Experimental results on data analysis algorithms for extracting and interpreting edge feature data for duct tape and textile physical fit examinations.

A physical fit is an important observation that can result from the forensic analysis of trace evidence as it conveys a high degree of association between two items. However, physical fit examinations can be time-consuming, and potential bias from analysts may affect judgment. To overcome these shortcomings, a data analysis algorithm using mutual information and a decision tree has been developed to support practitioners in interpreting the evidence. We created these tools using data obtained from physical fit examinations of duct tape and textiles analyzed in previous studies, along with the reasoning behind the analysts' decisions. The relative feature importance is described by material type, enhancing the knowledge base in this field. Compared with the human analysis, the algorithms provided accuracies above 90%, with an improved rate of true positives for most duct tape subsets. Conversely, false positives were observed in high-quality scissor cut (HQ-HT-S) duct tape and textiles. As such, it is advised to use these algorithms in tandem with human analysis. Furthermore, the study evaluated the accuracy of physical fits when only partial sample lengths are available. The results of this investigation indicated that acceptable accuracies for correctly identifying true fits and non-fits occurred when at least 35% of a sample length was present. However, lower accuracies were observed for samples prone to stretching or distortion. Therefore, the models described here can provide a valuable supplementary tool but should not be the sole means of evaluating samples.

Using convolutional neural networks to support examiners in duct tape physical fit comparisons.

This paper describes the construction and use of a machine-learning model to provide objective support for a physical fit examination of duct tapes. We present the ForensicFit package that can preprocess and database raw tape images. Using the processed tape image, we trained a convolutional neural network to compare tape edges and predict membership scores (i.e., fit or non-fit category). A dataset of nearly 2000 tapes and 4000 images was evaluated, including various quality grades: low, medium, and high, as well as two separation methods, scissor-cut and hand-torn. The model predicts medium-quality and high-quality scissor-cut tape more accurately than hand-torn, whereas for low-quality tape predicts the hand-torn tapes more accurately. These results are consistent with previous studies performed on the same datasets by analyst examinations. A method of pixel importance was also implemented to show which pixels are used to make the decision. This method can confirm some fit features that correspond with analyst-identified features, like edge morphology and backing pattern. This pilot study demonstrates the feasibility of computational algorithms to build physical fit databases and automated comparisons using deep neural networks, which can be used as a model for other materials.

Two-Dimensional Noble Metal Chalcogenides in the Frustrated Snub-Square Lattice.

We study two-dimensional noble metal chalcogenides, with compositions {Cu, Ag, Au}2{S, Se, Te}, crystallizing in a snub-square lattice. This is a semiregular two-dimensional tesselation formed by triangles and squares that exhibits geometrical frustration. We use for comparison a square lattice, from which the snub-square tiling can be derived by a simple rotation of the squares. The monolayer snub-square chalcogenides are very close to thermodynamic stability, with the most stable system (Ag2Se) a mere 7 meV/atom above the convex hull of stability. All compounds studied in the square and snub-square lattice are semiconductors, with band gaps ranging from 0.1 to more than 2.5 eV. Excitonic effects are strong, with an exciton binding energy of around 0.3 eV. We propose the Cu (001) surface as a possible substrate to synthesize Cu2Se, although many other metal and semiconducting surfaces can be found with very good lattice matching.

Topic modeling in density functional theory on citations of condensed matter electronic structure packages.

With an increasing number of new scientific papers being released, it becomes harder for researchers to be aware of recent articles in their field of study. Accurately classifying papers is a first step in the direction of personalized catering and easy access to research of interest. The field of Density Functional Theory (DFT) in particular is a good example of a methodology used in very different studies, and interconnected disciplines, which has a very strong community publishing many research articles. We devise a new unsupervised method for classifying publications, based on topic modeling, and use a DFT-related selection of documents as a use case. We first create topics from word analysis and clustering of the abstracts from the publications, then attribute each publication/paper to a topic based on word similarity. We then make interesting observations by analyzing connections between the topics and publishers, journals, country or year of publication. The proposed approach is general, and can be applied to analyze publication and citation trends in other areas of study, beyond the field of Density Function Theory.

Vickers hardness prediction from machine learning methods.

