bluuebunny/crossref_metadata_2025_split huggingface dataset:
Revision of Failed Sternal Fixation Using Tricortical Iliac Crest In-Lay Autograft and Mesh Plate
Authors: Ogunleye Temi D. , Carlson Tim A. , Cole Peter A. 
Published: March 2021

Case:
We present the case of a 57-year-old woman who sustained a comminuted transverse sternal fracture that failed primary open reduction internal fixation (ORIF). The patient underwent staged nonunion reconstruction with a tricortical iliac crest bone graft and mesh plate. With 18 months of a sustained successful outcome, we propose a treatment strategy for a challenging clinical problem.

Conclusion:
When primary ORIF fails, bone healing and resolution of a painful sternal nonunion can be effectively managed with a tricortical iliac crest in-lay autograft and locking mesh plate.
Monitoring Debris-Flow Surges and Triggering Rainfall at the Lattenbach Creek, Austria
Authors: Huebl Johannes , Kaitna Roland 
Published: March 2021

ABSTRACT
Debris-flow events often comprise a sequence of surges, sometimes termed “roll waves.” The reason for this surging behavior is still a matter of debate. Explanations include the growth of hydraulic instabilities, periodic sediment deposition and release, or grain size sorting. High-resolution field measurements together with triggering rainfall characteristics are rare. We present results for 3 years of monitoring debris-flow events at Lattenbach Creek in the western part of Austria. The monitoring system includes a weather station in the headwaters of the creek, radar sensors for measuring flow depth at different locations along the channel, as well as a two-dimensional rotational laser sensor installed over a fixed cross section that yields a three-dimensional surface model of the passing debris-flow event. We find that the debris flows at Lattenbach Creek were all triggered by rainstorms of less than 2 hours and exhibited surges for each observed event. The velocities of the surges were up to twice as high as the front velocity. Often, the first surges that included boulders and woody debris had the highest flow depth and discharge and showed an irregular geometry. The shape of the surges in the second half of the flow, which carried smaller grain sizes and less woody debris, were rather regular and showed a striking geometric similarity, but still high velocities. The results of our monitoring efforts aim to improve our understanding of the surging behavior of debris flows and provide data for model testing for the scientific community.
Scaling Up Low-Salinity Waterflooding in Heterogenous Reservoirs
Authors: Al-Ibadi Hasan , Stephen Karl , Mackay Eric 
Published: March 2021

SummaryModeling the dynamic fluid behavior of low-salinity waterflooding (LSWF) at the reservoir scale is a challenge that requires a coarse-grid simulation to enable prediction in a feasible time scale. However, evidence shows that using low-resolution models will result in a considerable mismatch compared with an equivalent fine-scale model with the potential of strong, numerically induced pulses and other dispersion-related effects. This work examines two new upscaling methods that have been applied to improve the accuracy of predictions in a heterogeneous reservoir where viscous crossflow takes place.We apply two approaches to upscaling to bring the flow prediction closer to being exact. In the first method, we shift the effective-salinity range for the coarse model using algorithms that we have developed to correct for numerical dispersion and associated effects. The second upscaling method uses appropriately derived pseudorelative permeability curves. The shape of these new curves is designed using a modified fractional-flow analysis of LSWF that captures the relationship between dispersion and the waterfront velocities. This second approach removes the need for explicit simulation of salinity transport to model oil displacement. We applied these approaches in layered models and for permeability distributed as a correlated random field.Upscaling by shifting the effective-salinity range of the coarse-grid model gave a good match to the fine-scale scenario, while considerable mismatch was observed for upscaling of the absolute permeability alone. For highly coarsened models, this method of upscaling reduced the appearance of numerically induced pulses. On the other hand, upscaling by using a single (pseudo)relative permeability produced more robust results with a very promising match to the fine-scale scenario. These methods of upscaling showed promising results when they were used to scale up fully communicating and noncommunicating layers as well as models with randomly correlated permeability.Unlike documented methods in the literature, these newly derived methods take into account the substantial effects of numerical dispersion and effective concentration on fluid dynamics using mathematical tools. The methods could be applied for other models where the phase mobilities change as a result of an injected solute, such as surfactant flooding and alkaline flooding. Usually these models use two sets of relative permeability and switch from one to another as a function of the concentration of the solute.
Monitoring land use changing detection maps with MODIS and AVHRR data from 2001 to 2015 in South Asia regions
Authors: ali shahzad , Qi Huang An , Henchiri Malak , Sha Zhang , Khan Fahim Ullah , Sajid Muhammad , Ali Sajid , Yao Fengmei , Zhang Jiahua 
Published: March 2021

