Nano-networks communication architecture: Modeling and functions

Nano-network is a communication network at the Nano-scale between Nano-devices. Nano-devices face certain challenges in functionalities, because of limitations in their processing capabilities and power management. Hence, these devices are expected to perform simple tasks, which require different and novel approaches. In order to exploit different functionalities of Nano-machines, we need to manage and control a set of Nano-devices in a full Nano-network using an appropriate architecture. This step will enable unrivaled applications in the biomedical, environmental and industrial fields. By the arrival of Internet of Things (IoT) the use of the Internet has transformed, where various types of objects, sensors and devices can interact making our future networks connect nearly everything from traditional network devices to people. In this paper, we provide an unified architectural model of Nano-network communication with a layered approach combining Software Defined Network (SDN), Network Function Virtualization (NFV) and IoT technologies and present how this combination can help in Nano-networks’ context. Consequently, we propose a set of functions and use cases that can be implemented by Nano-devices and discuss the significant challenges in implementing these functions with Nano-technology paradigm and the open research issues that need to be addressed.Peer ReviewedPostprint (published version

Machine learning models for traffic classification in electromagnetic nano-networks

The number of nano-sensors connected to wireless electromagnetic nano-network generates different traffic volumes that have increased dramatically, enabling various applications of the Internet of nano-things. Nano-network traffic classification is more challenging nowadays to analyze different types of flows and study the overall performance of a nano-network that connects to the Internet through micro/nanogateways. There are traditional techniques to classify traffic, such as port-based technique and load-based technique, however the most promising technique used recently is machine learning. As machine learning models have a great impact on traffic classification and network performance evaluation in general, it is difficult to declare which is the best or the most suitable model to address the analysis of large volumes of traffic collected in operational nano-networks. In this paper, we study the classification problem of nano-network traffic captured by micro/nano-gateway, and then five supervised machine learning algorithms are used to analyze and classify the nano-network traffic from traditional traffic. Experimental analysis of the proposed models is evaluated and compared to show the most adequate classifier for nano-network traffic that gives very good accuracy and performance score to other classifiers.This work was supported in part by the ‘‘Agencia Estatal de Investigación’’ of ‘‘Ministerio de Ciencia e Innovación’’ of Spain under Project PID2019-108713RB-C51/MCIN/AEI/10.13039/501100011033, and in part by the ‘‘Agència de Gestió d’Ajuts Universitaris i de Recerca’’ (AGAUR) of the ‘‘Generalitat de Catalunya’’ under Grant 2021FI_B2 00091.Postprint (published version

Obesity and hypertension in an Iranian cohort study; Iranian women experience higher rates of obesity and hypertension than American women

BACKGROUND: Once considered as the main public health problem in developed countries, obesity has become a major problem throughout the world and developing countries, like Iran, are joining the global obesity pandemic. We determined the prevalence of overweight, obesity, and hypertension in a large cohort of Iranians and compared age-adjusted rates with the rates in the US. METHODS: Golestan Cohort Study is a population-based study of 8,998 men and women, aged 35-81 years, from urban and rural areas. Anthropometric parameters were measured by interviewers. Prevalence rates were directly adjusted to the 2000 United States standard population. RESULTS: The age-adjusted prevalence rates of overweight (BMI ≥ 25 kg/m2) and obesity (BMI ≥ 30 kg/m2) in this Iranian population were 62.2% and 28.0%, respectively. Both overweight and obesity were more common in women than men. Age-adjusted prevalence of overweight was significantly higher in Iranian women compared to the American women (68.6% vs. 61.6%), while the age-adjusted prevalence of obesity is closer in these two populations (34.9% vs. 33.2%). Iranian men—compared to American men—had significantly lower age-adjusted prevalence of overweight (53.7% vs. 68.8%) and obesity (16.2% vs. 27.5%). Age-adjusted prevalence of hypertension was higher in Iranian women than American women (35.7% vs. 30.5%). Diabetes mellitus was reported in 6.2% of participants. Mean waist-to-hip ratio (WHR) among women was 0.96. Smoking rates in men and women were 33.2% and 2.2%, respectively. CONCLUSION: The prevalence of obesity, overweight, and hypertension in Iran is as high as the US. However, Iranian women are more obese than American women and Iranian men are less obese than their American counterparts. This discrepancy might be due to the low rate of smoking among Iranian women. Iranian women have higher mean WHR than what WHO has defined in 19 other populations

