bluuebunny/crossref_metadata_2025_split huggingface dataset:
Rhodococcus erythropolis ATCC 4277 behavior against different metals and its potential use in waste biomining
Authors: Brandão Igor Yannick Neves Vasconcellos , Silva Pedro Henrique Barboza Souza , Castori Tayna Vale , Souza Yasmin Tavares , Souza Ricardo Gabbay , Batista Aline Fontana , Petroni Sergio Luis Graciano , Zanutto Talita Corrêa Nazareth , Campos Claudia Barbosa Ladeira , Maass Danielle 
Published: December 2023

Abstract
Rhodococcus erythropolis bacterium is known for its remarkable resistance characteristics that can be useful in several biotechnological processes, such as bioremediation. However, there is scarce knowledge concerning the behavior of this strain against different metals. This study sought to investigate the behavior of R. erythropolis ATCC 4277 against residue of chalcopyrite and e-waste to verify both resistive capacities to the metals present in these residues and potential use for biomining processes. These tests were carried out in a stirred tank bioreactor for 48 h, at 24 ºC, pH 7.0, using a total volume of 2.0 L containing 2.5% (v/v) of a bacterial pre-culture. The pulp density of chalcopyrite was 5% (w/w), and agitation and oxygen flow rates were set to 250 rpm and 1.5 LO2.min− 1, respectively. In the tests with e-waste (waste of computer printed circuit board - WPCB), it was used a pulp density of 10% (w/w), agitation at 400 rpm, and 3.0 LO2.min− 1 of oxygen flow rate. Metal concentration analyses post-fermentation showed that R. erythropolis ATCC 4277 was able to leach about 38% of the Cu present in the chalcopyrite residue (in ~ 24 h), and 49.5% of Fe, 42.3% of Ni, 27.4% of Al, and 15% Cu present in WPCB (in ~ 24 h). In addition the strain survived well in the environment containing such metals, demonstrating the potential of using this bacterium for waste biomining processes as well as in other processes with these metals.
Interactions between fungal communities and localized conservative N cycling in mixed mycorrhizal tropical forests
Authors: Seyfried Georgia S , Edwards Joseph D , Dalling James W , Kent Angela D , Yang Wendy H 
Published: December 2023

Abstract
Background and aims Ectomycorrhizal (ECM) trees and associated fungal communities can interact with underlying nutrient dynamics to suppress carbon (C) and nitrogen (N) cycling locally. Specifically, N availability may dictate interactions between ECM and saprotrophic fungi and belowground C allocation by ECM trees, potentially determining the potential of fungal communities to suppress N cycling beneath ECM trees. However, these mechanisms have largely been tested in temperate and boreal systems where underlying N limitation is common.Methods Here, we quantified fungal community metrics and soil chemical properties in a long-term N addition experiment located in a lower montane tropical forest to assess the role of fungal communities in driving conservative N cycling beneath ECM trees within mixed ECM-AM stands where N is not necessarily limiting.Results We found that natural abundance N isotopes correlated with a shift in fungal community composition between control and N addition plots, suggesting that N availability may affect belowground C allocation to increase colonization by ECM fungi that are a larger C investment and have a greater potential to interact with soil N cycling. However, we found no effect of N addition on the distribution of ECM and saprotrophic fungal guilds through the soil profile, suggesting that abiotic and biotic conditions which promote rapid N cycling may decrease interguild competition in a tropical montane forest.Conclusions Overall, local scale nutrient limitation dynamics driven by interactions between ECM host trees and underlying fungal communities may be partially mediated by ecosystem scale nutrient cycling dynamics.
Health Outcomes Following Covid-19 Infection and Vaccination in Hereditary Hemorrhagic Telangiectasia
Authors: Tarulli Christopher M. , Ma Xiayi , Chokar Kamalprit , Vozoris Nicholas T. , Clancy Marianne S. , Faughnan Marie E. 
Published: December 2023

