bluuebunny/crossref_metadata_2025_split huggingface dataset:
Mechanisms Controlling Carbon Sinks in Semi‐Arid Mountain Ecosystems
Authors: Guo Weichao , Safeeq Mohammad , Liu Hongyan , Wu Xiuchen , Cui Guotao , Ma Qin , Goulden Michael L. , Lindeskog Mats , Bales Roger C. 
Published: March 2022

AbstractFeedbacks between the intertwined water and carbon cycles in semi‐arid mountain ecosystems can introduce large uncertainties into projections of carbon storage. In this study, we sought to understand the influence of key mechanisms on carbon balances, focusing on an ecosystem whose complex terrain and large interannual variability in precipitation adds to its vulnerability to warming. We applied a dynamic vegetation‐ecosystem model (Lund‐Potsdam‐Jena General Ecosystem Simulator) to simulate water‐carbon interactions in the 104,512 km2 Mediterranean‐climate ecosystems of California's Sierra Nevada for 1950–2099. Our 48 scenarios include a combination of carbon dioxide (CO2) increase, air temperature change, and varying plant rooting depths. We found that with warming (+2 and +5°C), water limitations on growth and enhanced soil respiration reduce carbon storage; however, CO2 fertilization and associated enhanced water‐use efficiency offset this loss. Using the 4 km model resolution to capture steep mountain precipitation gradients, plus accounting for the several meters of actual root‐accessible water storage in the region, were also important. With warming accompanied by CO2 fertilization our projections show that the Sierra Nevada sequestering at least 200 Tg (2 kg m−2) carbon, versus carbon loss with warming alone. The increase reflects coniferous forests growing at high elevations, and some increase in broadleaved forests at low‐to‐intermediate elevations. Importantly, uncertainty in fire disturbance could shift our finding from carbon sink to source. The improved mechanistic understanding of these feedbacks can advance modeling of carbon‐water interactions in mountain‐ecosystem under a warmer and potentially drier climate.
Quantifying the Impact of Bedrock Topography Uncertainty in Pine Island Glacier Projections for This Century
Authors: Wernecke Andreas , Edwards Tamsin L. , Holden Philip B. , Edwards Neil R. , Cornford Stephen L. 
Published: March 2022

AbstractThe predicted Antarctic contribution to global‐mean sea‐level rise is one of the most uncertain among all major sources. Partly this is because of instability mechanisms of the ice flow over deep basins. Errors in bedrock topography can substantially impact the projected resilience of glaciers against such instabilities. Here we analyze the Pine Island Glacier topography to derive a statistical model representation. Our model allows for inhomogeneous and spatially dependent uncertainties and avoids unnecessary smoothing from spatial averaging or interpolation. A set of topography realizations is generated representing our best estimate of the topographic uncertainty in ice sheet model simulations. The bedrock uncertainty alone creates a 5%–25% uncertainty in the predicted sea level rise contribution at year 2100, depending on friction law and climate forcing. Pine Island Glacier simulations on this new set are consistent with simulations on the BedMachine reference topography but diverge from Bedmap2 simulations.
Configuration of Magnetotail Current Sheet Prior to Magnetic Reconnection Onset
Authors: An Xin , Artemyev Anton , Angelopoulos Vassilis , Runov Andrei , Lu San , Pritchett Philip 
Published: March 2022

AbstractThe magnetotail current sheet configuration determines magnetic reconnection properties that control the substorm onset, one of the most energetic phenomena in the Earth’s magnetosphere. The quiet‐time current sheet is often approximated as a two‐dimensional (2D) magnetic field configuration balanced by isotropic plasma pressure gradients. However, reconnection onset is preceded by the current sheet thinning and the formation of a nearly one‐dimensional (1D) magnetic field configuration. In this study, using particle‐in‐cell simulations, we investigate the force balance of such thin current sheets when they are driven by plasma inflow. We demonstrate that the magnetic field configuration transitions from 2D to 1D thanks to the formation of plasma pressure nongyrotropy and reveal its origin in the nongyrotropic terms of the ion distributions. We show that substorm onset may be controlled by the instability and dynamics of such nongyrotropic current sheets, having properties much different from the most commonly investigated 2D isotropic configuration.
Impulsive Noise Suppressing Method in Power Line Communication System Using Sparse Iterative Covariance Estimation
Authors: Liu Zaihui , Li Youming , Shi Shoudong 
Published: March 2022

