Miracle-dz/UniFAR-FTUs huggingface dataset:
The central amygdala modulates distinctive conflict-like behaviors in a naturalistic foraging task

Conflict situations elicit a diverse range of behaviors that extend beyond the simplistic approach or avoidance dichotomy. However, many conflict-related studies have primarily focused on approach suppression, neglecting the complexity of these behaviors. In our study, we exposed rats to a semi-naturalistic foraging task, presenting them with a trade-off between a food reward and a predatory threat posed by a robotic agent. We observed that rats displayed two conflict-like behaviors (CLBs)—diagonal approach and stretched posture—when facing a robotic predator guarding a food pellet. After electrolytic lesions to the central amygdala (CeA), both conflict behaviors were significantly reduced, accompanied by a decrease in avoidance behavior (hiding) and an increase in approach behavior (frequency of interactions with the robot). A significant negative correlation between avoidance and approach behaviors emerged after the CeA lesion; however, our data suggest that CLBs are not tightly coupled with either approach or avoidance behaviors, showing no significant correlation to those behaviors. Our findings indicate that the CeA plays a crucial role in modulating conflict behaviors, competing with approach suppression in risky situations.
Long-time dynamics of coherent states in strong magnetic fields

abstract:We consider the Schr\"odinger evolution of strongly localized wave packets under the magnetic Laplacian in the plane $\Bbb{R}^2$. When the initial energy is low, we obtain a precise control, in Schwartz seminorms, of the propagated states for times of order $1/\hbar$, where $\hbar$ is Planck's constant. In this semiclassical regime, we prove that the initial particle will always split into multiple coherent states, each one following the average dynamics of the guiding center motion but at its own speed, demonstrating a purely quantum ``ubiquity'' phenomenon.
A Tailored Approach to Leishmaniases Vaccination: Comparative Evaluation of the Efficacy and Cross-Protection Capacity of DNA vs. Peptide-Based Vaccines in a Murine Model

Zoonotic leishmaniases are a worldwide public health problem for which the development of effective vaccines remains a challenge. A vaccine against leishmaniases must be safe and affordable and should induce cross-protection against the different disease-causing species. In this context, the DNA vaccine pHisAK70 has been demonstrated to induce, in a murine model, a resistant phenotype against L. major, L. infantum, and L. amazonensis. Moreover, a chimeric multiepitope peptide, HisDTC, has been obtained by in silico analysis from the histone proteins encoded in the DNA vaccine and has showed its ability to activate a potent CD4+ and CD8+ T-cell protective immune response in mice against L. infantum infection. In the present study, we evaluated the plasmid DNA vaccine pHisAK70 in comparison with the peptide HisDTC (with and without saponin) against L. major and L. infantum infection. Our preliminary results showed that both formulations were able to induce a potent cellular response leading to a decrease in parasite load against L. infantum. In addition, the DNA candidate was able to induce better lesion control in mice against L. major. These preliminary results indicate that both strategies are potentially effective candidates for leishmaniases control. Furthermore, it is important to carry out such comparative studies to elucidate which vaccine candidates are the most appropriate for further development.
Study of the influence of oscillating trailing edge flaps on the AVATAR rotor using CFD simulations

In the present paper the effect of an oscillating trailing edge flap on the wind turbine blade loading and performance is investigated. Two CFD Unsteady Reynolds Averaged Navier-Stokes (URANS) solvers along with a simpler engineering Blade Element Momentum (BEM) model are used to simulate sinusoidal trailing edge flaps with a length of 10% chord and 10° maximum deflection, centered at 75% span and extending at 15% of the blade radius. The predictions reveal significant 3D effects on the hysteresis, as well as the location and magnitude of the maximum amplitude of loading. The increase of flapping frequency from 1P to 3P results in lower amplitude and larger hysteresis. A stronger influence of the flap is observed at the negative flap angles. The effect of increasing the flap length on the power and thrust of the turbine rotor is also investigated.
Model Predictive Controller Approach for Automated Vehicle’s Path Tracking

