Miracle-dz/UniFAR-FTUs huggingface dataset:
Possibilities Of Extension Of The Algorithmization And Programming Teaching At Primary Schools

The teaching of algorithmization and programming is currently at the forefront of the interest of many professionals involved in the innovation of educational content within IT subjects. The view of the pupils as well as their acceptance of possible changes in the educational content towards a substantial extension of the teaching of algorithmization and programming, as envisaged in the Strategy of Digital Learning up to 2020, have also partially disappeared from this professional discussion. Although, of course, it is not only up to the pupils to determine the content and focus of the teaching, at the moment of preparation of the concept and content of the lesson thus designed, their views and preferences are among the unavoidable factors which can influence later results and benefits. For this reason, a research survey was conducted, using quantitative methods of exploration, focused on the issue of acceptance of possible changes in the educational content of IT subjects towards a substantial extension of the teaching of algorithmization and programming from the point of view of pupils of the 9th year of primary school. The research shows that algorithmization and programming are both attractive and interesting for the primary school pupils, the best known and most popular tool among the latter being Game Lab Code. © 2019 Published by Future Academy www.FutureAcademy. org.UK
On Negotiating Aggressive Quadrotor Attitude Tracking Maneuvers Under Actuator Constraints

The quadrotor task of negotiating aggressive attitude maneuvers while adhering to motor constraints is addressed here. The majority of high level quadrotor Nonlinear Control Systems (NCS) ignore motor control authority limitations, especially important during aggressive attitude maneuvers, generating unrealizable thrusts and negating the validity of the accompanying stability proofs. Here, an attitude control framework is developed, comprised by a thrust allocation strategy and a specially designed geometric attitude tracking controller, allowing the quadrotor to achieve aggressive attitude maneuvers, while complying to actuator constraints and simultaneously staying “close” to a desired position command in a computationally inexpensive way. This is a novel contribution resulting in thrusts realizable by available quadrotors during aggressive attitude maneuvers, and enhanced performance guaranteed by valid stability proofs. Also, it is shown that the developed controller can be combined with a collective thrust expression in producing a position/yaw tracking controller. Through rigorous stability proofs, both the position and attitude frameworks are shown to have desirable closed loop properties that are almost global. This establishes a quadrotor control solution allowing the vehicle to negotiate aggressive maneuvers position/attitude on SE(3). Simulations validate the effectiveness/capabilities of the developed solution.
Extreme physiological plasticity in a hibernating basoendothermic mammal, Tenrec ecaudatus

ABSTRACT Physiological plasticity allows organisms to respond to diverse conditions. However, can being too plastic actually be detrimental? Malagasy common tenrecs, Tenrec ecaudatus, have many plesiomorphic traits and may represent a basal placental mammal. We established a laboratory population of T. ecaudatus and found extreme plasticity in thermoregulation and metabolism, a novel hibernation form, variable annual timing, and remarkable growth and reproductive biology. For instance, tenrec body temperature (Tb) may approximate ambient temperature to as low as 12°C even when tenrecs are fully active. Conversely, tenrecs can hibernate with Tb of 28°C. During the active season, oxygen consumption may vary 25-fold with little or no change in Tb. During the austral winter, tenrecs are consistently torpid but the depth of torpor may vary. A righting assay revealed that Tb contributes to but does not dictate activity status. Homeostatic processes are not always linked, e.g. a hibernating tenrec experienced a ∼34% decrease in heart rate while maintaining constant body temperature and oxygen consumption rates. Tenrec growth rates vary but young may grow ∼40-fold in the 5 weeks until weaning and may possess indeterminate growth as adults. Despite all of this profound plasticity, tenrecs are surprisingly intolerant of extremes in ambient temperature (<8 or >34°C). We contend that while plasticity may confer numerous energetic advantages in consistently moderate environments, environmental extremes may have limited the success and distribution of plastic basal mammals. Highlighted Article: Common tenrecs, Tenrec ecaudatus, which may be representative of ancestral placental mammals, demonstrate extreme physiological plasticity.
Decentralized Dynamic Economic Dispatch for Integrated Transmission and Active Distribution Networks Using Multi-Parametric Programming

