Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantum Correlations in Quantum Cloning

We utilize quantum discord to charecterize the correlation present in Buzek-Hillery quantum copying machine \cite{bh} (not necessarily universal quantum cloning machine). In other words we quantify the correlation present beetween the original and the replicated copy of the quantum state obtained at the outport port, Interestingly, we find some domain of the machine parameter, for which the quantum disord is non negative even in the mere absence of entanglement. These non zero values of the quantum discord is a strong signature for the presence of non classical correlations. This is one step forward evidence in the support of the fact that quantum discord and entanglement are not synonymous.
CLIMATE IMPACT OF SWEDISH IMPORTS OF AMERICAN LOBSTER (HOMARUS AMERICANUS) FROM NORTH AMERICA A comparison of alternative supply chains using life cycle assessment

Annually, around 400 tonnes of live and frozen American lobster ( Homarus americanus ) are imported to Sweden from North America. Live American lobster released into the wild poses a threat to European lobster ( Homarus gammarus ). While an environmental evaluation of the fishery existed, the impacts of importing live and frozen lobster by different transport modes had not yet been investigated. In this study, Life Cycle Assessment (LCA) methodology was used to study greenhouse gas emissions from the entire supply chain. The study builds on the existing LCA of the fisheries, updated using recent data on fishing effort and landings. An inverse correlation between fuel use in the fishery and landings per unit of effort was assumed. The main objective was to compare two product forms; live and frozen, transported using three modes; airfreight (live), sea shipping (frozen) and sea shipping in specialized containers (live) with regard to their climate impact. The fuel efficiency of the fisheries over time was also analysed. Results indicate that the fisheries have become more efficient since 2006. Importing live lobster, using airfreight and sea shipping emits almost forth fold and double the amount of greenhouse gasses (GHG), respectively, than frozen lobster. So, from an environmental perspective, both in terms of GHG emissions and to mitigate the biological risks, importing frozen lobster is the most sustainable option when importing lobster to Sweden. The results can be seen as a guide for both policy makers as well as consumers and importers, to make way for a more sustainable consumption of lobster.
Robust adaptive fault‐tolerant tracking control of multiple time‐delays systems with mismatched parameter uncertainties and actuator failures

This study deals with the problem of robust adaptive fault‐tolerant tracking for uncertain systems with multiple delayed state perturbations, mismatched parameter uncertainties, external disturbances, and actuator faults including loss of effectiveness, outage, and stuck. It is assumed that the upper bounds of the delayed state perturbations, the external disturbances and the unparameterizable time‐varying stuck faults are unknown. Then, by estimating online such unknown bounds and on the basis of the updated values of these unknown bounds from the adaptive mechanism, a class of memoryless state feedback fault‐tolerant controller with switching signal function is constructed for robust tracking of dynamical signals. Furthermore, by making use of the proposed adaptive robust tracking controller, the tracking error can be guaranteed to be asymptotically zero in spite of multiple delayed state perturbations, mismatched parameter uncertainties, external disturbances, and actuator faults. In addition, it is also proved that the solutions with tracking error of resulting adaptive closed‐loop system are uniformly bounded. Finally, a simulation example for B747‐100/200 aircraft system is provided to illustrate the efficiency of the proposed fault‐tolerant design approach. Copyright © 2014 John Wiley & Sons, Ltd.
Automated Knowledge Discovery from Functional Magnetic Resonance Images using Spatial Coherence