Impact of opioid-free analgesia on pain severity and patient satisfaction after discharge from surgery: multispecialty, prospective cohort study in 25 countries

Background: Balancing opioid stewardship and the need for adequate analgesia following discharge after surgery is challenging. This study aimed to compare the outcomes for patients discharged with opioid versus opioid-free analgesia after common surgical procedures.Methods: This international, multicentre, prospective cohort study collected data from patients undergoing common acute and elective general surgical, urological, gynaecological, and orthopaedic procedures. The primary outcomes were patient-reported time in severe pain measured on a numerical analogue scale from 0 to 100% and patient-reported satisfaction with pain relief during the first week following discharge. Data were collected by in-hospital chart review and patient telephone interview 1 week after discharge.Results: The study recruited 4273 patients from 144 centres in 25 countries; 1311 patients (30.7%) were prescribed opioid analgesia at discharge. Patients reported being in severe pain for 10 (i.q.r. 1-30)% of the first week after discharge and rated satisfaction with analgesia as 90 (i.q.r. 80-100) of 100. After adjustment for confounders, opioid analgesia on discharge was independently associated with increased pain severity (risk ratio 1.52, 95% c.i. 1.31 to 1.76; P < 0.001) and re-presentation to healthcare providers owing to side-effects of medication (OR 2.38, 95% c.i. 1.36 to 4.17; P = 0.004), but not with satisfaction with analgesia (beta coefficient 0.92, 95% c.i. -1.52 to 3.36; P = 0.468) compared with opioid-free analgesia. Although opioid prescribing varied greatly between high-income and low- and middle-income countries, patient-reported outcomes did not.Conclusion: Opioid analgesia prescription on surgical discharge is associated with a higher risk of re-presentation owing to side-effects of medication and increased patient-reported pain, but not with changes in patient-reported satisfaction. Opioid-free discharge analgesia should be adopted routinely

Burnout among surgeons before and during the SARS-CoV-2 pandemic: an international survey

Background: SARS-CoV-2 pandemic has had many significant impacts within the surgical realm, and surgeons have been obligated to reconsider almost every aspect of daily clinical practice. Methods: This is a cross-sectional study reported in compliance with the CHERRIES guidelines and conducted through an online platform from June 14th to July 15th, 2020. The primary outcome was the burden of burnout during the pandemic indicated by the validated Shirom-Melamed Burnout Measure. Results: Nine hundred fifty-four surgeons completed the survey. The median length of practice was 10 years; 78.2% included were male with a median age of 37 years old, 39.5% were consultants, 68.9% were general surgeons, and 55.7% were affiliated with an academic institution. Overall, there was a significant increase in the mean burnout score during the pandemic; longer years of practice and older age were significantly associated with less burnout. There were significant reductions in the median number of outpatient visits, operated cases, on-call hours, emergency visits, and research work, so, 48.2% of respondents felt that the training resources were insufficient. The majority (81.3%) of respondents reported that their hospitals were included in the management of COVID-19, 66.5% felt their roles had been minimized; 41% were asked to assist in non-surgical medical practices, and 37.6% of respondents were included in COVID-19 management. Conclusions: There was a significant burnout among trainees. Almost all aspects of clinical and research activities were affected with a significant reduction in the volume of research, outpatient clinic visits, surgical procedures, on-call hours, and emergency cases hindering the training. Trial registration: The study was registered on clicaltrials.gov "NCT04433286" on 16/06/2020

Global, regional, and national burden of disorders affecting the nervous system, 1990–2021: a systematic analysis for the Global Burden of Disease Study 2021