As large scale distributed energy resources are integrated into distribution networks, coordinated dynamic economic dispatch (DED) for integrated transmission and distribution networks is becoming essential. In this paper, we describe a transmission and distribution network coordinated DED model and propose an efficient decentralized method to solve this problem using multi-parametric quadratic programming. In the proposed method, only boundary variables are exchanged between transmission and distribution networks so that the privacy between different operators can be guaranteed. A revised procedure is developed based on the characteristics of the distribution network problem, which can significantly accelerate the iteration. An effective method for dealing with degeneracy in multi-parametric programming is also proposed. Numerical tests demonstrate that the proposed method can achieve a global optimal solution and that the coordinated DED method can provide additional economic benefits compared with the isolated economic dispatch method. Furthermore, the computational performance of the proposed method is far superior to some popular decentralized methods in terms of both iteration number and computation time.
Ferroelectric HfZrOx FETs on SOI Substrate With Reverse-DIBL (Drain-Induced Barrier Lowering) and NDR (Negative Differential Resistance)

Ferroelectric-Hf<sub>1−x</sub>Zr<sub>x</sub>O<sub>2</sub> FETs on silicon on insulator (SOI) are modeled and demonstrated with improvement on subthreshold swing (SS) and hysteresis (<inline-formula> <tex-math notation="LaTeX">$V_{T}$ </tex-math></inline-formula>-shift), which is based on the capacitance matching concept. The minimum reverse SS = 45 mV/dec and 52 mV/dec are obtained experimentally for SOI and bulk-Si, respectively. The steep SS range (<60 mV/dec) is extended from ~2.5 (bulk-Si) decades to ~3.5 decades SOI. Reverse-drain-induced barrier lowering and negative differential resistance are confirmed at subthreshold region and weak inversion region, respectively.
Motion Planning of Autonomous Personal Transporter using Model Predictive Control for Minimizing Non-minimum Phase Behavior

A novel autonomous personal transporter is introduced. When the autonomous personal transporter is in self-driving conditions, there is various disturbance acceleration for the person riding on it. This disturbance acceleration should be compensated for a safe drive. Motion planning methods using LQR and discrete model predictive control are suggested for a cart inverted pendulum model. When the cart inverted pendulum model is controlled using LQR, there is non-minimum phase behavior causing undesired undershoot response. For minimizing the non-minimum phase behavior, we suggest discrete model predictive control using pre-planned motion trajectory. For experiments, we developed an autonomous driving robot called a ball-plate mecanum robot. On the ball-plate mecanum robot, we put an iron ball with which it is possible to measure position using a resistive touch sensor. The ball is basically stabilized by PID control. However, the ball position is out of center when there is a disturbance. By measuring the position of the ball, we investigate how much the disturbance acceleration can be compensated for using motion planning methods. LQR motion planning and MPC motion planning are compared through simulations and experiments, and we consider which motion planning method is more suitable for the autonomous personal transporter.
MQTT-G: A Publish/Subscribe Protocol with Geolocation

Message Queue Transport Telemetry or MQTT is an open source publisher/subscriber standard for M2M (Machine to Machine) communication. This makes it highly suitable for Internet of Things (IoT) messaging situations where power usage is at a premium or in mobile devices such as phones, embedded computers or microcontrollers. In its original state, MQTT is lacking the ability to broadcast geolocation as part of the protocol. In today's age of IoT however, it has become more pertinent to have geolocation as part of the protocol. In this paper, we add geolocation to the MQTT protocol and offer a revised version, which we call MQTT-G. We describe the protocol here and show where we were able to embedd geolocation successfully.
Do Character-Level Neural Network Language Models Capture Knowledge of Multiword Expression Compositionality?

