Miracle-dz/UniFAR-FTUs huggingface dataset:
Evolution of Pediatric Home Mechanical Ventilation Program in Serbia—What Has Changed in the Last Decade

Home mechanical ventilation (HMV) is a method of treatment in children with sleep-disordered breathing (SDB) and alveolar hypoventilation regardless of primary disease. The goal of the study was to describe the changes in the HMV program in Serbia during the last two decades. Cross-sectional retrospective study included data from the national HMV database from 2001 until 2019. HMV was initiated in clinically stable patients after the failure to wean from mechanical ventilation succeeded acute respiratory deterioration or electively after the confirmation of SDB and alveolar hypoventilation by sleep study or continuous transcutaneous capnometry and oximetry. The study included 105 patients (50 ventilated noninvasively and 55 ventilated invasively via tracheostomy). The median age at the time of HMV initiation was 6.2 years (range: 0.3–18 years). Invasive ventilation had been initiated significantly earlier than noninvasive ventilation (NIV) (p < 0.01), without difference in duration of ventilatory support (p = 0.95). Patients on NIV were significantly older (p < 0.01) than those ventilated invasively (13 and 1.5 years, respectively). Average waiting time on equipment had been shortened significantly—from 6.3 months until 2010 to 1 month at the end of the study (p < 0.01). Only 6.6% of patients had obstructive sleep apnea syndrome (OSAS) requiring HMV. During the study period, 24% patients died, mostly due to uncontrolled infection or progression of underlying disease. Availability and shortened waiting time for the equipment accompanied by advanced overall health care led to substantial improvements in the national HMV program. However, future improvements should be directed to systematic evaluation of SDB in patients with OSAS, early diagnosis of nocturnal hypoventilation, and subsequent timely initiation of chronic ventilation.
5G Network Slicing: A Security Overview

The fifth-generation (5G) of cellular networks is currently under deployment by network operators, and new 5G end-user devices are about to be commercialized by many manufacturers. This is just a first step in the 5G’s development, and the true potential of 5G is still far from being reached. Currently, one of the main 5G technologies under the interest of the research community is the network slicing. Network slicing will allow exploiting the 5G infrastructure to flexibly and efficiently provide heterogeneous services (e.g., voice communication, video streaming, e-health, vehicular communication). Like every new technology, one of the critical aspects that need to be considered is the security. In this article, we spotlight the security in 5G network slicing. We highlight threats and recommendations, which are presented in terms of life-cycle security, intra-slice security, and inter-slice security. Furthermore, we identify and discuss open security issues related to network slicing.
A Proposal of FPGA-Based Low Cost and Power Efficient Autonomous Fruit Harvester

In this paper, we present a power-efficient and low- cost prototype of a robotic harvester which employs multiple subsystems such as fruit detection, odometry, localization, profi- cient manipulation through computer vision, deep learning and a novel end-effector design. Fruit Plucking is performed using an end effector, and 3-degree of freedom (DOF) arm (made out of the integration of two linear actuators and a rotating platform) consolidated with a 4-wheeled differential drive mobile platform. Effective implementation of the visual processing is executed on the FPGA Fabric of the Xilinx PYNQ-Z2 Board, which accelerates Deep Neural Networks (DNNs) with improved Latency and Energy Efficiency as compared to a CPU or GPU based implementation.
Special Session – Emerging Memristor Based Memory and CIM Architecture: Test, Repair and Yield Analysis

