bluuebunny/crossref_metadata_2025 huggingface dataset:
Intra-Pancreatic Insulin Nourishes Cancer Cells: Do Insulin-Receptor Antagonists such as PGG and EGCG Play a Role?
Authors: Hu Lijuan , Chen Xijuan , Qiu Shuai , Yang Jing , Liu Hongyi , Zhang Jie , Zhang Dapeng , Wang Feng
Published: May 2020

Harboring insulin-producing cells, the pancreas has more interstitial insulin than any other organ. In vitro, insulin activates both insulin receptor (IR) and insulin-like growth factor-1 receptor (IGF1R) to stimulate pancreatic cancer cells. Whether intra-pancreatic insulin nourishes pancreatic cancer cells in vivo remains uncertain. In the present studies, we transplanted human pancreatic cancer cells orthotopically in euglycemic athymic mice whose intra-pancreatic insulin was intact or was decreased following pretreatment with streptozotocin (STZ). In the next eight weeks, the tumor carriers were treated with one of the IR/IGF1R antagonists penta-O-galloyl-[Formula: see text]-D-glucose (PGG) and epigallocatechin gallate (EGCG) or treated with vehicle. When pancreatic tumors were examined, their fraction occupied with living cells was decreased following STZ pretreatment and/or IR/IGF1R antagonism. Using Western blot, we examined tumor grafts for IR/IGF1R expression and activity. We also determined proteins that were downstream to IR/IGF1R and responsible for signal transduction, glycolysis, angiogenesis, and apoptosis. We demonstrated that STZ-induced decrease in intra-pancreatic insulin reduced IR/IGF1R expression and activity, decreased the proteins that promoted cell survival, and increased the proteins that promoted apoptosis. These suggest that intra-pancreatic insulin supported local cancer cells. When tumor carriers were treated with PGG or EGCG, the results were similar to those seen following STZ pretreatment. Thus, the biggest changes in examined proteins were usually seen when STZ pretreatment and PGG/EGCG treatment concurred. This suggests that intra-pancreatic insulin normally combated pharmacologic effects of PGG and EGCG. In conclusion, intra-pancreatic insulin nourishes pancreatic cancer cells and helps the cells resist IR/IGF1R antagonism.
Noncommutative photon-added squeezed vacuum states
Authors: Fakhri H. , Sayyah-Fard M.
Published: May 2020

Noncommutative optical squeezed vacuum states are constructed as eigenstates of an appropriate two-photon annihilation operator corresponding to the Biedenharn–Macfarlane [Formula: see text]-oscillator. We consider in details the role of noncommutativity parameter [Formula: see text] on the nonclassical behaviors including quadrature squeezing and sub-Poissonian statistics. Also, we construct the noncommutative photon-added squeezed vacuum states and consider their Hillery-type higher-order squeezing and single-mode noise band.
Dirac neutrinos from Peccei–Quinn symmetry: A fresh look at the axion
Authors: Peinado Eduardo , Reig Mario , Srivastava Rahul , Valle Jose W. F.
Published: May 2020

We show that a very simple solution to the strong CP problem naturally leads to Dirac neutrinos. Small effective neutrino masses emerge from a type-I Dirac seesaw mechanism. Neutrino mass limits probe the axion parameters in regions currently inaccessible to conventional searches.
Sound Radiation Analysis of Functionally Graded Porous Plates with Arbitrary Boundary Conditions and Resting on Elastic Foundation
Authors: Hu Zhengmin , Zhou Kai , Chen Yong
Published: May 2020

In this paper, the sound radiation behaviors of the functionally graded porous (FGP) plate with arbitrary boundary conditions and resting on elastic foundation are studied by means of the modified Fourier series method. It is assumed that a total of three types of porosity distributions are considered in the present study. The material parameters are determined according to the porosity coefficient used to denote the size of pores in the plate. The governing equations of the FGP plate are derived by utilizing the Hamilton’s principle on the basis of the first-order deformation theory (FSDT). Each displacement component of the FGP plate is expanded as the Fourier cosine series combined with auxiliary polynomial functions introduced to enhance the convergence rate of the series expansions. The acoustic response of the FGP plate due to a concentrated harmonic load is calculated by evaluating the Rayleigh integral. Good agreements are attained by comparing the present results with those in available literatures, which show the accuracy and versatility of the developed method in this paper. Finally, the influences of the porosity distribution type, porosity coefficient, boundary condition and elastic foundation on the sound radiation of the FGP plate are analyzed in detail.
Binary chemical reaction with activation energy in dissipative flow of non-Newtonian nanomaterial
Authors: Khan M. Ijaz , Alzahrani Faris
Published: May 2020

This paper deals with the entropy optimization and heat transport of magneto-nanomaterial flow of non-Newtonian (Jeffrey fluid) towards a curved stretched surface. MHD fluid is accounted. The modeling of energy expression is developed subject to Brownian diffusion, Joule (Ohmic) heating, thermophoresis and viscous dissipation. Total entropy rate is discussed with the help of fluid friction irreversibility, mass transfer irreversibility, Joule heating irreversibility and heat transfer irreversibility. Binary chemical reaction with the smallest amount of activation energy is further considered. The governing equations of Jeffrey fluid with effects of hydrodynamic, thermal radiation, heat and mass transfer were solved through built-in-shooting method. The flow variables on the entropy rate, velocity field, concentration, Bejan number, skin friction coefficient and temperature are physically discussed through various graphs. The outcomes reveal that the entropy rate increases with an enhancement in curvature parameter. Such obtained outcomes help in mechanical and industrial engineering sciences. Moreover, the velocity and temperature decays versus ratio of relaxation to retardation times are also noticed.
How to introduce the connective implication in orthomodular posets
Authors: Chajda Ivan , Länger Helmut
Published: May 2020

