The impact of armed conflict on cancer among civilian populations in low- and middle-income countries: a systematic review

Commitee On Publication Ethics ecancermedicalscience Submit article Articles Editorials Special issues Author interviews Category Sub-category Article type Volume Keyword Bookmark and Share Article metrics: 204 views https://doi.org/10.3332/ecancer.2020.1039 Abstract | Full Article | PDF Review The impact of armed conflict on cancer among civilian populations in low- and middle-income countries: a systematic review Mohammed Jawad1, Christopher Millett1, Richard Sullivan2, Fadel Alturki3, Bayard Roberts4 and Eszter P Vamos1 1Public Health Policy Evaluation Unit, Imperial College London, Hammersmith, London W6 8RP, UK 2Institute of Cancer Policy, Cancer Epidemiology, Population and Global Health, King's College London and Guy's & St Thomas' NHS Trust, London, UK 3Faculty of Medicine, American University of Beirut, Lebanon 4Department of Health Services Research and Policy, London School of Hygiene and Tropical Medicine, London WC1H 9SH, UK Abstract Background: Armed conflicts are increasingly impacting countries with a high burden of cancer. The aim of this study is to systematically review the literature on the impact of armed conflict on cancer in low- and middle-income countries (LMICs). Methods: In November 2019, we searched five medical databases (Embase, Medline, Global Health, PsychINFO and the Web of Science) without date, language or study design restrictions. We included studies assessing the association between armed conflict and any cancer among civilian populations in LMICs. We systematically re-analysed the data from original studies and assessed quality using the Newcastle-Ottawa Scale. Data were analysed descriptively by cancer site. Results: Of 1,543 citations screened, we included 20 studies assessing 8 armed conflicts and 13 site-specific cancers (total study population: 70,172). Two-thirds of the studies were of low methodological quality (score <5) and their findings were often conflicting. However, among outcomes assessed by three or more studies, we found some evidence that armed conflict was associated with increases in the incidence and mortality of non-specific cancers, breast cancer and cervical cancer. Single studies reported a positive association between armed conflict and the incidence of stomach and testicular cancers, some as early as 3 years after the onset of conflict. Some studies reported a post-conflict impact on time to diagnosis. Conclusion: Our findings support the need for more rigorous longitudinal and cohort studies of populations in and immediately post-conflict to inform the development of basic packages of cancer services, and post-conflict cancer control planning and development

Modelling and analyzing adaptive self-assembling strategies with Maude

Building adaptive systems with predictable emergent behavior is a challenging task and it is becoming a critical need. The research community has accepted the challenge by introducing approaches of various nature: from software architectures, to programming paradigms, to analysis techniques. We recently proposed a conceptual framework for adaptation centered around the role of control data. In this paper we show that it can be naturally realized in a reflective logical language like Maude by using the Reflective Russian Dolls model. Moreover, we exploit this model to specify and analyse a prominent example of adaptive system: robot swarms equipped with obstacle-avoidance self-assembly strategies. The analysis exploits the statistical model checker PVesta

Model Checking Classes of Metric LTL Properties of Object-Oriented Real-Time Maude Specifications

This paper presents a transformational approach for model checking two important classes of metric temporal logic (MTL) properties, namely, bounded response and minimum separation, for nonhierarchical object-oriented Real-Time Maude specifications. We prove the correctness of our model checking algorithms, which terminate under reasonable non-Zeno-ness assumptions when the reachable state space is finite. These new model checking features have been integrated into Real-Time Maude, and are used to analyze a network of medical devices and a 4-way traffic intersection system.Comment: In Proceedings RTRTS 2010, arXiv:1009.398

Impact of residual hardware impairment on the iot secrecy performance of RIS-assisted NOMA networks

