bluuebunny/crossref_metadata_2025_split huggingface dataset:
Digging deeper: microbial communities in subsoil are strongly promoted by trees in temperate agroforestry systems
Authors: Beule Lukas , Guerra Victor , Lehtsaar Ena , Vaupel Anna 
Published: July 2022

Abstract
Aims
Temperate alley-cropping agroforestry systems maintain agricultural production while offering several environmental benefits. Central benefits of agroforestry systems such as the ‘safety-net’-role of the trees for leached nutrients are mainly due to processes occurring below the soil surface: the subsoil. Microorganisms in the subsoil may play a key role in the ‘safety-net’-function as they can improve the capturing and uptake of nutrients by the trees. Systematic investigations of microbial communities in temperate agroforestry systems, however, are restricted to topsoil.

Methods
We quantified bacteria, fungi, and functional groups of microorganisms in the topsoil and subsoil of two alley-cropping systems using real-time PCR. Topsoil and subsoil samples were collected in the tree rows and at multiple distances from the trees within the crop rows of the agroforestry systems as well as at an adjacent monoculture cropland.

Results
Microbial population size decreased with soil depth likely due to limited resource availability in subsoil. Tree rows in agroforestry systems not only promote soil microbial populations in both the topsoil and subsoil but the promotion also extends gradually into the crop rows of the systems. The promotion of microorganisms through trees is stronger in subsoil than topsoil, pointing at more intense resource scarcity in the subsoil than topsoil.

Conclusions
We propose that tree root-derived resources and root litter, which are scarce in agricultural subsoils, triggered the strong positive response of the subsoil community to the trees. Finally, we provide initial evidence that subsoil microorganisms contribute to the ‘safety-net’-role of the trees in agroforestry systems.
Spatiotemporally variable incident light, leaf photosynthesis, and yield across a greenhouse: fine-scale hemispherical photography and a photosynthesis model
Authors: Kimura Kensuke , Yasutake Daisuke , Koikawa Kota , Kitano Masaharu 
Published: July 2022

AbstractAlthough greenhouse agriculture can generate high crop yields, they vary due to spatiotemporal differences in incident light and photosynthesis. To elucidate these dynamics, multipoint analysis of hemispheric images and a photosynthesis model were used to visualize the spatiotemporal distribution of photosynthetic photon flux density (PPFD) and leaf photosynthetic rate (A) and compared these with strawberry fruit yield in a greenhouse. This method enabled successful estimation of spatiotemporal variability in PPFD and A with relative root mean square errors of 4.4% and 11.0%, respectively. PPFD, captured at ca. 2 m resolution, varied diurnally and seasonally based on sun position and external light intensity. A showed less spatial variability, because it is reduced by physical and physiological mechanisms in the leaves at excessive leaf temperatures and becomes saturated at high PPFD. Yield spatial variability was better explained by A than by PPFD. The association between A and yield weakened over the cultivation period (R2 declined from 46% in winter to 12% in spring), thus suggesting that, over the cultivation period, factors such as photoassimilate availability replaced A as the primary limiting factor. The proposed method can be directly applied to other types of greenhouses, and the findings may facilitate spatiotemporal optimization in crop production, improving precision greenhouse agriculture.
An Inlet Computation Zone Optimization for EHL Line Contacts
Authors: Higashitani Yuko , Kawabata Sanemasa , Björling Marcus , Almqvist Andreas 
Published: July 2022

AbstractMost EHL numerical calculation methods considering both starved and flooded conditions, employ a fixed multiple of the Hertzian radius for the normalization of the computational domain. These methods are often used to investigate the influence of the lubricant supply on friction etc., but the solutions obtained might be numerically starved. The present numerical calculation method utilizes an optimized normalization of the computational domain to ensure that the solutions obtained are not numerically starved. With this normalization method, the computational domain can be appropriately meshed, regardless of the variability in the inlet length due to changes in the operating conditions. This method can, therefore, be used to obtain accurate EHL film thickness and pressure data over a wide range of operating conditions.
Short-term outcomes after transplantation of deceased donor kidneys with acute kidney injury: a retrospective analysis of a multicenter cohort of marginal donor kidneys with post-explantation biopsies
Authors: Scurt Florian G. , Ernst Angela , Wassermann Tamara , Hammoud Ben , Mertens Peter R. , Schwarz Anke , Becker Jan U. , Chatzikyrkou Christos 
Published: July 2022

Abstract
Background
Deceased donor kidneys with acute kidney injury (AKI) are often discarded because of concerns about inferior transplant outcomes. A means of grading the quality of such kidneys is the performance of procurement biopsies.

