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Abstract Non-uniform, event-driven sampling of signals can be advantageous for different applications. In this paper, we focus on event-based sampling strategy for electricity metering purposes. Specifically, we propose an improvement in the enhanced event-driven metering (EDM) technique introduced by Simonov et al. Our solution provides additional flexibility on the types of measurements to be sent, by including the option to reduce the sending of consecutive measurements. Numerical results are presented for 4 different open databases of electricity consumption and consistently show that, in relation to the other options, our proposed strategy leads to both: (i) reduction in the amount of measurements sent, and (ii) improvements on the signal reconstruction by decreasing its reconstruction error. These two aspects are extremely useful in a scenario of massive deployment of measurement devices.
Abstract In flotation process, the efficiency and selectivity depend on mineralogy, particle size distribution and liberation, reagents added, mixing, and particle coverage. However, the kinetics of particle recovery is highly dependent on cell hydrodynamic and circuit configuration and operational strategy. Controlling froth depth and gas flow rate, measured as superficial gas velocity, is a straightforward alternative related to kinetics in the froth and collection zones. However, these parameters are not measured accurately. Froth depth measurement is based on a floating device coupled with a sonic sensor; this configuration presents hysteresis and deviation due to variation in the gas holdup and pulp density. In self-aspirated machines, there is no technology to measure gas velocity. To address this problem, the intelligent online gas dispersion sensor based on two concentric HDPE cylindres is proposed. The intelligent online gas dispersion sensor is based on two concentric HDPE cylinders. The methodology improves the accuracy of gas velocity calculation with a new algorithm. Froth depth measurement is based on two pressure transducers, reducing the uncertainty of the floating sonic sensor to 1 cm. Pulp bulk density is directly measured, and gas holdup can be estimated. Experimental results and industrial device validation indicate that the new intelligent system can measure superficial gas velocity (Jg) online and self-calibrate, with a 2% error, the froth depth error being ±1 cm. Therefore, a multiparameter sensor for measuring gas dispersion in industrial flotation cells was experimentally designed and validated in an industrial environment (TRL 8). In this context, the proposed online gas dispersion sensor emerges as a robust technology to improve the operation of the flotation process.
Abstract This paper focuses on the detection of utilization patterns in electricity residential consumption, which are closely related to the occupant characteristics (e.g. number, age, occupancy, and social class). Our goal is to identify groups of appliances that are often used together via their statistically relatedness. This relation might be obvious (as in TV and Home Theater), or not. The results can be used, for example, to guide a recommendations letter from the energy supplier to the final user, suggesting specific change of habits in order to improve the residence’s energy efficiency. We propose here a methodology for identifying patterns from a large sets of system status, which is a computationally hard task defined in R n with n being the number of appliances involved. The approach consist in the following steps: (i) the Principal Component Analysis method is employed to reduce the set dimensionality to R 3 with explained variance from 68% to 90% to guarantee minimum information loses, (ii) the k-means method to clustering appliances into different groups and (iii) the elbow method was used to define the best number of clusters for each house with explained variance of at least 93% and reaching more than 99% for the best k. Numerical tests using the UK-DALE dataset are presented to show the effectiveness of the proposed solution. The main contribution of this work is a method with low computational cost that requires no other information than a large set of reliable system status (binary vectors) to reveal utilization patterns in the residence.
Abstract This paper assesses different applied pattern recognition algorithms to decide the most appropriate power factor compensator for a particular point of common coupling. Power factor, current unbalance factor, total demand distortion, voltage harmonic distortion and reactive power daily variation, as well as human expertise, are the key parameters used to set each recognition algorithm. These algorithms are then trained with a series of both simulation and experimental data. Numerical results consistently indicate the decision-tree algorithm with depth 20 as the best classifier for power factor improvement in terms of all metrics considered in this work.
Abstract This paper provides a tutorial on the most recent advances of event-driven metering (EDM) while indicating potential extensions to improve its performance. We have revisited the effects on signal reconstruction of (i) a fine-tuned procedure for defining power variation events, (ii) consecutive-measurements filtering that refers to the same event, (iii) spike filtering, and (iv) timeout parameter. We have illustrated via extensive numerical results that EDM can provide high-fidelity signal reconstruction while decreasing the overall number of acquired measurements to be transmitted. Its main advantage is to only store samples that are informative based on predetermined events, avoiding redundancy and decreasing the traffic offered to the underlying communication network. This tutorial highlights the key advantages of EDM and points out promising research directions.
