bluuebunny/crossref_metadata_2025_split huggingface dataset:
Model-sharing Games: Analyzing Federated Learning Under Voluntary Participation
Authors: Donahue Kate , Kleinberg Jon 
Published: September 2022

Federated learning is a setting where agents, each with access to their own data source, combine models learned from local data to create a global model. If agents are drawing their data from different distributions, though, federated learning might produce a biased global model that is not optimal for each agent. This means that agents face a fundamental question: should they join the global model or stay with their local model? In this work, we show how this situation can be naturally analyzed through the framework of coalitional game theory.

Motivated by these considerations, we propose the following game: there are heterogeneous players with different model parameters governing their data distribution and different amounts of data they have noisily drawn from their own distribution. Each player's goal is to obtain a model with minimal expected mean squared error (MSE) on their own distribution. They have a choice of fitting a model based solely on their own data, or combining their learned parameters with those of some subset of the other players. Combining models reduces the variance component of their error through access to more data, but increases the bias because of the heterogeneity of distributions. In this work, we derive exact expected MSE values for problems in linear regression and mean estimation. We use these values to analyze the resulting game in the framework of hedonic game theory; we study how players might divide into coalitions, where each set of players within a coalition jointly constructs a single model. In a case with arbitrarily many players that each have either a "small" or "large" amount of data, we constructively show that there always exists a stable partition of players into coalitions.
Hilbert–Huang Transform and Energy Rate Functions for Earthquake Source Characterization—A Study from the Japan Trench
Authors: Mache Swapnil , Chatterjee Avigyan , Rajendran Kusala , Seelamantula Chandra Sekhar 
Published: September 2022

ABSTRACT
The Hilbert–Huang Transform (HHT) has been sparsely applied to problems in seismology, although previous studies have pointed to its broad scope. In this maiden attempt, we use the HHT to represent earthquake energy release duration and frequency content and compare the results with two conventional inversion methods. By selecting examples from interplate, intraplate, and intraslab settings, we demonstrate that the HHT has the power to discriminate energy release of earthquakes with different tectonic affiliations. We observe that the dominant frequencies for energy release are higher for intraslab earthquakes than for interplate and intraplate events. We use the empirical mode decomposition-based HHT and introduce a new parameter, which we name the energy rate function (ERF), to quantify the energy release. By employing empirical Green’s functions to remove the path and site effects and using a linear combination of a select set of intrinsic mode functions, we generate the station-specific relative measure of energy that we refer to as relative ERFs (RERFs). Averaged over RERFs from multiple stations, the ERF represents a measure of the total relative energy release, comparable to the moment rate functions (MRFs) and SCARDEC source time functions (STFs). Results for six of the seven earthquakes we analyzed show high cross correlation with the STFs (0.84 ± 0.03) and MRFs (0.79 ± 0.06), but there are mismatches between ERFs and MRFs or STFs when the energy release is complex and involves multisegment or bilateral ruptures. The proposed method is computationally efficient, requiring only 3.46 ± 2.62 s on average, compared to ~20 min (~1200 s) for the teleseismic inversion method we employ. With its ability to represent the seismic source in terms of energy release, the ERF method has the potential to evolve not as an alternative to waveform inversion but as a rapid time–frequency analysis tool, useful for earthquake hazard assessment.
Two-Stage Revision Total Knee Arthroplasty for Chronic Histoplasma Capsulatum Prosthetic Joint Infection
Authors: Williams Brady T. , Hogan Craig , Damioli Laura 
Published: September 2022

Case:
This report describes a histoplasma capsulatum total knee prosthetic joint infection (PJI) in an immunosuppressed patient treated with a 2-stage revision. The diagnosis of PJI was made based on minor criteria, and the causative organism was identified from cultures obtained at the time of explantation. The patient underwent induction with amphotericin B, followed by oral antifungal therapy and a successful 2-stage revision with a hinged prosthesis with an interval of ∼7 months between stage 1 and stage 2. At the most recent follow-up (18 months), she remained clear from infection with planned lifetime antifungal suppression

