Miracle-dz/UniFAR-FTUs huggingface dataset:
Precise, Low-Cost, and Large-Scale Indoor Positioning System Based on Audio Dual-Chirp Signals

Existing indoor positioning systems, such as WiFi, Bluetooth and ultra-wideband based solutions, have difficulty achieving a balance among cost, accuracy and coverage simultaneously. In this article, we present a precise, low-cost and large-scale (>1000 m2) indoor positioning system based on audio dual-chirp signals and some inexpensive commercial devices that consists of four basic transmitters and supports unlimited receivers. In this system, the transmitters can be easily deployed on the sidewall or the ceiling indoors, and the receivers can be easily integrated or placed on moving targets, such as trailers, badges and helmets. In addition, this system has a better ability to assist the localization drift caused by Doppler shift by relying only on acoustic signals. To fully evaluate the performance of the proposed system, such as the positioning accuracy, coverage and robustness, experiments were conducted in a field environment, and a comparative experiment based on an ultra-wideband solution was presented. All experimental results show that the proposed prototype positioning system can achieve decimeter-level localization accuracy, a stable 4 Hz update rate and good robustness with less infrastructure, which is sufficient for mobile device positioning and tracking in actual indoor environments.
The Effect of the BCO2 Genotype on the Expression of Genes Related to Carotenoid, Retinol, and α-Tocopherol Metabolism in Rabbits Fed a Diet with Aztec Marigold Flower Extract

This study investigated the effect of the BCO2 genotype and the addition of Aztec marigold flower extract to rabbit diets on the expression of BCO1, BCO2, LRAT, and TTPA genes in the liver. The levels of lutein, zeaxanthin, β-carotene, retinol, and α-tocopherol in the liver and blood serum of rabbits, as well as plasma biochemical parameters and serum antioxidant enzyme activities were also determined. Sixty male Termond White growing rabbits were divided into three groups based on their genotype at codon 248 of the BCO2 gene (ins/ins, ins/del and del/del); each group was divided into two subgroups: one subgroup received a standard diet, and the other subgroup was fed a diet supplemented with 6 g/kg of marigold flower extract. The obtained results indicate that the BCO2 genotype may affect the expression levels of BCO1 and BCO2 genes in rabbits. Moreover, the addition of marigold extract to the diet of BCO2 del/del rabbits may increase the expression level of the BCO2 gene. Finally, an increase in the amount of lutein in the diet of rabbits with the BCO2 del/del genotype contributes to its increased accumulation in the liver and blood of animals without compromising their health status or liver function.
Another Look at the Edited Nearest Neighbor Rule.

Abstract : In this paper we present a slight modification of Wilson's Edited Nearest Neighbor Rule (1) in the one dimensional case for which it is possible to compute tight bounds on the average asymptotic risk. It is pointed out that the argument used by Wilson to establish his bounds is probably incorrect with the bounds being somewhat optimistic. The rule presented here is not in itself of any great significance since it does not generalize to more than one dimension. The contribution lies in the fact that for this type of rule (which is very similar to Wilson's rule) an exact analysis is possible which permits comparison of the relative merits of various editing schemes. Although no proof is offered, the strong similarities involved give reason to believe that the results concerning the relative efficiencies of the various editing schemes will carry over to higher dimensional problems with the usual version of the nearest neighbor rule. (Author)
Locomotor adaptations: paradigms, principles and perspectives

The term ‘locomotor adaptations’ (LMA) indicates the alteration in motor commands that is automatically or volitionally generated in response to a perturbation continuously altering the task demands of locomotion. LMAs have been widely studied, using a variety of experimental paradigms and analysis techniques. The perturbation can be expected or unexpected and constituted by a change in the movement environment, by forces actively pushing the person’s body segments, by a modification in the sensory feedback associated with the task or by explicit task instructions. The study of LMAs has been key in widening our understanding of the principles regulating bipedal locomotion, from the overall strategies driving the short-term adjustments of motor commands, down to the different neural circuits involved in the different aspects of locomotion. In this paper we will provide an in-depth review of the research field of LMAs. We will start with an analysis of the principles driving the evolution of bipedal locomotion in humans. Then we will review the different experimental paradigms that have been used to trigger LMAs. We will analyze the evidence on the neurophysiological correlates of adaptation and the behavioral reasons behind it. We will then discuss the characteristics of LMA such as transfer, generalization, and savings. This will be followed by a critical analysis of how different studies point to different task-goal related drivers of adaptation. Finally, we will conclude with a perspective on the research field of LMAs and on its ramifications in neuroscience and rehabilitation.
Combined Pulsed Electric Field and Microwave-Assisted Extraction as a Green Method for the Recovery of Antioxidant Compounds with Electroactive Potential from Coffee Agro-Waste

