Minimal Setup Research Articles

The gauge coupling evolutions of an SU(8) theory with the maximally symmetry breaking pattern

We study the renormalizable group equations (RGEs) of the extended strong and weak gauge couplings in an SU(8) theory, where three-generational SM fermions are non-trivially embedded. This framework was previously found to generate the observed SM quark/lepton mass hierarchies and the Cabibbo-Kobayashi-Maskawa mixing pattern through its maximally breaking pattern. The field theoretical two-loop RGEs can not achieve the gauge coupling unification with the minimal setup, unless additional adjoint Higgs fields as well as the gravity-induced d = 5 term to the SU(8) field strength term are included.

Methods for Evaluating Tibial Accelerations and Spatiotemporal Gait Parameters during Unsupervised Outdoor Movement.

The purpose of this paper is to introduce a method of measuring spatiotemporal gait patterns, tibial accelerations, and heart rate that are matched with high resolution geographical terrain features using publicly available data. These methods were demonstrated using data from 218 Marines, who completed loaded outdoor ruck hikes between 5-20 km over varying terrain. Each participant was instrumented with two inertial measurement units (IMUs) and a GPS watch. Custom code synchronized accelerometer and positional data without a priori sensor synchronization, calibrated orientation of the IMUs in the tibial reference frame, detected and separated only periods of walking or running, and computed acceleration and spatiotemporal outcomes. GPS positional data were georeferenced with geographic information system (GIS) maps to extract terrain features such as slope, altitude, and surface conditions. This paper reveals the ease at which similar data can be gathered among relatively large groups of people with minimal setup and automated data processing. The methods described here can be adapted to other populations and similar ground-based activities such as skiing or trail running.

Designing a virtual reality system for clinical education and examination

The COVID-19 pandemic clearly showed how much medical and clinical students’ education relied on physical instruction and examination. The work presented here was born by the fact that medical and clinical education had to be suspended during the social distancing phase of the pandemic. This work presents the lessons learned from creating a virtual reality system (VTRACS) for educating and assessing clinical students on a limited budget. Our work showed that clinical education could be done in a virtual space with a minimal virtual reality setup and a low-cost virtual reality headset.

A Scalable Method to Fabricate 2D Hydrogel Substrates for Mechanobiology Studies with Independent Tuning of Adhesiveness and Stiffness.

Mechanical signals from the extracellular matrix are crucial in guiding cellular behavior. Two-dimensional hydrogel substrates for cell cultures serve as exceptional tools for mechanobiology studies because they mimic the biomechanical and adhesive characteristics of natural environments. However, the interdisciplinary knowledge required to synthetize and manipulate these biomaterials typically restricts their widespread use in biological laboratories, which may not have the material science expertise or specialized instrumentation. To address this, we propose a scalable method that requires minimal setup to produce 2D hydrogel substrates with independent modulation of the rigidity and adhesiveness within the range typical of natural tissues. In this method, norbornene-terminated 8-arm polyethylene glycol is stoichiometrically functionalized with RGD peptides and crosslinked with a di-cysteine terminated peptide via a thiol-ene click reaction. Since the synthesis process significantly influences the final properties of the hydrogels, we provide a detailed description of the chemical procedure to ensure reproducibility and high throughput results. We demonstrate examples of cell mechanosignaling by monitoring the activation state of the mechanoeffector proteins YAP/TAZ. This method effectively dissects the influence of biophysical and adhesive cues on cell behavior. We believe that our procedure will be easily adopted by other cell biology laboratories, improving its accessibility and practical application.

Modeling Conformational Transitions of Biomolecules from Atomic Force Microscopy Images using Normal Mode Analysis.

Observing a single biomolecule performing its function is fundamental in biophysics as it provides important information for elucidating the mechanism. High-speed atomic force microscopy (HS-AFM) is a unique and powerful technique that allows the observation of biomolecular motion in a near-native environment. However, the spatial resolution of HS-AFM is limited by the physical size of the cantilever tip, which restricts the ability to obtain atomic details of molecules. In this study, we propose a novel computational algorithm designed to derive atomistic models of conformational dynamics from AFM images. Our method uses normal-mode analysis to describe the expected motions of the molecule, allowing these motions to be represented with a limited number of coordinates. This approach mitigates the problem of overinterpretation inherent in the analysis of AFM images with limited resolution. We demonstrate the effectiveness of our algorithm, NMFF-AFM, using synthetic data sets for three proteins that undergo significant conformational changes. NMFF-AFM is a fast and user-friendly program that requires minimal setup and has the potential to be a valuable tool for biophysical studies using HS-AFM.