Abstract
Background: There has been concern that individuals living with Hereditary Hemorrhagic Telangiectasia (HHT) could be at higher risk for poor outcomes if infected with SARS-CoV2, the virus that causes COVID-19 disease. As literature is lacking on outcomes on COVID-19 infection and vaccination in HHT, the objectives of this study were to determine and assess outcomes in HHT, as well as quantify vaccination rates and vaccination side effects in a large cohort of individuals with HHT.
Method: Individuals previously recruited to OUR HHT Registry at St. Michael’s Hospital, Toronto were contacted for participation in this study. Data were collected during annual assessment through a series of questionnaires asking specifically about HHT complications, treatments, and symptom management, along with COVID infection and vaccination data.
Results: Of the 262 subjects recruited to the registry, 215 (82%) have been contacted at least once regarding COVID-19 related inquiries between April 2020 and August 2022. Forty-nine COVID-19 infections were reported in 47/215 (21.9%) individuals. Among 47 patients with recorded COVID-19 infection, 2/47 (4.3%) required urgent care and 7/47 (14.9%) were hospitalized following infection. Of the 7 individuals who were hospitalized, 3 (42.9%) required new supplemental oxygen. Zero deaths were reported due to COVID-19 infection.
COVID vaccination history was available in 147/215 (68.4%). Of these, 135/147 (91.8%) of individuals reported vaccination and side effects were mild.
Discussion: While our sample population is much like the general HHT population with regards to gender, HHT symptoms, and genetics, study limitations including survivor bias, lack of vaccine effectiveness assessment, and participant reported data should be acknowledged.
Conclusion: Our results suggest that HHT patients are not at higher risk of severe infection with COVID-19 compared to the general population. Vaccination rates are high with only mild side effects being observed.
The Association of Regular Dog Walking with Mobility, Falls and Fear of Falling in Later Life.
Authors: Gallagher Eleanor , Lavan Amanda , Kenny Rose Anne , Briggs Robert 
Published: December 2023

Abstract
Purpose
To assess whether regular dog walking was associated with reduced likelihood of falls, fear of falling and mobility problems in a large cohort of community-dwelling older people.
Methods
Participants aged ≥60 years at TILDA Wave 5 were included. Regular dog walking was ≥4 days/week.
Falls and fear of falling were by self-report. Mobility was measured with Timed-Up-and-Go (TUG).
Logistic Regression models assessed the association between regular dog walking and outcomes of interest.
Results
Regular dog walkers had a significantly faster TUG (10.3 (10.1-10.5) vs 11.7 (11.1-12.2) seconds) and a lower likelihood of unexplained falls (OR 0.59 (0.37–0.95; p=0.028), fear of falling (OR 0.78 (95% CI 0.63–0.96); p=0.022) and mobility problems (0.60 (0.40–0.92); p=0.017) in fully-adjusted models.
Discussion
While longitudinal studies are required, older people should be encouraged to continue regular walking their dog where feasible as it may reduce the risk of falls and mobility problems.
Urban and Rural Disparities in the Availability of Diabetes Prevention Programs in US Hospitals
Authors: Hughes Allyson , Sri Shyamkumar , Franz Berkeley , Cronin Cory 
Published: December 2023

Abstract

Purpose
Type 2 diabetes is a global pandemic, with 1 in 6 people expected to be diagnosed by 2050. The Diabetes Prevention Program (DPP) is an evidence-based program that has been shown to reduce A1c and bolster health outcomes in people with type 2 diabetes and prediabetes, but implementation has been varied, with lower uptake in rural communities. The study assessed whether there are geographic disparities between rural and urban communities in hospital-supported DPPs in the US.
Methods
We assessed DPPs in 3,204 general medical hospitals. Data on hospital and county characteristics came from the American Hospital Association (AHA) Annual Survey, the Area Health Resource File, and County Health Rankings. We assessed geographic differences between hospitals with and without DPPs using t-tests and chi-square tests. Rurality was determined based on the 2013 Rural-Urban Continuum Codes (RUCC). We then conducted a multivariable analysis to assess the relationship between geographic location and the presence of a DPP, independent of hospital, county, and population characteristics.
Findings
In the unadjusted model, hospitals located in counties with lower population density had significantly lower odds of offering DPP (OR = .93, 95% CI: .0.91, 0.96). After controlling for organizational and community characteristics, population density was no longer a significant predictor of DPP. Larger hospitals had higher odds of offering DPP (OR = 1.002, 95% CI: 1.001, 1.002) as did both nonprofit (OR = 3.25, 95% CI: 2.46, 4.30) and public hospitals (OR = 3.10, 95% CI: 2.24, 4.30) as compared to their for-profit counterparts. Hospitals in the South (OR = .65, 95% CI: .53, .79) and Western (OR = .77, 95% CI: .62, .95) regions of the United States had lower odds of offering diabetes prevention programs in comparison to hospitals located in the Midwest.
Conclusions
DPP implementation is less common in rural and underserved areas. These programs are also less common in smaller hospitals. The interaction between resources and hospital location is helpful for understanding barriers to program implementation.
Guns, Germs, and Slaves: an Alternative View of the Colonial Origins of Comparative Development
Authors: ARCAND JEAN LOUIS , Sylvan David , Aladysheva Anastasia , Gadjanova Elena 
Published: December 2023