Since orthomodular posets serve as an algebraic axiomatization of the logic of quantum mechanics, it is a natural question how the connective of implication can be defined in this logic. It should be introduced in such a way that it is related with conjunction, i.e. with the partial operation meet, by means of some kind of adjointness. We present here such an implication for which a so-called unsharp residuated poset can be constructed. Then this implication is connected with the operation meet by the so-called unsharp adjointness. We prove that also conversely, under some additional assumptions, such an unsharp residuated poset can be converted into an orthomodular poset and that this assignment is nearly one-to-one.
CuS–Cu9S8 nanoparticles as an efficient catalyst: A facile method via anion controlled
Authors: Liang Mengfan , Zhu Yan , Sun Shuhong
Published: May 2020

In this paper, a facile, surfactant-free and mild solution chemistry route was employed to prepare copper sulfide (CuS–Cu9S8) nanoparticles (NPs) by using anion-controlled agents with a different electronegativity. Counterions CH3COO− were found to be suitable for regular hexagonal morphology formation, whereas in the presence of [Formula: see text], irregular structure is obtained. By changing the anion of the copper precursor, the ratio of formation of Cu9S8 and CuS can be changed, and the band gap energy (Eg) of as-prepared NPs can be controlled in the presence of anion-controlled agents. Moreover, we demonstrate here the catalytic performance of the as-prepared samples for the degradation of methylene blue (MB) both under the simulated natural light and in dark, and the result shows that the CuS–Cu9S8 NPs exhibited better catalytic activity under visible light ([Formula: see text]%) than in darkness (45%), and CuS–Cu9S8 NPs with higher electronegativity of anion-controlled exhibited the higher catalytic performance. In addition, a simple and direct diagram was applied to illustrate the mechanism of the degradation of MB.
Comparing nexus of ranking among mutual fund categories and families of performance measures at investment policy level
Authors: Ahmed Wajid Shakeel , Sheikh Jibran , Paracha Adil Tahir
Published: May 2020

The aim of the study covers, at first, the rank comparison drawn among mutual funds at categorical and investment policy level and secondly, among the selected three families of performance measures against famous Sharpe ratio. The Spearman rank order correlation and mean rank order approach have been used for this purpose. The major findings of the study reveal that the most of the performance measures have shown a similar ranking order of mutual funds, at the investment policy level, against the standard measure i.e., Sharpe ratio. However, funds that have shown a non-normal trend, led to misspecification syndrome.
Resource Management and Scheduling in Distributed Stream Processing Systems
Authors: Liu Xunyun , Buyya Rajkumar
Published: May 2020

Stream processing is an emerging paradigm to handle data streams upon arrival, powering latency-critical application such as fraud detection, algorithmic trading, and health surveillance. Though there are a variety of Distributed Stream Processing Systems (DSPSs) that facilitate the development of streaming applications, resource management and task scheduling is not automatically handled by the DSPS middleware and requires a laborious process to tune toward specific deployment targets. As the advent of cloud computing has supported renting resources on-demand, it is of great interest to review the research progress of hosting streaming systems in clouds under certain Service Level Agreements (SLA) and cost constraints. In this article, we introduce the hierarchical structure of streaming systems, define the scope of the resource management problem, and present a comprehensive taxonomy in this context covering critical research topics such as resource provisioning, operator parallelisation, and task scheduling. The literature is then reviewed following the taxonomy structure, facilitating a deeper understanding of the research landscape through classification and comparison of existing works. Finally, we discuss the open issues and future research directions toward realising an automatic, SLA-aware resource management framework.
A Survey on Fuzzy Deep Neural Networks
Authors: Das Rangan , Sen Sagnik , Maulik Ujjwal
Published: May 2020

Deep neural networks are a class of powerful machine learning model that uses successive layers of non-linear processing units to extract features from data. However, the training process of such networks is quite computationally intensive and uses commonly used optimization methods that do not guarantee optimum performance. Furthermore, deep learning methods are often sensitive to noise in data and do not operate well in areas where data are incomplete. An alternative, yet little explored, method in enhancing deep learning performance is the use of fuzzy systems. Fuzzy systems have been previously used in conjunction with neural networks. This survey explores the different ways in which deep learning is improved with fuzzy logic systems. The techniques are classified based on how the two paradigms are combined. Finally, the real-life applications of the models are also explored.
A Survey and Classification of Software-Defined Storage Systems
Authors: Macedo Ricardo , Paulo João , Pereira José , Bessani Alysson
Published: May 2020