Coffee agro-waste is a potential source of polyphenols with antioxidant activity and application in the food and cosmetic trades. The usage of these byproducts persists as a challenge in the industrial landscape due to their high content of purported toxic substances hindering management. This study presents a green extractive process using pulsed electric field (PEF) and microwave assisted extraction (MAE) to recover polyphenols from coffee parchment and two varieties of pulp, posing quick processing times and the use of water as the only solvent. The performance of this process with regard to the bioactivity was assessed through the Folin-Ciocalteu assay, total flavonoid content, DPPH, ABTS and FRAP antioxidant tests. The phenolic composition of the extracts was also determined through HPLC-MS and quantified through HPLC-DAD. When compared to treatment controls, PEF + MAE treated samples presented enhanced yields of total phenolic content and radical scavenging activity in all analyzed residues (Tukey test significance: 95%). The chromatographic studies reveal the presence of caffeic acid on the three analyzed by-products. The HPLC-DAD caffeic acid quantification validated that a combination of MAE + PEF treatment in yellow coffee pulp had the highest caffeic acid concentration of all studied extraction methods.
A hemispheric-scale quasi-decadal oscillation and its signature in northern Japan.

Pronounced quasi-decadal oscillation in surface air temperature over northern Japan is linked to the North Atlantic Oscillation (NAO). A NAO-based regression analysis reveas a hemispheric-scale decadal temperature anomaly pattern that features a seesaw between eastern Canada/Greenland and northern Eurasia at high latitudes, with additional centers of action in the eastern United States and North Africa/Middle East. Advection of climatological mean temperature gradient by anomalous winds seems to be a mechanism for these temperature anomalies. Particularly, positive temperature anomalies over Siberia at NAO's positive phase are associated with anomalous southwesterly winds on the upstream side. The advection by mean westerlies is also important over Eurasia, bringing large decadal variability to northern Japan. This quasi-decadal oscillation can be traced farther eastward to the North Pacific, in the Aleutian low and in sea surface temperature on the subarctic front. A possible inter-oceanic link between the North Atlantic and Pacific is discussed.
Volume holographic pupils in ray, wave, statistical optics, and Wigner space

This thesis explores various aspects of the volume holographic pupils to better understand and implement multi–dimensional imaging. A full description and applications of volume holographic pupils are presented in ray, wave, statistical optics, and Wigner space. Volume holograms have both a shift variant nature and multiplex capability, which can efficiently extract specific information of multi–dimensional objects by engineering imaging kernels with shift variant point spread functions and using post–processing. Based on the k–sphere formulation, an efficient computation method of analyzing volume diffraction is developed. It is integrated with the ray tracing software ZEMAXr whose built–in analysis and optimization features provide a great versatility for analysis, design, and optimization of novel volume holographic imaging systems. For a plane wave reference hologram, the shape of the Bragg diffraction image is analyzed in detail, where the shape is a distorted ellipse. The wave optics formulation of volume diffraction is revisited and further developed into statistical optics. The partially coherent response of a volume holographic imaging system is derived. Based on spatial coherence measurements, new passive binary depth detection is proposed, which is a special case of multi–dimensional imaging. Spatially incoherent two objects at two distinct depths are discriminated: focused objects in the foreground and defocused objects in the background. The passive detection is demonstrated for featureless uniform objects under quasi–monochromatic light by measuring mutual intensity with a volume holographic imager. By exploiting cross spectral density measurement, the passive binary depth detection is also demonstrated under white light illumination. Finally, the Wigner distribution function for volume holographic pupils is introduced. The space–spatial frequency characteristics of volume holograms are analyzed with linear systems approach. Wigner representations of two volume holograms are examined: plane and spherical wave reference holograms. Then, various axial imaging systems, which measure the depth of objects from intensity images, are explored by the Wigner analysis. Two important conditions for axial imaging are established:
Small width, low distortions: quasi-isometric embeddings with quantized sub-Gaussian random projections

