and deaths, future research should focus on accurately determining the rates of myo/pericarditis linked to mRNA COVID-19 vaccines, understanding the biological mechanisms behind these rare cardiac events and identifying those most at risk.
Socioeconomic inequalities in cervical precancer screening among women in Ethiopia, Malawi, Rwanda, Tanzania, Zambia and Zimbabwe: analysis of Population-Based HIV Impact Assessment surveys
Authors: Chipanta David , Kapambwe Sharon , Nyondo-Mipando Alinane Linda , Pascoe Margaret , Amo-Agyei Silas , Bohlius Julia , Estill Janne , Keiser Olivia
Published: June 2023

Objectives

We examined age, residence, education and wealth inequalities and their combinations on cervical precancer screening probabilities for women. We hypothesised that inequalities in screening favoured women who were older, lived in urban areas, were more educated and wealthier.

Design

Cross-sectional study using Population-Based HIV Impact Assessment data.

Setting

Ethiopia, Malawi, Rwanda, Tanzania, Zambia and Zimbabwe. Differences in screening rates were analysed using multivariable logistic regressions, controlling for age, residence, education and wealth. Inequalities in screening probability were estimated using marginal effects models.

Participants

Women aged 25–49 years, reporting screening.

Outcome measures

Self-reported screening rates, and their inequalities in percentage points, with differences of 20%+ defined as high inequality, 5%–20% as medium, 0%–5% as low.

Results

The sample size of participants ranged from 5882 in Ethiopia to 9186 in Tanzania. The screening rates were low in the surveyed countries, ranging from 3.5% (95% CI 3.1% to 4.0%) in Rwanda to 17.1% (95% CI 15.8% to 18.5%) and 17.4% (95% CI 16.1% to 18.8%) in Zambia and Zimbabwe. Inequalities in screening rates were low based on covariates. Combining the inequalities led to significant inequalities in screening probabilities between women living in rural areas aged 25–34 years, with a primary education level, from the lowest wealth quintile, and women living in urban areas aged 35–49 years, with the highest education level, from the highest wealth quintile, ranging from 4.4% in Rwanda to 44.6% in Zimbabwe.

Conclusions

Cervical precancer screening rates were inequitable and low. No country surveyed achieved one-third of the WHO’s target of screening 70% of eligible women by 2030. Combining inequalities led to high inequalities, preventing women who were younger, lived in rural areas, were uneducated, and from the lowest wealth quintile from screening. Governments should include and monitor equity in their cervical precancer screening programmes.
Cohort profile: radiotherapy dataset (RTDS) in England
Authors: Sandhu Sabrina , Sharpe Michael , Findlay Úna , Roe Catherine , Broggio John , Spencer Katie , Thackray Katherine
Published: June 2023

Purpose

The purpose of the Radiotherapy Dataset (RTDS) is to collect consistent and comparable data across all providers of National Health Service (NHS)-funded radiotherapy and to provide intelligence for service planning, commissioning, clinical practice and research.

Participants

The RTDS is a mandated dataset requiring providers to collect and submit data monthly for patients treated in England. Data is available from 01 April 2009 to 2 months behind the calendar month.

The National Disease Registration Service (NDRS) started receiving data from 01 April 2016. Prior to this, the National Clinical Analysis and Specialised Applications Team (NATCANSAT) were responsible for the RTDS. NDRS holds a copy of the NATCANSAT data for English NHS providers.

The RTDS contains clinical information on the primary disease being treated, modality and intent of treatment, dose fractionation and hospital appointment details. Due to constraints in RTDS coding, linkage to the English National Cancer Registration dataset is beneficial.

Findings to date

The RTDS has been linked to the English National Cancer Registration and Systemic Anti-Cancer Therapy (SACT) datasets and to Hospital Episode Statistics (HES) to provide a more complete picture of the patient cancer pathway. Findings include a study to compare outcomes for patients treated with radical radiotherapy, an investigation of factors influencing 30-day mortality, assessing sociodemographic variation in the use of treatment and a study to assess the service impact of the COVID-19 pandemic. A range of other studies have been completed or are ongoing currently.