The search for new superhard materials is of great interest for extreme industrial applications. However, the theoretical prediction of hardness is still a challenge for the scientific community, given the difficulty of modeling plastic behavior of solids. Different hardness models have been proposed over the years. Still, they are either too complicated to use, inaccurate when extrapolating to a wide variety of solids or require coding knowledge. In this investigation, we built a successful machine learning model that implements Gradient Boosting Regressor (GBR) to predict hardness and uses the mechanical properties of a solid (bulk modulus, shear modulus, Young's modulus, and Poisson's ratio) as input variables. The model was trained with an experimental Vickers hardness database of 143 materials, assuring various kinds of compounds. The input properties were calculated from the theoretical elastic tensor. The Materials Project's database was explored to search for new superhard materials, and our results are in good agreement with the experimental data available. Other alternative models to compute hardness from mechanical properties are also discussed in this work. Our results are available in a free-access easy to use online application to be further used in future studies of new materials at www.hardnesscalculator.com .

Elective laparoscopic sigmoidectomy with preservation of the superior rectal artery prior to endoscopic decompression in sigmoid volvulus

Sigmoid volvulus is a frequent cause of intestinal obstruction. Its management has evolved with the use of laparoscopic surgery, achieving an elective sigmoid resection with anastomosis after a flexible endoscopic detorsion. A female patient was admitted to the emergency room with abdominal pain, distention, and constipation. The abdominal computed tomography showed a whirled sigmoid mesentery in addition to dilated sigmoid loops, and coffee bean sign. The patient successfully underwent a flexible endoscopic detorsion and was scheduled for elective sigmoid colectomy with rectal superior artery preservation and primary anastomosis. During the sigmoid resection, the superior rectal artery preservation is related to a better prognostic, with less bleeding, anastomotic leakage, and hospital stay. Currently, there are few reports of the laparoscopic preservation of the superior rectal artery in patients with sigmoid volvulus. (AU)

Pressure-induced order-disorder transitions in ß-In2S3: an experimental and theoretical study of structural and vibrational properties.

This joint experimental and theoretical study of the structural and vibrational properties of ß-In2S3 upon compression shows that this tetragonal defect spinel undergoes two reversible pressure-induced order-disorder transitions up to 20 GPa. We propose that the first high-pressure phase above 5.0 GPa has the cubic defect spinel structure of α-In2S3 and the second high-pressure phase (ϕ-In2S3) above 10.5 GPa has a defect α-NaFeO2-type (R3̄m) structure. This phase, related to the NaCl structure, has not been previously observed in spinels under compression and is related to both the tetradymite structure of topological insulators and to the defect LiTiO2 phase observed at high pressure in other thiospinels. Structural characterization of the three phases shows that α-In2S3 is softer than ß-In2S3 while ϕ-In2S3 is harder than ß-In2S3. Vibrational characterization of the three phases is also provided, and their Raman-active modes are tentatively assigned. Our work shows that the metastable α phase of In2S3 can be accessed not only by high temperature or varying composition, but also by high pressure. On top of that, the pressure-induced ß-α-ϕ sequence of phase transitions evidences that ß-In2S3, a BIII2XV3 compound with an intriguing structure typical of AIIBIII2XVI4 compounds (intermediate between thiospinels and ordered-vacancy compounds) undergoes: (i) a first phase transition at ambient pressure to a disordered spinel-type structure (α-In2S3), isostructural with those found at high pressure and high temperature in other BIII2XV3 compounds; and (ii) a second phase transition to the defect α-NaFeO2-type structure (ϕ-In2S3), a distorted NaCl-type structure that is related to the defect NaCl phase found at high pressure in AIIBIII2XVI4 ordered-vacancy compounds and to the defect LiTiO2-type phase found at high pressure in AIIBIII2XVI4 thiospinels. This result shows that In2S3 (with its intrinsic vacancies) has a similar pressure behaviour to thiospinels and ordered-vacancy compounds of the AIIBIII2XVI4 family, making ß-In2S3 the union link between such families of compounds and showing that group-13 thiospinels have more in common with ordered-vacancy compounds than with oxospinels and thiospinels with transition metals.

Unveiling the mechanisms behind the ferroelectric response in the Sr(Nb,Ta)O2N oxynitrides.

