Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantitative Analysis of Cell Aggregation Dynamics Identifies HDAC Inhibitors as Potential Regulators of Cancer Cell Clustering

Simple Summary Metastases formation involves the formation, circulation and seeding of cohesive group of tumor cells called circulating tumors cells clusters at distant organs from the primary tumor. These clusters have a much higher metastatic potential than individual circulating tumor cell, it is therefore important to understand the molecular mechanisms involved in their formation. To this aim, in this study, from the analysis of the relationship between in vitro aggregation quantitative characterization of 25 cancer cell lines and their expression data, we identified genes significantly associated with aggregation. Interestingly, we found that these genes were strongly correlated with the transcriptional signature induced by HDAC inhibitors treatment and we finally showed experimentally that two HDAC inhibitors inhibits tumor cells cluster formation in vitro. These results open new therapeutic perspectives to prevent metastasis formation. Abstract Characterization of the molecular mechanisms involved in tumor cell clustering could open the way to new therapeutic strategies. Towards this aim, we used an in vitro quantitative procedure to monitor the anchorage-independent cell aggregation kinetics in a panel of 25 cancer cell lines. The analysis of the relationship between selected aggregation dynamic parameters and the gene expression data for these cell lines from the CCLE database allowed identifying genes with expression significantly associated with aggregation parameter variations. Comparison of these transcripts with the perturbagen signatures from the Connectivity Map resource highlighted that they were strongly correlated with the transcriptional signature of most histone deacetylase (HDAC) inhibitors. Experimental evaluation of two HDAC inhibitors (SAHA and ISOX) showed that they inhibited the initial step of in vitro tumor cell aggregation. This validates our findings and reinforces the potential interest of HDCA inhibitors to prevent metastasis spreading.
Theoretical and experimental characterization of the EMP-interaction with composite-metallic enclosures

A numerical procedure is developed for the prediction of the electric and magnetic field distribution inside an enclosure having aluminum and carbon-fiber reinforced composite (CFRC) walls, illuminated by a transient electromagnetic plane wave. The composite panel is simulated by an effective layer model; time-domain surface impedance boundary conditions are enforced on the external faces of the composite slab, to express the relations among the tangential electric and magnetic field components. A coupling model for the calculation of the current induced along thin wires inside the enclosure is presented. The proposed models are implemented in a three-dimensional (3-D) finite-difference time-domain (FDTD) procedure, which is applied to the analysis of the shielding performances of an aluminum box with one CFRC face, illuminated by a transient electromagnetic wave. The computed results are compared with measured data obtained by using a full scale EMP generator.
Autonomous Ship Collision Avoidance Navigation Concepts, Technologies and Techniques

This study provides both a spherical understanding about autonomous ship navigation for collision avoidance (CA) and a theoretical background of the reviewed work. Additionally, the human cognitive abilities and the collision avoidance regulations (COLREGs) for ship navigation are examined together with water based collision avoidance algorithms. The requirements for autonomous ship navigation are addressed in conjunction with the factors influencing ship collision avoidance. Humans are able to appreciate these factors and also perform ship navigation at a satisfactory level, but their critical decisions are highly subjective and can lead to error and potentially, to ship collision. The research for autonomous ship navigation may be grouped into the classical and soft computing based categories. Classical techniques are based on mathematical models and algorithms while soft-computing techniques are based on Artificial Intelligence (AI). The areas of AI for autonomous ship collision avoidance are examined in this paper are evolutionary algorithms, fuzzy logic, expert systems, and neural networks (NN), as well as a combination of them (hybrid system).
Flexible Use of Spatial Frames of Reference for Object–Location Memory in Older Adults

In memory, representations of spatial features are stored in different reference frames; features relative to our position are stored egocentrically and features relative to each other are stored allocentrically. Accessing these representations engages many cognitive and neural resources, and so is susceptible to age-related breakdown. Yet, recent findings on the heterogeneity of cognitive function and spatial ability in healthy older adults suggest that aging may not uniformly impact the flexible use of spatial representations. These factors have yet to be explored in a precisely controlled task that explicitly manipulates spatial frames of reference across learning and retrieval. We used a lab-based virtual reality task to investigate the relationship between object–location memory across frames of reference, cognitive status, and self-reported spatial ability. Memory error was measured using Euclidean distance from studied object locations to participants’ responses at testing. Older adults recalled object locations less accurately when they switched between frames of reference from learning to testing, compared with when they remained in the same frame of reference. They also showed an allocentric learning advantage, producing less error when switching from an allocentric to an egocentric frame of reference, compared with the reverse direction of switching. Higher MoCA scores and better self-assessed spatial ability predicted less memory error, especially when learning occurred egocentrically. We suggest that egocentric learning deficits are driven by difficulty in binding multiple viewpoints into a coherent representation. Finally, we highlight the heterogeneity of spatial memory performance in healthy older adults as a potential cognitive marker for neurodegeneration, beyond normal aging.
Highly Predictive Modelling of Entire Si Solar Cells for Industrial Applications

