bluuebunny/crossref_metadata_2025_split huggingface dataset:
Blood-feeding patterns of Culex pipiens biotype pipiens and pipiens/molestus hybrids in relation to avian community composition in urban habitats
Authors: Blom Rody , Krol Louie , Langezaal Melissa , Schrama Maarten , Trimbos Krijn B. , Wassenaar Daan , Koenraadt Constantianus J. M. 
Published: February 2024

Abstract
Background
Culex pipiens sensu stricto (s.s.) is considered the primary vector of Usutu virus and West Nile virus, and consists of two morphologically identical but behaviourally distinct biotypes (Cx. pipiens biotype pipiens and Cx. pipiens biotype molestus) and their hybrids. Both biotypes are expected to differ in their feeding behaviour, and pipiens/molestus hybrids are presumed to display intermediate feeding behaviour. However, the evidence for distinct feeding patterns is scarce, and to date no studies have related differences in feeding patterns to differences in host abundance.

Methods
Mosquitoes were collected using CO2-baited traps. We collected blood-engorged Cx. pipiens/torrentium specimens from 12 contrasting urban sites, namely six city parks and six residential areas. Blood engorged Cx. pipiens/torrentium mosquitoes were identified to the species and biotype/hybrid level via real-time polymerase chain reaction (PCR). We performed blood meal analysis via PCR and Sanger sequencing. Additionally, avian host communities were surveyed via vocal sounds and/or visual observation.

Results
We selected 64 blood-engorged Cx. pipiens/torrentium mosquitoes of which we successfully determined the host origin of 55 specimens. Of these, 38 belonged to biotype pipiens, 14 were pipiens/molestus hybrids and the identity of three specimens could not be determined. No blood-engorged biotype molestus or Cx. torrentium specimens were collected. We observed no differences in feeding patterns between biotype pipiens and pipiens/molestus hybrids across different habitats. Avian community composition differed between city parks and residential areas, whereas overall avian abundance did not differ between the two habitat types.

Conclusions
Our results show the following: (1) Cx. pipiens s.s. feeding patterns did not differ between city parks and residential areas, regardless of whether individuals were identified as biotype pipiens or pipiens/molestus hybrids. (2) We detected differences in host availability between city parks and residential areas. (3) We show that in both urban habitat types, biotype pipiens and pipiens/molestus hybrids fed on both mammalian and avian hosts. This underscores the potential role in arbovirus transmission of biotype pipiens and pipiens/molestus hybrids.

Graphical Abstract
Effects of six-week stroboscopic training program on visuomotor reaction speed in goal-directed movements in young volleyball players: a study focusing on agility performance
Authors: Zwierko Michał , Jedziniak Wojciech , Popowczak Marek , Rokita Andrzej 
Published: February 2024

Abstract
Background
In team sports, deficits in visuomotor reaction speed are considered a significant and modifiable risk factor that can lead to decreased performance and an increased risk of injuries. Thus, identifying effective methods to enhance visuomotor abilities is crucial. The main objective of this research was to investigate the impact of a six-week stroboscopic intervention on visuomotor reaction speed in goal-directed specific movements based on agility among young volleyball players. Additionally, the study aimed to explore the impact of saccade dynamics on visuomotor reaction speed performance throughout the experiment.

Methods
There were 50 athletes (26 males and 24 females) with an average age of 16.5 years (± 0.6) who participated in this study. Over a six-week training period, athletes performed volleyball-specific training either wearing stroboscopic glasses (intervention) or under normal visual conditions (control). Prior to and after the training period, the agility tests based on change-of-direction speed (CODS) and reactive agility (RA) were used to identify visuomotor reaction speed performance. To measure agility performance a five-repetition shuttle run to gates was conducted. The REAC-INDEX, which represents visuomotor reaction speed, was analyzed as the resulting difference between the CODS test and the RA test. To elicit saccadic dynamics, a laboratory visual search task was performed.

Results
A significant GROUP×TIME interaction was observed for the REAC-INDEX (p = 0.012, ηp2 = 0.13). ANCOVA analyses revealed significant GROUP differences, indicating improved post-training REAC-INDEX results (p = 0.004, d = 0.87), regardless of gender. Training-induced modulations in saccade acceleration did not reach significance, but a significant relationship was observed between changes in saccade acceleration and changes in the REAC-INDEX (r = -0.281, p = 0.048), indicating that higher performance gains following training were associated with a stronger increase in saccade acceleration.