Future plans

The RTDS can be used for a variety of functions including cancer epidemiological studies to investigate inequalities in treatment access; provide service planning intelligence; monitor clinical practice; and support clinical trial design and recruitment. Collection is to continue indefinitely, with regular updates to the data specification to enable capture of more detailed information on radiotherapy planning and delivery.
Children using a unilateral cochlear implant and contralateral hearing aid: bimodal hearing outcomes when one ear is outside the UK (NICE 2009) audiological criteria for cochlear implantation – a single site case–control study
Authors: Bruce Iain , Schaefer Simone , Kluk Karolina , Nichani Jaya , Odriscoll Martin , Rajai Azita , Sladen Mark
Published: June 2023

Introduction

In the new revised National Institute for Health & Care Excellence (NICE, TA566, 2019) guidelines for cochlear implantation (CI) have clearly stipulated that the hearing loss must be bilateral. Prior to this revision, children and young people (CYP) with asymmetrical thresholds have been considered for unilateral CI when one ear was in audiological criteria. Children with asymmetrical hearing loss represent an important cohort of potential CI candidates, who will continue to be prevented from benefiting from CI unless evidence is produced to support implantation and maximise subsequent benefit.

The aim of this study is to evaluate the ‘real-life’ hearing performance in a group of children who have received a unilateral CI and who have hearing thresholds in the contralateral ear that are outside the current UK NICE 2019 audiological criteria for CI. The contralateral ear will be aided using a conventional hearing aid (HA). The outcomes from this ‘bimodal’ group will be compared with a group of children who have received bilateral CI, and a group of children using bilateral HA, to extend the current knowledge about the different performance levels between bilateral CI, bilateral HA and bimodal hearing in CYP.

Methods and analysis

Thirty CYP aged 6–17 years old, 10 bimodal users, 10 bilateral HA users and 10 bilateral cochlear implant users will be subjected to a test battery consisting of: (1) spatial release from masking, (2) complex pitch direction discrimination, (3) melodic identification, (4) perception of prosodic features in speech and (5) TEN test. Subjects will be tested in their optimal device modality. Standard demographic and hearing health information will be collected. In the absence of comparable published data to power the study, sample size was determined on pragmatic grounds. Tests are exploratory and for hypothesis generating purposes. Therefore, the standard criterion of p<0.05 will be used.

Ethics and dissemination

This has been approved by the Health Research Authority and NHS REC within the UK (22/EM/0104). Industry funding was secured via a competitive researcher-led grant application process. Trial results will be subject to publication according to the definition of the outcome presented in this protocol.
Method for estimation of apoptotic cell fraction of cytotherapy using in vivo fluorine-19 magnetic resonance: pilot study in a patient with head and neck carcinoma receiving tumor-infiltrating lymphocytes labeled with perfluorocarbon nanoemulsion
Authors: Ahrens Eric T , Helfer Brooke M , O’Hanlon Charles F , Lister Deanne R , Bykowski Julie L , Messer Karen , Leach Benjamin I , Chen Jiawen , Xu Hongyan , Daniels Gregory A , Cohen Ezra E W
Published: June 2023

Background

Adoptive transfer of T cells is a burgeoning cancer therapeutic approach. However, the fate of the cells, once transferred, is most often unknown. We describe the first clinical experience with a non-invasive biomarker to assay the apoptotic cell fraction (ACF) after cell therapy infusion, tested in the setting of head and neck squamous cell carcinoma (HNSCC). A patient with HNSCC received autologous tumor-infiltrating lymphocytes (TILs) labeled with a perfluorocarbon (PFC) nanoemulsion cell tracer. Nanoemulsion, released from apoptotic cells, clears through the reticuloendothelial system, particularly the Kupffer cells of the liver, and fluorine-19 (19F) magnetic resonance spectroscopy (MRS) of the liver was used to non-invasively infer the ACF.