Abstract Connectivity in low-density rural and remote areas where distances are long is a big challenge because of high deployment costs and challenging radio channels with long delay profiles. Spectrum sharing can make spectrum available for 5G local network deployments to serve rural and remote areas. Spectrum sensing can be used to complement the traditional database approach in order to enable efficient and dynamic use of the radio spectrum. In rural and remote areas, long range coverage is required in order to enable flexible and cost-effective solutions. This calls for efficient and low-complex sensing methods who are able to operate in those challenging environments. In this paper we study spectrum sensing method called the window-based (WIBA) energy detector in a challenging rural area channel model for 5G networks. The results are compared to that of the localization algorithm based on double-thresholding (LAD) energy detector. Simulations using a rural area channel model with long delay profile indicated that the WIBA method is able to operate in a rural area channel, and it clearly outperforms the LAD method in terms of detection distance. The detection difference was even 15-fold for the WIBA method, depending on the transmit power and the signal bandwidth.
In this paper, we introduce a new fading model which is capable of characterizing both the shadowing of the dominant component and composite shadowing which may exist in wireless channels. More precisely, this new model assumes a κ-μ envelope where the dominant component is fluctuated by a Nakagami-m random variable (RV) which is preceded (or succeeded) by a secondary round of shadowing brought about by an inverse Nakagami-m RV. We conveniently refer to this as the double shadowed κ-μ fading model. In this context, novel closed-form and analytical expressions are developed for a range of channel related statistics, such as the probability density function, cumulative distribution function, and moments. All of the derived expressions have been validated through Monte-Carlo simulations and reduction to a number of well-known special cases. It is worth highlighting that the proposed fading model offers remarkable flexibility as it includes the κ-μ, η-μ, Rician shadowed, double shadowed Rician, κ-μ shadowed, κ-μ/inverse gamma and η-μ/inverse gamma distributions as special cases.
In this paper, we extensively investigate the way in which κ - μ fading channels can be impacted by shadowing. Following from this, a family of shadowed κ - μ fading models are introduced and classified according to whether the underlying κ - μ fading undergoes single or double shadowing. In total, we discuss three types of single shadowed κ - μ model (denoted Type I to Type III) and three types of double shadowed κ - μ model (denoted Type I to Type III). The taxonomy of the single shadowed Type I - III models is dependent upon whether the fading model assumes that the dominant component, the scattered waves, or both experience shadowing. Although the physical definition of the examined models make no predetermination of the statistics of the shadowing process, for illustrative purposes, two example cases are provided for each type of single shadowed model by assuming that the shadowing is influenced by either a Nakagami- m random variable (RV) or an inverse Nakagami- m RV. It is worth noting that these RVs have been shown to provide an adequate characterization of shadowing in numerous communication scenarios of practical interest. The categorization of the double shadowed Type I - III models is dependent upon whether a) the envelope experiences shadowing of the dominant component, which is preceded (or succeeded) by a secondary round of (multiplicative) shadowing, or b) the dominant and scattered contributions are fluctuated by two independent shadowing processes, or c) the scattered waves of the envelope are subject to shadowing, which is also preceded (or succeeded) by a secondary round of multiplicative shadowing. Similar to the single shadowed models, we provide two example cases for each type of double shadowed model by assuming that the shadowing phenomena are shaped by a Nakagami- m RV, an inverse Nakagami- m RV or their mixture. It is worth highlighting that the double shadowed κ - μ models offer remarkable flexibility as they include the κ - μ , η - μ , and the various types of single shadowed κ - μ distribution as special cases. This property renders them particularly useful for the effective characterization and modeling of the diverse composite fading conditions encountered in communication scenarios in many emerging wireless applications.
In this paper we present a study of boron-doped nc-Si:H films prepared by PECVD at high depositionpressure (>4 mbar), high plasma power and low substrate temperature (<200 C) using trimethylboron (TMB) as a dopant gas. The influence of deposition parameters on electrical, structural and optical propertiesis investigated. We determine the deposition conditions that lead to the formation of p-type nanocrystallinesilicon thin films with very high crystallinity, high value of dark conductivity (>7 (U cm)1) andhigh optical band gap (>1.7 eV). Modeling of ellipsometry spectra reveals that the film growth mechanismshould proceed through a sub-surface layer mechanism that leads to silicon crystallization.The obtained films are very good candidates for application in amorphous and nanocrystalline siliconsolar cells as a p-type window layer.