Conclusions
This study demonstrates that stroboscopic training effectively enhances visuomotor reaction speed in goal-directed movements based on agility. Furthermore, visuomotor reaction speed gains could potentially be mediated by saccade dynamics. These findings provide valuable insights into the effectiveness of stroboscopic eyewear for training sport-specific visuomotor skills among young volleyball players.
Progression analysis versus traditional methods to quantify slowing of disease progression in Alzheimer’s disease
Authors: Jönsson Linus , Ivkovic Milana , Atri Alireza , Handels Ron , Gustavsson Anders , Hahn-Pedersen Julie Hviid , León Teresa , Lilja Mathias , Gundgaard Jens , Raket Lars Lau 
Published: February 2024

AbstractBackgroundThe clinical meaningfulness of the effects of recently approved disease-modifying treatments (DMT) in Alzheimer’s disease is under debate. Available evidence is limited to short-term effects on clinical rating scales which may be difficult to interpret and have limited intrinsic meaning to patients. The main value of DMTs accrues over the long term as they are expected to cause a delay or slowing of disease progression. While awaiting such evidence, the translation of short-term effects to time delays or slowing of progression could offer a powerful and readily interpretable representation of clinical outcomes.MethodsWe simulated disease progression trajectories representing two arms, active and placebo, of a hypothetical clinical trial of a DMT. The placebo arm was simulated based on estimated mean trajectories of clinical dementia rating scale–sum of boxes (CDR-SB) recordings from amyloid-positive subjects with mild cognitive impairment (MCI) from Alzheimer’s Disease Neuroimaging Initiative (ADNI). The active arm was simulated to show an average slowing of disease progression versus placebo of 20% at each visit. The treatment effects in the simulated trials were estimated with a progression model for repeated measures (PMRM) and a mixed model for repeated measures (MMRM) for comparison. For PMRM, the treatment effect is expressed in units of time (e.g., days) and for MMRM in units of the outcome (e.g., CDR-SB points). PMRM results were implemented in a health economics Markov model extrapolating disease progression and death over 15 years.ResultsThe PMRM model estimated a 19% delay in disease progression at 18 months and 20% (~ 7 months delay) at 36 months, while the MMRM model estimated a 25% reduction in CDR-SB (~ 0.5 points) at 36 months. The PMRM model had slightly greater power compared to MMRM. The health economic model based on the estimated time delay suggested an increase in life expectancy (10 months) without extending time in severe stages of disease.ConclusionPMRM methods can be used to estimate treatment effects in terms of slowing of progression which translates to time metrics that can be readily interpreted and appreciated as meaningful outcomes for patients, care partners, and health care practitioners.
New insights into bioaugmented removal of sulfamethoxazole in sediment microcosms: degradation efficiency, ecological risk and microbial mechanisms
Authors: Chen Jianfei , Chen Xiuli , Zhu Ying , Yan Shuang , Xie Shuguang 
Published: February 2024

Abstract
Background
Bioaugmentation has the potential to enhance the ability of ecological technology to treat sulfonamide-containing wastewater, but the low viability of the exogenous degraders limits their practical application. Understanding the mechanism is important to enhance and optimize performance of the bioaugmentation, which requires a multifaceted analysis of the microbial communities. Here, DNA-stable isotope probing (DNA-SIP) and metagenomic analysis were conducted to decipher the bioaugmentation mechanisms in stabilization pond sediment microcosms inoculated with sulfamethoxazole (SMX)-degrading bacteria (Pseudomonas sp. M2 or Paenarthrobacter sp. R1).