Emerging memristor-based architectures are promising for data-intensive applications as these can enhance the computation efficiency, solve the data transfer bottleneck and at the same time deliver high energy efficiency using their normally-off/instant-on attributes. However, their storing devices are more susceptible to manufacturing defects compared to the traditional memory technologies because they are fabricated with new materials and require different manufacturing processes. Hence, in order to ensure correct functionalities for these technologies, it is necessary to have accurate fault modeling as well as proper test methodologies with high test coverage. In this paper, we propose technology specific cell-level defect modeling, accurate fault analysis and yield improvement solutions for memristor-based memory as well as Computation-In-Memory (CIM) architectures. Our overall contributions cover three abstraction levels, namely, device, architecture and system. First, we propose a device-aware test methodology in which we have introduced a key device-level characteristic to develop accurate defect model. Second, we demonstrate a yield analysis framework for memristor arrays considering reliability and permanent faults due to parametric variations and explore fault-tolerant solutions. Third, a lightweight on-line test and repair schemes is proposed for emerging CIM devices in machine learning applications.
An Inventory of UV-Absorbing Mycosporine-Like Amino Acids in Macroalgae from Polar to Warm-Temperate Regions

A qualitative and quantitative survey of 11 green, 27 brown and 30 red macroalgal species collected from polar (Spitsbergen), cold-temperate (Helgoland) and warm-temperate (southern Spain) regions revealed that all Rhodophyceae from the eulittoral zone contained several UV-absorbing mycosporine-like amino acid compounds (MAAs), which are assumed to function as natural UV-sunscreens. In contrast, deep-water red algae, as well as the Chlorophyceae and Phaeophyceae did not contain MAAs or exhibited only trace concentrations. Within all species investigated 9 distinct compounds were found, of which 7 were identified as mycosporine-glycine, shinorine, porphyra-334, palythine, asterina-330, palythinol and palythene. The remaining two substances are unknown; they had different retention times under the Chromatographie conditions used, but identical absorption spectra with a maximum at 357 nm. Both compounds are restricted to a few polar red algae. In Polysiphonia arctica J. Agardh (Rhodophyta) from Spitsbergen the concentrations of MAAs decreased from depths of 1 to 7 m. Shallow-water isolates contained > 5-fold higher total MAA amounts compared to deep-water samples. In addition, the contents of all MAAs correlated with the biogeographic region indicating that the lower the natural solar irradiance in the respective habitat the less MAAs are synthesised and accumulated. The red algal samples from Spain exhibited up to 2-fold higher MAA contents compared to species from cold-temperate and polar waters supporting the idea of a UV-dose-dependent induction and/or concentration. The data support the idea that MAAs represent a least for red macroalgae a natural defense system against exposure to biologically harmful UV-radiation.
Visual Analytics Design To Support Knowledge Generation: The Case Of Outcome Based Education Assessment in Malaysia

Colleges and universities serve to prepare students for the working world. However, there is a gap between what was learned and taught in colleges and universities with the demands of the working industries. In order to produce graduates equipped with the necessary skills, knowledge and attitude for the working industries, Ministry of Education (MoHE) introduces iCGPA. iCGPA is an outcome based assessment platform that reports students holistic values attainment in the form of a static spider web. However, because students' skills attainment can go beyond the classroom, the existing outcome based education assessment platform output which only shows the students' skills level based on classroom assessment and the static representation in the form of spider chart prevents data exploration for deeper understanding on the students' performance. Besides students' results, higher education institutes stored a number of different students' data which can be leverage to acquire deeper insight to a certain situation. The use of visual analytics to handle different data related to students' skills and values attainment can enhance the outcome-based education assessment platform mechanism by enabling the generation of more insights and knowledge to discover ways to improve students' results. Therefore, in this study, the proposed framework for visual analytics design to support knowledge generation was refined after research requirement analysis was done with experts and the outcome was the finalization of visualization, interaction and data types. The outcome supports the proposed framework's ability to expedite the exploration of students' data result together with their out of classroom activities data thus supporting knowledge generation.
System Prototype Proposed for Vehicle Communications Based on VLC-RF Technologies Adaptable on Infrastructure