The exponential growth of digital information is imposing increasing scale and efficiency demands on modern storage infrastructures. As infrastructure complexity increases, so does the difficulty in ensuring quality of service, maintainability, and resource fairness, raising unprecedented performance, scalability, and programmability challenges. Software-Defined Storage (SDS) addresses these challenges by cleanly disentangling control and data flows, easing management, and improving control functionality of conventional storage systems. Despite its momentum in the research community, many aspects of the paradigm are still unclear, undefined, and unexplored, leading to misunderstandings that hamper the research and development of novel SDS technologies. In this article, we present an in-depth study of SDS systems, providing a thorough description and categorization of each plane of functionality. Further, we propose a taxonomy and classification of existing SDS solutions according to different criteria. Finally, we provide key insights about the paradigm and discuss potential future research directions for the field.
The Effect of Context on Small Screen and Wearable Device Users’ Performance - A Systematic Review
Authors: Akpinar Elgin , Yeşilada Yeliz , Temizer Selim
Published: May 2020

Small screen and wearable devices play a key role in most of our daily tasks and activities. However, depending on the context, users can easily experience situationally induced impairments and disabilities (SIIDs). Previous studies have defined SIIDs as a new type of impairment in which an able-bodied user’s behaviour is impaired by the context including the characteristics of a device and the environment. This article systematically reviews the empirical studies on the effect of context on SIIDs. In particular, this review aims to answer the following two research questions: Which contextual factors have been examined in the literature that can cause SIIDs and how different contextual factors affect small screen and wearable device users’ performance. This article systematically reviews 187 publications under a framework that has five factors for context analysis: physical, temporal, social, task, and technical contexts. This review shows that a significant amount of empirical studies have been conducted focusing on some factors such as mobility but there still are some factors such as social factors that need to be further considered for SIIDs. Finally, some factors have shown to have significant impact on users’ performance such as multitasking but not all factors has been empirically demonstrated to have an effect on users’ performance.
Real-time Illumination and Visual Coherence for Photorealistic Augmented/Mixed Reality
Authors: Alhakamy A’Aeshah , Tuceryan Mihran
Published: May 2020

A realistically inserted virtual object in the real-time physical environment is a desirable feature in augmented reality (AR) applications and mixed reality (MR) in general. This problem is considered a vital research area in computer graphics, a field that is experiencing ongoing discovery. The algorithms and methods used to obtain dynamic and real-time illumination measurement, estimating, and rendering of augmented reality scenes are utilized in many applications to achieve a realistic perception by humans. We cannot deny the powerful impact of the continuous development of computer vision and machine learning techniques accompanied by the original computer graphics and image processing methods to provide a significant range of novel AR/MR techniques. These techniques include methods for light source acquisition through image-based lighting or sampling, registering and estimating the lighting conditions, and composition of global illumination. In this review, we discussed the pipeline stages with the details elaborated about the methods and techniques that contributed to the development of providing a photo-realistic rendering, visual coherence, and interactive real-time illumination results in AR/MR.
A Survey of Machine Learning Approaches for Student Dropout Prediction in Online Courses
Authors: Prenkaj Bardh , Velardi Paola , Stilo Giovanni , Distante Damiano , Faralli Stefano
Published: May 2020

The recent diffusion of online education (both MOOCs and e-courses) has led to an increased economic and scientific interest in e-learning environments. As widely documented, online students have a much higher chance of dropping out than those attending conventional classrooms. It is of paramount interest for institutions, students, and faculty members to find more efficient methodologies to mitigate withdrawals. Following the rise of attention on the Student Dropout Prediction (SDP) problem, the literature has witnessed a significant increase in contributions to this subject. In this survey, we present an in-depth analysis of the state-of-the-art literature in the field of SDP, under the central perspective, but not exclusive, of machine learning predictive algorithms. Our main contributions are the following: (i) we propose a comprehensive hierarchical classification of existing literature that follows the workflow of design choices in the SDP; (ii) to facilitate the comparative analysis, we introduce a formal notation to describe in a uniform way the alternative dropout models investigated by the researchers in the field; (iii) we analyse some other relevant aspects to which the literature has given less attention, such as evaluation metrics, gathered data, and privacy concerns; (iv) we pay specific attention to deep sequential machine learning methods—recently proposed by some contributors—which represent one of the most effective solutions in this area. Overall, our survey provides novice readers who address these topics with practical guidance on design choices, as well as directs researchers to the most promising approaches, highlighting current limitations and open challenges in the field.
C-Reference: Improving 2D to 3D Object Pose Estimation Accuracy via Crowdsourced Joint Object Estimation
Authors: Song Jean Y. , Chung John Joon Young , Fouhey David F. , Lasecki Walter S.
Published: May 2020

Converting widely-available 2D images and videos, captured using an RGB camera, to 3D can help accelerate the training of machine learning systems in spatial reasoning domains ranging from in-home assistive robots to augmented reality to autonomous vehicles. However, automating this task is challenging because it requires not only accurately estimating object location and orientation, but also requires knowing currently unknown camera properties (e.g., focal length). A scalable way to combat this problem is to leverage people's spatial understanding of scenes by crowdsourcing visual annotations of 3D object properties. Unfortunately, getting people to directly estimate 3D properties reliably is difficult due to the limitations of image resolution, human motor accuracy, and people's 3D perception (i.e., humans do not "see" depth like a laser range finder). In this paper, we propose a crowd-machine hybrid approach that jointly uses crowds' approximate measurements of multiple in-scene objects to estimate the 3D state of a single target object. Our approach can generate accurate estimates of the target object by combining heterogeneous knowledge from multiple contributors regarding various different objects that share a spatial relationship with the target object. We evaluate our joint object estimation approach with 363 crowd workers and show that our method can reduce errors in the target object's 3D location estimation by over 40%, while requiring only $35$% as much human time. Our work introduces a novel way to enable groups of people with different perspectives and knowledge to achieve more accurate collective performance on challenging visual annotation tasks.
Supporting Storytelling With Evidence in Holistic Review Processes: A Participatory Design Approach
Authors: Metoyer Ronald A. , Chuanromanee Tee , Girgis Gina M. , Zhi Qiyu , Kinyon Eleanor C.
Published: May 2020