Results
The bioaugmentation with both strains M2 and R1, especially strain R1, significantly improved the biodegradation rate of SMX, and its biodegradation capacity was sustainable within a certain cycle (subjected to three repeated SMX additions). The removal strategy using exogenous degrading bacteria also significantly abated the accumulation and transmission risk of antibiotic resistance genes (ARGs). Strain M2 inoculation significantly lowered bacterial diversity and altered the sediment bacterial community, while strain R1 inoculation had a slight effect on the bacterial community and was closely associated with indigenous microorganisms. Paenarthrobacter was identified as the primary SMX-assimilating bacteria in both bioaugmentation systems based on DNA-SIP analysis. Combining genomic information with pure culture evidence, strain R1 enhanced SMX removal by directly participating in SMX degradation, while strain M2 did it by both participating in SMX degradation and stimulating SMX-degrading activity of indigenous microorganisms (Paenarthrobacter) in the community.

Conclusions
Our findings demonstrate that bioaugmentation using SMX-degrading bacteria was a feasible strategy for SMX clean-up in terms of the degradation efficiency of SMX, the risk of ARG transmission, as well as the impact on the bacterial community, and the advantage of bioaugmentation with Paenarthrobacter sp. R1 was also highlighted﻿.
Application of computer vision technology in surface damage detection and analysis of shedthin tiles in China: a case study of the classical gardens of Suzhou
Authors: Yan Lina , Chen Yile , Zheng Liang , Zhang Yi 
Published: February 2024

Abstract
In computer artificial intelligence, there is great potential in research on the protection of Suzhou's traditional gardens, a world cultural heritage site. As a special material in Suzhou's traditional garden architecture, shedthin tile is widely used in roof base laying and is one of the important materials for building roofs. However, professionals need to reach the roof and spend much time and effort assessing the damage before repairing it. Therefore, the main goals of this study are to investigate a machine learning-based method for finding targets and determining the type of surface damage on a shedthin tile using the YOLOv4 model trained in this study. Using 500 shedthin tile on-site photos as training samples, the model was trained for 750 epochs. The main results of this study are as follows: (1) An object detection method based on machine learning can efficiently and accurately identify damage content, overcoming the manpower and time–cost limitations of traditional assessment methods. (2) The detection model in this study has an accuracy of 85.89% for water stain recognition of shedthin tiles, 93.29% for surface scaling, 87.37% for color aberration, and 96.15% for too wide a gap. The comprehensive accuracy is 90.20%, which meets the basic testing requirements. (3) The model demonstrated its robustness and reliability in complex environments in application tests in actual scenarios, providing a methodological reference for computer vision and target detection technology in cultural heritage protection.
Magnesium silicate chimneys at the Strytan hydrothermal field, Iceland, as analogues for prebiotic chemistry at alkaline submarine hydrothermal vents on the early Earth
Authors: Gutiérrez-Ariza Carlos , Barge Laura M. , Ding Yang , Cardoso Silvana S. S. , McGlynn Shawn Erin , Nakamura Ryuhei , Giovanelli Donato , Price Roy , Lee Hye Eun , Huertas F. Javier , Sainz-Díaz C. Ignacio , Cartwright Julyan H. E. 
Published: February 2024

AbstractThe Strytan Hydrothermal Field (SHF) in basaltic terrain in Iceland is one of the extant alkaline submarine hydrothermal vent systems favoured as analogues for where life on Earth may have begun. To test this hypothesis we analyse the composition, structure, and mineralogy of samples from hydrothermal chimneys generated at the SHF. We find that the chimney precipitates are composed of Mg-silicates including clays of the saponite-stevensite group (high Mg and Si, low Fe and Al), Ca-carbonates and Ca-sulfates. The chimneys comprise permeable structures with pores sizes down to 1 µm or less. Their complex interiors as observed with SEM (Scanning Electron Microscopy) and X-ray CT (computed tomography scanning), exhibit high internal surface areas. EDX (energy-dispersive X-ray spectroscopy) analysis reveals an increase in the Mg/Si ratio toward the chimney exteriors. Chemical garden analogue experiments produce similar Mg–silicate chimneys with porous internal structures, indicating that injection-precipitation experiments can be high-fidelity analogues for natural hydrothermal chimneys at the SHF. We conclude that SHF chimneys could have facilitated prebiotic reactions comparable to those proposed for clays and silica gels at putative Hadean to Eoarchean alkaline vents. Analysis of the fluid dynamics shows that these chimneys are intermediate in growth rate compared to faster black smokers though slower than those at Lost City. The SHF is proposed as a prebiotic alkaline vent analogue for basaltic terrains on the early Earth.
Net valence analysis of iris recognition technology-based FinTech
Authors: Al-Debei Mutaz M. , Hujran Omar , Al-Adwan Ahmad Samed 
Published: February 2024