AbstractPower line communication (PLC) is severely affected by impulsive noise, especially asynchronous impulsive noise with high power spectral density and short duration. This paper presents an asynchronous impulsive noise suppression method in PLC system. Based on the component of the asynchronous impulsive noise and the background noise extracted from the received signal by using a null subcarrier matrix, a sparse iterative covariance estimation method is proposed. A optimization problem for estimating impulsive noise power is formed based on a minimum covariance matrix fitting criterion, and the impulsive noise power is then obtained by an iterative algorithm. After that, the impulsive noise is estimated by using the linear minimum mean square estimate method and subtracted from the received signal. Finally, simulation results show that the proposed method can achieve better performance in terms of bit error rate, and has lower computational complexity.
Self-supervised optimization of random material microstructures in the small-data regime
Authors: Rixner Maximilian , Koutsourelakis Phaedon-Stelios 
Published: March 2022

AbstractWhile the forward and backward modeling of the process-structure-property chain has received a lot of attention from the materials’ community, fewer efforts have taken into consideration uncertainties. Those arise from a multitude of sources and their quantification and integration in the inversion process are essential in meeting the materials design objectives. The first contribution of this paper is a flexible, fully probabilistic formulation of materials’ optimization problems that accounts for the uncertainty in the process-structure and structure-property linkages and enables the identification of optimal, high-dimensional, process parameters. We employ a probabilistic, data-driven surrogate for the structure-property link which expedites computations and enables handling of non-differential objectives. We couple this with a problem-tailored active learning strategy, i.e., a self-supervised selection of training data, which significantly improves accuracy while reducing the number of expensive model simulations. We demonstrate its efficacy in optimizing the mechanical and thermal properties of two-phase, random media but envision that its applicability encompasses a wide variety of microstructure-sensitive design problems.
Feeding behavior and activity levels are associated with recovery status in dairy calves treated with antimicrobials for Bovine Respiratory Disease
Authors: Cantor M. C. , Renaud David L. , Neave Heather W. , Costa Joao H. C. 
Published: March 2022

AbstractCalves with Bovine Respiratory Disease (BRD) have different feeding behavior and activity levels prior to BRD diagnosis when compared to healthy calves, but it is unknown if calves who relapse from their initial BRD diagnosis are behaviorally different from calves who recover. Using precision technologies, we aimed to identify associations of feeding behavior and activity with recovery status in dairy calves (recovered or relapsed) over the 10 days after first antimicrobial treatment for BRD. Dairy calves were health scored daily for a BRD bout (using a standard respiratory scoring system and lung ultrasonography) and received antimicrobial therapy (enrofloxacin) on day 0 of initial BRD diagnosis; 10–14 days later, recovery status was scored as either recovered or relapsed (n = 19 each). Feeding behaviors and activity were monitored using automated feeders and pedometers. Over the 10 days post-treatment, recovered calves showed improvements in starter intake and were generally more active, while relapsed calves showed sickness behaviors, including depressed feed intake, and longer lying times. These results suggest there is a new potential for precision technology devices on farms in evaluating recovery status of dairy calves that are recently treated for BRD; there is opportunity to automatically identify relapsing calves before re-emergence of clinical disease.
A novel approach for reliable qualitative and quantitative prey spectra identification of carnivorous plants combining DNA metabarcoding and macro photography
Authors: Krueger Thilo , Cross Adam T. , Hübner Jeremy , Morinière Jérôme , Hausmann Axel , Fleischmann Andreas 
Published: March 2022

AbstractPrey spectra (the number and composition of captured arthropods) represent a crucial aspect of carnivorous plant ecology, yet remain poorly studied. Traditional morphology-based approaches for prey identification are time-intensive, require specialists with considerable knowledge of arthropod taxonomy, and are hampered by high numbers of unidentifiable (i.e., heavily digested) prey items. We examined prey spectra of three species of closely-related annual Drosera (Droseraceae, sundews) from tropical northern Australia using a novel DNA metabarcoding approach with in-situ macro photography as a plausibility control and to facilitate prey quantity estimations. This new method facilitated accurate analyses of carnivorous plant prey spectra (even of heavily digested prey lacking characteristic morphological features) at a taxonomic resolution and level of completeness far exceeding morphology-based methods and approaching the 100% mark at arthropod order level. Although the three studied species exhibited significant differences in detected prey spectra, little prey specialisation was observed and habitat or plant population density variations were likely the main drivers of prey spectra dissimilarity.
An end-to-end computer vision methodology for quantitative metallography
Authors: Rusanovsky Matan , Beeri Ofer , Oren Gal 
Published: March 2022

