Miracle-dz/UniFAR-FTUs huggingface dataset:
Frequency-Hopping Signal Network-Station Sorting Based on Maxout Network Model and Generative Method

Automatic frequency-hopping (FH) signal network-station sorting is one of the most difficult and import problems in the field of electronic warfare, especially in a complex electromagnetic environment. In this paper, an automatic and reliable network-station sorting method of FH signal with maxout network feature extraction and generative-based classification method is proposed. Experiments on real FH data sets demonstrate that the proposed method not only outperforms the competitive feature extraction methods with a higher accuracy of FH signal network-station sorting but also has a better robustness against noise, especially Gaussian noise.
Validation of the ICH score in patients with spontaneous intracerebral haemorrhage admitted to the intensive care unit in Southern Spain

Objective Validation of the intracerebral haemorrhage (ICH) score in patients with a diagnosis of spontaneous ICH admitted to the intensive care unit (ICU). Methods A multicentre cohort study was conducted in all consecutive patients with ICH admitted to the ICUs of three hospitals with a neurosurgery department between 2009 and 2012 in Andalusia, Spain. Data collected included ICH, Glasgow Coma Scale (GCS) and Acute Physiology and Chronic Health Evaluation II (APACHE-II) scores. Demographic data, location and volume of haematoma and 30-day mortality rate were also collated. Results A total of 336 patients were included. 105 of whom underwent surgery. Median (IQR) age: 62 (50–70) years. APACHE-II: 21(15–26) points, GCS: 7 (4–11) points, ICH score: 2 (2–3) points. 11.1% presented with bilateral mydriasis on admission (mortality rate=100%). Intraventricular haemorrhage was observed in 58.9% of patients. In-hospital mortality was 54.17% while the APACHE-II predicted mortality was 57.22% with a standardised mortality ratio (SMR) of 0.95 (95% CI 0.81 to 1.09) and a Hosmer-Lemenshow test value (H) of 3.62 (no significant statistical difference, n.s.). 30-day mortality was 52.38% compared with the ICH score predicted mortality of 48.79%, SMR: 1.07 (95% CI 0.91 to 1.23), n.s. Mortality was higher than predicted at the lowest scores and lower than predicted in the more severe patients, (H=55.89, p<0.001), Gruppo Italiano per la Valutazione degli Interventi in Terapia Intensiva calibration belt (p<0.001). The area under a receiver operating characteristic (ROC) curve was 0.74 (95% CI 0.69 to 0.79). Conclusions ICH score shows an acceptable discrimination as a tool to predict mortality rates in patients with spontaneous ICH admitted to the ICU, but its calibration is suboptimal.
Securing Data Through Steganography and Secret Sharing Schemes: Trapping and Misleading Potential Attackers

Data hiding is the process of concealing recognizable digital data by converting it into indiscernible forms, i.e., those that are imperceptible to the human eye, and it uses numerous techniques to accomplish this task. In this article, we propose a new data-hiding technique that uses the concept of steganography and secret image-sharing schemes. The encryption and decryption is carried out at two levels: at the first level, the encryption process is done using steganography; it is then followed by a secret-sharing scheme at the second level. The decryption process is the opposite of the encryption process; accordingly, we use secret sharing at the first level and steganography in the second level. In the encryption process, n + 1 shared images are generated using n cover images and a secret image. By performing the decryption algorithm on these n + 1 shared images, we get n recovered images and one stego image. The proposed scheme is similar to a secret-sharing scheme because it deceives the attacker by producing pseudo images. In addition to deceiving the a t tacker, it also provides an additional advantage to the user by capturing the attacker. The attacker considers n recovered images to be output and follows his/her wrong intuition. The experimental results demonstrate that the proposed scheme is secure at both levels and altering any of the n shares will not reveal even a portion of secret information. To check the effectiveness of the proposed scheme, which works efficiently for grayscale and color images, correlation, mean-square error (MSE), and peak signal-to-noise ratio (PSNR) techniques were used.
ROLE OF ICT IN KNOWLEDGE MANAGEMENT IN ORGANISATIONS

