Miracle-dz/UniFAR-FTUs huggingface dataset:
How Does Tesla Motors Achieve Competitive Advantage in the Global Automobile Industry?

This study analyzed the growth background of Tesla Motors regarded as a new leader in the global automobile industry while deriving its environment and core competencies based on the resource-based view (RBV), which are widely used as the tool in building theoretical frameworks in management research. First of all, Tesla Motors has a lot of threats such as the threats of rivalry, buyers, suppliers, and substitutes. Also, Tesla Motors has abundant resources based on Elon musk’s specific leadership, contributing to gaining dynamic capabilities and ultimately achieving sustainable competitive advantage. In addition, Tesla Motors pursued differentiated strategies such as direct sales, service, charger’s network simultaneously achieving creative innovation and quantitative efficiency. Tesla Motors successfully overcame and sublimated these threats and weaknesses, it could create more differentiated and sustainable competitive advantages. This study offers useful implications to multinational firms by systematically investigating the specific features and growth strategies of Tesla Motors as a benchmark.
Fear, freaks, and fat phobia: an examination of how My 600 Lbs Life displays “fat” Black women

ABSTRACT This article examines how Black women are represented on The Learning Channel’s (TLC) My 600 Lbs Life (M6L) and explores the racist, sexist, and ableist narratives that are used to incite fatphobia through the “enfreakment” of its participants. It is theorized that the combination of these narratives not only work to bolster the “white slender ideal” by reflecting societal attitudes that fuse anti-fatness with anti-blackness, but utilizes “freak-ish” images of “fat” Black women to validate race, sex, and disability prejudice and hierarchies.
Association of post-COVID-19 fatigue with mental health problems and sociodemographic risk factors

ABSTRACT Purpose : Our objective was to obtain an initial prevalence estimate of post-COVID-19 fatigue in Turkey and identify psychological and sociodemographic risk factors associated with post-COVID-19 fatigue. Materials and methods : The data were collected from a cross-sectional community-based survey among the population recovered from COVID-19 in Turkey. A sociodemographic data form, the Fatigue Assessment Scale (FAS), and the Depression Anxiety Stress Scale-21 (DASS-21) were included in the survey. Participants were divided into two groups, fatigued and non-fatigued, based on their FAS scores. Sociodemographic and psychological characteristics of the two groups were examined with comparative analyses, and binary regression analysis identified predictors of post-COVID-19 fatigue. Results : The completed survey (N = 275) included individuals from 50 cities in Turkey who reported a prior COVID-19 illness. The mean age was 34.67 ± 8.35 years and 58.2% were female. Significant fatigue was detected in 56.4% (155) of participants. Female gender, history of psychiatric illness, history of psychiatric drug use, and current psychiatric drug use were significantly higher in the fatigued group than in the non-fatigued group (p < 0.01). In addition, the fatigued group showed significantly higher scores on all domains of the FAS and DASS-21 scales than the non-fatigued group (p < 0.01). Female gender and a high DASS-21 total score were predictors of post-COVID-19 fatigue. Conclusion : Patients with post-COVID-19 fatigue should be evaluated for mental health issues.
CD4+CD25+ Regulatory T Cells in Intracranial Thrombi Are Inversely Correlated with Hemorrhagic Transformation after Thrombectomy: A Clinical-Immunohistochemical Analysis of Acute Ischemic Stroke

Mechanical thrombectomy is not only effective for managing patients with acute ischemic stroke (AIS), but it also enables a valuable histological analysis of thrombi. Previous studies indicated that regulatory T cells (Treg) adoptive transfer might alleviate the hemorrhagic transformation. However, whether Treg in intracranial thrombi correlates with hemorrhagic transformation after mechanical thrombectomy remains unclear. This study mainly analyzed the colocation of Treg markers in serial thrombus sections stained serially for CD4 and CD25 in groups of hemorrhagic or nonhemorrhagic transformation. Second, to investigate whether these immunohistochemical parameters could provide any additional information beyond hemorrhagic transformation, we compared the overlap between Treg markers among other groups, such as functional outcomes, stroke subtypes, and gender. Our results showed that the number of CD4+CD25+ Treg cells was lower in the hemorrhagic transformation thrombi than in the nonhemorrhagic group (p < 0.001) but there were no significant differences otherwise. The present finding of CD4+CD25+ Treg cell reductions in thrombi associated with hemorrhagic transformation provides the histological evidence supporting that thromboinflammation might involve in the pathological process of an acute stroke after mechanical thrombectomy.
Could significant regression be treated as insignificant: An anomaly in statistics?

