Miracle-dz/UniFAR-FTUs huggingface dataset:
Air‐Blast Suppression as a Function of Explosive‐Charge Burial Depth

The blast wave from buried explosions consists primarily of a pulse induced by the ground shock followed by another pulse when the explosive gases are vented to the atmosphere. The latter pulse provides the dominant contribution for the shallower burial depths. Air‐blast measurements made along the ground surface for 46 chemical explosive and 7 nuclear explosive detonations have shown the peak overpressure of the ground‐shock‐induced pulse to be about the same for chemical and nuclear explosions in basal rock as for chemical explosions in alluvial soil. The ground‐shock‐induced pulse has not been observed for nuclear explosions in soil. The peak overpressure from venting gases is about equal for chemical explosives in basalt rock and alluvial soil. Peak overpressures are higher for nuclear explosions in soil, in part because the cavity pressures at the time of venting are higher; peak overpressures are lower for nuclear explosions in rock, presumably because less gas is formed and because the pulse from venting gas coincides with the negative phase following the ground‐shock‐induced pulse, thus reducing overpressure amplitude. Measurements have been made over a sufficiently large range of charge burial depths that a pattern of air‐blast suppression with charge burial can be presented.
Comparative study on cupric oxide nanoparticles synthesis in saline buffer versus basic water by Spondias mombin peel extract for biocatalysis

Abstract The authors herein compared the morphology, homogeneity and biocatalytic (peroxidase) activity of the synthesized cupric oxide nanoparticles (CuO NPs) from Spondias mombin peel extract for the first time in saline buffer and basic H2O system respectively. The saline buffer-assisted synthesis of CuO NPs produced homogenous and monoclinic shaped nanoparticles having excellent peroxidase activity compared to basic H2O. The saline buffer-assisted synthesis of CuO NPs was optimized in terms of peel extract concentration, time, and light. The study about elemental compositions, crystallinity, size and shape of CuO NPs (average size ⁓ 45 nm and monoclinic shape in PBS system) were confirmed through EDS, XRD, and SEM techniques. And the completion of CuO NPs synthesis within 5 minutes much shorter than the basic H2O system was confirmed through UV-visible studies. Finally, the saline buffer-assisted CuO NPs showed 10 times higher peroxidase activity against TMB-H2O2 system than basic H2O-system.
Photoelectron energy spectra from elastic rescattering in ultrastrong laser fields: A relativistic extension of the three-step model

Using a relativistic adaptation of a three-step recollision model we calculate photoelectron energy spectra for ionization with elastic scattering in ultrastrong laser ﬁelds up to 24 a.u. (2 × 10 19 W/cm 2 ). Hydrogen-like and noble gas species with Hartree-Fock scattering potentials show a reduction in elastic rescattering beyond 6 × 10 16 W/cm 2 when the laser Lorentz deﬂection of the photoelectron exceeds its wave function spread. A relativistic rescattering enhancement occurs at 2 × 10 18 W/cm 2 , commensurate with the relativistic motion of a classical electron in a single ﬁeld cycle. The noble gas results are compared with available experiments. The theory approach is well suited to modeling scattering in the ultrastrong intensity regime that lies between traditional strong ﬁelds and extreme relativistic interactions.
Generation and interferometric analysis of high charge optical vortices

We report on the generation of optical vortex beams using spatial phase modulation with spiral phase mirrors. The spiral phase mirrors are manufactured by direct machining with an ultra-precision single point diamond turning lathe. The imperfection of the machined phase mirrors and its impact on the generated vortex beams are analyzed with interferometric measurements. Our phase mirror has a surface roughness of 3 nm and a maximum peak–valley deviation of λ/30. The vortex charges of our light beams are directly verified by counting the fringes of their corresponding interferograms. We directly observed the successful generation of an optical vortex beam with a charge as high as 5050. We study the Fourier images of the vortex beams to characterize the quality of the beams. We obtained a conversion efficiency of 92.8% from a TEM00 beam to a vortex beam with charge 1020. This technique of generating optical singularities can potentially be used to produce more complex optical wavefronts, such as optical knots.
Polymorphic Uncertain Structural Analysis: Challenges in Data‐Driven Inelasticity

This contribution addresses polymorphic uncertainty quantification within structural analysis of reinforced concrete structures composed of heterogeneous concrete and reinforcement (e.g. steel bars or carbon fibres). The macroscopic material behaviour of concrete is strongly dependent on the mesoscopic heterogeneities, which are considered by multiscale modelling. The heterogeneous mesoscopic material behaviour is characterized by representative volume elements (RVE) and the transition of scales is carried out by utilizing numerical homogenization methods.
Optimizing artificial neural networks for mechanical problems by physics‐based Rao‐Blackwellization: Example of a hyperelastic microsphere model