In this paper, we propose the first model for multiword expression (MWE) compositionality prediction based on character-level neural network language models. Experimental results on two kinds of MWEs (noun compounds and verb-particle constructions) and two languages (English and German) suggest that character-level neural network language models capture knowledge of multiword expression compositionality, in particular for English noun compounds and the particle component of English verb-particle constructions. In contrast to many other approaches to MWE compositionality prediction, this character-level approach does not require token-level identification of MWEs in a training corpus, and can potentially predict the compositionality of out-of-vocabulary MWEs.
Exact Outage Performance of Power Beacon Assisted Non-Orthogonal Multiple Access Networks

—The paper considers Non-Orthogonal Multiple Access (NOMA) together with Multiple Input Single Output (MISO) model in transmitting of proximity users under help of wireless power transfer. To support more harvested energy, a multiple-antenna Power Beacon (PB) is proposed to robust NOMA transmission network, especially enhanced successful communication with short distance transmission. Accordingly, the alternative energy source can be used to maintain small devices which can operate at close position efficiently. In this paper, a model of RF wireless energy transfer for NOMA system will be investigated. As an important result, we derive novel analytical expressions for outage probability to performance evaluation. This paper will analyze outage probability by matching Monte-Carlo and analytical simulations to corroborate the exactness of derived expressions.
Real life triplet FIr/FOx chemotherapy in first-line metastatic pancreatic ductal adenocarcinoma patients: recommended schedule for expected activity and safety and phase II study

Background Gemcitabine/nab-paclitaxel and FOLFIRINOX demonstrated significantly increased survival compared with gemcitabine in metastatic pancreatic ductal adenocarcinoma (PDAC): objective response rate (ORR) 23 and 31.6%, progression-free survival (PFS) 5.5 and 6.4 months, overall survival (OS) 8.7 and 11.1 months. Present phase II study evaluated recommended first-line triplet FIr/FOx schedule. Methods Simon two-step design: p010%, p130%, power 80%, α5%, β20%. Projected ORR: I step, 1/10; II 5/29. Schedule: 12h-timed-flat-infusion/5-fluorouracil 750-800-900 mg/m2 d1-2,8-9,15-16,22-23; irinotecan 120-140-160 mg/m2 d1,15; oxaliplatin 70-80 mg/m2 d8,22; every 4 weeks, according to clinical parameters (age, comorbidities, performance status (PS), liver function). Activity and efficacy were evaluated, and compared using log-rank; limiting toxicity syndromes (LTS), using chi-square. Results Twenty-nine consecutive patients were enrolled, according to primary/intermediate/secondary Cumulative Illness Rating Scale (CIRS). Median age 62; elderly 13 (44.7%); PS2 3 (10.4%), secondary CIRS 5 (17.2%). Primary endpoint was met: ORR 53% (7/13 patients) as-treated, 50% intent-to-treat. Cumulative G3-4 toxicities: diarrhea 17%, asthenia 14%, hypertransaminasemy 7%, mucositis 7%, vomiting 3%, anemia 3%, thrombocytopenia 3%. LTS were 27.5% overall, 38.4% in elderly. At 3 months median follow-up, PFS 4 months, OS 11 months. PS2 patients showed significantly worse OS (P 0.022). Conclusion Intensive first-line triplet FIr/FOx is tolerable at modulated doses, and confirms high activity/efficacy in metastatic PDAC. Patients’ careful selection, and exclusion of PS2, can maintain safety profile and efficient dose intensity.
Nonlinear torque control with online algebraic identification for power tracking in variable-speed wind turbines

In this work, a nonlinear torque control for power tracking in variable-speed wind turbines is proposed. The controller has been designed by means of the differentially flat output of the system such that the power tracking error be asymptotically stable. An algebraic identification method is then used to estimate the unknown wind turbine parameters. The effectiveness of the proposed control strategy, which only depends on the power reference and the rotor speed, is illustrated with the use of the wind turbine simulator FAST.
Alzheimer’s Disease and Intranasal Fluticasone Propionate in the FDA MedWatch Adverse Events Database

