Miracle-dz/UniFAR-FTUs huggingface dataset:
Remote Photoplethysmography in Infrared - Towards Contactless Sleep Monitoring

Current state-of-the-art remote PPG (rPPG) algorithms are capable of extracting a clean pulse-signal in ambient light conditions using a regular color camera, even when subjects move significantly. In this study, we investigate the feasibility of rPPG in the (near)-infrared spectrum, which broadens the scope of applications for rPPG. Two camera setups are investigated, one setup consisting of three monochrome cameras with different optical filters, and one setup consisting of a single RGB camera with a visible light blocking filter. Simulation results predict the monochrome setup to be more motion robust, but this simulation neglects parallax. To verify this, a challenging benchmark dataset consisting of 30 videos is created with various motion scenarios and skin-tones. The pulse signal is extracted with an earlier proposed framework, which exploits the spatial redundancy of the camera by combining pulse signals extracted from different skin sites. Experiments show that both camera setups are capable of accurate pulseextraction in all motion scenarios, with an average SNR of +6.45 and +7.26 dB respectively. The single camera setup proves to be superior in scenarios involving scaling, likely due to parallax of the multi-camera setup. To further improve motion robustness of the RGB camera, dedicated LED-illumination with two distinct wavelengths is proposed and verified. A validation study in a Neonatal Intensive Care Unit showed good results during the typical wriggling, turning and respiratory movements of neonates. This chapter is based on M. van Gastel, S. Stuijk, and G. de Haan. Motion robust remote-PPG in infrared. IEEE Transactions on Biomedical Engineering, 62(5):1425–1433, 2015 20 Chapter 2. Robust pulse extraction M. van Gastel, B. Balmaekers, S. B. Oetomo, and W. Verkruysse. Near-continuous non-contact cardiac pulse monitoring in a neonatal intensive care unit in near darkness. In Optical Diagnostics and Sensing XVIII: Toward Point-of-Care Diagnostics, volume 10501, page 1050114. International Society for Optics and Photonics, 2018 2.
Classification of a Song

We live in a world full of data. Every day, people handle different types of data from a variety of measurements and observations. Data describes the characteristics of a species of life, depicts the properties of a natural phenomenon; summarizes the results of experiences or records the dynamics of system operation. Thus, the data provides a basis for analysis, reasoning, decision and ultimately, for understanding all kinds of objects and phenomena. The new information technology, at the same time they facilitate the movement and storage of information, contributing to their exponential growth, they are in numbers disproportionate to the human resources to address them. This paper addresses the problem of indexing database containing songs using title and artist particularities to enable their effective exploitation. In this article, we present our experiments in automated song categorization, where we suggest the use of an ant colony algorithm. A Naive Bayes algorithm is used as a baseline in our tests. Keywords-componen: Song categorisation; Information Retrieval, Audio indexing; Naive Bayes Algorithm; Ant Colony Algorithm.
A microfluidic-based method for micro particle trapping and positioning

Micro particle trapping and positioning is widely used in bioengineering, pharmaceuticals, micro-assembly, chemical analysis, and material performance evaluation. In this paper, we present a non-contact microfluidic-based method for trapping and positioning micro particles. With this method, two identical microtubes are symmetrically aligned on both sides of a particle, which squirt inside fluid to produce a flow field. The particle is enveloped by a pressure surface which enables trapping and clamping the particle. This method is valid for micron-sized particles of arbitrary shapes. The trapping and positioning mechanism is analysed and the feasibility of the method is verified by experiments.
The current status of robot-assisted cystectomy

Robot-assistance is being increasingly used for radical cystectomy (RC). Fifteen years of surgical evolution might be considered a short period for a radical procedure to be established as the treatment of choice, but robot assisted radical cystectomy (RARC) is showing promising results when compared with the current gold standard, open RC (ORC). In this review, we describe the current status of RARC and continue the discussion on the on-going RARC versus ORC debate.
Memory Efficient PCA Methods for Large Group ICA

