Opportunistic Spectrum Research Articles

Nurse coaching improves healthy conditions: an integrative review of the literature

Coaching has become a popular strategy in a complex environment. Nurses who incorporate coaching into their professional practice broaden their skills and opportunities in the entire spectrum of health, wellness, and healing. The aim was to illustrate and compare coaching models and to address their relevance in health promotion. A literature review from 2010 to 2019, retrieved from MEDLINE, reference tracking, and consultation of academic networks, has led to peer-reviewed articles on coaching models for health promotion. A total of 70 articles were found, 45 of which were excluded because too generic and not specific to the clinical nursing field. Finally, only 15 articles that well respected the inclusion criteria have been selected. The implementation of coaching can be seen in several health care fields, especially in nursing, to enhance health by empowering individuals.

Machine learning supervised antenna for software defined cognitive radios

ABSTRACT Software-defined radio (SDR) deals with the opportunistic detection and allocation of the radio frequency (RF) signals in the cognitive radio network (CRN). The opportunistic spectrum use between primary licenced and secondary unlicensed user depends upon the adequate detection of the spectrum hole. This paper presents a design of a smart compact wideband patch antenna for SDR in cognitive radios. The fractal slot antenna with electromagnetic bandgap structure is designed on 12 × 18 mm2 FR4 substrate as a primary perception module in the cognitive radio sensor network. The wide operating range of antenna 0.68–12.1 GHz is highly compatible with adaptive learning of SDR to deal with dynamic spectrum variation over a large bandwidth. The antenna exhibits high radiation efficiency with consideration of tangential losses of FR4 and sustainable gain 2.5 dBi over the complete impedance bandwidth. The proposed five-layered ANN-ML supervised SDR comprises multispectral resolution via coefficient estimation for primary and secondary user and elicits high throughput of proposed antenna during white space spectrum sensing. The data analytics for ANN-ML has modelled on Python 3.0 IDE and the results are validated to justify the candidature of the antenna for wideband sensing as per the Federal Communications Commission standards for CRN.

Bell Peppers (Capsicum annum L.) Losses and Wastes: Source for Food and Pharmaceutical Applications.

Currently, the high added-value compounds contained in plant by-products and wastes offer a wide spectrum of opportunities for their reuse and valorization, contributing to the circular economy. The bell pepper (Capsicum annum L.) is an exotic vegetable with high nutritional value that, after processing, leaves wastes (peel, seeds, and leaves) that represent desirable raw material for obtaining phytochemical compounds. This review summarizes and discusses the relevant information on the phytochemical profile of bell peppers and their related biological properties as an alternative to revalorize losses and wastes from bell peppers for their application in the food and pharmaceutical industries. Bell pepper fruits, seeds, and leaves contain bioactive compounds (phenols, flavonoids, carotenoids, tocopherol, and pectic polysaccharides) that exhibit antioxidant, antibacterial, antifungal, immunosuppressive and immunostimulant properties, and antidiabetic, antitumoral and neuroprotective activities, and have a potential use as functional food additives. In this context, the revalorization of food waste is positioned as a technological and innovative research area with beneficial effects for the population, the economy, and the environment. Further studies are required to guarantee the safety use of these compounds and to understand their mechanisms of action.

MP21-11 A FELLOW'S FATE: OUTCOMES OF ANDROLOGY FELLOWSHIP TRAINING

INTRODUCTION AND OBJECTIVE:Post graduate fellowships involve a spectrum of training opportunities that include reproductive and sexual medicine. Herein we seek to develop metrics defining the outco...

Energy-Efficient Cross-Layer Spectrum Sharing in CR Green IoT Networks

Internet-of-Things (IoT) aims to connect intelligent things to the Internet, enable thing-to-everything communication, and sustainability sensing and control. However, the exponential increase of connected IoT devices is resulting in tremendous demand on the limited spectrum. Cognitive radio (CR) technology is envisioned to be one of the main enabling technology for efficient IoT deployment. CR offers huge spectrum opportunities for sustainable green IoT devices by opportunistically utilizing the idle licensed bands. Since most green IoT devices are expected to be sensor nodes with limited energy sources, efficient communication protocols for CR-based IoT sensor networks are needed. This paper proposes an efficient cross-layer design consisting of joint optimization of the modulation order as a physical-layer parameter and the backoff probability as a MAC-layer parameter with the objective of minimizing the energy consumption in the CR-based green IoT networks subject to IoT delay guarantees, licensed primary radio (PR) channel availability and PR user activities. Simulation results reveal that the proposed cross-layer design has significantly reduced energy consumption while achieving the delay requirements in the network compared to the physical-layer-only and MAC-layer-only adaptation schemes.

