Global Task Research Articles

Terror of 10 MB, a cross-sectional study investigates the regulation to the prospective of medical device

An instrument, apparatus, implement, machine, implant, in vitro reagent, a component part or accessory which Intended for use in diagnosis of disease or other condition, or in the cure, mitigation and treatment or prevention of disease is called medical devices. Medical devices under new rule classified as Class A (low risk), Class B (low moderate risk), Class C (moderate high risk), and Class D (high risk) commemorating the notification of January 31, 2017 of Ministry of Health and Family Welfare which is conformity with Global Harmonisation Task Force framework. As per make in India program, the industry of medical devices is USD 5.2 billion and is contributing 4%–5% to the USD 96.7 billion Indian health-care industry. A total of 750–800 medical device manufacturers in India, an average investment of Rs 170–200 million and an average turnover of Rs 450–500 million. An online licensing portal of the Central Drugs Standard Control Organization (CDSCO) called “Sugam portal” has been launched on November 14, 2015, to file application and grant permission of registration exclusively for Medical Device CDSCO MD Online portal. By making the document submission easier, there are lot of challenges also present in “Sugam-online Portal.” One of the main challenges in Sugam Portal is that there is no provision to upload files greater than 10MB file size. The current study addresses the issues and challenges faced by medical device industry and regulators with their potential solutions and recommendations.

Possibilities and perspectives of strategic planning of socio-economic and technological development of a region with the usage of the foresight methodology

Due to the global tasks of transition of the Russian economy to high technologies and the necessity for improvement of the material and technical basis in the new conditions of the modern market, it is supposed that foresight could become an effective tool of implementing the necessary structural shifts that stimulate the creation of the innovative level of the Russian market. The authors substantiate the necessity for development of a scenario of creation of the organisational and economic system at the level of a territory, which would perform transformation of all existing sectorial and regional resources into the products of innovative activities of companies, which would be the basis for provision of investment attractiveness of Rostov Oblast and the innovative activities on its territory, as well as strengthening the competitive potential of the analyzed region.

Synchronized mobile manipulators for kinematic cooperative tasks: control design and analysis

Abstract In this paper we present a synchronization feedback control scheme for kinematic cooperative mobile manipulator robots performing a global task of manipulation and transportation, where an object is taken to a desired 6D pose. We define the motion of the object which is translated to each end-effector as desired coordinates, that trajectory is generated on-line and is a function of every robot in the scene. The group of robots follow the object’s motion where the control of each robot is also a function of every other robot, meanwhile they are constrained to a common object. This leads to a complicated interaction scheme, so we thoroughly analyze the effects of the interactions that alter the behavior of each robot, and determine under what conditions those effects help to increase the performance of the proposed control scheme, such that the motions are coordinated to minimize the total energy and stabilize themselves as the common object reaches its objective. For this we performed a stability analysis and tested our control scheme through simulations.

Possibilities and perspectives of strategic planning of socio-economic and technological development of a region with the usage of the foresight methodology

Due to the global tasks of transition of the Russian economy to high technologies and the necessity for improvement of the material and technical basis in the new conditions of the modern market, it is supposed that foresight could become an effective tool of implementing the necessary structural shifts that stimulate the creation of the innovative level of the Russian market. The authors substantiate the necessity for development of a scenario of creation of the organisational and economic system at the level of a territory, which would perform transformation of all existing sectorial and regional resources into the products of innovative activities of companies, which would be the basis for provision of investment attractiveness of Rostov Oblast and the innovative activities on its territory, as well as strengthening the competitive potential of the analyzed region.

