Thermodynamics predicts how confinement modifies hard-sphere dynamics

We study how confining the equilibrium hard-sphere fluid to restrictive one- and two-dimensional channels with smooth interacting walls modifies its structure, dynamics, and entropy using molecular dynamics and transition-matrix Monte Carlo simulations. Although confinement strongly affects local structuring, the relationships between self-diffusivity, excess entropy, and average fluid density are, to an excellent approximation, independent of channel width or particle-wall interactions. Thus, thermodynamics can be used to predict how confinement impacts dynamics.Comment: 4 pages, 4 figure

Spectral statistics of the k-body random-interaction model

We reconsider the question of the spectral statistics of the k-body random-interaction model, investigated recently by Benet, Rupp, and Weidenmueller, who concluded that the spectral statistics are Poissonian. The binary-correlation method that these authors used involves formal manipulations of divergent series. We argue that Borel summation does not suffice to define these divergent series without further (arbitrary) regularization, and that this constitutes a significant gap in the demonstration of Poissonian statistics. Our conclusion is that the spectral statistics of the k-body random-interaction model remains an open question.Comment: 17 pages, no figure

Origin of chaos in the spherical nuclear shell model: role of symmetries

To elucidate the mechanism by which chaos is generated in the shell model, we compare three random-matrix ensembles: the Gaussian orthogonal ensemble, French's two-body embedded ensemble, and the two-body random ensemble (TBRE) of the shell model. Of these, the last two take account of the two-body nature of the residual interaction, and only the last, of the existence of conserved quantum numbers like spin, isospin, and parity. While the number of independent random variables decreases drastically as we follow this sequence, the complexity of the (fixed) matrices which support the random variables, increases even more. In that sense we can say that in the TBRE, chaos is largely due to the existence of (an incomplete set of) symmetries.Comment: 21 pages, 3 ps-figures. Revised version to appear in Nucl. Phys. A. New text and figures adde

Kinematic measures provide useful information after intracranial aneurysm treatment

Introduction; Current methods of assessing the outcomes of intracranial aneurysm treatment for aneurysmal subarachnoid haemorrhage are relatively insensitive, and thus unlikely to detect subtle deficits. Failures to identify cognitive and motor outcomes of intracranial aneurysm treatment might prevent delivery of optimal post-operative care. There are also concerns over risks associated with using intracranial aneurysm treatment as a preventative measure. Methods; We explored whether our kinematic tool would yield useful information regarding motor/cognitive function in patients who underwent intracranial aneurysm treatment for aneurysmal subarachnoid haemorrhage or unruptured aneurysm. Computerised kinematic motor and learning tasks were administered alongside standardised clinical outcome measures of cognition and functional ability, in 10 patients, as a pilot trial. Tests at post-intracranial aneurysm treatment discharge and six-week follow-up were compared to see which measures detected changes. Results; Kinematic tests captured significant improvements from discharge to six-week follow-up, indexed by reduced motor errors and improved learning. Increased Addenbrooke’s Cognitive Examination-Revised scores reflected some recovery of memory function for most individuals, but other standardised cognitive measures, functional outcome scores and a psychological questionnaire showed no changes. Conclusions; Kinematic measures can identify variation in performance in individuals with only slightly improved abilities post-intracranial aneurysm treatment. These measures may provide a sensitive way to explore post-operative outcomes following intracranial aneurysm treatment, or other similar surgical procedures

Equilibrium crystal shapes in the Potts model

The three-dimensional $q$-state Potts model, forced into coexistence by fixing the density of one state, is studied for $q=2$, 3, 4, and 6. As a function of temperature and number of states, we studied the resulting equilibrium droplet shapes. A theoretical discussion is given of the interface properties at large values of $q$. We found a roughening transition for each of the numbers of states we studied, at temperatures that decrease with increasing $q$, but increase when measured as a fraction of the melting temperature. We also found equilibrium shapes closely approaching a sphere near the melting point, even though the three-dimensional Potts model with three or more states does not have a phase transition with a diverging length scale at the melting point.Comment: 6 pages, 3 figures, submitted to PR

Advanced biopolymer-coated drug-releasing titania nanotubes (TNTs) implants with simultaneously enhanced osteoblast adhesion and antibacterial properties

Abstract not availableTushar Kumeria, Htwe Mon, Moom Sinn Aw, Karan Gulati, Abel Santos, Hans J. Griesser, Dusan Losi

Properties of Interfaces in the two and three dimensional Ising Model

To investigate order-order interfaces, we perform multimagnetical Monte Carlo simulations of the $2D$ and $3D$ Ising model. Following Binder we extract the interfacial free energy from the infinite volume limit of the magnetic probability density. Stringent tests of the numerical methods are performed by reproducing with high precision exact $2D$ results. In the physically more interesting $3D$ case we estimate the amplitude $F^s_0$ of the critical interfacial tension $F^s = F^s_0 t^\mu$ to be $F^s_0 = 1.52 \pm 0.05$. This result is in good agreement with a previous MC calculation by Mon, as well as with experimental results for related amplitude ratios. In addition, we study in some details the shape of the magnetic probability density for temperatures below the Curie point.Comment: 25 pages; sorry no figures include

FoFi: The Development of a Handheld Monitoring Device in Predicting Naturally Occurring Forest Fires

Forest fires, which are natural or artificial burning of woodlands, negatively affect people and the environment. In the Philippines, Cordillera is one of the hotspots for forest fires, with approximately 122 forest fire incidents. Thus, developing a monitoring device for the early prevention of forest fires would reduce these incidents\u27 frequency. This research aimed to create a handheld prototype device, FoFi, that gathers quantitative data which can be used with the Department of Natural Resources\u27s data science and predictive analytics. Using an Arduino Microcontroller and sensors, the device will collect and send data. Two phases were conducted to create a monitoring prototype device for predicting forest fires. According to the results, the temperature and humidity (DHT-22) sensor showed reliable data since it can detect temperature under normal conditions, having a mean of 30.65°C; also, it precisely recorded the relative humidity with a mean of 7.89%. The Global Positioning System (GPS) module obtained a mean error of 7.251 m, which exhibited accuracy in detecting GPS coordinates. Additionally, the Globe SIM showed efficiency for Global Systems for Mobile (GSM) communication since the mean length of time for sending a message is 5.022 s. On the other hand, the gas sensor (MQ-2) and photoresistor lacks sensitivity when used; thus, a more sensitive sensor is recommended. In conclusion, the handheld device was able to achieve its purpose of monitoring forest fires

Spectral ergodicity and normal modes in ensembles of sparse matrices

We investigate the properties of sparse matrix ensembles with particular regard for the spectral ergodicity hypothesis, which claims the identity of ensemble and spectral averages of spectral correlators. An apparent violation of the spectral ergodicity is observed. This effect is studied with the aid of the normal modes of the random matrix spectrum, which describe fluctuations of the eigenvalues around their average positions. This analysis reveals that spectral ergodicity is not broken, but that different energy scales of the spectra are examined by the two averaging techniques. Normal modes are shown to provide a useful complement to traditional spectral analysis with possible applications to a wide range of physical systems.Comment: 22 pages, 15 figure