Review processes involve complex and often subjective decision-making tasks in which individual reviewers must read and rate submissions, such as a college application, along many relevant dimensions and typically with a rubric in mind. A common part of the work is committee review, where individual reviewers meet to discuss the merits of a particular submission in order to recommend an accept or reject decision. Prior work indicates that visualization and sensemaking support may be beneficial in such processes where reviewers must present the "story" of the applicant under question. We conducted a series of participatory design workshops with reviewers in the domain of holistic college admissions to better understand the challenges and opportunities regarding storytelling. Based on these workshops, we contribute a characterization for how reviewers in this domain construct visual stories, we provide guidance for designing for evidence capture and storytelling, and we draw parallels and distinctions between this domain and other reviewing domains.
The novel P2X7 receptor antagonist PKT100 improves cardiac function and survival in pulmonary hypertension by direct targeting of the right ventricle
Authors: Hansen Thomas , Karimi Galougahi Keyvan , Besnier Marie , Genetzakis Elijah , Tsang Michael , Finemore Meghan , O’Brien-Brown James , Di Bartolo Belinda A. , Kassiou Michael , Bubb Kristen J. , Figtree Gemma A.
Published: May 2020

This study demonstrates the therapeutic potential for right-sided heart failure of a novel inhibitor of the P2X7 receptor (P2X7R). Inflammatory signaling and right ventricular function were improved in a mouse model of pulmonary fibrosis with secondary pulmonary hypertension when treated with this inhibitor. Importantly, survival was also improved, suggesting that this inhibitor, and other P2X7R antagonists, could be uniquely effective in right ventricle (RV)-targeted therapy in pulmonary hypertension. This addresses a major limitation of current treatment options, where the significant improvements in pulmonary pressures ultimately do not prevent mortality due to RV failure.
Berberine Induces CYP2J2 Expression in Human U251 Glioma Cells via Regulation of Peroxisome Proliferator-Activated Receptor Alpha
Authors: Yu Xuming , Wang Shanshan , Wang Jia , Gong Jie , Shi Jinmin , Yu Shirong
Published: May 2020

Background: Berberine is a promising natural drug that has a potential therapeutic effect on neurodegenerative diseases. Objectives: Using U251 cells in vitro, we investigated whether berberine exerts its neuroprotective effect via regulation of CYP2J2. Method: After pretreatment with increasing concentrations (1, 3, and 10 μmol/L) of berberine for 0.5 h, U251 cells were stimulated with 1 μg/mL of lipopolysaccharide (LPS). Cell viability was measured 24 h later using a CCK8 kit. mRNA and protein levels of CYP2J2 and peroxisome proliferator-activated receptor alpha (PPARα) were measured by quantitative real-time-polymerase chain reaction and western blotting, respectively, after 24 h of exposure to 1, 3, or 10 μmol/L berberine. Fluorescence immunocytochemistry was also used to evaluate PPARα protein expression after treatment of U251 cells with 10-μmol/L berberine for 24 h. Transient transfection (cotransfection with the plasmid of PPARα- and RXRα-containing) followed by luciferase and chromatin immunoprecipitation assays was used to elucidate the molecular mechanism underlying the observed effects. Results: Compared to the control, LPS-induced U251 cell death was attenuated by berberine in a dose-dependent manner. After 24 h, cell viability was found to be 52.3% (p < 0.05), 66.2% (p < 0.01), and 70.9% (p < 0.001) using 1, 3, and 10 μmol/L berberine treatment, respectively. At these concentrations, berberine increased the CYP2J2 mRNA levels by 1.31-fold (p < 0.05), 1.48-fold (p < 0.01), and 1.88-fold (p < 0.01), respectively, and increased the PPARα mRNA levels 1.17-fold (p < 0.05), 1.29-fold (p < 0.05), and 1.53-fold (p < 0.01), respectively, compared with the respective control groups. In addition, the CYP2J2 and PPARα protein level was also significantly upregulated in U251 cells by berberine (concentrations in 1, 3, and 10 μmol/L) in a dose-dependent manner, compared with the respective control groups. Further investigation indicated that berberine enhances the heterodimerization of PPARα and RXRα, which together bind to the CYP2J2 promoter to induce the expression of CYP2J2 in U251 cells. Conclusion: Upon exposure of U251 cells to berberine, CYP2J2 expression is induced as a result of PPARα stimulation, resulting in a neuroprotective effect.
Self-Maintenance of Cardiac Resident Reparative Macrophages Attenuates Doxorubicin-Induced Cardiomyopathy Through the SR-A1-c-Myc Axis
Authors: Zhang Hanwen , Xu Andi , Sun Xuan , Yang Yaqing , Zhang Lai , Bai Hui , Ben Jingjing , Zhu Xudong , Li Xiaoyu , Yang Qing , Wang Zidun , Wu Wei , Yang Di , Zhang Yongjie , Xu Yong , Chen Qi
Published: May 2020

Rationale:

Doxorubicin-induced cardiomyopathy (DiCM) is a primary cause of heart failure and mortality in cancer patients, in which macrophage-orchestrated inflammation serves as an essential pathological mechanism. However, the specific roles of tissue-resident and monocyte-derived macrophages in DiCM remain poorly understood.