Methods
This is a retrospective study of 221 brain death donors with marginal kidneys transplanted in 223 recipients in Germany. Marginal kidneys were defined as kidneys with procurement biopsies done exceptionally to assess suitability for transplantation in otherwise potentially discarded organs. The impact of deceased donor AKI on patient survival and death-censored graft survival at 1, 3 and 5 years and graft function at 1 and 3 years after transplantation was investigated.

Results
Recipients of kidneys with stage 3 AKI had a greater incidence of delayed graft function [DGF; ORStage 1: 1.435 (95% CI 0.438–0.702), ORStage 2: 2.463 (95% CI 0.656–9.245), ORStage 3: 4.784 (95% CI 1.421–16.101)] but a similar graft and patient survival compared to recipients of donors without AKI and with AKI stage 1 and 2 as well. The coexistence of recipient DGF and donor AKI was associated with the lowest graft survival and function rates.

Conclusion
The transplantation of deceased donor marginal kidneys with AKI confers a higher risk for DGF but is associated with acceptable graft and patient outcomes, which do not differ in comparison with marginal donor kidneys without AKI. Graft prognosis is especially poor if donor AKI and recipient DGF concur. Donor AKI was a risk factor independent of the histological lesions of procurement biopsies.
Pairwise Alignment of Archaeological Fragments Through Morphological Characterization of Fracture Surfaces
Authors: ElNaghy Hanan , Dorst Leo 
Published: July 2022

AbstractWe design a computational method to align pairs of counter-fitting fracture surfaces of digitized archaeological artefacts. The challenge is to achieve an accurate fit, even though the data is inherently lacking material through abrasion, missing geometry of the counterparts, and may have been acquired by different scanning practices. We propose to use the non-linear complementarity-preserving properties of Mathematical Morphology to guide the pairwise fitting in a manner inherently insensitive to these aspects. In our approach, the fracture surface is tightly bounded by a concise set of characteristic multi-local morphological features. Such features and their descriptors are computed by analysing the discrete distance transform and its causal scale-space information. This compact morphological representation provides the information required for accurately aligning the fracture surfaces through applying a RANSAC-based algorithm incorporating weighted Procrustes to the morphological features, followed by ICP on morphologically selected ‘flank’ regions. We propose new criteria for evaluating the resulting pairwise alignment quality, taking into consideration both penetration and gap regions. Careful quantitative evaluation on real terracotta fragments confirms the accuracy of our method under the expected archaeological noise. We show that our morphological method outperforms a recent linear pairwise alignment method and briefly discuss our limitations and the effects of variations in digitization and abrasion on our proposed alignment technique.
Impact of economic policy uncertainty, energy intensity, technological innovation and R&D on CO2 emissions: evidence from a panel of 18 developed economies
Authors: Vitenu-Sackey Prince Asare , Acheampong Theophilus 
Published: July 2022