Abstract Literature has found that regression of independent (nearly) nonstationary time series could be spurious. We incorporate this idea to examine whether significant regression could be treated as insignificant in some situations. To do so, we conjecture that significant regression could appear significant in some cases but it could become insignificant in some other cases. To check whether our conjecture could hold, we set up a model in which both dependent and independent variables Yt and Xt are the sum of two variables, say and , in which and are independent and (nearly) nonstationary AR(1) time series such that and . Following this model-setup, we design some situations and the algorithm for our simulation to check whether our conjecture could hold. We find that on the one hand, our conjecture could hold that significant regression could appear significant in some cases when α 1 and α 2 are of different signs. On the other hand, our findings show that our conjecture does not hold and significant regression cannot be treated as insignificant when α 1 and α 2 are of the same signs. We note that as far as we know, our article is the first article to discover that significant regression can be treated as insignificant in some situations. Thus, the main contribution of our article is that our article is the first article to discover that significant regression can be treated as insignificant in some situations and remains significant in other situations. We believe that our discovery could be an anomaly in statistics. Our findings are useful for academics and practitioners in their data analysis in the way that if they find the regression is insignificant, they should investigate further whether their analysis falls into the problem studied in our article.
The Long Shadow of Agrarian Conflict: Agrarian Inequality and Voting in Spain

Abstract This article studies the persistent effects of past agrarian inequality on contemporary voting preferences. Although Western European countries became industrial (and later post-industrial) economies, the political effects of the agrarian cleavage are still visible in those countries in which the agrarian issue was dominant in the interwar period (the industrial laggards). Looking at the spatial variation in voting patterns in the fifteen elections held in Spain since 1977, we show through mediation analysis that areas with high historical agrarian inequality have higher levels of leftist vote. We examine two transmission channels: one economic (related to backwardness); the other political (related to family transmission of political allegiances). A survey analysis provides evidence in favour of family transmission. A brief exploration of other cases confirms the general argument: a similar effect is found in Italy (an industrial laggard), but not in England (an early industrializer).
Numerical Bifurcation Analysis of a Film Flowing over a Patterned Surface through Enhanced Lubrication Theory

The bifurcation analysis of a film falling down an hybrid surface is conducted via the numerical solution of the governing lubrication equation. Instability phenomena, that lead to film breakage and growth of fingers, are induced by multiple contamination spots. Contact angles up to 75∘ are investigated due to the full implementation of the free surface curvature, which replaces the small slope approximation, accurate for film slope lower than 30∘. The dynamic contact angle is first verified with the Hoffman–Voinov–Tanner law in case of a stable film down an inclined plate with uniform surface wettability. Then, contamination spots, characterized by an increased value of the static contact angle, are considered in order to induce film instability and several parametric computations are run, with different film patterns observed. The effects of the flow characteristics and of the hybrid pattern geometry are investigated and the corresponding bifurcation diagram with the number of observed rivulets is built. The long term evolution of induced film instabilities shows a complex behavior: different flow regimes can be observed at the same flow characteristics under slightly different hybrid configurations. This suggest the possibility of controlling the rivulet/film transition via a proper design of the surfaces, thus opening the way for relevant practical application.
Multicellular Ovarian Cancer Model for Evaluation of Nanovector Delivery in Ascites and Metastatic Environments

A novel multicellular model composed of epithelial ovarian cancer and fibroblast cells was developed as an in vitro platform to evaluate nanovector delivery and ultimately aid the development of targeted therapies. We hypothesized that the inclusion of peptide-based scaffold (PuraMatrix) in the spheroid matrix, to represent in vivo tumor microenvironment alterations along with metastatic site conditions, would enhance spheroid cell growth and migration and alter nanovector transport. The model was evaluated by comparing the growth and migration of ovarian cancer cells exposed to stromal cell activation and tissue hypoxia. Fibroblast activation was achieved via the TGF-β1 mediated pathway and tissue hypoxia via 3D spheroids incubated in hypoxia. Surface-modified nanovector transport was assessed via fluorescence and confocal microscopy. Consistent with previous in vivo observations in ascites and at distal metastases, spheroids exposed to activated stromal microenvironment were denser, more contractile and with more migratory cells than nonactivated counterparts. The hypoxic conditions resulted in negative radial spheroid growth over 5 d compared to a radial increase in normoxia. Nanovector penetration attenuated in PuraMatrix regardless of surface modification due to a denser environment. This platform may serve to evaluate nanovector transport based on ovarian ascites and metastatic environments, and longer term, it provide a means to evaluate nanotherapeutic efficacy.
Identification of Autophagy-Related Prognostic Signature and Analysis of Immune Cell Infiltration in Low-Grade Gliomas

