Miracle-dz/UniFAR-FTUs huggingface dataset:
Deep Neural Network-based Joint Active User Detection and Channel Estimation for mMTC

As a means to support the access of massive machine-type communication devices, grant-free access and nonorthogonal multiple access (NOMA) have received a lot of attention recently. In the grant-free environment, each device transmits information without scheduling. Hence, the device identification process called active user detection (AUD) is indispensable at the base station. After the AUD process, the channel estimation for active devices is performed in the base station before detecting the data. These processes are challenging problems in the NOMAbased systems since it is difficult to detect the active devices and estimate the channel of those devices from the superimposed received signal. In this paper, we propose a deep neural network (DNN)-based joint AUD and CE scheme for the practical mMTC systems. Specifically, the proposed scheme consists of long short term memory (LSTM)-based AUD (L-AUD) and DNN-based CE (D-CE). In L-AUD, by feeding the training data in the designed network, the proposed LSTM network is trained to exploit the extracted features when mapping the received NOMA signal to the indices of active devices. After the AUD process, by using the deeply stacked hidden layers, D-CE extracts the channel features and the codebook features of the active devices to map the received NOMA signal to the corresponding channel. As a result, the trained DNN can jointly handle the whole AUD and CE processes, achieving an accurate detection of the active devices and the small channel estimation error.
Kidney transplantation: an attractive and cost-effective alternative for older patients? A cost–utility study

Abstract Background In the elderly, kidney transplantation is associated with increased survival and improved health-related quality of life compared with dialysis treatment. We aimed to study the short-term health economic effects of transplantation in a population of elderly kidney transplant candidates. Methods Self-perceived health, quality-adjusted life years (QALYs) and costs were evaluated and compared 1 year before and 1 year after kidney transplantation in patients included in a single-centre prospective study of 289 transplant candidates ≥65 years of age. Results Self-perceived health and QALYs both significantly improved after transplantation. At 1 year, the costs per QALY were substantially higher for transplantation (€88 100 versus €76 495), but preliminary analyses suggest a favourable long-term health economic effect. Conclusions Kidney transplantation in older kidney transplant recipients is associated with improved health but also with increased costs the first year after engraftment when compared with remaining on the waiting list. Any long-term cost-effectiveness needs to be confirmed in studies with longer observation times.
Prescribed–time stabilization of the linearized Schrödinger equation

We study the stabilization of the linearized Schrödinger equation within a prescribed terminal time. We make use of time–varying boundary feedback to obtain the desired stabilization, where the stabilization time is prescribed independently of the initial condition. The complex–valued feedback gain used herein is developed by selecting a target equation with time–varying damping that stabilizes to zero at the terminal time. We utilize an invertible backstepping transformation to infer the plant’s stabilization from the target equation stability, leading to boundary feedback actuation. The ensuing time–varying feedback gain diverges as time approaches the terminal time. Nevertheless, we can guarantee boundedness of the control law by characterizing the growth–in–time of the feedback gain and comparing it to the stability of the target equation. Furthermore, this boundary actuation results in the prescribed–time stabilization of the plant. Due to a connection between the linearized Schrödinger equation and flat plate theory, we also generate prescribed–time stabilizing boundary feedback for the Euler–Bernoulli beam equation to a constant profile.
Optimization of base catalyzed transesterification of peanut oil biodiesel

This paper is confined to the production and physico-chemical characterization of peanut oil biodiesel (POB). An optimum conversion of POB from triglycerides (TD) was achieved by using 1:6 molar ratio (methanol : oil) at 60oC. Fuel properties of POB were determined and compared with ASTM (American Standard Testing Material). The kinemetic viscosity at 40oC (eta) of POB (100%) was 5.908, specific gravity 0.918, density at 40oC (Rho) 0.0992, flash point (FP) 192, pour point (PP) 3oC, cloud point (CP) 6oC, and sulfur contents 0.0087. The engine performance by using POB in terms of consumption, efficiency and power output was quite comparable with petro-diesel (PD). It is concluded that most important factors affecting the fatty acid methyl esters (FAME) yield during transesterification are molar ratio of methanol to oil and reaction temperature.
Simultaneous Transmitting and Air Computing for High-Speed Point-to-Point Wireless Communication