The Rao‐Blackwell scheme provides an algorithm on how to implement sufficient information into statistical models and is adopted here to deterministic material modeling. Even crude initial predictions are improved significantly by Rao‐Blackwellization, which is proven by an error inequality. This is first illustrated by an analytical example of hyperelasticity utilizing knowledge on principal stretches. Rao‐Blackwellization improves a 1‐d uniaxial strain‐energy relation into a 3‐d relation that resembles the classical micro‐sphere approach. The presented scheme is moreover ideal for data‐based approaches, because it supplements existing predictions with additional physical information. A second example hence illustrates the application of Rao‐Blackwellization to an artificial neural network to improve its prediction on load paths, which were absent in the original training process.
A phase field model for fractures in ice shelves

Ice shelves are large floating ice masses, that are formed when glaciers are becoming afloat at the margin of ice sheets. One dominating mass loss mechanism of ice shelves is calving, describing the detachment of icebergs at the front. Ice shelves stabilize inland ice glaciers due to buttressing. If the stabilizing effect of an ice shelf vanishes because of disintegration or thinning, the corresponding glacier accelerates resulting in sea level rise.
Neural populations in the language network differ in the size of their temporal receptive windows

Language comprehension is fast and seemingly effortless. However, in spite of long knowing what brain regions enable this feat, our knowledge of the precise neural computations that these frontal and temporal regions implement remains limited. One highly controversial question is whether functional differences exist among the neural populations that comprise the language network. Leveraging the high spatiotemporal resolution of intracranial recordings, we clustered the timecourses of responses to sentences and linguistically degraded conditions and discovered three response profiles that robustly differ in their temporal dynamics. These profiles appear to reflect different temporal receptive windows (TRWs), with average TRWs of about 1, 4, and 6 words, as estimated with a simple one-parameter model. Neural populations exhibiting these profiles are interleaved across the language network, which suggests that all language regions have direct access to distinct, multi-scale representations of linguistic input—a property that may be critical for the efficiency and robustness of language processing.
Book Review: Joint Models for Longitudinal and Time-to-Event Data: With Applications in R, by Dimitris Rizopoulos

Joint models for longitudinal and time-to-event (survival) data have received much attention in the statistical literature in the past two decades. These models are useful in the analysis of survival data and longitudinal data, especially data from health research. For example, in cancer studies we may wish to identify time-varying markers or risk factors for progression to cancer. We may consider a longitudinal model for data from potential markers or risk factors and a survival model for progression to cancer, and then make a joint statistical inference since the two types of data are associated. In AIDS studies, we may investigate the relationship between CD4 values and times to death or AIDS. In this case, we should consider a joint model for the longitudinal CD4 data and times to death or AIDS in order to address measurement errors in CD4. More generally, in survival models with time-dependent covariates, a longitudinal model for the covariates is required to address possible measurement errors and missing data (since covariate data may not be available at event times). In longitudinal models with informative dropouts, a survival model may be used to address dropouts. In both cases, the longitudinal data and the survival data are associated, so a joint model is required in order to make unbiased and efficient statistical inference, since separate inferences for the two models may lead to biased and inefficient results. Although there has been extensive research on joint models in statistical literature, comprehensive reviews of joint model research have only appeared in journal articles and book chapters. To my knowledge, this is probably the first book dedicated to joint models. Although joint models are useful in many applications, their use in practice has still been quite limited. A major reason is the lack of software for joint models, due to intensive computation-associated joint model inference. The author of this book has filled this important gap and developed a nice R package “JM” for joint models. The book provides a detailed description of the “JM” R package, with many nice illustrating examples. Most examples are chosen from medical studies. The “JM” R package allows users to fit a wide variety of joint models, including Cox models and accelerated failure time models for survival data. It can also be used to make predictions of event times, generate imputations for missing longitudinal data, and perform model diagnostics for the longitudinal model and the survival model in the joint model context. Overall, the R package is quite flexible and easy to use. It is an important contribution to the area of joint models. There are several nice features of this book. First, it is quite readable. It is accessible to graduate students or senior undergraduate students in statistics,
Complete Configuration Space Analysis for Structure Determination of Symmetric Homo-oligomers by NMR