Functional Magnetic Resonance Imaging (fMRI) has the potential to unlock many of the mysteries of the brain. Although this imaging modality is popular for brain-mapping activities, clinical applications of this technique are relatively rare. For clinical applications, classification models are more useful than the current practice of reporting loci of neural activation associated with particular disorders. Also, since the methods used to account for anatomical variations between subjects are generally imprecise, the conventional voxel-by-voxel analysis limits the types of discoveries that are possible. This work presents a classification-based framework for knowledge discovery from fMRI data. Instead of voxel-centric knowledge discovery, this framework is segment-centric, where functional segments are clumps of voxels that represent a functional unit in the brain. With simulated activation images, it is shown that this segment-based approach can be more successful for knowledge discovery than conventional voxel-based approaches. The spatial coherence principle refers to the homogeneity of behavior of spatially contiguous voxels. Auto-threshold Contrast Enhancing Iterative Clustering (ACEIC) - a new algorithm based on the spatial coherence principle is presented here for functional segmentation. With benchmark data, it is shown that the ACEIC method can achieve higher segmentation accuracy than Probabilistic Independent Component Analysis - a popular method used for fMRI data analysis. The spatial coherence principle can also be exploited for voxel-centric image-classification problems. Spatially Coherent Voxels (SCV) is a new feature selection method that uses the spatial coherence principle to eliminate features that are unlikely to be useful for classification. For a Substance Use Disorder dataset, it is demonstrated that feature selection with SCV can achieve higher classification accuracies than conventional feature selection methods.
Dimensionnement et comparaison de machines synchrones à concentration de flux à encochage fractionnaire pour une application véhicule hybride

Deux machines synchrones a aimants permanents et a concentration de flux sont presentees dans cet article. Ce sont deux machines a bobinages concentres au stator et a encochage fractionnaire avec des aimants enterres au rotor. Nous presentons premierement la structure, la comparaison en terme du couple et puis le dimensionnement systemique de ces deux machines dans l'objectif d'obtenir le rapport couple/pertes cuivre maximal. Enfin, nous presentons le calcul des pertes moyennes pour un cycle de fonctionnement du vehicule hybride.
RANKING ALTERNATIVES FROM THE DECISION MAKER'S PREFERENCES : AN APPROACH BASED ON UTILITY AND THE NOTION OF MARGINAL ACTION

This paper proposes an operational approach (based on marginal actions) to specify multiattribute utility functions, which allows us to easily rank alternatives from criteria relevant to the manager, the customer or any other decision maker without heuristic remedies, imprecision or loss of generality. Marginal actions are fictitious alternatives which play a key role in preference analyses as a tool recently introduced for the ranking treatment of decision tables. As usual in multi-attribute value theory, preferential independence is assumed. A practical large-scale case in the textile industry to rank commercial fabrics –characterized by seven quality factors– is developed.
Natural chaotic inflation and ultraviolet sensitivity

If the recent measurement of B-mode polarization by BICEP2 is due to primordial gravitational waves, it implies that inflation was driven by energy densities at the GUT scale $M_{GUT} \sim 2\times 10^{16} GeV$. This favors single-field chaotic inflation models. These models require transplanckian excursions of the inflaton, forcing one to address the UV completion of the theory. We use a benchmark 4d effective field theory of axion-4-form inflation to argue that inflation driven by a quadratic potential (with small corrections) is well motivated in the context of high-scale string theory models; that it presents an interesting incitement for string model building; and the dynamics of the UV completion can have observable consequences.
Measuring the Higgs Boson Self Coupling at the LHC and Finite Top Mass Matrix Elements

Inclusive Standard Model Higgs boson pair production and subsequent decay to same-sign dileptons via weak gauge W bosons at the CERN Large Hadron Collider has the capability to determine the Higgs boson self-coupling, . The large top quark mass limit is found not to be a good approximation for the signal if one wishes to utilize differential distributions in the analysis. We find that it s hould be possible at the LHC with design luminosity to establish that the Standard Model Higgs boson has a non-zero self-coupling and that = SM can be restricted to a range of 0–3.7 at 95% confidence level if its mass is between 150 and 200 GeV.
Self-reported and physiological reactions to the third BNT162b2 mRNA 1 COVID-19 (booster) vaccine dose 2 Running title: Reactions to the third Pfizer COVID-19 (booster) vaccine dose