AbstractIris recognition technology (IRT)-based authentication is a biometric financial technology (FinTech) application used to automate user recognition and verification. In addition to being a controversial technology with various facilitators and inhibitors, the adoption of IRT-based FinTech is driven by contextual factors, such as customer perceptions, deployed biometric technology, and financial transaction settings. Due to its controversial and contextual properties, analyzing IRT-based FinTech acceptance is challenging. This study uses a net valence framework to investigate the salient positive and negative factors influencing the intention to use IRT-based FinTech in automated teller machines (ATMs) in Jordan. This study is pertinent because there is a dearth of research on IRT-based FinTech in the relevant literature; most previous research has taken purely engineering and technical approaches. Furthermore, despite considerable investments by banks and other financial institutions in this FinTech, target user adoption is minimal, and only 6% of Jordan’s ATM transactions are currently IRT-enabled. This study employs mixed methods. In the first qualitative study, 17 Jordanian customers were interviewed regarding the benefits and risks of IRT-based FinTech in ATMs. Content analyses determined the most important concepts or themes. The advantages include financial security, convenience, and FinTech-enabled hygiene, whereas the concerns include performance, financial, privacy, and physical risks. The research model is constructed based on the qualitative study and theoretical underpinnings, wherein 631 Jordanian bank customers with active ATM accounts were surveyed to validate the research model. The findings indicate that IRT-based FinTech usage in ATMs is proportional to its perceived value. In descending order of effect, financial security, FinTech-enabled hygiene, and convenience benefits positively impact perceived value. Privacy, financial, and physical risks have negative impacts on perceived value, whereas performance risk has no effect. This study contributes to the relatively untapped domain of biometric technology in information systems, with important theoretical and practical implications.
The environmental impact of energy consumption and carbon emissions in radiology departments: a systematic review
Authors: Roletto Andrea , Zanardo Moreno , Bonfitto Giuseppe Roberto , Catania Diego , Sardanelli Francesco , Zanoni Simone 
Published: February 2024

Abstract
Objectives
Energy consumption and carbon emissions from medical equipment like CT/MRI scanners and workstations contribute to the environmental impact of healthcare facilities. The aim of this systematic review was to identify all strategies to reduce energy use and carbon emissions in radiology.

Methods
In June 2023, a systematic review (Medline/Embase/Web of Science) was performed to search original articles on environmental sustainability in radiology. The extracted data include environmental sustainability topics (e.g., energy consumption, carbon footprint) and radiological devices involved. Sustainable actions and environmental impact in radiology settings were analyzed. Study quality was assessed using the QualSyst tool.

Results
From 918 retrieved articles, 16 met the inclusion criteria. Among them, main topics were energy consumption (10/16, 62.5%), life-cycle assessment (4/16, 25.0%), and carbon footprint (2/16, 12.5%). Eleven studies reported that 40–91% of the energy consumed by radiological devices can be defined as “nonproductive” (devices “on” but not working). Turning-off devices during idle periods 9/16 (56.2%) and implementing workflow informatic tools (2/16, 12.5%) were the sustainable actions identified. Energy-saving strategies were reported in 8/16 articles (50%), estimating annual savings of thousand kilowatt-hours (14,180–171,000 kWh). Cost-savings were identified in 7/16 (43.7%) articles, ranging from US $9,225 to 14,328 per device. Study quality was over or equal the 80% of high-quality level in 14/16 (87.5%) articles.

Conclusion
Energy consumption and environmental sustainability in radiology received attention in literature. Sustainable actions include turning-off radiological devices during idle periods, favoring the most energy-efficient imaging devices, and educating radiological staff on energy-saving practices, without compromising service quality.

Relevance statement
A non-negligible number of articles — mainly coming from North America and Europe — highlighted the need for energy-saving strategies, attention to equipment life-cycle assessment, and carbon footprint reduction in radiology, with a potential for cost-saving outcome.