Knowledge has been lately recognized as one of the most important assets of organisations. The past two decades have seen growing interest in knowledge management and the use of information technologies. However, it is not clear how the relation between IT competency and knowledge management works. This study provides a better understanding of that relation. IT competency has a direct effect on the processes of knowledge management: knowledge generation, knowledge transfer, and knowledge codification and storage. At the same time, IT competency also has an indirect effect on knowledge management by facilitating the development of organisational structures that favour the development and expansion of
Discovery and Visualization of New Information from Clinical Reports in the EHR - Final Report

Principal Investigator and Team Members: Genevieve Melton-Meaux, MD, PhD, Principal Investigator Terrence Adam, RPh, PhD, MD, Co-Investigator Kathleen Harder, PhD, Co-Investigator Bryan Jarabek, MD, PhD, Co-Investigator Michael Kim, MD, Co-Investigator Jenna Marquard, MS, PhD, Co-Investigator Serguei Pakhomov, PhD, Co-Investigator Rubina Rizvi, PhD, MBBS, MS, Co-Investigator Rui Zhang, MS, PhD, Co-Investigator Pamela Mink, PhD, Co-Investigator Tamara Winden, PhD, MBA Lindsay Bork, MBA Jed Elison Greg Finley, PhD Robert Giaquinto Gretchen Hultman, MPH Elizabeth Lindemann Reed McEwan, MS Jeff Rogers Gopal Sarda, MS Deyu Sun, PhD Mike Timm Yan Wang, MS, PhD
Mobile Demand Forecasting via Deep Graph-Sequence Spatiotemporal Modeling in Cellular Networks

The demand forecasting plays a crucial role in the predictive physical and virtualized network management in cellular networks, which can effectively reduce both the capital and operational expenditures by fully exploiting the network infrastructure. In this paper, we study the per-cell demand forecasting in cellular networks. The success of demand forecasting relies on the effective modeling of both the spatial and temporal aspects of the per-cell demand time series. However, the main challenge of the spatial relevancy modeling in the per-cell demand forecasting is the irregular spatial distribution of cells in a network, where applying grid-based models (e.g., convolutional neural networks) would lead to degradation of spatial granularity. In this paper, we propose to model the spatial relevancy among cells by a dependency graph based on spatial distances among cells without the loss of spatial granularity. Such spatial distance-based graph modeling is confirmed by the spatiotemporal analysis via semivariogram, which suggests that the relevancy between any two cells declines as their spatial distance increases. Hence, the graph convolutional networks and long short-term memory (LSTM) from deep learning are employed to model the spatial and temporal aspects, respectively. In addition, the deep graph-sequence model, graph convolutional LSTM, is further employed to simultaneously characterize both the spatial and temporal aspects of mobile demand forecasting. Experiments demonstrate that our proposed graph-sequence demand forecasting model could achieve a superior forecasting performance compared with the other two proposed models as well as the traditional auto regression integrated moving average time series model.
Chapter 1 Introduction to Finite Frame Theory

To date, frames have established themselves as a standard notion in applied mathematics, computer science, and engineering as a means to derive redundant, yet stable decompositions of a signal for analysis or transmission, while also promoting sparse expansions. The reconstruction procedure is then based on one of the associated dual frames, which—in the case of a Parseval frame—can be chosen to be the frame itself. In this chapter, we provide a comprehensive review of the basics of finite frame theory upon which the subsequent chapters are based. After recalling some background information on Hilbert space theory and operator theory, we introduce the notion of a frame along with some crucial properties and construction procedures. Then we discuss algorithmic aspects such as basic reconstruction algorithms and present brief introductions to diverse applications and extensions of frames. The subsequent chapters of this book will then extend key topics in many intriguing directions.
Copepod ectoparasites of Labeo rohita from Dera Ismail Khan , Khyber Pakhtunkhwa Pakistan

