Collective ordering of microscale matters in natural analogy

Collective interaction occurs in many natural and artificial matters in broad scales. In a biological system, collective spatial organization of live individuals in a colony is important for their viability determination. Interactive motions between a single individual and an agglomerate are critical for whole procedure of the collective behaviors, but few has been clarified for these intermediate range behaviors. Here, collective interactions of microscale matters are investigated with human cells, plant seeds and artificial microspheres in terms of commonly occurring spatial arrangements. Human cancer cells are inherently attractive to form an agglomerate by cohesive motion, while plant chia seeds are repulsive by excreting mucilage. Microsphere model is employed to investigate the dynamic assembly equilibrated by an attraction and repulsion. There is a fundamental analogy in terms of an onset of regular pattern formation even without physical contact of individuals. The collective interactions are suggested to start before the individual components become physically agglomerated. This study contributes to fundamental understanding on the microscale particulate matters and natural pattern formation which are further useful for various applications both in academic and industrial areas.110Ysciescopu

Living plants ecosystem sensing: A quantum bridge between thermodynamics and bioelectricity

The in situ measurement of the bioelectric potential in xilematic and floematic superior plants reveals valuable insights into the biological activity of these organisms, including their responses to lunar and solar cycles and collective behaviour. This paper reports on the “Cyberforest Experiment” conducted in the open-air Paneveggio forest in Valle di Fiemme, Trento, Italy, where spruce (i.e., Picea abies) is cultivated. Our analysis of the bioelectric potentials reveals a strong correlation between higher-order complexity measurements and thermodynamic entropy and suggests that bioelectrical signals can reflect the metabolic activity of plants. Additionally, temporal correlations of bioelectric signals from different trees may be precisely synchronized or may lag behind. These correlations are further explored through the lens of quantum field theory, suggesting that the forest can be viewed as a collective array of in-phase elements whose correlation is naturally tuned depending on the environmental conditions. These results provide compelling evidence for the potential of living plant ecosystems as environmental sensors

On the relation between complex brain activity and consciousness

Why does it feel like something to be awake? I.e. how is consciousness generated by the body, the brain in particular? Seeking to map phenomenological properties of any first person experience to neural activity patterns, theories of consciousness suggest a correlation between a specific type of neural dynamical complexity and the level of consciousness: When awake and aware, all brain regions are to a certain extent connected and there is diversity in the interactions. In support of this, Casali et al. (2013) have used EEG and transcranial magnetic stimulation to show extensively that brain response activity to direct perturbation is the more diverse across regions and time, the higher the level of consciousness. The spatio-temporal diversity of the response signal is quantified by a single index, the perturbational complexity index (PCI), using a Lempel-Ziv compression algorithm. Motivated by this result, and given that spontaneous neural signals are easier to obtain than response signals to perturbation, this thesis proposes measures - based on Lempel-Ziv compression and entropy - to quantify spontaneous neural signal diversity across channels and observations. Our measures’ sensitivity and specificity to conscious level is demonstrated by re-analysing resting state scalp EEG during propofol-induced anaesthesia and depth electrode recordings during sleep stages, resulting in consistently higher scores for subjects that are awake than being in propofol-induced anaesthesia or non-rapid eye movement sleep. In addition we demonstrate that our measures score higher for states induced by psychedelic substances by re-analysing resting state magnetoencephalography (MEG) data. We further explore in computer simulation how our measures and PCI behave as a function of connectivity of coupled oscillators, informing models of brain mechanisms associated with the loss of consciousness. While our measures may be weaker than PCI in terms of specificity and sensitivity to conscious level, they are quick and easy to compute and applicable to readily available resting state data. This thesis provides strong evidence that cortical signal diversity is a hallmark of consciousness, as predicted by integrated information and complexity theories of consciousness. i

The search for dark matter in xenon: Innovative calibration strategies and novel search channels