The development of the fifth-generation (5G) cellular technologies promotes the rapid deployment of the Internet of Things (IoT), where low latency is highly demanded for wireless devices with small size and limited resources. For the intensive computation tasks, how to reduce the latency is still a challenging issue along with the boosting of IoT devices. To reduce the latency, in this paper we consider high-speed point-to-point wireless communications, e.g., orbital-angular-momentum (OAM) based wireless communications, and develop a practical scheme with the computation executed during transmissions. Specifically, we design a new weighted function for the data-stream transmitted on each OAM-mode to achieve the simultaneous transmitting and air computing (STAC). Then, we propose the STAC signal detection scheme to directly obtain the computation result without individually processing each transmitted data-stream. Theoretical analyses show that the computation latency can be efficiently decreased. Also, the symbol error rate (SER) is significantly reduced with our proposed scheme, which helps decrease the number of re-transmissions and the corresponding time used for communications. Simulation and numerical results verify the performance improvements with the proposed scheme.
sEMG-Based Human-in-the-Loop Control of Elbow Assistive Robots for Physical Tasks and Muscle Strength Training

In this letter we present a sEMG-driven human-in-the-loop (HITL) control designed to allow an assistive robot produce proper support forces for both muscular effort compensations, i.e. for assistance in physical tasks, and muscular effort generations, i.e. for the application in muscle strength training exercises related to the elbow joint. By employing our control strategy based on a Double Threshold Strategy (DTS) with a standard PID regulator, we report that our approach can be successfully used to achieve a target, quantifiable muscle activity assistance. In this relation, an experimental concept validation was carried out involving four healthy subjects in physical and muscle strength training tasks, reporting with single-subject and global results that the proposed sEMG-driven control strategy was able to successfully limit the elbow muscular activity to an arbitrary level for effort compensation objectives, and to impose a lower bound to the sEMG signals during effort generation goals. Also, a subjective qualitative evaluation of the robotic assistance was carried out by means of a questionnaire. The obtained results open future possibilities for a simplified usage of the sEMG measurements to obtain a target, quantitatively defined, robot assistance for human joints and muscles.
Provisioning habitat with custom-designed nest-boxes increases reproductive success in an endangered finch

Manipulating resource availability to assess the strength and effects of resource limitation on an animal population is relatively straightforward, and thus, common in the scientific literature. Resource quality, however, is rarely manipulated, as this requires a priori knowledge of a relationship between some measurable variation in the resource and individual preference and/or fitness. Recent research on nest-site selection was used to inform the design of custom-built nest-boxes for an endangered hollow-nester, the Gouldian finch (Erythrura gouldiae). By provisioning breeding populations with these ‘high quality’ artificial nest sites over 3 years, we experimentally investigated the strength and effects of nest-site limitation in this species. Breeding pairs using nest-boxes initiated nesting earlier, produced larger clutches and fledged more offspring per season than those in natural hollows. Total and mean reproductive output also increased in nest-box provisioned sites over the duration of the study. All of these effects were predominantly driven by pairs initiating clutches earlier, potentially because of the reduced intra- and interspecific competition for nest sites at optimal breeding times. Our findings suggest that reproduction in wild Gouldian finch populations may be limited by the availability of high quality nest sites in the landscape, and that nest-boxes could be used as a tool for enhancing reproduction in recovering populations. Furthermore, we conclude that resource quality is equally, if not more important than quantity when supplementing resource-limited habitats.
On the Performance of Irregular Repetition Slotted Aloha with Multiple Packet Reception

A modern method of random access for packet networks, named “Irregular Repetition Slotted Aloha (IRSA)”, had been proposed: it is based repeating transmitted packets, and on the use of successive interference cancellation at the receiver. In classical idealized settings of slotted random access protocols (where slotted ALOHA achieves 1/e), it has been shown that IRSA could asymptotically achieve the maximal throughput of 1 packet per slot. Additionally, IRSA had previously been studied for many different variants and settings, including the case where the receiver is equipped with “multiple-packet reception” (MPR) capability. In this article, we extensively revisit the case of IRSA with MPR. First, one of our major results is the proof that K-IRSA cannot reach the natural bound of throughput, and we prove a new, lower bound for its performance. Second, we give a simple expression for its excellent loss rate at lower loads. Third, we show how to formulate the search for the appropriate parameters of IRSA as an optimization problem, and how to solve it efficiently. By doing that for a comprehensive set of parameters, and by providing this work with simulations, we give numerical results that shed light on the performance of IRSA with MPR.
Deep Reinforcement Learning for Trajectory Design and Power Allocation in UAV Networks

