Measuring the Cosmic Ray Muon-Induced Fast Neutron Spectrum by (n,p) Isotope Production Reactions in Underground Detectors

While cosmic ray muons themselves are relatively easy to veto in underground detectors, their interactions with nuclei create more insidious backgrounds via: (i) the decays of long-lived isotopes produced by muon-induced spallation reactions inside the detector, (ii) spallation reactions initiated by fast muon-induced neutrons entering from outside the detector, and (iii) nuclear recoils initiated by fast muon-induced neutrons entering from outside the detector. These backgrounds, which are difficult to veto or shield against, are very important for solar, reactor, dark matter, and other underground experiments, especially as increased sensitivity is pursued. We used fluka to calculate the production rates and spectra of all prominent secondaries produced by cosmic ray muons, in particular focusing on secondary neutrons, due to their importance. Since the neutron spectrum is steeply falling, the total neutron production rate is sensitive just to the relatively soft neutrons, and not to the fast-neutron component. We show that the neutron spectrum in the range between 10 and 100 MeV can instead be probed by the (n, p)-induced isotope production rates 12C(n, p)12B and 16O(n, p)16N in oil- and water-based detectors. The result for 12B is in good agreement with the recent KamLAND measurement. Besides testing the calculation of muon secondaries, these results are also of practical importance, since 12B (T1/2 = 20.2 ms, Q = 13.4 MeV) and 16N (T1/2 = 7.13 s, Q = 10.4 MeV) are among the dominant spallation backgrounds in these detectors

Combined Neutrase-Alcalase Protein Hydrolysates from Hazelnut Meal, a Potential Functional Food Ingredient

Consumers\u27 interest in functional foods has significantly increased in the past few years. Hazelnut meal, the main valuable byproduct of the hazelnut oil industry, is a rich source of proteins and bioactive peptides and thus has great potential to become a valuable functional ingredient. In this study, hazelnut protein hydrolysates obtained by a single or combined hydrolysis by Alcalase and Neutrase were mainly characterized for their physicochemical properties (SDS-PAGE, particle size distribution, Fourier-transform infrared (FTIR) spectroscopy, molecular weight distribution, etc.) and potential antiobesity effect (Free fatty acid (FFA) release inhibition), antioxidant activity (DPPH and ABTS methods), and emulsifying properties. The impact of a microfluidization pretreatment was also investigated. The combination of Alcalase with Neutrase permitted the highest degree of hydrolysis (DH; 15.57 \ub1 0.0%) of hazelnut protein isolate, which resulted in hydrolysates with the highest amount of low-molecular-weight peptides, as indicated by size exclusion chromatography (SEC) and SDS-PAGE. There was a positive correlation between the DH and the inhibition of FFA release by pancreatic lipase (PL), with a significant positive effect of microfluidization when followed by Alcalase hydrolysis. Microfluidization enhanced the emulsifying activity index (EAI) of protein isolates and hydrolysates. Low hydrolysis by Neutrase had the best effect on the EAI (84.32 \ub1 1.43 (NH) and 88.04 \ub1 2.22 m2/g (MFNH)), while a negative correlation between the emulsifying stability index (ESI) and the DH was observed. Again, the combined Alcalase-Neutrase hydrolysates displayed the highest radical scavenging activities (96.63 \ub1 1.06% DPPH and 98.31 \ub1 0.46% ABTS). FTIR results showed that the application of microfluidization caused the unfolding of the protein structure. The individual or combined application of the Alcalase and Neutrase enzymes caused a switch from the β-sheet organization of the proteins to α-helix structures. In conclusion, hazelnut meal may be a good source of bioactive and functional peptides. The control of its enzymatic hydrolysis, together with an appropriate pretreatment such as microfluidization, may be crucial to achieve the best suitable activity

Chemistry of Protein-Phenolic Interactions Toward the Microbiota and Microbial Infections

