bluuebunny/crossref_metadata_2025_split huggingface dataset:
Top advances of the year: Leukemia
Authors: Kent Andrew , Pollyea Daniel A. 
Published: December 2022

AbstractIn the year 2021, there were three new Food and Drug Administration approvals for all leukemia types: asciminib (Scemblix) for chronic myeloid leukemia, brexucabtagene autoleucel (Tecartus) for relapsed/refractory B‐cell acute lymphocytic leukemia, and asparaginase erwinia chrysanthemi (recombinant)‐rywn (Rylaze) for acute lymphocytic leukemia. This is down from 2017–2018 when eight new therapies were approved for acute myeloid leukemia alone. However, this decrease from prior years does not imply that little progress was made in our understanding or treatment of leukemias in 2021. Asciminib and brexucabtagene autoleucel, in particular, are representative of major developing trends. Asciminib, a targeted therapy, is only one of many drugs in development that are products of a bedside‐to‐bench approach fueled by new sequencing and other genetic technologies that have greatly increased our understanding of the biology behind hematologic diseases. Brexucabtagene autoleucel, an adoptive cell therapy, is the newest of several similar treatments for B cell–associated neoplasms, and it is representative of a massive push to develop novel immunotherapies for a broad range of hematologic malignancies. This commentary reviews the development of asciminib and brexucabtagene autoleucel and describes other major advances in the associated fields of targeted therapy and immunotherapy for leukemias.
An effective veracity management for sentiment analysis in social media using crowdsourcing and multi‐set feature learning
Authors: Aruna Arulanandam Gnanaprakasam , Sangeetha Manickam 
Published: December 2022

SummaryRecent innovations of the Internet‐of‐Things (IoT) are facilitated the data processing to an enormous scale. Nevertheless, the collected data are inherently uncertain because of noise, discrepancy, and incompleteness. To solve these constraints, improving data veracity is crucial for IoT‐based applications. As big data veracity is more critical, it must predict the veracity of tweets automatically for decision‐making. There have been many techniques developed including artificial intelligence and crowdsourcing models to estimate the veracity of tweets from single sources. But, these models are ineffective while the amount of crowd labels for tweets from multiple sources is not feasible. Also, analyzing the sentiment of public opinions has high complexity. Therefore, this article focuses on developing an efficient model to predict the veracity of tweets from multiple sources and analyze the sentiments of the passage. Primarily, different tweets with text labels are collected. Afterward, a crowdsourcing model is introduced which utilizes the crowdflower dataset to obtain the crowd labels for collected tweets. The Generative Adversarial Network (GAN) model is applied to increase the veracity of tweets by handling the low‐veracity tweets. Finally, the multi‐set feature learning model is implemented to classify the sentiment of opinions. The performance results manifest that the proposed model accomplishes superior accuracy of 97% than the classical veracity prediction models.
An optimization method for PLL‐based charge control SIMO Buck DC‐DC
Authors: Liu Yuyang , Wu Zhaohui , Li Bin , Zheng Yanqi , Chen Zhijian 
Published: December 2022

SummaryThe PLL‐based charge control scheme is optimized and implemented in a single‐inductor multiple‐output (SIMO) Buck DC‐DC in this paper. In order to decrease cross regulation (CR) during heavy load transient, the gain adaptive charge pump (GACP) is optimized to speed up the regulation of inductor current, and the current loop off‐time (CLOT) control is introduced to prevent the PLL‐based structure from frequency unlock. The proposed SIMO is designed in a 0.18 μm standard CMOS process. Experimental results show that the worst CR performance is 0.026 mV/mA, which is a 50% improvement of PLL‐based charge control scheme and 61.19% advantage above the existing charge‐controlled SIMO.
Algerian Youth and the Contestation over Sound on TikTok
Authors: Bruls Luca 
Published: January 2023