Background: Studies of Alzheimer’s disease suggest that neuroinflammation or deranged brain wound healing may be a cause of some cases. But a placebo controlled study showed no effect at all on Alzheimer’s disease of low dose oral prednisone after one year. Introducing the steroid directly into the hippocampus and rhinencephalon via the nose, as happens in hay fever subjects, could be more effective. Objective: In the present study, we analyzed FDA MedWatch data for intranasal fluticasone propionate (Flonase) to determine the frequency of Alzheimer’s disease as an adverse event reported after use of the medication. Methods: Machine-readable data from MedWatch, including adverse drug reaction reports from manufacturers, are part of a public database. We used the online tool eHealthMe to query the database. Results: By September 20, 2017, 35,221 people reported side effects to MedWatch after taking Flonase. Among them, 9 people (0.03%) had Dementia Alzheimer’s type. By October 3, 2017, 185,636 people reported side effects after taking Lipitor. Among them, 243 people (0.13%) had Dementia Alzheimer’s type. The lower incidence of Alzheimer’s dementia in the Flonase group compared to the Lipitor group was significant (p < 0.001, Fisher exact test, two tailed). Conclusion: Long term use of oral non-steroidal anti-inflammatory drugs (NSAIDs) is linked with reduced risk of developing Alzheimer’s disease. Data from MedWatch suggest that fluticasone propionate administered intranasally might have a similar preventive effect to ibuprofen. Perhaps combining ibuprofen and Flonase could be therapeutic. Further studies would be desirable.
FRAME: Framework for Real Time Analysis of Malware

The present work provides a system and method for malware detection wherein the system stores malicious files and replicates only safe files to the main server by the use of containerized scanners. This architecture is a cost-effective solution to provide security from malware. This system introduces a perimeter defense strategy. This works outside of main servers to maintain the confidentiality, integrity, and authenticity of already in place servers.
A Performance Benchmarking Analysis of Hypervisors Containers and Unikernels on ARMv8 and x86 CPUs

Network Functions Virtualization paradigm has emerged as a new concept in networking which aims at cost reduction and ease of network scalability by leveraging on virtualization technologies and commercial-off-the-shelf hardware to disintegrate the software implementation of network functions from the underlying hardware. Recently, lightweight virtualization techniques have emerged as efficient alternatives to traditional Virtual Network Functions (VNFs) developed as VMs. At the same time ARMv8 servers are gaining traction in the server world, mostly because of their interesting performance per watt characteristics. In this paper, the CPU, memory and Input/Output (I/O) performance of such lightweight techniques are compared with that of classic virtual machines on both x86 and ARMv8 platforms. More in particular, we selected KVM as hypervisor solution, Docker and rkt as container engines and finally Rumprun and OSv as unikernels. On x86, our results for CPU and memory related workloads highlight a slightly better performance for containers and unikernels whereas both of them perform almost twice as better as KVM for network I/O operations. This highlights performance issues of the Linux tap bridge with KVM but that can easily be overcome by using a user space virtual switch such as VOSYSwitch and OVS/DPDK. On ARM, both KVM and containers produce similar results for CPU and memory workloads, but have an exception for network I/O operations where KVM proves to be the fastest. We also showcase the several shortcomings of unikernels on ARM which account for their lack of stable support for this architecture.
Optimal Charge Pattern for the High-Performance Multistage Constant Current Charge Method for the Li-Ion Batteries

In this paper, a method is introduced to find out the optimal charge pattern (OCP) of the multistage constant current (MSCC) charge method based on the equivalent circuit model of a Li-ion battery. Unlike the conventional methods, the proposed one does not require several kinds of time-consuming and labor-intensive experiments. The OCP can be simply calculated by the developed equations with the results obtained by a simple experiment. The validity of the proposed method has been verified through the experimental results and it shows that the charge time and the charge energy can be reduced by 12% and 1.8%, respectively, and the charge efficiency of a Li-ion battery can be improved by 0.54% as compared to the conventional constant current–constant voltage (CC–CV) method. A lower temperature rise during the charge can be regarded as an additional advantage of the proposed method.
Optimal Price-Energy Demand Bids for Aggregate Price-Responsive Loads