The Backscatter Gating method for time, energy, and position resolution characterization of long form factor organic scintillators

This work details a Compton-scattering-based methodology, referred to as Backscatter Gating (BSG), for characterizing the time, energy, and position resolutions of long form factor organic scintillators using a single, fairly minimal measurement setup. Such a method can ease the experimental burden in scenarios where many such scintillator elements may need to be individually characterized before assembly into a larger detector system. A thorough theoretical exploration of the systematic parameters is provided, and the BSG method is then demonstrated by a series of experimental measurements. This “complete” characterization via the BSG method is novel, having previously been used primarily for energy resolution characterization. The method also allows for determination of the assembled scintillator's technical attenuation length and provides a means of verifying the presence or absence of flaws within the scintillator or its optical coupling.

Enhanced Gait Phases Recognition by EMG and Kinematics Information Fusion and a Minimal Recording Setuping Setup

The limited mobility of lower limb amputees highlights the need for advancements in prosthetic control strategies to restore natural locomotion. This paper proposes an information fusion approach for gait phase recognition using surface electromyography (sEMG) and kinematics data. Time-domain (TD) features were extracted from the myoelectric data and three data-driven models, specifically Support Vector Machine (SVM), K-Nearest Neighbours (KNN), and Artificial Neural Network (ANN), were compared in three different input conditions i.e. sEMG features, hip angle, and their fusion. Gait phase estimation results averaged from 40 healthy participants during normal walking with 10 strides per each demonstrated that the proposed fusion approach has consistently outperformed (p<0.0001) the other two conditions achieving a maximum accuracy of 85.48% with SVM. The findings suggest promising applications in prosthetic motion control and rehabilitative exoskeletons, highlighting the potential for improved user-driven strategies in lower limb prostheses.

Minimal quantum heat pump based on high-frequency driving and non-Markovianity.

We propose a minimal setup for a quantum heat pump consisting of two tunnel-coupled quantum dots, each hosting a single level and each being coupled to a different fermionic reservoir. The working principle relies on both non-Markovian system-bath coupling and driving-induced resonant coupling. We describe the system using a reaction-coordinate mapping in combination with Floquet-Born-Markov theory and characterize its performance.

A cosmological sandwiched window for lepton-number breaking scale

A singlet majoron can arise from the seesaw framework as a pseudo-Goldstone boson when the heavy Majorana neutrinos acquire masses via the spontaneous breaking of global U(1) L symmetry. The resulting cosmological impacts are usually derived from the effective majoron-neutrino interaction, and the majoron abundance is accumulated through the freeze-in neutrino coalescence. However, a primordial majoron abundance can be predicted in a minimal setup and lead to distinctive cosmological effects. In this work, we consider such a primordial majoron abundance from relativistic freeze-out and calculate the modification to the effective neutrino number N eff. We demonstrate that the measurements of N eff will constrain the parameter space from a primordial majoron abundance in an opposite direction to that from neutrino coalescence. When the contributions from both the primordial abundance and the freeze-in production coexist, the U(1) L -breaking scale (seesaw scale) f will be pushed into a “sandwiched window”. Remarkably, for majoron masses below 1 MeV and above the eV scale, the future CMB-S4 experiment will completely close such a low-scale seesaw window for f ∈ [1,105] GeV. We highlight that any new light particle with a primordial abundance that couples to Standard Model particles may lead to a similar sandwiched window, and such a general phenomenon deserves careful investigation.

Misalignment production of vector boson dark matter from axion-SU(2) inflation

We present a new mechanism to generate a coherently oscillating dark vector field from axion-SU(2) gauge field dynamics during inflation. The SU(2) gauge field acquires a nonzero background sourced by an axion during inflation, and it acquires a mass through spontaneous symmetry breaking after inflation. We find that the coherent oscillation of the dark vector field can account for dark matter in the mass range of 10-13 – 1 eV in a minimal setup. In a more involved scenario, the range can be wider down to the fuzzy dark matter region. One of the dark vector fields can be identified as the dark photon, in which case this mechanism evades the notorious constraints for isocurvature perturbation, statistical anisotropy, and the absence of ghosts that exist in the usual misalignment production scenarios. Phenomenological implications are discussed.