Abstract This study aimed to synthesize a green powdered layered double hydroxide (LDH) based on nickel-aluminum (Ni–Al-LDH) to evaluate its efficiency in the removal of rare earth elements (REEs), Praseodymium (Pr3+) and Samarium (Sm3+), from synthetic effluents and real leachate using phosphogypsum as a secondary source of REEs. Several characterization techniques were employed to evaluate the physicochemical properties of Ni-Al-LDH adsorbent, such as specific surface area and porosity, functional surface groups and phases, and point of zero charge. The characterization results indicated that Ni-Al-LDH exhibited a typical layered structure confirming the successful synthesis. The effect of key adsorption variables, such as pH, contact time, initial concentration, and temperature, on the REEs adsorption was extensively studied in single-factor experiments separately. The kinetic and equilibrium adsorption data agreeably fitted the Avrami and Sips models, respectively. The maximum adsorption capacities for Pr3+ and Sm3+ adsorption were 18.13 and 15.68 mg g−1 at 298 K, respectively. The thermodynamic parameters (ΔH0, ΔS0, ΔG0) indicated that the adsorption was spontaneous, favorable, and exothermic for both Pr3+ and Sm3+. The interactions between Pr33+ and Sm3+ onto Ni-Al-LDH suggest that multiple adsorption mechanisms are involved, such as ion exchange, precipitation, chelation, and pore filling. Finally, the Ni-Al-LDH could selectively recover REEs, specially Pr3+ and Sm3+, from the real phosphogypsum leachate. It has been demonstrated that Ni-Al-LDH is a promising adsorbent material that could be used as an adsorbent for the recovery of REEs from synthetic and real effluents.
Abstract Background: When designing Connected Health (CH) solutions for home care, it is vital to focus on usability and user experience to ensure that technologies are easy to use and meet users’ expectations and needs. Generally, the usability and user experience tests are conducted during short-term exposure, which does not allow a true understanding of how the technology can help with the home caring tasks. Research aim: We aim to investigate informal caregivers’ feedback on the utility and usability of a CH monitoring platform for People with Dementia (PwD) during a period of extended use in the natural living context, and to understand how this was related to compliance patterns. Methods: Informal caregiver’s feedback about the CH platform, usability, and the impact of short-term versus long-term exposure were investigated through semi-structured individual interviews at the beginning and end of a 6-month deployment in the home care setting. Informal caregivers’ compliance with the CH platform was analysed from their daily platform utilization during the deployment time. Results: 11 informal caregivers agreed to participate. There was a change in the participants’ opinions about the CH platform between the short-term and the long-term exposure feedback. Their initial impressions about what the CH platform could offer them to improve their delivery of home care for the PwD did not correspond with what they found that the CH platform could provide them following the long-term exposure. If at the beginning they saw the CH platform as a helpful tool to facilitate home care delivery and to improve their self-efficacy, after the deployment they expressed that because of the way the platform was designed it was mainly conceived for dementia research benefit and not to fulfill their caring needs. Compliance with the CH platform was quite low and similar between all participants. Conclusions: Most contemporary CH studies are not conducted in real-life settings and without enough duration in time. Consequently, this is not providing accurate insights into the factual informal caregivers’ interaction with these technologies and their suitability for their caring needs and support. With this study, we have recognized the importance of studying how informal caregivers’ are engaging with CH for home care in their own environments and for enough duration of time. We have also highlighted that, despite the fact of applying UCD, the result may not always be satisfactory for the user. For these reasons, more longitudinal research on PwD and their informal caregivers, CH technologies adoption need to be conducted.