In this paper, a model predictive control (MPC) approach for controlling automated vehicle steering during path tracking is presented. A (linear parameter-varying) LPV vehicle plant model including steering dynamics is proposed to determine the system evolution matrices. The steering dynamics are modeled in two different ways by using first-order lag and a second-order lag; the application of the first-order system resulted in a slightly more accurate path-following. Additionally, a cascade MPC structure is applied in which two MPCs are used; the second-order steering dynamics are separated from the path-following controller in a second MPC. Both steering system models and the cascade MPC are evaluated in simulation and on a test vehicle. The reference trajectory is calculated based on a fixed predefined path by transforming the necessary path segment to the vehicle ego coordinate system, thereby describing the reference for the path-following task in a novel way. The MPC method computes the optimal steering angle vector at each time step for following the path. The longitudinal dynamics is controlled separately by a PI controller. After simulation evaluation, experimental tests were conducted on a test vehicle on an asphalt surface. Both simulation and experimental results prove the effectiveness of the proposed reference definition method. The effect of the applied steering system models is evaluated. The inclusion of the steering dynamics in the prediction model resulted in a significant increase in controller performance. Finally, the computational requirements of the proposed control and modeling methods are also discussed.
Optical Coherence Tomography in Neurodegenerative Disorders

Purpose Ophthalmic findings, including abnormalities of the optic nerve and retina, are common features of a number of neurodegenerative disorders. These ophthalmic abnormalities have emerged as potential biomarkers of disease progression in several neurodegenerative conditions. In addition, anterior visual system changes have clinical relevance because they can be a significant cause of disability. Optical coherence tomography (OCT) allows for rapid, non-invasive imaging and quantitative analysis of the optic nerve and retina. Over the past 15 years, OCT has been widely used to investigate axonal and neuronal degeneration in the eye, and the relationship with disease severity in multiple sclerosis, neuromyelitis optica Alzheimer’s disease and Parkinson’s disease. OCT is now frequently utilised in observational studies, clinical practice and therapeutic trials of potential neuroprotective agents. The objectives of the studies outlined in this research thesis were twofold: Firstly, to investigate the morphology of the optic nerve head and retina, using OCT, in patients with neurodegenerative disorders, and to determine the relationship between OCT measurements and disease duration and severity. Methods Subjects with neurodegenerative disorders including muscular dystrophies, Huntington’s disease, Parkinson’s disease, motor neuron disease, ataxias and hereditary spastic paraplegia were recruited. All participants underwent a complete neuro-ophthalmic assessment including retinal photography and OCT examination of the peripapillary retinal nerve fibre layer (RNFL) and macula. Ophthalmic findings were compared with those from a healthy control group. Additionally, neurological assessment was undertaken in order to be able to assess the relationship between OCT findings and disease severity. Results OCT examination was performed in patients with a diverse range of neurodegenerative disorders. There was preferential thinning of the temporal RNFL in the Huntington’s disease and cerebellar ataxia neuropathy vestibular areflexia syndrome (CANVAS) cohorts. Global RNFL thickness was reduced in the Friedreich’s ataxia and hereditary spastic paraplegia (HSP) groups. In the myotonic dystrophy type 1 (DM1), Parkinson’s disease, motor neuron disease and facioscapulohumeral
Characterization of Chiral Nanostructured Surfaces Made via Colloidal Lithography

