Miracle-dz/UniFAR-FTUs huggingface dataset:
Importance of CEO Attention in Influencing Incumbent Responses to Disruptive Innovation

This study investigates incumbent firm responses to disruptive innovation in the rapidly evolving South Korean retail industry. The study explores the factors behind an incumbent firm’s decision-making processes when responding to disruptive innovation and examines the reasons behind varied incumbent responses. It investigates the agents that influence a firm’s decision by conducting the qualitative case study of a South Korean retail giant, Lotte. By collecting archival data from various sources, this paper was able to analyze different interviews and statements of the chief executive officer (CEO). From the analysis, it was determined that the firm’s overall actions were aligned with the CEO’s assertions. Thus, this paper asserts that Lotte’s response to disruptive innovation was directly influenced by the CEO’s attention. The results of this study further add to the discourse of disruptive innovation by highlighting the importance of CEO discretion in deciding a firm’s direction and by further emphasizing the relationship between managerial leadership and innovation.
Strategy for finding a reliable starting point for G 0 W 0 demonstrated for molecules

Many-body perturbation theory in the G 0 W 0 approximation is an increasingly popular tool for calculating electron removal energies and fundamental gaps for molecules and solids. However, the predictive power of G 0 W 0 for molecules is limited by its sensitivity to the density functional theory (DFT) starting point. We introduce a non-empirical scheme, which allows us to find a reliable DFT starting point for G 0 W 0 calculations. This is achieved by adapting the amount of Hartree-Fock-exchange in a hybrid DFT functional. The G 0 W 0 spectra resulting from this starting point reliably predict experimental photoelectron spectra for a test set of 13 typical organic semiconductor molecules.
Effects of Precipitation on the Upper-Ocean Response to a Hurricane

Abstract The effect of precipitation on the upper-ocean response during a tropical cyclone passage is investigated using a numerical model in this paper. For realistic wind forcing and empirical rain rates based on satellite climatology, numerical simulations are performed with and without precipitation forcing to delineate the effects of freshwater forcing on the upper-ocean heat and salt budgets. Additionally, the performance of five mixing parameterizations is also examined for the two forcing conditions to understand the sensitivity of simulated ocean response. Overall, results from 15 numerical experiments are analyzed to quantify the precipitation effects on the oceanic mixed layer and the upper ocean. Simulated fields for the same mixing scheme with and without precipitation indicate a decrease in the upper-ocean cooling of about 0.2°–0.5°C. This is mainly due to reduced mixing of colder water from below induced by the increased stability of the added freshwater. The cooler rainwater contributes a .
Passive and active parental food allocation in a songbird

Abstract Parent–offspring conflict over food allocation can be modeled using two theoretical frameworks: passive (scramble competition) and active choice (signaling) resolution models. However, differentiating between these models empirically can be challenging. One possibility involves investigating details of decision-making by feeding parents. Different nestling traits, related to competitive prowess or signaling cryptic condition, may interact additively or non-additively as predictors of parental feeding responses. To explore this, we experimentally created even-sized, small broods of pied flycatchers and manipulated nestling cryptic quality, independently of size, by vitamin E supplementation. We explored how interactions between nestling cryptic condition, size, signals, and spatial location predicted food allocation and prey-testing by parents. Parents created the potential for spatial scramble competition between nestlings by feeding from and to a narrow range of nest locations. Heavier supplemented nestlings grew faster and were more likely to access profitable nest locations. However, the most profitable locations were not more contested, and nestling turnover did not vary in relation to spatial predictability or food supply. Postural begging was only predicted by nestling hunger and body mass, but parents did not favor heavier nestlings. This suggests that size-mediated and spatial competition in experimental broods was mild. Pied flycatcher fathers allocated food in response to nestling position and begging order, while mothers seemingly followed an active choice mechanism involving assessment of more complex traits, including postural intensity interacting with order, position, and treatment, and perhaps other stimuli when performing prey-testings. Differences in time constraints may underlie sex differences in food allocation rules.
Biosensing attributes of Trench Double Gate Junctionless Field Effect Transistor

Biomolecules sensing is turning out to be the most promising area of research due to ever decreasing healthy lifestyle. Field effect transistorized biosensing approach puts its signature as label free, portable and also very careful pathway. In this present work a trench structured dielectric modulated double gate junction-less field effect transistor (TG-DMJLFET) is urbanized using SILVACO ATLAS simulator for label free detection of biomolecules. The as developed structure has two vertically positioned gates in distinct trenches. For immobilizing biomolecules, two cavities are formed in the gate oxide region for dielectric modulation. The dielectric constant (k) has been varied over a wide range of 1 to 12 signifying the sensing of neutral biomolecules. The sensitivity is evaluated in terms of threshold voltage shift. Fin case of neutral biomolecules, the shift in threshold voltage is obtained as 500 mV for change in the di-electric constant (k) ranging from 1 to 12. The device has showed excellent performance in biomolecules sensing.
Root Structure of a Special Generalized Kac