Abstract A considerable amount of very fine particles can be found, e.g., stored in tailing ponds, and they can include valuable or hazardous minerals that have the potential to be recovered. Selective flocculation, i.e., the formation of larger aggregates from specific minerals, offers a promising approach to improve the recovery of ultrafine particles. This study focuses on the use of a new bio-based flocculation agent made of silylated cellulose nanofibers containing a thiol-functional moiety (SiCNF). Flocculation was performed in separated systems of ultrafine mineral dispersions of pyrite, chalcopyrite, and quartz in aqueous alkaline medium. The flocculation performance of SiCNF was addressed in terms of the turbidity reduction of mineral dispersions and the floc size, and the results were compared with the performance of a commercial anionic polyacrylamide. SiCNF exhibited a turbidity removal efficiency of approximately 90%–99% at a concentration of 4000–8000 ppm with chalcopyrite and pyrite, whereas the turbidity removal of quartz suspension was significantly lower (a maximum of approximately 30%). The sulfide particles formed flocs with a size of several hundreds of micrometers. The quartz in turn did not form any visible flocs, and the dispersion still had a milky appearance after dosing 12,000 ppm of the flocculant. These results open a promising path for the investigation of SiCNF as a selective flocculation agent for sulfide minerals.
New Ag(I) coordination polymers, formulated as [Ag(μ-PTAH)(NO3)2]n (1) and [Ag(μ-PTA)(NO2)]n (2), were self-assembled as light- and air-stable microcrystalline solids and fully characterized by NMR and IR spectroscopy, electrospray ionization mass spectrometry (ESI-MS(±), elemental analysis, powder (PXRD) and single-crystal X-ray diffraction. Their crystal structures reveal resembling 1D metal-ligand chains that are driven by the 1,3,5-triaza-7-phospaadamantane (PTA) linkers and supported by terminal nitrate or nitrite ligands; these chains were classified within a 2C1 topological type. Additionally, the structure of 1 features a 1D!2D network extension through intermolecular hydrogen bonds, forming a two-dimensional hydrogen-bonded network with fes topology. Furthermore, both products 1 and 2 exhibit remarkable antimicrobial activity against different human pathogen bacteria (S. aureus, E. coli, and P. aeruginosa) and yeast (C. albicans), which is significantly superior to the activity of silver(I) nitrate as a reference topical antimicrobial.
This study aimed to synthesize a green powdered layered double hydroxide (LDH) based on nickel-aluminum (Ni–Al-LDH) to evaluate its efficiency in the removal of rare earth elements (REEs), Praseodymium (Pr3+) and Samarium (Sm3+), from synthetic effluents and real leachate using phosphogypsum as a secondary source of REEs. Several characterization techniques were employed to evaluate the physicochemical properties of Ni-Al-LDH adsorbent, such as specific surface area and porosity, functional surface groups and phases, and point of zero charge. The characterization results indicated that Ni-Al-LDH exhibited a typical layered structure confirming the successful synthesis. The effect of key adsorption variables, such as pH, contact time, initial concentration, and temperature, on the REEs adsorption was extensively studied in single-factor experiments separately. The kinetic and equilibrium adsorption data agreeably fitted the Avrami and Sips models, respectively. The maximum adsorption capacities for Pr3+ and Sm3+ adsorption were 18.13 and 15.68 mg g-1 at 298 K, respectively. The thermodynamic parameters (ΔH0, ΔS0, ΔG0) indicated that the adsorption was spontaneous, favorable, and exothermic for both Pr3+ and Sm3+. The interactions between Pr3+ and Sm3+ onto Ni-Al-LDH suggest that multiple adsorption mechanisms are involved, such as ion exchange, precipitation, chelation, and pore filling. Finally, the Ni-Al-LDH could selectively recover REEs, specially Pr3+ and Sm3+, from the real phosphogypsum leachate. It has been demonstrated that Ni-Al-LDH is a promising adsorbent material that could be used as an adsorbent for the recovery of REEs from synthetic and real effluents.
Abstract In this study, a sustainable and easily prepared hydrochar from wood waste was studied to adsorb and recover the rare earth element cerium (Ce(III)) from an aqueous solution. The results revealed that the hydrochar contains several surface functional groups (e.g., C–O, C = O, OH, COOH), which largely influenced its adsorption capacity. The effect of pH strongly influenced the Ce(III) removal, achieving its maximum removal efficiency at pH 6.0 and very low adsorption capacity under an acidic solution. The hydrochar proved to be highly efficient in Ce(III) adsorption reaching a maximum adsorption capacity of 327.9 mg g−1 at 298 K. The kinetic and equilibrium process were better fitted by the general order and Liu isotherm model, respectively. Possible mechanisms of Ce(III) adsorption on the hydrochar structure could be explained by electrostatic interactions and chelation between surface functional groups and the Ce(III). Furthermore, the hydrochar exhibited an excellent regeneration capacity upon using 1 mol L−1 of sulfuric acid (H2SO4) as eluent, and it was reused for three cycles without losing its adsorption performance. This research proposes a sustainable approach for developing an efficient adsorbent with excellent physicochemical and adsorption properties for Ce(III) removal.