Unmanned aerial vehicle (UAV) is considered to be a key component in the next-generation cellular networks. Considering the non-convex characteristic of the trajectory design and power allocation problem, it is difficult to obtain the optimal joint strategy in UAV-assisted cellular networks. In this paper, a reinforcement learning-based approach is proposed to obtain the maximum long-term network utility while meeting with user equipments’ quality of service requirement. The Markov decision process (MDP) is formulated with the design of state, action space, and reward function. In order to achieve the joint optimal policy of trajectory design and power allocation, deep reinforcement learning approach is investigated. Due to the continuous action space of the MDP model, deep deterministic policy gradient approach is presented. Simulation results show that the proposed algorithm outperforms other approaches on overall network utility performance with higher system capacity and faster processing speed.
Optimal Randomized Complete Visibility on a Grid for Asynchronous Robots with Lights

We consider the distributed setting of N autonomous mobile robots that operate in Look-Compute-Move (LCM) cycles and communicate with other robots using colored lights (the robots with lights model). This model assumes obstructed visibility where a robot cannot see another robot if a third robot is positioned between them on the straight line connecting them. In this paper, we consider robot movements to be on a grid (integer plane) of unbounded size. In any given step a robot positioned at a grid point can move only to an adjacent grid point to its north, south, east or west. The grid setting naturally discretizes the 2-dimensional Euclidean plane and finds applications in many real-life robotic systems. The COMPLETE VISIBILITY problem is to reposition N autonomous robots (starting at arbitrary, but distinct, initial positions) so that, on termination, each robot is visible to all others. The objective in this problem is to simultaneously minimize (or provide trade-off between) two fundamental performance metrics: (i) Time to solve COMPLETE VISIBILITY and (ii) Area occupied by the solution. We also consider the number of distinct colors used by each robot light. We provide the first $\mathcal{O}(\max\{D,\ N\})$-time algorithm for COMPLETE VISIBILITY in the asynchronous setting, where D is the diameter of the initial configuration. The area occupied by the final configuration is $\mathcal{O}(N^{2})$; both the time and area are optimal. The time is randomized if no symmetry breaking mechanism is available for the robots. The number of colors used in our algorithm depends on whether leader election is required or not: (i) 17 colors if leader election is not required and (ii) 50 colors if leader election is required.
Hybrid Source Prior Based Independent Vector Analysis for Blind Separation of Speech Signals

Blind Source Separation (BSS) application is a delinquent issue in a complex reverberant environment with changing room geometric dimensions and an increasing number of speech sources. The BSS application issue is determined by the independent component analysis that usually manipulates higher-order statistical approaches. However, the permutation between desired speech sources remains a challenging issue for BSS applications. The permutation problem is been rectified by Independent Vector Analysis (IVA) for BSS applications in the frequency domain. The performance dependency of the IVA approach solely relies on the selection of appropriate source-prior to preserve the inter-frequency dependencies between the same speech source amongst different frequency bins. Therefore, a hybrid model for the IVA method is presented, which comprises of multivariate generalized Gaussian and super-Gaussian distribution source priors to model low as well as high amplitudes speech signals. The weights of the hybrid model between multivariate Gaussian and generalized Gaussian are assigned in accordance to the energy of the observed non-stationary speech mixture signal. In the simulations, different speech mixtures are generated from various speech sources by simulated room model. The proposed approach evaluates the blind separation performance in terms of signal-to-distortion ratio (SDR) and is compared with well-known BSS methods. The results show an improvement of the proposed methodology for non-stationary speech signals over the state-of-the-art IVA models having a fixed source prior.
Restructuring the Ancorabolidae Sars (Copepoda, Harpacticoida) and Cletodidae T. Scott, with a new phylogenetic hypothesis regarding the relationships of the Laophontoidea T. Scott, Ancorabolidae and Cletodidae

Uncovering the systematics of Copepoda Harpacticoida, the second-most abundant component of the meiobenthos after Nematoda, is of major importance for any further research dedicated especially to ecological and biogeographical approaches. Based on the evolution of the podogennontan first swimming leg, a new phylogenetic concept of the Ancorabolidae Sars and Cletodidae T. Scott sensu Por (Copepoda, Harpacticoida) is presented, using morphological characteristics. It confirms the polyphyletic status of the Ancorabolidae and its subfamily Ancorabolinae Sars and the paraphyletic status of the subfamily Laophontodinae Lang. Moreover, it clarifies the phylogenetic relationships of the so far assigned members of the family. An exhaustive phylogenetic analysis was undertaken using 150 morphological characters, resulting in the establishment of a now well-justified monophylum Ancorabolidae. In that context, the Ancorabolus-lineage sensu Conroy-Dalton and Huys is elevated to sub-family rank. Furthermore, the membership of Ancorabolina George in a rearranged monophylum Laophontodinae is confirmed. Conversely, the Ceratonotus-group sensu Conroy-Dalton is transferred from the hitherto Ancorabolinae to the Cletodidae. Within these, the Ceratonotus-group and its hypothesised sister-group Cletodes Brady are combined to form a monophyletic subfamily Cletodinae T. Scott, subfam. nov. Consequently, it was necessary to restructure the Ancorabolidae, Ancorabolinae and Laophontodinae and extend the Cletodidae to include the displacement and exclusion of certain taxa. Moreover, comparison of the Ancorabolidae, Cletodidae, Laophontoidea and other Podogennonta shows that the Ancorabolidae and Cletodidae form sister-groups in a monophylum Cletodoidea Bowman and Abele, which similarly has a sister-group-relationship with the Laophontoidea T. Scott. According to the present study, both taxa constitute a derived monophylum within the Podogennonta Lang.
POLISH JOURNAL OF NATURAL SCIENCES