AbstractThis study examines the impact of economic policy uncertainty (EPU) and ecological innovation on carbon (CO2) emissions in a panel of 18 developed countries from 2005 to 2018 using second-generation time-series panel data techniques. We use three robust long-run estimators, namely two-stage least squares (2SLS), panel generalised method of moments (GMM) and generalised least squares (GLS), to resolve heterogeneity, endogeneity and simultaneity in the panels. We further performed causality tests to ascertain the direction of causality between the variables. Our estimations suggest three innovative findings. First, economic growth contributes significantly and positively to CO2 emissions; however, this happens at an optimal level of growth after which carbon emission reduces, indicating that our sample exhibits an inverted U-shaped environmental Kuznets curve (EKC) relationship. Second, the impact of EPU on CO2 emissions is diverse: high levels of EPU have a significant influence on CO2 emissions only in high-polluting countries but not in low-polluting ones. Thirdly, research and development (R&D), foreign direct investment (FDI), urbanisation and renewable energy (RE) usage were also found to have varying effects on CO2 emissions. These findings highlight the heterogeneous relationship between carbon emissions and economic indicators even in advanced economies, as the pollution haven hypothesis (PHH) holds true in high-pollution countries while the pollution halo effect holds for low-pollution ones. A key policy implication of this work is that the quest to mitigate emissions should not be a one-size-fits-all approach because not every country’s urbanisation rate, FDI inflows, R&D and renewable energy consumption directly affect CO2 emissions in the face of economic policy uncertainties.
Inter- and intra-chromosomal modulators of the APOE ɛ2 and ɛ4 effects on the Alzheimer’s disease risk
Authors: Nazarian Alireza , Philipp Ian , Culminskaya Irina , He Liang , Kulminski Alexander M. 
Published: July 2022

AbstractThe mechanisms of incomplete penetrance of risk-modifying impacts of apolipoprotein E (APOE) ε2 and ε4 alleles on Alzheimer’s disease (AD) have not been fully understood. We performed genome-wide analysis of differences in linkage disequilibrium (LD) patterns between 6,136 AD-affected and 10,555 AD-unaffected subjects from five independent studies to explore whether the association of theAPOEε2 allele (encoded by rs7412 polymorphism) and ε4 allele (encoded by rs429358 polymorphism) with AD was modulated by autosomal polymorphisms. The LD analysis identified 24 (mostly inter-chromosomal) and 57 (primarily intra-chromosomal) autosomal polymorphisms with significant differences in LD with either rs7412 or rs429358, respectively, between AD-affected and AD-unaffected subjects, indicating their potential modulatory roles. Our Cox regression analysis showed that minor alleles of four inter-chromosomal and ten intra-chromosomal polymorphisms exerted significant modulating effects on the ε2- and ε4-associated AD risks, respectively, and identified ε2-independent (rs2884183 polymorphism, 11q22.3) and ε4-independent (rs483082 polymorphism, 19q13.32) associations with AD. Our functional analysis highlighted ε2- and/or ε4-linked processes affecting the lipid and lipoprotein metabolism and cell junction organization which may contribute to AD pathogenesis. These findings provide insights into the ε2- and ε4-associated mechanisms of AD pathogenesis, underlying their incomplete penetrance.
Toward a diagnostic CART model for Ischemic heart disease and idiopathic dilated cardiomyopathy based on heart rate total variability
Authors: Accardo Agostino , Restivo Luca , Ajčević Miloš , Miladinović Aleksandar , Iscra Katerina , Silveri Giulia , Merlo Marco , Sinagra Gianfranco 
Published: July 2022

AbstractDiagnosis of etiology in early-stage ischemic heart disease (IHD) and dilated cardiomyopathy (DCM) patients may be challenging. We aimed at investigating, by means of classification and regression tree (CART) modeling, the predictive power of heart rate variability (HRV) features together with clinical parameters to support the diagnosis in the early stage of IHD and DCM. The study included 263 IHD and 181 DCM patients, as well as 689 healthy subjects. A 24 h Holter monitoring was used and linear and non-linear HRV parameters were extracted considering both normal and ectopic beats (heart rate total variability signal). We used a CART algorithm to produce classification models based on HRV together with relevant clinical (age, sex, and left ventricular ejection fraction, LVEF) features. Among HRV parameters, MeanRR, SDNN, pNN50, LF, LF/HF, LFn, FD, Beta exp were selected by the CART algorithm and included in the produced models. The model based on pNN50, FD, sex, age, and LVEF features presented the highest accuracy (73.3%). The proposed approach based on HRV parameters, age, sex, and LVEF features highlighted the possibility to produce clinically interpretable models capable to differentiate IHD, DCM, and healthy subjects with accuracy which is clinically relevant in first steps of the IHD and DCM diagnostic process.
Graphical abstract
Image De-occlusion via Event-enhanced Multi-modal Fusion Hybrid Network
Authors: Li Si-Qi , Gao Yue , Dai Qiong-Hai 
Published: July 2022