In the present study two hundred rohu (Labeo rohita) form Dera Ismail Khan, Khyber Pakhtunkhwa were examined for ecto parasites, the copepod ectoparasites found were Lernaea cyprinacea, L. arcuata, L. lophiara. Out of 200 fish, 37 were infested (18.5%). In which the predominant parasite was Lernaea cyprinacea. An overall prevalence of ectoparasites was Lernaea. cyprinacea (18.01%), L. arcuata (15.5%). L. lophiara (10.51). Lernaea. Cyprinacea is the most abundant ectoparasite in the overall study.
A Learning Framework for Tool Creation by a Robot

The ability to use tools is one of the features of human intelligence. When the available tools are not suitable, humans can modify the existing tools, or even create new ones. It is also useful for robots to learn to use and create tools so that they can accomplish more complex tasks. Some work in tool use learning by a robot has been done, however, to the best of our knowledge, no previous work addresses tool creation. In this paper, we elaborate this problem and propose a relational learning framework that has the potential to solve this problem. Some promising results are described from preliminary experiments on simple tool use learning and generation of novel tools by a real robot.
A METHODICAL APPROACH FOR DYNAMIC SYSTEM ANALYSIS & SYNTHESIS IN THE DIMENSIONING OF VARIANT LIGHTWEIGHT CABIN INTERIOR Dipl

To obtain valid simulation parameters for simulation based lightweight optimization of cabin interior, various system identification tests have been performed with specimens ranging from sandwich panels to fully loaded galleys. Furthermore, a methodical approach using dynamic substructuring algorithms was developed to support simulation based vibration behaviour prediction of a modular product structure and improve the dimensioning for highly variant lightweight structures.
A Hardware and Secure Pseudorandom Generator for Constrained Devices

Hardware security for an Internet of Things or cyber physical system drives the need for ubiquitous cryptography to different sensing infrastructures in these fields. In particular, generating strong cryptographic keys on such resource-constrained device depends on a lightweight and cryptographically secure random number generator. In this research work, we have introduced a new hardware chaos-based pseudorandom number generator, which is mainly based on the deletion of an Hamilton cycle within the <inline-formula><tex-math notation="LaTeX">$N$</tex-math></inline-formula> -cube (or on the vectorial negation), plus one single permutation. We have rigorously proven the chaotic behavior and cryptographically secure property of the whole proposal: the mid-term effects of a slight modification of the seed (proven to be sensitive to the initial conditions) or of the inputted generator cannot be predicted. The proposal has been fully deployed on a FPGA and 65 <inline-formula><tex-math notation="LaTeX">$\text{nm}$</tex-math> </inline-formula> ASIC, it runs completely in parallel while consuming as low resources as possible, and achieving: (a) 11.5 Gb/s for FPGA and 9.4 Gb/s for ASIC random bit throughput, (b) <inline-formula><tex-math notation="LaTeX"> $3.3\,\mu \text{W}$</tex-math></inline-formula> (LF) to <inline-formula><tex-math notation="LaTeX">$7.8 \,\text{mW}$ </tex-math></inline-formula> (UHF) total power consumption with <inline-formula><tex-math notation="LaTeX">$5\%$ </tex-math></inline-formula> leakage power, measured at <inline-formula><tex-math notation="LaTeX">$1.32\,\text{V}$ </tex-math></inline-formula>, and (c) able to successfully pass the statistical tests of NIST and TestU01 (BigCrush).
A Novel Very Low Voltage Topology to implement MCML XOR Gates

A new very low-voltage topology to implement MOS current mode logic (MCML) XOR gates is proposed in this paper. Instead of stacking several level oftransistors to implement a two inputs XOR gate, a p-type differential pair is used to steer the current in n-type differential pairs through current mirrors. The proposed topology allows to reduce the minimum supply voltage of MCML XOR gates while guaranteeing a fully current mode behavior as in the conventional XOR gate. The proposed topology has been compared against the conventional and triple tail MCML XOR gates. Simulation results referring to a $40\mathrm {n}\mathrm {m}$ CMOS technology for $V_{DD}=1\mathrm {V}$ confirm that the XOR gate presented in this work exhibits a lower propagation delay than the previously published low voltage MCML XOR gate. Furthermore both theoretical analysis and simulation results in a $40\mathrm {n}\mathrm {m}$ process show that the proposed topology is able to work with a VDD as low as $0. ~65\mathrm {V}$ whereas state of the art topologies are not usable below $0. ~8\mathrm {V}. $
Experimental Characterization of Long Term Evolution Multiple Input Multiple Output Performance in Urban Propagation Scenarios