Abstract
In South Asia, annual land cover and land use (LCLU) is a severe issue in the field of earth science because it affects regional climate, global warming, and human activities. Therefore, it is vital essential to obtain correct information on the LCLU in the South Asia regions. LULC annual map covering the entire period is the primary dataset for climatological research. Although the LULC annual global map was produced from the MODIS dataset in 2001, this limited the perspective of the climatological analysis. This study used AVHRR GIMMS NDVI3g data from 2001 to 2015 to randomly forests classify and produced a time series of the annual LCLU map of the South Asia. The MODIS land cover products (MCD12Q1) are used as data from reference for trained classifiers. The results were verified using of the annual map of LCLU time series, and the space-time dynamics of the LCLU map were shown in the last 15 years, from 2001 to 2015. The overall precision of our 15-year land cover map simplifies 16 classes, which is 1.23% and 86.70% significantly maximum as compared to the precision of the MODIS data map. Findings of the past 15 years shows the changing detection that forest land, savanna, farmland, urban and established land, arid land, and cultivated land have increased; by contrast, woody prairie, open shrub-lands, permanent ice and snow, mixed forests, grasslands, evergreen broadleaf forests, permanent wetlands, and water bodies have been significantly reduced over South Asia regions.
Practical strategies to mitigate ruminant greenhouse gas emissions
Authors: Ortega Alejandra , Tester Mark , Lauersen Kyle 
Published: March 2021

Abstract
Livestock contributes to 14.5 percent of global greenhouse gas emissions, with ruminants being the largest contributor through enteric methane emissions. Although several strategies are available to mitigate livestock methane, no consensus exists on which methods are the most effective. Here, we projected by 2050 the impact of the most pragmatic strategies to reduce enteric methane, modelling cattle emissions. The projection shows that supplementing ruminant feed with anti-methanogenic seaweed and converting grassland into silvopasture offer the greatest potential to reduce emissions. A synergic combination of strategies can aid Europe and most of Asia to can reach ruminant carbon neutrality by 2035 and 2038, respectively. However, global cattle CO2-eq emissions will be reduced by no more than 34 percent by 2050, remaining far above the carbon neutrality target. Mitigation strategies alone are insufficient to lower emissions, and reducing the demand for ruminant products is also necessary – particularly in Africa and Western Asia.
Molecular Dynamics Study of Nanoparticles/argon Atoms Size Effects on Atomic Aggregation Phenomena in Ideal Platinum Nanochannel Affected by the External Magnetic Field
Authors: Karimipour Arash 
Published: March 2021

Abstract
In this paper, the computational method is used to describe the atomic behavior of Fe3O4 nanoparticles size effect on these nanoparticles aggregation phenomena in ideal platinum nanochannel and in the presence of outer magnetic major. In this work molecular dynamics (MD) method used and argon atoms described as base fluid. Technically, for the interaction between base fluid atoms, we used Lennard-jones (LJ) potential, while the nanochannel wall and nanoparticle structures are simulated. To calculate the atomic behavior of simulated systems, we report temperature, total energy, and distance of nanoparticles center of mass (COM) and time of aggregation phenomena. Our MD simulation results show the Fe3O4 nanoparticle size is an important factor in aggregation phenomenon occur. Numerically, by enlarging the Fe3O4 nanoparticle size, the aggregation time of Al2O3 nanoparticles changes from 1.41 ns to 1.29 ns. Further, the external magnetic field can be delayed this atomic phenomenon effectively.
Mental Health Consultations on College Campuses: Examining the Predictive Ability of Social Media
Authors: Saha Koustuv , Yousuf Asra , Boyd Ryan L. , Pennebaker James W. , Choudhury Munmun 
Published: March 2021