AbstractSeeing through dense occlusions and reconstructing scene images is an important but challenging task. Traditional frame-based image de-occlusion methods may lead to fatal errors when facing extremely dense occlusions due to the lack of valid information available from the limited input occluded frames. Event cameras are bio-inspired vision sensors that record the brightness changes at each pixel asynchronously with high temporal resolution. However, synthesizing images solely from event streams is ill-posed since only the brightness changes are recorded in the event stream, and the initial brightness is unknown. In this paper, we propose an event-enhanced multi-modal fusion hybrid network for image de-occlusion, which uses event streams to provide complete scene information and frames to provide color and texture information. An event stream encoder based on the spiking neural network (SNN) is proposed to encode and denoise the event stream efficiently. A comparison loss is proposed to generate clearer results. Experimental results on a large-scale event-based and frame-based image de-occlusion dataset demonstrate that our proposed method achieves state-of-the-art performance.
RoCS: Robotic Curriculum for young Surgeons
Authors: Stockheim Jessica , Perrakis Aristotelis , Sabel Bernhard A. , Waschipky Robert , Croner Roland S. 
Published: July 2022

AbstractRobotic-assisted procedures gain increasing acceptance for daily surgical routine. However, structured training programs are designed for surgeons with high expertise. Hence, a comprehensive training curriculum was established to ensure a basic competence in robotic abdominal surgery for young surgeons during their residency. The aim of the current work is to propose a feasible and effective training concept. The development process of this training curriculum is based on a comprehensive literature review which led to the concept of “robotic curriculum for young surgeons” (RoCS). It was implemented in the daily routine of a German university hospital starting in 2020. The robotic assessment questionnaire (RAQ) was used for electronic data collection. After the initial phase adjustments, it led to an improvement of the initial version of the curriculum. RoCS is a multimodal training program containing basic training through assistance at the operation table during robotic-assisted operations and basic console training. Key elements are the robotic team time-out (rTTO), perioperative process standardization including feasible personnel scheduling and useful procedure clustering into organ systems, procedural steps and procedural step complexity. Evaluation of standardized communication, performance assessment, patient factors and individual overall workload using NASA Task Load Index is realizable. Flexibility and adaptability to internal organization processes of surgical departments are the main advantages of the concept. RoCS is a strong training tool to meet the specific needs of young surgeons and evaluate their learning success of robotic procedural training. Furthermore, comparison within the different robotic systems should be considered. Further studies are needed to validate a multicenter concept design.
Effect of rhizosphere bacteria on antioxidant enzymes and some biochemical characteristics of Medicago sativa L. subjected to herbicide stress
Authors: Motamedi Marzieh , Zahedi Morteza , Karimmojeni Hassan , Motamedi Hossein , Mastinu Andrea 
Published: July 2022

AbstractAbiotic stresses such as herbicides can affect plant growth and yield. Using herbicide-resistant plant growth-promoting bacteria is a new approach to mitigate these side effects. This study was conducted to evaluate the effect of three native plant growth-promoting bacteria isolated from the Medicago sativa rhizosphere, including Serratia rubidaea (A) and Pseudomonas putida (B), Serratia sp. (C) plus Synorhizobium meliloti (R) and their combinations (AB, AC, BC, ABC, AR, BR, CR, ABR, ACR, BCR, and ABCR) on microbial population, plant biomass, antioxidant enzymes (CAT, APX, and GPX) activities, and hydrogen peroxide and malondialdehyde contents at the presence and absence of imazethapyr herbicide. The results indicated that herbicide application decreased plant biomass but increased microbial population, antioxidant enzymes activities, and the concentrations of hydrogen peroxide and malondialdehyde of all inoculated and non-inoculated plants. Bacterial inoculation in most cases increased microbial population, plant biomass, and antioxidant activities. These increases were more evident under herbicide application. The highest increase in these attributes was achieved by AB, AR, and ABR inoculums in the presence and absence of the herbicide. The microbial population, plant biomass and antioxidant activities were decreased under BC, CR, BCR, and ABCR inoculations. It can be concluded that in addition to growth promotion, these bacteria increase resistance against herbicide stress by controlling free-radical induced oxidative stress and lipid peroxidation through antioxidant enzymes. These findings create new visions in biofertilizer preparation for reducing environmental stresses.
Comparison of the characteristics, morbidity and mortality of COVID-19 between first and second/third wave in a hospital setting in Lombardy: a retrospective cohort study
Authors: Leidi Francesca , Boari Gianluca Edoardo Mario , Scarano Ottavio , Mangili Benedetta , Gorla Giulia , Corbani Andrea , Accordini Beatrice , Napoli Federico , Ghidelli Chiara , Archenti Giulia , Turini Daniele , Saottini Michele , Guarinoni Vittoria , Ferrari-Toninelli Giulia , Manzoni Francesca , Bonetti Silvia , Chiarini Giulia , Malerba Paolo , Braglia-Orlandini Federico , Bianco Gianluca , Faustini Cristina , Agabiti-Rosei Claudia , De Ciuceis Carolina , Rizzoni Damiano 
Published: July 2022