Asynchronous Silent Programmable Matter Achieves Leader Election and Compaction

We study models and algorithms for Programmable Matter (PM), that is matter with the ability to change its physical properties (e.g., shape or optical properties) in a programmable fashion. PM can be implemented by assembling a system of weak self-organizing computational elements, called particles, that can be programmed via distributed algorithms to collectively achieve some global task. Recent advances in the production of nanotechnologies have rendered such systems increasingly possible in practice, thus triggering research interests from many areas of computer science. The most established models for PM assume that particles: are modeled as finite state automata; are all identical, executing the same algorithm based on local observation of the surroundings; live and operate in the cells of a hexagonal grid; can move from one cell to another by repeatedly alternating between a contracted state (a particle occupies one cell) and an expanded state (a particle occupies two neighboring cells). Given these elementary features, it is rather hard to design distributed algorithms even for basic tasks and, in fact, all existing solutions to solve fundamental problems via PM have resorted to endowing PM systems with various capabilities to overcome such hardness, thus assuming quite unrealistic features. In this paper, we move toward more realistic computational models for PM. Specifically, we first introduce SILBOT, a new modeling approach that relaxes several assumptions used in previous ones. Second, we present a distributed algorithm to solve, in the SILBOT model, a foundational primitive for PM, namely Leader Election. This algorithm works in O(n) rounds for all initial configurations of n particles that are both connected (i.e. particles induce a connected graph) and compact (i.e. without holes, that is no empty cells surrounded by particles occur). As usual in asynchronous contexts, a round is intended as the time within which all particles have been activated at least once. Third, we show that, if the initial configuration admits holes, it is impossible to achieve leader election while preserving connectivity. Finally, by slightly empowering the robots, we design an algorithm to handle initial configurations admitting holes that in O(n <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> ) rounds solves the leader election problem while obtaining also compaction.

Pseudo-perturbation-based broadcast control of multi-agent systems

The present paper proposes a novel broadcast control (BC) law for multi-agent coordination. A BC framework has been developed to achieve global coordination tasks with low communication volume. The BC law uses broadcast communication, which transmits an identical signal to all agents indiscriminately without any agent-to-agent communication. Unfortunately, all of the agents are required to take numerous random actions because the BC law is based on stochastic optimization. Such random actions degrade the control performance for coordination tasks and may invoke dangerous situations. In order to overcome these drawbacks, the present paper proposes the pseudo-perturbation-based broadcast control (PBC) law, which introduces multiple virtual random actions instead of the single physical action of the BC law. The following advantages of the PBC law are theoretically proven. The PBC law achieves coordination tasks asymptotically with probability 1. Compared with the BC law, unavailing actions are reduced and agents’ states converge twice as fast. Increasing the number of multiple actions further improves the control performance because averaging multiple actions reduces unavailing randomness. Numerical simulations demonstrate that the PBC improves the control performance as compared with the BC law.

Зміст інтегральної компетентності майбутніх викладачів музичного мистецтва і хореографії

У статті розглянуто зміст інтегральної компетентності майбутніх викладачів музичного мистецтва та хореографії як кваліфікаційного метаконструкту, який реалізує функцію координації процесів актуалізації та формування компетентностей, відповідно до мети та завдань варіативно-творчого процесу мистецької освіти. На основі здійсненого аналізу таксономії освітніх цілей Б. Блума та концепції, відтвореної Л. Андерсеном та співавторами, з’ясовано, що зміст інтегральної компетентності майбутніх викладачів музичного мистецтва та хореографії визначається на двох рівнях – процесуальному і результативному. На процесуальному рівні такий зміст складають уміння та навички, сформовані в процесі досягнення таксономічно структурованих цілей мистецько-освітнього процесу. На результативному рівні такий зміст проявляється як метазнання, систематизоване у змістові домени: “стратегічні знання”, “знання когнітивних завдань”, “самопізнання”, “оцінювання цілей”.

Multi-omics reveals functional genomic and metabolic mechanisms of milk production and quality in dairy cows.

Enhancing the utilization of human-inedible crop by-products by ruminants to produce high-quality milk for human consumption is an emerging global task. We performed a multi-omics-based study to decipher the regulatory biological processes of milk production when cows fed low-quality crop by-products with the aim to improve their utilization. Seven types of different high-throughput omics data were generated across three central organs [rumen, liver and mammary gland (MG)] and biofluids (rumen fluid and blood) that involved in milk production. The integrated multi-omics analysis including metabolomics, metagenomics and transcriptomics showed altered microbiome at compositional and functional levels, microbial metabolites in the rumen, down-regulated genes and associated functions in liver and MG. These changes simultaneously contributed to down-regulated three key metabolic nodes (propionate, glucose and amino acid) across these organs and biofluids that led to lowered milk yield and quality when cows consumed corn stover (CS). Hippuric acid was identified as a biomarker that led to low milk production in CS-fed cows, suggesting a future evaluation parameter related to the metabolic mechanism of low-quality forage utilization. This study unveils the milk production-related biological mechanism across different biofluids and tissues under a low-quality forage diet, which provides a novel understanding and potential improvement strategies for future crop by-products utilization and sustainable ruminant production. The raw files of metagenomics, metabolomics, and transcriptomics data can be accessed at NCBI SRA (No. SRR5028206), EMBI-EBI (No. MTBLS411), and GEO (NO. GSE78524) databases respectively. Supplementary data are available at Bioinformatics online.