Abstract
The mental health of college students is a growing concern, and gauging the mental health needs of college students is difficult to assess in real-time and in scale. While social media has shown potential as a viable “passive sensor” of mental health, the construct validity and in-practice reliability of such computational assessments remain largely unexplored. Towards this goal, we study how assessing the mental health of college students using social media data correspond with ground-truth data of on-campus mental health consultations. For a large U.S. public university, we obtained ground-truth data of on-campus mental health consultations between 2011–2016, and collected 66,000 posts from the university’s Reddit community. We adopted machine learning and natural language methodologies to measure symptomatic mental health expressions of depression, anxiety, stress, suicidal ideation, and psychosis on the social media data. Seasonal auto-regressive integrated moving average (SARIMA) models of forecasting on-campus mental health consultations showed that incorporating social media data led to predictions with r=0.86 and SMAPE=13.30, outperforming models without social media data by 41%. Our language analyses revealed that social media discussions during high mental health consultations months consisted of discussions on academics and career, whereas months of low mental health consultations saliently show expressions of positive affect, collective identity, and socialization. This study reveals that social media data can improve our understanding of college students’ mental health, particularly their mental health treatment needs.
Intelligent Decision Making Algorithm for Balanced Cluster Formation in Wireless Sensor Networks
Authors: B Santhosh Kumar , P Trinatha Rao 
Published: March 2021

Abstract
In this paper, we propose an optimal cluster-based multiple sink reconnection technology for wireless sensor networks using a hybrid optimization algorithm. The proposed design used an intermediate sensor / mobile node next to the sink node and a sensor node ready to transmit data. Here, the weighted k-mean algorithm is converted to a cluster node. The optimal cluster head code was chosen using a mass optimization method that targets the available energy and available bandwidth for successfully transferring data without node optimization. So with resource updates, you can find the right location for your sink node for better data transfer.
Validating a Prognostic Model for 1-Year Mortality of Psychogeriatric Inpatients.
Authors: Moebs Isabelle , Gale Chris , Abeln Esther , Seifert Annalise , Barak Yoram 
Published: March 2021

Abstract
Background

To validate a predictive scoring system for 1-year mortality among psychogeriatric inpatients admitted for acute psychiatric care.
Methods

Computerized data were extracted from the District Health Board Database for a university affiliated general hospital. A geriatric risk scoring system developed in the USA was employed to validate mortality within 1-year of hospital discharge.
Results

Among 125 psychogeriatric inpatients who were discharged in 2017, [mean age 82.8 (± 8.9) years, 82 (65.6%) women] 33 (26.4%), [mean age, 87.7 (± 11.1) years, 25 (75.7%) women] died within 1-year. Levine’s mortality index predicted death. A post hoc probit analysis found two factors significantly associated with predicted mortality: metastatic cancer and discharge to care.
Conclusions

A geriatric1-year mortality scoring system accurately predicted mortality among psychogeriatric inpatients. Predicting psychogeriatric mortality should be considered a guideline for ensuring quality of care and appropriate discharge and advanced care planning.
Hierarchical Diversity Entropy for the Early Fault Diagnosis of Rolling Bearing
Authors: Wang Xianzhi , Si Shubin , Li Yongbo 
Published: March 2021

