bluuebunny/crossref_metadata_2025_split huggingface dataset:
Entrepreneurial ecosystems during COVID-19: the survival of small businesses using dynamic capabilities
Authors: Rashid Sumayya , Ratten Vanessa 
Published: March 2021

PurposeThe world is going through a global crisis after the outbreak of coronavirus (COVID-19) in most areas of the world. Businesses particularly small ones do not work in isolation but instead are embedded in an entrepreneurial ecosystem that is dependent on environmental conditions. The disruptive changes from COVID-19 have caused serious damage to the global economy, so it is up to entrepreneurs to bring equilibrium by introducing change. This paper adopts the lens of dynamic capabilities to study how small business entrepreneurs are trying to survive and grow in an entrepreneurial ecosystem affected by coronavirus.Design/methodology/approachUsing qualitative research methods, 20 Pakistani entrepreneurs have been interviewed in order to assess how the entrepreneurial ecosystem in an emerging economy has been affected by COVID-19. This enables a contemporary and realistic understanding about the way small business entrepreneurs have adjusted to a crisis.FindingsFrom the data analysis, the three main dimensions of dynamic capabilities for small business entrepreneurs emerge, which involve a sensing, seizing and transforming capability.Research limitations/implicationsThe findings suggest that small businesses utilise the following strategies to cope with change: emergent humanitarian crisis, carte blanche agile business models and effectual business functions. These findings contribute to the literature about the challenges of current crises and how businesses can cope in this situation using a dynamic capabilities perspective.Practical implicationsThe findings contribute to the ability of small businesses to cope during the current pandemic situations and anticipate how to manage future crises. Furthermore, the entrepreneurial practices exercised by small businesses are also presented that represent an innovative way to understand crisis management techniques by entrepreneurs in emerging economies.Social implicationsThese findings contribute to the literature about the challenges of current crises and how businesses can cope in this situation using a dynamic capabilities perspective.Originality/valueBy drawing on the existing literature of COVID-19's impact on businesses, the theoretical contribution of this paper highlights the applicability of dynamic capabilities on small businesses to survive during the global crisis.
Empirical analysis of urban youth unemployment in Ethiopia
Authors: Berhe Mesfin Welderufael 
Published: March 2021

AbstractLack of adequate jobs and long unemployment duration becomes a challenge for urban youth in Ethiopia. This study empirically examines youth unemployment and its determinants in urban Ethiopia. It aims to examine the incidences and durations of youth unemployment and their determinant factors. In addition to logistic regression model, a nonparametric Kaplan–Meier survival analysis and Cox proportional hazards model are used. The results indicate that both the incidence and duration of youth unemployment is higher in urban Ethiopia. The hazards model shows that the hazard rate of leaving unemployment are significantly related to individual characteristics such as age and educational level of the youth, and labor market factors such as experience and job market information. Gender and regional disparities are observed. Young women exit unemployment much slower than men and the exit rate increases with age. Big and relatively more urbanized regions have a higher incidence and longer duration of unemployment spells than the small regions. Finally, based on the results, the study suggests that there is a need to adopt target policies that will promote skills and employment opportunities for the youth. Providing entrepreneurship training and startup capital to encourage youth to create rather than seek jobs is critical in this regard.
Identification of differentially expressed circular RNAs associated with thymoma
Authors: Wu Qingjun , Luo Xuanmei , Li Hexin , Zhang Lili , Su Fei , hou Shifang , Yin Jian , Zhang Wei , Zou Lihui 
Published: March 2021