The direct detection dark matter experiment XENON1T became operational in early 2016, heralding the era of tonne-scale dark matter detectors. Direct detection experiments typically search for elastic scatters of dark matter particles off target nuclei. XENON1T\u27s larger xenon target provides the advantage of stronger dark matter signals and lower background rates compared to its predecessors, XENON10 and XENON100; but, at the same time, calibration of the detector\u27s response to backgrounds with traditional external sources becomes exceedingly more difficult. A 220Rn source is deployed on the XENON100 dark matter detector in order to address the challenges in calibration of tonne-scale liquid noble element detectors. I show that the subsequent 212Pb beta emission can be used for low-energy electronic recoil calibration in searches for dark matter. The isotope spreads throughout the entire active region of the detector, and its activity naturally decays below background level within a week after the source is closed. I find no increase in the activity of the troublesome 222Rn background after calibration. Alpha emitters are also distributed throughout the detector and facilitate calibration of its response to 222Rn. Using the delayed coincidence of 220Rn/216Po, I map for the first time the convective motion of particles in the XENON100 detector. Additionally, I make a competitive measurement of the half-life of 212Po, t1/2=293.9±(1.0)stat±(0.6)ns. In contrast to the elastic scattering of dark matter particles off nuclei, I explore inelastic scattering where the nucleus is excited to a low-lying state of 10-100 keV, with a subsequent prompt de-excitation. I use the inelastic structure factors for the odd-mass xenon isotopes based on state-of-the-art large-scale shell-model calculations with chiral effective field theory WIMP-nucleon currents, finding that the inelastic channel is comparable to or can dominate the elastic channel for momentum transfers around 150 MeV. I calculate the inelastic recoil spectra in the standard halo model, compare these to the elastic case, and discuss the expected signatures in a xenon detector, along with implications for existing and future experiments. The combined information from elastic and inelastic scattering will allow for the determination of the dominant interaction channel within one experiment. In addition, the two channels probe different regions of the dark matter velocity distribution and can provide insight into the dark halo structure. The allowed recoil energy domain and the recoil energy at which the integrated inelastic rates start to dominate the elastic channel depend on the mass of the dark matter particle, thus providing a potential handle to constrain its mass. Similarly, now that liquid xenon detectors have reached the tonne scale, they have sensitivity to all flavors of supernova neutrinos via coherent elastic neutrino-nucleus scattering. I consider for the first time a realistic detector model to simulate the expected supernova neutrino signal for different progenitor masses and nuclear equations of state in existing and upcoming dual-phase liquid xenon experiments. I show that the proportional scintillation signal (S2) of a dual-phase detector allows for a clear observation of the neutrino signal and guarantees a particularly low energy threshold, while the backgrounds are rendered negligible during the supernova burst. XENON1T (XENONnT and LZ; DARWIN) experiments will be sensitive to a supernova burst up to 25 (35; 65) kpc from Earth at a significance of more than 5 sigma, observing approximately 35 (123; 704) events from a 27 Solar mass supernova progenitor at 10 kpc. Moreover, it will be possible to measure the average neutrino energy of all flavors, to constrain the total explosion energy, and to reconstruct the supernova neutrino light curve. My results suggest that a large xenon detector such as DARWIN will be competitive with dedicated neutrino telescopes, while providing complementary information that is not otherwise accessible

Mathematical modelling and statistics of biodiversity

Life on Earth is characterised by an amazing variety of living forms which are in continuous evolution to better adapt to the surrounding environment and highly connected one to the other. A deep investigation of different living systems has recently been favoured by the huge quantity of data nowadays available. The present thesis is the final result of a journey through complex patterns in theoretical ecology. We study both models and issues in data analysis as well as the connections between them within a mathematical framework. In particular, we explore the different aspects of the biodiversity of an ecosystem, referring with this term to the variety of its species. Our interest is to investigate how these species interact with each other and with the surrounding environment and how these connections can structure recurrent macro-ecological patterns. Indeed, despite their diversity and complexity, it is straightforward that ecological systems share similar behaviours. This fact suggests that such systems are driven by a common mechanism, which is insensitive to the details of the systems on which it acts. A theoretical understanding is therefore possible through the development of mathematical models rich enough to reproduce the investigated patterns, but containing only the essential ingredients able to originate them. In the first part of the present thesis, we explore the fundamentals of spatial point process theory, a powerful mathematical tool to model data in the form of sets of spatial locations of points. In particular, since our datasets usually consist of information on trees belonging to different species, we focus on the so-called superposed process and its first and second-order statistics. We then study an algorithm to infer the intensity function of a point process which is capable to reduce sampling fluctuations and to capture relevant spatial characteristics of a spatial pattern, as space anisotropy and clustering. Finally, we explore in details the notions of ecological diversity and similarity and some of the most popular indexes used to measure them. In particular, we study how to insert them in the context of point processes’ theory. Our aim is at finding an analytical relation for the decay of similarity between two regions of a landscape as a function of the distance between them, by extending the classic notion of Sørensen’s index to incorporate spatial information. In the second part of the thesis, we tackle the problem of inferring the total bio- diversity of an ecosystem when only scattered samples are observed. In particular, we propose a novel upscaling method which, by exploiting the scaling invariance property of the negative binomial distribution, generates accurate and robust pre- dictions. We test it on both computer-generated and real forests and we show that it outperforms other methods previously proposed in literature