The chaotic increase in the number of vehicles and the population density makes road safety an important topic from all points of view. Urban planning and disorganization in terms of traffic efficiency and fluidization solutions cause massive traffic congestion in most cities around the world. The diversity of mechanisms and devices dedicated to the fluidization of traffic in pedestrian areas or pedestrian crossings does not offer safety to all categories of persons, here referring to the sick, elderly, children. A number of studies that have analyzed and focused on the field, offer solutions whereby a combination of vehicles and automated tools, used in conjunction with an efficient data communication type, can reduce traffic congestion problems and reduce traffic jams. Wireless communications technologies have the possibility of the dynamic and increase the security of the transmission mode. We can say that this article presents an overview. of the most important and promising technologies that can be. used in the applications dedicated to the road safety sector based on communication between cars. We propose a system prototype based on RF (Radio-Frequency) communications and VLC (Visible Light Communications) technology, thus making a promising alternative in the field. Based on these proposals, analyzes and simulations are performed on a hybrid architecture, offering results on performance evaluation of the solution.
A sympatric sibling species complex of Petrotilapia Trewavas from Lake Malawi analysed by enzyme electrophoresis (Pisces: Cichlidae)

The protein electromorphs of three taxa of Petrotilapia, referred to in earlier works as sibling species, were examined by starch-gel electrophoresis. The results indicated that, for the three taxa, no alternative fixed alleles occurred for any of the 25 loci (enzymes) examined. However, heterogeneous gene frequencies were indicated at seven polymorphic loci. This suggests that either the taxa are isolated ‘sibling’ species which recently diverged, or that they are ‘incipient’ species with minimal gene flow between morphs. The genetic and field data lend support to the hypothesis that sympatric splitting of morphs could be important in the explosive radiation of the cichlidae.
Inoculation With Desulfovibrio sp. Does Not Enhance Chalk Formation in the Pacific Oyster

Some oyster species precipitate a soft, friable form of calcite that is occluded within their shells, often referred to as chalk or chalky deposits. Because of the unusual microstructure of this shell feature, it has been proposed that chalk is the result of microbial involvement in the calcification process. Specifically, chalk has been hypothesized to be induced or influenced by microbial sulfate-reduction, and therefore chalk formation may not be under direct control of the oysters themselves. Specimens of the Pacific oyster, Magallana gigas, well-known for chalk deposition within shells, were grown in Bodega Harbor, Bodega Bay, California, and exposed monthly to treatments that altered the abundance of sulfate-reducing bacteria within oysters. The four treatment conditions evaluated included a control group (not exposed to any reagents), as well as oysters exposed to ciprofloxacin (a broad spectrum antibiotic), sodium molybdate (a compound known to inhibit bacterial sulfate reduction), and an inoculum of a sulfate-reducing bacterium isolated for this study. At the end of a 7 month growing period, specimens were culled and shells from treatment groups were assessed for chalk content by measuring bulk shell density and percentage of chalk in a cross sectional area. While analyses show that treatment conditions were successful with respect to altering abundances of sulfate-reducing bacteria in oysters, increasing SRB populations did not correlate to enhanced chalk expression in oyster shells. Interestingly, control oysters produced more chalk than the other treatment groups, according to both bulk shell density and percent chalk measured in cross section. Given that control oysters represent the wild type for chalk expression in shells, it is inferred that the decreased formation of chalk in the other groups was due to a perturbation of the microbiome in the oyster calcifying fluid. However, the methods used here only quantify the presence of sulfate-reducing bacteria in oysters, and therefore, additional work is necessary to evaluate the role of the microbiome in oyster calcification.
Mining Pool Game Model and Nash Equilibrium Analysis for PoW-Based Blockchain Networks

Blockchain technology, has the characteristics of decentralization, openness and transparency, so that everyone can participate in database recording. Therefore, blockchain technology has a good application prospect in various industries. As the most successful application of blockchain technology, the Bitcoin system applies the Proof of Work (PoW) consensus mechanism. Under the PoW consensus mechanism, each miner competes through his own power to solve a SHA256 mathematical problem together, so as to gain profits. Due to the difficulty of the cryptography puzzle, miners tend to join the mining pool to obtain stable income. And the block withholding attacks will be carried out between the mining pools, so as to maximize his own income by controlling the infiltration rate dispatched to other mining pools. In this paper, we build a game model between mining pools based on the PoW consensus algorithm, and analyze its Nash equilibrium from two perspectives. The influence of the mining pools’ power, the ratio of the power to be infiltrated, and the betrayed rate of dispatched miners on the mining pool’s infiltration rate selection and income were explored, and the results were obtained through numerical simulations.
Application of Near-Infrared Reflectance Spectroscopy for the Rapid Chemical Analysis of Sydney Rock Oyster (Saccostrea Glomerata) and Pacific Oyster (Crassostrea gigas)