AbstractMetallography is crucial for a proper assessment of material properties. It mainly involves investigating the spatial distribution of grains and the occurrence and characteristics of inclusions or precipitates. This work presents a holistic few-shot artificial intelligence model for Quantitative Metallography, including Anomaly Detection, that automatically quantifies the degree of the anomaly of impurities in alloys. We suggest the following examination process: (1) deep semantic segmentation is performed on the inclusions (based on a suitable metallographic dataset of alloys and corresponding tags of inclusions), producing inclusions masks that are saved into a separated dataset. (2) Deep image inpainting is performed to fill the removed inclusions parts, resulting in ‘clean’ metallographic images, which contain the background of grains. (3) Grains’ boundaries are marked using deep semantic segmentation (based on another metallographic dataset of alloys), producing boundaries that are ready for further inspection on the distribution of grains’ size. (4) Deep anomaly detection and pattern recognition is performed on the inclusions masks to determine spatial, shape, and area anomaly detection of the inclusions. Finally, the end-to-end model recommends an expert on areas of interest for further examination. The physical result can re-tune the model according to the specific material at hand. Although the techniques presented here were developed for metallography analysis, most of them can be generalized to a broader set of microscopy problems that require automation. All source-codes as well as the datasets that were created for this work, are publicly available at https://github.com/Scientific-Computing-Lab-NRCN/MLography.
Design, synthesis and bioactive properties of a class of macrocycles with tunable functional groups and ring size
Authors: Thurakkal Liya , Nanjan Pandurangan , Porel Mintu 
Published: March 2022

AbstractThe design and synthesis of a versatile class of macrocycles with tunable functional groups and ring size are unfolded. Herein, a synthetic strategy is reported to furnish a new class of macrocycles in multi-gram scale in a two-step reaction. The total time taken for synthesizing a macrocycle is 1.5 h. Dithiocarbamates, an important functional group in biomedical and material sciences, is strategically incorporated in the macrocyclic backbone without metal for the first time. It is noteworthy that when state-of-the-art macrocycle synthesis is in millimolar concentration, this work employs the reaction in molar concentration (0.2–0.4 M). As proof-of-principle, a library of macrocycles was synthesized, varying the functional groups and ring size. The physicochemical properties of macrocycles revealed their druggable nature and are affirmed by protein (serum albumin) interaction study theoretically and experimentally. Diverse functional groups and ring sizes of macrocycles brought about twenty-five-fold difference in binding constant with the model protein.
Eye orbit effects on eyeball resonant frequencies and acoustic tonometer measurements
Authors: Shih Po-Jen , Wu Shao-Jie , Sung Ya-Hsing , Tung Yu-Ting , Chang Chia-Yu , Hatamie Shadie , Dai Zhi-Xuan 
Published: March 2022

AbstractThe eye orbit has mechanical and acoustic characteristics that determine resonant frequencies and amplify acoustic signals in certain frequency ranges. These characteristics also interfere with the acoustic amplitudes and frequencies of eyeball when measured with an acoustic tonometer. A model in which a porcine eyeball was embedded in ultrasonic conductive gel in the orbit of a model skull was used to simulate an in vivo environment, and the acoustic responses of eyeballs were detected. The triggering source was a low-power acoustic speaker contacting the occipital bone, and the detector was a high-resolution microphone with a dish detecting the acoustic signals without contacting the cornea. Dozens of ex vivo porcine eyeballs were tested at various intraocular pressure levels to detect their resonant frequencies and acoustic amplitudes in their power spectra. We confirmed that the eyeballs’ resonant frequencies were proportional to intraocular pressure, but interference from orbit effects decreased the amplitudes in these resonant frequency ranges. However, we observed that the frequency amplitudes of eyeballs were correlated with intraocular pressure in other frequency ranges. We investigated eye orbit effects and demonstrated how they interfere with the eyeball’s resonant frequencies and frequency amplitudes. These results are useful for developing advanced acoustic tonometer.
COVID-19 in liver transplant recipients: incidence, hospitalization and outcome in an Italian prospective double-centre study
Authors: Guarino Maria , Cossiga Valentina , Loperto Ilaria , Esposito Ilaria , Ortolani Rosanna , Fiorentino Andrea , Pontillo Giuseppina , De Coppi Lucia , Cozza Valentina , Galeota Lanza Alfonso , Di Costanzo Giovanni Giuseppe , Picciotto Francesco Paolo , Morisco Filomena 
Published: March 2022