Abstract
This paper shows that early colonial interactions between Europeans and indigenous populations, specifically the deaths of the latter, have long-term effects on economic development. We propose an alternative view on the historical origins of comparative development, arguing for links between pre-colonial conditions, colonial-era practices, and growth centuries later. We explore the decades of first contact between Europeans and the indigenous population for both violence against that population and the type of political-economic regime established. These violence and regime consequences affected the strength or weakness of property-protecting institutions, with the latter in turn influencing per capita income today. JEL: O43, O47, N40
Nudge-Based Misinformation Interventions are Effective in Information Environments with Low Misinformation Prevalence
Authors: Butler Lucy H. , Prike Toby , Ecker Ullrich K. H. 
Published: December 2023

Abstract

Nudge-based misinformation interventions are presented as cheap and effective ways to reduce the spread of misinformation online. However, despite online information environments typically containing low volumes of misinformation, most studies testing the effectiveness of nudge interventions present equal proportions of true and false information. As the effectiveness of nudges can be highly context-dependent, it is imperative to validate the effectiveness of nudge-based interventions in environments with more realistic proportions of misinformation. The current study (N = 1387) assessed the effectiveness of a combined accuracy and social-norm nudge in simulated social-media environments with varying proportions of misinformation (50%, 20%, and 12.5%). The nudge intervention was effective at improving engagement behavior in all conditions, including those with a lower proportion of misinformation. These findings provide ecologically valid support for the use of nudge-based interventions to counter misinformation propagation on social-media platforms.
An integer programming approach for determining optimal building height
Authors: Egozcue Martin 
Published: December 2023

Abstract
Building height is of crucial importance in architectural design. In this paper, we develop an integer programming model to determine the optimal number of stories in high-rise buildings. This model relies on the analysis of profit cash flow over time. The practical insights of our proposal are illustrated through a real-world case study involving a hypothetical development in Punta del Este, Uruguay. A sensitivity analysis of the variables that exert a more significant impact on the optimal height is studied as well.
A novel α,β-unsaturated ketone inhibits leukemia cell growth as PARP1 inhibitor
Authors: Zhao Weijia , Mo Min , Yu Jia , Cheng Sha , Long GuiPing , Luo ZhiQiong , Liang Wei , Yan Chen , Luo Heng , Sun Baofei 
Published: December 2023

Abstract
Leukemia is a malignant disease of the hematopoietic system, in which clonal leukemia cells accumulate and inhibit normal hematopoiesis in the bone marrow and other hematopoietic tissues as a result of uncontrolled proliferation and impaired apoptosis, among other mechanisms. In this study, the anti-leukemic effect of a compound (SGP-17-S) extracted from Chloranthus multistachys, a plant with anti-inflammatory, antibacterial and anti-tumor effects, was evaluated. The effect of SGP-17-S on the viability of leukemic cell was demonstrated by MTT assay, cell cycle and apoptosis were assessed by flow cytometry using PI staining and Annexin V/PI double staining. Combine network pharmacology and cellular thermal shift assay (CETSA) with western blot were used to validate agents that act on leukemia targets. The results showed that SGP-17-S inhibited the growth of leukemia cells in a time- and dose-dependent manner. SGP-17-S blocked HEL cells in the G2 phase, induced apoptosis, decreased Bcl-2 and caspase-8 protein expression, and increased Bax and caspase-3 expression. In addition, CETSA revealed that PARP1 is an important target gene for the inhibition of HEL cell growth and SGP-17-S exerted its action on leukemia cells by targeting PARP1. Therefore, this study might provide new solutions and ideas for the treatment of leukemia.
Assessing the impact of Delta and Omicron in German intensive care units: a retrospective multistate analysis based on nationwide inpatient billing data
Authors: Lottes Matthäus , Grodd Marlon , Grabenhenrich Linus , Wolkewitz Martin 
Published: December 2023