Karen Layou: A Wider 2-Year Track

Supporting geoscience education across a spectrum of opportunities.

Parent Education Beyond Learning: An Ethnographic Exploration of a Multi‐family Program for Families in Post‐divorce Conflict

The paper builds on ethnographic, qualitative research that explores the ‘No Kids in the Middle’ program for high‐conflict divorce families, as practiced in the Agder region of South Norway. Parent education programs targeting parents in divorce are generally found to be ‘effective’ in the sense that parents learn about the pitfalls of conflict and become socialised into less negative patterns of co‐parenting. However, a narrow understanding of the potential of such programs as vehicles for the transfer of knowledge fails to attend to the relational sides of both education and therapy, and the existential sides of parenthood. Drawing on Gert Biesta’s articulation of education as a process working along three dimensions of purpose, the paper approaches the ‘No Kids in the Middle’ program as an educational practice. It aims to explore whether the educational ambitions of the ‘No Kids in the Middle’ program should be understood primarily in the general terms of qualification (i.e., parents acquiring knowledge and skills) and socialisation (i.e., parents gaining a specific orientation toward a set of norms and values), or if there were practices or elements that seemed directed at subjectification or bringing the ‘I’ of each parent into play. Analysing field notes from participant observation in a ‘No Kids in the Middle’ multi‐family group and interviews with parents, therapists, judges, and child welfare caseworkers, the paper concludes that programs like ‘No Kids in the Middle’ provide a broad spectrum of educational opportunities. While some of these might be intended to instruct along pre‐defined normative paths toward understanding and behaviour, such practices can also be seen as addressing parents in a different, more existential, way. In the particular local practice studied, the dimension of subjectification was perhaps most clearly in play in the informal settings surrounding the program itself.

Deep learning-driven opportunistic spectrum access (OSA) framework for cognitive 5G and beyond 5G (B5G) networks

The evolving 5G and beyond 5G (B5G) wireless technologies are envisioned to provide ubiquitous connectivity and great heterogeneity in communication infrastructure by connecting diverse devices and providing multifarious services. Recently, the Internet of Things (IoT) and unmanned aerial vehicles (UAVs) are realized as an essential component of the upcoming 5G/B5G networks, enabling enhanced communication capacity, high reliability, low latency, and massive connectivity. However, one limiting factor in the expansion of 5G/B5G technology is the finite radio spectrum, which necessitates managing the anticipated spectrum crunch for future wireless networks. One potential solution is to develop intelligent cognitive methods to dynamically optimize the use of spectrum in 5G/B5G networks to solve the imminent problem of spectrum congestion and improve radio efficiency. This paper addresses the opportunistic spectrum access (OSA) problem in the 5G/B5G cognitive radio (CR) network of IoTs and UAVs through the novel deep learning-based detector, dubbed as Deep-CRNet. The proposed detector employs residual connections with cascaded multi-kernel convolutions to identify the primary user (PU) spectrum usage by extracting the inherent multi-scale signal and noise features in the sensed transmission patterns. Thereby, Deep-CRNet intelligently learns and locates the spectrum holes so that secondary users (SUs) and PUs can dynamically share network spectrum resources. The efficacy of Deep-CRNet is validated through simulation results, where it achieved 99.74% accuracy with 99.65% precision and 99.83% recall in accurately classifying the PU status. In addition, the average correct detection probability of Deep-CRNet in the low signal-to-noise ratio (−20 dB to −15 dB) range is 38.21% higher than the second best-performing detector.

Chinese Industrial Policy: A Challenge for the European Union amid the Global Pandemic

The COVID-19 pandemic, which triggered lockdowns in Europe and around the world, had a major effect on European Union (EU) industries. Multiple supply chains in a variety of industries were disrupted, especially at the start of the crisis, and particularly in internationalized and complex value chains. Unparalleled policy responses have been undertaken in Europe and the world to mitigate the impact of this economic shock and help recovery. However, the pandemic has also created a wide spectrum of opportunities in many sectors of the global economy, as consumers and businesses have changed radically their behavior. Under this context, superpowers such as the People’s Republic of China have taken constructive steps to facilitate the digital transformation of their industry leaving behind United States and the European Union. The purpose of this policy brief is the provision of an overview of China’s national strategic plan titled “Made in China 2025” and its fundamental pillars as well as the development of policy recommendations regarding strengthening European Union’s industrial policy amid the global pandemic.