Key points
• Energy consumption and environmental sustainability in radiology received attention in the literature (16 articles published from 2010 to 2023).
• A substantial portion (40–91%) of the energy consumed by radiological devices was classified as “non-productive” (devices “on” but not working).
• Sustainable action such as shutting down devices during idle periods was identified, with potential annual energy savings ranging from 14,180 to 171,000 kWh.

Graphical Abstract
Repeat drug-coated balloon angioplasty for femoropopliteal lesions: 12-month results from a retrospective observational study
Authors: Haraguchi Takuya , Tsujimoto Masanaga , Kashima Yoshifumi , Sato Katsuhiko , Fujita Tsutomu 
Published: February 2024

Abstract
Background
The clinical implications of restenosis after drug-coated balloon (DCB) treatment remain unclear. We compared the clinical outcomes between DCB angioplasty for restenosis and de novo femoropopliteal artery lesions. This single-center retrospective study included 571 patients (737 limbs) who underwent either repeat (54 patients, 64 limbs) or de novo DCB (517 patients, 673 limbs) without bailout stenting. After propensity score matching, 49 matched pairs were analyzed. The primary endpoint was the 1-year primary patency, with secondary endpoints including the freedom from target lesion revascularization (TLR), major adverse limb events (MALE), and early restenosis. Predictors of restenosis were identified using multivariable Cox regression analysis.

Results
The repeat-DCB group displayed significantly lower rates of 1-year primary patency and freedom from TLR compared to those of the de novo-DCB group (50.1% vs. 77.4%, p = 0.029 and 54.9% vs. 83.6%, p = 0.0.44, respectively). No significant differences were observed in early restenosis or MALE (10.7% vs. 5.9%, p = 0.455 and 48.3% vs. 73.4%, p = 0.055, respectively). Restenosis after DCB angioplasty was associated with repeat DCB (hazard ratio [HR], 5.13; 95% confidence interval [CI], 1.43–18.4; p = 0.012) and small vessel size of < 4.5 mm (HR, 6.25; 95% CI, 1.17–33.4; p = 0.032). Furthermore, restenosis after repeat DCB angioplasty was associated with the Peripheral Artery Calcification Scoring System (PACSS) grade 4 (HR, 4.20; 95% CI, 1.08–16.3; p = 0.038), small vessel size of < 4.5 mm (HR, 9.44; 95% CI, 1.21–73.7; p = 0.032), and intravascular ultrasound (IVUS) use (HR, 0.05; 95% CI, 0.01–0.44; p = 0.007).

Conclusions
The 1-year primary patency rate following repeat DCB angioplasty for femoropopliteal lesions was notably lower than that of DCB treatment for de novo lesions. Repeat DCB strategy was associated with an increased risk of patency loss. Regarding repeat restenosis after DCB treatments, PACSS grade 4 calcification and small vessel diameter of < 4.5 mm were associated with an increased risk of restenosis, whereas IVUS use correlated with a decreased risk of restenosis.
Probabilistic forecast of electric vehicle charging demand: analysis of different aggregation levels and energy procurement
Authors: Ostermann Adrian , Haug Theodor 
Published: February 2024

AbstractElectric vehicles (EVs) are expected to be vital in transitioning to a low-carbon energy system. However, integrating EVs into the power grid poses significant challenges for grid operators and energy suppliers, especially regarding the uncertainty and variability of EV charging demand. Accurate forecasting of EV charging demand is essential for optimal power system integration, yet previous studies have often only considered point predictions that are inadequate for risk assessment. Therefore, this paper compares different probabilistic forecasting models for the short-term prediction of EV charging demand at various aggregation levels, using a large and novel dataset of over 350,000 charging processes at more than 500 locations across Germany. The performance of both machine learning and deep learning methods is evaluated against a naïve benchmark model, and the impact of data availability on the forecasting models is investigated. Further, the paper examines the effects of forecast accuracy on energy procurement, which has so far received minor attention in the literature. The results show that machine learning methods such as Ada Boosting and Random Forest yield robust results with a normalized root mean square error of 0.42 and 0.41 and a mean absolute scaled error of 0.36 and 0.34 at the highest aggregation level. Furthermore, the results show the influence of different site compositions on the forecast quality and how many charging points are likely to yield a robust forecast. Energy and fleet managers can use the described method to reliably predict the required energy quantities for fleets of sufficient size and procure them at low risk.