AbstractBackgroundThymomas and thymic carcinomas are the most common tumor types among anterior mediastinal lesions. However, the relationship between molecular aberrations and thymoma patients are poorly understood, especially abnormal changes in the expression profiles of circRNAs. The purpose of the present study was to investigate the expression profiles of circRNAs in thymoma patients and their possible roles in the pathogenesis of thymoma.MethodsDiseased tissues and surrounding normal thymic tissues in two thymoma patients were collected for circRNA sequencing. The top four upregulated circRNAs were selected as candidates and further validated with RT‐PCR in 20 thymoma patients. Gene ontology and signal transduction network analyses of circRNA‐related mRNAs were performed to analyze the functional properties. Survival analysis of their parental genes were also carried out to evaluate the clinical value of differentially expressed circRNA.ResultsA total of 73 circRNAs were differentially expressed in thymoma tissues using high‐throughput sequencing. Among these circRNAs, hsa_circ_0001173, hsa_circ_0007291, hsa_circ_0003550, and hsa_circ_0001947 were significantly upregulated in thymoma tissues compared with normal thymic tissues. We identified that these four circRNA‐related mRNAs were involved in cell–cell adhesion, MAPK pathways, and TNF pathway, which may contribute to the pathological immune disorder in thymoma. Finally, we also found that SCAP (hsa_circ_0007291 parental gene) and AFF2 (hsa_circ_0001947 parental gene) were all significantly related with progression‐free survival (PFS) of thymoma patients in a Kaplan‐Meier plot (p‐value <0.05).ConclusionsThe expression levels of hsa_circ_0001173, hsa_circ_0007291, hsa_circ_0003550, and hsa_circ_0001947 were significantly upregulated and positively correlated with immune imbalance in thymoma patients.
Are wildfires affecting seed germination in cactus? An experimental assessment
Authors: Roca Julieta , Jaureguiberry Pedro , Gurvich Diego E. 
Published: March 2021

AbstractCacti are conspicuous plants across arid and semi‐arid ecosystems of the American continent and are currently under threat due to human pressures, such as habitat loss, illegal collection and changes in fire regimes. Although much of their habitat is highly fire prone, there are strikingly few studies on their germination response to fire cues. The aim of this work was to analyse the effect of heat shock (simulating wildfires) on the ‘germination %’ and the ‘mean germination time’ of 13 cactus species of two growth forms (six columnar and seven globose) from a fire‐prone cactus diversity hotspot in Córdoba Mountains, central Argentina. We also analysed the effect of growth form and seed mass on species responses. Seeds were subjected to the following treatments: 70°C/5 min, 70°C/10 min, 105°C/5 min, 105°C/10 min and a control (i.e. no heat). Germination decreased under at least one treatment in seven species, increased in three species, had contrasting changes in one species, and showed no effect of treatments in two species. Germination was faster in eight species, slower in one species and showed no effects of treatments in four species. Germination was significantly higher for globose species following the 70°C/10 min treatment and for columnar species under the treatment of 110°C/10 min; while germination time did not differ between growth forms. Seed mass did not have a significant effect on germination, and only affected germination time under the 70ºC treatments, under which lighter seeds germinated faster than heavier seeds. Our results show that the studied species exhibited a high diversity of responses, with most of the species presenting tolerance to heat shock, and that under certain conditions growth form and seed mass are important traits related to species responses to heat shock treatments.
Effect of climatic factors on urinary cortisol and peripheral blood leukocytes in lambs grazing on a semi‐natural grassland in the Hokuriku District of Japan
Authors: Asano Keigo , Takamatsu Erina , Numata Hana , Nitta Momoyo , Ishida Motohiko 
Published: March 2021

AbstractThe effects of climatic factors on stress and immune functions of grazing lambs in summer and autumn in the Hokuriku District of Japan were evaluated by determining urinary cortisol (U‐COR) levels and peripheral blood leukocyte populations and comparing those with lambs kept indoors. Two groups of five lambs, consisting of those grazed on a semi‐natural grassland (GRL) and those housed indoors in a domestic animal shelter (INL), were maintained at from July to October. The temperature–humidity index at each location was indicative of heat stress during summer; however, the U‐COR elevation was not observed in both groups. The elevation was observed in GRL in autumn and was higher than INL in October. Climatic conditions in autumn were characterized by high humidity and a sudden drop in temperature. U‐COR was positively correlated with the relative humidity. The GRL was exposed to low‐nutrient conditions for a relatively long time. The CD4+/CD8+ T cell ratio in GRL decreased in October. Subsequently, the total leucocyte, including granulocytes, monocytes, and lymphocytes, sharply increased. The responses indicated an immune deficiency caused by immunosuppression because of a low nutrition caused by grazing and high‐stress conditions in autumn.
Spatial factor modeling: A Bayesian matrix‐normal approach for misaligned data
Authors: Zhang Lu , Banerjee Sudipto 
Published: March 2021