Methods

Autologous TILs were isolated from a patient in their late 50s with relapsed, refractory human papillomavirus-mediated squamous cell carcinoma of the right tonsil, metastatic to the lung. A lung metastasis was resected for T cell harvest and expansion using a rapid expansion protocol. The expanded TILs were intracellularly labeled with PFC nanoemulsion tracer by coincubation in the final 24 hours of culture, followed by a wash step. At 22 days after intravenous infusion of TILs, quantitative single-voxel liver19F MRS was performed in vivo using a 3T MRI system. From these data, we model the apparent ACF of the initial cell inoculant.

Results

We show that it is feasible to PFC-label ~7×1010TILs (F-TILs) in a single batch in a clinical cell processing facility, while maintaining >90% cell viability and standard flow cytometry-based release criteria for phenotype and function. Based on quantitative in vivo19F MRS measurements in the liver, we estimate that ~30% cell equivalents of adoptively transferred F-TILs have become apoptotic by 22 days post-transfer.

Conclusions

Survival of the primary cell therapy product is likely to vary per patient. A non-invasive assay of ACF over time could potentially provide insight into the mechanisms of response and non-response, informing future clinical studies. This information may be useful to developers of cytotherapies and clinicians as it opens an avenue to quantify cellular product survival and engraftment.
Discussion of off-target and tentative genomic findings may sometimes be necessary to allow evaluation of their clinical significance
Authors: Horton Rachel H , Macken William L , Pitceathly Robert D S , Lucassen Anneke M
Published: June 2023

We discuss a case where clinical genomic investigation of muscle weakness unexpectedly found a genetic variant that might (or might not) predispose to kidney cancer. We argue that despite its off-target and uncertain nature, this variant should be discussed with the man who had the test, not because it is medical information, but because this discussion would allow the further clinical evaluation that might lead it to becoming so. We argue that while prominent ethical debates around genomics often take ‘results’ as a starting point and ask questions as to whether to look for and how to react to them, the construction of genomic results is fraught with ethical complexity, although often couched as a primarily technical problem. We highlight the need for greater focus on, and appreciation of, the ethical work undertaken daily by scientists and clinicians working in genomic medicine and discuss how public conversations around genomics need to adapt to prepare future patients for potentially uncertain and unexpected outcomes from clinical genomic tests.
Financial hardship during the COVID-19 pandemic and increased receipt of commercial tobacco discount coupons among US adults who use commercial tobacco
Authors: Zarei Kasra , Hamilton-Moseley Kristen R , Chen-Sankey Julia , Phan Lilianna , Ajith Aniruddh , Hacker Kiana , Jewett Bambi , Choi Kelvin
Published: June 2023

Introduction

Many individuals experienced financial hardship during the COVID-19 pandemic; yet commercial tobacco (CT) sales increased in the USA. We examined how experiencing financial hardships relates to increased CT discount coupon reception during the pandemic.

Methods

A nationally representative sample of 1700 US adults who used CT during the 12 months prior to the survey were surveyed online during January to February 2021. Participants reported if they had received more discount coupons for various CT products during (compared with before) the pandemic. They also reported whether they experienced six different types of financial hardships since the pandemic, and the total number of hardships experienced was counted. Weighted multivariable logistic regressions were used to examine the associations between financial hardships and increased coupon reception, adjusting for demographics and CT product use.

Results

During the first 10–11 months of the pandemic, 21.3% of US adults who used CT during the 12 months prior to the survey reported receiving more CT discount coupons. Experiencing financial hardship during the pandemic was associated with higher odds of receiving more coupons for all types of CT products: every additional count of financial hardship was associated with higher odds of increased reception of discount coupons for all CT products (adjusted odds ratios ranging from 1.13 to 1.23 across products).