AbstractLiver transplant (LT) recipients are vulnerable to SARS-CoV-2-infection (COVID-19), due to immunosuppression and comorbidities. This study aimed to evaluate the impact of COVID-19 on LT recipients compared to general population in the Campania region. In this prospective double-centre study, we enrolled all consecutive adult LT recipients with confirmed SARS-CoV-2-infection. Data were collected at diagnosis of COVID-19 and during follow-up and compared with the regional population. Thirty LT recipients (3.28%) developed SARS-CoV-2-infection (76.66% male, median age 62.61 years). Sixteen (53.33%) were symptomatic. Common symptoms were fever, cough, fatigue, and anosmia. Twenty-five (83.33%) were outpatients, 5 (16.66%) required hospitalization (6.66% admitted to Intensive Care Unit, 6.62% developed Acute Respiratory Distress Syndrome and 6.66% died). Immunosuppressors were in 3 (10%) patients. Incidence rate of COVID-19 was similar between LT patients and general population (3.28% vs 4.37%, p = 0.142) with higher rate of symptoms in LT patients (53.33% vs 15.87%, p < 0.000). At univariate analysis, hospitalization and case fatality rates were higher in LT patients compared to general population (16.66% vs 4.54%, p = 0.001; and 6.66% vs 1.76%, p = 0.041, respectively). At multivariable logistic regression analysis, LT patients with COVID-19 were more frequently symptomatic (OR 5.447 [95% CI 2.437–12.177], p < 0.000), whereas hospitalization and death for COVID-19 were not significatively associated with LT condition (p = 0.724 and p = 0.462, respectively) and were comparable with general population. LT is not a risk factor for acquiring COVID-19. Nonetheless, LT patients are more frequently symptomatic, although comparable to the general population for hospitalization rate and mortality.
Variability and agreement of frailty measures and risk of falls, hospital admissions and mortality in TILDA
Authors: Kim Dani J. , Massa M. Sofia , Clarke Robert , Scarlett Siobhan , O’Halloran Aisling M. , Kenny Rose Anne , Bennett Derrick 
Published: March 2022

AbstractLittle is known about the within-person variability of different frailty instruments, their agreement over time, and whether use of repeat assessments could improve the strength of associations with adverse health outcomes. Repeat measurements recorded in 2010–2011 (Wave 1) and 2012 (Wave 2) from The Irish Longitudinal Study on Ageing (TILDA) were used to classify individuals with frailty using the frailty phenotype (FP) and frailty index (FI). Within-person variability and agreement of frailty classifications were assessed using ANOVA and kappa (K) statistics, respectively. Associations of each frailty measure (wave 1, wave 2, or mean of both waves) with risk of falls, hospitalisations and all-cause mortality were assessed using logistic regression. Among 7455 individuals (mean age 64.7 [SD 9.9] years), within-person SD was 0.664 units (95% CI 0.654–0.671) for FP and 2 health deficits (SD 0.050 [0.048–0.051]) for FI. Agreement of frailty was modest for both measures, but higher for FI (K 0.600 [0.584–0.615]) than FP (K 0.370 [0.348–0.401]). The odds ratios (ORs) for all-cause mortality were higher for frailty assessed using the mean of two versus single measurements for FI (ORs for mortality 3.5 [2.6–4.9] vs. 2.7 [1.9–3.4], respectively) and FP (ORs for mortality 6.9 [4.6–10.3] vs. 4.0 [2.8–5.635], respectively). Frailty scores based on single measurements had substantial within-person variability, but the agreement in classification of frailty was higher for FI than FP. Frailty assessed using the mean of two or more measurements recorded at separate visits was more strongly associated with adverse health outcomes than those recorded at a single visit.
Intensity changes of Indian Ocean dipole mode in a carbon dioxide removal scenario
Authors: An Soon-Il , Park Hyo-Jin , Kim Soong-Ki , Shin Jongsoo , Yeh Sang-Wook , Kug Jong-Seong 
Published: March 2022