AbstractMultivariate spatially oriented data sets are prevalent in the environmental and physical sciences. Scientists seek to jointly model multiple variables, each indexed by a spatial location, to capture any underlying spatial association for each variable and associations among the different dependent variables. Multivariate latent spatial process models have proved effective in driving statistical inference and rendering better predictive inference at arbitrary locations for the spatial process. High‐dimensional multivariate spatial data, which are the theme of this article, refer to data sets where the number of spatial locations and the number of spatially dependent variables is very large. The field has witnessed substantial developments in scalable models for univariate spatial processes, but such methods for multivariate spatial processes, especially when the number of outcomes are moderately large, are limited in comparison. Here, we extend scalable modeling strategies for a single process to multivariate processes. We pursue Bayesian inference, which is attractive for full uncertainty quantification of the latent spatial process. Our approach exploits distribution theory for the matrix‐normal distribution, which we use to construct scalable versions of a hierarchical linear model of coregionalization (LMC) and spatial factor models that deliver inference over a high‐dimensional parameter space including the latent spatial process. We illustrate the computational and inferential benefits of our algorithms over competing methods using simulation studies and an analysis of a massive vegetation index data set.
The diagnostic and therapeutic challenges of Grade 3B follicular lymphoma
Authors: Barraclough Allison , Bishton Mark , Cheah Chan Y. , Villa Diego , Hawkes Eliza A. 
Published: March 2021

SummaryGrade 3B follicular lymphoma (G3B FL) is rare, accounting for only 5–10% of FLs. Not only has it been routinely excluded from clinical trials, but data published on diagnosis, outcomes, choice of therapies and role of imaging are conflicting. With the advent of increasingly diverse treatment options for low‐grade (G1–3A) FL, and the molecular subcategorisation of high‐grade B‐cell lymphomas, characterisation and treatment of G3B FL is ever more important as extrapolation of data becomes more difficult. New data have emerged exploring unique genetic characteristics, specific features on positron emission tomography imaging, choice of therapy, and outcomes of G3B FL in the current era. The present review will summarise and appraise these new data, and offer recommendations based on current evidence.
Deep learning approach to predict lymph node metastasis directly from primary tumour histology in prostate cancer
Authors: Wessels Frederik , Schmitt Max , Krieghoff‐Henning Eva , Jutzi Tanja , Worst Thomas S. , Waldbillig Frank , Neuberger Manuel , Maron Roman C. , Steeg Matthias , Gaiser Timo , Hekler Achim , Utikal Jochen S. , von Kalle Christof , Fröhling Stefan , Michel Maurice S. , Nuhn Philipp , Brinker Titus J. 
Published: March 2021

ObjectiveTo develop a new digital biomarker based on the analysis of primary tumour tissue by a convolutional neural network (CNN) to predict lymph node metastasis (LNM) in a cohort matched for already established risk factors.Patients and MethodsHaematoxylin and eosin (H&E) stained primary tumour slides from 218 patients (102 N+; 116 N0), matched for Gleason score, tumour size, venous invasion, perineural invasion and age, who underwent radical prostatectomy were selected to train a CNN and evaluate its ability to predict LN status.ResultsWith 10 models trained with the same data, a mean area under the receiver operating characteristic curve (AUROC) of 0.68 (95% confidence interval [CI] 0.678–0.682) and a mean balanced accuracy of 61.37% (95% CI 60.05–62.69%) was achieved. The mean sensitivity and specificity was 53.09% (95% CI 49.77–56.41%) and 69.65% (95% CI 68.21–71.1%), respectively. These results were confirmed via cross‐validation. The probability score for LNM prediction was significantly higher on image sections from N+ samples (mean [SD] N+ probability score 0.58 [0.17] vs 0.47 [0.15] N0 probability score, P = 0.002). In multivariable analysis, the probability score of the CNN (odds ratio [OR] 1.04 per percentage probability, 95% CI 1.02–1.08; P = 0.04) and lymphovascular invasion (OR 11.73, 95% CI 3.96–35.7; P < 0.001) proved to be independent predictors for LNM.ConclusionIn our present study, CNN‐based image analyses showed promising results as a potential novel low‐cost method to extract relevant prognostic information directly from H&E histology to predict the LN status of patients with prostate cancer. Our ubiquitously available technique might contribute to an improved LN status prediction.
Early postoperative acute myocardial infarction in kidney transplant recipients: A nested case‐control study
Authors: Deeb Maya , Gupta Nikita , Overgaard Christopher B. , Li Yanhong , Famure Olusegun , Joseph Kim S. 
Published: March 2021