AbstractIn Algeria, youth form attitudes towards music as a result of their TikTok usage. The responses of governmental institutions, Facebook users, and middle‐class TikTokers to popular raï songs unfold the contestation over sound. Drawing on nethnography, I expose the moralizing and politicized responses that couple these different groups in their criticism. Through an account of the conversations and interactions with middle‐class Algerian youth, I demonstrate TikTok's subdivision into two opposed, yet interdependent scenes. The text draws on examples of the engagement between the two groups to reveal how youth call attention to their class identities by listening and sounding, as well as related expressions of dancing and dressing. The friendships and engagements online are a result of youth's scaling practices in TikTok's For You algorithm. Through their negotiation of songs, performances, and humour, middle‐class youth create a sonic class line that separates them from vulnerable classes. The moralizing stories that these middle‐class youth tell are an everyday representation of the different classes in Algeria. Studying sound on TikTok can help ethnographers learn about the concomitant memes and stereotypes that circulate online.
DEICA: A differential evolution‐based improved clustering algorithm for IoT‐based heterogeneous wireless sensor networks
Authors: Chaurasiya Sandip K. , Biswas Arindam , Nayyar Anand , Zaman Jhanjhi Noor , Banerjee Rajib 
Published: January 2023

SummaryWith the evolution of technology, many modern applications like habitat monitoring, environmental monitoring, disaster prediction and management, and telehealth care have been proposed on wireless sensor networks (WSNs) with Internet of Things (IoT) integration. However, the performance of these networks is restricted because of the various constraints imposed due to the participating sensor nodes, such as nonreplaceable limited power units, constrained computation, and limited storage. Power limitation is the most severe among these restrictions. Hence, the researchers have sought schemes enabling energy‐efficient network operations as the most crucial issue. A metaheuristic clustering scheme is proposed here to address this problem, which employs the differential evolution (DE) technique as a tool. The proposed scheme achieves improved network performance via the formulation of load‐balanced clusters, resulting in a more scalable and adaptable network. The proposed scheme considers multiple parameters such as nodes' energy level, degree, proximity, and population for suitable network partitioning. Through various simulation results and experimentation, it establishes its efficacy over state‐of‐the‐art schemes in respect of load‐balanced cluster formation, improved network lifetime, network resource utilization, and network throughput. The proposed scheme ensures up to 57.69%, 33.16%, and 57.74% gains in network lifetime, energy utilization, and data packet delivery under varying network configurations. Besides providing the quantitative analysis, a detailed statistical analysis has also been performed that describes the acceptability of the proposed scheme under different network configurations.
Iodine and Iodide in Reductive Transformations
Authors: Luján‐Montelongo J. Armando , Mateus‐Ruiz Jeferson B. , Valdez‐García Ricardo M. 
Published: January 2023

AbstractThis review provides a comprehensive overview of strategies and methodologies for reducing C−O and heteroatomic−oxygen bonds (N−O, S−O, P−O) using I2/I−, as well as other synthetically relevant bonds such as C−C, N−N, C−N, C−X, C−S. It highlights and discusses most of the mechanistic details provided by the original authors. Selected examples of other halides (Br and Cl) as reductants are also covered.
Racial and ethnic differences in the use of lumbar imaging, opioid analgesics and spinal surgery for low back pain: A systematic review and meta‐analysis
Authors: Chen Qiuzhe , Vella Simon P. , Maher Chris G. , Ferreira Giovanni E. , Machado Gustavo C. 
Published: December 2022

AbstractBackground and ObjectiveThere is a substantial gap between evidence and clinical care for low back pain (LBP) worldwide despite recommendations of best practice specified in clinical practice guidelines. The aim of this systematic review was to identify disparities associated with race or ethnicity in the use of lumbar imaging, opioid analgesics, and spinal surgery in people with LBP.Databases and Data TreatmentWe included observational studies which compared the use of lumbar imaging, opioid analgesics, and spinal surgery for the management of non‐serious LBP between people from different racial/ethnic populations. We searched in MEDLINE, EMBASE and CINAHL from January 2000 to June 2021. Risk of bias of included studies was appraised in six domains. For each type of care, we pooled data stratified by race and ethnicity using random effects models.ResultsWe identified 13 eligible studies; all conducted in the United States. Hispanic/Latino (OR 0.69, 95%CI 0.49–0.96) and Black/African American (OR 0.59, 95%CI 0.46–0.75) people with LBP were less likely to be prescribed opioid analgesics than White people. Black/African Americans were less likely to undergo or be recommended spinal surgery for LBP (OR 0.47, 95%CI 0.33–0.67) than White people. There was a lack of high certainty evidence on racial/ethnic disparities in the use of lumbar imaging.ConclusionThis review reveals lower rate of the use of guideline‐discordant care, especially opioid prescription and spinal surgery, in racial/ethnic minority populations with LBP in the United States. Future studies in other countries evaluating care equity for LBP are warranted.PROSPERO Registration ID: CRD42021260668.SignificanceThis systematic review and meta‐analysis revealed that people with low back pain from the minority racial/ethnic backgrounds were less likely to be prescribed opioid analgesics and undergo spinal surgery than the majority counterparts. Strategic interventions to improve the access to, and the value of, clinical care for minority populations with low back pain are warranted.
Investigation of the effect of compression ratio on performance of a beta type Stirling engine with rhombic mechanism byCFDanalysis
Authors: Arslan Turan Alp , Solmaz Hamit , İpci Duygu , Aksoy Fatih 
Published: December 2022

