Miracle-dz/UniFAR-FTUs huggingface dataset:
A multi-beam holographic light concentrator for solar applications

High efficiency solar cells are emerging as a viable tool for tapping solar energy. Such cells need cool light to be concentrated on them for high conversion efficiency. Conventional refractive and reflective light concentrators, with sun tracking systems, are bulky and heat the solar cell due to single focus convergence of heat and light radiation. HOEs are emerging as an active candidate for making new generation light concentrators. In this paper we report the design, development and characterization of a multi beam reflection HOE for light concentration. The proposed design of single focus, multiple exposed reflection element with wavelength selectivity can be used to avoid sun following system.
Aperiodic birefringent photonic structures based on Kolakoski sequence

A novel type of aperiodic porous silicon-based multilayered structures which can be used for the electromagnetic radiation manipulation in the visible and infrared parts of spectrum are proposed in this paper. The one-dimensional aperiodic structures under consideration are arranged by stacking together two anisotropic layers according to the Kolakoski self-generation scheme. The spectral properties of the structures are theoretically investigated by using the electromagnetic field scalarization method in coupling with the finite-difference method. It is shown that the Kolakoski multilayers have both completely transparent states in the transmission spectra and pronounced omnidirectional reflectance which can used in integrated optics, optical fiber telecommunications, vertical cavity surface emitting lasers, laser cavities, etc. Also, it is shown numerically that the anisotropic nature of layered media significantly affects on optical properties of the structures.
Transcriptional profiling of Pseudomonas aeruginosa mature single- and dual-species biofilms in response to meropenem

Pseudomonas aeruginosa is a Gram-negative opportunistic pathogen frequently isolated from chronic infections of the cystic fibrosis lung and burn wounds, and is a major cause of antimicrobial-resistant nosocomial infections. P. aeruginosa is frequently co-isolated with the opportunistic fungal pathogen Candida albicans, with the presence of C. albicans in dual-species biofilms promoting tolerance to meropenem. Here, transcription profiling of mature P. aeruginosa single- or dual-species biofilms was carried out to understand the molecular mechanism(s) by which C. albicans enhances meropenem tolerance. C. albicans appeared to have a mild impact on the transcriptome of P. aeruginosa mature biofilms, with most differentially regulated genes being involved in interkingdom interactions (i.e. quorum sensing and phenazine biosynthesis). The addition of meropenem to mature single- or dual-species biofilms resulted in a significant bacterial transcriptional response, including the induction of the beta-lactamase, ampC, genes involved in biofilm formation. P. aeruginosa elicited a similar transcriptional response to meropenem in the presence of C. albicans, but C. albicans promoted the expression of additional efflux pumps, which could play roles in increasing the tolerance of P. aeruginosa to meropenem.
Identifying Deviating Systems with Unsupervised Learning

We present a technique to identify deviating systems among a group of systems in aself-organized way. A compressed representation of each system is used to compute similarity measures, which are combined in an affinity matrix of all systems. Deviation detection and clustering is then used to identify deviating systems based on this affinity matrix.The compressed representation is computed with Principal Component Analysis andKernel Principal Component Analysis. The similarity measure between two compressedrepresentations is based on the angle between the spaces spanned by the principalcomponents, but other methods of calculating a similarity measure are suggested aswell. The subsequent deviation detection is carried out by computing the probability ofeach system to be observed given all the other systems. Clustering of the systems isdone with hierarchical clustering and spectral clustering. The whole technique is demonstrated on four data sets of mechanical systems, two of a simulated cooling system and two of human gait. The results show its applicability on these mechanical systems.
Silent Brain Changes in Children with Sickle Cell Disease

Background: Cerebrovascular steno-occlusive disease constitutes one of the most dangerous complications of sickle cell disease (SCD). It could result in overt or silent cerebral infarctions (SCI). Objective: The aim of this study was to demonstrate silent parenchymal and vascular brain changes that are incidentally observed in neurologically free SCD children using screening MRI and MRA. Patients and methods: This prospective cross-sectional study was conducted on 78 children diagnosed with SCD who were neurologically free. Magnetic resonance imaging (MRI) and Magnetic Resonance Angiography (MRA) were done to all the participant children. Results: Thirty (38.4%) of our children demonstrated pathologic parenchymal features on their MRI. There were 29 (37.17%) patients had pathologic changes in MRA; 6 of them had isolated vascular abnormality, whereas the remaining patients had concurrent parenchymal abnormalities. There was significant high positive correlation between low hemoglobin and presence of silent cerebral infarction (SCI). Moya-moya vasculopathy showed significant positive correlation with arterial occlusion and old SCI. HB SS phenotype was significantly correlated with moya-moya vasculopathy, arterial occlusion and old SCI. Conclusions: Silent cerebral and cerebrovascular changes in SCD children are frequent abnormalities requiring utilization of MRI and MRA to find out their exact prevalence and their risk factors.
Improved Ridge Regression Estimators for Binary Choice Models: An Empirical Study