Optically anisotropic materials were produced via colloidal lithography and characterized using scanning electronic microscopy (SEM), confocal microscopy, and polarimetry. A compact hexagonal array mask composed of silica sub-micron particles was fabricated via the Langmuir–Blodgett self-assembly technique. Subsequently, the mask pattern was transferred onto monocrystalline silicon and commercial glass substrates using ion beam etching in a vacuum. Varying the azimuthal angle while etching at oblique incidence carved screw-like shaped pillars into the substrates, resulting in heterochiral structures depending on the azimuthal angle direction. To enhance the material’s optical properties through plasmon resonance, gold films were deposited onto the pillars. Polarimetric measurements were realized at normal and oblique incidences, showing that the etching directions have a clear influence on the value of the linear birefringence and linear dichroism. The polarimetric properties, especially the chiroptical responses, increased with the increase in the angle of incidence.
Age-Period-Cohort Study of Breast Cancer Mortality in Brazil in State Capitals and in Non-Capital Municipalities from 1980 to 2019

Breast cancer was identified as the cancer with the highest mortality rate among women in Brazil. This study analyzed the effects of age, period and birth cohort on the breast cancer mortality rate for Brazilian women, comparing state capitals and non-capital municipalities. Population and deaths data were extracted from the Brazilian Unified Health System database for women aged 30 years or older, for the years between 1980 and 2019. The effects were analyzed using the age-period-cohort model. Age effect on breast cancer mortality is observed in the model through higher mortality rates at older ages. Period effect is similar in all regions in the form of a marked increase in the rate ratio (RR) in non-capital municipalities by period than in state capitals. The RR of birth cohorts in the state capitals remained stable (north, northeast and central-west regions) or decreased followed by an increase in the most recent cohorts (Brazil as a whole and the southeast and south regions). The RR for the other municipalities, however, showed a progressive increase in the cohorts for all regions. Policies and actions focused on breast cancer in women should consider these differences among Brazilian regions, state capitals and other municipalities.
Machine Learning-Assisted Computationally Efficient Target Detection and Tracking in Massive Fully Digital Phased Arrays

We consider the problem of 3D target detection and tracking using large fully digital radar arrays such as phased array radars or MIMO radars, in the presence of interference or jammers and under realistic array impairments. Accurate target detection and tracking in such case demands a large amount of computation due to beamforming and subsequent detection operations, which can create a bottleneck in the rate at which IQ samples are processed. In addition, the beamforming approach needs to provide suppression of strong jammers under practical array imperfections such as calibration errors. To ensure robust interference suppression and enable real time target tracking, we propose several methods to reduce the complexity of beamforming, detection and tracking. We develop a reinforcement learning-based framework to adaptively control the angle resolution of beamforming and detection based on the location estimates and uncertainties of currently tracked targets. We comprehensively investigate robust and computationally efficient adaptive beamformer design through a closed loop analysis of several covariance based algorithms with reduced complexity of matrix inversion or iterative beamforming coefficient adaptation. We demonstrate and evaluate our methods in both a simulated environment and on a real radar array for long range target tracking with a software-defined GPU-accelerated digital radar processing pipeline incorporating our proposed algorithms.
Principles for tuning heat zone controllers in a belt furnace through modeling and simulation

In this thesis the heating area of a belt furnace for annealing metal powder has been modeled. The model was extended with PI-controllers for controlling the energy added to the model. It was simulated with differently tuned controllers to test tuning principles for finding suitable control parameters for the process. The most promising tuning principles was then written as a manual with the aim for process engineers at Hoganas AB. The process is running on a daily basis with control parameters that causes unnecessary overshoots and oscillations in the system.With updated and more suitable control parameters, the furnace is believed to be more efficient. Hoganas has several processes of the same type which the manual could be applied to. The process consists of non-linear thermal radiation, conduction and convection. It is very slow and has approximately no dead time, thus excluding many tuning principles that rely on the dead time. The most promising tuning principle to apply is the lambda-tuning principle which is often used in the process industry [Astrom and Hagglund, 2006]. Due to the accuraccy of the model, the design parameter was choosen to ensure stability and monotonic setpoint changes. The manual can be found in Appendix D.
Protein Secondary Structure Prediction Using AutoEncoder Network and Bayes Classifier