Review of Particle Physics

The Review summarizes much of particle physics and cosmology. Using data from previous editions, plus 2,143 new measurements from 709 papers, we list, evaluate, and average measured properties of gauge bosons and the recently discovered Higgs boson, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as supersymmetric particles, heavy bosons, axions, dark photons, etc. Particle properties and search limits are listed in Summary Tables. We give numerous tables, figures, formulae, and reviews of topics such as Higgs Boson Physics, Supersymmetry, Grand Unified Theories, Neutrino Mixing, Dark Energy, Dark Matter, Cosmology, Particle Detectors, Colliders, Probability and Statistics. Among the 120 reviews are many that are new or heavily revised, including a new review on Machine Learning, and one on Spectroscopy of Light Meson Resonances. The Review is divided into two volumes. Volume 1 includes the Summary Tables and 97 review articles. Volume 2 consists of the Particle Listings and contains also 23 reviews that address specific aspects of the data presented in the Listings. The complete Review (both volumes) is published online on the website of the Particle Data Group (pdg.lbl.gov) and in a journal. Volume 1 is available in print as the PDG Book. A Particle Physics Booklet with the Summary Tables and essential tables, figures, and equations from selected review articles is available in print, as a web version optimized for use on phones, and as an Android app.United States Department of Energy (DOE) DE-AC02-05CH11231government of Japan (Ministry of Education, Culture, Sports, Science and Technology)Istituto Nazionale di Fisica Nucleare (INFN)Physical Society of Japan (JPS)European Laboratory for Particle Physics (CERN)United States Department of Energy (DOE

Geologic processes that control sourcing and migration of subsurface helium

There is an ever-pressing need to find more helium (He) because 1) it is an essential resource for modern life, 2) reserves are dwindling faster than He accumulations are discovered, and 3) new He projects are delayed. The motivation for this work is to provide updated frameworks on the geologic processes and migration mechanisms of He in the mid-continent USA, using noble gas geochemistry, structural geology and geophysics. The Colorado Plateau field area (Four Corners area), USA was chosen to represent a moderate tectonic activity environment, and Yellowstone (and its environs), USA, were chosen to represent a very tectonically active region and to investigate the impact of heat on gas release. In the Four Corners area, utilizing bulk gas and isotopes of hydrocarbons, non-hydrocarbons, and noble gases (n=31), we construct mass balance and noble gas fractionation models that provide evidence for advective fault-controlled systems responsible for basement sourced He accumulations. Regarding Yellowstone, utilizing heat flow data, bulk gas, and isotopes of non-hydrocarbons and noble gases (n=43), we quantify gas origin, fluid flow, and heat influence in a regional context using noble gas heat and fractionation models. We show a poor relationship regarding He and heat flow on a regional scale for Yellowstone, and we propose that localized heat sources are important in releasing He trapped in minerals. Our prediction of fault-controlled He-systems in the Four Corners area is corroborated with high-resolution geophysical data that shows a strong non-random relationship with He-rich occurrences and structural features (faults/intrusions) and historical He-well data (n=94). Based on the distributions of these relationships, we create a regional probabilistic predictive He map to reduce exploration risk. Additional work utilizing soil gas data (n=1974), was used to construct a higher-resolution localized predictive model calibrated with real-world data illustrating areas that are higher-likelihood of containing He-rich gas

Untangling hotel industry’s inefficiency: An SFA approach applied to a renowned Portuguese hotel chain

The present paper explores the technical efficiency of four hotels from Teixeira Duarte Group - a renowned Portuguese hotel chain. An efficiency ranking is established from these four hotel units located in Portugal using Stochastic Frontier Analysis. This methodology allows to discriminate between measurement error and systematic inefficiencies in the estimation process enabling to investigate the main inefficiency causes. Several suggestions concerning efficiency improvement are undertaken for each hotel studied.info:eu-repo/semantics/publishedVersio

Fuzzy Sets in Business Management, Finance, and Economics

This book collects fifteen papers published in s Special Issue of Mathematics titled “Fuzzy Sets in Business Management, Finance, and Economics”, which was published in 2021. These paper cover a wide range of different tools from Fuzzy Set Theory and applications in many areas of Business Management and other connected fields. Specifically, this book contains applications of such instruments as, among others, Fuzzy Set Qualitative Comparative Analysis, Neuro-Fuzzy Methods, the Forgotten Effects Algorithm, Expertons Theory, Fuzzy Markov Chains, Fuzzy Arithmetic, Decision Making with OWA Operators and Pythagorean Aggregation Operators, Fuzzy Pattern Recognition, and Intuitionistic Fuzzy Sets. The papers in this book tackle a wide variety of problems in areas such as strategic management, sustainable decisions by firms and public organisms, tourism management, accounting and auditing, macroeconomic modelling, the evaluation of public organizations and universities, and actuarial modelling. We hope that this book will be useful not only for business managers, public decision-makers, and researchers in the specific fields of business management, finance, and economics but also in the broader areas of soft mathematics in social sciences. Practitioners will find methods and ideas that could be fruitful in current management issues. Scholars will find novel developments that may inspire further applications in the social sciences