bluuebunny/crossref_metadata_2025_split huggingface dataset:
GoldMiner: Elastic Scaling of Training Data Pre-Processing Pipelines for Deep Learning
Authors: Zhao Hanyu , Yang Zhi , Cheng Yu , Tian Chao , Ren Shiru , Xiao Wencong , Yuan Man , Chen Langshi , Liu Kaibo , Zhang Yang , Li Yong , Lin Wei 
Published: June 2023

Training data pre-processing pipelines are essential to deep learning (DL). As the performance of model training keeps increasing with both hardware advancements (e.g., faster GPUs) and various software optimizations, the data pre-processing on CPUs is becoming more resource-intensive and a severe bottleneck of the pipeline. This problem is even worse in the cloud, where training jobs exhibit diverse CPU-GPU demands that usually result in mismatches with fixed hardware configurations and resource fragmentation, degrading both training performance and cluster utilization.
We introduce GoldMiner, an input data processing service for stateless operations used in pre-processing data for DL model training. GoldMiner decouples data pre-processing from model training into a new role called the data worker. Data workers facilitate scaling of data pre-processing to anywhere in a cluster, effectively pooling the resources across the cluster to satisfy the diverse requirements of training jobs. GoldMiner achieves this decoupling in a fully automatic and elastic manner. The key insight is that data pre-processing is inherently stateless, thus can be executed independently and elastically. This insight guides GoldMiner to automatically extract stateless computation out of a monolithic training program, efficiently disaggregate it across data workers, and elastically scale data workers to tune the resource allocations across jobs to optimize cluster efficiency. We have applied GoldMiner to industrial workloads, and our evaluation shows that GoldMiner can transform unmodified training programs to use data workers, accelerating individual training jobs by up to 12.1x. GoldMiner also improves average job completion time and aggregate GPU utilization by up to 2.5x and 2.1x in a 64-GPU cluster, respectively, by scheduling data workers with elasticity.
What's the Difference? Incremental Processing with Change Queries in Snowflake
Authors: Akidau Tyler , Barbier Paul , Cseri Istvan , Hueske Fabian , Jones Tyler , Lionheart Sasha , Mills Daniel , Pauliukevich Dzmitry , Probst Lukas , Semmler Niklas , Sotolongo Dan , Zhang Boyuan 
Published: June 2023

Incremental algorithms are the heart and soul of stream processing. Low latency results depend on the ability to react to the subset of changes in a dataset over time rather than reprocessing the entirety of a dataset as it evolves. But while the SQL language is well suited for representing streams of changes (via tables) and their application to tables over time (via DML), it entirely lacks a method to query the changes to a table or view in the first place.
In this paper, we present CHANGES queries and STREAM objects, Snowflake's primitives for querying and consuming incremental changes to table objects over time. CHANGES queries and STREAMs have been in use within Snowflake for three years, and see broad adoption across our customers. We describe the semantics of these primitives, discuss the implementation challenges, present an analysis of their usage at Snowflake, and contrast with other offerings.
DFL: High-Performance Blockchain-Based Federated Learning
Authors: Tian Yongding , Guo Zhuoran , Zhang Jiaxuan , Al-Ars Zaid 
Published: June 2023

Many researchers have proposed replacing the aggregation server in federated learning with a blockchain system to improve privacy, robustness, and scalability. In this approach, clients would upload their updated models to the blockchain ledger and use a smart contract to perform model averaging. However, the significant delay and limited computational capabilities of blockchain systems make it inefficient to support machine learning applications on the blockchain.
In this article, we propose a new public blockchain architecture called DFL, which is specially optimized for distributed federated machine learning. Our architecture inherits the merits of traditional blockchain systems while achieving low latency and low resource consumption by waiving global consensus. To evaluate the performance and robustness of our architecture, we implemented a prototype and tested it on a physical four-node network, and also developed a simulator to simulate larger networks and more complex situations. Our experiments show that the DFL architecture can reach over 90% accuracy for non-I.I.D. datasets, even in the presence of model poisoning attacks, while ensuring that the blockchain part consumes less than 5% of hardware resources.
EdgeMart
: A Sustainable Networked OTT Economy on the Wireless Edge for Saving Multimedia IP Bandwidth
Authors: Pal Ranjan , Sastry Nishanth , Obiodu Emeka , Prabhu Sanjana , Psounis Konstantinos 
Published: June 2023