Wireless sensor and actuator networks are gaining momentum in the era of Industrial Internet of Things IIoT. The usage of the close-loop data from sensors in the manufacturing chain is extending the common monitoring scenario of the Wireless Sensors Networks WSN where data were just logged. In this paper we present an accurate timing synchronization for TDMA implemented on the state of art IoT radio, such as LoRa, that is a good solution in industrial environments for its high robustness. Experimental results show how it is possible to modulate the drift correction and keep the synchronization error within the requirements.
Histone Deacetylase Inhibitor Suberanilohydroxamic Acid Treatment Reverses Hyposensitivity to γ‐Aminobutyric Acid in the Ventral Tegmental Area During Ethanol Withdrawal

Background The ventral tegmental area (VTA) is important for alcohol‐related reward and reinforcement. Mouse VTA neurons are hyposensitive to γ‐aminobutyric acid (GABA) during ethanol (EtOH) withdrawal, and GABA responsiveness is normalized by in vitro treatment with histone deacetylase inhibitors (HDACi). The present study examined the effect of a systemically administered HDACi, suberanilohydroxamic acid (SAHA) on GABA sensitivity, and related molecular changes in VTA neurons during withdrawal after chronic EtOH intake in rats. Methods Sprague Dawley male adult rats were fed with Lieber‐DeCarli diet (9% EtOH or control diet) for 16 days. Experimental groups included control diet‐fed and EtOH diet‐fed (0‐ or 24‐hour withdrawal) rats treated with either SAHA or vehicle injection. Single‐unit recordings were used to measure the response of VTA neurons to GABA. Immunohistochemistry was performed to examine levels of HDAC2, acetylated histone H3 lysine 9 (acH3K9), and GABAA receptor α1 and α5 subunits in the VTA; quantitative polymerase chain reaction was performed to examine the mRNA levels of HDAC2 and GABAA receptor subunits. Results VTA neurons from the withdrawal group exhibited GABA hyposensitivity. In vivo SAHA treatment 2 hours before sacrifice normalized the sensitivity of VTA neurons to GABA. EtOH withdrawal was associated with increased HDAC2 and decreased acH3K9 protein levels; SAHA treatment normalized acH3K9 levels. Interestingly, no significant change was observed in the mRNA levels of HDAC2. The mRNA levels, but not protein levels, of GABAA receptor α1 and α5 subunits were increased during withdrawal. Conclusions Withdrawal from chronic EtOH exposure results in a decrease in GABA‐mediated inhibition, and this GABA hyposensitivity is normalized by in vivo SAHA treatment. Disruption of signaling in the VTA produced by alteration of GABA neurotransmission could be 1 neuroadaptive physiological process leading to craving and relapse. These results suggest that HDACi pharmacotherapy with agents like SAHA might be an effective treatment for alcoholism.
Parallel implementation of the Ramalingam decremental algorithm for dynamic updating the single-sink shortest paths subgraph

We propose an efficient parallel implementation of the Ramalingam algorithm for dynamic updating the single-sink shortest paths subgraph of a directed weighted graph after deletion of an edge on a model of associative (content addressable) parallel systems with vertical processing (the STAR-machine). The associative version of the Ramalingam decremental algorithm for updating the shortest paths subgraph is given as procedure DeleteEdge, whose correctness is proved and the time complexity is evaluated. We compare implementations of the Ramalingam decremental algorithm and its associative version and present the main advantages of the associative version.
Correction: Wdr62 is involved in female meiotic initiation via activating JNK signaling and associated with POI in humans