Principal component analysis (PCA) is widely used for data reduction in group independent component analysis (ICA) of fMRI data. Commonly, group-level PCA of temporally concatenated datasets is computed prior to ICA of the group principal components. This work focuses on reducing very high dimensional temporally concatenated datasets into its group PCA space. Existing randomized PCA methods can determine the PCA subspace with minimal memory requirements and, thus, are ideal for solving large PCA problems. Since the number of dataloads is not typically optimized, we extend one of these methods to compute PCA of very large datasets with a minimal number of dataloads. This method is coined multi power iteration (MPOWIT). The key idea behind MPOWIT is to estimate a subspace larger than the desired one, while checking for convergence of only the smaller subset of interest. The number of iterations is reduced considerably (as well as the number of dataloads), accelerating convergence without loss of accuracy. More importantly, in the proposed implementation of MPOWIT, the memory required for successful recovery of the group principal components becomes independent of the number of subjects analyzed. Highly efficient subsampled eigenvalue decomposition techniques are also introduced, furnishing excellent PCA subspace approximations that can be used for intelligent initialization of randomized methods such as MPOWIT. Together, these developments enable efficient estimation of accurate principal components, as we illustrate by solving a 1600-subject group-level PCA of fMRI with standard acquisition parameters, on a regular desktop computer with only 4 GB RAM, in just a few hours. MPOWIT is also highly scalable and could realistically solve group-level PCA of fMRI on thousands of subjects, or more, using standard hardware, limited only by time, not memory. Also, the MPOWIT algorithm is highly parallelizable, which would enable fast, distributed implementations ideal for big data analysis. Implications to other methods such as expectation maximization PCA (EM PCA) are also presented. Based on our results, general recommendations for efficient application of PCA methods are given according to problem size and available computational resources. MPOWIT and all other methods discussed here are implemented and readily available in the open source GIFT software.
Investigating the properties and application of tantalum pentoxide nanostructures for cancer radiotherapy

In this thesis, a new material is investigated for application in radiation medicine. In particular, to the fields of dose-enhancement radiotherapy (DERT) and UV protection. The material developed was tantalum pentoxide (elemental composition Ta2O5) in the form of ceramic nanostructured particles (NSPs). Prior to this study, no literature existed on the application of Ta2O5 NSPs to DERT or UV protection, highlighting the novelty and significance of the results presented in this thesis. A series of toxicity studies revealed Ta2O5 NSPs to be non-toxic over time periods of up to 14 days, concentrations up to 500 μg/ml and multiple cell lines. Efficacy of radiosensitisation was quantified using the sensitisation enhancement ratio, with a maximum SER of 1.46 measured in a 10 MV X-ray photon beam with a concentration of 500 μg/ml on 9L cells. This enhancement not only compares well with other compounds currently utilised in DERT, but in some cases exceeds the efficacy at this beam energy, notably in the case of gold (Au) nanoparticles (NPs). Furthermore, radiosensitisation was observed to be dependent on beam energy and NSP morphology, although at higher NSP concentrations no significant change in enhancement was observed. This lack of enhancement was attributed to a phenomenon not yet observed in DERT, referred to as the ”shell effect”. The first introduction of Ta2O5 NSPs for UV protection applications was investigated using UV-visible absorbance spectroscopy, as well as cellular experiments with non-cancerous MDCK cells. All results were compared to commercial-grade zinc oxide (ZnO) NPs, which are currently utilised in sunscreen and cosmetic products
HME: A lightweight emulator for hybrid memory