The paper systematically discusses the root structure of a special generalized Kac-Moody algebra . It's extended one point from the finite Coxter diagram B2.At the beginning the paper define a special generalized generalized Cartan matrix (abbreviated as GGCM) and a special generalized Kac-Moody algebra(abbreviated as GK algebra). As a starting point for the special GK algebra it mainly obtain the special imaginary root system, the relationship between reflections determined by imaginary roots and the Weyl group for the special GMC algebra and the purely and the strictly imaginary roots.
The benefit of knowing your linear structures in mammographic images

Certain kinds of abnormalities in x-ray mammograms are associated with specific anatomical structures in particular, linear structures. This association can be exploited to improve the specificity and sensitivity with which the abnormalities can be detected. Here we describe how the detection and classification of linear structures can improve the detectability ( from 0.74 to 0.93) of micro-calcifications and be used as an indication of malignancy (with equal to 0.69). The detection stage uses a non-linear operator and the classification is based on cross-sectional profiles of the detected linear structures.
The alidade temperature behaviour of TM65m antenna and its effects on pointing accuracy

Aimed at the alidade of TM65m antenna, the distributions of temperature field and effects of thermal deformations on pointing accuracy were analyzed based on thermometers and inclinometer. The alidade temperature and cross-elevation tilt were recorded for one year when the antenna was at different azimuth and elevation angles. And, the emphasis is on studying the data of sunny days in summer and winter during the antenna parked its home position (azimuth angle=155°, elevation angle=90°). The results show the maximum temperature difference between day and night is 14.6 °C in summer and is 27 °C in winter. In winter, the larger temperature difference, shorter sunshine time and later sunrise contribute to the temperature variation per unit time is larger. In addition, pointing offset was checked by scanning polestar for continuous 24 hours. From the results obtained so far, it seems that the elevation offset caused by the alidade temperature variation is more than 20 arcsec from 8:00 am to 10:00 am. The research results provide a base for the enhancement of pointing accuracy.
Bloodstream Infection and Gram-Negative Resistance: The Role for Newer Antibiotics

Gram-negative resistance remains a major challenge. Rates of in vitro resistance to commonly utilized antibiotics have skyrocketed over the last decade. Clinicians now encounter multidrug-resistant organisms routinely. Fortunately, newer agents, such as ceftazidime–avibactam, ceftolozone–tazobactam, meropenem–vaborbactam, and cefiderocol, have been developed and are now available for use against these pathogens. Clinical trials with these novel therapies have focused on multiple infection types ranging from complicated urinary tract infections to nosocomial pneumonia. Nonetheless, there remains little information about the efficacy of these drugs for bacteremia. To better appreciate the types and limitations of the evidence supporting the role for these unique molecules in bloodstream infection, one requires an appreciation of the initial clinical trials supporting the regulatory approval of these antibiotics. Furthermore, physicians must understand the subsequent case series and reports specifically focusing on outcomes for patients with bacteremia treated with these drugs. Despite the limitations of the data and reports relating to treatment for bacteremia with these antibiotics, each agent appears to be efficacious and can provide good outcomes in bloodstream infections due to resistant pathogens.
Permanent Magnet Electrodynamic Suspension System Integrated With a Car: Design, Implementation, and Test

In this article, a permanent magnet electrodynamic suspension (PMEDS) system integrated with a car has been developed by our group, along with a 100-m-long test track made of copper. The entire vehicle weighs 2.8 ton and is freely suspended in air over 35 mm without a lateral constraint on guideway. The car uses its own wheels and engine to provide a take-off speed for the PMEDS system, eliminating the excessive costs of the motor, with a maximum speed of 70 km/h. First, a new topology structure equipped with the damping magnets is presented. Afterward, the onboard magnets and guideway are designed via the simulation method verified by the high-speed rotary experimental platform with a diameter of 2500 mm, clarifying the mapping between the electromagnetic forces and structure parameters. The suspension frame and gap adjustment mechanism are developed, and a complete test system is built to monitor the levitation gap, accelerations, and deflection angle. Lastly, the integrated PMEDS system is implemented and tested. In-house experiment and line test results not only reveal that the PMEDS has a significant weak guidance capability but also confirm the effectiveness of the proposed damping magnets. Through the damping magnets, the maximum lateral deflection is limited to less than 11°. The tested levitation–drag ratio is in general agreement with the simulation results. The great suspension capacity of the PMEDS system can be visually demonstrated. This article conducts the free suspension test of the PMEDS system for the first time in China, which can open up prospects for further engineering applications.
Exploring partially observable Markov decision processes by exploting structure and heuristic information