Background : The rapid rise in hospitalizations associated with the Delta-driven COVID-19 15 resurgence, and the imminent risk of hospital overcrowding, led the Israeli government to 16 initialize a national third (booster) COVID-19 vaccination campaign in early August 2021, 17 offering the BNT162b2 mRNA vaccine to individuals who received their second dose over five 18 months ago. However, the safety of the third (booster) dose has not been fully established yet. 19 Objective : Evaluate the short-term, self-reported and physiological reactions to the third 20 BNT162b2 mRNA COVID-19 (booster) vaccine dose. 21 Design : A prospective observational study, in which participants are equipped with a smartwatch 22 and fill in a daily questionnaire via a dedicated mobile application for a period of 21 days, 23 starting seven days before the vaccination. Setting : An Israel-wide third (booster) vaccination campaign. : group of at least one BNT162b2 2021, out of a larger cohort 27 of 2,848 prospective study participants. 1,231 of participants 28 vaccine Measurements : Daily self-reported questionnaires regarding local and systemic reactions, mood level, stress level, duration, and sleep quality. Heart rate and heart rate variability were continuously measured by Garmin Vivosmart 4 smartwatches. Results : Local and systemic reactions reported following the third (booster) dose administration are similar to those reported following the second dose and considerably greater than those reported following the first dose. Our analyses of self-reported well-being indicators as well as the objective heart rate and heart rate variability measures recorded by the smartwatches further support this finding. These measures returned to their baseline levels within three days from inoculation with the third dose. These were consistent regardless of age, or the existence of an underlying medical Conclusion Our work further supports the safety of a third COVID-19 BNT162b2 (booster) vaccine dose from both a subjective and an objective perspective.
New Insight into the Impact of Effervescence on Gel Layer Microstructure and Drug Release of Effervescent Matrices Using Combined Mechanical and Imaging Characterisation Techniques

Gel layer characteristics play a crucial role in hydrophilic hydroxypropyl methylcellulose (HPMC) matrix development. Effervescent agents have the potential to affect the gel layer microstructures. This study aimed to investigate the influence of effervescence on the microstructure of the gel layer around HPMC matrices using a combination of texture analysis and imaging techniques. The relationship with drug release profile and release mechanisms were also examined. The high amounts of effervescent agents promoted a rapid carbonation reaction, resulting in a high gel layer formation with a low gel strength through texture analysis. This finding was ascribed to the enhanced surface roughness and porosity observed under digital microscopy and microporous structure of the gel layer under scanning electron microscopy. The reconstructed three-dimensional images from synchrotron radiation X-ray tomographic microscopy notably exhibited the interconnected pores of various sizes from the carbonation reaction of effervescent and microporous networks, indicating the gel layer on the tablet surface. Notably, effervescence promoted the increase in interconnected porosities, which directly influenced the strength of the gel layer microstructure, drug release patterns and release mechanism of the effervescent matrix tablet. Therefore, combined mechanical characterisation and imaging techniques can provide new insights into the role of effervescent agents on the gel layer microstructure, and describe the relationship of drug release patterns and release mechanism of matrix tablets.
Drug Delivery Systems as a Strategy to Improve the Efficacy of FDA-Approved Alzheimer’s Drugs

Alzheimer’s disease (AD) is the most common form of dementia, with a high impact worldwide, accounting for more than 46 million cases. The continuous increase of AD demands the fast development of preventive and curative therapeutic strategies that are truly effective. The drugs approved for AD treatment are classified into acetylcholinesterase inhibitors and N-methyl-D-aspartate receptor antagonists. The therapeutic effectiveness of those drugs is hindered by their restricted access to the brain due to the blood–brain barrier, low bioavailability, and poor pharmacokinetic properties. In addition, the drugs are reported to have undesirable side effects. Several drug delivery systems (DDSs) have been widely exploited to address these issues. DDSs serve as drug carriers, combining the ability to deliver drugs locally and in a targeted manner with the ability to release them in a controlled and sustained manner. As a result, the pharmacological therapeutic effectiveness is raised, while the unwanted side effects induced by the unspecific distribution decrease. This article reviews the recently developed DDSs to increase the efficacy of Food and Drug Administration-approved AD drugs.
CAMBRIDGE WORKING PAPERS IN ECONOMICS JANEWAY INSTITUTE WORKING PAPERS The Emergence of Enforcement