Protein secondary structure prediction is belong to bioinformatics,and it's important in research area. In this paper, we propose a new prediction way of protein using bayes classifier and autoEncoder network. Our experiments show some algorithms including the construction of the model, the classification of parameters and so on. The data set is a typical CB513 data set for protein. In terms of accuracy, the method is the cross validation based on the 3-fold. Then we can get the Q3 accuracy. Paper results illustrate that the autoencoder network improved the prediction accuracy of protein secondary structure.
Comparative detection efficacy of primers targeting SpeI-AvaI restriction fragment and small subunit ribosomal RNA gene of Babesia bigemina

The objective of the study is to evaluate the comparative detection efficacy of primers targeting SpeI-AvaI restriction fragment and small subunit ribosomal RNA (SSU rRNA) gene of Babesia bigemina by employing conventional polymerase chain reaction (PCR) on 783 animals (296 cattle and 487 buffaloes) of low lying (bet) area of Punjab. The detection rate of SpeI-AvaI and SSU rRNA PCR assays was 3.96% (31/783), and 6.64% (52/783), respectively. Among cattle and buffaloes, prevalence of B. bigemina was higher (P<0.01) in cattle by both the primers. The sensitivity and specificity of SSU rRNA PCR as compared to SpeI-AvaI restriction fragment PCR was 100% and 97.2%, respectively. The blast analysis of the nucleotides of the sequenced amplicons of Ludhiana isolates of SpeI-AvaI and SSU rRNA PCR assay of B. bigemina showed 83 and 100% similarity with available sequence in Genbank. The analysis of evolutionary divergence revealed that range of divergence was lying between 0.000 to 0.011 between SSU rRNA sequence with the other sequences of B. bigemina as well as Babesia species. To conclude, the primers targeting SSU rRNA gene are a better tool for amplification of the B. bigemina.
Nanotechnology-Enabled Ultrasound Transducers

Ultrasound transducer is a core component for transductions between acoustic energy and electrical energy in numerous applications including medical imaging, therapy, human health monitoring and non-destructive testing (NDT). The rapid advancement of nanotechnology in recent years has opened up new prospects for ultrasound transducers. The integration of nanomaterials and nanofabrication techniques with ultrasound transducers offers ample opportunities for enhancing transducer performances and opening up new applications. The objective of this review is to provide the state-of-the-art advancement of nanotechnology-enabled ultrasound transducers, with a focus on nanomaterials applied in both piezoelectric transducers and optoacoustic transducers, as well as fabrication techniques of nanostructured materials for ultrasound transducers. Firstly, nanomaterials and nanofabrication techniques for both piezoelectric transducers and optoacoustic transducers are reviewed and summarized. Representative nanotechnology-enabled ultrasound transducers for biomedical and NDT applications are then examined. Finally, a discussion of major challenges and future research directions of nanotechnology-enabled ultrasound transducers are presented.
The effects of laser beam incident angle and intensity distribution on Fabry-Perot etalon spectrum

Fabry-Perot(F-P) etalon has important applications in laser detection, lidar and laser communication systems. In practical applications, the spectrum of the F-P etalon is affected by various factors, such as incident angle, divergence angle, spectral width, intensity distribution of the incident beam, absorption loss, surface defects of the plate and so on. The effects of the incident angle and the beam intensity distribution on F-P etalon spectrum are mainly analyzed. For the first time, taking into account both the beam incident angle and divergence angle, the precise analytical expression of the F-P etalon transmission spectrum is derived. For the Gaussian light intensity distribution, the precise analytical expression of the F-P etalon transmission spectrum is derived. The simulation analysis is carried out and the results are as follows. When the beam divergence angle is not zero, the incident angle increases, on the one hand, the center of the etalon spectrum is moved to the high frequency, and the frequency shift is linear with the square of the incident angle. The slope decreases with the increase of the divergence angle. On the other hand, resulting in peak reduction, spectral line broadening, and with the divergence angle increases, the more obvious the phenomenon. Considering the distribution of Gaussian light intensity, the spectrum of the etalon will be improved with the increase concentration of beam energy. On the one hand, the peak value is increased, the spectral line is narrowed and with the incidence angle increases, the degree of improvement is more obvious. On the one hand, the center of the spectrum moves toward the low frequency, but the larger the incident angle, the smaller the movement amount. The error of frequency discrimination or frequency locking by using the F-P etalon spectrum increases rapidly with the increase of the beam incident angle and beam divergence angle, and the Gaussian light intensity distribution beam can effectively reduce the measurement error.
Critical review of electrocardiography measurement systems and technology