Objective:

Uncovering the origins, phenotypes, and functions of proliferative cardiac resident macrophages and mechanistic insights into the self-maintenance of cardiac macrophage during DiCM progression.

Methods and Results:

Mice were administrated with doxorubicin to induce cardiomyopathy. Dynamic changes of resident and monocyte-derived macrophages were examined by lineage tracing, parabiosis, and bone marrow transplantation. We found that the monocyte-derived macrophages primarily exhibited a proinflammatory phenotype that dominated the whole DiCM pathological process and impaired cardiac function. In contrast, cardiac resident macrophages were vulnerable to doxorubicin insult. The survived resident macrophages exhibited enhanced proliferation and conferred a reparative role. Global or myeloid specifically ablation of SR-A1 (class A1 scavenger receptor) inhibited proliferation of cardiac resident reparative macrophages and, therefore, exacerbated cardiomyopathy in DiCM mice. Importantly, the detrimental effect of macrophage SR-A1 deficiency was confirmed by transplantation of bone marrow. At the mechanistic level, we show that c-Myc (Avian myelocytomatosis virus oncogene cellular homolog), a key transcriptional factor for the SR-A1-P38-SIRT1 (Sirtuin 1) pathway, mediated the effect of SR-A1 in reparative macrophage proliferation in DiCM.

Conclusions:

The SR-A1-c-Myc axis may represent a promising target to treat DiCM through augmentation of cardiac resident reparative macrophage proliferation.
Treatment of Acute Ischemic Stroke due to Large Vessel Occlusion With COVID-19
Authors: Escalard Simon , Maïer Benjamin , Redjem Hocine , Delvoye François , Hébert Solène , Smajda Stanislas , Ciccio Gabriele , Desilles Jean-Philippe , Mazighi Mikael , Blanc Raphael , Piotin Michel
Published: May 2020

Background and Purpose:

Higher rates of strokes have been observed in patients with coronavirus disease 2019 (COVID-19), but data regarding the outcomes of COVID-19 patients suffering from acute ischemic stroke due to large vessel occlusion (LVO) are lacking. We report our initial experience in the treatment of acute ischemic stroke with LVO in patients with COVID-19.

Methods:

All consecutive patients with COVID-19 with acute ischemic stroke due to LVO treated in our institution during the 6 first weeks of the COVID-19 outbreak were included. Baseline clinical and radiological findings, treatment, and short-term outcomes are reported.

Results:

We identified 10 patients with confirmed COVID-19 treated for an acute ischemic stroke due to LVO. Eight were men, with a median age of 59.5 years. Seven had none or mild symptoms of COVID-19 at stroke onset. Median time from COVID-19 symptoms to stroke onset was 6 days. All patients had brain imaging within 3 hours from symptoms onset. Five patients had multi-territory LVO. Five received intravenous alteplase. All patients had mechanical thrombectomy. Nine patients achieved successful recanalization (mTICI2B-3), none experienced early neurological improvement, 4 had early cerebral reocclusion, and a total of 6 patients (60%) died in the hospital.

Conclusions:

Best medical care including early intravenous thrombolysis, and successful and prompt recanalization achieved with mechanical thrombectomy, resulted in poor outcomes in patients with COVID-19. Although our results require further confirmation, a different pharmacological approach (antiplatelet or other) should be investigated to take in account inflammatory and coagulation disorders associated with COVID-19.
Political Marxism and the Rules of Reproduction of Capitalism: A Historicist Critique
Authors: Knafo Samuel , Teschke Benno
Published: May 2020

Marxism has often been associated with two different legacies. The first rests on a strong exposition and critique of the logic of capitalism, grounded in a systematic analysis of the laws of motion of capitalism as a system. The second legacy refers to a strong historicist perspective grounded in a conception of social relations that emphasises the centrality of power and social conflict to the analysis of history. This article challenges the prominence of structural accounts of capitalism by showing how the tension between these legacies has played out within Political Marxism, both orientations already having co-existed, somewhat uneasily, within Robert Brenner’s original contributions to the Transition Debate. Through this internal critique and re-formulation of Political Marxism, we wish to open a broader debate within Marxism on the need for a more agency-based account of capitalism, which builds more explicitly on the concept of social relations, to recover the historicist legacy of Marxism.
Marx’s Theory of Metabolism in the Age of Global Ecological Crisis
Authors: Saito Kohei
Published: May 2020