Abstract Background: While the relevance of the World Health Organization histopathological grading system as a prognostic tool for oral squamous cell carcinoma has received many critics, other histopathological features such as tumor-stroma ratio, tumor-infiltrating lymphocytes, and tumor budding are displaying promising results. Here, we evaluated the prognostic impact of the incorporation of tumor-stroma ratio, tumor-infiltrating lymphocytes, and tumor budding into World Health Organization histopathological grading for patients with oral squamous cell carcinoma. Methods: A total of 95 patients with early-stage oral squamous cell carcinoma were enrolled in the study, and World Health Organization tumor grading, tumor-stroma ratio, tumor-infiltrating lymphocytes, and tumor budding were evaluated in surgical slides stained with hematoxylin and eosin. Survival analyses for cancer-specific survival and disease-free survival were performed using Cox regression models, and receiver operating characteristic curves were applied for assessment of the performance of the combinations. Results: Tumor-stroma ratio (stroma-rich) was significantly and independently associated with both shortened cancer-specific survival and poor disease-free survival, individually and in combination with World Health Organization histopathological grading. The combination of tumor-stroma ratio with World Health Organization grading did not improve the discriminatory ability compared to tumor-stroma ratio alone. Although low tumor-infiltrating lymphocytes were associated with shortened cancer-specific survival, the association did not withstand multivariate analysis. However, in combination with World Health Organization grading, low tumor-infiltrating lymphocytes were independently associated with poor cancer-specific survival. The combination of tumor-infiltrating lymphocytes and World Health Organization histopathological grading displayed a better discrimination of poor cancer-specific survival than tumor-infiltrating lymphocytes alone, but not at a significant level. Conclusions: Our findings support tumor-stroma ratio as a potential prognostic marker for patients with oral squamous cell carcinoma, and the incorporation of tumor-infiltrating lymphocytes into the World Health Organization grading system improves the prognostic ability of the tumor grading alone.
Abstract Background: Changes in Caveolin-1 (CAV-1) expression are related to tumorigenesis. The aim of this study was to evaluate the role of CAV-1 in tumor progression in oral squamous cell carcinoma (SCC) tissue samples and the effect of CAV-1 silencing on two oral tongue SCC (OTSCC) cell lines (SCC-25, from a primary tumor, and HSC-3 from lymph node metastases). Methods: Mycroarray hybridization, mRNA expression, and immunohistochemistry were performed on OSCC tissue samples and corresponding non-tumoral margin tissues. The effects of CAV-1 silencing (siCAV-1) on cell viability, membrane fluidity, on the expression of epithelial to mesenchymal transition (EMT) markers and on cell migration and invasion capacity of OTSCC cell lines were evaluated. Results: Microarray showed a greater CAV-1 expression (1.77-fold) in OSCC tumors than in non-tumoral tissues and 2.0-fold more in less aggressive OSCCs. However, significant differences in CAV-1 gene expression were not seen between tumors and non-tumoral margins nor CAV-1 with any clinicopathological parameters. CAV-1 protein was localized both in carcinoma and in spindle cells of the tumor microenvironment (TME), and CAV-1 positive TME cells were associated with smaller/more aggressive tumors, independent of the carcinoma cells’ expression. Silencing of CAV-1 increased cell viability only in SCC-25 cells. It also stimulated the invasion of HSC-3 cells and increased ECAD and BCAT mRNA in these cells; however, the protein levels of the EMT markers were not affected. Conclusion: Decreased expression of CAV-1 by tumor cells in OSCC and an increase in the TME were associated with increased cell invasiveness and tumor aggressiveness.