Non-orthogonal multiple access (NOMA) technology is expected to effectively improve the spectrum efficiency of fifth-generation and later wireless networks. As a new technology, reconfigurable Intelligent surfaces (RIS) can achieve high spectral and energy efficiency with a low cost in wireless networks. These are achieved by integrating a great quantity of low-cost passive reflective units (RUs) on the plane. In this article, in order to meet the needs of high efficiency, low power consumption, and wide coverage, we combine RIS-assisted NOMA technology with the internet of things (IoT). Because in the actual wireless communication system, the residual hardware impairment (RHI) characteristics of the actual transceiver equipment will have an important impact on system secrecy performance. Therefore, the study will propose a single eavesdropper RIS-assisted downlink NOMA system with RHI (E-RHI-RIS-NOMA). The study will also investigate the impact of RHI on the physical layer security (PLS) performance of the system and the closed-form expression of the user's secrecy outage probability (SOP) is derived. Finally, the simulation results show that 1) the main factors affecting the SOP are the quantity of RUs in RIS, the transmit SNR, and the target data rate, 2) it is proved that the hardware impairment of the transceiver harms the system's secrecy outage performance while the severity of the impact of RHI on the system performance depends on the transmit SNR and target data rate. Moreover, RHI at different nodes has a different influence on system secrecy performance. 3) the system performance of RIS relying on NOMA is improved compared with orthogonal multiple access (OMA) and conventional NOMA

Influence of maturity stages on postharvest physico-chemical properties of grapefruit (Citrus paradisi var. ‘Shamber Tarnab’) under different storage durations

The present study was conducted to evaluate the effect of maturity stages on the physicochemical characteristics of grapefruit (Citrus paradisi&nbsp;cv. ‘Shamber Tarnab’) under storage conditions for 60 days at ambient temperature (16±1 °C with 55-60% relative humidity). Grapefruits were harvested at different maturity stages, namely mature green (MG) and full ripe (FR). The fruits of both stages were assessed for different physical quality parameters at 15 days interval. The experimental results showed that ascorbic acid content, titratable acidity, fruit firmness, percent disease incidence was higher at FR stage. In contrast, weight loss, percent juice content, total soluble solid (TSS), and TSS/acid ratio at MG (mature green) were lower than that of FR fruits.&nbsp;Regarding storage durations, the fruit firmness, titratable acidity, percent juice content, ascorbic acid content decreased significantly, whilst total soluble solid, TSS/Acid ratio, weight loss, and percent disease incidence increased significantly with the extension of storage duration from 0 to 60 days. As concerned to its interactive effects, the highest ascorbic acid content, titratable acidity, percent juice content, and maximum fruit firmness were observed in fresh grapefruit, harvested at (MG) mature green stages, whereas the maximum total soluble solid, percent disease incidence, and TSS/Acid ratio were recorded in fruit harvested at (FR) full ripe stage, stored for 60 days at room temperature. Similarly, the Pearson’s Correlation Analysis (p&gt; 0.05) of grapefruit was positive effect for most of the quality traits of grapefruit at different storage durations and maturity stages. It was concluded that grapefruit could be harvested at the mature green stage (MG) for sustaining quality attributes up to 60 days of storage at room temperature

Sensor-Cloud Architecture: A Taxonomy of Security Issues in Cloud-Assisted Sensor Networks

The orchestration of cloud computing with wireless sensor network (WSN), termed as sensor-cloud, has recently gained remarkable attention from both academia and industry. It enhances the processing and storage capabilities of the resources-constrained sensor networks in various applications such as healthcare, habitat monitoring, battlefield surveillance, disaster management, etc. The diverse nature of sensor network applications processing and storage limitations on the sensor networks, which can be overcome through integrating them with the cloud paradigm. Sensor-cloud offers numerous benefits such as flexibility, scalability, collaboration, automation, virtualization with enhanced processing and storage capabilities. However, these networks suffer from limited bandwidth, resource optimization, reliability, load balancing, latency, and security threats. Therefore, it is essential to secure the sensor-cloud architecture from various security attacks to preserve its integrity. The main components of the sensor-cloud architecture which can be attacked are: (i) the sensor nodes; (ii) the communication medium; and (iii) the remote cloud architecture. Although security issues of these components are extensively studied in the existing literature; however, a detailed analysis of various security attacks on the sensor-cloud architecture is still required. The main objective of this research is to present state-of-the-art literature in the context of security issues of the sensor-cloud architecture along with their preventive measures. Moreover, several taxonomies of the security attacks from the sensor-cloud's architectural perspective and their innovative solutions are also provided