Under which conditions a subset $\mathcal K$ of $\mathbb R^N$ can be embedded in another one of $\delta \mathbb Z^M$ for some resolution $\delta>0$? We address this general question through the specific use of a quantized random linear mapping ${\bf A}:\mathbb R^N \to \delta \mathbb Z^M$ combining a linear projection of $\mathbb R^N$ in $\mathbb R^M$ associated to a random matrix $\boldsymbol \Phi \in \mathbb R^{M\times N}$ with a uniform scalar (dithered) quantization $\mathcal Q$ of $\mathbb R^M$ in $\delta\mathbb Z^M$. The targeted embedding relates the $\ell_2$-distance of any pair of vectors in $\mathcal K$ with the $\ell_1$-distance of their respective mappings in $\delta \mathbb Z^M$, allowing for both multiplicative and additive distortions between these two quantities, i.e., describing a $\ell_2/\ell_1$-quasi-isometric embedding. We show that the sought conditions depend on the Gaussian mean width $w(\mathcal K)$ of the subset $\mathcal K$. In particular, given a symmetric sub-Gaussian distribution $\varphi$ and a precision $\epsilon > 0$, if $M \geq C \epsilon^{-5} w(\mathcal K)^2$ and if the sensing matrix $\boldsymbol \Phi$ has entries i.i. d. as $\varphi$, then, with high probability, the mapping $\bf A$ provides a $\ell_2/\ell_1$-quasi-isometry between $\mathcal K$ and its image in $\delta \mathbb Z^M$. Moreover, in this embedding, the additive distortion is of order $\delta\epsilon$ while the multiplicative one grows with $\epsilon$. For non-Gaussian random $\boldsymbol \Phi$, the multiplicative error is also impacted by the sparsity of the vectors difference, i.e., being smaller for "not too sparse" difference. When $\mathcal K$ is the set of bounded $K$-sparse vectors in any orthonormal basis, then only $M \geq C \epsilon^{-2} \log(c N/K\epsilon^{3/2})$ measurements suffice. Remark: all values $C,c>0$ above only depend on $\delta$ and on the distribution $\varphi$.
Progress, challenges, and future steps in data assimilation for convection‐permitting numerical weather prediction: Report on the virtual meeting held on 10 and 12 November 2021

In November 2021, the Royal Meteorological Society Data Assimilation (DA) Special Interest Group and the University of Reading hosted a virtual meeting on the topic of DA for convection‐permitting numerical weather prediction. The goal of the meeting was to discuss recent developments and review the challenges including methodological developments and progress in making the best use of observations. The meeting took place over two half days on the 10 and 12 November, and consisted of six talks and a panel discussion. The scientific presentations highlighted some recent work from Europe and the USA on convection‐permitting DA including novel developments in the assimilation of observations such as cloud‐affected satellite radiances in visible channels, ground‐based profiling networks, aircraft data, and radar reflectivity data, as well as methodological advancements in background and observation error covariance modelling and progress in operational systems. The panel discussion focused on key future challenges including the handling of multiscales (synoptic‐, meso‐, and convective‐scales), ensemble design, the specification of background and observation error covariances, and better use of observations. These will be critical issues to address in order to improve short‐range forecasts and nowcasts of hazardous weather.
Development of a Laser-Produced Plasma X-Ray Source for Phase-Contrast Radiography of D-T Ice Layers