With the advent of 5G+ services, it has become increasingly convenient for mobile users to enjoy high-quality multimedia content from CDN driven streaming and catch-up TV services (Netflix, iPlayer) in the (post-) COVID over-the-top (OTT) content rush. To relieve ISP owned fixed-line networks from CDN streamed multimedia traffic, system ideas (e.g.,
Wi-Stitch
in [
45
]) have been proposed to (a) leverage 5G services and enable consumers to share cached multimedia content at the edge, and (b) consequently, and more importantly, reduce IP traffic at the core network. Unfortunately, given that contemporary multimedia content might be a monetized asset, these ideas
do not take this important fact into account for shared content.
We present
EdgeMart
—a content provider (CP) federated, and computationally sustainable networked (graphical) market economy for paid-sharing of cached licensed (OTT) content with autonomous users of a wireless edge network (WEN). EdgeMart is a unique oligopoly multimedia market (economy) that comprises competing networked sub-markets of non-cooperative content sellers/buyers—each sub-market consisting of a single buyer connected (networked) to only a subset of sellers. We prove that for
any WEN-supported supply-demand topology
, a pure strategy EdgeMart equilibrium exists that is (a) nearly efficient (in a microeconomic sense) indicating economy sustainability, (b) robust to edge user entry/exit, and (c) can be reached in poly-time (indicating computational sustainability). In addition, we experimentally show that for physical WENs of varying densities, a rationally selfish EdgeMart economy induces similar orders of multimedia IP traffic savings when compared to the
ideal
(relatively less practical),
altruistic
, and
non-monetized
“economy” implemented atop the recently introduced Wi-Stitch WEN-based content trading architecture. Moreover, the EdgeMart concept helps envision a regulated edge economy of
opportunistic
(pay per licensed file) client services for commercial OTT platforms.
Effect of Fish Meal Substitution with Black Soldier Fly (Hermetia illucens) on Growth Performance, Feed Stability, Blood Biochemistry, and Liver and Gut Morphology of Siamese Fighting Fish (Betta splendens)
Authors: Kari Zulhisyam Abdul , Téllez-Isaías Guillermo , Hamid Noor Khalidah Abdul , Rusli Nor Dini , Mat Khairiyah , Sukri Suniza Anis Mohamad , Kabir Muhammad Anamul , Ishak Ahmad Razali , Dom Nazri Che , Abdel-Warith Abdel-Wahab A. , Younis Elsayed M. , Khoo Martina Irwan , Abdullah Faizuan , Shahjahan Md , Rohani Md Fazle , Davies Simon J. , Wei Lee Seong 
Published: June 2023

Insects such as black soldier fly larvae (BSFL) are gaining interest among researchers and the aquafeed industry due to the fluctuating price and supply of fish meal (FM). This study evaluated the growth performance, feed stability, blood biochemistry, and liver and gut morphology of Betta splendens using BSFL as an alternative to FM. Five formulated diets were prepared: 0% BSFL, 6.5% BSFL, 13% BSFL, 19.5% BSFL, and 24.5% BSFL. The expansion rate, pellet durability index, floatability, bulk density, and water stability of the prepared feed have been assessed. Except for the diameter of the feed, all the parameters studied differed significantly (

p
<
0.05

) across the experimental diets. After 60 days, the fish fed with 13% BSFL had the highest final length, final weight, net weight gain, specific growth rate, weight gain, and gastrointestinal weight, with mean and standard deviation values of

3.97
±
0.43

cm,

3.95
±
0.1

g,

2.78
±
0.1

g,

4.63
±
0.17

,

4.65
±
0.13

,

237.26
±
7.9
%

, and

0.04
±
0.01

mg, respectively. Similar blood haematology and biochemical properties, including corpuscular volume, lymphocytes, white blood cells, red blood cells, haematocrit, albumin, and alkaline phosphatase, were the highest (

p
<
0.05

) in the 13% BSFL diet group compared to the other treatment groups. In addition, BSFL had a significant impact (

