The concept of transformative resilience emerges from complex recent literature and represents a way to interpret the potential opportunities to change in vulnerable territories, where a socio-economic change is required. This article extends the perspective of transformative resilience to assessing of the landscape multi-functionality of inland areas, exploring the potentials to identify a network of synergies among the different municipalities able to trigger a process of territorial resilience. A Spatial Decision Support System (SDSS) for multi-functionality landscape assessment aims to support the local actors to understand local resources and multi-functional values of the Partenio Regional Park (PRP) and surrounding municipalities, in the South of Italy, stimulating their cooperation to the management of environmental and cultural sites and the co-design of new strategies of enhancement.

This paper presents novel feature descriptors and classification algorithms for automated scoring of HER2 in Whole Slide Images (WSI) of breast cancer histology slides. Since a large amount of processing is involved in analyzing WSI images, the primary design goal has been to keep the computational complexity to the minimum possible level and to use simple, yet robust feature descriptors that can provide accurate classification of the slides. We propose two types of feature descriptors that encode important information about staining patterns and the percentage of staining present in ImmunoHistoChemistry (IHC) stained slides. The first descriptor is called a characteristic curve which is a smooth non-increasing curve that represents the variation of percentage of staining with saturation levels. The second new descriptor introduced in this paper is an LBP feature curve which is also a non-increasing smooth curve that represents the local texture of the staining patterns. Both descriptors show excellent interclass variance and intraclass correlation, and are suitable for the design of automatic HER2 classification algorithms. This paper gives the detailed theoretical aspects of the feature descriptors and also provides experimental results and comparative analysis.

Speckle noise reduction is an important area of research in the field of ultrasound image processing. Several algorithms for speckle noise characterization and analysis have been recently proposed in the area. Synthetic ultrasound images can play a key role in noise evaluation methods as they can be used to generate a variety of speckle noise models under different interpolation and sampling schemes, and can also provide valuable ground truth data for estimating the accuracy of the chosen methods. However, not much work has been done in the area of modelling synthetic ultrasound images, and in simulating speckle noise generation to get images that are as close as possible to real ultrasound images. An important aspect of simulated synthetic ultrasound images is the requirement for extensive quality assessment for ensuring that they have the texture characteristics and gray-tone features of real images. This paper presents texture feature analysis of synthetic ultrasound images using local binary patterns (LBP) and demonstrates the usefulness of a set of LBP features for image quality assessment. Experimental results presented in the paper clearly show how these features could provide an accurate quality metric that correlates very well with subjective evaluations performed by clinical experts.

This paper analyzes low-Earth orbit (LEO) satellite downlinks when an airborne interference source moves parallel to the satellite trajectory by considering the relative angle differences be-tween the satellites and the interference sources. To make the experimental interference situations more like actual environments, the LEO trajectories are obtained from two-line element set (TLE) data. Airborne interference sources with various altitudes move parallel to the LEO trajectories, and the jamming to signal (J/S) ratio is calculated based on the relative angle differences between the ground station, the LEO satellite, and the interference source. In order to calculate the relative angle difference psi, the coordinates of the satellite and the interference source are converted from the World Geodetic System 1984 (WGS84) to the ground station-centered east-north-up (ENU) system. By applying the relative angle difference psi, we can obtain the sidelobe gain of the ground station antenna in the direction from which the interference comes. The results of the study confirm that, from a J/S ratio perspective, the distances between the ground station, LEO satellite, and airborne interference source are important, and in particular, the relative angle difference psi between the interference source and the satellite is more critical factor.

(1) Background: Most patients with mycosis fungoides (MF), a form of cutaneous T-cell lym-phoma (CTCL), develop relapsed/refractory (R/R) disease following front-line systemic therapy. This report describes treatment patterns and outcomes from the subpopulation with R/R MF. (2) Methods: This observational, retrospective, cohort study analysed patient records (1984–2016) from 27 clinical sites in Eurpe. Outcomes included treatments received, response to first-, second- and third-line treatment, overall survival (OS), and progression-free survival (PFS). (3) Results: Of 104 patients with MF, 100 received second-line and 61 received third-line therapy. Median (range) times from start of first-line therapy to first R/R MF and from first to second R/R MF were 11.2 (0.3–166.5) and 13.5 (0.0–174.6) months, respectively. Second-and third-line treatment options varied and comprised systemic therapies (85% and 79% of patients, respectively), radio-therapy (32% and 34%, respectively) and topical therapies (48% and 36%, respectively). Median (95% confidence interval [CI]) OS from the diagnosis of first R/R MF was 11.5 (6.5–not reached [NR]) years and was higher with non-chemotherapy (NR) versus chemotherapy (6.5 years); es-timated median PFS (95% CI) from the time of first R/R MF was 1.3 (1.0–2.1) years. (4) Conclu-sion: High rates of R/R disease were observed after second- and third-line treatments in this re-al-world cohort, with longer median OS in patients receiving non-chemotherapy versus chemo-therapy. Following the standard management of MF and using recently approved targeted therapies can help improve patient outcomes in advanced-stage MF.