Autophagy plays an important role in cancer. Many studies have demonstrated that autophagy-related genes (ARGs) can act as a prognostic signature for some cancers, but little has been known in low-grade gliomas (LGG). In our study, we aimed to establish a prognostical model based on ARGs and find prognostic risk-related key genes in LGG. In the present study, a prognostic signature was constructed based on a total of 8 ARGs (MAPK8IP1, EEF2, GRID2, BIRC5, DLC1, NAMPT, GRID1, and TP73). It was revealed that the higher the risk score, the worse was the prognosis. Time-dependent ROC analysis showed that the risk score could precisely predict the prognosis of LGG patients. Additionally, four key genes (TGFβ2, SERPING1, SERPINE1, and TIMP1) were identified and found significantly associated with OS of LGG patients. Besides, they were also discovered to be strongly related to six types of immune cells which infiltrated in LGG tumor. Taken together, the present study demonstrated the promising potential of the ARG risk score formula as an independent factor for LGG prediction. It also provided the autophagy-related signature of prognosis and potential therapeutic targets for the treatment of LGG.
LDPC Hardware Acceleration in 5G Open Radio Access Network Platforms

The Open Radio Access Network (RAN) concept has been gaining wide acceptance in recent network architectures, including 5G New Radio (NR) network deployments. Current Open RAN radio implementation efforts, aim at integrating several white-box hardware elements and executing digital processing on open-source software. When building such a software-based, 5G Open RAN platform, challenges include achieving real-time execution times for demanding computational blocks of the 5G NR physical layer processing, such as Low Density Parity Check (LDPC) decoding. In this context, having already identified both the capabilities as well as the challenges that Field-programmable Gate Arrays (FPGAs) offer for accelerating LDPC, we present our novel LDPC FPGA accelerator system. In this paper, we contribute the implementation details of our FPGA accelerator design as well as the process of integrating the accelerator with OpenAirInterface (OAI), the basis for our 5G NR platform. For the first time in the literature, we show an FPGA-based LDPC accelerator fully integrated with a complete software platform, that is able to achieve more than 1.6Gbps decoding throughput and up to 13 times faster execution times compared to single core software implementations. Finally, in our results, we show that LDPC encoding is more challenging to accelerate due to lower computational complexity.
Realization of microwave amplification, attenuation, and frequency conversion using a single three-level superconducting quantum circuit

Using different configurations of applied strong driving and weak probe fields, we find that only a single three-level superconducting quantum circuit (SQC) is enough to realize amplification, attenuation and frequency conversion of microwave fields. Such a three-level SQC has to possess $\Delta$-type cyclic transitions. Different from the parametric amplification (attenuation) and frequency conversion in nonlinear optical media, the real energy levels of the three-level SQC are involved in the energy exchange when these processes are completed. We quantitatively discuss the effects of amplification (attenuation) and the frequency conversion for different types of driving fields. The optimal points are obtained for achieving the maximum amplification (attenuation) and conversion efficiency. Our study provides a new method to amplify (attenuate) microwave, realize frequency conversion, and also lay a foundation for generating single or entangled microwave photon states using a single three-level SQC.
Evaluation of Ultrasonication and Agitation Extraction Methods at Different Conditions on the Phenolic Composition and Antioxidant Activities of Mammillaria prolifera

The study focuses on the comparative evaluation of extraction methods (ultrasonication and agitation) based on phenolic composition and antioxidative activities of Mammillaria prolifera and it is the first report on this subject. The effects of extraction conditions of temperature (25° and 60°), time (15, 30 and 60 min) and solvent type (water and 70 % and 100 % methanol) on total phenolic compounds, 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) and 2,2-diphenyl-1-picrylhydrazyl anti-radical activities and ferric ion reducing antioxidant power values were determined. Moreover, the phenolic acid compositions of the extracts were investigated by high performance liquid chromatography. The extracts prepared with the ultrasonic method showed stronger antioxidant activity than those prepared with agitation methods. In both methods total phenolic compounds and antioxidant activity values were the lowest in the aqueous extracts. The results showed a positive correlation observed between total phenolic compounds and antioxidant activities of the studied extracts. The optimal conditions for the extraction of phenolic compounds from Mammillaria prolifera were found as 60 min extraction time, 60° extraction temperature and 70 % methanol concentration by using the ultrasonication method. Notably, protocatechualdehyde, gallic acid, para hydroxy benzoic acid and ferulic acid were identified in Mammillaria prolifera by using the high performance liquid chromatography-diode array detector system and 14 phenolic standards. Consequently, Mammillaria prolifera cladodes can be used in food or pharmaceutical practices, as a potential natural source of antioxidants.
Robust modeling of mixture probabilistic principal component analysis and process monitoring application

