Miracle-dz/UniFAR-FTUs huggingface dataset:
Possibilistic clustering criterion for the segmentation of magnetic resonance images

Combining the possibilistic methodology with topological concepts, we present a new clustering criterion for segmenting magnetic resonance images. The clustering criterion generates a covering of the image, thereby permitting the perception of intersections of different brain tissues, which gives the specialist another way of representing data in order to refine his/her perception in said structures. Furthermore, an analysis is carried out regarding the validation of the clusters generated by the algorithm, such as the grade of compactification of the objects in each class, as well as the separability of classes.
A 47 TOPS/W 10T SRAM-Based Multi-Bit Signed CIM With Self-Adaptive Bias Voltage Generator for Edge Computing Applications

This brief presents a 10T static random-access memory (SRAM) – computing in memory (CIM) structure of 32kb macro unit for convolutional neural networks (CNNs). The proposed CIM handles ± computation with signed input signals in a single bitcell and obtains 3 times $\Delta $ BL range for a larger sensing margin. Although the area overhead of the SRAM bitcell is 27% larger due to the positive branch PMOS, the array size is reduced to half for the same computation. A serial multi-bit weight technique is used to extend the number of weight bits with improved linearity and no significant time penalty. A bias voltage generator is implemented to regulate the discharge current under different PT variations. Both weight and input can be adjusted to 1, 2, and 4-b. For 4-b weight and 4-b input, the proposed structure achieves 85.7% accuracy with the CIFAR-10 dataset and 47 TOPS/W energy consumption in CMOS 28nm technology.
Sampling Boltzmann-Gibbs distributions restricted on a manifold with diusions: Application to free energy calculations

We consider the problem of sampling a Boltzmann-Gibbs probability distribution when this distribution is restricted (in some suitable sense) on a manifold Σ of R implicitly defined by N constraints q1(x) = · · · = qN (x) = 0. This problem arises for example in systems subject to hard constraints or in the context of free energy calculations. We prove that the constrained stochastic differential equations (i.e. diffusions) proposed in [W. E and E. Vanden-Eijnden, in: Multiscale Modelling and Simulation, eds. S. Attinger and P. Koumoutsakos (LNCSE 39, Springer, 2004)] and [G. Ciccotti, R. Kapral, and E. Vanden-Eijnden, ChemPhysChem 6, 1809 (2005)] are ergodic with respect to this restricted distribution. We also construct numerical schemes for the integration of the constrained diffusions. Finally, we show how these schemes can be used to compute the gradient of the free energy associated with the constraints. SAMPLING ON MANIFOLDS WITH DIFFUSIONS 2
Identification of New FG-Repeat Nucleoporins with Amyloid Properties

Amyloids are fibrillar protein aggregates with a cross-β structure. More than two hundred different proteins with amyloid or amyloid-like properties are already known. Functional amyloids with conservative amyloidogenic regions were found in different organisms. Protein aggregation appears to be beneficial for the organism in these cases. Therefore, this property might be conservative for orthologous proteins. The amyloid aggregates of the CPEB protein were suggested to play an important role in the long-term memory formation in Aplysia californica, Drosophila melanogaster, and Mus musculus. Moreover, the FXR1 protein demonstrates amyloid properties among the Vertebrates. A few nucleoporins (e.g., yeast Nup49, Nup100, Nup116, and human Nup153 and Nup58), are supposed or proved to form amyloid fibrils. In this study, we performed wide-scale bioinformatic analysis of nucleoporins with FG-repeats (phenylalanine–glycine repeats). We demonstrated that most of the barrier nucleoporins possess potential amyloidogenic properties. Furthermore, the aggregation-prone properties of several Nsp1 and Nup100 orthologs in bacteria and yeast cells were analyzed. Only two new nucleoporins, Drosophila melanogaster Nup98 and Schizosaccharomyces pombe Nup98, aggregated in different experiments. At the same time, Taeniopygia guttata Nup58 only formed amyloids in bacterial cells. These results rather contradict the hypothesis about the functional aggregation of nucleoporins.
Curvilinear smoothed particle hydrodynamics