This paper suggests some new estimators of the ridge parameter for binary choice models that may be applied in the presence of a multicollinearity problem. These new ridge parameters are functions of other estimators of the ridge parameter that have shown to work well in the previous research. Using a simulation study we investigate the mean square error (MSE) properties of these new ridge parameters and compare them with the best performing estimators from the previous research. The results indicate that we may improve the MSE properties of the ridge regression estimator by applying the proposed estimators in this paper, especially when there is a high multicollinearity between the explanatory variables and when many explanatory variables are included in the regression model. The benefit of this paper is then shown by a health related data where the effect of some risk factors on the probability of receiving diabetes is investigated.
Effects of context on perceptions of the language of suicide

ABSTRACT Objective. There is concern regarding use of the phrase ‘committed suicide’, given its connotations of immorality. Limited research has examined influences on people’s use of this phrase. The current studies examined whether portraying a suicide as highly immoral affects perceptions of the phrase ‘committed suicide’. Method. Undergraduate participants in western Canada read a suicide vignette in which the suicide was depicted either neutrally or as sinful (Study 1, N = 188) or as either altruistic or vengeful (Study 2, N = 204). They then judged, from the perspective of the deceased person’s family, the preference for statements employing ‘committed suicide’ or ‘died by suicide’ (Study 1) or the acceptability of statements employing ‘committed suicide’, ‘ended her[his] life’, ‘took her[his] own life’, or ‘died by suicide’ (Study 2). Results. In Study 1, ‘committed suicide’ statements received higher preference judgments for the scenario depicted as sinful. In Study 2, phrases alternative to ‘committed suicide’ received higher acceptability ratings for the altruistic scenario. Discussion. We consider limitations of our work, directions for future research on the language of suicide, and implications of our findings.
On Howard's upper bound for heat transport by turbulent convection

The variational problem introduced by Howard (1963) for the derivation of an upper bound on heat transport by convection in a layer heated from below is analyzed for the case in which the equation of continuity is added as constraint for the velocity field. Howard's conjecture that the maximizing solution of the Euler equations is characterized by a single horizontal wave-number is shown to be true only for a limited range of the Rayleigh number, Ra. A new class of solutions with a multiple boundary-layer structure is derived. The upper bound for the Nusselt number, Nu, given by these solutions is Nu ≤ (Ra/1035)½ in the limit when the Rayleigh number tends to infinity. The comparison of the maximizing solution with experimental observations by Malkus (1954a) and Deardorff & Willis (1967) emphasizes the similarity pointed out by Howard.
Analysis of autocorrelation-based parameters in Creaky voice

“Creaky voice” has many other terminologies, such as “creak”, “vocal fry”, “glottal fry”, “laryngealization”, “glottalization”, and “pulse register phonation”, used in several research areas (like Linguistics, Physiology, and Phonetics) [1,2]. Creaky voice is defined as “. a train of discrete laryngeal excitations, or “pulses”, of extremely low frequency (7 to about 78 Hz), with almost complete damping of the vocal tract between excitations. ” (Hollien 66 cited in [1]). “The auditory effect is of a rapid series of taps, like a stick being run along a railing. ” (Catford 64 cited in [2]). Creaky phonation carries many linguistic and paralinguistic information, depending on the language. For example, contrast between creaky and modal voicing among vowels and nasals is particularly common in some American Indian languages [3]. In [4,5], relationship between different phonation types and paralinguistic information like emotions and attitudes are reported for English. Strong correlations were reported between creaky voice and perception of relaxed/stressed, sad/happy, and bored/interested. In Japanese, expressive pressed voice that is frequently realized by creaky phonation also carries important paralinguistic information such as attitudes, emotional states and emphasis [6]. Further, in creaky segments, periodicity is disturbed and the pitch extraction becomes difficult, affecting the subsequent prosodic analysis, like intonation. Tendency of creaky segments for specific tone types is reported in [7] for phrase finals in Japanese. In the JST/CREST ESP Project [8], one of the goals is an expressive speech synthesizer based on unit selection, using a large database of spontaneous speech. For this purpose, labels of voice qualities (phonation types) become as important as prosodic labels. With the goal of doing automatic labeling of voice quality on a large speech database, in the present research, we focus on the automatic detection of creaky phonation.
47.4: Invited Paper: Wobulation: Doubling the Addressed Resolution of Projection Displays