Evaluation of the Effects of Compressive Spectrum Sensing Parameters on Primary User Behavior Estimation

As the Internet of Things (IoT) technology is being deployed, the demand for radio spectrum is increasing. Cognitive radio (CR) is one of the most promising solutions to allow opportunistic spectrum access for IoT secondary users through utilizing spectrum holes resulting from the underutilization of frequency spectrum. A CR needs to frequently sense the spectrum to avoid interference with primary users (PUs). Compressive spectrum sensing techniques have been gaining increasing interest in wideband spectrum sensing, as they reduce the need for high-rate analog-to-digital converters, reducing the complexity and energy requirements of the CR. In order to enhance spectrum sensing performance, researchers proposed to incorporate PU spectrum usage information into the process of spectrum sensing. Spectrum usage information can be obtained through pilot signals, geo-locational databases or through evaluation of previous spectrum sensing results. In this paper, we are studying the effects of compressive sensing parameters namely compression ratio, sensing period, and sensing duration on the estimation of primary user behavior statistics. We achieved an accurate estimation of the primary user's behavior while saving 40% of the sampling rate by using compressive spectrum sensing compared to traditional spectrum sensing with Nyquist rate sampling.

Supporting the vital role of boundary-spanning physician researchers in the advancement of medical innovation

A wide range of stakeholders recognise that physicians play a vital role in medical innovation and, in particular, the importance of boundary-spanning engagement between physicians and industry in clinical research. While UK physicians are keen to take part in research, this article draws on a range of literature to identify apparent and anticipated challenges that discourage or prevent cross-sector engagement by physician researchers. To encourage greater interaction and exploration of associated support mechanisms, we present a full spectrum of engagement modes, funding opportunities and illustrative initiatives, showing how different stakeholders (from government institutions, charities, professional bodies and industry) can contribute to improving the engagement of physicians in boundary spanning research. We emphasise the importance of mutual understanding, trust and commonly shared practices, as well as adequate resources, to encourage these vital interactions.

A Centralized Model Enabling Channel Reuse for Spectrum Allocation in Cognitive Radio Networks

Abstract Cognitive Radio (CR) is an advanced technology, which intends to boost the radio spectrum utilization. On perceiving the spectrum holes, next there is a need to provide a fair distribution of the vacant licensed channels amongst Secondary Users (SUs) during the spectrum allocation process. In this context, our paper introduces two allocation models to resolve the spectrum allocation problem. Initially, we design a simple centralized model to assign the channels. Then, we extend it to a centralized fair allocation model that aims to impart a better utilization of the free channels. Both approaches assign a common channel to a group of non-interfering SUs simultaneously. This facilitates spectrum reuse. The constraint related to dynamics in spectrum opportunities in CR is handled during channel allocation. Simulation study analyzes the proposed approaches with an existing allocation mechanism and reveals the performance improvement of centralized fair allocation model in terms of spectrum utilization.

Innovative Local Policies in Portuguese Low-Density Rural Areas

Abstract Nowadays, the issue of rural development has a central place on the agenda of policy-makers, prompting a discussion on the instrumental and procedural options of public policies. This paper seeks to contribute to the reflection on the potentialities and limitations of promoting rural development based on innovative strategies sustained by territorial governance modalities, which entail an active involvement of local agents, especially local authorities. For this, it takes as case studies three public policy experiences led by local authorities within a Portuguese low-density region, with one of the lowest development rates among EU regions. Specifically, it aims to discuss: (a) the effectiveness of adopting innovative policies in the context of low-density rural areas; and (2) the role of territorial governance in the success of those policies. The research followed a document analysis and interviews with local development actors. The analysis suggests that peripheral rural areas are not condemned to human desertification. There is a wide spectrum of opportunities for these areas. They can bring together a strategic view of the future, and an institutional leadership capable of dynamizing an adjusted territorial governance model. This is the challenge currently facing rural development policy.