We suggest a new set of equations to employ smoothed particle hydrodynamics (SPH) in a curvilinear space, and we refer to it as curvSPH. In classical SPH, the horizontal and vertical resolution of discretization is supposed to be equal for fluid particles. However, curvSPH makes the horizontal and vertical resolutions independent from each other. This is performed by transformation of physical space into an appropriate computational space with a different scale in horizontal and vertical directions. Solving a problem using SPH in a curvilinear space also provides capability to model curved boundaries as straight lines. In classical SPH, special care is needed to reach a uniform mass distribution along curved boundaries; however, producing uniform mass distribution along a line using curvSPH is straight forward. Different simulations, including simulation of a flip bucket are performed to demonstrate the applicability of the proposed method. Good agreement of results with experimental data and classical SPH confirms the capabilities of curvSPH. Copyright © 2016 John Wiley & Sons, Ltd.
Voiculescu amenable Hopf von Neumann algebras with applications

For a Hopf von Neumann algebra (ℳ, Γ), we give a fixed point characterization of Voiculescu amenability of (ℳ, Γ) in terms of modules over ℳ∗. As a consequence, we present some descriptions for amenability of locally compact groups in terms of certain associated Hopf von Neumann algebras. We finally apply this result to some modules of continuous functions on a multiplicative subsemigroup of ℳ∗.
Machine learning-based segmentation of aerial LiDAR point cloud data on building roof

ABSTRACT Three-dimensional (3D) reconstruction of a building can be facilitated by correctly segmenting different feature points (e.g. in the form of boundary, fold edge, and planar points) over the building roof, and then, establishing relationships among the constructed feature lines and planar patches using the segmented points. Present machine learning-based segmentation approaches of Light Detection and Ranging (LiDAR) point cloud data are confined only to different object classes or semantic labelling. In the context of fine-grained feature point classification over the extracted building roof, machine learning approaches have not yet been explored. In this paper, after generating the ground truth data for the extracted building roofs from three different datasets, we apply machine learning methods to segment the roof point cloud based on seven different effective geometric features. The goal is not to semantically enhance the point cloud, but rather to facilitate the application of 3D building reconstruction algorithms, making them easier to use. The calculated F1-scores for each class confirm the competitive performances over the state-of-the-art techniques, which are more than 95% almost in each area of the used datasets.
Biomass Fuel Production through Fermentation of Lysinibacillus sp. LC 556247 in Various Ratios of Palm Oil Mill Effluent and Empty Fruit Bunch

Biomass wastes originating from palm oil milling activities can be characterized by their high biochemical oxygen demand (BOD), chemical oxygen demand (COD), total suspended solid (TSS), and oil and grease content. The utilization of oil palm wastes such as palm oil mill effluent (POME) and empty fruit bunch (EFB) has great potential for a sustainable energy biomass pellet as it reduces the reliance on conventional materials for energy production. A mixture of POME and EFB in various ratios ranging between 7:3, 8:2, 9:1, and 10:0 was fermented in the presence of Lysinibacillus sp. LC 556247 for 120 h at 37 ± 2 °C and 180 rpm with the aim of elucidating the biodegradation of complex organic material in terms of BOD, COD, TSS, total organic carbon, inorganic carbon, and total carbon content. After fermentation, the mixtures were oven dried at 105 °C overnight and then subjected to calorific energy value (CEV) determination. The highest CEV of 20.26 MJ/kg was achieved for a ratio of 10:0 (slightly higher than the control experiment with the value of 18.67 MJ/kg), with maximum removal efficiencies of COD (12.19%), BOD (11.72%), TSS (93.94%), and oil reduction of 17.43%. The addition of EFB did not positively increase the CEV.
Current Measurement Gain Compensation Using High-Frequency Signal Injection in Dual Three-Phase PMSM Systems