Oxynitride perovskites of the type ABO2N have attracted considerable attention thanks to their potential ferroelectric behavior and tunable bandgap energy, making them ideal candidates for photocatalysis processes. Therefore, in order to shed light on the origin of their ferroelectric response, here we report a complete analysis of the structural and vibrational properties of SrNbO2N and SrTaO2N oxynitrides. By employing first-principles calculations, we analyzed the symmetry in-equivalent structures considering the experimentally reported parent I4/mcm space group (with a phase a0a0c- in Glazer's notation). Based on the I4/mcm reference within the 20-atoms unit-cell, we found and studied the ensemble of structures where different octahedral anionic orderings are allowed by symmetry. Thus, by exploring the vibrational landscape of the cis- and trans-type configuration structures and supported by the ionic eigendisplacements and the Born effective charges, we explained the mechanism responsible for the appearance of stable ferroelectric phases in both anionic orderings. The latter goes from covalent-driven in the trans-type ordering to the geometrically-driven in the cis-type configuration. Finally, we found in both cases that the biaxial xy epitaxial strain considerably enhances such ferroelectric response.

Honduras: two hurricanes, COVID-19, dengue and the need for a new digital health surveillance system.

A recently published article of this journal stated that informatics solutions can guide better public health decision-making during the COVID 19 (Coronavirus Disease 2019) pandemic. Honduras is a country facing the COVID-19 pandemic with a weak health surveillance system while also fighting a dengue epidemic and the aftermath of two hurricanes that struck its territory in November 2020. In response, we as academics started a COVID-19 and Dengue Observatory combining several technological platforms and developing multidisciplinary research to help the country navigate the crisis. Mapping the pandemic and the natural disasters showed us that technology can be applied toward epidemiology to benefit communities in a time of need by quickly building a basic digital health surveillance system for Honduras.

ABINIT: Overview and focus on selected capabilities.

abinit is probably the first electronic-structure package to have been released under an open-source license about 20 years ago. It implements density functional theory, density-functional perturbation theory (DFPT), many-body perturbation theory (GW approximation and Bethe-Salpeter equation), and more specific or advanced formalisms, such as dynamical mean-field theory (DMFT) and the "temperature-dependent effective potential" approach for anharmonic effects. Relying on planewaves for the representation of wavefunctions, density, and other space-dependent quantities, with pseudopotentials or projector-augmented waves (PAWs), it is well suited for the study of periodic materials, although nanostructures and molecules can be treated with the supercell technique. The present article starts with a brief description of the project, a summary of the theories upon which abinit relies, and a list of the associated capabilities. It then focuses on selected capabilities that might not be present in the majority of electronic structure packages either among planewave codes or, in general, treatment of strongly correlated materials using DMFT; materials under finite electric fields; properties at nuclei (electric field gradient, Mössbauer shifts, and orbital magnetization); positron annihilation; Raman intensities and electro-optic effect; and DFPT calculations of response to strain perturbation (elastic constants and piezoelectricity), spatial dispersion (flexoelectricity), electronic mobility, temperature dependence of the gap, and spin-magnetic-field perturbation. The abinit DFPT implementation is very general, including systems with van der Waals interaction or with noncollinear magnetism. Community projects are also described: generation of pseudopotential and PAW datasets, high-throughput calculations (databases of phonon band structure, second-harmonic generation, and GW computations of bandgaps), and the library libpaw. abinit has strong links with many other software projects that are briefly mentioned.

Low-Energy Phases of Bi Monolayer Predicted by Structure Search in Two Dimensions.

We employ an ab-initio structure search algorithm to explore the configurational space of bismuth in quasi-two dimensions. A confinement potential is introduced to restrict the movement of atoms within a predefined thickness to find the stable and metastable forms of monolayer Bi. In addition to the two known low-energy structures (puckered monoclinic and buckled hexagonal), our calculations predict three new phases: α, ß, and γ. Each phase exhibits peculiar electronic properties, ranging from metallic (α and γ) to semiconducting (puckered monoclinic, buckled hexagonal, and ß) monolayers. Topologically nontrivial features are predicted for buckled hexagonal and γ phases. We also remark on the role of 5d electrons on the electronic properties of Bi monolayer. We conclude that Bi provides a rich playground to study distortion-mediated metal-insulator phase transitions in quasi-2D.

Optimizing the orbital occupation in the multiple minima problem of magnetic materials from the metaheuristic firefly algorithm.

We present the use and implementation of the firefly algorithm to help in scanning the multiple metastable minima of orbital occupations in density functional theory (DFT) plus Hubbard U correction and to identify the ground state occupations in strongly correlated materials. We show the application of this implementation with the Abinit code on KCoF3 and UO2 crystals, which are typical d and f electron systems with numerous occupation minima. We demonstrate the validity and performance of the method by comparing with previous methodologies. The method is general and can be applied to any code using constrained occupation matrices.

