Casimir force on a piston

We consider a massless scalar field obeying Dirichlet boundary conditions on the walls of a two-dimensional L x b rectangular box, divided by a movable partition (piston) into two compartments of dimensions a x b and (L-a) x b. We compute the Casimir force on the piston in the limit L -> infinity. Regardless of the value of a/b, the piston is attracted to the nearest end of the box. Asymptotic expressions for the Casimir force on the piston are derived for a << b and a >> b.Comment: 10 pages, 1 figure. Final version, accepted for publication in Phys. Rev.

Ultrafast Optical Control of the Electronic Properties of ZrTe5ZrTe_5

We report on the temperature dependence of the $ZrTe_5$ electronic properties, studied at equilibrium and out of equilibrium, by means of time and angle resolved photoelectron spectroscopy. Our results unveil the dependence of the electronic band structure across the Fermi energy on the sample temperature. This finding is regarded as the dominant mechanism responsible for the anomalous resistivity observed at T* $\sim$ 160 K along with the change of the charge carrier character from holelike to electronlike. Having addressed these long-lasting questions, we prove the possibility to control, at the ultrashort time scale, both the binding energy and the quasiparticle lifetime of the valence band. These experimental evidences pave the way for optically controlling the thermoelectric and magnetoelectric transport properties of $ZrTe_5$

A Self-Adaptive Approach to Exploit Topological Properties of Different GAs’ Crossover Operators

Evolutionary algorithms (EAs) are a family of optimization algorithms inspired by the Darwinian theory of evolution, and Genetic Algorithm (GA) is a popular technique among EAs. Similar to other EAs, common limitations of GAs have geometrical origins, like premature convergence, where the final population’s convex hull might not include the global optimum. Population diversity maintenance is a central idea to tackle this problem but is often performed through methods that constantly diminish the search space’s area. This work presents a self- adaptive approach, where the non-geometric crossover is strategically employed with geometric crossover to maintain diversity from a geometrical/topological perspective. To evaluate the performance of the proposed method, the experimental phase compares it against well-known diversity maintenance methods over well-known benchmarks. Experimental results clearly demonstrate the suitability of the proposed self-adaptive approach and the possibility of applying it to different types of crossover and EAs

A Fast Non-Parametric Algorithm for Coherent Change Detection

Developing algorithms to detect temporal and spatial changes in radar targets is paramount. This paper specifically addresses the temporal change detection aspect, introducing a rapid non-parametric Coherent Change Detection (CCD) algorithm named Fast-Permutational Change Detection (F-PCD). The F-PCD identifies temporal Change Points (CPs) in a radar target by recognizing block structures in the coherence matrix, showing great robustness against non-stationary noise sources that generally affect the performance of the standard approaches. Moreover, the F-PCD is characterized by an accelerated inference process, ensuring efficiency without substantial performance loss. The F-PCD algorithm can be applied to different scenarios, for example, where DEM changes happen, e.g., mining sites, volcano eruptions, and earthquakes. For this reason, an example of the F-PCD application on an active open-pit mining site is presented to validate its effectiveness. Moreover, its generalization capability is demonstrated by a multi frequency-geometry analysis conducted on the same mining site. Finally, fully exploiting the F-PCD outcomes contributes to a broader understanding of temporal changes in SAR data and introduces new perspectives for interpreting InSAR datasets

Probabilistic reconstruction via machine-learning of the Po watershed aquifer system (Italy)

A machine-learning-based methodology is proposed to delineate the spatial distribution of geomaterials across a large-scale three-dimensional subsurface system. The study area spans the entire Po River Basin in northern Italy. As uncertainty quantification is critical for subsurface characterization, the methodology is specifically designed to provide a quantitative evaluation of prediction uncertainty at each location of the reconstructed domain. The analysis is grounded on a unique dataset that encompasses lithostratigraphic data obtained from diverse sources of information. A hyperparameter selection technique based on a stratified cross-validation procedure is employed to improve model prediction performance. The quality of the results is assessed through validation against pointwise information and available hydrogeological cross-sections. The large-scale patterns identified are in line with the main features highlighted by typical hydrogeological surveys. Reconstruction of prediction uncertainty is consistent with the spatial distribution of available data and model accuracy estimates. It enables one to identify regions where availability of new information could assist in the constraining of uncertainty. The comprehensive dataset provided in this study, complemented by the model-based reconstruction of the subsurface system and the assessment of the associated uncertainty, is relevant from a water resources management and protection perspective. As such, it can be readily employed in the context of groundwater availability and quality studies aimed at identifying the main dynamics and patterns associated with the action of climate drivers in large-scale aquifer systems of the kind here analyzed, while fully embedding model and parametric uncertainties that are tied to the scale of investigation

