Miracle-dz/UniFAR-FTUs huggingface dataset:
The performance of openSAFETY protocol via IEEE 802.11 wireless communication

Functional safety has become a crucial part of industrial automation. With industry environments being connected more than ever, achieving required functional safety depends on establishing safety-critical communication. Numerous application layer safety protocols have been developed to ensure compliance with functional safety standards for wired communications. However, with all the benefits wireless communications entails, wireless communication is pushing for an important place in the future of industrial automation. It is important that safety protocols also follow this transition and are able to operate as intended using a wireless channel. By default, openSAFETY frames are exchanged using UDP broadcast, whereas TCP provides additional reliability features. Thus, the aim of this paper is to analyze if safety-critical communication using a wireless channel can benefit from the additional reliability features provided by TCP. To answer this, we experimentally analyze the performance of openSAFETY protocol providing functional safety over the IEEE 802.11 standard for three different test cases. We analyze the performance in terms of median end-to-end delay and time spent by a safety node in a safe state for both protocol stacks. Results show that UDP provides lower median end-to-end delay, whereas TCP is able to achieve less time spent in a safe state under bounded delay constraint.
Influence of the Adoption and Use of Social Media Tools on Absorptive Capacity in New Product Development

Abstract: In this article, we discuss how the adoption and use of social media tools influences new product development (NPD). Our aim is specifically to consider how an organization's absorptive capacity is influenced by using social media tools. Based on a two-phase data collection process comparing the situation before and after adoption of social media tools in three organizations, we conclude that the amount of accessible knowledge and the number of ideas increases as an organization's ability to find and access various sources of intra-organizational expertise increases, thus, increasing knowledge acquisition and assimilation. Consequently, we infer that organizational absorptive capacity rises and is linked to improvement in new product development.
Future prospects and challenges associated with intelligent reflecting surfaces enabled wireless communication

The considerable increase in number of connected devices over the past few years has led to the new challenges for wireless communication technology. Most of the work was focused on enhancing the capability of either the transmitter or receiver, as the propagation environment was considered uncontrollable. The concept of controlling propagation environment in order to produce smart radio environment has been introduced and gained considerable attention. The propagation environment can be controlled by deploying intelligent reflecting surfaces between the transmitter and receiver. In this paper, we aim to provide a brief overview of prospective uses and research challenges associated with intelligent reflecting surfaces.
Optimizing shared data plans for mobile data access

The demand for mobile data has been steadily increasing over the last decade, forming an ever increasing portion of the overall Internet traffic. A considerable portion of this demand is served through capped cellular data plans that charge a fixed fee for data consumption respecting the cap and a typically higher penalty rate for additional consumption. Although shared data plans have been identified as a way to better utilize capacity that is paid for but not used, they are largely restricted to closed groups (e.g., family members) or the devices of a single user.In this paper we advocate the extension of shared data plans towards more open groups of users. We take the viewpoint of a platform that seeks to recommend optimal data plans to users subscribing to it and address the two main algorithmic tasks it faces: the partitioning of users to subscription groups and the selection of data plans that maximize their cost savings. We devise three algorithms that leverage clustering techniques. One of them addresses simultaneously the two tasks, whereas the other two decompose the problem and solve the two tasks sequentially. Our evaluation results suggest that the savings in subscription charges with shared plans are significant, ranging from 20% up to 80% of what users would pay with the cost-optimal individual data plans. They also highlight properties of the three algorithms and trade-offs they present involving the achieved cost savings, the intensity of under utilization and their sensitivity to deviations from the predicted users’ data consumption.
Broadband transmission below the cutoff frequency of a waveguide loaded with resonant scatterer arrays

A computer-aided method for the design of waveguide structures loaded with the arrays of metamaterial cells is described. Broadside coupled split ring resonators and Ω scatterers are chosen as the resonant metamaterial cells. By optimisation of the resonator geometry, the bandwidth of the transmission range below the cutoff frequency of the waveguide is enlarged compared with the results reported in the literature. The modes propagated below the waveguide cutoff possess a passband of the order of 30–50% and can be of the backward as well as of the forward type. The presented optimisation approach is based on the eigensolver simulations of a metamaterial unit cell. The designed metamaterial arrays are fabricated and measured. The experimental results are compared with the simulations validating the proposed design approach.
Infrastructure delivery and spatial planning