Detection of gastrointestinal foreign bodies in pets using single-grid-based dark-field X-ray imaging

Gastrointestinal foreign bodies (GI-FBs) occur when pets consume non-digestible items that do not readily pass through the stomach or intestines. While some GI-FBs pass through, many become lodged along the gastrointestinal tract and cause discomfort, often leading to sickness. Conventional absorption-based radiography is widely used to detect GI-FBs in pets. However, detecting low-density FBs, such as wood, plastic, clothing, and sticks, is typically difficult using conventional radiography. This study presents a novel approach for detecting low-density GI-FBs in pets by using single-grid-based dark-field X-ray imaging (SG-DFXI). It obtains microstructural information from small-angle X-ray scattering (SAXS) of the sample using a conventional X-ray source and grid. SG-DFXI requires minimal exposure and system setup and is specifically utilized to detect low-density materials that are invisible when using conventional radiography. To validate the efficacy of the proposed method, an experiment was conducted on a mouse phantom attached to a wooden chopstick as a low-density GI-FB. Quantitative evaluation was performed using image quality metrics of the contrast-to-noise ratio (CNR) and relative contrast gain (RCG). The CNR value measured in the dark-field image obtained with an autocorrelation length of ξG = 294 nm was 4.59, approximately 5.4 times larger than that of the absorption image obtained in the same imaging setup. In addition, the RCG characteristics improved as the autocorrelation length of the system increased; the RCG value for ξG = 294 nm was 5.4, approximately 3.2 times larger than that for ξG = 194 nm. Thus, increasing the autocorrelation length of the system is critical to improve its ability to detect low-density FBs. Consequently, SG-DFXI appears to be a promising method that can be used effectively and easily to detect GI-FBs in pets, which are barely visible in absorption images.

A Comparison of Neural-Network-Based Intrusion Detection against Signature-Based Detection in IoT Networks

Over the last few years, a plethora of papers presenting machine-learning-based approaches for intrusion detection have been published. However, the majority of those papers do not compare their results with a proper baseline of a signature-based intrusion detection system, thus violating good machine learning practices. In order to evaluate the pros and cons of the machine-learning-based approach, we replicated a research study that uses a deep neural network model for intrusion detection. The results of our replicated research study expose several systematic problems with the used datasets and evaluation methods. In our experiments, a signature-based intrusion detection system with a minimal setup was able to outperform the tested model even under small traffic changes. Testing the replicated neural network on a new dataset recorded in the same environment with the same attacks using the same tools showed that the accuracy of the neural network dropped to 54%. Furthermore, the often-claimed advantage of being able to detect zero-day attacks could not be seen in our experiments.

Dynamical inflation stimulated cogenesis

We propose a minimal setup that realises dynamical inflection point inflation, and, using the same field content, generates neutrino masses, a baryon asymmetry of the universe, and dark matter. A dark SU(2)D gauge sector with a dark scalar doublet playing the role of inflaton is considered along with several doublet and singlet fermions sufficient to realise multiple inflection points in the inflaton potential. The singlet fermions couple to SM leptons and generate neutrino masses via the inverse seesaw mechanism. Those fermions also decay asymmetrically and out of equilibrium, generating a baryon asymmetry via leptogenesis. Some of the fermion doublets are dark matter, and they are produced via inflaton decay and freeze-in annihilation of the same fermions that generate the lepton asymmetry. Reheating, leptogenesis, and dark matter are all at the TeV scale.

AVDOS-VR: Affective Video Database with Physiological Signals and Continuous Ratings Collected Remotely in VR

Investigating emotions relies on pre-validated stimuli to evaluate induced responses through subjective self-ratings and physiological changes. The creation of precise affect models necessitates extensive datasets. While datasets related to pictures, words, and sounds are abundant, those associated with videos are comparatively scarce. To overcome this challenge, we present the first virtual reality (VR) database with continuous self-ratings and physiological measures, including facial EMG. Videos were rated online using a head-mounted VR device (HMD) with attached emteqPRO mask and a cinema VR environment in remote home and laboratory settings with minimal setup requirements. This led to an affective video database with continuous valence and arousal self-rating measures and physiological responses (PPG, facial-EMG (7x), IMU). The AVDOS-VR database includes data from 37 participants who watched 30 randomly ordered videos (10 positive, neutral, and negative). Each 30-second video was assessed with two-minute relaxation between categories. Validation results suggest that remote data collection is ecologically valid, providing an effective strategy for future affective study designs. All data can be accessed via: www.gnacek.com/affective-video-database-online-study.

A Minimal and Multi-Source Recording Setup for Ankle Joint Kinematics Estimation During Walking Using Only Proximal Information From Lower Limb

A Minimal and Multi-Source Recording Setup for Ankle Joint Kinematics Estimation During Walking Using Only Proximal Information From Lower Limb

Effective noisy dynamics within the phenotypic space of a growth-rate maximizing population

Microbial systems exhibit marked variability in metabolic phenotypes. A recently-proposed class of models explains this feature within a minimal mathematical setup which assumes that populations evolve towards maximum growth rate in a ‘phenotypic space’ subject to an intrinsic ‘diffusive’ stochasticity that causes small random changes in single-cell phenotypes. In such a framework, variability results from the exploration–exploitation balance between hardly accessible fast-growing phenotypes and easily accessible slow-growing ones. Here we extend the above scheme to include a degree of extrinsic noise, showing that the population dynamics over the phenotypic space is captured by an effective process that conflates both sources of randomness. This in turn leads to a simple approximation for the asymptotic distribution of the population over the phenotypic space, highlighting the connection between the strength of the noise that affects the dynamics and the degree of optimization. The theory thus obtained displays an excellent agreement with numerical simulations of low-dimensional systems.