AbstractStirling engines take attention due to their high thermal efficiency potential. Many experimental and numerical studies have been performed up to date. Numerical performance analyses of Stirling engines implemented with CFD simulations are classified as 4th order analyses. In the present study, the effect of compression ratio on engine performance of a beta type Stirling engine with rhombic mechanism was investigated by 2D CFD simulation. CFD simulations of the Stirling engine were performed by ANSYS Fluent software. The engine examined by CFD analysis was modeled using the dimensions of an engine manufactured and tested in a previous study, and validation of the CFD simulation was conducted regarding in‐cylinder pressure at 4 bar charge pressure. The crank radius and length of the regenerator zone of the engine were optimized by considering the compression ratio of the engine and engine performance was investigated. Maximum engine performance was obtained at a compression ratio of 2.24 which was ensured by 31.5 mm crank radius and 609.9 mm a length of the regenerator zone. By optimizing the dimensions the engine performance was improved by 99% compared to the base engine configuration. The cyclic work, power, torque, and thermal efficiency were calculated as 62.47 J, 728.93 W, 9.94 Nm, and 37.7% respectively.
Enabling security in MANETs using an efficient cluster based group key management with elliptical curve cryptography in consort with sail fish optimization algorithm
Authors: Shanmuganathan C. , Boopalan K. , Elangovan G. , Sathish Kumar P.J. 
Published: December 2022

AbstractIn MANET, group key management is a vital part of multicast security. But distribution of keys in an authenticated manner is a difficult task in group key management. The existing methods provide low security with high processing time during group key management resulting does not provide sufficient results. Therefore, enabling security in MANETs using an efficient cluster based group key management with elliptical curve cryptography in consort with sail fish optimization algorithm is proposed in this article for two‐level security with reduced computational overhead. At first, all the nodes in the cluster are structured in hierarchy method. The key server creates public key utilizing private key of the group node. Here, elliptical curve cryptography based meta‐heuristic sail fish optimization algorithm is used to select the optimal private key for better secure communication. After selecting this optimum private key, the key server creates the public key, and a common group key is created using this generated public keys. If the nodes joint or exit from the subgroup, the reset process is executed in group key management process. Finally, this process reduces the computational overhead of rekeying method. The proposed method is simulated by Python programming and network simulator‐3. The proposed elliptical curve cryptography based sail fish optimization algorithm attains 10.9%, 22.21%, and 11.43% low computational overhead, 19.34%, 13.45%, and 42.13% low latency, 43.45%, 22.21%, and 12.22% high packet delivery rate, 11.23%, 13.41%, and 21.11% high network life time than the existing methods.
Providing a health‐promotion behaviors model in elderly: Psychological capital, perceived social support, and attitudes toward death with mediating role of cognitive emotion regulation strategies
Authors: Ahmadboukani Soliman , Fathi Davod , Karami Mina , Bashirgonbadi Sepideh , Mahmoudpour Abdolbaset , Molaei Behnam 
Published: December 2022