Abstract
Intelligent fault diagnosis provides great convenience for the prognostic and health management of the rotating machinery. Recently, the entropy-based feature extraction method has aroused researchers’ attentions due to its independence with prior knowledge, unnecessary of preprocessing, and easy to perform. The multiscale diversity entropy has been proven to be a promising feature extraction method for the intelligent fault diagnosis. Compared to the existing entropy methods, the multiscale diversity entropy has advantages of high consistency, strong robustness and high calculation efficiency. However, the multiscale diversity entropy encounters the challenge to extract features for early fault diagnosis due to the weak fault symptoms and strong noise. This can be attributed to the multiscale diversity entropy only concerns the fault information embedded in the low frequency, which ignores the information hidden in the high frequency. To address this defect, the hierarchical diversity entropy (HDE) is proposed, which can synchronously extract fault information hidden in both high and low frequency. Based on HDE and random forest, a novel intelligent fault diagnosis frame has been proposed. The effectiveness of the proposed method has been evaluated through simulated and experimental bearing signals. The results show that the proposed HDE has the best feature extraction ability compare to multiscale sample entropy, multiscale permutation entropy, multiscale fuzzy entropy, and multiscale diversity entropy.
68Ga-FAPI PET/MR is Helpful in Differential Diagnosis of Pancreatitis From Pancreatic Malignancy Compared to 18F-FDG PET/CT
Authors: Shou Yi , Xue Qiaoyi , Yuan Jianmin , Zhao Jun 
Published: March 2021

Abstract
Background: 68Ga-fibroblast activation protein specific enzyme inhibitor (FAPI) is a novel PET agent for tumor imaging. Case description: We herein present a case where 68Ga-FAPI PET/MR helped to diagnose IgG4-RD that involved pancreas and bile duct. Our 62-year-old patient suffered from middle upper abdomen and brown urine. Blood test revealed abnormal liver function and elevated IgG4 (4.830g/L↑). 18F-FDG PET showed enlarged uncinate process and dilated bile duct tree. Mild increase of FDG uptake in uncinate process and head of pancreas indicated possible pancreatic malignancy, but the evidence was not sufficient enough. 68Ga-FAPI PET revealed prominent fibroblast mediated inflammation in the entire pancreas and bile duct, suggesting IgG4-RD.Conclusion: The case illustrates that 68Ga-FAPI PET is more sensitive to IgG4-RD than 18F-FDG, and thus could be helpful in improving the differential diagnosis of pancreatitis and pancreatic cancer.
Aberrant Functional and Effective Connectivity of the Frontostriatal Network in Unilateral Acute Tinnitus Patients with Hearing Loss
Authors: Zhou Gang-Ping , Chen Yu-Chen , Li Wang-Wei , Wei Heng-Le , Yu Yu-Sheng , Zhou Qing-Qing , Yin Xindao , Tao Yue-Jin , Zhang Hong 
Published: March 2021

Abstract
Purpose: The present study combined resting-state functional connectivity (FC) and Granger causality analysis (GCA) to explore frontostriatal network dysfunction in unilateral acute tinnitus (AT) patients with hearing loss. Methods: The participants included 42 AT patients and 43 healthy control (HC) subjects who underwent resting-state functional magnetic resonance imaging (fMRI) scans. Based on the seed regions in the frontostriatal network, FC and GCA were conducted between the AT patients and HC subjects. Correlation analyses were used to examine correlations among altered FC values, GCA values, and clinical features in AT patients. Results: Compared with HCs, AT patients showed a general reduction in FC between the seed regions in the frontostriatal network and nonauditory areas, including the frontal cortices, midcingulate cortex (MCC) , supramarginal gyrus (SMG), and postcentral gyrus (PoCG) . Using the GCA algorithm, we detected abnormal effective connectivity (EC) in the inferior occipital gyrus (IOG), MCC, Cerebelum_Crus1, and PoCG. Furthermore, correlations between disrupted FC/EC and clinical characteristics, especially tinnitus distress-related characteristics, were found in AT patients. Conclusions: Our work demonstrated abnormal FC and EC between the frontostriatal network and several nonauditory regions in AT patients with hearing loss, suggesting that multiple large-scale network dysfunctions and interactions are involved in the perception of tinnitus. These findings not only enhance the current understanding of the frontostriatal network in tinnitus but also serve as a reminder of the importance of focusing on tinnitus at an early stage.
Nasopharyngeal Expression of Angiotensin-Converting Enzyme 2 (ACE2) and Transmembrane Serine Protease 2 (TMPRSS2) in Children Compared to Adults Within Family Clusters Exposed to COVID-19
Authors: Hasan Mohammad , Ahmad Muneera , Dargham Soha , Ibrahim Hatem , Hashemi Alaa Al , Ngwabi Nonhlanhla , Lopez Andres , Dobson Simon , Abu-Raddad Laith , Tang Patrick 
Published: March 2021