Abstract Refraction-enhanced X-ray phase-contrast imaging is crucial for characterization of deuterium-tritium (D-T) ice layer roughness in optically opaque inertial confinement fusion capsules. Observation of the time development of D-T ice roughness over approximately second timescales requires a bright X-ray source that can produce an image faster than the evolution of the ice surface roughness. A laser-produced plasma X-ray source is one of the candidates that can meet this requirement. Experiments were performed at the Janus laser facility at Lawrence Livermore National Laboratory to assess the characteristics of a laser-produced plasma X-ray source as a potential backlight for in situ target characterization.
Drug Delivery System Based on Carboxymethyl Cellulose Containing Metal-Organic Framework and Its Evaluation for Antibacterial Activity

A novel drug delivery system based on carboxymethyl cellulose containing copper oxide at melamine and zinc oxide at melamine framework (CMC-Cu-MEL and CMC-Zn-MEL) was prepared by the hydrothermal route. Synthesized nanocomposites were characterized by FTIR, SEM, and Raman spectroscopy. In addition, transmission electron microscopy (TEM) and selected area electron diffraction (SAED) images were applied to confirm the particle size and diffraction pattern of the prepared nanocomposites. Furthermore, the crystallinity of the synthesized CMC, CMC-Cu-MEL, and CMC-Zn-MEL materials was studied via X-ray diffraction (XRD). Estimating the transport exponent, which discloses the solvent diffusion and chain relaxation processes, and the Ritger–Peppas kinetic model theory were used to control the TC release mechanism from CMC-Cu-MEL and CMC-Zn-MEL. Additionally, the CMC-Cu-MEL and CMC-Zn-MEL containing TC had the highest activity index percents of 99 and 106% against S. aureus and 93 and 99% against E. coli, respectively. The tailored CMC-Cu-MEL and CMC-Zn-MEL for drug delivery systems are expected to be feasible and efficient.
Investigating Methods for Cognitive Workload Estimation for Assistive Robots

Robots interacting with humans in assistive contexts have to be sensitive to human cognitive states to be able to provide help when it is needed and not overburden the human when the human is busy. Yet, it is currently still unclear which sensing modality might allow robots to derive the best evidence of human workload. In this work, we analyzed and modeled data from a multi-modal simulated driving study specifically designed to evaluate different levels of cognitive workload induced by various secondary tasks such as dialogue interactions and braking events in addition to the primary driving task. Specifically, we performed statistical analyses of various physiological signals including eye gaze, electroencephalography, and arterial blood pressure from the healthy volunteers and utilized several machine learning methodologies including k-nearest neighbor, naive Bayes, random forest, support-vector machines, and neural network-based models to infer human cognitive workload levels. Our analyses provide evidence for eye gaze being the best physiological indicator of human cognitive workload, even when multiple signals are combined. Specifically, the highest accuracy (in %) of binary workload classification based on eye gaze signals is 80.45 ∓ 3.15 achieved by using support-vector machines, while the highest accuracy combining eye gaze and electroencephalography is only 77.08 ∓ 3.22 achieved by a neural network-based model. Our findings are important for future efforts of real-time workload estimation in the multimodal human-robot interactive systems given that eye gaze is easy to collect and process and less susceptible to noise artifacts compared to other physiological signal modalities.
Introducing ARTMO’s Machine-Learning Classification Algorithms Toolbox: Application to Plant-Type Detection in a Semi-Steppe Iranian Landscape