The prospective efficiency improvements due to advanced metallisation technology of industrially fabricated Czochralski (Cz) silicon solar cells are assessed by means of highly predictive numerical modelling in two- and three dimensions. The analysis shows that an improved emitter design is only possible with advanced metallisation concepts, and that about 19% efficiency can be achieved with this. Then, the fully metallised back surface field (BSF) limits cell performance. If this BSF is replaced by point contacts without substantial BSF (PERC design), the efficiency is limited to about 20% because the wafer resistivity must be 0.5 Ωcm at maximum, so Cz material has a very limited carrier lifetime due to the boron-oxygen complex. If local BSFs are formed at the rear point contacts (PERL design), higher wafer resistivities can be used, so the base operates under high-injection conditions where the boron-oxygen complex is less detrimental. However, such improvements to the rear side increase cell efficiency only substantially if the lifetime in the Cz material, in particular its interstitial oxygen density, is reduced.
A Comparative Study of the Mechanical Properties of FDM 3D Prints Made of PLA and Carbon Fiber-Reinforced PLA for Thin-Walled Applications

This study focused on the analysis of the mechanical properties of thin-walled specimens fabricated by fused deposition modelling (FDM). Two materials were considered, i.e., polylactide (PLA) and polylactide with carbon fiber (PLA-CF). The article describes how the specimens with different thicknesses and printing orientations were designed, printed, measured to assess their geometric and dimensional accuracy, subjected to tensile testing, and examined using scanning electron microscopy. The data provided here can be used for further research aimed at improving filament deposition and modifying the base material by combining it with different components, for example carbon fiber. The investigations revealed that the properties of thin-walled elements produced by FDM varied significantly depending on the thickness. So far, this problem has not been investigated extensively. Research by analyzing the key parameter, which is the direction of printing that is important for thin-walled models, provides a lot of new information for designers and technologists and opens the way to further extended scientific research in the field of the strength analysis of thin-walled models produced by 3D printing, which is very applicable to structure optimization in the era of the industrial revolution 4.0 and progress in the LEAN manufacturing process.
Transients on multiconductor transmission lines above dissipative earth-numerical simulation and measurement

A finite-difference time-domain (FDTD) analysis is presented to simulate, up to the high-frequency regime, transients on multiconductor transmission lines above dissipative earth. Excitation is in the high-frequency regime if the pulse has significant spectral content up to /spl omega//spl ap//spl omega//sub c/, with /spl omega//sub c/ the frequency where the conduction and displacement current densities have equal magnitude. Thus, /spl omega//sub c/=/spl sigma//sub g///spl epsi//sub 0//spl epsi//sub rg/ with /spl sigma//sub g/ and /spl epsi//sub rg/ the ground conductance and relative permittivity. The FDTD algorithm extends the formulation of Agrawal et al. (1980), by incorporating the theory of D'Amore and Sarto for the interaction of wide-band transients with the earth. Careful experimental testing of the new algorithm is presented. The measurement configuration consists of two parallel wires; first suspended above an aluminum sheet to test the code in the low-frequency regime; then above a block of absorbing material for experiments in the high-frequency regime. The end of one of the conductors is driven with a 2-ns synthesized impulse by a stepped-frequency, automatic network analyzer. Reflected and cross-talk signals are presented in the time domain. These show good agreement with the numerically predicted common mode, differential mode and mode-converted pulses.
A Taxonomy and Design Methodology for Hybrid Memory Systems

The number of concurrently executing processes and their memory demand in multicore systems continue to grow. Larger and still fast main memory is needed for meeting the demand and avoiding an increase in backing store accesses that are much slower and less energy efficient than main memory accesses. Luckily, Non-Volatile Memory (NVM) technologies can bridge the cost, density, performance, and energy efficiency gaps between backing store and DRAM, the conventional main memory technology. Thus, NVM can be combined with DRAM into hybrid main memory striving to enjoy both the larger capacity enabled by NVM and the speed and energy efficiency of DRAM. NVM adds a new dimension to the system design space inspiring researchers to investigate sophisticated hybrid memories. This has resulted in a large body of work that, unfortunately, lacks systematization. The thesis at hand addresses this problem by proposing a taxonomy and a notation for classifying hybrid main memory organizations. The design space of hybrid systems is large, and the best partitioning of resources between DRAM and NVM is nontrivial. The high implementation and computation efforts of detailed modeling impede extensive design space exploration required for finding the most promising design points. This thesis aids such extensive exploration by proposing a workload methodology and first-order models for system-level execution time and energy. Next, the thesis contributes with Rock, an insightful performance model showing how memory system throughput can be boosted by installing more DRAM and NVM thus motivating Design-time Resource Partitioning (DRP). The lack of an approach suitable for extensive partitioning is addressed by proposing Crystal, a DRP method powered by the system-level models and framing partitioning as an optimization problem, such that the first-order nature of the models does not restrict its applicability, as shown by validation. Crystal is practical and facilitates early and rapid DRP finding promising design points for further detailed evaluation. For instance, Crystal shows how for specific workloads higher performance and energy efficiency can be achieved by employing NVM with the speed and energy consumption of NAND Flash instead of a much faster and more energy efficient NVM technology like phase-change memory.
Clustering and switching in verbal fluency: a comparison between control and individuals with brain damage