Symmetric homo-oligomers (protein complexes with similar subunits arranged symmetrically) play pivotal roles in complex biological processes such as ion transport and cellular regulation. Structure determination of these complexes is necessary in order to gain valuable insights into their mechanisms. Nuclear Magnetic Resonance (NMR) spectroscopy is an experimental technique used for structural studies of such complexes. The data available for structure determination of symmetric homo-oligomers by NMR is often sparse and ambiguous in nature, raising concerns about existing heuristic approaches for structure determination. We have developed an approach that is complete in that it identifies all consistent conformations, data-driven in that it separately evaluates the consistency of structures to data and biophysical constraints and efficient in that it avoids explicit consideration of each of the possible structures separately. By being complete, we ensure that native conformations are not missed. By being data-driven, we are able to separately quantify the information content in the data alone versus data and biophysical modeling. We take a configuration space (degree-of-freedom) approach that provides a compact representation of the conformation space and enables us to efficiently explore the space of possible conformations. This thesis demonstrates that the configuration space-based method is robust to sparsity and ambiguity in the data and enables complete, data-driven and efficient structure determination of symmetric homo-oligomers.
A new approach for the genetic algorithm

This paper proposes a new approach based on two explicit rules of Mendel experiments and Mendel's population genetics for the genetic algorithm (GA). These rules are the segregation and independent assortment of alleles, respectively. This new approach has been simulated for the optimization of certain test functions. The doctrinal sense of GA is conceptually improved by this approach using a Mendelian framework. The new approach is different than the conventional one in terms of crossover, recombination, and mutation operators. The results obtained here are in agreement with those of the conventional GA, and even better in some cases. These results suggest that the new approach is overall more sensitive and accurate than the conventional one. Possible ways of improving the approach by including more genetic formulae in the code are also discussed.
Quantum state determination: Quorum for a particle in one dimension

In this paper we wish to illuminate the axiom that the quantal state describes a statistical ensemble of similar systems identically prepared, and is not to be identified with any single system. The mathematical representative of the general quantum state is the density matrix or statistical operator in Hilbert space. We demonstrate how this operator may be determined empirically by calculations involving only the measured mean values of a set of observables we call a ’’quorum. ’’ As an example of this approach a state determination procedure is described for a spinless particle moving in one dimension; the corresponding quorum turns out to involve only position data associated with various instants subsequent to the act of preparation.
Seamless Authentication for Ubiquitous Devices

User authentication is an integral part of our lives; we authenticate ourselves to personal computers and a variety of other things several times a day. Authentication is burdensome. When we wish to access to a computer or a resource, it is an additional task that we need to perform – an interruption in our workflow. In this dissertation, we study people’s authentication behavior and attempt to make authentication to desktops and smartphones less burdensome for users. First, we present the findings of a user study we conducted to understand people’s authentication behavior: things they authenticate to, how and when they authenticate, authentication errors they encounter and why, and their opinions about authentication. In our study, participants performed about 39 authentications per day on average; the majority of these authentications were to personal computers (desktop, laptop, smartphone, tablet) and with passwords, but the number of authentications to other things (e.g., car, door) was not insignificant. We saw a high failure rate for desktop and laptop authentication among our participants, affirming the need for a more usable authentication method. Overall, we found that authentication was a noticeable part of all our participants’ lives and burdensome for many participants, but they accepted it as cost of security, devising their own ways to cope with it. Second, we propose a new approach to authentication, called bilateral authentication,
Computational design of novel Cas9 PAM-interacting domains using evolution-based modelling and structural quality assessment

We present here an approach to protein design that enables to leverage (i) scarce functional information such as experimental data (ii) evolutionary information learned from a natural sequence variants and (iii) physics-grounded modeling. Using a Restricted Boltzmann Machine (RBM), we learned a sequence model of a protein family. We use semi-supervision to leverage available functional information during the RBM training. We then propose a strategy to explore the protein representation space that can be informed by external models such as an empirical force field method (FoldX). This method was applied to a domain of the Cas9 protein responsible for recognition of a short DNA motif. We experimentally assessed the functionality of 71 variants that were generated to explore a range of RBM and FoldX energies. We show how a combination of functional, structural and evolutionary information can identify functional variants with high accuracy. Sequences with as many as 50 differences (20% of the protein domain) to the wild-type retained functionality. Overall, 21/71 sequences designed with our method were functional. Interestingly, 6/71 sequences showed an improved activity in comparison with the original wild-type protein sequence. These results demonstrate the interest in further exploring the synergies between machine-learning of protein sequence representations and physics grounded modeling strategies informed by structural information.
Multicellular PD Control in Microbial Consortia

We propose a multicellular implementation of a biomolecular PD feedback controller to regulate gene expression in a microbial consortium. The implementation involves distributing the proportional and derivative control actions between two different cellular populations that can communicate with each other and regulate the output of a third target cellular population. We derive analytical conditions on biological parameters and control gains to adjust the system’s static and dynamical properties. We then validate the strategy’s performance and robustness through extensive in silico experiments.
Grain size dependence of electrical and optical properties in Nb-doped anatase TiO2