Background: Depression, a multifaceted mental health condition, necessitates a multidimensional approach to treatment. This study aimed to elucidate the potential efficacy of various mitochondrial interventions, ranging from pharmacological treatments to lifestyle modifications, in alleviating depressive symptoms and enhancing overall mental well-being and assess the diverse range of mitochondrial assessments for managing depression by synthesizing findings from selected studies. Methods: A systematic compilation of studies, employing observational, interventional, and animal-based designs, was undertaken to elucidate the intricate relationship between mitochondrial function and depression as well as depressive signs and symptoms. The PRISMA guidelines were employed for conducting this review and a specific set of selection criterion were formulated by a team of reviewers for selection of relevant papers. Results: The synthesized results from the 21 selected papers highlighted the potential of these interventions to target diverse aspects of depression. Hyperbaric oxygen therapy and psychotherapy demonstrated significant reductions in depression and anxiety scores, with hyperbaric oxygen therapy particularly effective in improving nerve function and daily living activities. Whole-body cryotherapy displayed substantial improvements in depressive symptoms and quality of life. Frequent sauna bathing exhibited a lower risk of depressive symptoms in males. Dietary patterns, including Paleolithic and Mediterranean diets, showcased potential protective effects against depression, anxiety, and stress. The ketogenic diet revealed promise in ameliorating depression and psychosis symptoms alongside positive metabolic changes. Fasting interventions, though challenging, were associated with lower anxiety and depression levels without increased fatigue. Bright white light therapy enhanced remission rates and reduced depression scores in bipolar depression. Probiotic supplementation exhibited potential in reducing depression scores and improving metabolic markers, although further investigation is warranted. Conclusion: The diverse array of interventions explored in this study underlines the multifaceted nature of depression treatment. While these findings offer hope for more personalized and effective approaches, it is imperative to consider the variability in study designs, sample sizes, and methodologies among the selected papers. The mechanisms underlying the observed effects remain partially understood, emphasizing the need for continued mechanistic research. This study sets the stage for future investigations and clinical practices, showcasing the potential of various interventions in mitigating the challenges posed by depression and paving the way for more effective treatment strategies.

This research is a preliminary phase of a general effort to develop a generic-data transferring capability via human haptic thermal sensation (generic-data refers to a coded language like Morse or Braille). For the capability to be effective, it must include a large variety of short recognizable cues. Hence, we propose the concept of cues based on sequences of thermal pulses, i.e., combinations of warm and cool pulses with several levels of intensity. The objective of this study was to determine the feasibility of basing a generic-data-transfer capability on thermal cues composed of sequences of short pulses. The research included defining the basic characteristics of the stimuli parameters and developing practical methods for generating and measuring them. Several sequences were designed in light of the relevant data known to date, and tests were conducted. The thermal cues presented to the participants were sensed and recognized by touch. The results indicate high feasibility for a capability that is applicable in various scenarios. In addition, the low impact on human skin temperature due to short stimuli duration represents an inherent advantage for later implementation. This report presents promising findings and offers insights for further investigation.

The contribution of extra-tropical synoptic cyclones to the formation of summer-mean atmospheric circulation patterns in the Arctic is investigated by clustering the dominant Arctic circulation patterns by the self-organizing maps (SOMs) using the daily mean sea level pressure (MSLP) in the Arctic domain (≥ 60°N). Three SOM patterns are identified: one with prevalent low pressure anomalies in the Arctic Circle (SOM1) and two opposite dipoles with primary high pressure anomalies covering the Arctic Ocean (SOM2 and SOM3). The time series of summertime occurrence frequencies demonstrate the largest inter-annual variation in the SOM1, the slight decreasing trend in the SOM2, and the abrupt upswing after 2007 in the SOM3. The relevant analyses with produced cyclone track data confirm that the vital contribution. The Arctic cyclone activity is enhanced in the SOM1 because the meridional temperature gradient increases over the land–Arctic Ocean boundaries co-located with major extra-tropical cyclone pathways. The composite daily synoptic evolutions for each SOM reveal that the persistence of all the three SOMs is less than 5 days on average. These evolutionary short-term weather patterns have substantial variability at inter-annual and longer timescales. Therefore, the synoptic-scale activity is central to forming the seasonal-mean climate of the Arctic.

: One of the challenges facing operations management is the design, choice and imple-mentation of action plans adapted to the magnitude of the deviations of the variables of an industrial process. Making conscious and quick decisions is crucial to achieving im-provements in productivity. This will be achieved if the organization's internal and external communication model is strategically designed, considering specific cultural factors and the symmetry or asymmetry required in the communication model. However, how do we organize ourselves and through what channels do we communicate within a production process to generate Big Data that combines data from technologies and the perception, comprehension and projection of experienced humans? Our purpose is to create an operations management model that facilitates the incorporation of technology, allows a prompt response to failures, and promotes the sustainability of processes, without losing sight of its alignment with the organizational strategy. The developed model was implemented in an operations management team, following the guidelines of an action researcher methodology. This resulted in the design of an operations management model and a detailed methodology for its implementation, achieving sig-nificant improvements in the metrics of the current process, making it a success story.