When the existing order cannot offer a solution, the solution to climate crisis must come from the radical left, and this is precisely why Karl Marx’s idea of ecosocialism is more important than ever. In this context, it is worth revisiting not only the legacy of István Mészáros’s theory of ‘social metabolism’ and that of his successors – who can be categorised as comprising the ‘metabolic rift school’, which includes John Bellamy Foster, Paul Burkett, and Brett Clark –, but also Karl Marx’s own theory of metabolism. In order to highlight the contemporary importance of Marx’s theory of metabolism after its long suppression in the twentieth century, this paper aims at classifying the three different levels of Marx’s concept of ‘metabolic rift’, which also entails clarifying three different levels of ‘metabolic shift’ as the theoretical foundation for updating Marx’s theory of postcapitalism in the age of global ecological crisis.
Do Ultrafine Cloud Condensation Nuclei Invigorate Deep Convection?
Authors: Grabowski Wojciech W. , Morrison Hugh
Published: May 2020

Numerical simulations of the impact of ultrafine cloud condensation nuclei (CCN) on deep convection are analyzed to investigate the idea proposed by Fan et al. that addition of ultrafine CCN to an otherwise pristine environment leads to convective invigoration. The piggybacking methodology is applied, allowing rigorous separation of the impact of aerosols from different flow realizations that typically occur when even a small element of the model physics or modeling setup is changed. The setup follows the case of daytime convective development over land based on observations during the Large-Scale Biosphere–Atmosphere (LBA) experiment in Amazonia. Overall, the simulated impacts of ultrafine CCN are similar to the previous study by the authors on the impact of pollution on deep convection. There is no convective invigoration above the freezing level, but there is a small invigoration (increase in vertical velocities) below due to the supersaturation and buoyancy differences in conditions with additional ultrafine CCN compared to unperturbed pristine conditions. As in the previous study, the most significant impact is on the upper-tropospheric convective anvils that feature higher cloud fractions in conditions with ultrafine CCN. The increase comes from purely microphysical considerations as the increased cloud droplet concentrations from ultrafine CCN lead to increased ice crystal concentrations and, consequently, smaller sizes and fall velocities, and longer residence times. Mesoscale organization due to low-level shear has a small effect on the simulated ultrafine CCN impacts. Finally, an alternative explanation of increased lightning above oceanic shipping lines seen in satellite observations and argued to result from convective invigoration is provided.
Convective-Scale Sampling Error and Its Impact on the Ensemble Radar Data Assimilation System: A Case Study of a Heavy Rainfall Event on 16 June 2008 in Taiwan
Authors: Wu Pin-Ying , Yang Shu-Chih , Tsai Chih-Chien , Cheng Hsiang-Wen
Published: May 2020

Sampling error stems from the use of ensemble-based data assimilation (EDA) with a limited ensemble size and can result in spurious background error covariances, leading to false analysis corrections. The WRF-LETKF radar assimilation system (WLRAS) is performed separately with 256 and 40 members to investigate the characteristics of convective-scale sampling errors in the EDA and its impact on precipitation prediction based on a heavy rainfall event on 16 June 2008. The results suggest that the sampling errors for this event are sensitive to the relationships between the simulated observations and model variables, the intensity of reflectivity, and how the prevailing wind projects to the radial wind in the areas that the radar cannot resolve U or V wind. The sampling errors lead to an underprediction of heavy rainfall when the horizontal localization radius is inadequately large, but this can be mitigated when a more accurate moisture condition is provided. In addition, being able to use a larger vertical localization plays an important role in providing necessary adjustments for representing the vertical thermodynamical structure of convection, which further improves precipitation prediction. A strategy mitigating the impact of sampling errors associated with the limitation of radial wind measurement by inflating the observation error over sensitive areas can bring benefits to precipitation prediction.
Surgical Intervention for Laryngomalacia: Age-Related Differences in Postoperative Sequelae
Authors: Patel Vijay A. , Adkins David , Ramadan Jad , Williamson Adrian , Carr Michele M.
Published: May 2020

Objective:

Identify risk factors and determine perioperative morbidity of children undergoing surgery for laryngomalacia (LM).

Methods:

A retrospective analysis of the multi-institutional American College of Surgeons National Surgical Quality Improvement Program-Pediatric Database (ACS-NSQIP-P) was performed to abstract patients aged <18 years with LM (ICD-10 code Q31.5) who underwent laryngeal surgery (CPT code 31541) from 2015 to 2017. Analyzed clinical variables include patient demographics, hospital setting, length of stay, medical comorbidities, postoperative complications, readmission, and reoperation.

Results:

A total of 491 patients were identified, 283 were male (57.6%) and 208 were female (42.4%). The mean age at time of surgery was 1.07 years (range .01-17 years). Younger patients were more likely to undergo surgery in the inpatient setting compared to their counterparts ( P < .001). Infants were more likely to have prolonged duration of days from admission to surgery ( P < .001), days from surgery to discharge ( P < .001), and total length of stay ( P<.0010). Finally, there was no significant difference between age groups with respect to 30-day general surgical complications ( P = .189), with an overall low incidence of reintubation (1.2%), readmission (3.1%), and reoperation (1.6%).