This thesis is about chance and choice, or decisions under uncertainty. The desire for creating an intelligent agent performing rewarding tasks in a realistic world urges for working models to do sequential decision making and planning. In responding to this grand wish, decision-theoretic planning (DTP) has evolved from decision theory and control theory, and has been applied to planning in artificial intelligence. Recent interest has been directed toward Markov Decision Processes (MDPs) introduced from operations research. While fruitful results have been tapped from research in fully observable MDPs , partially observable M D P s (POMDPs) are still too difficult to solve as observation uncertainties are incorporated. Abstraction and approximation techniques become the focus. This research attempts to enhance P O M D P s by applying A l techniques. In particular, we transform the linear P O M D P constructs into a structured representation based on binary decision trees and Bayesian Networks to achieve compactness. A handful of tree-oriented operations is then developed to perform structural belief updates and value computation. Along
Heme Oxygenase-1 Expression in Dendritic Cells Contributes to Protective Immunity against Herpes Simplex Virus Skin Infection

Herpes simplex virus type 1 (HSV-1) and type 2 (HSV-2) infections are highly prevalent in the human population and produce mild to life-threatening diseases. These viruses interfere with the function and viability of dendritic cells (DCs), which are professional antigen-presenting cells that initiate and regulate the host’s antiviral immune responses. Heme oxygenase-1 (HO-1) is an inducible host enzyme with reported antiviral activity against HSVs in epithelial cells and neurons. Here, we sought to assess whether HO-1 modulates the function and viability of DCs upon infection with HSV-1 or HSV-2. We found that the stimulation of HO-1 expression in HSV-inoculated DCs significantly recovered the viability of these cells and hampered viral egress. Furthermore, HSV-infected DCs stimulated to express HO-1 promoted the expression of anti-inflammatory molecules, such as PDL-1 and IL-10, and the activation of virus-specific CD4+ T cells with regulatory (Treg), Th17 and Treg/Th17 phenotypes. Moreover, HSV-infected DCs stimulated to express HO-1 and then transferred into mice, promoted the activation of virus-specific T cells and improved the outcome of HSV-1 skin infection. These findings suggest that stimulation of HO-1 expression in DCs limits the deleterious effects of HSVs over these cells and induces a favorable virus-specific immune response in the skin against HSV-1.
Lyapunov-like stability theorems for continuous-time fuzzy control systems

The essential characteristics of fuzzy logic control are analysed in this paper. The locality of fuzzy control and the interpolation among fuzzy rules may be the most important characteristics of fuzzy control systems. Based on these two characteristics a new Lyapunov-like stability analysis approach is developed for both Mamdani and Takagi-Sugeno type fuzzy control systems. In this approach we apply the theory of generalized dynamical systems and contingent equations. Thus, the method can be used for both model-free and model-based fuzzy controller designs. Finally, an example is given to illustrate the application of the method.
MapReduce for Graphs Processing: New Big Data Algorithm for 2-Edge Connected Components and Future Ideas

Finding connectivity in graphs has numerous applications, such as social network analysis, data mining, intra-city or inter-cities connectivity, neural network, and many more. The deluge of graph applications makes graph connectivity problems extremely important and worthwhile to explore. Currently, there are many single-node algorithms for graph mining and analysis; however, those algorithms primarily apply to small graphs and are implemented on a single machine node. Finding 2-edge connected components (2-ECCs) in massive graphs (billions of edges and vertices) is impractical and time-consuming, even with the best-known single-node algorithms. Processing a big graph in a parallel and distributed fashion saves considerable time to finish processing. Moreover, it enables stream data processing by allowing quick results for vast and continuous nature data sets. This research proposes a distributed and parallel algorithm for finding 2-ECCs in big undirected graphs (subsequently called “ $BiECCA$ ”) and presents its time complexity analysis. The proposed algorithm is implemented on a MapReduce framework and uses an existing algorithm to find connected components (CCs) in a graph as a sub-step. Finally, we suggest a few novel ideas and approaches as extensions to our work.
New approach to collective phenomena in superconductivity models

A new approach to collective phenomena in superconductivity models is presented. In this approach nonlinear spinor models are converted into equivalent theories involving fermions and collective bosonic states. For a wide class of nonlinear spinor theories, interactions among fermions and collective states are of the renormalizable kind, and hence these models themselves turn out to be renormalizable. The equivalence of various four-fermion theories to known renormalizable models is pointed out. The original Nambu--Jona-Lasinio model, for instance, is shown to be equivalent to the linear sigma model. Detailed discussions are given on the origin of massless fields and the local gauge invariance. Implications of Pauli-Guersey-type symmetry in spinor theories are also expounded. (AIP)
Spatial Fisher Vectors for Image Categorization