ABSTRACT Purpose The aim of this study is to analyze and compare the performance and strategies used by control subjects and patients with unilateral brain damage on phonemic and semantic Verbal Fluency tasks. Methods The sample consisted of 104 participants divided into four groups (26 with left hemisphere damage and aphasia- LHDa, 28 with left hemisphere damage and no aphasia- LHDna, 25 with right hemisphere damage- RHD and 25 neurologically healthy control subjects). All participants were administered the phonemic (“M” letter-based) and semantic (animals) verbal fluency tasks from the Montreal-Toulouse Language Assessment Battery (MTL-BR). Results Patients in the LHDa group showed the worst performance (fewer words produced, fewer clusters and switches) in both types of fluency task. RHD group showed fewer switching productions when compared with controls and LHDna had fewer words productions than controls in the first 30 seconds block. Conclusion Our findings suggest that the LHDa group obtained lower scores in most measures of SVF and PVF when compared to the other groups.
Clinical Significance of Intermediate-Density Lipoprotein Cholesterol Determination as a Predictor for Coronary Heart Disease Risk in Middle-Aged Men

Background: Not only low-density lipoprotein (LDL) cholesterol but also non-high-density lipoprotein cholesterol (non-HDL-C), very low-density lipoprotein (VLDL) cholesterol (VLDL-C), and intermediate-density lipoprotein (IDL) cholesterol (IDL-C) are reported to be significant risk markers for coronary heart disease (CHD). We reported the relevance of IDL-C to Framingham risk score (F-score), but the present study addressed the relevance of IDL-C to Suita score (S-score), a risk score for coronary heart disease (CHD) developed for the Japanese individuals in addition to F-score. Methods: The cholesterol levels of lipoproteins, including triglyceride (TG)-rich lipoproteins (IDL and VLDL), were measured by an anion exchange high-performance liquid chromatography (AEX-HPLC). This study enrolled 476 men, aged mean 51 years and free of CHD and stroke. Results: Non-HDL-C, IDL-C, and VLDL-C significantly correlated with F-score and S-score. In the multiple stepwise regression analysis, IDL-C as well as body mass index (BMI) significantly correlated with both F-score and S-score in both the total subjects and the subjects without drug therapy. The multivariate logistic analysis with the model composed of BMI and IDL-C as the predictor variables demonstrated that 1 SD increase in IDL-C was an independent predictor for 10-year CHD risk >10% of F-score (OR 1.534, 95% CI 1.266–1.859, p < 0001) and that of S-score (OR 1.372, 95% CI 1.130–1.667, p = 0.0014) in the total subjects. Even in the subjects without the drug therapy, the increased IDL-C, as well as BMI, were significant predictors for 10-year CHD risk >10% of S-score as well as F-score. Conclusion: These results suggest the significant relevance of the increased IDL-C for CHD risk scores in middle-aged men free of CHD and stroke. Further investigations are needed in women and elderly subjects.
Cells and Robots: Modeling and Control of Large-Size Agent Populations

Cells and Robots is an outcome of the multidisciplinary research extending over Biology, Robotics and Hybrid Systems Theory. It is inspired by modeling reactive behavior of the immune system cell population, where each cell is considered as an independent agent. In our modeling approach, there is no difference if the cells are naturally or artificially created agents, such as robots. This appears even more evident when we introduce a case study concerning a large-size robotic population scenario. Under this scenario, we also formulate the optimal control of maximizing the probability of robotic presence in a given region and discuss the application of the Minimum Principle for partial differential equations to this problem. Simultaneous consideration of cell and robotic populations is of mutual benefit for Biology and Robotics, as well as for the general understanding of multi-agent system dynamics. The text of this monograph is based on the PhD thesis of the first author. The work was a runner-up for the fifth edition of the Georges Giralt Award for the best European PhD thesis in Robotics, annually awarded by the European Robotics Research Network (EURON).
Machine Learning-based Vulnerability Study of Interpose PUFs as Security Primitives for IoT Networks