Assessment of Petri nets Regulation Control methodologies for automation systems

Industry 4.0 and smart manufacturing bring new interesting possibilities and challenges, a particular one is the large-scale automation with minimal set-up time and flexibility. To face this challenge, control approaches based on Discrete Event Systems (DES), such as Supervisory Control Theory (SCT), Generalized Mutual Exclusions Constraints (GMEC) and Petri net-based Regulation Control (RC), may provide convenient solutions; however, few works have been reported in the literature describing the application of these approaches. In this work, the RC approach based on Petri nets is applied to three case studies: (1) an electro-pneumatic cell controlled by a Programming Logic Controller device (PLC); (2) a simulated hydraulic process controlled by a PLC (a virtual commissioning scheme); (3) a simulated robotic manufacturing cell controlled by a software tool. In addition, an assessment of the existing methodologies in RC for modelling, specification, control synthesis and control implementation is conducted. The findings of this work provide three contributions: (1) a practical validation of the applied methodologies and the identification of required extensions; (2) a discussion about the validity of frequently considered assumptions and hypotheses in DES; (3) a reference for practitioners on the implementation of the RC approach, as well as its limitations and advantages.

Scale invariant Einstein-Cartan gravity and flat space conformal symmetry

We find the conditions under which scale-invariant Einstein-Cartan gravity with scalar matter fields leads to an approximate conformal invariance of the flat space particle theory up to energies of the order of the Planck mass. In the minimal setup, these models, in addition to the fields of the Standard Model and the graviton, contain only one extra particle — a massless dilaton. Theories of this type can pave the way for a self-completion all the way up the Planck scale and lead to rather universal inflationary predictions, close to those of the simplest Higgs-inflation scenario in the metric theory of gravity.

Evaluating a cutting-edge augmented reality-supported navigation system for spinal instrumentation

ObjectiveDorsal instrumentation using pedicle screws is a standard treatment for multiple spinal pathologies, such as trauma, infection, or degenerative indications. Intraoperative three-dimensional (3D) imaging and navigated pedicle screw placement are used at multiple centers. For the present study, we evaluated a new navigation system enabling augmented reality (AR)-supported pedicle screw placement while integrating navigation cameras into the reference array and drill guide. The present study aimed to evaluate its clinical application regarding safety, efficacy, and accuracy.MethodsA total of 20 patients were operated on between 06/2021 and 01/2022 using the new technique for intraoperative navigation. Intraoperative data with a focus on accuracy and patient safety, including patient outcome, were analyzed. The accuracy of pedicle screw placement was evaluated by intraoperative CT imaging.ResultsA median of 8 (4–18) pedicle screws were placed in each case. Percutaneous instrumentation was performed in 14 patients (70%). The duration of pedicle screw placement (duration scan–scan) was 56 ± 26 (30–107) min. Intraoperative screw revision was necessary for 3 of 180 pedicle screws (1.7%). Intraoperatively, no major complications occurred—one case of delay due to software issues and one case of difficult screw placement were reported.ConclusionThe current study's results could confirm the use of the present AR-supported system for navigated pedicle screw placement for dorsal instrumentation in clinical routine. It provides a reliable and safe tool for 3D imaging-based pedicle screw placement, only requires a minimal intraoperative setup, and provides new opportunities by integrating AR.

Distractor Application and Dry Arthroscopy to Improve Articular Visualization During Scapula Fracture Surgery Via a Posterior Approach.

Intra-articular glenoid displacement is an indication for open reduction and internal fixation of scapular fractures. However, direct visualization of the glenoid is limited, and articular reductions are typically performed and assessed using extra-articular cortical reduction reads and fluoroscopic imaging. In this technique, we describe the application of a distractor for direct visualization of the glenoid articular surface. In this way, anatomic reduction of the glenoid articular surface can be assessed and achieved. In addition, we discuss the use of a portable, dry arthroscopy when needed. This technique has resulted in good-to-excellent articular reductions by adjusting extra-articular reads that seemed adequate before intra-articular visualization. This technique is safe, requires minimal extra set-up or instruments, and results in good-to-excellent articular reductions.