AbstractCoronavirus disease 2019 (COVID-19) represents a major health problem in terms of deaths and long-term sequelae. We conducted a retrospective cohort study at Montichiari Hospital (Brescia, Italy) to better understand the determinants of outcome in two different COVID-19 outbreaks. A total of 634 unvaccinated patients admitted from local emergency room to the Internal Medicine ward with a confirmed diagnosis of SARS-CoV-2 infection and a moderate-to-severe COVID-19 were included in the study. A group of 260 consecutive patients during SARS-CoV-2 first wave (from February to May 2020) and 374 consecutive patients during SARS-CoV-2 2nd/3rd wave (from October 2020 to May 2021) were considered. Demographic data were not significantly different between waves, except a lower prevalence of female sex during first wave. Mortality was significantly higher during the 1st wave than in the following periods (24.2% vs. 11%; p < 0.001). Time from symptoms onset to hospital admission was longer during first wave (8 ± 6 vs. 6 ± 4 days; p < 0.001), while in-hospital staying was significantly shorter (10 ± 14 vs. 15 ± 11 days; p < 0.001). Other significant differences were a larger use of corticosteroids and low-molecular weight heparin as well less antibiotic prescription during the second wave. Respiratory, bio-humoral and X-ray scores were significantly poorer at the time of admission in first-wave patients. After a multivariate regression analysis, C-reactive protein and procalcitonin values, % fraction of inspired oxygen on admission to the Internal Medicine ward and length of hospital stay and duration of symptoms were the strongest predictors of outcome. Concomitant anti-hypertensive treatment (including ACE-inhibitors and angiotensin-receptor blockers) did not affect the outcome. In conclusion, our data suggest that earlier diagnosis, timely hospital admission and rational use of the therapeutic options reduced the systemic inflammatory response and were associated to a better outcome during the 2nd/3rd wave.
Indoor air quality analysis in naturally ventilated university training laboratories: a health risk assessment
Authors: Seseña Susana , Rodríguez Ana M. , Palop M. Llanos 
Published: July 2022

AbstractThe indoor air quality (IAQ) of eleven naturally ventilated training laboratories was analysed to evaluate the health risk to occupants. IAQ evaluation included analysis of physical (temperature (T) and relative humidity (RH)), chemical (CO2, CO, O3, total volatile organic compounds (TVOC), and particulate matter (PM)) and microbiological (fungi and bacteria) pollutants. Monitoring was carried out in labs used for teaching different academic disciplines (biology, chemical, ecology, and computers) during two periods of the academic year. Ventilation rates (VR), air change per hour (ACH) in every lab, and the hazard quotients for each of the chemical pollutants and the accumulated (HQ and HI) were calculated. Environmental comfort was not fully satisfactory considering the RH and CO2 values, especially during hours with higher occupancy. Coarse particles and bacteria were generated indoor related to human activity. At chemical and biological laboratories, TVOC concentrations were sometimes above the recommended value, and all the labs presented VR below the European guideline’s recommendations. Results from this study show natural ventilation is not enough to get an adequate IAQ, although no significant non-carcinogenic risk was estimated. However, installation of complementary ventilation systems would be advisable to avoid health risk by acute short-term exposure.
Graphical abstract