BackgroundDisorders affecting the nervous system are diverse and include neurodevelopmental disorders, late-life neurodegeneration, and newly emergent conditions, such as cognitive impairment following COVID-19. Previous publications from the Global Burden of Disease, Injuries, and Risk Factor Study estimated the burden of 15 neurological conditions in 2015 and 2016, but these analyses did not include neurodevelopmental disorders, as defined by the International Classification of Diseases (ICD)-11, or a subset of cases of congenital, neonatal, and infectious conditions that cause neurological damage. Here, we estimate nervous system health loss caused by 37 unique conditions and their associated risk factors globally, regionally, and nationally from 1990 to 2021.MethodsWe estimated mortality, prevalence, years lived with disability (YLDs), years of life lost (YLLs), and disability-adjusted life-years (DALYs), with corresponding 95% uncertainty intervals (UIs), by age and sex in 204 countries and territories, from 1990 to 2021. We included morbidity and deaths due to neurological conditions, for which health loss is directly due to damage to the CNS or peripheral nervous system. We also isolated neurological health loss from conditions for which nervous system morbidity is a consequence, but not the primary feature, including a subset of congenital conditions (ie, chromosomal anomalies and congenital birth defects), neonatal conditions (ie, jaundice, preterm birth, and sepsis), infectious diseases (ie, COVID-19, cystic echinococcosis, malaria, syphilis, and Zika virus disease), and diabetic neuropathy. By conducting a sequela-level analysis of the health outcomes for these conditions, only cases where nervous system damage occurred were included, and YLDs were recalculated to isolate the non-fatal burden directly attributable to nervous system health loss. A comorbidity correction was used to calculate total prevalence of all conditions that affect the nervous system combined.FindingsGlobally, the 37 conditions affecting the nervous system were collectively ranked as the leading group cause of DALYs in 2021 (443 million, 95% UI 378–521), affecting 3·40 billion (3·20–3·62) individuals (43·1%, 40·5–45·9 of the global population); global DALY counts attributed to these conditions increased by 18·2% (8·7–26·7) between 1990 and 2021. Age-standardised rates of deaths per 100 000 people attributed to these conditions decreased from 1990 to 2021 by 33·6% (27·6–38·8), and age-standardised rates of DALYs attributed to these conditions decreased by 27·0% (21·5–32·4). Age-standardised prevalence was almost stable, with a change of 1·5% (0·7–2·4). The ten conditions with the highest age-standardised DALYs in 2021 were stroke, neonatal encephalopathy, migraine, Alzheimer's disease and other dementias, diabetic neuropathy, meningitis, epilepsy, neurological complications due to preterm birth, autism spectrum disorder, and nervous system cancer.InterpretationAs the leading cause of overall disease burden in the world, with increasing global DALY counts, effective prevention, treatment, and rehabilitation strategies for disorders affecting the nervous system are needed

Contribution to the system architecture design for electromagnetic nano-network communications