In this paper, we seek to optimally operate a retailer that, on one side, aggregates a group of price-responsive loads and on the other, submits block-wise demand bids to the day-ahead and real-time markets. Such a retailer/aggregator needs to tackle uncertainty both in customer behavior and wholesale electricity markets. The goal in our design is to maximize the profit for the retailer/aggregator. We derive closed-form solutions for the risk-neutral case and also provide a stochastic optimization framework to efficiently analyze the risk-averse case. In the latter, the price-responsiveness of the load is modeled by means of a non-parametric analysis of experimental random scenarios, allowing for the response model to be non-linear. The price-responsive load models are derived based on the Olympic Peninsula experiment load elasticity data. We benchmark the proposed method using data from the California ISO wholesale electricity market.
Everything-as-a-Thing for Abstracting the Internet-of-Things

This paper discusses Everything-as-a-Thing (*aaT) as a novel way for abstracting the Internet-of-Things (IoT) applications. Compared to other forms of abstraction like Everything-as-a-Service (*aaS) and Everything-as-a-Resource (*aaR), *aaT puts emphasis on living things, on top of non-living things, that populate these applications. On the one hand, living things take over roles that are defined in terms of rights and duties. On the other hand, non-living things offer capabilities that are defined in terms of functional and non-functional properties. Interactions that occur between living and non-living things are specified as stories that define who does what, when, and where. For illustration purposes, *aaT is put into action using a healthcare case study.
V2X Access Technologies: Regulation, Research, and Remaining Challenges

As we edge closer to the broad implementation of intelligent transportation systems, the need to extend the perceptual bounds of sensor-equipped vehicles beyond the individual vehicle is more pressing than ever. Research and standardization efforts toward vehicle to everything (V2X), technology is intended to enable the communication of individual vehicles with both one another and supporting road infrastructure. The topic has drawn interest from a large number of stakeholders, from governmental authorities to automotive manufacturers and mobile network operators. With interest sourced from many disparate parties and a wealth of research on a large number of topics, trying to grasp the bigger picture of V2X development can be a daunting task. In this tutorial survey, to the best of our knowledge, we collate research across a number of topics in V2X, from historical developments to standardization activities and a high-level view of research in a number of important fields. In so doing, we hope to provide a useful reference for the state of V2X research and development for newcomers and veterans alike.
Multiobjective Model of Time-of-Use and Stepwise Power Tariff for Residential Consumers in Regulated Power Markets

Time-of-use (TOU) rates and stepwise power tariff (SPT) are important economic levers to motivate residents to shift their electricity usage in response to electricity price. In this paper, a new multiobjective optimal tariff-making model of TOU and SPT (TOUSPT) is proposed, which combines the complementary characteristics of two power tariffs, for residential energy conservation and peak load shaving. In the proposed approach, the residential demand response with price elasticity in regulated power market is considered to determine the optimum peak–valley TOU tariffs for each stepwise electricity partition. Furthermore, two practical case studies are implemented to test the effectiveness of the proposed TOUSPT, and the results demonstrate that TOUSPT can achieve efficient end-use energy saving and also shift load from peak to off-peak periods.
Frequency Support for Remote Microgrid Systems With Intermittent Distributed Energy Resources—A Two-Level Hierarchical Strategy

A two-level decentralized hierarchical control strategy is developed to cope with active power deficiencies in remote microgrid (MG) systems containing intermittent energy resources. The primary level consists of a multilayer droop-based scheme designed to dispatch the required loads to be shed amongst controllable loads (CLs). The dispatch is proportionally fulfilled through the appropriate assignment of each layer of the droop curves to its corresponding priority type of the CLs. If the primary level is unable to handle the shortfall, the secondary level of the scheme is invoked by coupling of the overloaded MG with a neighboring one. Appropriate criteria are accurately formulated to assure desirable interconnections and proper isolations of the MGs. By detecting an overloading condition, the primary level attempts to raise the frequency by managing the CLs, whereas the secondary level assesses the possibility of forming a system of coupled MGs (CMG). Depending on the level of support provided by the neighboring MG, the shed loads can be restored completely or partially once the system of CMG is formed. Implementation of the two levels is coordinated such that the power shortfall can be relieved with very low bandwidth communication systems. Validity of the proposed strategy is demonstrated through several PSCAD/EMTDC studies.