CONTRIBUTION OF THE CORPUS CALLOSUM TO THE SYMMETRICAL REPRESENTATION OF TASTE IN THE HUMAN BRAIN: AN fMRI STUDY OF CALLOSOTOMIZED PATIENTS

The present study was designed to establish the contribution of the corpus callosum (CC) to the cortical representation of unilateral taste stimuli in the human primary gustatory area (GI). Unilateral taste stimulation of the tongue was applied to eight patients with partial or total callosal resection by placing a small cotton pad soaked in a salty solution on either side of the tongue. Functional images were acquired with a 1.5 Tesla machine. Diffusion tensor imaging and tractography were also performed. Unilateral taste stimuli evoked bilateral activation of the GI area in all patients, including those with total resection of the CC, with a prevalence in the ipsilateral hemisphere to the stimulated tongue side. Bilateral activation was also observed in the primary somatic sensory cortex (SI) in most patients, which was more intense in the contralateral SI. This report confirms previous functional studies carried out in control subjects and neuropsychological findings in callosotomized patients, showing that gustatory pathways from tongue to cortex are bilaterally distributed, with an ipsilateral predominance. It has been shown that the CC does play a role, although not an exclusive one, in the bilateral symmetrical representation of gustatory sensitivity in the GI area, at least for afferents from one side of the tongue

Wide-range optical spin orientation in Ge from near-infrared to visible light

Ge-based spin-photodiodes have been employed to investigate the spectral dependence of optical spin orientation in germanium, in the range 400-1550 nm. We found the expected maximum in the spin polarization of photocarriers for excitation at the direct gap in Γ (1550 nm) and a second sizable peak due to photogeneration in the L valleys (530 nm). Data suggest distinct spin depolarization mechanisms for excitation at Γ and L, with shorter spin relaxation times whether the X point is involved. These devices can be used as integrated photon-helicity detectors over a wide spectral range

Electron-Phonon Coupling in High-Temperature Cuprate Superconductors Determined from Electron Relaxation Rates

We determined electronic relaxation times via pump-probe optical spectroscopy using sub-15 fs pulses for the normal state of two different cuprate superconductors.We show that the primary relaxation process is the electron-phonon interaction and extract a measure of its strength, the second moment of the Eliashberg function\lambda=800\pm200 meV^{2} for La_{1.85}Sr_{0.15}CuO_{4} and \lambda=400\pm100 meV^{2} for YBa_{2}Cu_{3}O_{6.5}. These values suggest a possible fundamental role of the electron-phonon interaction in the superconducting pairing mechanism.Comment: As published in PR

Towards Collective Sentiment Analysis in IoT-Enabled Scenarios

An interesting and innovative activity in Collective Intelligence systems is Sentiment Analysis (SA) which, starting from users' feedback, aims to identify their opinion about a specific subject, for example in order to develop/improve/customize products and services. The feedback gathering, however, is complex, time-consuming, and often invasive, possibly resulting in decreased truthfulness and reliability for its outcome. Moreover, the subsequent feedback processing may suffer from scalability, cost, and privacy issues when the sample size is large or the data to be processed is sensitive. Internet of Things (IoT) and Edge Intelligence (EI) can greatly help in both aspects by providing, respectively, a pervasive and transparent way to collect a huge amount of heterogeneous data from users (e.g., audio, images, video, etc.) and an efficient, low-cost, and privacy-preserving solution to locally analyze them without resorting to Cloud computing-based platforms. Therefore, in this paper we outline an innovative collective SA system which leverages on IoT and EI (specifically, TinyML techniques and the EdgeImpulse platform) to gather and immediately process audio in the proximity of entities-of-interest in order to determine whether audience' opinions are positive, negative, or neutral. The architecture of the proposed system, exemplified in a museum use case, is presented, and a preliminary, yet very promising, implementation is shown, reveling interesting insights towards its full development