(English) A nano-network is a communication network at the nano-scale between nano-devices. Nanodevices face certain challenges in functionalities, because of limitations in their processing capabilities and power management due to their nano-scale size. One of these challenges is the ability to perceive partial or full routing tables, which are the main decision makers for data routing in legacy communication networks. The reason is that creating and updating routing tables continuously require adequate processing power with sufficient memory and computing capabilities, which is not the case with nano- devices. Hence, these devices are expected to perform simple tasks, which equire different and novel approaches. In order to exploit the different functionalities of nano-machines, a set of nano-devices in a full nano-network needs to be managed and controlled using an appropriate architecture. This step will enable unrivaled applications in different fields. An Electromagnetic (EM) nano-network is a type of nano-communication that uses terahertz (THz) EM waves in communication. Nano-network has attracted increasing attention in recent years. Consequently, several developments have been achieved in the fabrication, communication and management of various EM nano network devices serving potential applications ranging from software- defined metamaterials, wireless robotic materials and body-centric communication. Such applications need uplink and downlink communication between the deployed nano-network and the external macro- world or the Internet through nano-interfaces. This causes heterogeneity and interoperability in different Internet of Nano-things (IoNT) applications, which become new challenges for nano-network communication. In this regard, dynamic, flexible and distributed micro/nano gateways can accommodate such sustainable issues and make the nano-network fully operational, regardless of the adopted application domain or the protocols used in communication. With the arrival of the Internet of Things (IoT), the use of the Internet has transformed, where various types of objects, sensors and devices can interact, making future networks connect nearly everything from traditional network devices to people. It is worth remarking that Software Defined Networking (SDN) and Network Function Virtualization (NFV) are two useful technologies for IoT. By outlining the way of combining SDN, NFV, IoT and fog computing technologies altogether, nano- network can overcome its challenges and limitations. The main objective of this thesis is to contribute to the system architectural design of EM nano- networks by developing an operational communication architecture to allow nano-machines to access the Internet. This communication architecture uses next-generation network technologies such as IoT and fog computing, besides well-known virtualization network technologies such as SDN and NFV to guarantee such accessibility. In addition, this communication architecture will provide added value to the data routing in the nano-network paradigm, whether inside the nano-domain or towards the macro- domain by providing virtualization and externalization of the complex routing decisions to be compiled externally on a powerful data center hosted on the cloud. The nano-machines will be able to access the cloud with the aid of smart hybrid devices called micro/nano-gateways, which provide two-way communication between nano-machines and the cloud. This two-way communication allows the end-user to easily control and manage a group of nanomachines expanding various applications in different fields. Moreover, it allows the nano-machines to store their measurements on the cloud, providing very large sets of data that are generated by a variety of nano-sensors/actuators forming big data, where Machine Learning (ML) approaches are used to perform complex analysis, intelligent judgments and creative problem solving on this big data extracting valuable information.(Español) Una nano-red es una red de comunicaciones a la escala nano, entre nano-dispositivos. Los nano-dispositivos afrontan determinados desafíos en funcionalidades, debido a las limitaciones de sui capacidad de procesado y la gestión de energía derivado de su nano-tamaño. Uno de estos desafíos es su capacidad de obtener una tabla de rutas parcial o completa, que es uno de los grandes puntos de decisión para el encaminamiento en redes de comunicaciones. La razón se encuentra en la dificultad y esfuerzo necesario para crear y actualizar continuamente las tablas, en términos de energía, memoria y capacidades de cómputo. En consecuencia, estos dispositivos únicamente efectuarán tareas sencillas, para las que se van a necesitar nuevas propuestas. Con el fin de aprovechar las funcionalidades de las nano-máquinas, un conjunto de nano-dispositivos en una nano-red completa necesita de mecanismos de gestión y control, a través de una arquitectura adecuada. Con ello, se podrán proporcionar nuevas aplicaciones en diversos campos. Una nano-red electromagnética (EM) es un tipo de nano-comunicación que emplea ondas en la banda de Teraherzios (THz). Las nano-redes han sido objeto de creciente atracción en los últimos años. En consecuencia, se han conseguido diversos desarrollos en la fabricación, comunicación y gestión con varios dispositivos en nano-redes EM, para aplicaciones desde metamateriales definidos por software, materiales robóticos wireless y comunicaciones en el cuerpo. Tales aplicaciones necesitan comunicaciones en sentido de subida y bajada, entre la nano-red desplegada y el macro-mundo externo, o Internet, a través de nano-interfaces. Ello causa heterogeneidad e inter-operabilidad en diversas aplicaciones de la Internet de las Nano-Things (IoNT), que constituyen nuevos desafíos para las comunicaciones en nano-redes. En este sentido, micro/nano gateways que sean dinámicos, flexibles y distribuidos, han de poder facilitar el acomodo de dichas aplicaciones y hacer que la red sea completamente operacional, independientemente del dominio de aplicaciones usadas o los protocolos de comunicaciones. Con la llegada de la Internet of Things (IoT), el uso de Internet se ha transformado, donde varios tipos de objetos, sensores y dispositivos pueden interactuar, haciendo que las futuras redes puedan conectar prácticamente cualquier cosa. Software Defined Networking (SDN) y Network Function Virtualization (NFV) son 2 tecnologías relevantes para IoT. Por medio de la combinación de SDN, NFV, IoT y fog computing, las nano-redes pueden solventar sus desafíos y limitaciones. El principal objetivo de esta tesis es contribuir al diseño de la arquitectura del sistema de las nano-redes EM por medio del desarrollo de una propuesta operacional que permita el acceso a Internet a las nano-máquinas Esta arquitectura de comunicaciones emplea las tecnologías de IoT y Fog Computing, además de las conocidas tecnologías de virtualización basadas en SDN y NFV. Además, la arquitectura de comunicaciones proporcionará un valor añadido al encaminamiento en el paradigma de la nano-red, ya sea dentro del nano-dominio o hacia el macro-dominio, por medio de virtualización y externalización de las decisiones complejas de encaminamiento, que serán compiladas externamente en un centro de datos situado en la nube. Las nano-máquinas serán capaces de acceder a la nube con la ayuda de dispositivos híbridos inteligentes denominados micro/nano gateways, que podrán proporcionar comunicaciones completas entre las nano-máquinas y la nube. De esta manera, el usuario final podrá controlar y gestionar un grupo de nano-máquinas y facilitar la creación de aplicaciones en diversos campos. Además, permite a las nano-máquinas almacenar su información en la nube, proporcionando grandes conjuntos de información, big-data, donde estrategías de Machine Learning (ML) se pueden usar para resolver diversos problemas complejos.Postprint (published version