To online compensate the scaling errors in current measurement caused by incorrect calibration, temperature, aging, and noise, in this article, we propose a new solution based on high-frequency (HF) carrier voltage injection in dual three-phase permanent magnet synchronous machines. The relationship between the measured HF currents and scaling errors is derived. It shows that the amplitudes of the HF currents are proportional to the scaling errors, based on which three HF current control loops are subsequently designed to eliminate the measured HF currents and compensate the scaling errors. The designed HF controller is independent from the main current and torque regulators, and thus, it can be used for initial scaling gain calibration or periodically used during normal machine operation. Different from general three-phase machine systems, the generated HF current components only exist in z1z2 subspace, and thus, no extra torque ripples will be produced. The experimental results validate the proposed control algorithm.
Proteomics Methodologies: The Search of Protein Biomarkers Using Microfluidic Systems Coupled to Mass Spectrometry

Protein biomarkers have been the subject of intensive studies as a target for disease diagnostics and monitoring. Indeed, biomarkers have been extensively used for personalized medicine. In biological samples, these biomarkers are most often present in low concentrations masked by a biologically complex proteome (e.g., blood) making their detection difficult. This complexity is further increased by the needs to detect proteoforms and proteome complexity such as the dynamic range of compound concentrations. The development of techniques that simultaneously pre-concentrate and identify low-abundance biomarkers in these proteomes constitutes an avant-garde approach to the early detection of pathologies. Chromatographic-based methods are widely used for protein separation, but these methods are not adapted for biomarker discovery, as they require complex sample handling due to the low biomarker concentration. Therefore, microfluidics devices have emerged as a technology to overcome these shortcomings. In terms of detection, mass spectrometry (MS) is the standard analytical tool given its high sensitivity and specificity. However, for MS, the biomarker must be introduced as pure as possible in order to avoid chemical noise and improve sensitivity. As a result, microfluidics coupled with MS has become increasingly popular in the field of biomarker discovery. This review will show the different approaches to protein enrichment using miniaturized devices and the importance of their coupling with MS.
STBC-Enabled Secure Wireless Transmission With Cooperative Devices Under Imperfect CSI of Destination

In this work, we investigate a practical secure multiple-input single-output (MISO) wireless transmission of information from a source to a destination assisted by cooperative devices. In the first phase, a space-time block code (STBC) is employed; thus, the source does not require any channel state information (CSI). In the second phase, the cooperative devices are divided into two groups, depending on whether they serve for relaying or jamming. Based on the imperfect CSI toward the destination, the devices allocated to the relay group assist the source in forwarding information, whereas those within the jamming group send artificial noise (AN) so as to prevent the eavesdropper from receiving information. Furthermore, the system utilizes two grouping strategies, referred to as random and adaptive. In the former case the role (relaying or jamming) of each device is predetermined randomly, whereas in the latter case it is determined autonomously depending on the decoding results. We analyze the outage probability of our proposed system with and without power allocation optimization under the assumption of imperfect CSI at the cooperative devices, and their accuracy is verified by Monte-Carlo simulations.
Guidance on selecting a translational framework for intervention development: Optimizing interventions for impact

Abstract Intervention development frameworks offer the behavioral sciences a systematic and rigorous empirical process to guide the translation of basic science into practice in pursuit of desirable public health and clinical outcomes. The multiple frameworks that have emerged share a goal of optimization during intervention development and can increase the likelihood of arriving at an effective and disseminable intervention. Yet, the process of optimizing an intervention differs functionally and conceptually across frameworks, creating confusion and conflicting guidance on when and how to optimize. This paper seeks to facilitate the use of translational intervention development frameworks by providing a blueprint for selecting and using a framework by considering the process of optimization as conceptualized by each. First, we operationalize optimization and contextualize its role in intervention development. Next, we provide brief overviews of three translational intervention development frameworks (ORBIT, MRC, and MOST), identifying areas of overlap and divergence thereby aligning core concepts across the frameworks to improve translation. We offer considerations and concrete use cases for investigators seeking to identify and use a framework in their intervention development research. We push forward an agenda of a norm to use and specify frameworks in behavioral science to support a more rapid translational pipeline.
Improving the biological interfacing capability of diketopyrrolopyrrole polymers via p-type doping