Conclusion:

This analysis supports laryngeal surgery as a safe surgical procedure for LM. However, younger children are more likely to undergo operative intervention in the inpatient setting, endure delays from hospital admission to surgical intervention, and experience a prolonged length of stay due to their overall medical complexity. Recognition of key factors may assist in optimizing perioperative risk assessment and promote timely procedural planning in this unique pediatric patient subpopulation.
The Clinical Significance of IGF-1R and Relationship with Epstein–Barr Virus Markers: LMP1 and EBERs in Tunisian Patients with Nasopharyngeal Carcinoma
Authors: Baizig Nehla Mokni , Wided Ben Ayoub , Amine Olfa El , Gritli Said , ElMay Michele
Published: May 2020

Objectives:

Tunisia is in the endemic area of nasopharyngeal carcinoma. Epstein–Barr virus (EBV) based assays have been commonly used as standard markers for screening and monitoring the disease. So, it is very important to find novel factors for the early diagnostic and prognostic evaluation of this cancer. The aim of the study was to evaluate the expression of IGF-1R (Insulin Growth Factor Receptor 1), LMP 1 (Latent Membrane Protein 1) and EBERs (EBV encoded RNAs) in order to determine their correlation with clinicopathologic parameters and survival rates in patients with nasopharyngeal carcinoma (NPC). We also looked for the relationship between these biomarkers.

Methods:

IGF-1R and LMP1 expression was performed by means of immunohistochemical method and EBERs were detected using in situ hybridization of paraffin embedded tumor tissues of 94 patients with nasopharyngeal carcinoma and 45 non-cancerous nasopharyngeal mucosa samples.

Results:

Our findings demonstrated that IGF-1R was over expressed in 47.87% of NPC patients and only in 2.22% of controls. Positive LMP1 expression was detected in 56.38% of NPC patients and all NPC patients were positive for the EBV-encoded RNAs staining. A statistically significant positive correlation was observed between IGF-1R expression and the tumor size ( P < .001). Kaplan–Meier survival curves showed that NPC patients with a strong IGF-1R expression level have shorter median and 5-year Overall Survival than those with weak expression rates (100.15 vs 102.68 months, P = .08). In addition, median and 5-year Disease-Free Survival was significantly lower in the LMP1 positive NPC patients than in the LMP1 negative ones (53.38 vs 93.37 months, P = .03). Moreover, LMP1 expression correlated strongly with IGF-1R expression ( P = .018). The relationship between these two biomarkers could influence patient survival.

Conclusion:

IGF1-R and LMP1 could be valuable prognostic markers in Tunisian NPC patients.
The Drivers of Greenhouse Gas Emissions Intensity Improvements in Major Economies: Analysis of Trends 1995–2009
Authors: Ghosh Madanmohan , Luo Deming , Siddiqui Muhammad Shahid , Rutherford Thomas , Zhu Yunfa
Published: May 2020

This article analyses the trends in greenhouse gas (GHG) emissions intensity over the period 1995–2009 in a mix of developing and developed economies that account for almost two-thirds of global emissions. From the accounting point of view, it distinguishes between the production-based emissions (PBEs) and consumption or demand-based emissions (DBEs). Several studies find that while PBEs in many developed economies during the last decades have stabilised, the DBEs are on the rise. Understanding the relative influence of various factors that have shaped the different patterns of emissions growth can provide us with important policy insights for controlling GHG emissions. The article undertakes a decomposition exercise to understand the variations/fluctuations in both PBEs and DBEs intensities due to changes in technology and changes in economic structure (i.e., composition of aggregate production and final consumption). The main findings of this article are that, over the period 1995–2009, technological change has been the key driver of emissions intensity improvements in both PBEs and DBEs. Emissions intensity improvements in consumption activities have been slower than production, particularly in EU 27. Structural changes or changes in the composition of aggregate production and demand have relatively smaller contribution in overall intensity improvement. Structural shifts in the economy have somewhat negatively contributed to emissions intensity improvements in Canada and China. In India, structural shifts in both production and consumption activities have contributed significantly to emissions intensity improvements. When taking account of trade, changes in the sources of imports have worked against overall emissions intensity improvements, particularly in the developed economies of Canada, European Union (EU 27) and USA, where imports from relatively emissions intensive sources have increased during the period.

JEL: D58, Q56, O13
The Recent Coronavirus (COVID-19) Pandemic: A Review of Issues for Indian Pharmaceutical Exports
Authors: Ahmed Aaheli , Chakraborty Debashis , Bhattacharyya Ranajoy
Published: May 2020

The world today is facing a major challenge in adjusting to the adverse effects of the Coronavirus (COVID-19) spread. Meeting the demand for several key drugs and preventive medical supplies has emerged as major concern in many countries. India has over the years consolidated its position as a major producer and exporter of not only bulk drugs and formulations but also other medical provisions and equipment. The present commentary makes an attempt to understand the possible trade opportunities for India’s pharmaceutical sector in light of the recent export policy interventions. An analysis of the recent export policy adjustments reflects the evolving attitude of the country towards domestic risk perception and commitment to support other countries. The trade opportunities for India are analysed next with the help of select trade indices, and it appears that there is significant scope for enhancing India’s global competitiveness in several product groups. The evolving trends have then been judged by exploring their plausible implications from a theoretical standpoint. It has been concluded that in order to meet the growing world demands for these products, India needs to enhance productivity of the upstream segments through a rigorous policy framework.