We ask how enforcement can endogenously emerge in a landscape in which only raw power, iron ﬁsts, govern the interaction of agents. If two agents are ranked in terms of power, the more powerful one can expropriate, at a cost, the less powerful one. Alternatively, both agents can engage in surplus-augmenting cooperation (e.g. trade). If expropriation is not too costly and cooperation is not overwhelmingly productive, for any pair of ranked agents the possibility of expropriation prevents cooperation. The more powerful agent ﬁnds it proﬁtable to expropriate the less powerful one. However, if expropriating agents who are net expropriators of others is cheaper, then a more powerful agent may endogenously become an “enforcer” for lower ranked agents. In equilibrium, the more powerful agent expropriates the less powerful ones by smaller amounts, and the less powerful ones cooperate and refrain from expropriating agents below them. This is because if they do not the more powerful agent will ﬁnd it cheaper to expropriate only them by a larger amount. Surprisingly, the details of the power structure are irrelevant for enforcement to emerge as an equilibrium phenomenon prov ided that the original jungle is inhabited by a suﬃciently large number of agents and by one that dominates all others. Abstract. We ask how enforcement can endogenously emerge in a landscape in which only raw power iron ﬁsts, govern the interaction of agents. If two agents are ranked in terms of power, the more powerful one can expropriate, at a cost, the less powerful one. Alternatively, both agents can engage in surplus-augmenting cooperation (e.g. trade). If expropriation is not too costly and cooperation is not overwhelmingly productive, for any pair of ranked agents the possibility of expropriation prevents cooperation. The more powerful agent ﬁnds it proﬁtable to expropriate the less powerful one. However, if expropriating agents who are net expropriators of others is cheaper, then a more powerful agent may endogenously become an “enforcer” for lower ranked agents. In equilibrium, the more powerful agent expropriates the less powerful ones by smaller amounts, and the less powerful ones cooperate and refrain from expropriating agents below them. This is because if they do not the more powerful agent will ﬁnd it cheaper to expropriate only them by a larger amount. Surprisingly, the details of the power structure are irrelevant for enforcement to emerge as an equilibrium phenomenon provided that the original jungle is inhabited by a suﬃciently large number of agents and by one that dominates all others.
Abstract—Does your personality determine what props you

Does your personality determine what props you would like to buy in online games? The present study addressed this question through conducting an online survey that aimed to test how players’ consuming propensity to certain types of in-game props relates to their big five personalities. The online survey contained questions from Big Five Inventory (BFI-44) that tested on big-five personality traits (openness, conscientiousness, extraversion, agreeableness, and neuroticism) and questions that tested on participants' willingness to pay for props that serve different purposes (social, aesthetic, and combat). Results showed that only openness-to-experience was negatively related to players' buying tendency of socialization props and no significant relationship was found between other personality traits and consuming tendencies. The current study is one of the first few studies that investigate a player's consuming behavior in relation to their personality. It provides insights for game companies to increase their understanding of players and their consumption characteristics. More future research in this area will facilitate game companies to optimize their in-game props design and marketing strategy.
Neural Response Effects of Oxytocin and Vasopressin on Human Learning for Social Cooperation