Polydiketopyrrolopyrrole terthiophene (DPP3T) is an organic semiconducting polymer that has been widely investigated as the active layer within organic electronic devices, such as photovoltaics and bioelectronic sensors. To facilitate interfacing between biological systems and organic semiconductors it is crucial to tune the material properties to support not only cell adhesion, but also proliferation and growth. Herein, we highlight the potential of molecular doping to judiciously modulate the surface properties of DPP3T and investigate the effects on Schwann cell behaviour on the surface. By using p-type dopants FeCl3 and Magic Blue, we successfully alter the topography of DPP3T thin films, which in turn alters cell behaviour of a Schwann cell line on the surfaces of the films over the course of 48 hours. Cell numbers are significantly increased within both DPP3T doped films, as well as cells possessing larger, more spread out morphology indicated by cell size and shape analysis. Furthermore, the viability of the Schwann cells seeded on the surfaces of the films was not significantly lowered. The use of dopants for influencing cell behaviour on semiconducting polymers holds great promise for improving the cell-device interface, potentially allowing better integration of cells and devices at the initial time of introduction to a biological environment.
Construction d'une base spéciale pour la résolution de quelques problèmes d'Océanographie physique en dimension deux

Cette Note a pour objet de presenter un certain nombre de resultats relatifs a la base de fonctions propres du probleme: -Δu=λu dans Ω inclus dans R 2 , verifiant u.n=0, rot u=0 sur la frontiere γ de Ω et ou u est une fonction de Ω dans R 2 . Principalement on peut extraire de cette base une base de fonctions a divergence nulle et projeter de facon originale les termes non lineaires des equations que nous donnons ci-apres
Stock Market Response to the Russia-Ukraine War: Evidence from an Emerging Market

Abstract This study examines the role of financial factors contributing to firms’ resilience during the Russia-Ukraine war. Event study results show a significant adverse reaction, which started before the official war announcement and grew over time. Further, cross-sectional analyses uncover that the negative effect is mitigated for larger and more profitable firms but amplified for high market-cap firms with high cash and debt-holding; both effects are more pronounced for non-financial companies. This study contributes by exploring Turkey as a unique emerging market setting due to its significant geopolitical position, strategic trade, and business partnership with the European Union and Russia.
Integrated use of GIS, RS and USLE model for LULC change analysis and soil erosion risk mapping in the Lake Hawassa Watershed, Southern Ethiopia

Abstract Soil erosion is a worldwide problem leading to loss of nutrient rich top soil resulting in reduction of agricultural productivity that threatens the livelihood of agrarian societies. Assessment of soil loss due to water-induced erosion using Models is essential to quantify and map erosion prone areas for possible application of soil conservation measures. In the current study, GIS, RS, and USLE model were integrated with the aim to quantify LULC classes, estimate soil loss rates, and identify priority areas for conservation in the Lake Hawassa Watershed for the two temporal instants, 1975 and 2020. The use of thematic recoding and model maker during LULC classification process has improved the accuracy of thematic classes, producing more than 89% for both classified images. The LULC change analysis showed that agricultural land and built-up area expanded by 0.44% and 15.26% per annum, respectively over the last 45 years. The declines in vegetation cover coupled with steep slopes have contributed to the increase in soil loss from 1975 to 2020 by 65%. The model estimated annual soil erosion rate in 1975 that ranged from nil to 158.77 t ha−1 yr−1 with a mean annual soil loss rate of 25.16 t ha−1 yr−1. Likewise, the annual soil loss estimated for the year 2020 varied from zero to 262.48 t ha−1 yr−1 with a mean annual soil loss rate of 28.20 t ha−1 yr−1. Generally, a total of 23,580.59 and 27,783.35 tons of soil have been lost per annum for the year 1975 and 2020, respectively, which is a direct reflection of vegetation clearance. The identified highest three severity classes combined accounted for 50.54% in 1975 and 55.40% of the entire soil loss in 2020 and these losses occurred on areas less than 2% in both 1975 and 2020 periods. Besides, 23.48% and 31.04% of soil loss rates exceeded the established tolerable limit of soil loss for the study area. The integrated use of USLE model, GIS and RS have identified erosion risk areas that could help apply conservation measures.
Interaction of Ions in Organic and Aqueous Media with an Ion-Pair Sensor Equipped with a BODIPY Reporter: An ON1-OFF-ON2-ON3 Fluorescent Assay