Emerging non-volatile memory (NVM) technologies have been widely studied in recent years. Those studies mainly rely on cycle-accurate architecture simulators because the commercial NVM hardware is still unavailable. However, current simulation approaches are either too slow, or cannot simulate complex and large-scale workloads. In this paper, we propose a DRAM-based hybrid memory emulator, called HME, to emulate the performance characteristics of NVM devices. HME exploits hardware features available in commodity Non-Uniform Memory Access (NUMA) architectures to emulate two kinds of memories: fast, local DRAM, and slower, remote NVM on other NUMA nodes. HME can emulate a wide range of NVM latencies by injecting software-created memory access delays on the remote NUMA nodes. To evaluate the impact of hybrid memories on the application performance, we also provide application programming interfaces to allocate memory from NVM or DRAM regions. We evaluate the accuracy of the read/write delay injection models by using SPEC CPU2006 and compare the results with a state-of-the-art NVM emulator Quartz. Experimental results demonstrate that the average emulation errors of NVM read and write latencies are less than 5% in HME, which is much lower than Quartz. Moreover, the application performance overhead in HME is one order of magnitude lower than Quartz.
Ternary Near-Infrared Spectroscopy Brain-Computer Interface With Increased Information Transfer Rate Using Prefrontal Hemodynamic Changes During Mental Arithmetic, Breath-Holding, and Idle State

The implementation of a multi-class brain-computer interface (BCI) is an efficient way to increase the information transfer rate (ITR) generally expressed in a unit of bits/trial. The improvement of ITR is of specific importance for near-infrared spectroscopy (NIRS)-BCI, because brain hemodynamic responses recorded by NIRS are much slower than the electrophysiological responses of the brain. In this paper, to implement a ternary NIRS-BCI with increased ITR, we used prefrontal cortex (PFC) hemodynamic changes induced by breath-holding (i.e., the voluntary suppression of breathing movements), which have never been used in the field of BCIs. Additionally, we used traditional BCI tasks such as mental arithmetic and idle state to implement ternary NIRS-BCI. As a result, an average offline ternary classification accuracy of 72.6 ± 10.7% could be achieved, which is the best performance of NIRS-BCI based on PFC hemodynamic changes reported to date. Because the number of available input commands was increased and the classification accuracy remained at an acceptable level, the ITR of the ternary BCI (0.51 ± 0.29 bits/trial) was 1.6 times higher than that of the traditional binary BCI (0.31 ± 0.21 bits/trial). Although the hemodynamic changes induced by the breath-holding were not caused by mental state changes, breath-holding proved to be a promising hybrid BCI task for implementing more efficient ternary NIRS-BCI.
CDA: A Clustering Degree Based Influential Spreader Identification Algorithm in Weighted Complex Network

Identifying the most influential spreaders in a weighted complex network is vital for optimizing utilization of the network structure and promoting the information propagation. Most existing algorithms focus on node centrality, which consider more connectivity than clustering. In this paper, a novel algorithm based on clustering degree algorithm (CDA) is proposed to identify the most influential spreaders in a weighted network. First, the weighted degree of a node is defined according to the node degree and strength. Then, based on the node weighted degree, the clustering degree of a node is calculated in respect to the network topological structure. Finally, the propagation capability of a node is achieved by accounting the clustering degree of the node and the contribution from its neighbors. In order to evaluate the performance of the proposed CDA algorithm, the susceptible-infected-recovered model is adopted to simulate the propagation process in real-world networks. The experiment results have showed that CDA is the most effective algorithm in terms of Kendall’s tau coefficient and with the highest accuracy in influential spreader identification compared with other algorithms such as weighted degree centrality, weighted closeness centrality, evidential centrality, and evidential semilocal centrality.
The Mitogen-Activated Protein Kinase Slt2 Regulates Nuclear Retention of Non-Heat Shock mRNAs during Heat Shock-Induced Stress

ABSTRACT Cellular adaptation to environmental stress conditions requires rapid and specific changes in gene expression. During heat shock, most polyadenylated mRNAs are retained in the nucleus, whereas the export of heat shock-induced mRNAs is allowed. Although essential mRNA export factors are known, the precise mechanism for regulating transport is not fully understood. Here we find that during heat shock in Saccharomyces cerevisiae, the mRNA-binding protein Nab2 is phosphorylated on threonine 178 and serine 180 by the mitogen-activated protein (MAP) kinase Slt2/Mpk1. Slt2 is required for nuclear poly(A+) mRNA accumulation upon heat shock, and thermotolerance is decreased in a nup42 nab2-T178A/S180A mutant. Coincident with phosphorylation, Nab2 and Yra1 colocalize in nuclear foci with Mlp1, a protein involved in mRNA retention. Nab2 nuclear focus formation and Nab2 phosphorylation are independent, suggesting that heat shock induces multiple cellular alterations that impinge upon transport efficiency. Under normal conditions, we find that the mRNA export receptor Mex67 and Nab2 directly interact. However, upon heat shock stress, Mex67 does not localize to the Mlp1 nuclear foci, and its association with Nab2 complexes is reduced. These results reveal a novel mechanism by which the MAP kinase Slt2 and Mlp1 control mRNA export factors during heat shock stress.
The extracellular matrix: A dynamic niche in cancer progression