MBSO Algorithm For Handling Energy-Throughput Trade-Off In Cognitive Radio Networks

Abstract Cognitive Radio network (CRN) depends on opportunistic spectrum access and spectrum sensing for improving the wireless networks’ spectrum efficiency. Since throughput maximization can result in high-energy consumption, the spectrum sensing technique should address the energy-throughput trade-off. The spectrum sensing time has to be determined by the considering the residual battery energies of each secondary user (SU). The primary user (PU) interference degrades the throughput of the entire network. Hence, the transmit power level should be determined by considering the PU interference and SU battery energy. This paper proposes the multi-objective brain storm optimization (MBSO) algorithm for handling energy-throughput trade-off in CRN. In this work, the sensing time is adaptively determined based on the residual battery energy of SUs, and the transmit power is determined based on the energy level of the PU signal and the residual battery energy of the SUs. A multi-objective optimization problem is formulated in order to maximize the throughput and minimize the packet error rate (PER) and is solved by applying the MBSO algorithm. Experimental results show that MBSO attains improved throughput, higher residual energy with lesser PER. The spectrum sensing performance is enhanced with higher probability of detection.

INTEGRATED VILLAGE TOURISM FOR RURAL SUSTAINABILITY AND DEVELOPMENT: A REVIEW OF VILLAGE TOURISM AND ITS IMPACT ON THE ENVIRONMENT AND SOCIETY OF KUMBALANGHI MODEL TOURISM VILLAGE

Tourism is a multi-faceted activity of economic, social, cultural, and environmental inputs which cut across other conventional sectors in the economy. Tourism creates more job opportunities for a wide spectrum of job seekers from the unskilled to the specialized, even in the remote parts of the country. Village tourism is among the most polymorphous of all forms of Special Interest Tourism [SIT]. It unveils the village life, art, culture, and heritage at its locations, thereby benefiting the local community economically and socially by interacting with tourists and the natives of the place for a more enriching tourism experience. It also gives opportunities to the guests to enjoy the unique culture of village life through participation in events, experiencing the local cuisine, and collecting the ethnic goods, which in turn can improve the welfare of the local people. This paper provides an overview of village tourism and the sustainable development of the rural ecosystem through integral activity and thereby understands the influence of tourism development among the local community and overall in Kumbalanghi village.

Spectrum-Agile Cognitive Radios Using Multi-Task Transfer Deep Reinforcement Learning

This work proposes a cognitive engine design that enables a radio to find transmission opportunities in non-contiguous wideband spectrum to avoid interference. The radio’s objective is to apply both frequency hopping and transmit power adjustment to maintain a required level of quality-of-service (QoS). The spectrum is partitioned into sub-bands each made of a number of narrowband channels. A multi-task deep Q-network (DQN) is utilized to solve the underlying problem where communications over each sub-band represents a single task. The proposed technique exploits transfer learning between tasks to speed up learning operation for new tasks. The proposed multi-task transfer DQN is proved to be converged. It is shown through simulations that the radio is able to learn an efficient strategy to evade interference signals in a partially observable environment. The experimental results indicate that the proposed approach offers up to 24% improvement to the percentage of successful communications when compared to other RL-based approaches found in existing literature.

A survey of current research trends and potential future directions in reproductive immunology clinical trials

Abstract Reproductive immunology is a relatively recent field with a wide spectrum of research opportunities. Within the reproductive system, immune system dysfunction has been suggested to contribute to a variety of conditions - such as endometriosis, infertility, recurrent miscarriage, preeclampsia, and preterm delivery. Although there is preliminary research supporting these possible connections, further studies are necessary. A survey was conducted of current clinical trials to show the current state of reproductive immunology research to assess needs in less researched conditions. The survey was performed by accessing the ClinicalTrials.gov registry. “Reproductive immunology” was entered into the database, and the following filters were applied: “recruiting,” “active, not recruiting,” and “enrolling by invitation.” 153 studies were obtained, and the associated conditions were counted for how many times they were listed. Similar conditions were combined into one category – e.g. different types of leukemias were categorized as “Leukemia.” Although the rate of new female breast cancer cases is significantly higher than the rate of new leukemias in the general population, this survey suggests reproductive immunology research is more focused on leukemia than breast cancer. Male and female reproductive/breast cancer/endometrial cancer/endometriosis (6.17%), autoimmune diseases (4.43%), and pregnancy/contraception (0.58%) are less frequently listed compared to leukemia (45.28%) and hematologic diseases (15.80%) in the clinical trials registry as associated conditions. This information can potentially guide future research towards less studied conditions in the relatively new field of reproductive immunology.