Conclusion:
This case report highlights the importance of consideration of atypical organisms when treating immunocompromised patients. Furthermore, this case report documents one of the few cases of histoplasma PJI and provides a successful treatment algorithm to potentially be applied to future cases.
Recurrent Iliopsoas Abscesses Due to Migrated Appendicular Fecalith
Authors: Nagai Sota , Hachiya Kurenai , Takeda Hiroki , Kawabata Soya , Ikeda Daiki , Tsukamoto Tetsuya , Kaneko Shinjiro , Fujita Nobuyuki 
Published: September 2022

Case:
Appendicular fecaliths have been reported to migrate to nearby organs before or during surgical treatment and become a late source of infection. We report an extremely rare case of recurrent iliopsoas abscesses caused by appendicular fecaliths that have migrated to the psoas muscle before or during the previous appendicectomy for acute appendicitis. In this case, surgical removal of fecaliths cured the iliopsoas abscess.

Conclusion:
Orthopaedic surgeons and gastroenterologists should remember that appendicular fecaliths that migrated into the iliopsoas muscle may cause late-onset iliopsoas abscesses.
Ultrasound-Guided Needle Aspiration of Subperiosteal Abscess in a Child with Acute Osteomyelitis of the Fibula
Authors: Kanamoto Takashi , Mazuka Takeo 
Published: September 2022

Case:
An 8-year-old boy with left lateral ankle pain was diagnosed with acute osteomyelitis after methicillin-susceptible Staphylococcus aureus was identified in a subperiosteal abscess in the distal fibula that had been aspirated using an ultrasound-guided needle. Symptoms improved after 2 weeks of intravenous and 4 weeks of oral antimicrobial therapy; no additional treatment was required. No growth retardation or sequelae were observed at the 6-year follow-up.

Conclusions:
In acute osteomyelitis, the identification of subperiosteal abscess is key for early diagnosis. Ultrasound evaluation of the distal fibula should also be considered in the diagnosis of lateral ankle pain in children.
A Novel Queueing Access Scheme with Variable Service Probability for Multiple Access Applications
Authors: Liao Chien-Hsing , Woo Tai–Kuo , Guo Ren–Rong 
Published: September 2022

Abstract
Queueing access systems have many applications in daily life, industry, and technology, i.e., bank counter, supermarkets, parts process, router, CPU scheduling, I/O access arrangements, etc. When multiple services are required to match the level of demand for a limited access resource, a multitasking server is needed to release the queueing access problems. In this paper, a multiple queueing access scheme with both fair and enhanced throughput characteristic is available, which can avoid both service conflicts for more throughputs and meet fair service opportunity for each user simultaneously. The proposed scheme represented as M/M/1*/∞ with multiple virtual servers (superscript with 1*) will also provide flexibility for arranging VSPs for users with priority or specific quality of services. Moreover, the proposed scheme will be also exemplified, formulated, and compared with conventional M/M/1/∞ queuing access approach. The system performance and characteristics are also presented with the specified queuing parameters and VSP. It shows that the expected probability and user number in service (not in queue) are enhanced with the proposed scheme.
WITHDRAWN: Efficient Modified Slice Handover Algorithm for 5G Wireless Networks
Authors: A AZHAGU JAISUDHAN PAZHANI , GUNASEKARAN P 
Published: September 2022

Abstract

The goal of 5G wireless networks is to address the growing need for network services among users. User equipments have progressed to the point where they now expect diverse services from the network. The latency, reliability, and bandwidth requirements of users can all be classified. 5G systems are planned to leverage technologies like Software Defined Networks, Network Function Virtualisation and Network Slicing to fulfil the different needs of users in an economical manner while guaranteeing network resources are resourcefully assigned to consumers. For the purpose to ensure continuous handover among network slices, new mobility management techniques must be adopted in Sliced 5G networks with the advent of varied 5G application scenarios. Users can travel from one region of coverage to another region without fading their network connection. Different network slices can coexist in 5G networks, with every slice offering services customised to various QoS demands. As a result, when customers travel from one region of coverage to another, the call can be transferred to a slice that caters to the similar or slightly different requirements. The goal of this study is to develop an algorithm for determining handover decisions in sliced 5G networks and to assess its performance.
Vascular Changes in Chronic Hepatitis C Cirrhotic Patients Treated with Direct Acting Antiviral Agents
Authors: Sieddek Asmaa Salama , Taha Mohamed Kamal , Attia Dina Ismail 
Published: September 2022