We introduce an extension of bag-of-words image representations to encode spatial layout. Using the Fisher kernel framework we derive a representation that encodes the spatial mean and the variance of image regions associated with visual words. We extend this representation by using a Gaussian mixture model to encode spatial layout, and show that this model is related to a soft-assign version of the spatial pyramid representation. We also combine our representation of spatial layout with the use of Fisher kernels to encode the appearance of local features. Through an extensive experimental evaluation, we show that our representation yields state-of-the-art image categorization results, while being more compact than spatial pyramid representations. In particular, using Fisher kernels to encode both appearance and spatial layout results in an image representation that is computationally efficient, compact, and yields excellent performance while using linear classifiers.
Divergences for prototype-based classification and causal structure discovery

Dit proefschrift bestaat uit twee delen. In het eerste deel beschrijven we hoe de op prototypen gebaseerde classificator LVQ uitgebreid kan worden door gebruik te maken van maten uit de informatie theorie. Daarnaast vergelijken we verschillende manieren van datarepresentatie in deze LVQ configuratie, in dit geval histogrammen van foto’s, SIFT- en SURF-kenmerken. We tonen hoe hiervoor een enkele gecombineerde afstandsmaat kan worden geformuleerd, door de afzonderlijke afstandsmaten samen te nemen. In het tweede deel onderzoeken we het vinden van causale verbanden en toepassingen op problemen die uit het leven zijn gegrepen. Daarnaast verkennen we de combinatie met relevantie leren in LVQ en tonen we enkele toepassingen.
Explicit Expression of the Stationary Values of Young's Modulus and the Shear Modulus for Anisotropic Elastic Materials

Explicit expressions of the direction n and the stationary values (maximum, minimum and saddle point) of Young's modulus E ( n ) for orthotropic, tetragonal, trigonal, hexagonal and cubic materials are presented. For the shear modulus G ( n, m ), explicit expressions of the extrema (maximum and minimum) and the two mutually orthogonal unit vectors n, m are given for cubic and hexagonal materials. We also present a general procedure for computing the extrema of G ( n, m ) for more general anisotropic elastic materials. It is shown that Young's modulus E ( n ) can be made as large as we wish for certain n without assuming that the elastic compliance s 11 , s 22 or s 33 is very small. As to the shear modulus G ( n,m ), it can be made as large as we wish for certain n and m without assuming that any one of the elastic compliance s αβ is very small. We also show that Young's modulus E ( n ) can be independent of n for orthotropic and hexagonal materials while the shear modulus G ( n, m ) can be independent of n and m for hexagonal materials.
Factors affecting functional outcomes after surgery to repair extensive volar forearm lacerations with nerve injuries identified via quantitative and qualitative methods

Objectives We aimed to investigate factors affecting the functional outcomes of patients with extensive volar forearm lacerations combined with nerve injuries who underwent surgery. Patients and methods Between January 2012 and December 2018, a total of 71 patients (58 males, 13 females; mean age: 41±12.1 years; range, 20 to 66 years) with extensive volar forearm lacerations treated in our center were retrospectively analyzed. Demographic data and injury details of the patients were recorded. The functional results were quantitatively evaluated using the Rosén-Lundborg protocol (RLP) and qualitatively evaluated using the Quick Disability of Arm, Shoulder, and Hand (QuickDASH) scale. Results The mean follow-up time 69.8±36.7 (range, 18 to 148) months. The mean final RLP and QuickDASH scores were 2.17±0.4 and 8.03±10.55, respectively. There were no major complications such as infection, necrosis, re-rupture of a structure, or amputation. Patients with combined median and ulnar nerve injuries had poorer RLP scores than the others. Patients with combined median and ulnar nerve injuries, combined radial and ulnar arterial injuries, and who were of low education status, had lower QuickDASH scores than the others. Conclusion The main factors affecting long-term functional outcomes are a combined artery or nerve injury and a low education status. Favorable results can be achieved with the cooperation of experienced surgeons and hand rehabilitation specialists for patients with severe hand injuries.
From Industrial Food Waste to Bioactive Ingredients: A Review on the Sustainable Management and Transformation of Plant-Derived Food Waste

According to the United Nations, approximately one-third of the food produced for human consumption is wasted. The actual linear “Take-Make-Dispose” model is nowadays obsolete and uneconomical for societies and the environment, while circular thinking in production systems and its effective adoption offers new opportunities and benefits. Following the “Waste Framework Directive” (2008/98/CE), the European Green Deal, and the actual Circular Economy Action Plan, when prevention is not possible, recovering an unavoidable food waste as a by-product represents a most promising pathway. Using last year’s by-products, which are rich in nutrients and bioactive compounds, such as dietary fiber, polyphenols, and peptides, offer a wake-up call to the nutraceutical and cosmetic industry to invest and develop value-added products generated from food waste ingredients.