The relationship between cognitive function and having diabetes in patients treated with hemodialysis

PurposePatients undergoing maintenance hemodialysis (MHD) have a higher prevalence of cognitive impairment and inferior cognitive performance than the general population, and those with cognitive impairment are at higher risk of death than those without cognitive impairment. Having diabetes has been associated with an increased risk of cognitive decline in end-stage kidney disease patients treated with peritoneal dialysis or kidney transplant. However, these findings may not extend to the hemodialysis population. Thus, we aim to investigate the relationship between having diabetes and cognitive function in MHD patients. MethodsThis was a cross-sectional study. A total of 203 patients treated with MHD from two blood purification centers were enrolled as subjects. The Chinese version of the Montreal Cognitive Assessment (MoCA) was utilized to assess cognitive function. ResultsMHD patients with diabetes had a significantly higher prevalence of global cognitive impairment and inferior performance in global cognition, visuospatial/executive function, naming, language, abstraction and orientation tasks compared with those without diabetes. According to the multiple linear analyses, having diabetes was significantly associated with lower global cognitive function, naming, and language scores, with β coefficients and 95% CIs of −1.30 [ −2.59, −0.01], −0.25 [−0.47, −0.02], and −0.32 [−0.58, −0.07], respectively (all P < 0.05). Having diabetes could not independently predict an increased risk of global cognitive impairment. ConclusionsIn MHD patients, having diabetes is significantly associated with lower cognitive function scores. Medical staff should evaluate early and focus on the decline of cognitive function in MHD patients with diabetes, in order to achieve early diagnosis and early intervention.

Using Interval Analysis to Compute the Invariant Set of a Nonlinear Closed-Loop Control System

In recent years, many applications, as well as theoretical properties of interval analysis have been investigated. Without any claim for completeness, such applications and methodologies range from enclosing the effect of round-off errors in highly accurate numerical computations over simulating guaranteed enclosures of all reachable states of a dynamic system model with bounded uncertainty in parameters and initial conditions, to the solution of global optimization tasks. By exploiting the fundamental enclosure properties of interval analysis, this paper aims at computing invariant sets of nonlinear closed-loop control systems. For that purpose, Lyapunov-like functions and interval analysis are combined in a novel manner. To demonstrate the proposed techniques for enclosing invariant sets, the systems examined in this paper are controlled via sliding mode techniques with subsequently enclosing the invariant sets by an interval based set inversion technique. The applied methods for the control synthesis make use of a suitably chosen Gröbner basis, which is employed to solve Bézout’s identity. Illustrating simulation results conclude this paper to visualize the novel combination of sliding mode control with an interval based computation of invariant sets.

Path planning for robotic teams based on LTL specifications and Petri net models

This research proposes an automatic strategy for planning a team of identical robots evolving in a known environment. The robots should satisfy a global task for the whole team, given in terms of a Linear Temporal Logic (LTL) formula over predefined regions of interest. A Robot Motion Petri Net (RMPN) system is used for modeling the evolution of the robotic team in the environment, bringing the advantage of a fixed topology versus the number of robots, with respect to methods based on synchronous automaton products. The algorithmic method iterates the selection of an accepted run that satisfies the specification and the search for RMPN sequences of reachable markings that can produce desired observations. A Buchi automaton witnesses the advancement towards formula fulfillment, and at the core of our methods are three Mixed Integer Linear Programming (MILP) formulations that yield firing sequences and markings of RMPN model. The cost functions of these formulations reduce the number of robot synchronizations and induce collision avoidance. Simulation examples support the computational feasibility of the proposed method.

The resources vertical aggregation model in the construction and installation works planning

The exchange of information between the global and local tasks occurs in the aggregated nomenclature, which reduces the bandwidth requirements of inter-layer communication channels. In the horizontal aggregation scheme, a global task is formed on the basis of non-aggregated information of local systems. The resources vertical aggregation model was obtained in the construction production planning, which differs by taking into account the restrictions on the number of teams used for the works functional dependencies.