Meiosis is a germ cell-specific division that is indispensable for the generation of haploid gametes. However, the regulatory mechanisms of meiotic initiation remain elusive. Here, we report that the Wdr62 (WD40-repeat protein 62) is involved in meiotic initiation as a permissive factor rather than an instructive factor. Knock-out of this gene in a mouse model resulted in female meiotic initiation defects. Further studies demonstrated that Wdr62 is required for RA-induced Stra8 expression via the activation of JNK signaling, and the defects in meiotic initiation from Wdr62-deficient female mice could be partially rescued by JNK1 overexpression in germ cells. More importantly, two novel mutations of the WDR62 gene were detected in patients with premature ovarian insufficiency (POI), and these mutations played dominant-negative roles in regulating Stra8 expression. Hence, this study revealed that Wdr62 is involved in female meiotic initiation via activating JNK signaling, which displays a novel mechanism for regulating meiotic initiation, and mutation of WDR62 is one of the potential etiologies of POI in humans.
Detailed Assessment of the Spatial Distribution of Urban Parks According to Day and Travel Mode Based on Web Mapping API: A Case Study of Main Parks in Wuhan

This article employs two indexes—accessibility and effective service ratio (ESR)—to assess the spatial distribution of urban parks with the consideration of both equity and efficiency. Traditional approaches to calculate these two indexes are often based on the shortest distance to the park within its service radius by network analysis. Such approaches cannot reflect the actual travel behaviors of urban residents and require extensive data collection of road networks and complex parameter setting. To avoid these defects, this study directly acquires travel time data for various travel modes in a specific time period to the park through web mapping API (Application Program Interface), then calculates the accessibility and ESR of urban parks based on these detailed data. This method gets closer to actual park usage situation and avoids the cumbersome process of road network model building. At last, a case study is conducted on the assessment of spatial distribution of main parks in Wuhan, finding that districts with poor park accessibility in Wuhan can be divided into three types: districts with an absence of parks, districts with an insufficiency with parks, and districts separated from parks by traffic. Then, pertinent improvement suggestions are proposed, which provide some bases for decisions on future park planning and construction.
Numerical Techniques ( others ) : Paper ICA 2016-371 Room acoustics design using SWARM optimization method

This work presents an acoustic inverse problem, where the absorption coefficients are obtained from the Impulse Response (IR) and from the knowledge of the room geometry, source and receive locations. The parameter extraction is achieved by the particle swarm optimization (PSO) method, where a given impulse response – measured in a real room or with some desired characteristics – is compared with simulated ones. The IR simulation is performed by an improved ray-tracing method, which clusters the first reflections. Several issues are addressed in the paper, such as the reflection order influence and the multiple solutions according to the objective function. The paper describes how to combine the Ray-tracing and the Swarm methods in order to extract the absorption coefficients. It is also presented the optimization algorithm performance for several objective functions, such as impulse response, decay curves, magnitude spectrum and other error criteria. The converge rate and final parameter error are also investigated in order to present the applicability of the proposed method and to define the most apropriate objetive function to solve the inverse problem.
SOME NEW RECORDS OF LICHENS FROM HUNZA VALLEY , PAKISTAN

There is a vast diversity of lichens in forests of Pakistan due to rich vegetation and suitable environmental conditions for their growth. During exploration of lichens of Hunza valley in Gilgit Baltistan, we found four species viz., Punctelia subrudecta, Punctelia borreri, Peltigera elisabethae and Xanthoria sogdiana, which are new records for Pakistan. Their molecular characterization is based on internal transcribed region of nuclear ribosome. Complete morphological descriptions along with phylogenetic analyses are also discussed in this work.
Learning optimal lighting patterns for efficient SVBRDF acquisition

Digitally acquiring high-quality material appearance from the real-world is challenging, with applications in visual effects, e-commerce and entertainment. One popular class of existing work is based on hand-derived illumination multiplexing [Ghosh et al. 2009], using hundreds of patterns in the most general case [Chen et al. 2014].