Security is of importance for communication networks, and many network nodes, like sensors and IoT devices, are resource-constrained. Physical Unclonable Functions (PUFs) leverage physical variations of the integrated circuits to produce responses unique to individual circuits and have the potential for delivering security for low-cost networks. But before a PUF can be adopted for security applications, all security vulnerabilities must be discovered. Recently, a new PUF known as Interpose PUF (IPUF) was proposed, which was tested to be secure against reliability-based modeling attacks and machine learning attacks when the attacked IPUF is of small size. A recent study showed IPUFs succumbed to a divide-and-conquer attack, and the attack method requires the position of the interpose bit known to the attacker, a condition that can be easily obfuscated by using a random interpose position. Thus, large IPUFs may still remain secure against all known modeling attacks if the interpose position is unknown to attackers. In this paper, we present a new modeling attack method of IPUFs using multilayer neural networks, and the attack method requires no knowledge of the interpose position. Our attack was tested on simulated IPUFs and silicon IPUFs implemented on FPGAs, and the results showed that many IPUFs which were resilient against existing attacks cannot withstand our new attack method, revealing a new vulnerability of IPUFs by re-defining the boundary between secure and insecure regions in the IPUF parameter space.
Field programmable gate array implementation of space-vector pulse-width modulation technique for five-phase voltage source inverter

This study analyses a field programmable gate array (FPGA) implementation of space-vector pulse-width modulation (SVPWM) technique for five-phase voltage source inverter (VSI). The five-phase VSIs are dominantly used to supply the fivephase drives that are used for high-power applications. It is necessary to develop an appropriate SVPWM technique for the inverters to provide the required output voltages to five-phase induction motor load. In the proposed work, SVPWM algorithm is described in high-speed integrated circuit hardware description language coding and implemented in an XILINX XC3SD1800A FPGA processor. The relationship between the SVPWM technique for medium, large and combinations of large and medium space vectors for five-phase VSI is analysed. The selection of active space vector and zero vectors is discussed and the possibilities of FPGA implementations are explored. The experimental results with 1 hp five-phase induction motor drive are presented for the different SVPWM techniques. The best SVPWM scheme is identified based on the output voltage and total harmonic distortion.
ANALYTICAL STUDY OF WIDE-BAND BANDPASS FILTERS BASED ON WIRE-BONDED MULTICONDUCTOR TRANSMISSION LINES WITH LH BEHAVIOUR

This paper presents a design methodology of wide-band bandpass fllters based on short-circuited multi-conductor transmission lines with bonding wires between alternated strips. General design guidelines, based on analytical equations, are derived and a left- handed behaviour of the multiconductor structure is inferred and studied. Analytical equations are assessed by means of full-wave electromagnetic simulations and experimental work. A very good agreement between theoretical results and measurements is achieved, that allows both the design and performance analysis of fllters without the need for costly electromagnetic simulations. In addition, the equations presented yield a compact design of the fllter with a left- handed behavior.
A Tool for Estimating Variability in Wood Preservative Treatment Retention

Abstract Composite sampling is standard practice for evaluation of preservative retention levels in preservative-treated wood. Current protocols provide an average retention value but no estimate of uncertainty. Here we describe a statistical method for calculating uncertainty estimates using the standard sampling regime with minimal additional chemical analysis. This tool can be used by wood treaters to generate lower prediction intervals that with a certain level of confidence give lower bounds on preservative retention estimates for a future analysis (e.g., by a customer) indicating whether the treated wood charge would result in a below-target retention value.
Miniscope-LFOV: A large-field-of-view, single-cell-resolution, miniature microscope for wired and wire-free imaging of neural dynamics in freely behaving animals

Imaging large-population, single-cell fluorescent dynamics in freely behaving animals larger than mice remains a key endeavor of neuroscience. We present a large field of view open-source miniature microscope (MiniLFOV) designed for large-scale (3.6 × 2.7 mm), single cell resolution neural imaging in freely behaving rats. It has an electrically adjustable working distance of up to 3.5 mm±100 μm, incorporates an absolute head-orientation sensor, and weighs only 13.9 grams. The MiniLFOV is capable of both deep brain and cortical imaging and has been validated in freely behaving rats by simultaneously imaging >1000 GCaMP7s expressing neurons in the hippocampal CA1 layer and in head-fixed mice by simultaneously imaging ~2000 neurons in the dorsal cortex through a cranial window. The MiniLFOV also supports optional wire-free operation using a novel, wire-free data acquisition expansion board. We expect this new open-source implementation of the UCLA Miniscope platform will enable researchers to address novel hypotheses concerning brain function in freely behaving animals.