Conclusions

Over one-fifth of US adults who used CT received more discount coupons during the pandemic. Those facing financial hardships had higher discount coupon reception, suggesting potential targeted marketing to financially vulnerable individuals by the tobacco industry.
Analysis of linearized Weyl gravity via the Hamilton–Jacobi method
Authors: Escalante Alberto , Zavala-Pérez Víctor Alberto
Published: June 2023

The Hamilton–Jacobi formalism is used to analyze the Weyl theory in the weak-field limit. The complete set of involutive Hamiltonians is obtained, which are classified into involutive and non-involutive. The counting of degrees of freedom is performed. Additionally, the generalized brackets and gauge symmetries are reported.
More on the first-order thermodynamics of scalar-tensor and Horndeski gravity
Authors: Faraoni Valerio , Houle Julien
Published: June 2023

Two issues in the first-order thermodynamics of scalar-tensor (including “viable” Horndeski) gravity are elucidated. The application of this new formalism to FLRW cosmology is shown to be fully legitimate and then extended to all Bianchi universes. It is shown that the formalism holds thanks to the almost miraculous fact that the constitutive relations of Eckart’s thermodynamics are satisfied, while writing the field equations as effective Einstein equations with an effective dissipative fluid does not contain new physics.
A polynomial invariant of Kauffman type for knotoids II
Authors: Miyazawa Yasuyuki
Published: June 2023

In this paper, we construct a polynomial invariant of Kauffman type for kd([Formula: see text])-linkoids and compute the polynomials for knotoids with up to three crossings. As a consequence, it is shown that the polynomial is different from the previous one in [Y. Miyazawa, A polynomial invariant of Kauffman type for knotoids, preprint].
Photocarrier relaxation and saturable absorption in defect-rich, direct chemical vapor deposition-grown graphene glass
Authors: Zhao Xin , Liu Fang , Chen Xu-Dong , Liu Zhi-Bo , Yan Xiao-Qing , Tian Jian-Guo
Published: June 2023

Direct growth of large-area uniform graphene films on insulating materials could facilitate the applications of graphene in optoelectronic devices. The ultrafast photocarrier relaxation and saturable absorption of direct chemical vapor deposition-grown graphene glasses, with lots of defects, are studied by using femtosecond time-resolved pump–probe and Z-scan techniques at 800 nm. We find that both the relaxation times associated with hot carrier cooling and the hot phonon effect are greatly suppressed in these defect-rich graphene glasses, which further leads to the increase of both saturation intensity and anisotropy in transient optical response for graphene glasses as compared with defect-free graphene. And, both the suppression effect and saturation intensity increase with the thickness of graphene film. The dominance of defect-assisted carrier-acoustic phonon scattering (i.e., supercollision, the collision of a carrier with both an acoustic phonon and defects) in the cooling process of hot carriers is responsible for the suppression of relaxation time.
Existence of primitive pairs with two prescribed traces over finite fields
Authors: Choudhary Aakash , Sharma R. K.
Published: June 2023

Given [Formula: see text], a field with [Formula: see text] elements, where [Formula: see text] is a prime power and [Formula: see text] is a positive integer. Let [Formula: see text] and [Formula: see text] is a rational function, where [Formula: see text] and [Formula: see text] are distinct irreducible polynomials with [Formula: see text] in [Formula: see text]. We construct a sufficient condition on [Formula: see text] which guarantees primitive pairing [Formula: see text] exists in [Formula: see text] such that [Formula: see text] and [Formula: see text] for any prescribed [Formula: see text]. Further, we demonstrate for any positive integer [Formula: see text], such a pair definitely exists for large [Formula: see text]. The scenario when [Formula: see text] is handled separately and we verified that such a pair exists for all [Formula: see text] except from possible 71 values of [Formula: see text]. A result for the case [Formula: see text] is given as well.
Faltings’ annihilator theorem and almost Cohen–Macaulay rings
Authors: Ando Glenn
Published: June 2023