Here, we present a ditopic ion-pair sensor, B1, containing the BODIPY reporter unit in its structure, which is shown to be able—thanks to the presence of two heterogeneous binding domains—to interact with anions in an enhanced manner in the presence of cations. This enables it to interact with salts even in 99% aqueous solutions, making B1 a good candidate in terms of visual salt detection in the aquatic environment. Receptor B1’s ability to extract and release salt was applied in the transport of potassium chloride through a bulk liquid membrane. Working with a concentration of B1 in the organic phase and with the presence of a specific salt in an aqueous solution, an inverted transport experiment was also demonstrated. By varying the type and the amount of the anions added to B1, we were able to develop diverse optical responses, including a unique four-step ON1-OFF-ON2-ON3 output.
Spherical-Earth-Based Measurement Modeling for Practical OTHR Target Tracking

In this article, we revisit the problem of modeling of over-the-horizon radar (OTHR) target tracking. The accuracies of target kinematic and measurement models are critical factors affecting tracking performance. In most of the existing literature, a flat Earth OTHR measurement model is used. This has two obvious drawbacks: 1) a state vector with components of ground range, range rate, bearing, and bearing rate cannot be used directly in common kinematic models, such as nearly constant velocity (NCV), nearly constant acceleration (NCA), nearly constant turn (NCT), and a combination of these; and 2) the curvature of earth is ignored, which affects the measurement accuracy of the OTHR. We develop a spherical-earth-based measurement model. First, the target kinematic state is modeled in a 2D tracker coordinate frame, which is suitable for common kinematic models. Second, measurement modeling is completed using the spherical earth model, which fully considers the curvature of earth among the receiver, transmitter, and target. Furthermore, the inverse mapping for track initiation is derived. Finally, the effectiveness of the developed model is demonstrated by a nonmaneuvering target moving with the NCV motion and a maneuvering target moving with a sequence of NCV, NCT, and NCA motions. The interacting multiple model algorithm is used for state estimation of the maneuvering target. The unscented Kalman filter, cubature Kalman filter, and quadrature Kalman filter are compared for state estimation.
Engine control design using globally linearizing control and sliding mode

In this paper the control design methods for spark ignition engine models are discussed. Both single-input single-output (SISO) and multi-input multi-output (MIMO) systems are investigated for the design of an engine control system. A comprehensive comparative study for two classes of non-linear control methods, i.e. globally linearizing control (GLC) and sliding mode control, is given. The simulations results are presented to illustrate the capability and performance of the two kinds of controllers. The results show that the controller applying GLC can give accurate tracking for the engine model without uncertainty and disturbance; however, it fails to keep good tracking performance when uncertainty is considered. In contrast, the controller using the sliding mode is able to achieve the target, which shows that the engine system with the proposed sliding mode controller has good robustness to uncertainty and disturbance.
A Few Things You Need to Know to Tell if a Mathematical Physicist is Talking Nonsense: the Black Hole - a Case Study

Cosmologists claim that they have found black holes all over the Cosmos. The black hole is however entirely a product of mathematics. The simplest case is the 'Schwarzschild' black hole, from the solution to Einstein's field equations in the absence of matter, for a static, uncharged, non-rotating mass. "In the absence of matter" involves linguistic legerdemain, but in any event all types of black holes reduce, mathematically speaking, to a very simple question: Can a squared real number take values less than zero? Symbolically this is restated as follows. Let r be any real number. Is r^2 < 0 possible? No, it's not possible. Thus, the black hole is not possible. Anybody who can square a real number is capable of understanding why the black hole is a fantasy of mathematical physicists and cosmologists, illustrating once again why it can be very dangerous to put trust in the word of an Authority.