In this paper “wobulation” is presented. Wobulation is a cost‐effective method of increasing the resolution of digital projection systems without changing the spatial light modulator (SLM). Multiple sub‐frames of data are generated from each frame of image data. An optical image shifting mechanism displaces the projected image of each sub‐frame by a fraction of a pixel. The sub‐frames are projected in rapid succession, thereby appearing as if they were projected simultaneously and superimposed. The resulting image has significantly higher resolution than images produced by unwobulated systems having the same number of SLM pixels.
Population Characteristics, Development Processes and Structure of Radar Echoes in South Florida

Abstract Radar data from the Florida Area Cumulus Experiment were used to study the ensemble characteristics of echo populations and also the structure of echo systems and their phenomenological growth and development process. The diurnal development of the convective field was explored as well. The overall distribution of echoes turned out to be of the truncated lognormal type, which is indicative of growth process that favor the larger, more vigorous clouds. Three principal scales of convective activity were apparent: single cell echoes conglomerates of several individual cells, and large areas of convection that normally form by the joining of existing cloud conglomerates by growth of new cells in the intervening space. The distributions of the radar characteristics of the individual cells were found to be very skewed, which indicates that the large majority of the cells are small and weak, and that only sporadically do a few large and strong cells appear. A considerable number. of the cells originated.
Predicting Hourly Boarding Demand of Bus Passengers Using Imbalanced Records From Smart-Cards: A Deep Learning Approach

The tap-on smart-card data provides a valuable source to learn passengers’ boarding behaviour and predict future travel demand. However, when examining the smart-card records (or instances) by the time of day and by boarding stops, the positive instances (i.e. boarding at a specific bus stop at a specific time) are rare compared to negative instances (not boarding at that bus stop at that time). Imbalanced data has been demonstrated to significantly reduce the accuracy of machine-learning models deployed for predicting hourly boarding numbers from a particular location. This paper addresses this data imbalance issue in the smart-card data before applying it to predict bus boarding demand. We propose the deep generative adversarial nets (Deep-GAN) to generate dummy travelling instances to add to a synthetic training dataset with more balanced travelling and non-travelling instances. The synthetic dataset is then used to train a deep neural network (DNN) for predicting the travelling and non-travelling instances from a particular stop in a given time window. The results show that addressing the data imbalance issue can significantly improve the predictive model’s performance and better fit ridership’s actual profile. Comparing the performance of the Deep-GAN with other traditional resampling methods shows that the proposed method can produce a synthetic training dataset with a higher similarity and diversity and, thus, a stronger prediction power. The paper highlights the significance and provides practical guidance in improving the data quality and model performance on travel behaviour prediction and individual travel behaviour analysis.
Eulerian backtracking of atmospheric tracers. II: Numerical aspects

In Part I of this paper, a mathematical equivalence was established between Eulerian backtracking or retro‐ transport, on the one hand, and adjoint transport with respect to an air‐mass‐weighted scalar product, on the other. The time symmetry which lies at the basis of this mathematical equivalence can however be lost through discretization. That question is studied, and conditions are explicitly identified under which discretization schemes possess the property of time symmetry. Particular consideration is given to the case of the LMDZ model. The linear schemes used for turbulent diffusion and subgrid‐scale convection are symmetric. For the Van Leer advection scheme used in LMDZ, which is nonlinear, the question of time symmetry does not even make sense. Those facts are illustrated by numerical simulations performed in the conditions of the European Transport EXperiment (ETEX). For a model that is not time‐symmetric, the question arises as to whether it is preferable, in practical applications, to use the exact numerical adjoint, or the retro‐transport model. Numerical results obtained in the context of one‐dimensional advection show that the presence of slope limiters in the Van Leer advection scheme can produce in some circumstances unrealistic (in particular, negative) adjoint sensitivities. The retro‐transport equation, on the other hand, generally produces robust and realistic results, and always preserves the positivity of sensitivities. Retro‐transport may therefore be preferable in sensitivity computations, even in the context of variational assimilation. Copyright © 2006 Royal Meteorological Society
Hyperthermic Extracorporeal Applied Tumor Therapy for Six Cycles for Recurrent Metastatic Peritoneal Serous Papillary Carcinoma

An elderly female with failed third-line peritoneal serous papillary carcinoma with metastasis (ovarian cancer) was treated by our proprietary method of whole-body hyperthermia-a recirculating extracorporeal circuit at 42°C for 120 minutes. She received six cycles, 28 days apart. Five index lesions were measured prior to and after each treatment. Results showed stable disease with reduced standard uptake volume. She then restarted six cycles of a previously failed chemotherapy, resulting in no evidence of disease for nine months; she survived for 27 months. Using our technology, the patient experienced an improvement in the quality of life and an increase in survival.
A class-based scheduling algorithm with high throughput for optical burst switching networks