AbstractBackground and AimsThe aim of this study was to present a health‐promotion behaviors model in the elderly based on psychological capital, social support, and attitudes toward death mediated with mediating role of emotional cognitive regulation strategies in the elderly in Ardabil.MethodsThe research method was correlational which was done by the path analysis method. The statistical population of the study consisted of all elderly people in Ardabil in 2020, from which 250 people were selected by convenient sampling method and were investigated with research tools including Health‐Promotion Lifestyle Profile (1998), attitudes toward death profile (1994), Psychological Capitals (2007), social support (1988) and Cognitive Emotion Regulation (2001). Data were analyzed by Amos‐24 software and using structural equation modeling.ResultsThe results showed that psychological capital, social support, and attitude towards death directly affect health‐promotion behaviors and also indirectly improve them through cognitive emotion regulation strategies. These results can have a significant impact on promoting health and improving the quality of life of the elderly population.ConclusionsBased on the findings of the present study, it can be claimed that the proposed model for the health of the elderly has an acceptable fitness and this model can be used in developing educational programs and intervention techniques to improve the health of this group of people.
Using smartphones to disseminate home learning support to primary caregivers: An exploratory proof‐of‐concept study
Authors: Cohrssen Caroline , Richards Ben , Wang Rhoda 
Published: January 2023

AbstractDuring the Covid‐19 pandemic, kindergartens in Hong Kong have sought ways in which to support children's learning at home while schools were closed. We report on a proof‐of‐concept study: short videos intended to support playful learning at home were distributed to parents/caregivers of preschool children via a smartphone app; toys and a storybook were provided to their children. No significant changes were observed in the importance attached to literacy and numeracy by parents/caregivers over time, perhaps because parents/caregivers place high value on children's academic progress in Hong Kong. However, significant increases in mean scores were observed for the intervention group but not the control group with regard to reported frequency of playing counting games and discussing/participating in weighing or measuring activities. Readily accessible opportunities to recognize learning in playful activities may have contributed to changed practices at homes.Highlights
Reports the extent of the impact of short videos distributed via a smartphone app on parents'/caregivers' HLE practices during Covid‐19 kindergarten closures.
Survey data reveal parent/caregiver practice unchanged by 4x weekly videos. However, practices increased across waves in the intervention group.
Smartphone dissemination of HLE demonstration videos holds promise as a strategy, but threshold conditions require further research.
Financial crises and the national logistics performance: Evidence from emerging and developing countries
Authors: Nguyen Thanh Cong , Le Trung Hieu 
Published: December 2022

AbstractThis study explores the effects of financial crises on the national logistics performance using a panel of more than 100 emerging and developing countries over the period 2007–2017. We focus on different types of financial crises (banking, currency, and debt crises) and find that any type of financial crisis undermines the national logistics performance. By focusing on critical dimensions of the national logistics performance, we find that financial crises have a negative impact on logistics‐supported infrastructure, market size, education and training, technological readiness, and innovation. This impact is more pronounced in low‐income countries and in election years, whilst it weakens in the presence of majority governments and when right‐wing governments stay in office.
Risk factors for loss to follow‐up after the start of direct‐acting antiviral treatment for hepatitis C virus infection
Authors: Kuwano Akifumi , Yada Masayoshi , Kurosaka Kazuki , Tanaka Kosuke , Masumoto Akihide , Motomura Kenta 
Published: December 2022

AbstractBackground and AimDirect‐acting antivirals (DAAs) have recently been developed to treat hepatitis C virus (HCV) infection. Additionally, interferon‐free DAA treatment has improved liver function and reduced the risk of hepatocellular carcinoma (HCC) following HCV eradication. Previous studies on HCV have focused mainly on the treatment rate and the risk of developing HCC, and less attention has been given to loss to follow‐up (LTFU) after DAA treatment. Therefore, the present study aimed to identify the definitive risk factors for LTFU after the start of DAA treatment.MethodsBetween September 2017 and March 2022, 296 patients receiving glecaprevir and pibrentasvir for HCV infection were enrolled in this study. The incidence of LTFU following DAA treatment and the risk factors contributing to LTFU were identified using the patients' clinical characteristics.ResultsIn the present study, 75 patients (25.3%) interrupted their follow‐up visits. Multivariate logistic analysis revealed a history of injection drug use (hazard ratio [HR], 1.81; P = 0.017), treatment duration (8 weeks) (HR, 3.51; P = 0.0033), and age <70 years (HR, 1.9; P = 0.0422) as independent factors associated with LTFU after the start of DAA treatment.ConclusionYoung patients and those with injection drug use are likely to discontinue their follow‐up visits after the start of DAA treatment for HCV infection. Therefore, these patients require strict supervision.
How guideline development has informed clinical research for organic acidurias (et vice versa)
Authors: Forny Patrick , Hörster Friederike , Baumgartner Matthias R. , Kölker Stefan , Boy Nikolas 
Published: January 2023