Nano-networks communication architecture: Modeling and functions

Nano-network is a communication network at the Nano-scale between Nano-devices. Nano-devices face certain challenges in functionalities, because of limitations in their processing capabilities and power management. Hence, these devices are expected to perform simple tasks, which require different and novel approaches. In order to exploit different functionalities of Nano-machines, we need to manage and control a set of Nano-devices in a full Nano-network using an appropriate architecture. This step will enable unrivaled applications in the biomedical, environmental and industrial fields. By the arrival of Internet of Things (IoT) the use of the Internet has transformed, where various types of objects, sensors and devices can interact making our future networks connect nearly everything from traditional network devices to people. In this paper, we provide an unified architectural model of Nano-network communication with a layered approach combining Software Defined Network (SDN), Network Function Virtualization (NFV) and IoT technologies and present how this combination can help in Nano-networks’ context. Consequently, we propose a set of functions and use cases that can be implemented by Nano-devices and discuss the significant challenges in implementing these functions with Nano-technology paradigm and the open research issues that need to be addressed.Peer Reviewe

Probability-based path discovery protocol for electromagnetic nano-networks

© . This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/One of the major challenges for nano-network is the forfeit of communication protocols to exploit the potential communication between nano-machines forming fully operational nano-network. Because nano-machines face some restrictions such as limited processing power and confined computing capabilities, up-to-date nano-machines cannot perceive partial or full routing tables, which are the main decision-makers for data routing in legacy communication networks. The reason is that creating and updating routing tables continuously require adequate processing power with sufficient memory and computing capabilities, which is not the case of nano-nodes. So, new innovative routing schemes have to be proposed for nano-networks to deal with such extremely low resources. This paper focuses on decoupling the routing intelligence from nano-network towards a computational architecture using Software Defined Networking (SDN) and Network Function Virtualization (NFV) technologies by externalizing routing decisions and complex computations from nano-nodes to be fully compiled externally. Moreover, the paper proposes a probability-based path discovery protocol denoted by (PBPD) for electromagnetic nano-nodes suitable for dynamic nano-network applications. The performance of the proposed protocol is evaluated and compared with other routing protocols discussed in the literature. The proposed scheme provides low energy consumption inside nano-nodes and low computational complexity thanks to SDN/NFV system.This work has been supported by the ”Ministerio de Economía y Competitividad” of the Spanish Government under project TEC2016-76795-C6-1-R, AEI/FEDER UE and ”Agència de Gestió d’Ajuts Universitaris i de Recerca” (AGAUR) of the ”Generalitat de Catalunya” under FI-AGAUR grant number 2019FI-B00056.Peer ReviewedPostprint (author's final draft

SDN-based gateway architecture for electromagnetic nano-networks

Electromagnetic nano-communication has increasing attention in recent years. Several developments have been achieved in the fabrication, communication and management of various nano-network devices serving potential applications ranging from software-defined metamaterials, wireless robotic materials and body-centric communication. Such applications need uplink and downlink communication between the deployed nano network and the external macro-world or the Internet through nano-interfaces. As a result, heterogeneous nano-network devices and their interoperability in different Internet of nano-things applications become new challenges for nano-network communication. In this regard, dynamic, flexible and distributed micro/nanogateways can accommodate such sustainable issues and make the nano-network fully operational, regardless of the adopted application domain or the protocols used in communication. Network functions virtualization and software-defined networking technologies altogether can overcome these challenges. This article proposes SDNbased architecture and software module for the micro/nano-gateway. The proposed software module converts data formats and protocols between nano-network and traditional network domains allowing the nano-devices to be linked to the Internet. A prototype of the module is built, and the performance of the proposed algorithm is evaluated based on two communication scenarios; single tenant and multitenant. The result shows the effect of the total number of connected nano-devices and the number of packets sent by each device on the total average round-trip processing delay and the overall throughput of the micro/nano-gateway