Faltings’ annihilator theorem is an important result in local cohomology theory. Recently, Doustimehr and Naghipour generalized the Falitings’ annihilator theorem. They proved that if [Formula: see text] is a homomorphic image of a Gorenstein ring, then [Formula: see text], where [Formula: see text] and [Formula: see text]. In this paper, we study the relation between [Formula: see text] and [Formula: see text], and prove that if [Formula: see text] is an almost Cohen–Macaulay ring, then [Formula: see text]. Using this result, we prove that if [Formula: see text] is a homomorphic image of a Cohen–Macaulay ring, then [Formula: see text].
FINANCIAL INNOVATION: THE IMPACT OF BLOCKCHAIN TECHNOLOGIES ON FINANCIAL INTERMEDIARIES
Authors: DEL SARTO NICOLA , GAI LORENZO , IELASI FEDERICA
Published: June 2023

The world around us has become increasingly digital in recent years, from the quick adoption of mobile phones to the emergence of the Internet and, more recently, social media and big data. With profound effects on all productive sectors, the “digital revolution,” considered as the widespread use of digital technology, has fundamentally changed the financial sector. This is presently in the midst of a profound and unheard-of change known as FinTech, which is the direct outcome of the application of technology to finance. Among other things, blockchain has recently gained popularity in the financial services industry. Therefore, a greater comprehension of how this novel technology could affect the financial industry is necessary. In this paper, we explore how blockchain may impact on financial intermediaries and banks.
BtrBlocks: Efficient Columnar Compression for Data Lakes
Authors: Kuschewski Maximilian , Sauerwein David , Alhomssi Adnan , Leis Viktor
Published: June 2023

Analytics is moving to the cloud and data is moving into data lakes. These reside on object storage services like S3 and enable seamless data sharing and system interoperability. To support this, many systems build on open storage formats like Apache Parquet. However, these formats are not optimized for remotely-accessed data lakes and today's high-throughput networks. Inefficient decompression makes scans CPU-bound and thus increases query time and cost. With this work we present BtrBlocks, an open columnar storage format designed for data lakes. BtrBlocks uses a set of lightweight encoding schemes, achieving fast and efficient decompression and high compression ratios.
LightCTS: A Lightweight Framework for Correlated Time Series Forecasting
Authors: Lai Zhichen , Zhang Dalin , Li Huan , Jensen Christian S. , Lu Hua , Zhao Yan
Published: June 2023

Correlated time series (CTS) forecasting plays an essential role in many practical applications, such as traffic management and server load control. Many deep learning models have been proposed to improve the accuracy of CTS forecasting. However, while models have become increasingly complex and computationally intensive, they struggle to improve accuracy. Pursuing a different direction, this study aims instead to enable much more efficient, lightweight models that preserve accuracy while being able to be deployed on resource-constrained devices. To achieve this goal, we characterize popular CTS forecasting models and yield two observations that indicate directions for lightweight CTS forecasting. On this basis, we propose the LightCTS framework that adopts plain stacking of temporal and spatial operators instead of alternate stacking that is much more computationally expensive. Moreover, LightCTS features light temporal and spatial operator modules, called L-TCN and GL-Former, that offer improved computational efficiency without compromising their feature extraction capabilities. LightCTS also encompasses a last-shot compression scheme to reduce redundant temporal features and speed up subsequent computations. Experiments with single-step and multi-step forecasting benchmark datasets show that LightCTS is capable of nearly state-of-the-art accuracy at much reduced computational and storage overheads.
Hereditary Cohesive Subgraphs Enumeration on Bipartite Graphs: The Power of Pivot-based Approaches
Authors: Dai Qiangqiang , Li Rong-Hua , Ye Xiaowei , Liao Meihao , Zhang Weipeng , Wang Guoren
Published: June 2023