Surface Recombination in Ultra-Fast Carrier Dynamics of Perovskite Oxide La0.7Sr0.3MnO3 Thin Films.

Aspects of the optoelectronic performance of thin-film ferromagnetic materials are evaluated for application in ultrafast devices. Dynamics of photocarriers and their associated spin polarization are measured using transient reflectivity (TR) measurements in cross linear and circular polarization configurations for La0.7Sr0.3MnO3 films with a range of thicknesses. Three spin-related recombination mechanisms have been observed for thicker films (thickness of d ≥ 20 nm) at different time regimes (τ), which are attributed to the electron-phonon recombination (τ < 1 ps), phonon-assisted spin-lattice recombination (τ ∼ 100 ps), and thermal diffusion and radiative recombination (τ > 1 ns). Density functional theory (DFT+U) based first-principles calculations provide information about the nature of the optical transitions and their probabilities for the majority and the minority spin channels. These transitions are partly responsible for the aforementioned recombination mechanisms, identified through the comparison of linear and circular TR measurements. The same sets of measurements for thinner films (4.4 nm ≤ d < 20 nm) revealed an additional relaxation dynamic (τ ∼ 10 ps), which is attributed to the enhanced surface recombination of charge carriers. Our DFT+U calculations further corroborate this observation, indicating an increase in the surface density of states with decreasing film thickness which results in higher amplitude and smaller time constant for surface recombination as the film thickness decreases.

Structural search for stable Mg-Ca alloys accelerated with a neural network interatomic model.

We have combined a neural network formalism with metaheuristic structural global search algorithms to systematically screen the Mg-Ca binary system for new (meta)stable alloys. The combination of these methods allows for an efficient exploration of the potential energy surface beyond the possibility of the traditional searches based on ab initio energy evaluations. The identified pool of low-enthalpy structures was complemented with special quasirandom structures (SQS) at different stoichiometries. In addition to the only Mg-Ca phase known to form under standard synthesis conditions, C14-Mg2Ca, the search has uncovered several candidate materials that could be synthesized under elevated temperatures or pressures. We show that the vibrational entropy lowers the relative free energy of several phases with magnesium kagome layers: C15 and C36 Laves structures at the 2 : 1 composition and an orthorhombic oS36 structure at the 7 : 2 composition. The estimated phase transition temperatures close to the melting point leave open the possibility of synthesizing the predicted materials at high temperatures. At high pressures up to 10 GPa, two new phases at the 1 : 1 and 3 : 1 Mg : Ca stoichiometries become thermodynamically stable and should form in multi-anvil experiments.

Direct Magnetization-Polarization Coupling in BaCuF_{4}.

Herewith, first-principles calculations based on density functional theory are used to describe the ideal magnetization reversal through polarization switching in BaCuF_{4} which, according to our results, could be accomplished close to room temperature. We also show that this ideal coupling is driven by a single soft mode that combines both polarization, and octahedral rotation. The later being directly coupled to the weak ferromagnetism of BaCuF_{4}. This, added to its strong Jahn-Teller distortion and its orbital ordering, makes this material a very appealing prototype for crystals in the ABX_{4} family for multifunctional applications. The described mechanism behaves ideally as it couples the ferroelectric and the magnetic properties naturally and it has not been reported previously.

Electrostatic potential and valence modulation in La0.7Sr0.3MnO3 thin films.

The Mn valence in thin film La0.7Sr0.3MnO3 was studied as a function of film thickness in the range of 1-16 unit cells with a combination of non-destructive bulk and surface sensitive X-ray absorption spectroscopy techniques. Using a layer-by-layer valence model, it was found that while the bulk averaged valence hovers around its expected value of 3.3, a significant deviation occurs within several unit cells of the surface and interface. These results were supported by first principles calculations. The surface valence increases to up to Mn3.7+, whereas the interface valence reduces down to Mn2.5+. The change in valence from the expected bulk value is consistent with charge redistribution due to the polar discontinuity at the film-substrate interface. The comparison with theory employed here illustrates how this layer-by-layer valence evolves with film thickness and allows for a deeper understanding of the microscopic mechanisms at play in this effect. These results offer insight on how the two-dimensional electron gas is created in thin film oxide alloys and how the magnetic ordering is reduced with dimensionality.