Along with health concerns, interest in plants as food and bioactive phytochemical sources has been increased in the last few decades. Phytochemicals as secondary plant metabolites have been the subject of many studies in different fields. Breakthrough for research interest on this topic is re-juvenilized with rising relevance in this global pandemics\u27 era. The recent COVID-19 pandemic attracted the attention of people to viral infections and molecular mechanisms behind these infections. Thus, the core of the present review is the interaction of plant phytochemicals with proteins as these interactions can affect the functions of co-existing proteins, especially focusing on microbial proteins. To the best of our knowledge, there is no work covering the protein-phenolic interactions based on their effects on microbiota and microbial infections. The present review collects and defines the recent data, representing the interactions of phenolic compounds -primarily flavonoids and phenolic acids- with various proteins and explores how these molecular-level interactions account for the human health directly and/or indirectly, such as increased antioxidant properties and antimicrobial capabilities. Furthermore, it provides an insight about the further biological activities of interacted protein-phenolic structure from an antiviral activity perspective. The research on the protein-phenolic interaction mechanisms is of great value for guiding how to take advantage of synergistic effects of proteins and polyphenolics for future medical and nutritive approaches and related technologies

Interactions between Hazelnut (Corylus avellana L.) Protein and Phenolics and In Vitro Gastrointestinal Digestibility

In this study, we investigated the formation of protein–phenolic complexes from dephenolized hazelnut meal protein isolates (dHPI) and hazelnut skin phenolic extracts (HSE) and their effects on the bioaccessibility of both hazelnut proteins and phenolics. The dHPI–HSE complexes were of considerable size and were dependent on HSE concentration due to aggregation. Although catechin was the main component of HSE, it did not cause aggregation, except for a slight rise in particle size. According to fluorescence quenching, the hazelnut protein–phenolic extract complex had a linear Stern–Volmer plot expressing static quenching between 0–0.5 mM concentration; the interaction was mainly dependent on hydrogen bonding and van der Waals forces (ΔH < 0 and ΔS < 0), and the reaction was spontaneous (ΔG < 0). According to Fourier transform infrared (FTIR) spectroscopy results, higher phenolic extract concentration caused an increase in irregular structures in hazelnut protein, while the lowest catechin and phenolic concentration altered the regular structure. Skin extracts did not alter the digestibility of dephenolized proteins, but dephenolization reduced the degree of hydrolysis by pancreatin. The formation of the protein–phenolic complex had a beneficial effect on the bioaccessibility of hazelnut skin phenols, predominantly those on the galloylated form of the catechins, such as gallocatechin gallate and epigallocatechin gallate. Thus, the bioaccessibility and antioxidant activity analysis results showed that protein–phenolic complexes obtained from hazelnut meal and skin may promote the transition of phenolic compounds from the gastrointestinal tract without degradation

Quantum Fluctuation Theorems

Recent advances in experimental techniques allow one to measure and control systems at the level of single molecules and atoms. Here gaining information about fluctuating thermodynamic quantities is crucial for understanding nonequilibrium thermodynamic behavior of small systems. To achieve this aim, stochastic thermodynamics offers a theoretical framework, and nonequilibrium equalities such as Jarzynski equality and fluctuation theorems provide key information about the fluctuating thermodynamic quantities. We review the recent progress in quantum fluctuation theorems, including the studies of Maxwell's demon which plays a crucial role in connecting thermodynamics with information.Comment: As a chapter of: F. Binder, L. A. Correa, C. Gogolin, J. Anders, and G. Adesso (eds.), "Thermodynamics in the quantum regime - Fundamental Aspects and New Directions", (Springer International Publishing, 2018