Anatase thin films of pure TiO2 and 6% niobium doped TiO2 (Nb:TiO2) were fabricated on LaAlO3(100) by pulsed laser deposition. The electrical properties of Nb:TiO2 films are grain-size dependent, i.e., the larger grain size, the higher conductivity, and mobility. For all TiO2 and for Nb:TiO2 with small mean grain size (d 15 nm), particularly, a blueshift in Nb:TiO2 is governed by the Burstein–Moss effect.
HIV-1 Vpr combats the PU.1-driven antiviral response in primary human macrophages

HIV-1 Vpr promotes efficient spread of HIV-1 from macrophages to T cells by transcriptionally downmodulating restriction factors that target HIV-1 Envelope protein (Env). Here we find that Vpr induces broad transcriptomic changes by targeting PU.1, a transcription factor necessary for expression of host innate immune response genes, including those that target Env. Consistent with this, we find silencing PU.1 in infected macrophages lacking Vpr rescues Env. Vpr downmodulates PU.1 through a proteasomal degradation pathway that depends on physical interactions with PU.1 and DCAF1, a component of the Cul4A E3 ubiquitin ligase. The capacity for Vpr to target PU.1 is highly conserved across primate lentiviruses. In addition to impacting infected cells, we find that Vpr suppresses expression of innate immune response genes in uninfected bystander cells, and that virion-associated Vpr can degrade PU.1. Together, we demonstrate Vpr counteracts PU.1 in macrophages to blunt antiviral immune responses and promote viral spread.
Neuronal phase shifts differ for excitation vs. inhibition: a computer modeling study

Rhythmic activity is ubiquitous in neural systems, and impedance analysis has been widely used to examine frequency-dependent responses of neuronal membranes to rhythmic inputs. Impedance analysis assumes the neuronal membrane is a linear system, requiring the use of small signals to stay in a near-linear regime. However, postsynaptic potentials are often large and trigger nonlinear mechanisms. We therefore augmented impedance analysis to evaluate membrane responses in this nonlinear domain, analyzing responses to injected current for subthreshold membrane voltage (V memb ), suprathreshold spike-blocked V memb , and spiking in a validated neocortical pyramidal neuron computer model. Responses in these output regimes were asymmetrical, with different phase shifts during hyperpolarizing and depolarizing half-cycles. Suprathreshold chirp stimulation gave equivocal results due to nonstationarity of response, requiring us to use fixed-frequency sinusoids. Sinusoidal inputs produced phase retreat : action potentials occurred progressively later in cycles of the input stimulus, resulting from adaptation. Conversely, sinusoidal current with increasing amplitude over cycles produced a pattern of phase advance : action potentials occurred progressively earlier. Phase retreat was dependent on I h and I AHP currents; phase advance was modulated by these currents. Our results suggest differential responses of cortical neurons depending on the frequency of oscillatory input in the delta – beta range, which will play a role in neuronal responses to shifts in network state. We hypothesize that intrinsic cellular properties complement network properties and contribute to in vivo phase-shift phenomena such as phase precession, seen in place and grid cells, and phase roll, observed in non-place cells in hippocampus
Single-cell multiomic analysis reveals the involvement of Type I interferon-responsive CD8+ T cells in amyloid beta-associated memory loss

Alzheimer’s disease (AD) is the leading cause of dementia worldwide, but there are limited therapeutic options and no current cure. While the involvement of microglia in AD has been highly appreciated, the role of other innate and adaptive immune cells remains largely unknown, partly due to their scarcity and heterogeneity. This study aimed to study non-microglial immune cells in wild type and AD-transgenic mouse brains across different ages. Our results uncovered the presence of a unique CD8+ T cell population that were selectively increased in aging AD mouse brains, here referred to as “disease-associated T cells (DATs)”. These DATs were found to express an elevated tissue-resident memory and Type I interferon-responsive gene signature. Further analysis of aged AD mouse brains showed that these CD8+ T cells were not present in peripheral or meningeal tissues. Preventing CD8+ T cell development in AD-transgenic mice via genetic deletion of beta-2 microglobulin (B2m) led to a reduction of amyloid-β plaque formation in aged mice, and improved memory in AD-transgenic mice as early as four months of age. The integration of transcriptomic and epigenomic profiles at the single-cell level revealed potential transcription factors that reshape the regulomes of CD8+ T cells. These findings highlight a critical role for DATs in the progression of AD and provide a new avenue for treatment.