Firefly Algorithm Applied to Noncollinear Magnetic Phase Materials Prediction.

In most noncollinear crystal magnets, the number of metastable states is quite large and any calculation that tries to predict the ground state can fall into one of the possible metastable phases. In this work, we generalize the population based meta-heuristic firefly algorithm to the problem of the noncollinear magnetic phase ground state prediction within density functional theory (DFT). We extend the different steps in the firefly algorithm to this specific problem by using polarized constrained DFT calculations, whereby using Lagrange multipliers the directions of the atom magnetic moments remain fixed. By locking the directions of the magnetic moments at each search iteration, the method allows one to explore the entire Born-Oppenheimer energy surface of existing and physically plausible noncollinear configurations present in a crystal. We demonstrate that the number of minima can be large, which restrains the use of exhaustive searches.

Isotopic Heft on the B1 l Silent Mode in Ultra-Narrow Gallium Nitride Nanowires.

Wurtzite semiconductor compounds have two silent modes, B1 l and B1 h. A silent mode is a vibrational mode that carries neither a dipole moment nor Raman polarizability. Thus, they are forbidden in both infrared reflectivity and Raman spectroscopy. Astonishingly, we detected the B1 l mode in high-quality, ultra-narrow GaN nanowires using resonant Raman scattering, although the B1 h was not observed, and there is no immediate explanation for this asymmetric finding. The Raman experiments were performed using several laser lines from 647 to 325 nm; the latter is a wavelength in which Raman becomes resonant. Actually, we observed the B1 l mode only in resonance, indicating that the appearance of this mode is related to Fröhlich electron-phonon interactions; i.e., a dipole moment emerging in the B1 l silent mode may not be present in the B1 h mode. To shed light onto the physical origin of these observations, we performed density functional theory calculations of the lattice dynamics in GaN. We performed a careful analysis of the different physical mechanisms that allow the forbidden mode to appear to explain the physics underlying the nonzero dipole moment in the B1 l mode, and the reason why this dipole moment is not present in the B1 h mode.

Controlling the magnetic and optical responses of a MoS2 monolayer by lanthanide substitutional doping: a first-principles study.

The electronic, magnetic and optical properties of lanthanide substitutional doping (∼2% concentration) on the MoS2 monolayer have been investigated within the density functional theory formalism together with the Hubbard correction (DFT+U). The dopants investigated include Ce, Eu, Gd, Lu and Tm. The calculated dopant substitutional energies under both Mo-rich and S-rich conditions suggest that it is possible to experimentally realize the lanthanide doped MoS2 monolayer systems. The Eu, Gd and Tm dopants induce strong magnetization in the host lattice. The electronic structure calculations reveal that the dopants have a p-type character and they exhibit a half-metallic behavior in the Gd and Eu doped systems. A dilute magnetic semiconducting behavior can also be realized in Gd, Eu and Tm doped systems by slightly tuning the Fermi level. All the dopants refine the optical responses of the host system with the onset of the optical absorption edge shifting to lower energies within the visible range (red shift phenomenon). We observe an optical anisotropy for two different directions of the electric field (E) polarizations, i.e. parallel, E∥, and perpendicular, E⊥, to the xy-plane. Lanthanide substitutional doping significantly influences the electron energy loss spectra (EELS), absorption spectra, and dielectric properties of the host MoS2 monolayer. Furthermore, we notice that lanthanide substitutional doping could enhance the photocatalytic properties of the MoS2 monolayer.

Room temperature ferroelectricity in fluoroperovskite thin films.

The NaMnF3 fluoride-perovskite has been found, theoretically, to be ferroelectric under epitaxial strain becoming a promising alternative to conventional oxides for multiferroic applications. Nevertheless, this fluoroperovskite has not been experimentally verified to be ferroelectric so far. Here we report signatures of room temperature ferroelectricity observed in perovskite NaMnF3 thin films grown on SrTiO3. Using piezoresponse force microscopy, we studied the evolution of ferroelectric polarization in response to external and built-in electric fields. Density functional theory calculations were also performed to help understand the strong competition between ferroelectric and paraelectric phases as well as the profound influences of strain. These results, together with the magnetic order previously reported in the same material, pave the way to future multiferroic and magnetoelectric investigations in fluoroperovskites.