p
<
0.05

) on villus length, width, and crypt depth for the anterior and posterior guts of B. splendens. The 13% BSFL diet group had an intact epithelial barrier in the goblet cell arrangement and a well-organized villus structure and tunica muscularis, compared to the other treatment groups. Furthermore, the liver cell was altered with different BSFL inclusions; the 13% FM group demonstrated better nuclei and cytoplasm structure than the other treatment groups. In conclusion, replacing 13% FM with BSFL could improve the growth performance, blood parameters, and liver and intestine morphology of B. splendens, thus providing a promising alternative diet for ornamental freshwater fish.
Tipifarnib Potentiates the Antitumor Effects of PI3Kα Inhibition inPIK3CA- andHRAS-Dysregulated HNSCC via Convergent Inhibition of mTOR Activity
Authors: Smith Alison E. , Chan Stacia , Wang Zhiyong , McCloskey Asako , Reilly Quinn , Wang Jayden Z. , Patel Hetika Vora , Koshizuka Keiichi , Soifer Harris S. , Kessler Linda , Dayoub Ashley , Villaflor Victoria , Adkins Douglas R. , Bruce Justine Y. , Ho Alan L. , Perez Cesar A. , Hanna Glenn J. , Gascó Hernández Amaya , Saunders Andrew , Dale Stephen , Gutkind J. Silvio , Burrows Francis , Malik Shivani 
Published: June 2023

AbstractOutcomes for patients with recurrent/metastatic (R/M) head and neck squamous cell carcinoma (HNSCC) are poor, with median overall survival (OS) ranging from 6 to 18 months. For those who progress on standard-of-care (chemo)immunotherapy, treatment options are limited, necessitating the development of rational therapeutic strategies. Toward this end, we targeted the key HNSCC drivers PI3K–mTOR and HRAS via the combination of tipifarnib, a farnesyltransferase (FTase) inhibitor, and alpelisib, a PI3Kα inhibitor, in multiple molecularly defined subsets of HNSCC. Tipifarnib synergized with alpelisib at the level of mTOR in PI3Kα- or HRAS-dependent HNSCCs, leading to marked cytotoxicity in vitro and tumor regression in vivo. On the basis of these findings, the KURRENT-HN trial was launched to evaluate the effectiveness of this combination in PIK3CA-mutant/amplified and/or HRAS-overexpressing R/M HNSCC. Preliminary evidence supports the clinical activity of this molecular biomarker-driven combination therapy. Combined alpelisib and tipifarnib has potential to benefit &gt;45% of patients with R/M HNSCC. By blocking feedback reactivation of mTORC1, tipifarnib may prevent adaptive resistance to additional targeted therapies, enhancing their clinical utility.Significance:The mechanistically designed, biomarker-matched strategy of combining alpelisib and tipifarnib is efficacious in PIK3CA- and HRAS-dysregulated head and neck squamous carcinoma and could improve outcomes for many patients with recurrent, metastatic disease.See related commentary by Lee et al., p. 3162
Discovery and Targeting of a Noncanonical Mechanism of Sarcoma Resistance to ADI-PEG20 Mediated by the Microenvironment
Authors: Rogers Leonard C. , Kremer Jeff C. , Brashears Caitlyn B. , Lin Zongtao , Hu Zhixian , Bastos Alliny C.S. , Baker Adriana , Fettig Nicole , Zhou Dong , Shoghi Kooresh I. , Dehner Carina A. , Chrisinger John S.A. , Bomalaski John S. , Garcia Benjamin A. , Oyama Toshinao , White Eileen P. , Van Tine Brian A. 
Published: June 2023

Abstract

Purpose:
Many cancers lack argininosuccinate synthetase 1 (ASS1), the rate-limiting enzyme of arginine biosynthesis. This deficiency causes arginine auxotrophy, targetable by extracellular arginine-degrading enzymes such as ADI-PEG20. Long-term tumor resistance has thus far been attributed solely to ASS1 reexpression. This study examines the role of ASS1 silencing on tumor growth and initiation and identifies a noncanonical mechanism of resistance, aiming to improve clinical responses to ADI-PEG20.

Experimental Design:
Tumor initiation and growth rates were measured for a spontaneous Ass1 knockout (KO) murine sarcoma model. Tumor cell lines were generated, and resistance to arginine deprivation therapy was studied in vitro and in vivo.

Results:
Conditional Ass1 KO affected neither tumor initiation nor growth rates in a sarcoma model, contradicting the prevalent idea that ASS1 silencing confers a proliferative advantage. Ass1 KO cells grew robustly through arginine starvation in vivo, while ADI-PEG20 remained completely lethal in vitro, evidence that pointed toward a novel mechanism of resistance mediated by the microenvironment. Coculture with Ass1-competent fibroblasts rescued growth through macropinocytosis of vesicles and/or cell fragments, followed by recycling of protein-bound arginine through autophagy/lysosomal degradation. Inhibition of either macropinocytosis or autophagy/lysosomal degradation abrogated this growth support effect in vitro and in vivo.