Finding cohesive subgraphs from a bipartite graph is a fundamental operator in bipartite graph analysis. In this paper, we focus on the problem of mining cohesive subgraphs from a bipartite graph that satisfy a hereditary property. Here a cohesive subgraph meets the hereditary property if all of its subgraphs satisfy the same property as itself. We show that several important cohesive subgraph models, such as maximal biclique and maximal k-biplex, satisfy the hereditary property. The problem of enumerating all maximal hereditary subgraphs was known to be NP-hard. To solve this problem, we first propose a novel and general pivot-based enumeration framework to efficiently enumerate all maximal hereditary subgraphs in a bipartite graph. Then, based on our general framework, we develop a new pivot-based algorithm with several pruning techniques to enumerate all maximal bicliques. We prove that the worst-case time complexity of our pivot-based maximal biclique enumeration algorithm is O(m x 2n/2 ) (or O(m\times 1.414^n)) which is near optimal since there exist up to O(2n/2 ) maximal bicliques in a bipartite graph with n vertices and m edges. Moreover, we also show that our algorithm can achieve polynomial-delay time complexity with a slight modification. Third, on the basis of our general framework, we also devise a novel pivot-based algorithm with several non-trivial pruning techniques to enumerate maximal k-biplexes in a bipartite graph. Finally, we conduct extensive experiments using 11 real-world bipartite graphs to evaluate the proposed algorithms. The results show that our pivot-based solutions can achieve one order of magnitude (three orders of magnitude) faster than the state-of-the-art maximal biclique enumeration algorithms (maximal k-biplex enumeration algorithms).
Updatable Learned Indexes Meet Disk-Resident DBMS - From Evaluations to Design Choices
Authors: Lan Hai , Bao Zhifeng , Culpepper J. Shane , Borovica-Gajic Renata
Published: June 2023

Although many updatable learned indexes have been proposed in recent years, whether they can outperform traditional approaches on disk remains unknown. In this study, we revisit and implement four state-of-the-art updatable learned indexes on disk, and compare them against the B+-tree under a wide range of settings. Through our evaluation, we make some key observations: 1) Overall, the B+-tree performs well across a range of workload types and datasets. 2) A learned index could outperform B+-tree or other learned indexes on disk for a specific workload. For example, PGM achieves the best performance in write-only workloads while LIPP significantly outperforms others in lookup-only workloads. We further conduct a detailed performance analysis to reveal the strengths and weaknesses of these learned indexes on disk. Moreover, we summarize the observed common shortcomings in five categories and propose four design principles to guide future design of on-disk, updatable learned indexes: (1) reducing the index's tree height, (2) better data structures to lower operation overheads, (3) improving the efficiency of scan operations, and (4) more efficient storage layout.
Generalizing Bulk-Synchronous Parallel Processing for Data Science: From Data to Threads and Agent-Based Simulations
Authors: Tian Zilu , Lindner Peter , Nissl Markus , Koch Christoph , Tannen Val
Published: June 2023

We generalize the bulk-synchronous parallel (BSP) processing model to make it better support agent-based simulations. Such simulations frequently exhibit hierarchical structure in their communication patterns which can be exploited to improve performance. We allow for the creation of temporary artificial network partitions during which agents synchronize only locally within their group in a way that does not compromise the correctness of a simulation. We have built a distributed engine, CloudCity, which uses this idea to improve the locality of computation, communication, and synchronization in such simulations. We experimentally evaluate the performance of our system on a benchmark of simulation workloads and compare it against other popular BSP-like systems, obtaining insights into the impact of various system design choices and optimization on simulation engine performance.
Incentive-Aware Decentralized Data Collaboration
Authors: Wang Yatong , Wu Yuncheng , Chen Xincheng , Feng Gang , Ooi Beng Chin
Published: June 2023