Forcing Gender Issues and Challenges Affecting Women Employees to Continue their Career in IT Industry

Despite the major advancements women have made in becoming a significant part of the workforce, they are still facing important career development issues. Although many women achieve lower and middle management positions, they seem to hit the “glass ceiling” in many organizations and are denied the most senior levels of upper management. The reasons are multi-dimensional; some women lack the confidence to apply for senior positions; some lack the necessary education or training; and others find themselves excluded from the top positions because of systemic gender bias that exists in some companies. There are plenty of statistics tracking the percentage of women in the workforce, their qualifications and their salaries. But the data doesn’t show us the whole picture. It doesn’t assess how women feel, how they fare in their day-to-day business, the challenges they encounter. And that is why the research embarked on a global task, asking more than 9,500 women across the G20 to identify the top five issues faced at work especially in IT industry.

Formal Expert Examination of Materials and Structures in Order to Assess the Possibility of Their Re-use

The re-use of materials, structures and their elements in the construction of buildings and structures of various responsibilities is dictated by the need to reduce the cost of the final product. Quite often, the end consumer (that is the owner) does not even realise that re-used materials were apploed for the construction of the object. The global task in this case is the established possibility of such application through a safety perspective. This requires the examination of materials and structures in order to assess the possibility of their re-use. In this study, the authors develop a methodical approach to such examinations, based on the existing normative-technical regulations. They also take into account their experience in inspection of materials and structures of re-used pipe piles in building construction.

A Dilated Inception Network for Visual Saliency Prediction

Recently, with the advent of deep convolutional neural networks (DCNN), the improvements in visual saliency prediction research are impressive. One possible direction to approach the next improvement is to fully characterize the multi-scale saliency-influential factors with a computationally-friendly module in DCNN architectures. In this work, we propose an end-to-end dilated inception network (DINet) for visual saliency prediction. It captures multi-scale contextual features effectively with very limited extra parameters. Instead of utilizing parallel standard convolutions with different kernel sizes as the existing inception module, our proposed dilated inception module (DIM) uses parallel dilated convolutions with different dilation rates which can significantly reduce the computation load while enriching the diversity of receptive fields in feature maps. Moreover, the performance of our saliency model is further improved by using a set of linear normalization-based probability distribution distance metrics as loss functions. As such, we can formulate saliency prediction as a global probability distribution prediction task for better saliency inference instead of a pixel-wise regression problem. Experimental results on several challenging saliency benchmark datasets demonstrate that our DINet with proposed loss functions can achieve state-of-the-art performance with shorter inference time.

Spatial Frequency Tuning and Transfer of Perceptual Learning for Motion Coherence Reflects the Tuning Properties of Global Motion Processing.

Perceptual learning is typically highly specific to the stimuli and task used during training. However, recently, it has been shown that training on global motion can transfer to untrained tasks, reflecting the generalising properties of mechanisms at this level of processing. We investigated (i) if feedback was required for learning in a motion coherence task, (ii) the transfer across the spatial frequency of training on a global motion coherence task and (iii) the transfer of this training to a measure of contrast sensitivity. For our first experiment, two groups, with and without feedback, trained for ten days on a broadband motion coherence task. Results indicated that feedback was a requirement for robust learning. For the second experiment, training consisted of five days of direction discrimination using one of three motion coherence stimuli (where individual elements were comprised of either broadband Gaussian blobs or low- or high-frequency random-dot Gabor patches), with trial-by-trial auditory feedback. A pre- and post-training assessment was conducted for each of the three types of global motion coherence conditions and high and low spatial frequency contrast sensitivity (both without feedback). Our training paradigm was successful at eliciting improvement in the trained tasks over the five days. Post-training assessments found evidence of transfer for the motion coherence task exclusively for the group trained on low spatial frequency elements. For the contrast sensitivity tasks, improved performance was observed for low- and high-frequency stimuli, following motion coherence training with broadband stimuli, and for low-frequency stimuli, following low-frequency training. Our findings are consistent with perceptual learning, which depends on the global stage of motion processing in higher cortical areas, which is broadly tuned for spatial frequency, with a preference for low frequencies.