Conclusions:
Noncanonical, ASS1-independent tumor resistance to ADI-PEG20 is driven by the microenvironment. This mechanism can be targeted by either the macropinocytosis inhibitor imipramine or the autophagy inhibitor chloroquine. These safe, widely available drugs should be added to current clinical trials to overcome microenvironmental arginine support of tumors and improve patient outcomes.
Liver Fibrosis Scores and Prostate Cancer Risk and Mortality in the Atherosclerosis Risk in Communities Study
Authors: Wang Anqi , Lazo Mariana , Lu Jiayun , Couper David J. , Prizment Anna E. , Vitolins Mara Z. , Denmeade Samuel R. , Joshu Corinne E. , Platz Elizabeth A. 
Published: June 2023

AbstractSubclinical liver impairment due to fibrosis could influence the development and detectability of prostate cancer. To investigate the association between liver fibrosis and prostate cancer incidence and mortality, we included 5,284 men (mean age: 57.6 years, 20.1% Black) without cancer or liver disease at Visit 2 in the Atherosclerosis Risk in Communities study. Liver fibrosis was assessed using the aspartate aminotransferase to platelet ratio index, fibrosis 4 index (FIB-4), and nonalcoholic fatty liver disease fibrosis score (NFS). Over 25 years, 215 Black and 511 White men were diagnosed with prostate cancer, and 26 Black and 51 White men died from the disease. We estimated HRs for total and fatal prostate cancer using Cox regression. FIB-4 [quintile 5 vs. 1: HR = 0.47, 95% confidence interval (CI): 0.29–0.77, Ptrend = 0.004] and NFS (HR = 0.56, 95% CI: 0.33–0.97, Ptrend = 0.03) were inversely associated with prostate cancer risk in Black men. Compared with no abnormal score, men with ≥1 abnormal score had a lower prostate cancer risk if they were Black (HR = 0.46, 95% CI: 0.24–0.89), but not White (HR = 1.04, 95% CI: 0.69–1.58). Liver fibrosis scores did not appear to be associated with fatal prostate cancer in Black or White men. Among men without a clinical diagnosis of liver disease, higher liver fibrosis scores were associated with lower incidence of prostate cancer in Black men, but not in White men, and not with fatal prostate cancer in either race. Further research is needed to understand the influence of subclinical liver disease on prostate cancer development versus detectability and the racial differences observed.Prevention Relevance:Investigating the link between liver fibrosis and prostate cancer risk and mortality, our study reveals the potential influence of liver health on prostate cancer development and on detection using PSA test, urging further research to understand the differential findings by race and to optimize prevention and intervention strategies.
Trends of Concomitant Diabetes and Peripheral Artery Disease and Lower Extremity Amputation in US Medicare Patients, 2007 to 2019
Authors: Fowler Xavier P. , Eid Mark A. , Barnes J. Aaron , Gladders Barbara , Austin Andrea M. , Goodney Eric J. , Moore Kayla O. , Kearing Stephen , Feinberg Mark W. , Bonaca Marc P. , Creager Mark A. , Goodney Philip P. 
Published: June 2023

Background:
Previous studies demonstrate geographic and racial/ethnic variation in diagnosis and complications of diabetes and peripheral artery disease (PAD). However, recent trends for patients diagnosed with both PAD and diabetes are lacking. We assessed the period prevalence of concurrent diabetes and PAD across the United States from 2007 to 2019 and regional and racial/ethnic variation in amputations among Medicare patients.

Methods:
Using Medicare claims from 2007 to 2019, we identified patients with both diabetes and PAD. We calculated period prevalence of concomitant diabetes and PAD and incident cases of diabetes and PAD for every year. Patients were followed to identify amputations, and results were stratified by race/ethnicity and hospital referral region.