Data collaboration enables multiple parties to pool data for deriving meaningful data insights. However, data misuse and unlawful data collection have led to precautionary measures being imposed by individual organizations to guide against data leakage and abuse. As a response, decentralized federated learning (DFL) has emerged as an attractive paradigm to facilitate data collaboration while being amenable to privacy-preserving data and knowledge sharing, cost reduction, and prediction accuracy improvement. Unfortunately, the participating parties in DFL tend to be heterogeneous with skew datasets and uneven capabilities. Inevitably, training and transmission costs, and the presence of free-riders pose challenges to the adoption and participation of DFL. The absence of centralized parameter servers further exacerbates the problem of evaluating the contribution of each individual party. Therefore, an effective incentive mechanism is essential to promote data collaboration.

In this paper, we propose a novel Incentive-aware Decentralized fEderated leArning (IDEA) framework for facilitating data collaboration. Specifically, we first design a customizable reward scheme for heterogeneous parties to optimize their respective objectives such as higher model accuracy, communication efficiency, and computational efficiency. To reward fairly to deserving parties while offering flexibility, we propose a novel multi-agent reinforcement learning (MARL) incentive mechanism, which enables heterogeneous parties to learn their own optimal collaboration policy. We then design an efficient decentralized data collaboration algorithm that supports the customizable reward scheme based on individual objective-specific collaboration policy. We theoretically prove that the algorithm achieves a Nash equilibrium, which ensures the fairness of the corresponding rewards for parties. We conduct extensive experiments to evaluate the performance of our proposed framework against four baselines on five real-world datasets. The results show that IDEA outperforms state-of-the-art methods in terms of effectiveness, efficiency, and accumulated reward.
Using Cloud Functions as Accelerator for Elastic Data Analytics
Authors: Bian Haoqiong , Sha Tiannan , Ailamaki Anastasia
Published: June 2023

Cloud function (CF) services, such as AWS Lambda, have been applied as the new computing infrastructure in implementing analytical query engines. For bursty and sparse workloads, CF-based query engine is more elastic than the traditional query engines running in servers, i.e., virtual machines (VMs), and might provide a higher performance/price ratio. However, it is still controversial whether CF services are good suites for general analytical workloads, in respect of the limitations of CFs in storage, network, and lifetime, as well as the much higher resource unit prices than VMs.

In this paper, we first present micro-benchmark evaluations of the features of CF and VM. We reveal that for query processing, though CF is more elastic than VM, it is less scalable and is more expensive for continuous workloads. Then, to get the best of both worlds, we propose Pixels-Turbo - a hybrid query engine that processes queries in a scalable VM cluster by default and invokes CFs to accelerate the processing of unpredictable workload spikes. In the query engine, we propose several optimizations to improve the performance and scalability of the CF-based operators and a cost-based optimizer to select the appropriate algorithm and parallelism for the physical query plan. Evaluations on TPC-H and real-world workload show that our query engine has a 1-2 orders of magnitude higher performance/price ratio than state-of-the-art serverless query engines for sustained workloads while not compromising the elasticity for workload spikes.
DUCATI: A Dual-Cache Training System for Graph Neural Networks on Giant Graphs with the GPU
Authors: Zhang Xin , Shen Yanyan , Shao Yingxia , Chen Lei
Published: June 2023

Recently Graph Neural Networks (GNNs) have achieved great success in many applications. The mini-batch training has become the de-facto way to train GNNs on giant graphs. However, the mini-batch generation task is extremely expensive which slows down the whole training process. Researchers have proposed several solutions to accelerate the mini-batch generation, however, they (1) fail to exploit the locality of the adjacency matrix, (2) cannot fully utilize the GPU memory, and (3) suffer from the poor adaptability to diverse workloads. In this work, we propose DUCATI, aDual-Cache system to overcome these drawbacks. In addition to the traditionalNfeat-Cache, DUCATI introduces a newAdj-Cache to further accelerate the mini-batch generation and better utilize GPU memory. DUCATI develops a workload-awareDual-Cache Allocator which adaptively finds the best cache allocation plan under different settings. We compare DUCATI with various GNN training systems on four billion-scale graphs under diverse workload settings. The experimental results show that in terms of training time, DUCATI can achieve up to 3.33 times speedup (2.07 times on average) compared to DGL and up to 1.54 times speedup (1.32 times on average) compared to the state-of-the-artSingle-Cache systems. We also analyze the time-accuracy trade-offs of DUCATI and four state-of-the-art GNN training systems. The analysis results offer users some guidelines on system selection regarding different input sizes and hardware resources.
Efficient and Effective Algorithms for Generalized Densest Subgraph Discovery
Authors: Xu Yichen , Ma Chenhao , Fang Yixiang , Bao Zhifeng
Published: June 2023