Abstract
There is accumulating evidence that the lower levels of angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2) in the nasal epithelium of children may be related to a lower incidence of COVID-19 compared to adults. However, no direct evidence is available to support this hypothesis. In this study, we compared the transcript levels of ACE2 and TMPRSS2 in nasopharyngeal swabs (n=207) from children and adult members within COVID-19-exposed families and assessed their association with SARS-CoV-2 infection status. The expression of both genes was higher in adults compared to the children (n=115 adults and 92 children, p<0.05), but was not significantly different between COVID-19 positive and negative patients of all ages or within the same age groups. Using paired data, expression of both genes was significantly higher in COVID-19 positive adults compared to COVID-19 negative children (n=47 pairs; p<0.001) within the same families. ACE2 and TMPRSS2 expression is positively associated [OR:1.16(1.06-1.3) and 1.14(1.04-1.26) for ACE2 and TMPRSS2, respectively, p<0.001)] with SARS-CoV-2 infection status in the sub-group of families with COVID-19 positive adults and COVID-19 negative children, suggesting that children with lower levels of nasal ACE2 and TMPRSS2 are more likely to remain COVID-19 negative despite being exposed to a COVID-19-positive adult family member.
GDAP1 loss of function inhibits the mitochondrial pyruvate dehydrogenase complex by altering the actin cytoskeleton
Authors: Wolf Christina , Pouya Alireza , Bitar Sara , Pfeiffer Annika , Bueno Diones Caeran , Arndt Sabine , Tenzer Stefan , Ritz Sandra , Schwirz Jonas , Dobrindt Kristina , Peitz Michael , Brustle Oliver , Bello Federica Dal , Vianello Caterina , Giacomello Marta , Hanschmannn Eva-Maria , Boussaad Ibrahim , Krüger Rejko , Methner Axel 
Published: March 2021

Abstract
Charcot-Marie-Tooth (CMT) disease 4A is an autosomal-recessive polyneuropathy caused by mutations of ganglioside-induced differentiation-associated protein 1 (GDAP1), a putative glutathione transferase, which affects mitochondrial shape and alters cellular calcium homeostasis. Here, we identify the underlying mechanism. We found that patient-derived motoneurons and GDAP1 knockdown SH-SY5Y cells display two phenotypes: more tubular mitochondria and a metabolism characterized by glutamine dependence and fewer cytosolic lipid droplets. GDAP1 interacts with the actin-depolymerizing protein Cofilin-1 in a redox-dependent manner, suggesting a role for actin signaling. Consistently, GDAP1 loss causes less F-actin close to mitochondria, which restricts mitochondrial localization of the fission factor dynamin-related protein 1, instigating tubularity. Changes in the actin cytoskeleton also disrupt mitochondria-ER contact sites. This results in lower mitochondrial calcium levels and inhibition of the pyruvate dehydrogenase complex, explaining the metabolic changes upon GDAP1 loss of function. Together, these findings reconcile GDAP1-associated phenotypes and implicate disrupted actin signaling in CMT4A pathophysiology.
Asymmetry Effects in Optical Properties of a Gold Nanotube
Authors: Moradi Afshin 
Published: March 2021

Abstract
Asymmetry effects in optical properties of an infinitely long gold nanotube is studied within the framework of the quasi-static approximation. In this way, incident, scattered and transmitted fields are represented with the appropriate electrostatic potentials in the cylindrical coordinates. The problem is investigated using a boundary-value approach. The expressions for the polarizability and dispersion of surface plasmons of the system are derived and numerical results, in the wavelength region 500 nm to 1000 nm, show that instead of the one well-known resonance peak of the nanotube, one pair of resonance peaks appear, as a result of the coupling between the dipole and quadrupole modes. Then, scattering, absorption and extinction widths of the system are formulated. Also, the effective dielectric function of a composite of aligned symmetry-broken gold nanotubes is presented.