Results:
9 410 785 patients with diabetes and PAD were identified (mean age, 72.8 [SD, 10.94] years; 58.6% women, 74.7% White, 13.2% Black, 7.3% Hispanic, 2.8% Asian/API, and 0.6% Native American). Period prevalence of diabetes and PAD was 23 per 1000 beneficiaries. We observed a 33% relative decrease in annual new diagnoses throughout the study. All racial/ethnic groups experienced a similar decline in new diagnoses. Black and Hispanic patients had on average a 50% greater rate of disease compared with White patients. One- and 5-year amputation rates remained stable at ≈1.5% and 3%, respectively. Native American, Black, and Hispanic patients were at greater risk of amputation compared with White patients at 1- and 5-year time points (5-year rate ratio range, 1.22–3.17). Across US regions, we observed differential amputation rates, with an inverse relationship between the prevalence of concomitant diabetes and PAD and overall amputation rates.

Conclusions:
Significant regional and racial/ethnic variation exists in the incidence of concomitant diabetes and PAD among Medicare patients. Black patients in areas with the lowest rates of PAD and diabetes are at disproportionally higher risk for amputation. Furthermore, areas with higher prevalence of PAD and diabetes have the lowest rates of amputation.
Measuring Attribution in Natural Language Generation Models
Authors: Rashkin Hannah , Nikolaev Vitaly , Lamm Matthew , Aroyo Lora , Collins Michael , Das Dipanjan , Petrov Slav , Tomar Gaurav Singh , Turc Iulia , Reitter David 
Published: June 2023

Abstract
Large neural models have brought a new challenge to natural language generation (NLG): It has become imperative to ensure the safety and reliability of the output of models that generate freely. To this end, we present an evaluation framework, Attributable to Identified Sources (AIS), stipulating that NLG output pertaining to the external world is to be verified against an independent, provided source. We define AIS and a two-stage annotation pipeline for allowing annotators to evaluate model output according to annotation guidelines. We successfully validate this approach on generation datasets spanning three tasks (two conversational QA datasets, a summarization dataset, and a table-to-text dataset). We provide full annotation guidelines in the appendices and publicly release the annotated data at https://github.com/google-research-datasets/AIS.
Evolutionary Algorithms for Parameter Optimization—Thirty
Years Later
Authors: Bäck Thomas H. W. , Kononova Anna V. , van Stein Bas , Wang Hao , Antonov Kirill A. , Kalkreuth Roman T. , de Nobel Jacob , Vermetten Diederick , de Winter Roy , Ye Furong 
Published: June 2023

Abstract
Thirty years, 1993–2023, is a huge time frame in science. We address some major developments in the field of evolutionary algorithms, with applications in parameter optimization, over these 30 years. These include the covariance matrix adaptation evolution strategy and some fast-growing fields such as multimodal optimization, surrogate-assisted optimization, multiobjective optimization, and automated algorithm design. Moreover, we also discuss particle swarm optimization and differential evolution, which did not exist 30 years ago, either. One of the key arguments made in the paper is that we need fewer algorithms, not more, which, however, is the current trend through continuously claiming paradigms from nature that are suggested to be useful as new optimization algorithms. Moreover, we argue that we need proper benchmarking procedures to sort out whether a newly proposed algorithm is useful or not. We also briefly discuss automated algorithm design approaches, including configurable algorithm design frameworks, as the proposed next step toward designing optimization algorithms automatically, rather than by hand.
Examining causes and characteristics of egg ejection behaviour in the American robin (Turdus migratorius)
Authors: Turner Abbigail M. , Sluis Victoria N. , Williams Emily J. , Benson Thomas J. , Ward Michael P. , Hauber Mark E. 
Published: June 2023

Abstract
American robins (Turdus migratorius) are among few hosts of parasitic brown-headed cowbirds (Molothrus ater) that frequently eject foreign eggs from their nests. However, we know little about some characteristics of the robins’ egg ejection process including its distance and direction. We used a novel technique (i.e., radio transmitters inserted into 3D-printed eggshells) to examine egg rejection in female robins as a function of model egg coloration (i.e., robin-mimetic blue, non-mimetic deep blue, and non-mimetic beige). Based on prior work, we predicted that female robins’ egg ejection decisions would be dependent on egg coloration. Accordingly, we found a significant effect of female identity (using nest identity as a proxy) and model egg colour on egg ejection, but neither predicted ejection distance or direction. Deep blue model eggs had shorter ejection latencies than beige eggs. Fully characterizing the egg ejection process will allow us to further understand the mechanisms and outcomes of egg ejection behaviours in host-parasite interactions.