The snakehead (Channa striata) in Sungai Batang River, Indonesia has high commercial value and high pressure on population caused by fishing. Meanwhile, scientific information on morphometric characteristic of snakehead is still lacking. Samples of 330 fishes having size range of 75–335 mm (202.68 ± 46.56 mm) total length (TL) and 9–288 g (81.23 ± 53.95 g) weight were taken to estimate length-weight relationship and condition factors. The snakehead grew allometrically (b = 2.6927–2.9125), indicating that fish becomes slender as the length increases. Total length and weight of female were significantly higher than male (P < 0.001). The highest number of catch was found between 160 and 179 mm TL (24.44%) for male and between 260 and 279 mm TL (16.00%) for female. The heaviest catches of male (33.89%) and female (14.00%) were noted between 30 and 49 g weight class. The mean condition factor (K) value of female was considerably higher than that of male (P < 0.001). The mean K values obtained for male and female were 0.83 ± 0.09 and 0.86 ± 0.08, indicating that the fish in the river was unfavorable condition. To the best our knowledge, this study is the first reference on length-weight and condition factor for snakehead from this river. Address: Ahmadi Ahmadi, Lambung Mangkurat University in Banjarmasin, Jalan Jenderal Achmad Yani km 36 PO.BOX6, Banjarbaru 70714, Kalimantan Selatan, Indonesia, phone: +62 511 47 72 124, e-mail: ahmadi@unlam.ac. id
Using Channel State Information for Estimating Moisture Content in Woodchips via 5 GHz Wi-Fi *

For the pulping process in a pulp & paper plant that uses wood as a raw material, it is important to have real-time knowledge about the moisture content of the woodchips so that the process can be optimized and/or controlled correspondingly to achieve satisfactory product quality while minimizing the consumption of energy and chemicals. Both destructive and non-destructive methods have been developed for estimating moisture content in woodchips, but these methods are often lab-based that cannot be implemented online, or too fragile to stand the harsh manufacturing environment. To address these limitations, we propose a non-destructive and economic approach based on 5 GHz Wi-Fi and use channel state information (CSI) to estimate the moisture content in woodchips. In addition, we propose to use statistics pattern analysis (SPA) to extract features from raw CSI data of amplitude and phase difference. The extracted features are then used for classification model building using linear discriminant analysis (LDA) and subspace discriminant (SD) classification. The woodchip moisture classification results are validated using the oven drying method.
Analog IC Design Using Precomputed Lookup Tables: Challenges and Solutions

Design productivity remains an important aspect in the analog integrated circuit design industry, as growing competition and shorter design cycles pressure the traditional flow that involves time-consuming manual iterations in a circuit simulator. This paper describes innovations within an alternative framework that uses precomputed look-up tables (LUTs) to enable fast and accurate evaluation of circuit sizing scenarios without a simulator in the loop. It lets the designer explore and understand the design space boundaries in a systematic setting, thus supporting informed decision making and architectural innovation that is difficult to attain with fully automated, black-box sizing tools. Our discussion begins with an overview of the LUT-based design paradigm and its two primary variants: inverse design (finding design parameters that meet the specifications) and forward evaluation (sweeping design parameters to search the design space). In support of the latter, the core of our work focuses on improving the accuracy and speed of LUT access, enabling millions of queries within seconds on a standard computer. Large improvements over prior art are enabled using enhanced interpolation methods, which allow for a relatively large LUT grid spacing (hence small memory footprint) and yet accurate parameter lookup. We evaluate the efficacy of the proposed methods using two classical analog circuits, a bandgap reference and a folded cascode amplifier. In the bandgap example, we observe less than 1 ppm error between the LUT-predicted temperature coefficient and circuit simulation. In the folded-cascode example, one million design points are generated in only 4 seconds, providing the designer with useful maps that delineate the reachability of certain target specifications.