ABSTRACT Near-infrared IR reflectance spectroscopy (NIRS) was applied to the compositional analysis of oysters (Crassostrea gigas and Saccostrea glomerata). Homogenized meat samples of 332 oysters were scanned by NIRS, subsamples were analyzed chemically, and, by combining the sets of information, calibration models were developed to allow prediction of proximate composition (moisture, protein, glycogen, and fat). Predicted and actual (chemically measured) data in independent validation sample sets were compared using R 2 and the ratio of the SE of chemical data to the SE of NIRS prediction (RPD). For S. glomerata, models gave excellent prediction for all components (R 2 = 0.95–0.97, RPD = 2.7–5.5). Prediction within the C. gigas validation set was generally less precise, but still very good for all components (R 2 = 0.92–0.96, RPD = 2.7–4.8). With a smaller subset of samples (n = 48), prediction models were also developed for estimating concentration of polyunsaturated fatty acid and long-chain polyunsaturated fatty acid (R 2 = 0.94 and 0.93, respectively). The major advantages of the methodology are its speed—250—300 samples can be analyzed simultaneously for all components each day—and cost-effectiveness when a large number of samples (e.g., several hundred or more per year) are analyzed. Therefore, the method is ideally suited to applications requiring the rapid analysis of many individuals, such as selective breeding programs for which chemical compositional data can provide information on traits associated with oyster condition or quality.
In-Memory Computing array using 40nm multibit SONOS achieving 100 TOPS/W energy efficiency for Deep Neural Network Edge Inference Accelerators

40nm SONOS (Si-Oxide-Nitride-Oxide-Si) based non-volatile memory (NVM) cell has been evaluated for analog memory to perform in-memory neuromorphic computing. Process flow and smart-write algorithms were developed to tune key parameters like sigma, retention and noise performance for this application. Their optimizations to meet the product reliability requirements are also discussed. The performance and power of SONOS in a dense array is evaluated, and the sigma and retention data obtained are discussed.
The differential rate of seed development in Dwalganup and Geraldton varieties of subterranean clover

The development of seed in the Dwalganup and Geraldton varieties of subterranean clover was studied in both buried and unburied burrs. Geraldton required six to nine less days after anthesis than did Dwalganup for the production of viable seed. Viable seed was produced two to four days earlier in buried than in unburied burrs. The magnitude of the differences between these varieties is influenced by the environmental conditions prevailing during seed development.
Deep Analysis of Process Model Matching Techniques

Process Model Matching (PMM) aims to automatically identify corresponding activities from two process models that exhibit similar behaviors. Recognizing the diverse applications of process model matching, several techniques have been proposed in the literature. Typically, the effectiveness of these matching techniques has been evaluated using three widely used performance measures, Precision, Recall, and F1 score. In this study, we have established that the values of these three measures for each dataset do not provide deeper insights into the capabilities of the matching techniques. To that end, we have made three significant contributions. Firstly, we have enhanced four benchmark datasets by classifying their corresponding activities into three sub-types. The enhanced datasets can be used for surface-level evaluation, as well as a deeper evaluation of matching techniques. Secondly, we have conducted a systematic search of the literature to identify an extensive set of 27 matching techniques and subsequently proposed a taxonomy for these matching techniques. Finally, we have performed 432 experiments to evaluate the effectiveness of all the matching techniques, and key observations about the effectiveness of the techniques are presented.
EM Wave Scattering on Thin Flexible Films Supplemented by a Set of Micro Particles