JEL: F10, F13, I18
Embracing Both Diagnostic and Dialogic Forms of Organization Development in Order to Exploit and Explore
Authors: Maxton Philip J.
Published: May 2020

As an academic-practitioner, I reflect on my 18 years’ experience as a CEO building a successful, ambidextrous company. The path to success was not linear, and I came to see diagnostic and dialogic forms of OD as complementary leadership-mindsets. Although Diagnostic OD encompasses a rational, planned approach to leadership and Dialogic OD is rooted in the belief that how stakeholders talk is an instrument of change and that change emerges without the need for a set plan, I learnt that both were necessary for achieving organizational ambidexterity. My Diagnostic OD approach to improving exploitation was successful but it failed as an approach to revitalize exploration. Subsequent success was enabled by my also embracing Dialogic OD. While a Diagnostic OD mindset can aid exploitation and a predictive approach toward exploration, a Dialogic OD mindset can better facilitate nonpredictive forms of exploration and, by increasing employee participation, can overcome commonly acknowledged barriers to change.
The Wealth and Competitiveness of National Economic Systems Moderates the Importance of Big Five Personality Dimensions for Life Satisfaction of Employed Persons in 18 Nations
Authors: Bond Michael Harris , Lu Qing , Lun Vivian Miu-Chi , Smith Peter B.
Published: May 2020

Measures of personality have been shown to predict employee satisfaction at work and in life, but these findings arise mostly from research conducted in national cultures of Anglo heritage. To broaden the generality of such findings, we explore the relationships between Big Five dimensions of personality and satisfaction with life across representative samples of 13,265 employed persons in 18 nations. We argue that the strength of relationships between these personality dimensions and life satisfaction will be moderated by a national economic culture characterized by wealth and by competitiveness, since employees derive their satisfaction with life from the personality qualities especially valued in such economic systems. Using data from the World Values Survey and its Wave 6 short-form measure of the Big Five, we find that the dimensions of agreeableness, conscientiousness, and emotional stability predict higher life satisfaction pan-nationally for employed persons. Cross-level moderation effects were found: national wealth enhances the linkage of conscientiousness and emotional stability to life satisfaction; agreeableness links to life satisfaction in wealthier but not in poorer nations; extroversion predicts life satisfaction in more competitive nations but not in less competitive nations. To explain this variability in the relationships of Big Five personality dimensions with the life satisfaction of employed persons, we reason that the national cultures of wealth and of competitiveness surrounding working life establish an incentive context within which enactments of these personality dispositions will generate greater social and personal rewards from the experience of work, yielding higher levels of life satisfaction among employed persons.
Examining Recovery Program Participants by Gender: Program Completion, Relapse, and Multidimensional Status 12 Months After Program Entry
Authors: Logan TK , Cole Jennifer , Walker Robert
Published: May 2020

This study examined individual-level characteristics and factors associated with program completion, relapse, and multidimensional status at follow-up for 213 men and 248 women who entered one of 17 peer-led recovery programs and who completed a follow-up interview 12 months later. Study results found that although there were some significant gender differences at program entry among participants entering Recovery Kentucky, there were few gender differences at follow-up. In addition, although participants had significant psychosocial problems, polysubstance use patterns, and severe substance use disorder (SUD), the majority of both men and women reported completing the program (80.3%), a small minority reported relapse (9.5%), and about one third had worse multidimensional status about 12 months after program entry. Lower quality of life rating at program entry was associated with program completion and with better multidimensional status at follow-up. Study results suggest the recovery program provides an important option for some of the most vulnerable individuals with SUD.
Psychophysical Olfactory Tests and Detection of COVID-19 in Patients With Sudden Onset Olfactory Dysfunction: A Prospective Study
Authors: Lechien Jerome R. , Cabaraux Pierre , Chiesa-Estomba Carlos M. , Khalife Mohamad , Plzak Jan , Hans Stéphane , Martiny Delphine , Calvo-Henriquez Christian , Barillari Maria R. , Hopkins Claire , Saussez Sven
Published: May 2020

Objective:

To investigate the coronavirus disease 2019 (COVID-19) status of patients with initial sudden olfactory anosmia (ISOA) through nasopharyngeal swabs for reverse transcription–polymerase chain reaction (RT-PCR) analysis and to explore their olfactory dysfunctions with psychophysical olfactory evaluation.

Methods:

A total of 78 ISOA patients were recruited from April 6, 2020, to April 10, 2020, through a public call of University of Mons (Mons, Belgium). Patients benefited from nasopharyngeal swabs and fulfilled the patient-reported outcome questionnaire. Among them, 46 patients performed psychophysical olfactory evaluation using olfactory identification testing. Based on the duration of the ISOA, 2 groups of patients were compared: patients with olfactory dysfunction duration ≤12 days (group 1) and those with duration >12 days (group 2).

Results:

In group 1, 42 patients (87.5%) had a positive viral load determined by RT-PCR and 6 patients (12.5%) were negative. In group 2, 7 patients (23%) had a positive viral load and 23 patients (77%) were negative. The psychophysical olfactory evaluation reported that anosmia and hyposmia occurred in 24 (52%) and 11 (24%) patients, respectively. Eleven patients were normosmic. The viral load was significantly higher in patients of group 1 compared with those of group 2.

Conclusions:

Coronavirus disease 2019 was detected in a high proportion of ISOA patients, especially over the first 12 days of olfactory dysfunction. Anosmia is an important symptom to consider in the detection of COVID-19 infection.