This paper examines the delivery of infrastructure requirements related to the plan-making (LDF) process in England introduced as part of the 2004 planning system reforms. Success or otherwise in terms of plan implementation and infrastructure delivery is crucial if the reformed spatial planning system is to be successful. The paper draws on research undertaken as part of a government-sponsored research project into the operation of the new LDF process. The research reveals a significant gap between government expectations and current practice. It suggests that longer-term commitments by central government, alongside improved understanding of the spatial planning process and the role of local government as part of a continued drive for ‘culture change’ among local planning authorities and delivery partners, will be required if the current barriers to the delivery of infrastructure are to be overcome. Otherwise, the new-style LDFs are as likely to be plagued by implementation gaps as were their predecessors.
Integrated pest management for African bollworm (Helicoverpa armigera (Hubner) in Botswana: review of past research and future perspectives

African bollworm or Old World bollworm (Helicoverpa armigera Hubner, Lepidoptera: Noctuidae) is an extremely polyphagous and major pest of many crops in Botswana. The damage to most crops results in reduction of yields. H. armigera is estimated to cause yield loss of 15 to 30% on sorghum in Botswana. Despite its importance, research on H. armigera has not been carried out in Botswana since 1979. This paper reviews the research on management of H. armigera that was undertaken in Botswana from the late sixties to late seventies (1967 to 1979). The research focused on developing various pest management methods that would be packaged into an integrated pest management strategy to manage H. armigera in field crops. The major findings were that microbial control (using nuclear polyhedrosis virus and Bacillus thuringiensis Berliner), enhancing natural enemies, cultural control and the use of insecticides had potential in management of H. armigera. These findings are discussed in comparison with other studies done in Asia, Australia and other parts of Africa where African bollworm is a major pest of field crops. The primary objective of this paper is to review the research that had been undertaken on H. armigera in Botswana and propose future research needs and directions.
Development of Land Use Judgment System using Deep Learning to Support Land Evaluation

Fixed asset tax which is assessed based on the purpose of land use, is a very important resource in Japanese municipalities. Article 408 of the Local Tax Act shows that field survey is required to be carried out once a year to confirm the use of land. Municipal officials spend a lot of time and effort to conduct field surveys to check the use of land in order to make a proper evaluation. Therefore, in this study, we utilize three types of data, aerial photography images, shapefiles, and taxable data of registered land category owned by local governments to promote the utilization of public and private sector data. The purpose of this study is to reduce the burden of land evaluation work and improve its efficiency and accuracy by using deep learning. It is confirmed that our system is effective in supporting land evaluation work and improving the efficiency of field survey work.
Comparison of experimental data to a model for bicycle steady-state turning

The steady-state turning of a bicycle arises when the bicycle/rider system negotiates a constant radius turn with constant speed and roll angle. This paper explores steady-state turning by employing a bicycle instrumented to measure steering torque, steering angle, and bicycle speed, acceleration, and angular velocity. We report data obtained from 134 trials using two subjects executing steady turns defined by nine different radii, three speeds, and three rider lean conditions. A model for steady-state turning, based on the Whipple bicycle model, is used to interpret the experimental results. Overall, the model explains 95.6% of the variability in the estimated bicycle roll angle, 99.4% of the variability in the measured steering angle, and 6.5% of the variability in the measured steering torque. However, the model explains 56.6% of the variability in steering torque for the subset of trials without exaggerated rider lean relative to the bicycle frame. Thus, the model, which assumes a rigid and non-leaning rider, reasonably predicts bicycle roll and steering angles for all rider lean conditions and steering torque without exaggerated rider lean. The findings demonstrate that lateral shifting of the bicycle/rider centre of mass strongly influences the steering torque, suggesting that rider lean plays an important role in bicycle control during steady-state turning. By contrast, the required steering angle is largely insensitive to rider lean, suggesting that the steering angle serves as a superior cue for bicycle control relative to the steering torque.
Cyclic Load Behavior of Concrete‐Filled Tubular Braces

Cyclic load behavior of concrete-filled rectangular steel tubular bracing members is investigated. Nine full-scale specimens made from A500 Grade B cold-formed steel tubes were tested under quasi-static cyclic loading. The main parameters of the study are: 1) presence of concrete; 2) strength of concrete; 3) effective slenderness ratio; and 4) width-thickness ratio. General cyclic behavior and modes of failure of the specimens are presented. Based on the observations of the behavior of test specimens two procedures are given to compute the first buckling load for such bracing members.
Small- And Large-Signal Modelling of a Modular Boost-Derived DC-DC Converter For High-Output Voltage Applications