The local microenvironment, or niche, of a cancer cell plays important roles in cancer development. A major component of the niche is the extracellular matrix (ECM), a complex network of macromolecules with distinctive physical, biochemical, and biomechanical properties. Although tightly controlled during embryonic development and organ homeostasis, the ECM is commonly deregulated and becomes disorganized in diseases such as cancer. Abnormal ECM affects cancer progression by directly promoting cellular transformation and metastasis. Importantly, however, ECM anomalies also deregulate behavior of stromal cells, facilitate tumor-associated angiogenesis and inflammation, and thus lead to generation of a tumorigenic microenvironment. Understanding how ECM composition and topography are maintained and how their deregulation influences cancer progression may help develop new therapeutic interventions by targeting the tumor niche.
Electrospinning Process and Structure Relationship of Biobased Poly(butylene succinate) for Nanoporous Fibers

Biobased poly(butylene succinate) (BioPBS) was electrospun to create hierarchical, highly porous fibers. Various grades of BioPBS were dissolved in one of the three solutions: chloroform, a co-solvent system of chloroform/N,N-dimethylformamide (DMF), or chloroform/dimethyl sulfoxide (DMSO). These solutions were then electrospun at room temperature to produce nanoporous micron-sized fibers. The variables investigated were the solvent system used, grade of BioPBS, concentration of BioPBS, applied voltage, and the distance between the electrodes. In determining the optimal solution and electrospinning conditions, it was found that solution properties such as the solvent system, the grade of BioPBS, and the concentration of BioPBS had a significant effect on the fiber morphology. A chloroform/DMSO cosolvent system resulted in less bead defects among fibers compared to those produced from chloroform/DMF systems, regardless of the BioPBS grade. An increase in BioPBS concentration resulted in the reduction of bead defects, which at 15 (% w/v) resulted in bead-free uniform fibers. Increasing BioPBS concentration also increased the porosity of the fibers while reducing the pore size. Dynamic mechanical analysis showed that the reduction of bead defects resulted in increased tensile strength and Young’s modulus of the electrospun fibrous nonwoven mat. The results of this study show that electrospun BioPBS fibers have high porosity at the micro- and nanoscale, resulting in a hierarchical structure that has sufficient mechanical properties for potential applications in wound healing and soft tissue engineering.
Is coccolithophore distribution in the Mediterranean Sea related to seawater carbonate chemistry?