Background: Oxytocin (OT) and vasopressin (AVP) are neuropep- tides thought to have essential roles during social interactions, while interacting with brain regions of the dopaminergic system, which influences reinforcement learning (RL) mechanisms. Objective: Investigate the roles of OT and AVP on social RL and its neural correlates, in different social contexts, and examine the added effect of participant’s sex. Methods: Participants (148 men; 144 women) randomly received intranasal OT, AVP or placebo (PB) and played the prisoner’s dilemma game. Behavioural data was modelled using computational RL models, model parameters were analyzed, and trial-by-trial Re- ward Prediction Error (RPE) signals were correlated with whole-brain and region-of-interest (ROI) brain activation. Results: OT increased the α C (learning rate) parameter in women playing with human, compared with computer partners. Generally, OT promoted a higher Q 0 parameter (initial bias) in games with human than computer partners. AVP increased Q 0 in men playing with humans compared to OT, and when playing with computers compared to PB. Both amygdala and caudate regions revealed a higher RPE-brain activation correlation in women under OT playing with computer than human partners. Only in the amygdala ROI, AVP increased the RPE correlation in males playing with human compared to computer partners. Conclusions: OT may promote a pro-self bias at the beginning of a social dilemma interaction, while increasing impulsive behaviours in women after their cooperation. Contrarily, AVP might promote a prosocial bias in males. Additionally, OT may enhance social learning in women during non-social contexts; and AVP might enhance social learning in males during social contexts.
Data Analysis and Graphics Using R: An Example-Based Approach

Chapters 5 and 6 are rather short and focus more on examples instead of detailed descriptions of methods, they include useful references for those wanting additional information. The final two chapters deal with data that are correlated in space (Chap. 7) and time (Chap. 8). These are perhaps two of the most overlooked issues in environmental data, and thus I am pleased to see them addressed in a concise and straightforward manner for readers who do not have advanced training in statistics. As for the other topics covered, the authors explain their recommendations using detailed examples. On the whole, the authors use a wide variety of examples representing a number of different aspects of environmental research, most of which are relatively current. The authors use the examples to illustrate their points and provide graphical and tabular displays for clarification and emphasis. The authors make no specific suggestions as to the intended audience for this text, but they do make general reference to the book’s usefulness for professionals in the environmental research fields who have questions about the specific types of analyses discussed. The book is also aimed toward those researchers who want to gain a better understanding of which statistical rules must be adhered to and which can legitimately be bent without rendering their analyses invalid. Given the authors’ intention of appealing to an applied audience, the level and clarity of the equations provided for the various concepts are appropriate. The authors do not include extensive mathematical details, but instead provide those equations that readers would need in an understandable form. The book does not include exercises or provide the data or analysis programs used in the examples in either printed or electronic format. The authors also readily admit that the text is not by any means comprehensive. They instead refer to the collection of techniques discussed as “idiosyncratic” and justify their choices of what to include based on what they feel is useful to a researcher. Both authors have extensive experience as statistical consultants and have drawn on that experience in offering the advice provided. This book was not written with the goal of being the sole or primary textbook for an applied statistics class, and I would not recommend it as one. I do feel, however, that both undergraduate and graduate students, as well as environmental professionals who have a basic familiarity with standard statistical concepts, will find the authors’ insights helpful. Additionally, there are sections and concepts that instructors who focus on environmental statistics will find useful in the classroom setting. Instructors of those and related subjects should consider this book for a secondary text or reference. The book’s overall philosophy is to strive to maintain a balance between adhering to important statistical rules and being flexible enough to answer the question at hand, given inevitable data limitations. This philosophy makes it a valuable resource for students and professionals who have limited statistical training.
Choosing between persistent and stationary volatility

This paper suggests a multiplicative volatility model where volatility is decomposed into a stationary and a non-stationary persistent part. We provide a testing procedure to determine which type of volatility is prevalent in the data. The persistent part of volatility is associated with a nonstationary persistent process satisfying some smoothness and moment conditions. The stationary part is related to stationary conditional heteroskedasticity. We outline theory and conditions that allow the extraction of the persistent part from the data and enable standard conditional heteroskedasticity tests to detect stationary volatility after persistent volatility is taken into account. Monte Carlo results support the testing strategy in small samples. The empirical application of the theory supports the persistent volatility paradigm, suggesting that stationary conditional heteroskedasticity is considerably less pronounced than previously thought.