Abstract A procedure is established for the small- and large-signal modelling of modular current-mode controlled (CMC) pulse-width modulated (PWM) boost-derived transformer-isolated DC-DC converters. A three-module converter employing full-bridge topology is taken as an example. The converter is intended for high-output voltage applications and works in the continuous-current conduction mode. It consists of DC-DC modules whose inputs are connected in parallel and outputs in series across a common resistive load. Cycle-by-cycle simulations using PSpice are performed to aid the analysis.
Simulation of Facial Palsy using Conditional Generative Adversarial Networks and Face Shape Normalization

The Yanagihara method for evaluating facial nerve palsy is based on physicians’ visual examinations, and the problem with this approach is that it is difficult to use patients’ images for physicians’ training and educations because of patients’ privacy protection. We aimed to solve this problem by creating a pseudo-facial image of a patient with facial paralysis that can be shared among doctors. To reproduce the patient’s facial expression in a public face image, we proposed a method to generate a target face image using a generative adversarial model based on deep learning. In addition, we conducted an experiment to reproduce the face image while considering the difference in human face shapes. Based on experimental results, we successfully generated the target image. Furthermore, the data preprocessing method needed to be improved to reproduce the fine details of the face.
Effective Counterterrorism and the Limited Role of Predictive Data Mining

spurred extraordinary efforts intended to protect America from the newly highlighted scourge of international terrorism. Among the efforts was the consideration and possible use of “data mining” as a way to discover planning and preparation for terrorism. Data mining is the process of searching data for previously unknown patterns and using those patterns to predict future outcomes. Information about key members of the 9/11 plot was available to the U.S. government prior to the attacks, and the 9/11 terrorists were closely connected to one another in a multitude of ways. The National Commission on Terrorist Attacks upon the United States concluded that, by pursuing the leads available to it at the time, the government might have derailed the plan. Though data mining has many valuable uses, it is not well suited to the terrorist discovery problem. It would be unfortunate if data mining for terrorism discovery had currency within national security, law enforcement, and technology circles because pursuing this use of data mining would waste taxpayer dollars, needlessly infringe on privacy and civil liberties, and misdirect the valuable time and energy of the men and women in the national security community. What the 9/11 story most clearly calls for is a sharper focus on the part of our national security agencies—their focus had undoubtedly sharpened by the end of the day on September 11, 2001—along with the ability to efficiently locate, access, and aggregate information about specific suspects. Effective Counterterrorism and the Limited Role of Predictive Data Mining
Nature of Freeplay-Induced Aeroelastic Oscillations

Time- and frequency-domain analyses are used to revisit a well studied case of an aeroelastic wing with control-surface freeplay nonlinearity. The dynamic response in general is presented as dependent on the stability of two linear systems, with zero and nominal control-surface rotational stiffness, and values of two angles, freeplay and preload. The principal new findings include the following. A physical explanation is given to the bifurcation airspeeds and frequencies of the oscillations for the system with both zero and nonzero aerodynamic preload of the control surface. For the latter and more complex case, it is shown and explained why a certain amount of the preload is not only always destabilizing but may also be the reason for the otherwise unexpected higher-frequency oscillations. A conclusion thus is drawn that the aircraft control-surface freeplay analyses based only on zero and high quenching aerodynamic preloads are nonconservative. All results are compared with the experimental and other pu.
Examining Factors Contributing to Tranquillity in the Scottish Highlands and Dartmoor National Park

The opportunity to experience tranquillity is what makes the countryside so different from cities for many visitors, and in a survey conducted by the UK’s Department for Environment, Food and Rural Affairs [1], 58% of people questioned stated that for them tranquillity was the most positive feature of the countryside. It is therefore not surprising that within the UK Government’s Rural White Paper [2] that tranquillity features as an important element and the UK has recently recognized the importance of protecting tranquil spaces in the National Planning Policy Framework [3]. Previous studies into modelling tranquil space [4,5] led to the development of the following Tranquillity Rating Prediction Tool (TRAPT), which can be used to predict the Tranquillity Rating (TR) of both urban and natural environments. It is important because for the first time it is possible to quantify the importance of natural features in the visual scene and of man-made noise. A practical formulation of the relationship for rural landscapes:
An All–at–Once CP Decomposition Method for Count Tensors