Abstract
Egypt has high prevalence of HCV infection. Portal hypertension is a leading cause of morbidity and mortality in patients with liver cirrhosis. Aim of our study evaluating changes of portal circulation by upper GIT endoscopy and gray scale abdominal ultrasound before and after 12 weeks treatment.
Methods Our study is a observational prospective of 150 HCV cirrhotic patients receiving different DAA regimens.
Results showed normalizations of Fibrosis-4 (FIB-4) score among patients after treatment which was statistically significant (p-value <0.001) while, ultrasound Measurements of PV, SMV, SV and Spleen diameter done before and after treatment, follow up period of 6 months with p-value (0.821 0.988, 0.841 ,0.923) respectively, and endoscopic follow up with progression esophageal varices size occurred in 3.7%, new varices incidance occurred in 2.3%, progression of red color signs occurred in 1.9% and 5.4% of patients had an attack of GIT bleeding with varices incidence between naïve and experienced patients (p-value0.395), PHG incidence, before and after treatment (p-value 0.780), without significant difference.
Conclusion HCV treatment improve liver enzymes in cirrhotic patients; however viral eradication did not always mean cure of liver cirrhotic patients on follow up with no statistically significant difference on portal hypertension changes
Efficacy of two different dosages of prednisone for treatment of subacute thyroiditis: a single-center, prospective, randomized, open-label, non-inferiority trial
Authors: Xu Yiqi , Zeng Xiaofan , Liu Shu , Wu Qian , Chen Yueping , He Chunling , Zhai Qing , Zhang Binhua , Gao Jialin 
Published: September 2022

Abstract
Background: The aim of study was to explore the efficacy and safety of low-dose (LD) and regular dose (RD) prednisone (PDN) for treatment of subacute thyroiditis (SAT).
Methods: Patients were randomly allocated using the block randomization method to the two groups. The primary outcome was the time required for PDN treatment. Secondary outcomes included percentages of relapse, mean score for the Morisky Medication Adherence Scale-8©（MMAS-8）, time required for symptoms to resolve, cumulative PDN dose (mg) and mean erythrocyte sedimentation rate (ESR) at 2 weeks and baseline.
Results: The study cohort included 77 patients, randomized 74 participants, and 68 completed the study. There was no significant difference in the treatment duration between the LD and RD groups (55.31±14.05 vs.61.25±19.95 days, p=0.053). The mean difference in the time required for PDN treatment between the LD and RD groups was -1.86 (95%CI =-10.64 to 6.92) days, which was within the non-inferiority margin of 7 days. There was a significant difference in the mean score for MMAS-8 between the LD and RD groups (5.84±0.88 vs.5.40±1.14, p=0.023). Also, there was a significant difference in the cumulative PDN dose between the LD and RD groups (504.22±236.86 vs.1002.28±309.86, p=0.046). The ESR at 2 weeks was statistically significant as compared to baseline values in both groups, with pre-treatment and post-treatment ESRs of 49.91±24.95 and 17.91±12.60/mm/h, (p<0.0001) in the LD group and 65.08±21.77 and 17.23±13.61/mm/h (p<0.0001) in the RD group.
Conclusion: Low-dose PDN therapy may be sufficient to achieve complete recovery and better outcomes of SAT.
This study is registered with Chinese Clinical Trial Registry (02/10/2021 ChiCTR2100051762).
Navigation function for Multi-Agent Multi-Target Interception Missions
Authors: Hacohen Shlomi , Shoval Shraga , Shvalb Nir 
Published: September 2022