AbstractThe Indian Ocean Dipole/Zonal mode (IOD) is an interannual phenomenon over the tropical Indian Ocean, causing a pronounced impact worldwide. Here, we investigate the mechanism of the change in IOD characteristics in a CO2 removal simulation for an earth system model (ESM). As the CO2 concentration increases, the intensity of IOD tends to increase, but at high CO2 concentrations, further increases decrease the IOD intensity. The minimum IOD amplitude was recorded during the early decrease in CO2. First, we developed a conceptual model for IOD that is composed of local air-sea coupled feedback, delayed ocean dynamics, El Niño impact, and noise forcing. Then, by adopting ESM results into this simple IOD model, we revealed that the local air–sea coupled feedback is a major factor for changing IOD amplitude, while El Niño does not exert a change in IOD amplitude. The local air–sea coupled feedback including thermocline feedback, wind-evaporation feedback, and Ekman feedback is strongly modified by the air–sea coupling strength during progression of a global warming. Consequently, under the higher CO2 concentrations, IOD amplitude is reduced due to the weakening of air-sea coupling over tropical Indian Ocean.
Smartphone applications for informal caregivers of chronically ill patients: a scoping review
Authors: Guessi Margarido Milena , Shah Amika , Seto Emily 
Published: March 2022

AbstractMobile-health applications can be used to deliver timely and personalized health information to family and friends of chronically ill adults living in the community. This scoping review aims to investigate the nature and extent of native smartphone applications for informal caregivers. Six databases were searched for articles on applications across ten chronic conditions, namely heart disease, stroke, cancer, chronic obstructive respiratory disease, asthma, diabetes, Alzheimer’s disease or other dementia, rheumatoid arthritis, hypertension, and mood or anxiety disorders. In total, 36 articles were included, encompassing 26 applications. Of these, smartphone applications were designed for use only by caregivers (n = 15), with a few applications also intended to be used with patients (n = 5), healthcare providers (n = 4), or all three roles (n = 2). Most applications targeted a single chronic condition (n = 25), with Alzheimer’s and other dementia being the most common (n = 18). Only one application was designed for management of multiple chronic conditions. Long-term evaluation methods are needed to continually assess the impact of applications on a range of process and health outcomes, such as usability, caregiver burden, and quality of life. Additional directions to advance native smartphone applications for caregivers are discussed, including personalization and expansion of eligibility criteria.
β-cell-specific deletion of PFKFB3 restores cell fitness competition and physiological replication under diabetogenic stress
Authors: Min Jie , Ma Feiyang , Seyran Berfin , Pellegrini Matteo , Greeff Oppel , Moncada Salvador , Tudzarova Slavica 
Published: March 2022

AbstractHIF1α and PFKFB3 play a critical role in the survival of damaged β-cells in type–2 diabetes while rendering β-cells non-responsive to glucose stimulation. To discriminate the role of PFKFB3 from HIF1α in vivo, we generated mice with conditional β-cell specific disruption of the Pfkfb3 gene on a human islet pancreatic polypeptide (hIAPP+/−) background and a high-fat diet (HFD) [PFKFB3βKO + diabetogenic stress (DS)]. PFKFB3 disruption in β-cells under DS led to selective purging of hIAPP-damaged β-cells and the disappearance of insulin- and glucagon positive bihormonal cells. PFKFB3 disruption induced a three-fold increase in β-cell replication as evidenced by minichromosome maintenance 2 protein (MCM2) expression. Unlike high-, lower DS or switch to restricted chow diet abolished HIF1α levels and reversed glucose intolerance of PFKFB3βKO DS mice. Our data suggest that replication and functional recovery of β-cells under DS depend on β-cell competitive and selective purification of HIF1α and PFKFB3-positive β-cells.