Abstract
Background
The spread of several severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) variants of concern (VOC) repeatedly led to increasing numbers of coronavirus disease 2019 (COVID-19) patients in German intensive care units (ICUs), resulting in capacity shortages and even transfers of COVID-19 intensive care patients between federal states in late 2021. In this respect, there is limited evidence on the impact of predominant VOC in German ICUs on the population level.
Methods
A retrospective cohort study was conducted from July 01, 2021, to May 31, 2022, using nationwide inpatient billing data from German hospitals on COVID-19 intensive care patients and SARS-COV-2 sequence data from Germany. A multivariable Poisson regression analysis was performed to estimate incidence rate ratios (IRRs) of transfer (to another hospital during inpatient care), discharge and death of COVID-19 intensive care patients associated with Delta or Omicron, adjusted for age group and sex. Furthermore, a multistate model was used for the clinical trajectories of COVID-19 intensive care patients to estimate their competing risk of transfer, discharge or death associated with Delta or Omicron, while further addressing patient age.
Results
Poisson regression analysis comparing Omicron versus Delta infection yielded an estimated adjusted IRR of 1.23 (95% CI 1.16–1.30) for transfers, 2.27 (95% CI 2.20–2.34) for discharges and 0.98 (95% CI 0.94–1.02) for deaths. For ICU deaths in particular, the estimated adjusted IRR increased from 0.14 (95% CI 0.08–0.22) for the 0–9 age group to 4.09 (95% CI 3.74–4.47) for those aged 90 and older compared to the reference group of 60-69-year olds. Multistate analysis showed that Omicron infection was associated with a higher estimated risk of discharge for COVID-19 intensive care patients across all ages, while Delta infection was associated with a higher estimated risk transfer and death.
Conclusions
Retrospective, nationwide comparison of transfers, discharges and deaths of COVID-19 intensive care patients during Delta- and Omicron-dominated periods in Germany suggested overall less severe clinical trajectories with Omicron. Age confirmed as an important determinant for fatal clinical outcomes in COVID-19 intensive care patients, necessitating close therapeutic care for the elderly and appropriate public health control measures.
Clockwork: A Discrete Event and Agent-Based Social Simulation Framework
Authors: Azad Sasha , Beymer David , Pillai Anup , Zimmerman Tom , Seabolt Ed , Bulu Hakan , Potts Colin M. , Burrowes Vanessa , Mukherjee Vandana , Jhala Arnav 
Published: December 2023

Abstract

Agent-based social simulation can be useful for creating digital twins of societies of interacting autonomous agents. Such simulations are useful for testing hypotheses about behaviour and belief change in the presence of interventions. In this paper, we introduce Clockwork, an efficient multi-agent simulation framework. The key contribution of this framework is integrating a behaviour-level simulation of autonomous agent schedules with a Discrete Event Simulator (DES) and a rich model of social interaction among agents modelled with Agent-Based Social Simulation (ABSS) methodology. Clockwork's ability to simulate deterministic and stochastic events and changes in individual agent models due to the influence of other agents through event-based emergent interactions is novel. We describe the design, architecture, and development of the Clockwork framework. Combining DES and ABSS in this way enables the modelling of detailed individual agent histories while maintaining population-level statistical distributions. We evaluated Clockwork with a real-life scenario modelling the digital twin of employees at a real-world worksite to test the efficacy of various policies put in place to mitigate the risk of contracting COVID-19 through a hybrid or in-person work model.
Enhanced K-NN with Bayesian Optimization Algorithm for Predicting Energy Efficiency of Smart Grids in IoT
Authors: ZHAO Wenlong , Yuanchao HU , Xiaopeng YAN , LIU Xiaowei , Rixian DING , Chaofeng DAI , CAO Ying 
Published: December 2023