CANDECOMP/PARAFAC (CP) tensor decomposition is a popular method for detecting latent behaviors in real–world data sets. As data sets grow larger and more elaborate, more sophisticated CP decomposition algorithms are required to enable these discoveries. Data sets from many applications can be represented as count tensors. To decompose count tensors, one should minimize the sum of the generalized Kullback–Leibler divergences from each tensor entry to each corresponding decomposition entry. Most often, this is done using the algorithm CP–APR (CP–Alternating Poisson Regression). In view of the fact that all-at-once optimization algorithms for related CP decomposition problems often achieve better decomposition accuracy than alternating algorithms like CP–APR, we develop CP–POPT–GDGN, an all–at–once algorithm for count tensor decomposition that utilizes a generalized damped Gauss-Newton method. We then implement a highly efficient version of CP–POPT–GDGN into the tensor package ENSIGN. After decomposing several tensors formed from real-world data sets, many of which are related to network traffic, we see that CP–POPT–GDGN typically outperforms CP–APR, both in terms of decomposition accuracy and latent behavior detection.
The Cost-Effectiveness of Psychodynamic Therapy: The Obstacles, the Law, and a Landmark Lawsuit

ABSTRACT Psychotherapy, especially dynamic psychotherapy and psychoanalysis, has been poorly supported by insurance although the Mental Health Parity Act mandates benefits for mental health care at parity with other health care and The Affordable Care Act lists mental health care, including psychotherapy, as an Essential Health Benefit. Limiting insurance support for psychotherapy turns away very ill, especially poorer patients who forego treatment and incur increased medical costs and disability. Patients with personality disorders, chronic anxiety depression, chronic illness and comorbidity require extended, often intensive, psychotherapy for optimal recovery. Brief cognitive-behavioral therapy is seen as a “gold standard” and “most evidence-based” although its research protocols study subjects not typical of most patients and who achieve only short-lived improvements. Research finds psychodynamic therapies to be highly cost-effective, equal to other efficacious therapies in improving symptoms, and also superior in improving maladaptive interpersonal relationship patterns, a high-risk factor for mortality. Knowledgeable attorneys and expert witnesses were key to the 2019 successful class action lawsuit against United Behavioral Health for declining to cover research supported generally accepted standards for mental health care and for a subsequent California state law mandating sufficient insurance coverage. To defend it in legal and policy arenas, providers and advocates for psychodynamic psychotherapy should familiarize themselves with its supporting research and the laws that demand its provision.
Revision and Further Validation of Surface Performance-Graded Specification for Chip Seal Binders

The design and selection of chip seal binders for adequate performance in service are currently based on specifications that include tests of emulsion residues or hot-applied asphalt cements at standard temperatures that do not cover the entire range of in-service temperatures, measure properties that are not performance related, and do not consider representative aging conditions for the critical first year. A surface performance-graded (SPG) specification for the evaluation and selection of chip seal binders that addressed these shortcomings was developed as part of previous Texas Department of Transportation (DOT) and NCHRP research projects. In the current study sponsored by the Texas DOT, the SPG specification was revised and further validated. This was accomplished through use of a single emulsion residue recovery method, determination of performance-related properties and exploration of additional criteria, and further validation of the SPG specification thresholds for these properties based on field performance monitoring and a comparison with laboratory results. This study was limited to producing a revised SPG specification for performance-related properties that addressed aggregate retention and bleeding in service. Specifically, the threshold for minimum shear strain at 0.8 G*i was reduced from 25% to 17.5%, and the m-value was removed. The effects of construction and quality control processes were beyond the scope of this study, and additional specifications are needed for use in conjunction with the SPG specification to address these issues and ensure adequate performance.
The L1624Q Variant in SCN1A Causes Familial Epilepsy Through a Mixed Gain and Loss of Channel Function

Variants of the SCN1A gene encoding the neuronal voltage-gated sodium channel NaV1.1 cause over 85% of all cases of Dravet syndrome, a severe and often pharmacoresistent epileptic encephalopathy with mostly infantile onset. But with the increased availability of genetic testing for patients with epilepsy, variants in SCN1A have now also been described in a range of other epilepsy phenotypes. The vast majority of these epilepsy-associated variants are de novo, and most are either nonsense variants that truncate the channel or missense variants that are presumed to cause loss of channel function. However, biophysical analysis has revealed a significant subset of missense mutations that result in increased excitability, further complicating approaches to precision pharmacotherapy for patients with SCN1A variants and epilepsy. We describe clinical and biophysical data of a familial SCN1A variant encoding the NaV1.1 L1624Q mutant. This substitution is located on the extracellular linker between S3 and S4 of Domain IV of NaV1.1 and is a rare case of a familial SCN1A variant causing an autosomal dominant frontal lobe epilepsy. We expressed wild-type (WT) and L1642Q channels in CHO cells. Using patch-clamp to characterize channel properties at several temperatures, we show that the L1624Q variant increases persistent current, accelerates fast inactivation onset and decreases current density. While SCN1A-associated epilepsy is typically considered a loss-of-function disease, our results put L1624Q into a growing set of mixed gain and loss-of-function variants in SCN1A responsible for epilepsy.