AbstractOrganic acidurias, such as glutaric aciduria type 1 (GA1), methylmalonic (MMA), and propionic aciduria (PA) are a prominent group of inherited metabolic diseases involving accumulation of eponymous metabolites causing endogenous intoxication. For all three conditions, guidelines for diagnosis and management have been developed and revised over the last years, resulting in three revisions for GA1 and one revision for MMA/PA. The process of clinical guideline development in rare metabolic disorders is challenged by the scarcity and limited quality of evidence available. The body of literature is often fragmentary and where information is present, it is usually derived from small sample sizes. Therefore, the development of guidelines for GA1 and MMA/PA was initially confronted with a poor evidence foundation that hindered formulation of concrete recommendations in certain contexts, triggering specific research projects and initiation of longitudinal, prospective observational studies using patient registries. Reversely, these observational studies contributed to evaluate the value of newborn screening, phenotypic diversities, and treatment effects, thus significantly improving the quality of evidence and directly influencing formulation and evidence levels of guideline recommendations. Here, we present insights into interactions between guideline development and (pre)clinical research for GA1 and MMA/PA, and demonstrate how guidelines gradually improved from revision to revision. We describe how clinical studies help to unravel the relative impact of therapeutic interventions on outcome and conclude that despite new and better quality of research data over the last decades, significant shortcomings of evidence regarding prognosis and treatment remain. It appears that development of clinical guidelines can directly help to guide research, and vice versa.
Assessing Tissue Hydration Dynamics Based on Water/Fat Separated MRI
Authors: Karlsson Markus , Indurain Ainhoa , Romu Thobias , Tunon Patrik , Segelmark Mårten , Uhlin Fredrik , Fernström Anders , Leinhard Olof Dahlqvist 
Published: January 2023

BackgroundOptimal fluid status is an important issue in hemodialysis. Clinical evaluation of volume status and different diagnostic tools are used to determine hydration status in these patients. However, there is still no accurate method for this assessment.PurposeTo propose and evaluate relative lean water signal (LWSrel) as a water–fat MRI‐based tissue hydration measurement.Study TypeProspective.PopulationA total of 16 healthy subjects (56 ± 6 years, 0 male) and 11 dialysis patients (60.3 ± 12.3 years, 9 male; dialysis time per week 15 ± 3.5 hours, dialysis duration 31.4 ± 27.9 months).Field Strength/SequenceA 3 T; 3D spoiled gradient echo.AssessmentLWSrel, a measurement of the water concentration of tissue, was estimated from fat‐referenced MR images. Segmentations of total adipose tissue as well as thigh and calf muscles were used to measure LWSrel and tissue volumes. LWSrel was compared between healthy subjects and dialysis patients, the latter before and after dialysis. Bioimpedance‐based body composition monitor over hydration (BCM OH) was also measured.Statistical TestsT‐tests were used to compare differences between the healthy subjects and dialysis patients, as well as changes between before and after dialysis. Pearson correlation was calculated between MRI and non‐MRI biomarkers. A P value <0.05 was considered statistically significant.ResultsThe LWSrel in adipose tissue was significantly higher in the dialysis cohort compared with the healthy cohort (246.8% ± 60.0% vs. 100.0% ± 10.8%) and decreased significantly after dialysis (246.8 ± 60.0% vs. 233.8 ± 63.4%). Thigh and calf muscle volumes also significantly decreased by 3.78% ± 1.73% and 2.02% ± 2.50% after dialysis. There was a significant correlation between changes in adipose tissue LWSrel and ultrafiltration volume (r = 87), as well as with BCM OH (r = 0.66).Data ConclusionMRI‐based LWSrel and tissue volume measurements are sensitive to tissue hydration changes occurring during dialysis.Evidence Level2.Technical EfficacyStage 3.