Optical burst switching (OBS) is more efficient and feasible solution to build terabit IP-over-WDM optical network by employing relatively matured photonic and opto-electronic devices and combining the advantage of high bandwidth of optical transmission/switching and high flexibility of electronic control/processing. Channel scheduling algorithm is one of the key issues related to OBS networks. In this paper, a class-based scheduling algorithm is presented with emphasis on fairly utilizing the bandwidth among different services. A maximum reserved channel numbers and a maximum channel search times is introduced for each service based on its class of services, load and available bandwidth resource in the class-based scheduling algorithm. The performance of the scheduling algorithm is studied in detail by simulation. The results show that the scheduling algorithm can allocate the bandwidth more fairly among different services and the total burst loss ratio under high throughput can be lowered with acceptable expense on delay performance of services with lower delay requirement. Problems related with burst loss ratio and the delay requirement of different services can be well solved simultaneously.
The Double Active Galactic Nucleus in NGC 6240 Revealed through 3-5 μm Spectroscopy

We present 3-5 μm spectroscopy of the interacting system NGC 6240, revealing the presence of two active galactic nuclei (AGNs). The brightest (southern) nucleus shows up with a starburst-like emission, with a prominent 3.3 μm emission feature. However, the presence of an AGN is revealed by the detection of a broad Brα emission line, with a width of ~1800 km s-1. The spectrum of the faintest (northern) nucleus shows typical AGN features, such as a steep continuum and broad absorption features in the M band. We discuss the physical properties of the dusty absorbers/emitters, and we show that in both nuclei, the AGN is dominant in the 3-5 μm band but that its contribution to the total luminosity is small (a few percent of the starburst emission).
Youth-focused Design and Regulation in eHealth Can Help Address the Mental Healthcare Crisis

An ongoing mental healthcare crisis has been exacerbated by COVID-19, particularly for youth. However, one unexpected effect of this pandemic is that access to digital mental healthcare has rapidly expanded. We argue that eHealth interventions, including telehealth and mobile interventions (mHealth), can effectively address mental health challenges, reduce costs for individuals and institutions, and broadly expand access to mental healthcare. For the promise of eHealth to be fully realized, FDA regulation must thoughtfully balance the promotion of evidence-based interventions with broad public accessibility. Furthermore, youth involvement throughout the design process and consideration of youth-specific needs when establishing regulations are critical to the success of eHealth in addressing youth mental health in the United States.
Data preparation for neural network of predicting malfunctions in a mobile network

Mobile data network operators are facing increasing operational complexity and rising maintenance costs when quantity of equipment is increasing. When the number of base stations increases, the number of malfunctions increases simultaneously. The ability to predict network outages in advance would be a great solution for mobile operators. Modern technological solutions based on neural network algorithms are able to predict in advance, with a certain probability, the appearance of equipment malfunctions. Data of operation and malfunctions on equipment of mobile network is required for training a neural network. In this article the issue of preliminary preparation of the collected data on the operation of 4G+ mobile operator’s network for further use in the development of a neural model for predicting malfunctions discussesed. The results of the analysis of the collected data are presented. Characteristics, composition, structure of the data, and features that can further affect training of the neural network are shown.
Nash Strategies for Large-Scale Stochastic Delay Systems

Abstract This paper discusses Nash games for a class of large-scale delay systems governed by Ito's stochastic differential equation. The sufficient conditions for the existence of Nash strategies are given by means of cross-coupled matrix inequalities. In order to obtain the strategy set, new cross-coupled algebraic equations (CSAEs) are established using Karush-Kuhn-Tucker (KKT) conditions, which constitute the necessary conditions for the existence of Nash strategies. It is noteworthy that the asymptotic structure of cross-coupled matrix inequalities is studied for the first time by using the CSAEs. It is shown that the approximate local state feedback Nash strategies can be obtained by solving the parameter-independent linear matrix inequality (LMI) recursively. Finally, a numerical example shows that the proposed methods can help in attaining an adequate cost bound.
Anti-Disturbance Control for Tethered Aircraft System With Deferred Output Constraints

In this paper, we investigate the peaking issue of extended state observers and the anti-disturbance control problem of tethered aircraft systems subject to the unstable flight of the main aircraft, airflow disturbances and deferred output constraints. Independent of exact initial values, a modified extended state observer is constructed from a shifting function such that not only the peaking issue inherently in the observer is circumvented completely but also the accurate estimation of the lumped disturbance is guaranteed. Meanwhile, to deal with deferred output constraints, an improved output constrained controller is employed by integrating the shifting function into the barrier Lyapunov function. Then, by combining the modified observer and the improved controller, an anti-disturbance control scheme is presented, which ensures that the outputs with any bounded initial conditions satisfy the constraints after a pre-specified finite time, and the tethered aircraft tracks the desired trajectory accurately. Finally, both a theoretical proof and simulation results verify the effectiveness of the proposed control scheme.