The densest subgraph problem (DSP) is of great significance due to its wide applications in different domains. Meanwhile, diverse requirements in various applications lead to different density variants for DSP. Unfortunately, existing DSP algorithms cannot be easily extended to handle those variants efficiently and accurately. To fill this gap, we first unify different density metrics into a generalized density definition. We further propose a new model, c-core, to locate the general densest subgraph and show its advantage in accelerating the searching process. Extensive experiments show that our c-core-based optimization can provide up to three orders of magnitude speedup over baselines. Moreover, we study an important variant of DSP under a size constraint, namely the densest-at-least-k-subgraph (DalkS) problem. We propose an algorithm based on graph decomposition, and it is likely to give a solution that is at least 0.8 of the optimal density in our experiments, while the state-of-the-art method can only ensure a solution with density at least 0.5 of the optimal density. Our experiments show that our DalkS algorithm can achieve at least 0.99 of the optimal density for over one-third of all possible size constraints.
Near-Duplicate Sequence Search at Scale for Large Language Model Memorization Evaluation
Authors: Peng Zhencan , Wang Zhizhi , Deng Dong
Published: June 2023

Recent studies show that large language models (LLM) unintendedly memorize part of the training data, which brings serious privacy risks. For example, it has been shown that over 1% of tokens generated unprompted by an LLM are part of sequences in the training data. However, current studies mainly focus on the exact memorization behaviors. In this paper, we propose to evaluate how many generated texts have near-duplicates (e.g., only differ by a couple of tokens out of 100) in the training corpus. A major challenge of conducting this evaluation is the huge computation cost incurred by near-duplicate sequence searches. This is because modern LLMs are trained on larger and larger corpora with up to 1 trillion tokens. What's worse is that the number of sequences in a text is quadratic to the text length. To address this issue, we develop an efficient and scalable near-duplicate sequence search algorithm in this paper. It can find (almost) all the near-duplicate sequences of the query sequence in a large corpus with guarantees. Specifically, the algorithm generates and groups the min-hash values of all the sequences with at least t tokens (as very short near-duplicates are often irrelevant noise) in the corpus in linear time to the corpus size. We formally prove that only 2 n+1/t+1 -1 min-hash values are generated for a text with n tokens in expectation. Thus the index time and size are reasonable. When a query arrives, we find all the sequences sharing enough min-hash values with the query using inverted indexes and prefix filtering. Extensive experiments on a few large real-world LLM training corpora show that our near-duplicate sequence search algorithm is efficient and scalable.
Hamming Tree: The Case for Energy-Aware Indexing for NVMs
Authors: Kargar Saeed , Nawab Faisal
Published: June 2023

Non-volatile memory (NVM) technologies are widely adopted in data storage solutions and battery-powered mobile and IoT devices. Wear-out and energy efficiency are two vital challenges facing the use of NVM. In Hamming Tree, we propose a software-level memory-aware solution that picks the memory segment of where a write operation is applied judiciously to minimize bit flipping. It has been shown that reducing bit flips leads to reducing energy consumption and improving write endurance. We performed real evaluations on an Optane memory device that show that Hamming Tree can achieve up to 67.8% reduction in energy consumption.