Abstract

Missions across a variety of disciplines require the interception of multiple targets. In defence scenarios, targets may pose a threat to sites, while in agriculture the targets may be invasive pests or fruit ready to harvest. This paper focuses on the cooperative control of a robot swarm for interception missions of multiple static and dynamic targets while avoiding collisions. We formulate two modifications of the classical Navigation-Function which are suited for deterministic and stochastic scenarios. Both provide a simultaneous solution for the problems of target assignment and motion-planning as opposed to the classical approaches that solve each problem independently.
We show analytically that by following the Swarm-Navigation-Function gradient, the swarm will intercept all static targets while avoiding agent-agent and agent-obstacle collisions and similarly following the gradient of the Probabilistic-Navigation-Function will almost surely converge to a target in finite time, while the probability for agent-agent and agent-obstacles collisions is limited to a predefined value. The complexity of both schemes is linear with the number of targets and robots, and therefore it is scalable. Although not optimal, these solutions are simple and efficient, making them suitable for an extended set of real-time and real-life applications. We compare the resulting Swarm-Navigation-Function trajectories to that of a human in a catch game and an interception virtual game, the comparison indicates that as the trajectories are similar, human decision-making performs better. We conclude the paper with a set of simulated experiments and real-world experiments demonstrating the efficiency of the proposed scheme for dynamic targets.
LncRNA miR663AHG represses the development of colon cancer in a miR663a expression-dependent negative feedback loop
Authors: Yuan Hongfan , Du Yantao , Ma Yuwan , Gu Liankun , Zhou Jing , Tian Wei , Deng Dajun 
Published: September 2022

Abstract
Background
The MIR663AHG gene encode both miR663AHG and miR663a. While miR663a contributes to the defense of host cells against inflammation and inhibits colon cancer development, the biological function of lncRNA miR663AHG has not been previously reported.
Methods
The subcellular localization of lncRNA miR663AHG was determined by RNA-FISH. miR663AHG and miR663a were measured by qRT-PCR. The effects of miR663AHG on the growth and metastasis of colon cancer cells were investigated in vitro and in vivo. CRISPR/Cas9, RNA pulldown, and other biological assays were used to explore the underlying mechanism of miR663AHG.
Results
miR663AHG was mainly distributed in the nucleus of Caco2 and HCT116 cells and the cytoplasm of SW480 cells. The expression level of miR663AHG was positively correlated with the level of miR663a (r = 0.179, P = 0.015) and significantly downregulated in colon cancer tissues relative to paired normal tissues from 119 patients (P < 0.008). Colon cancers with low miR663AHG expression were associated with advanced pTNM stage (P = 0.021), lymph metastasis (P = 0.041), and shorter overall survival (hazard ratio = 2.026; P = 0.021). Experimentally, miR663AHG inhibited colon cancer cell proliferation, migration, and invasion. The growth of xenografts from RKO cells overexpressing miR663AHG was slower than that of xenografts from vector control cells in BALB/c nude mice (P = 0.007). Interestingly, either RNA-interfering or resveratrol-inducing expression changes of miR663AHG or miR663a can trigger negative feedback regulation of transcription of the MIR663AHG gene. Mechanistically, miR663AHG could bind to miR663a and its precursor pre-miR663a, and prevent the degradation of miR663a target mRNAs. Disruption of the negative feedback by knockout of the MIR663AHG promoter, exon-1, and pri-miR663A-coding sequence entirely blocked these effects of miR663AHG.
Conclusion
miR663AHG functions as a tumor suppressor that inhibits the development of colon cancer through its cis-binding to miR663a/pre-miR663a. The negative feedback loop between miR663AHG and miR663a expression may play dominant roles in maintaining the functions of miR663AHG in colon cancer development.
Evaporated fraction of thujopsene from Thujopsis dolabrata starves cancer cells via PKM2
Authors: Nagata Takuya , Toume Kazufumi , Hashim Yasinjan , Satou Tadaaki , Phan Nguyen Duy , Saeki Shiori , Sukegawa Kenta , Tohda Chihiro , Komatsu Katsuko , Fujii Tsutomu , Watanabe Manabu , Saida Yoshihisa 
Published: September 2022