AbstractIntroductionThe epidemiology of early acute myocardial infarctions after kidney transplantation has not been well characterized. This study sought to examine the incidence, risk factors, and clinical outcomes of early acute myocardial infarctions or EAMI in kidney transplant recipients.MethodsA total of 1976 patients who underwent kidney transplantation at our center from Jan 1, 2000, to Sept 30, 2016, were included. A nested case‐control design was used to study EAMI risk factors using a conditional logistic regression model. A Cox proportional hazards model was used to assess the association of EAMI with death‐censored graft failure, death with graft function, and total graft failure.ResultsSeventy four patients had an EAMI within 3 months post‐transplant. Based on univariable analyses, risk factors for EAMI included age and recipient history of diabetes mellitus or coronary artery disease. After adjustment, recipient history of coronary artery disease was the only independent predictor for EAMI (OR 3.76, p < .001). Patients who experienced EAMI were more likely to experience death‐censored graft failure, death with graft function, and total graft failure.ConclusionWhile the incidence of EAMI in kidney transplant recipients is relatively low, these data show that EAMI has profound long‐term effects on morbidity and mortality.
Optimizing cardiovascular imaging in Staphylococcus aureus endocarditis
Authors: Shah Sangeeta , Gupta Tripti , White Christopher J , Jain Surma , Ramee Emily , Qamruddin Salima , Kemmerly Sandra A. 
Published: March 2021

AbstractIntroductionThe shift toward value‐based health care drives physicians to examine opportunities to optimize use of healthcare resources. There is discordance between providers’ use of cardiovascular imaging (CVI) in assessing patients for infective endocarditis (IE) with Staphylococcus aureus bacteremia (SAB). An evidence‐based algorithm was created to minimize variation of CVI use. The primary objective was to ensure sensitivity of the algorithm to recommend CVI in patients suspected of IE.MethodsA retrospective review evaluated patients at Ochsner Medical Center who developed SAB between 1/1/13 and 12/31/14. Predefined patient demographics, use of CVI, outcomes, and 12‐week follow‐up for readmission after first positive blood culture were collected from chart review. The created algorithm was applied retrospectively to determine its sensitivity and specificity in recommending the right CVI test.Results181 patients admitted were admitted with SAB, of which 114 (63%) were male. There were 115 TTEs and 55 TEEs performed. Out of 15 patients diagnosed with IE, 3 were found on TTE and 12 were found on TEE. The algorithm would have recommended a TEE in all 15 patients who had high‐risk features for IE and a true diagnosis of IE, suggesting a sensitivity of 100% and specificity of 74.7% for the algorithm to have recommended a highly sensitive CVI modality.ConclusionThis algorithm optimizes CVI for diagnosing IE in patients with SAB. As healthcare adapts to a value‐based system, use of best‐practice algorithms will promote consistency in practice among providers and help optimize patient outcomes and use of resources.
Architecture of an effective convolutional deep neural network for segmentation of skin lesion in dermoscopic images
Authors: Arora Ginni , Dubey Ashwani Kumar , Jaffery Zainul Abdin , Rocha Alvaro 
Published: March 2021

AbstractThe segmentation of dermoscopic‐based skin lesion images is considered to be challenging owing to various factors. Some of the most tangible reasons include poor contrast near the affected skin lesion, the fuzzy and unpredictable lesion limits, the presence of variations in noise, and capturing images under different conditions. This paper aims to develop an efficient segmentation model for dermoscopic images of different skin lesions based on deep learning. This paper proposes the 11‐layer convolutional deep neural network with two segmentation models trained from start to finish and do not depend on any previous information about the data. The viability, efficiency, and speculation ability of the models are evaluated on the ISIC2018 database. The proposed model achieves 0.903 accuracy and 0.820 Jaccard index in the segmentation of skin lesions. The model shows better performance compared to other image segmentation techniques from the leaderboards of ISIC2018 using deep learning.
Copper, Zinc and Lead Isotopic Delta Values and Isotope Ratios of Various Geological and Biological Reference Materials
Authors: Jeong Hyeryeong , Ra Kongtae , Choi Jin Young 
Published: March 2021