Accurate plant-type (PT) detection forms an important basis for sustainable land management maintaining biodiversity and ecosystem services. In this sense, Sentinel-2 satellite images of the Copernicus program offer spatial, spectral, temporal, and radiometric characteristics with great potential for mapping and monitoring PTs. In addition, the selection of a best-performing algorithm needs to be considered for obtaining PT classification as accurate as possible. To date, no freely downloadable toolbox exists that brings the diversity of the latest supervised machine-learning classification algorithms (MLCAs) together into a single intuitive user-friendly graphical user interface (GUI). To fill this gap and to facilitate and automate the usage of MLCAs, here we present a novel GUI software package that allows systematically training, validating, and applying pixel-based MLCA models to remote sensing imagery. The so-called MLCA toolbox has been integrated within ARTMO’s software framework developed in Matlab which implements most of the state-of-the-art methods in the machine learning community. To demonstrate its utility, we chose a heterogeneous case study scene, a landscape in Southwest Iran to map PTs. In this area, four main PTs were identified, consisting of shrub land, grass land, semi-shrub land, and shrub land–grass land vegetation. Having developed 21 MLCAs using the same training and validation, datasets led to varying accuracy results. Gaussian process classifier (GPC) was validated as the top-performing classifier, with an overall accuracy (OA) of 90%. GPC follows a Laplace approximation to the Gaussian likelihood under the supervised classification framework, emerging as a very competitive alternative to common MLCAs. Random forests resulted in the second-best performance with an OA of 86%. Two other types of ensemble-learning algorithms, i.e., tree-ensemble learning (bagging) and decision tree (with error-correcting output codes), yielded an OA of 83% and 82%, respectively. Following, thirteen classifiers reported OA between 70% and 80%, and the remaining four classifiers reported an OA below 70%. We conclude that GPC substantially outperformed all classifiers, and thus, provides enormous potential for the classification of a diversity of land-cover types. In addition, its probabilistic formulation provides valuable band ranking information, as well as associated predictive variance at a pixel level. Nevertheless, as these are supervised (data-driven) classifiers, performances depend on the entered training data, meaning that an assessment of all MLCAs is crucial for any application. Our analysis demonstrated the efficacy of ARTMO’s MLCA toolbox for an automated evaluation of the classifiers and subsequent thematic mapping.
Variation in Body Length, Length-Weight Relationship, and Condition Factor of Lionfish (Pterois volitans) Between Years in a Mesophotic Coral Ecosystem in Alacranes Reef, Southern Gulf of Mexico

Abstract More than 30 years ago the Indo-Pacific lionfish (Pterois volitans, P. miles) were introduced into the western Atlantic Ocean, where P. volitans has reached the level of biological invasion threatening the marine ecosystem. The aim of this study was to describe the variation in body length, length-weight relationship (LWR), and condition factor of P. volitans between years in a mesophotic coral ecosystem (MCE) in the southern Gulf of Mexico, to provide baseline life history data. From September 2014 to September 2017, we speared 92 lionfish at the same MCE in the Alacranes Reef, off the northern coast of the Yucatan Peninsula, Mexico. There were differences in length between years, with larger lionfish found in 2014, and also differences between the LWRs. The LWR for all lionfish indicate a positive allometric growth. No significant difference was found in length between females and males. Males showed a greater Fulton's condition factor in 2015 and 2016, in comparison to females. This study revealed P. volitans has attained a large length and good condition factor in the MCE. Human limitations for diving deep areas preclude mechanical removal of lionfish by culling. Further scientific research is necessary to quantify its density and understand the potential lionfish would have to impact the MCEs in the region. Resumen Desde hace más de 30 años el pez león del Indo-Pacífio (Pterois volitans, P. miles) fue introducido en el Atlántico Oeste, donde P. volitans ya ha alcanzado el nivel de invasión biológica que amenaza al ecosistema marino. El objetivo de este trabajo fue describir las variaciones en longitud corporal, relaciones peso-longitud (RPL) y factor de condición de P. volitans entre años en un ecosistema coralino mesofótico (ECM), en el sureste del Golfo de México, para proporcionar una línea base de datos de historia de vida. De septiembre 2014 a septiembre 2017, arponeamos 94 peces león en el mismo ECM en el Arrecife Alacranes, frente a la costa norte de la península de Yucatán, México. Hubo diferencias en longitud, con peces león más grandes en 2014 y también diferencias enre las relaciones RPLs. La RPL para todos los peces león indicó un crecimiento alométrico positivo. No hubo diferencias en la longitud entre las hembras y los machos. Los machos mostraron un factor de condición de Fulton mayor, en 2015 y 2016, en comparación con las hembras. Este estudio reveló que P. volitans ha adquirido una longitud mayor y un buen factor de condición en el ECM. Las limitaciones humanas para buceo en áreas profundas impiden la remoción mecánica de pez león por sacrificio. Se requiere de análisis más amplios para cuantificar su densidad y entender el potencial que el pez león tendría para impactar los ECMs en la región.