Abstract
Objective
Many cancer patients need for new treatment options with lower side effects. Herein, we report on the antitumor effect of thujopsene derived from the volatile components of Thujopsis dolabrata (asunaro).
Methods
The antitumor effect of the asunaro essential oil was analyzed using MTT (3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyltetrazolium bromide) assay and in vivo cancer metastasis model. Thujopsene was isolated from asunaro essential oil by liquid chromatography, and the tumor growth inhibitory mechanism of thujopsene was assessed using Western blotting and DARTS (Drug affinity responsive target stability) analysis.
Results
The volatile components of asunaro essential oil exhibited an antitumor effect on MCF7 and SKBR3 breast cancer cells as well as on MKN45 gastric and DLD1 colon cancer cells. Thujopsene was identified as an antitumor factor that tended to have a stronger tumor growth inhibitory effect. Pyruvate kinase M2 (PKM2) was found to be associated with thujopsene in cancer cells. The reaction of thujopsene with MKN45 cells reduced intracellular lactate production. These results indicate that thujopsene binds to PKM2 in cancer cells and inhibits the nutritional metabolic pathway, and causing apoptosis. In conclusion, thujopsene may suppress tumor growth and metastasis by inhibiting the trophic metabolism pathway of cancer cells.
Granular Directed Rough Sets, Concept Organization and Soft Clustering
Authors: A Mani 
Published: September 2022

Abstract
Up-directed rough sets are introduced and studied by the present author in earlier papers. This is extended by her in two different granular directions in this research, with a surprising algebraic semantics. The granules are based on ideas of generalized closure under up-directedness that may be read as a form of weak consequence. This yields approximation operators that satisfy cautious monotony, while pi-groupoidal approximations (that additionally involve strategic choice and algebraic operators) have nicer properties. The study is primarily motivated by possible structure of concepts in distributed cognition perspectives, real or virtual classroom learning contexts, and student-centric teaching. Rough clustering techniques for datasets that involve up-directed relations (as in the study of Sentinel project image data) are additionally proposed. This research is expected to see significant theoretical and practical applications in related domains.
OR Vision: Objective, explainable assessment of surgical skill with deep learning
Authors: Khalid Shuja , Palter Vanessa , Grantcharov Teodor , Rudzicz Frank 
Published: September 2022

Abstract
Background Currently, evaluating surgical technical performance is inefficient and subjective [1,2,3,4] and the established rubrics for assessing surgical ability are open to interpretation. To power programs for surgical training and Maintenance of Certification (MOC), a reliable and validated solution is required. To this end, we draw upon recent advances in machine learning and propose a framework for objective and scalable assessment of technical proficiency.Methods Different machine learning models were trained to predict surgical performance on the public EndoVis19 and JIGSAWS datasets. The most important features were extracted by probing each machine learning model, and these features form the basis of the proposed algorithm. We internally tested the performance of this model on proprietary datasets from Surgical Safety Technologies (SST) and the University of Texas Southwestern (UTSW). The performance of these models was assessed according to various statistical techniques such as precision, recall, f1-scores and the area under the receiver operating characteristic curve (AUC). Results OR Vision is a statistically-driven multi-stage machine learning tool that quantifies surgical skill objectively and explainably. Instrument motion, control, and coordination are quantified in terms of 150 objective metrics, extracted from tool motion tracked by the deep learning model. The N most highly correlated of these metrics (p<0.05) model surgical performance with quantifiable objective metrics (fine-motor precision, fluidity, tremor, disorder, etc.). These metrics are combined into clinically-weighted composite scores that represent the category-wise technical performance of surgeons. The OR Vision score discriminates between expert and novice surgeons with high precision (0.82-0.84) and provides constructive feedback in the form of a concise report for every participating member of the cohort. Each report provides a breakdown of user performance on statistically relevant categories.ConclusionA machine learning-based approach for identifying surgical skill is effective and meaningful and provides the groundwork for objective, precise, repeatable, cost-effective, clinically-meaningful assessments.