Evidence for sparse synergies in grasping actions

Converging evidence shows that hand-actions are controlled at the level of synergies and not single muscles. One intriguing aspect of synergy-based action-representation is that it may be intrinsically sparse and the same synergies can be shared across several distinct types of hand-actions. Here, adopting a normative angle, we consider three hypotheses for hand-action optimal-control: sparse-combination hypothesis (SC) – sparsity in the mapping between synergies and actions - i.e., actions implemented using a sparse combination of synergies; sparse-elements hypothesis (SE) – sparsity in synergy representation – i.e., the mapping between degrees-of-freedom (DoF) and synergies is sparse; double-sparsity hypothesis (DS) – a novel view combining both SC and SE – i.e., both the mapping between DoF and synergies and between synergies and actions are sparse, each action implementing a sparse combination of synergies (as in SC), each using a limited set of DoFs (as in SE). We evaluate these hypotheses using hand kinematic data from six human subjects performing nine different types of reach-to-grasp actions. Our results support DS, suggesting that the best action representation is based on a relatively large set of synergies, each involving a reduced number of degrees-of-freedom, and that distinct sets of synergies may be involved in distinct tasks

Analysis of action oriented effects on perceptual process of object recognition using physiological responses

Action on any objects provides perceptual information about the environment. There is a significant evidence that human visual system responds to action possibilities in an image as perceiving any ones action stimulates human motor system. However very limited studies have been done to analyze the effect of object affordance during action perception and execution. To study the effect of object affordance on human perception, in this paper we have analyzed the human brain signals using EEG based oscillatory activity of brain. EEG responses corresponding to images of objects shown with correct, incorrect and without grips are examined. Exploration of different gripping effects has been done by extracting Alpha and Beta frequency bands using Discrete Wavelet Transform based band extraction method, then baseline normalized power of Alpha and Beta frequency bands at 24 positions of motor area of left and right side of brain are examined. The result shows that 12 pooled electrodes at central and central parietal region provides a clear discrimination among the three gripping cases in terms of calculated power. The presented research explores new applicabilities of object affordance to develop a variety of Brain Computer Interface (BCI) based devices and to improve motor imagery ability among motor disorder related patients

Scaling Effects and Spatio-Temporal Multilevel Dynamics in Epileptic Seizures

Epileptic seizures are one of the most well-known dysfunctions of the nervous system. During a seizure, a highly synchronized behavior of neural activity is observed that can cause symptoms ranging from mild sensual malfunctions to the complete loss of body control. In this paper, we aim to contribute towards a better understanding of the dynamical systems phenomena that cause seizures. Based on data analysis and modelling, seizure dynamics can be identified to possess multiple spatial scales and on each spatial scale also multiple time scales. At each scale, we reach several novel insights. On the smallest spatial scale we consider single model neurons and investigate early-warning signs of spiking. This introduces the theory of critical transitions to excitable systems. For clusters of neurons (or neuronal regions) we use patient data and find oscillatory behavior and new scaling laws near the seizure onset. These scalings lead to substantiate the conjecture obtained from mean-field models that a Hopf bifurcation could be involved near seizure onset. On the largest spatial scale we introduce a measure based on phase-locking intervals and wavelets into seizure modelling. It is used to resolve synchronization between different regions in the brain and identifies time-shifted scaling laws at different wavelet scales. We also compare our wavelet-based multiscale approach with maximum linear cross-correlation and mean-phase coherence measures

The Electroencephalogram as a Biomarker Based on Signal Processing Using Nonlinear Techniques to Detect Dementia

Dementia being a syndrome caused by a brain disease of a chronic or progressive nature, in which the irreversible loss of intellectual abilities, learning, expressions arises; including memory, thinking, orientation, understanding and adequate communication, of organizing daily life and of leading a family, work and autonomous social life; leads to a state of total dependence; therefore, its early detection and classification is of vital importance in order to serve as clinical support for physicians in the personalization of treatment programs. The use of the electroencephalogram as a tool for obtaining information on the detection of changes in brain activities. This article reviews the types of cognitive spectrum dementia, biomarkers for the detection of dementia, analysis of mental states based on electromagnetic oscillations, signal processing given by the electroencephalogram, review of processing techniques, results obtained where it is proposed the mathematical model about neural networks, discussion and finally the conclusions