Energy efficiency of full-duplex cognitive radio in low-power regimes under imperfect spectrum sensing

This paper investigates the energy efficiency of a full duplex (FD) cognitive radio (CR) system in the low-power regime under a practical self-interference cancellation performance and imperfect spectrum sensing. We consider an opportunistic spectrum access network in which the secondary user (SU) is capable of self-interference suppression (SIS). The SIS ability enables the SU to work in simultaneous transmit and sense (TS) mode in order to increase the quality of channel sensing. Towards this goal, we first study the sensing performance, i.e., false-alarm and miss-detection probabilities, of the FD CR networks using TS, and compare the results with traditional half duplex (HD) CR systems using transmit only mode (TO). In the next step, we show that due to imperfect spectrum sensing, the secondary network channel is best characterized as a Gaussian-Mixture (GM) channel, which is widely used to capture the asynchronism in heterogeneous cellular networks. We then analytically characterize the low-signal-to-noise-ratio (low-SNR) metrics of the minimum energy per bit and wideband slope of the spectral-efficiency curve, and obtain these fundamental limits in closed-form. Furthermore, the characterization of these fundamental metrics allows us to identify practical signaling strategies that are optimally efficient in the low-SNR regime for the considered FD CR system. The benefits in terms of energy efficiency offered by FD CR over HD CR are also clearly demonstrated.

PRENATALINIS MUZIKINIS UGDYMAS LIETUVOJE: POVEIKIO NĖŠČIOSIOMS EMOCINIS ASPEKTAS

The article focuses on the emotional aspects of programs performed by institutions of prenatal music education (PME) in Lithuania and reveals how the content of this education helps pregnant women to experience positive emotions, especially joy, and overcome the increased nervousness and fear of childbirth. We conducted a study where fourteen respondents were interviewed: six women who during their pregnancy attended music education classes for future mothers (the musical educational health promotion school “Sveikutis”, Vilnius; and the studio of music therapy and meditation “Dabartis”, Klaipėda) and eight women who practiced musicianship independently. The experiences of these fourteen respondents of different age (from 20 to 45 years old at the time of pregnancy) and from different cities (Vilnius, Kaunas, Klaipėda, Panevėžys, Pasvalys and Šiauliai) has revealed that all women who during their pregnancy practiced musicianship had deep and significant experiences and felt the decrease of fear of childbirth. However, the women who attended music education classes had a larger spectrum of opportunities: they could play various instruments, perform additional and useful exercises, and receive more beneficial information, which allowed them to feel positive emotions more often. In addition, the women who attended PME classes claimed to achieve the connection with their unborn child faster and they rated their pregnancy with a higher grade concerning the smoothness of the period. It is significant that PME classes had a positive impact on the husbands of pregnant women as well – the received information encouraged soon to be fathers to communicate with their unborn children. The results of our study confirm that the PME classes in Lithuania promote the pregnant women’s positive emotions, especially experiencing joy, decrease the fear of childbirth, and also have a positive effect on couple’s relationships. KEYWORDS: , , , . DOI: http://dx.doi.org/

Scalable Service-Driven Database-Enabled Wireless Network Virtualization for Robust RF Sharing

Wireless virtualization has emerged as one of the efficient ways to overcome numerous wireless networking challenges such as resource sharing by allowing multiple concurrent virtual wireless networks having run on shared physical wireless infrastructure. Spectrum sharing in wireless networks focuses on increasing the usage efficiency of radio frequency (RF) spectrum with its increasing demand. To reduce uncertainties that accompany the spectrum sharing process caused by RF sensing, database-based spectrum sharing allows opportunistic spectrum access through occupancy information query of a spectrum database. In this article, we propose a 2-level hierarchical spectrum allocation framework for multiple service-based virtual networks (VN) by leasing wireless resources from Wireless Infrastructure Providers (WIPs). The framework leverages the software defined network (SDN)-enabled virtualization where network parameters are configured based on the operating environment on the fly. This article focuses on the competition between multiple VNs to get best RF channels to serve their users while eliminating the need for one-to-one contracts between VNs and WIPs. We develop a mathematical model for the spectrum allocation scheme which allows heterogeneous network configurations with better economic benefit. Using network segments formed based on available sharable resources, the allocation scheme is localized which makes the scalability of this scheme possible. A trust-based security mechanism is also proposed for early detection and prevention of security attacks to maintain the availability attribute of the resource allocation process. Simulation results show that spectrum sharing is efficient, and assures service availability to perceived legitimate VN users.