ПРОБЛЕМЫ И ПУТИ СНИЖЕНИЯ АНТРОПОГЕННОГО ВОЗДЕЙСТВИЯ НА ВОДЫ МИРОВОГО ОКЕАНА

The article touches upon the current problems of pollution of the oceans. The significant role of the ecosystem, fauna and flora of the World Ocean in the formation of climate on the planet are noted. The oceans, as a powerful regulator of climate and weather, plays an extremely important role in the development of life on Earth, controls oxygen balance, provides food, biological and mineral resources, etc. One of the global tasks that humanity needs to solve is the reduction (prevention) of negative impacts on aquatic ecosystems. Especially detrimental to the ecology of the oceans are drilling works, production and transportation of liquid hydrocarbons by tankers, because in the process of work there takes place the water surface pollution producing a thin oil film. With sewage waters from the industrial enterprises a huge amount of toxic heavy metal compounds enter the World Ocean. The source of pollution is the ballast water from vessels, which serve to ensure the balance and stability of the vessels. At present, man has already faced such problems as the greenhouse effect, warming trend on Earth, melting of ice at the North Pole and South Pole, rising sea levels above 3 m, reducing biological productivity of the World Ocean, etc. The invasion of alien organisms, including pathogenic ones for the ecosystem and humans, is considered in detail. The standards of the International Maritime Organization (IMO) for ballast discharged water have been given. Existing methods of ballast water treatment are described in accordance with the requirements of the International Convention on control and management of ships' ballast water and sediments 2004. The possible ways of combating pollution of ocean waters are proposed as an important element for protection of the ecosystem of the World Ocean.

Consensus of Multiagent Systems Via Asynchronous Cloud Communication

In this paper, we study a multiagent consensus problem in which agents are only able to communicate with each other intermittently through a cloud server. To reduce the amount of required communication, we develop a self-triggered algorithm that allows agents to communicate with the cloud only when necessary rather than at a fixed period. Unlike the vast majority of similar works that propose distributed event- and/or self-triggered control laws, this paper does not assume agents can be “listening” continuously. In other words, when an event is triggered by one agent, neighboring agents will not be aware of this until the next time they establish communication with the cloud themselves. Using a notion of “promises” about future control inputs, agents are able to keep track of higher quality estimates about their neighbors allowing them to stay disconnected from the cloud for longer periods of time while still guaranteeing a positive contribution to the global task. We prove that our self-triggered coordination algorithm guarantees that the system asymptotically reaches the set of desired states. Simulations illustrate our results.

Model consent clauses for rare disease research

BackgroundRare Disease research has seen tremendous advancements over the last decades, with the development of new technologies, various global collaborative efforts and improved data sharing. To maximize the impact of and to further build on these developments, there is a need for model consent clauses for rare diseases research, in order to improve data interoperability, to meet the informational needs of participants, and to ensure proper ethical and legal use of data sources and participants’ overall protection.MethodsA global Task Force was set up to develop model consent clauses specific to rare diseases research, that are comprehensive, harmonized, readily accessible, and internationally applicable, facilitating the recruitment and consent of rare disease research participants around the world. Existing consent forms and notices of consent were analyzed and classified under different consent themes, which were used as background to develop the model consent clauses.ResultsThe IRDiRC-GA4GH MCC Task Force met in September 2018, to discuss and design model consent clauses. Based on analyzed consent forms, they listed generic core elements and designed the following rare disease research specific core elements; Rare Disease Research Introductory Clause, Familial Participation, Audio/Visual Imaging, Collecting, storing, sharing of rare disease data, Recontact for matching, Data Linkage, Return of Results to Family Members, Incapacity/Death, and Benefits.ConclusionThe model consent clauses presented in this article have been drafted to highlight consent elements that bear in mind the trends in rare disease research, while providing a tool to help foster harmonization and collaborative efforts.

Energy-efficient thermal-aware multiprocessor scheduling for real-time tasks using TCPN

We present an energy-efficient thermal-aware real-time global scheduler for a set of hard real-time (HRT) tasks running on a multiprocessor system. This global scheduler fulfills the thermal and temporal constraints by handling two independent variables, the task allocation time and the selection of clock frequency. To achieve its goal, the proposed scheduler is split into two stages. An off-line stage, based on a deadline partitioning scheme, computes the cycles that the HRT tasks must run per deadline interval at the minimum clock frequency to save energy while honoring the temporal and thermal constraints, and computes the maximum frequency at which the system can run below the maximum temperature. Then, an on-line, event-driven stage performs global task allocation applying a Fixed-Priority Zero-Laxity policy, reducing the overhead of quantum-based or interval-based global schedulers. The on-line stage embodies an adaptive scheduler that accepts or rejects soft RT aperiodic tasks throttling CPU frequency to the upper lowest available one to minimize power consumption while meeting time and thermal constraints. This approach leverages the best of two worlds: the off-line stage computes an ideal discrete HRT multiprocessor schedule, while the on-line stage manage soft real-time aperiodic tasks with minimum power consumption and maximum CPU utilization.