The problem of electromagnetic (EM) wave scattering on thin layer (film) in presence of a set of small particles is studied based on the asymptotic approach. The size of particle is of order less than the distance between the adjacent particles; the number of particles is big and they are distributed with peculiar density in the initial material. A close form of solution to the scattering problem is reduced. The scattering characteristics of structure are studied for the different geometrical parameters in the case of plane incident wave.
A Novel Strategy of DFIG in the Frequency Modulation for Power Grid

The DFIG uses a converter based on space vector pulse width modulation (SVPWM) to realize the decoupling of electromagnetic and mechanical power, but the DFIG cannot respond immediately when the power grid frequency fluctuates. In order to solve this problem, based on the existing model of the DFIG and its control methods, this paper proposes an additional frequency control link in the active power control of rotor side and make the DFIG's rotor release or absorb part of kinetic energy, which can change the active power output according to the change of the grid frequency, so as to realize the frequency control of wind turbines and increase the equivalent inertia of the power system. Simulation results demonstrate the effectiveness of the proposed method. The control strategy can make the wind farm of DFIGs participate in the frequency regulation of power system, and the regulation effect becomes better with the increase of wind power penetration rate.
A Novel Image Description With the Stretched Natural Vector Method: Application to Face Recognition

Nowadays there is growing research interest in designing high performance algorithms for automatic facial recognition systems, and an efficient computational approach is required. Accurate face recognition, however, is difficult due to facial complexity. In this paper, we propose a novel and efficient facial image representation named the Stretched Natural Vector (SNV) method which is defined on the intensity values in a grayscale image matrix, where each entry in an intensity matrix records the level of gray at a single pixel in a $m\times n$ array. We prove that the SNV defined in this context can distinguish photo matrices in strict one-to-one fashion. This is to say it is theoretically possible to fully recover a grayscale image matrix from the corresponding complete SNV. Experiments on a number of datasets demonstrate that our truncated SNV method compares favorably both in recognition accuracy and efficiency (measured in wall-clock time) against “Full-Pixel” algorithm, Principal Component Analysis (PCA) method, and even its widely used variants – two dimensional PCA (2DPCA) method and two dimensional Euler PCA (2D-EPCA) method.
Generation of Chirped Femtosecond Pulses Near 977 nm Using a Mode-Locked All-Fiber Laser

A cladding-pumped all-fiber chirped femtosecond pulse Yb-doped mode-locked laser operating near 977 nm was demonstrated for the first time. Nonlinear polarization evolution was used as the mode-locking mechanism. The laser was self-starting and extremely stable (the stability of the repetition rate of 41.6 MHz was better than that of 15 Hz). Amplification near 977 nm was achieved using a specially designed cladding-pumped Yb-doped fiber. The main feature of the current laser design was its increased intracavity nonlinearity, which resulted in a strong self-phase modulation and significant widening of the generated pulse spectrum. This nonlinearity allowed us to generate pulses compressible down to a duration of 230 fs using an external diffraction grating compressor.
Ultra-Wideband Modulation Signal Measurement Using Local Sweep Digitizing Method

Recently, bandwidth for wireless communications are getting wider, i.e. 400 MHz for the 5th generation mobile communication (5G), and about 2 GHz for wireless LAN (IEEE 802.11ad). To evaluate the transceiver devices used in these communications, a high-speed waveform digitizer is required. In this paper, the "Local Sweep Digitizing Method" which accurately captures ultra-wideband signals covering 2 GHz with low cost is introduced. It is a method of decomposing a wideband signal transmitted at a high frequency into subband signals of several hundred megahertz bandwidths while downconverting it to an intermediate frequency, and capturing it for each subband signal by a low speed waveform digitizer. The captured waveform is synthesized by post digital processing. At this time, a correction process for matching the carrier phase and the conversion gain of each subband signal is performed. In this method, an ultra-wideband signal can be captured by a single low-speed high-resolution analog-to-digital converter (ADC) and the measurable bandwidth can be easily controlled by adjusting the Local Sweep section.