Abstract Background: Maternal smoking during pregnancy is associated with adverse offspring health outcomes across their life course. We hypothesize that DNA methylation is a potential mediator of this relationship. Methods: We examined the association of prenatal maternal smoking with offspring blood DNA methylation in 2821 individuals (age 16 to 48 years) from five prospective birth cohort studies and perform Mendelian randomization and mediation analyses to assess whether methylation markers have causal effects on disease outcomes in the offspring. Results: We identify 69 differentially methylated CpGs in 36 genomic regions (P value < 1 × 10−7) associated with exposure to maternal smoking in adolescents and adults. Mendelian randomization analyses provided evidence for a causal role of four maternal smoking-related CpG sites on an increased risk of inflammatory bowel disease or schizophrenia. Further mediation analyses showed some evidence of cg25189904 in GNG12 gene mediating the effect of exposure to maternal smoking on schizophrenia-related outcomes. Conclusions: DNA methylation may represent a biological mechanism through which maternal smoking is associated with increased risk of psychiatric morbidity in the exposed offspring.
Abstract There seems to exist an intricate relationship between airway inflammation, body mass index (BMI), and diet. The intake of specific foods or food groups has been suggested to suppress the oxidative stress and inflammatory processes that characterize airway inflammation, but little is known about dietary patterns and their complex interplay with BMI and airway inflammation. Therefore, this cross-sectional study aimed to explore the association between adherence to the Mediterranean diet (MD), a characteristic European diet, and levels of airway inflammation in school-aged children, taking into account their BMI. This cross-sectional analysis comprised 660 children: 49.1% females, 7–12 years old. Adherence to the MD was assessed through the alternate Mediterranean score (aMED). Higher scores represent a healthier diet (0–8). Airway inflammation was assessed measuring exhaled fractional nitric oxide (eNO). Two categories of BMI were considered: non-overweight/non-obese (p < 85th) and overweight/obese (p ≥ 85th). The associations between diet and airway inflammation were estimated using logistic regression models. Higher scores of the aMED were associated with decreased odds of having eNO ≥ 35 ppb, but only in non-overweight/non-obese children (OR = 0.77; 95% CI, 0.61–0.97). For overweight/obese children, the previous association was not significant (OR = 1.57, 95% CI, 0.88–2.79). Our findings suggest that adherence to the MD is associated with lower levels of airway inflammation among non-overweight/non-obese children.
Abstract Asthma is a chronic respiratory disease that impacts millions of people worldwide. Recent studies suggest that diet may play a role in asthma pathophysiology. Several dietary factors have been recognized as potential contributors to the development and severity of asthma for its inflammatory and oxidative effects. Some food groups such as fruits and vegetables, whole grains, and healthy fats appear to exert positive effects on asthma disease. On the other hand, a high consumption of dietary salt, saturated fats, and trans-fat seems to have the opposite effect. Nonetheless, as foods are not consumed separately, more research is warranted on the topic of dietary patterns. The mechanisms underlying these associations are not yet fully understood, but it is thought that diet can modulate both the immune system and inflammation, two key factors in asthma development and exacerbation. The purpose of this review is to examine how common food groups and dietary patterns are associated with asthma. In general, this research demonstrated that fruits and vegetables, fiber, healthy fats, and dietary patterns considered of high quality appear to be beneficial to asthma disease. Nonetheless, additional research is needed to better understand the interrelation between diet and asthma, and to determine the most effective dietary interventions for asthma prevention and management. Currently, there is no established dietary pattern for asthma management and prevention, and the nuances of certain food groups in relation to this disease require further investigation.
Abstract Background: Mindfulness-based interventions (MBIs) have been used in oncology contexts as a promising tool with numerous benefits for various health-related and psychosocial outcomes. Despite the increasing popularity of MBIs, few randomized controlled trials (RCTs) have examined their effects upon biological parameters. Specifically, no previous study has examined the effects of MBIs on extracellular vesicles (EVs), which are potentially important markers of health, disease, and stress. Moreover, the lack of RCTs is even more limited within the context of technology-mediated MBIs and long-term effects. Methods: The current study protocol presents a two-arm, parallel, randomized controlled study investigating the effects of internet-supported mindfulness-based cognitive therapy (MBCT) compared with treatment as usual (TAU). Primary outcomes are psychological distress and EV cargo of distressed participants with previous breast, colorectal, or prostate cancer diagnoses. Secondary outcomes are self-reported psychosocial and health-related measures, and additional biological markers. Outcomes will be assessed at baseline, 4 weeks after baseline (mid-point of the intervention), 8 weeks after baseline (immediately post-intervention), 24 weeks after baseline (after booster sessions), and 52 weeks after baseline. Our goal is to recruit at least 111 participants who have been diagnosed with breast, prostate, or colorectal cancer (cancer stage I to III), are between 18 and 65 years old, and have had primary cancer treatments completed between 3 months and 5 years ago. Half of the participants will be randomized to the TAU group, and the other half will participate in an 8-week online MBCT intervention with weekly group sessions via videoconference. The intervention also includes asynchronous homework, an online retreat after the fifth week, and 4 monthly booster sessions after completion of the 8-week programme. Discussion: This study will allow characterizing the effects of internet-based MBCT on psychosocial and biological indicators in the context of cancer. The effects on circulating EVs will also be investigated, as a possible neurobiological pathway underlying mind-body intervention effects. Trial registration: ClinicalTrials.govNCT04727593 (date of registration: 27 January 2021; date of record verification: 6 October 2021).