Abstract

With the increasing number of end users using electricity in modern cities, smart grids have some critical problems for energy efficiency and managing renewable energy resources. Therefore, electricity load forecasting is an important strategy to avoid power disconnection and power communication damages in smart grids. On the other hand, the Internet of Things (IoT) devices can collect appropriate data from end users with smart metering. In addition, smart devices can check and gather critical data from power stations using smart sensors and actuators to provide the Quality of Service (QoS) factors and energy efficiency of electricity transmission in the smart girds. Due to the huge data transmission, machine learning is useful for evaluating electricity load forecasting and power stability in smart grids. For detecting electric load forecasting and energy consumption factors, this paper develops Bayesian Optimization for K-nearest neighbor (BOKNN) with the hyper-parameters function to detect the electricity load forecasting and estimated power consumption factors in smart grids. The proposed technique optimizes the performance of electricity load forecasting and enhances the structure of the machine learning efficiency with high model accuracy. Two real-data sets as our case studies for Short-Term Electricity Load Forecasting are applied to evaluate the proposed BOKNN as existing experimental testbeds. The simulation results illustrate that the proposed BOKNN provides optimized high accuracy with 88.33% and 98.13% correlation coefficient and minimum Mean Absolute Error (MAE) with 0.04% for existing datasets. The experimental results show that the suggested BOKNN model greatly outperforms the state-of-the-art prediction algorithms.
SSB-YOLO: A vehicle object detection algorithm based on improved YOLOv8
Authors: Wang Mingda , Ren Luyuan 
Published: December 2023

Abstract
In the field of computer vision, vehicle object detection has been a topic of significant and complex interest. With the rise of intelligent transportation systems and autonomous driving technology, the importance of vehicle object detection continues to be highlighted. Given the current issues of low precision, high miss rate, and poor robustness in existing algorithms, this study introduces an improved vehicle detection algorithm, SSB-YOLO, based on the YOLOv8 model. The SSB-YOLO algorithm integrates the Shuffle Attention mechanism to filter out unimportant factors and enhance model performance; it also incorporates the spatial and channel reconstruction convolution mechanism to reduce spatial and channel redundancy between features in convolutional neural networks. Furthermore, a new and better algorithm based on Wise-IoU optimization is proposed, which yields superior bounding box regression performance throughout the training period. The model demonstrated improved detection accuracy and reduced computational cost. The experimental results indicate that, compared to the YOLOv8n model, SSB-YOLO achieves a 1.6% increase in mAP@50. This approach outperforms other object detection algorithms, enhancing the overall system's robustness and accuracy and thereby providing higher precision in the field of vehicle detection.
Patient’s Perspectives on Treatment Burden in Type 2 Diabetes Mellitus: Focus Groups in Primary Care Settings
Authors: Lin Kai , Yao Mi , ANDREW Lesley , Li Rouyan , Chen Yilin , OOSTHUIZEN Jacques , SIM Moira , CHEN Yongsong 
Published: December 2023

Abstract
Background
Understanding treatment burden is a crucial component of effectively managing Type 2 Diabetes Mellitus (T2DM). While our previous narrative review had proposed a thematic framework for identifying treatment burden in people with T2DM, the current study aimed to fill the knowledge gap about T2DM treatment burden from the patient’s perspective in primary care settings.
Methods
Purposive sampling was used to recruit a spread of participants from primary care settings across various socio-economic regions in China. Focus groups were organised to explore patients’ perspectives. The discussions were audio-recorded, transcribed, and analysed with a theoretical lens of the Cumulative Complexity Model (CuCoM) to facilitate the identification and understanding of patient workload and capacity in the context.
Results
The study engaged four focus groups, each consisting of five participants. Building on the thematic framework from previous research, this study further refined five key themes, including medical information, medication, administration, healthcare system, and lifestyle, through subtheme refinement and categorization. A significant development was the merging of the financial and time/travel themes into a new "personal resources" theme, reflecting their overlapping nature. This refinement led to a finalised conceptual framework with six core themes, including personal resources as an overlapping theme. The framework also incorporated antecedents and consequences as themes, identifying associated factors of T2DM treatment burden. Additionally, the study highlighted an often-overlooked theme of medical information in treatment burden research and underscored systemic inadequacies within the healthcare system, highlighting the critical challenge of balancing health needs with treatment accessibility in primary care settings.
Conclusions
This study underscores the multifaceted nature of the T2DM treatment burden. Significantly, it contributes to the development of a conceptual framework for understanding and measuring this construct in primary care settings. The study also highlights the need to consider each patient's personal resources allocation and utilisation of treatment.