Formal Model Engineering for Embedded Systems Using Real-Time Maude

This paper motivates why Real-Time Maude should be well suited to provide a formal semantics and formal analysis capabilities to modeling languages for embedded systems. One can then use the code generation facilities of the tools for the modeling languages to automatically synthesize Real-Time Maude verification models from design models, enabling a formal model engineering process that combines the convenience of modeling using an informal but intuitive modeling language with formal verification. We give a brief overview six fairly different modeling formalisms for which Real-Time Maude has provided the formal semantics and (possibly) formal analysis. These models include behavioral subsets of the avionics modeling standard AADL, Ptolemy II discrete-event models, two EMF-based timed model transformation systems, and a modeling language for handset software.Comment: In Proceedings AMMSE 2011, arXiv:1106.596

Modeling Dynamic Spatio-Temporal Correlations for Urban Traffic Flows Prediction

Prediction of traffic crowd movement is one of the most important component in many applications' domains ranging from urban management to transportation schedule. The key challenge of citywide crowd flows prediction is how to model spatial and dynamic temporal correlation. However, in recent years several studies have been done, but they lack the ability to effectively and simultaneously model spatial and temporal dependencies among traffic crowd flows. To address this issue, in this article a novel spatio-temporal deep hybrid neural network proposed termed STD-Net to forecast citywide crowd traffic flows. More specifically, STD-Net contains four major branches, i.e., closeness, period volume, weekly volume, and external branches, respectively. We design a residual neural network unit for each property to depict the spatio-temporal features of traffic flows. For various branches, STD-Net provides distinct weights and then combines the outputs of four branches together. Extensive experiments on two large-scale datasets from New York bike and Beijing taxi have demonstrated that STD-Net achieves competitive performances the existing state-of-the-art prediction baselines

Targeting Kaposi’s sarcoma associated herpesvirus encoded protease (ORF17) by a lysophosphatidic acid molecule for treating KSHV associated diseases

Kaposi’s sarcoma associated herpesvirus (KSHV) is causative agent of Kaposi’s sarcoma, Multicentric Castleman Disease and Pleural effusion lymphoma. KSHV-encoded ORF17 encodes a protease which cleaves -Ala-Ala-, -Ala-Ser- or -Ala-Thr-bonds. The protease plays an important role in assembly and maturation of new infective virions. In the present study, we investigated expression pattern of KSHV-encoded protease during physiologically allowed as well as chemically induced reactivation condition. The results showed a direct and proportionate relationship between ORF17 expression with reactivation time. We employed virtual screening on a large database of natural products to identify an inhibitor of ORF17 for its plausible targeting and restricting Kaposi’s sarcoma associated herpesvirus assembly/maturation. A library of 307,814 compounds of biological origin (A total 481,799 structures) has been used as a screen library. 1-oleoyl-2-hydroxy-sn-glycero-3-phospho-(1′-myo-inositol) was highly effective against ORF17 in in-vitro experiments. The screened compound was tested for the cytotoxic effect and potential for inhibiting Kaposi’s sarcoma associated herpesvirus production upon induced reactivation by hypoxia, TPA and butyric acid. Treatment of reactivated KSHV-positive cells with 1-oleoyl-2-hydroxy-sn-glycero-3-phospho-(1′-myo-inositol) resulted in significant reduction in the production of Kaposi’s sarcoma associated herpesvirus. The study identified a lysophosphatidic acid molecule for alternate strategy to inhibit KSHV-encoded protease and target Kaposi’s sarcoma associated herpesvirus associated malignancies