Forthcoming imaging surveys will increase the number of known galaxy-scale strong lenses by several orders of magnitude. For this to happen, images of billions of galaxies will have to be inspected to identify potential candidates. In this context, deep-learning techniques are particularly suitable for finding patterns in large data sets, and convolutional neural networks (CNNs) in particular can efficiently process large volumes of images. We assess and compare the performance of three network architectures in the classification of strong-lensing systems on the basis of their morphological characteristics. In particular, we implemented a classical CNN architecture, an inception network, and a residual network. We trained and tested our networks on different subsamples of a data set of 40 000 mock images whose characteristics were similar to those expected in the wide survey planned with the ESA mission Euclid, gradually including larger fractions of faint lenses. We also evaluated the importance of adding information about the color difference between the lens and source galaxies by repeating the same training on single- and multiband images. Our models find samples of clear lenses with 90% precision and completeness. Nevertheless, when lenses with fainter arcs are included in the training set, the performance of the three models deteriorates with accuracy values of ~0.87 to ~0.75, depending on the model. Specifically, the classical CNN and the inception network perform similarly in most of our tests, while the residual network generally produces worse results. Our analysis focuses on the application of CNNs to high-resolution space-like images, such as those that the Euclid telescope will deliver. Moreover, we investigated the optimal training strategy for this specific survey to fully exploit the scientific potential of the upcoming observations. We suggest that training the networks separately on lenses with different morphology might be needed to identify the faint arcs. We also tested the relevance of the color information for the detection of these systems, and we find that it does not yield a significant improvement. The accuracy ranges from ~0.89 to ~0.78 for the different models. The reason might be that the resolution of the Euclid telescope in the infrared bands is lower than that of the images in the visual band.
With WEST (Tungsten Environment in Steady State Tokamak) (Bucalossi et al 2014 Fusion Eng. Des. 89 907-12), the Tore Supra facility and team expertise (Dumont et al 2014 Plasma Phys. Control. Fusion 56 075020) is used to pave the way towards ITER divertor procurement and operation. It consists in implementing a divertor configuration and installing ITER-like actively cooled tungsten monoblocks in the Tore Supra tokamak, taking full benefit of its unique long-pulse capability. WEST is a user facility platform, open to all ITER partners. This paper describes the physics basis of WEST: the estimated heat flux on the divertor target, the planned heating schemes, the expected behaviour of the L-H threshold and of the pedestal and the potential W sources. A series of operating scenarios has been modelled, showing that ITER-relevant heat fluxes on the divertor can be achieved in WEST long pulse H-mode plasmas.
Background: Maternal smoking during pregnancy is associated with adverse offspring health outcomes across their life course. We hypothesize that DNA methylation is a potential mediator of this relationship. Methods: We examined the association of prenatal maternal smoking with offspring blood DNA methylation in 2821 individuals (age 16 to 48 years) from five prospective birth cohort studies and perform Mendelian randomization and mediation analyses to assess whether methylation markers have causal effects on disease outcomes in the offspring. Results: We identify 69 differentially methylated CpGs in 36 genomic regions (P value < 1 × 10−7) associated with exposure to maternal smoking in adolescents and adults. Mendelian randomization analyses provided evidence for a causal role of four maternal smoking-related CpG sites on an increased risk of inflammatory bowel disease or schizophrenia. Further mediation analyses showed some evidence of cg25189904 in GNG12 gene mediating the effect of exposure to maternal smoking on schizophrenia-related outcomes. Conclusions: DNA methylation may represent a biological mechanism through which maternal smoking is associated with increased risk of psychiatric morbidity in the exposed offspring.