In this article, a robust modeling strategy for mixture probabilistic principal component analysis (PPCA) is proposed. Different from the traditional Gaussian distribution driven model such as PPCA, the multivariate student t-distribution is adopted for probabilistic modeling to reduce the negative effect of outliers, which is very common in the process industry. Furthermore, for handling the missing data problem, a partially updating algorithm is developed for parameter learning in the robust mixture PPCA model. Therefore, the new robust model can simultaneously deal with outliers and missing data. For process monitoring, a Bayesian soft decision fusion strategy is developed which is combined with the robust local monitoring models under different operating conditions. Two case studies demonstrate that the new robust model shows enhanced modeling and monitoring performance in both outlier and missing data cases, compared to the mixture probabilistic principal analysis model. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2143–2157, 2014
Heuristic Approaches With Reinforced Parameter Tuning for the Car Sequencing Problems With Block Batches

Motivated by the practical supply chain management of the automobile industry, we study the car sequencing problem (CSP) that minimize the conflicts arising from scheduling cars into an assembly line. The CSP is a well established problem, subject to the paint batching constraints to reduce the the costs for color changes and capacity constraints in the assembly shop to level the usage of the options. However, the existing approaches to this problem do not take into account the block batches, which desires a consecutive production batch of cars requiring a certain option. This requirement often occurs when specialized labor time window is short in the customized car production scenario, and renders additional complexities to the traditional car sequencing problem. In this paper, we propose a novel model to deals with these constraints and simultaneously generate the sequencing and replenishment decisions. In addition to our model formulation, we develop two math-heuristic approaches to solve the propose large-scale car sequencing problem. The selected heuristics are based on relax-and-fix procedures, fix-and-optimize procedures and variable neighborhood search. To solve the large-sized instances (commercial solvers, i.e., Cplex, cannot provide a feasible solution within 1 hour), we design and implement a reinforced parameter tuning mechanism to dynamically select the parameter values, so as to speed up the search process. The proposed models and heuristics are tested on compatible instances from the benchmark in the literature (CSPLib), as well as large-sized instances generated from real-world cases. We report on extensive computational experiments, and provide basic managerial insights into the planning process.
Enterprise systems and organisational agility: Conceptualizing the link

The impact of enterprise systems (ES) on organisational agility (OA) is an under-researched area. Given the trends that most large organisations are moving towards ES and investing heavily on ES infrastructure and the increasing demand for agility, lack of research on ES and OA is a critical oversight. Using insights from the resource based view and dynamic capability theories; this paper argues that organisations can exploit the power of ES to improve their agility in three significant ways - by creating an ES enabled sensing capability and by constantly building ES enabled responding capability. We also argue that the quality of the ES infrastructure which we refer to as ES competence provides the necessary technical and business platform for deploying ES in building and rebuilding sensing and responding capabilities. Our theorising makes an original contribution to IS research by extending current ES research which thus far has focused on ES implementation issues.
Participatory IT Design: Designing for Business and Workplace Realities

The goal of participatory IT design is to set sensible, general, and workable guidelines for the introduction of new information technology systems into an organization. Reflecting the latest systems-development research, this book encourages a business- oriented and socially sensitive approach that takes into consideration the specific organizational context as well as first-hand knowledge of users' work practices and allows all stakeholdersusers, management, and staffto participate in the process. Participatory IT Design is a guide to the theory and practice of this process that can be used as a reference work by IT professionals and as a textbook for classes in information technology at introductory through advanced levels. Drawing on the work of a ten-year research program in which the authors worked with Danish and American companies, the book offers a framework for carrying out IT design projects as well as case studies that stand as examples of the process.The method presented in Participatory IT Designknown as the MUST method, after a Danish acronym for theories and methods of initial analysis and design activitieswas developed and tested in thirteen industrial design projects for companies and organizations that included an American airline, a multinational pharmaceutical company, a national broadcasting corporation, a multinational software house, and American and Danish universities. The first part of the book introduces the concepts and guidelines on which the method is based, while the second and third parts are designed as a practical toolbox for utilizing the MUST method. Part II describes the four phases of a design projectinitiation, in-line analysis, in-depth analysis, and innovation. Part III explains the method's sixteen techniques and related representation tools, offering first an overview and then specific descriptions of each in separate sections.