Abstract. The Mediterranean Sea is considered a "hot spot" for climate change, being characterized by oligotrophic to ultra-oligotrophic waters and rapidly increasing seasurface temperature and changing carbonate chemistry. Coccolithophores are considered a dominant phytoplankton group in these waters. As marine calcifying organisms they are expected to respond to the ongoing changes in seawater carbonate chemistry. We provide here a description of the springtime coccolithophore distribution in the Mediterranean Sea and relate this to a broad set of in situ-measured environmental variables. Samples were taken during the R/V Meteor (M84/3) oceanographic cruise in April 2011, between 0 and 100 m water depth from 28 stations. Total diatom and silicoflagellate cell concentrations are also presented. Our results highlight the importance of seawater carbonate chemistry, especially [CO32−] but also [PO43−] in unraveling the distribution of heterococcolithophores, the most abundant coccolithophore life phase. Holo- and heterococcolithophores respond differently to environmental factors. For instance, changes in heterococcolithophore assemblages were best linked to the combination of [CO32−], pH, and salinity (ρ = 0.57), although salinity might be not functionally related to coccolithophore assemblage distribution. Holococcolithophores, on the other hand, showed higher abundances and species diversity in oligotrophic areas (best fit, ρ = 0.32 for nutrients), thriving in nutrient-depleted waters. Clustering of heterococcolithophores revealed three groups of species sharing more than 65% similarities. These clusters could be assigned to the eastern and western basins and deeper layers (below 50 m), respectively. In addition, the species Gephyrocapsa oceanica, G. muellerae, and Emiliania huxleyi morphotype B/C are spatially distributed together and trace the influx of Atlantic waters into the Mediterranean Sea. The results of the present work emphasize the importance of considering holo- and heterococcolithophores separately when analyzing changes in species assemblages and diversity. Our findings suggest that coccolithophores are a main phytoplankton group in the entire Mediterranean Sea and can dominate over siliceous phytoplankton. They have life stages that are expected to respond differently to the variability in seawater carbonate chemistry and nutrient concentrations.
A Single IGF1 Allele Is a Major Determinant of Small Size in Dogs

The domestic dog exhibits greater diversity in body size than any other terrestrial vertebrate. We used a strategy that exploits the breed structure of dogs to investigate the genetic basis of size. First, through a genome-wide scan, we identified a major quantitative trait locus (QTL) on chromosome 15 influencing size variation within a single breed. Second, we examined genetic variation in the 15-megabase interval surrounding the QTL in small and giant breeds and found marked evidence for a selective sweep spanning a single gene (IGF1), encoding insulin-like growth factor 1. A single IGF1 single-nucleotide polymorphism haplotype is common to all small breeds and nearly absent from giant breeds, suggesting that the same causal sequence variant is a major contributor to body size in all small dogs.
Development of low alloy steel by direct metal laser sintering

DEVELOPMENT OF LOW ALLOY STEEL BY DIRECT METAL LASER SINTERING by Elias Jelis The US Department of Defense is interested in developing, understanding, and optimizing process parameters for low alloy (4340/4140 steel) for the powder bed fusion process. Low alloy steel is used in parts where high strength and toughness are required. During parameter optimization, several aspects of the process are investigated. Powder size and morphology optimization is important for manufacturability because adequate packing is required to produce full density components. Microstructure evaluation is used in order to provide insight into parameters that lead to optimal mechanical performance and recoating performance. Influence of residual stress is evaluated with this process. Large thermal stress can lead to high distortion and deflection. A general corrosion study is conducted on direct metal laser sintered parts in order to evaluate the factors which lead to corrosion. The main objectives of this effort are to produce mechanical properties of steel that are comparable to wrought 4340 and to understand the factors which influence the qualification of the powder bed fusion process.
NPAS2: An Analog of Clock Operative in the Mammalian Forebrain

Neuronal PAS domain protein 2 (NPAS2) is a transcription factor expressed primarily in the mammalian forebrain. NPAS2 is highly related in primary amino acid sequence to Clock, a transcription factor expressed in the suprachiasmatic nucleus that heterodimerizes with BMAL1 and regulates circadian rhythm. To investigate the biological role of NPAS2, we prepared a neuroblastoma cell line capable of conditional induction of the NPAS2:BMAL1 heterodimer and identified putative target genes by representational difference analysis, DNA microarrays, and Northern blotting. Coinduction of NPAS2 and BMAL1 activated transcription of the endogenous Per1,Per2, and Cry1 genes, which encode negatively activating components of the circadian regulatory apparatus, and repressed transcription of the endogenous BMAL1 gene. Analysis of the frontal cortex of wild-type mice kept in a 24-hour light-dark cycle revealed that Per1, Per2, andCry1 mRNA levels were elevated during darkness and reduced during light, whereas BMAL1 mRNA displayed the opposite pattern. In situ hybridization assays of mice kept in constant darkness revealed that Per2 mRNA abundance did not oscillate as a function of the circadian cycle in NPAS2-deficient mice. Thus, NPAS2 likely functions as part of a molecular clock operative in the mammalian forebrain.