Electrocardiography (ECG) is widely used in clinical practice, for example to diagnose coronary artery disease or the cause of chest pain during a stress test, while the patient is running on a treadmill. Ambulatory ECG monitoring is used for long term recording of ECG signals, while the patient carries out his/her daily activities. Artefacts in ECG are caused by the patient’s movement, moving cables, interference from outside sources, electromyography (EMG) interference and electrical contact from elsewhere on the body. Most of these artefacts can be minimized by using proper electrode design and ECG circuitry. However, artefacts due to subject’s movement are hard to identify and eliminate and can be easily mistaken for symptoms of arrhythmia and the physiological effects of exercise, leading to misdiagnosis and false alarms. This study provides an overview of various ambulatory ECG measurement systems and electrode topologies used for ECG sensing. The challenges associated with ambulatory ECG monitoring and the techniques used to overcome those challenges have also been discussed in this paper.
Confocal laser feedback microscopy for in-depth imaging applications

We propose confocal laser feedback microscopy for in-depth imaging of highly scattering samples. This technique provides a compact configuration for microscopy in reflectance mode; it is based on laser feedback interferometry which is a sensing technique where the laser acts as both transmitter and receiver of the beam. Operating at 850 nm, it offers an ideal platform for non-invasive and in vivo imaging of soft biological tissues. To explore the technique, the authors performed microscopic imaging of micro-glass-spheres (with diameter sizes of 10-20 mu m) deep within an agar gel sample, at depth of 0.43 mm from the surface. Experimental results show the feasibility of a compact, low-cost, and simple laser-scanning microscope with possible biomedical imaging applications.
Adaptive threshold method for peak detection of surface electromyography signal from around shoulder muscles

ABSTRACT This paper illustrates the accurate identification of the surface electromyography signal obtained from the shoulder muscles (Teres, Trapezius and Pectoralis) of amputee subjects with three different arm motions (elevation, protraction and retraction). During the acquisition of the signal, a variety of variations (amplitude, frequency and noise) were introduced into the acquired signal which will misguide in the prediction of motion of the shoulder. Therefore, a novel approach has been aimed to adaptively adjust the threshold of Teager energy operator in order to filter the unwanted peaks in the pre-processing stage of the surface electromyography (SEMG) signal. Results show that the proposed approach is accurate and effective in the analysis of biomedical signal where peaks are important to detect without the knowledge of the shape of the waveform. As clinical research continues, these algorithms helps us to process SEMG signal and the identified signal would be used to design more accurate and efficient controllers for the upper-limb amputee.
Research on channel-related polar code with an optimum code length for wireless ultraviolet communications

In this paper a polar coding scheme for ultraviolet communication (UVC) systems is proposed and experimentally implemented to address the high path loss propagation, which severely deteriorates the communication performance. Firstly, we analyze the property of the path loss in the optical domain by applying the particle-wave duality to the existing path loss model. Considering the characteristic of the UV channel, we design a polar code with specific channel correlations, and study the computational complexity in terms of the code length. A new theoretical Bhattacharyya upper-bound for the general polar codes is introduced and applied to the UV channel in order to derive a minimum code length without impairing a required bit error rate performance. Numerical simulations and off-line experimental investigations validate the proposed polar coding scheme, which can effectively combat path loss induced performance deterioration with a relatively low computational complexity.