Copper, Zn and Pb isotope ratios are important tracers for understanding geological and biological processes. We present optimised column separation methods using an anion exchange resin for Cu and Zn, and a Pb‐specific resin for Pb, and provide Cu, Zn and Pb isotope data for thirty‐three commercially available geological and biological reference materials (RMs) using MC‐ICP‐MS. Our measurement procedures can be applied to various environmental samples. The Cu, Zn and Pb yields were higher than 99.2%, and isotopic fractionation did not occur during column separation. Copper and Zn delta values of AGV‐2, BCR‐2, BIR‐1a, BHVO‐2, GSP‐2, NOD‐A‐1, NOD‐P‐1, DOLT‐4, BCR‐414, BCR‐279 and NIST SRM 1573a were in good agreement with previously reported values. The intermediate measurement precision for Cu and Zn delta values was better than ± 0.02‰ (2s). The δ65CuNIST976, δ66ZnJMCand206Pb/207Pb values determined in this study ranged from −0.19 to +0.73‰, −0.96 to +1.00‰ and 1.1172 to 1.2263, respectively. The δ66ZnJMCvariability (Δ66Znmax–min) in this study was relatively larger than that of δ65CuNIST976variability (Δ65Cumax–min). A combination of Cu, Zn and Pb isotopes can be used as potential environmental tracers to track the origins of these elements in the environment as well as to understand their influence on organisms.
Subcutaneous implantable cardioverter‐defibrillator electrode fracture: Follow‐up, troubleshooting, and evaluation
Authors: Kella Danesh K. , Stambler Bruce S. 
Published: March 2021

AbstractThe subcutaneous‐implantable cardioverter‐defibrillator (S‐ICD) and its electrode were developed to avoid long‐term complications of transvenous leads in the vasculature. We report a case of unexpected, inappropriate S‐ICD shocks due to oversensing of high‐amplitude, nonphysiologic, electrical noise artifacts that were not preceded by high‐impedance alerts or sensing electrogram noise detections. Following explant, high‐magnification X‐ray imaging of the S‐ICD electrode demonstrated partial fracture of the distal sensing conductor located near a short radius bend in the electrode at the electrode‐header interface. Clinicians should be aware of a potential for fatigue failure fracture of the S‐ICD electrode. Recommendations for systematic S‐ICD follow‐up and troubleshooting are discussed.
Angiotensin‐converting enzyme inhibitors increase anti‐fibrotic biomarkers in African Americans with left ventricular hypertrophy
Authors: A. Romero Cesar , Mathew Shobi , Wasinski Benjamin , Reed Brian , Brody Aaron , Dawood Rachelle , Twiner Michael J. , McNaughton Candace D. , Fridman Rafael , Flack John M. , Carretero Oscar A. , Levy Phillip D. 
Published: March 2021

AbstractAngiotensin‐converting enzyme inhibitors (ACEi) are part of the indicated treatment in hypertensive African Americans. ACEi have blood pressure‐independent effects that may make them preferred for certain patients. We aimed to evaluate the impact of ACEi on anti‐fibrotic biomarkers in African American hypertensive patients with left ventricular hypertrophy (LVH). We conducted a post hoc analysis of a randomized controlled trial in which hypertensive African American patients with LVH and vitamin D deficiency were randomized to receive intensive antihypertensive therapy plus vitamin D supplementation or placebo. We selected patients who had detectable lisinopril (lisinopril group) in plasma using liquid‐chromatography/mass spectrometry analysis and compared them to subjects who did not (comparison group) at the one‐year follow‐up. The pro‐fibrotic marker type 1 procollagen C‐terminal propeptide (PICP) and the anti‐fibrotic markers matrix metalloproteinase‐1 (MMP‐1), tissue inhibitor of metalloproteinases 1 (TIMP‐1), telopeptide of collagen type I (CITP), and N‐acetyl‐seryl‐aspartyl‐lysyl‐proline (Ac‐SDKP) peptide were measured. Sixty‐six patients were included, and the mean age was 46.2 ± 8 years. No difference was observed in the number and intensity of antihypertensive medications prescribed in each group. Patients with detectable lisinopril had lower blood pressure than those in the comparison group. The anti‐fibrotic markers Ac‐SDKP, MMP‐1, and MMP‐1/TIMP‐1 ratio were higher in patients with detectable ACEi (all p < .05). In a model adjusted for systolic blood pressure, MMP‐1/TIMP‐1 (p = .02) and Ac‐SDKP (p < .001) levels were associated with lisinopril. We conclude that ACEi increase anti‐fibrotic biomarkers in hypertensive African Americans with LVH, suggesting that they may offer added benefit over other agents in such patients.