This paper presents a concise exploration of the synthetic biology currently to artificially 1 create life, juxtaposed against natural life’s emergence over Earth’s 4.5-billion-year history. It explores 2 the complexities of life’s origins, sustaining factors, and the consequences of synthetic life creation, 3 addressing key scientific milestones such as the Urey-Miller experiment and Jacques Monod’s pro- 4 posals. The narrative navigates through the roles of energy, Maxwell’s demons, bifurcations, and 5 genetic information in the emergence and evolution of complex biological systems. Despite significant 6 strides in genetic engineering, the challenge of creating life from scratch persists, necessitating a deep 7 understanding of diverse scientific disciplines. While synthetic biology holds promise for medicine 8 and biotechnology, the creation of truly autonomous synthetic life forms raises ethical concerns. The 9 paper also stresses the imperative for careful ethical evaluation of the societal and environmental 10 implications arising from these advancements.

Glaucoma is a leading cause of blindness. Surgical and pharmacological treatment of glaucoma aims to lower the intraocular pressure (IOP) and preserve visual function. The severe acute res-piratory syndrome coronavirus 2 pandemic has placed a strain on the healthcare system. We aimed to compare the quantity, type of anti-glaucoma surgeries, and the disease stage before and during the coronavirus disease pandemic. We analyzed 362 eyes of 306 patients and 172 eyes of 149 patients from the pre-pandemic and pandemic groups, respectively. The number of an-ti-glaucoma surgeries was halved during the pandemic compared to a similar pre-pandemic pe-riod, with a significant difference in the procedural structures between the two groups (p<0.001). The most common procedures in the pre-pandemic group were Ex-Press implantation (33.7%) and trabeculectomy (31.5%). Within the pandemic group, half of the eyes underwent tra-beculectomy (50.0%), followed by Preserflo microshunt (11.6%). A significant difference in the average IOPs was revealed among patients who qualified for surgery 22.21 ± 7.83 mmHg in the pre-pandemic group and 25.16 ± 9.48 mmHg in the pandemic group; p<0.001). There was no significant difference in the best corrected visual acuity between the groups (p=0.263). Glaucoma treatment remained relatively accessible during the pandemic.

Since its inception in 2019, COVID-19 has been associated with significant changes in lifestyle-related behavior, including physical activity, diet, and sleep, which are vital to maintaining our well-being. This study measures lifestyle-related behavior during the COVID-19 pandemic lockdown using a 21-item questionnaire. The responses were collected from March 2021 to September 2021. Four hundred sixty-seven participants were engaged in assessing the changes caused by the pandemic and their effect on BMI. The validity and reliability of the questionnaire were tested for 71 participants. Cronbach's alpha values for the questionnaire all exceeded 0.7, demonstrating good validity and internal consistency for it. The effect of each question regarding physical activity and dietary habits over the BMI difference was studied using ANOVA. The study shows that more than half of the participants reported snacking more between meals and increased their sitting and screen time, while 74% felt more stressed and anxious. These indications were the cause of the increase in the BMI rate for individuals in the lockdown. In contrast, 62% of the participants showed more awareness about their health by increasing the intake of immunity-boosting foods, and 56% of the participants showed an increase in the consumption of nutrition supplements. Females and married individuals tended to be healthier, so their BMI showed stability compared to others based on their gender and marital status.

Grasping the spatial and temporal patterns of forest fires, along with the key factors that drive them and the ability to forecast such events accurately, is essential for the successful management of forests. In China's southern region, forest fires significantly endanger the ecological system, public safety, and economic well-being. Through the application of Geographic Information Systems (GIS) and LightGBM (Light Gradient Boosting Machine) model, this study investigates the determinants of fire incidents and formulates a predictive model for forest fire occurrences, alongside a zoning strategy, within the Central-South area. The results indicate: (i) Spatially, fire points exhibit significant clustering and autocorrelation characteristics; (ii) The Central-South Forest Fire Prediction Model shows exceptional accuracy, reliability, and predictive power, with high performance metrics across training and validation sets, including over 85% accuracy, precision, recall, and F1 scores, along with AUC values above 89%, underscoring its efficacy in forecasting forest fires and distinguishing between fire events; (iii) Throughout the year, forest fire risks in the Central-South region of China vary by region and season, with risk spikes from March to May in Guangdong, Guangxi, Hunan, Hubei, and Hainan. From June to August, localized risks are observed in Heyuan and Huangshi, while from September to November, an increase in risk is noted in Guangdong (Meizhou, Heyuan, Shaoguan), Guangxi (Nanning, Hezhou, Yulin), and Hunan (Binzhou, Yongzhou, Hengyang) due to cooler, drier conditions and leaf litter accumulation. From December to February, the risk continues in specific areas across Guangdong, Guangxi, Hunan, and Hubei.

The phenomenon of dissipative self-organization is studied on the example of time-crystal networks. Particular attention was given to transient processes, attractor topologies, phase transitions, and asymptotic stability. New concepts were introduced, including topological phases, spinorial states, and bond flavors. Concepts such as ground states, chemical potentials, elastic forces, temperature, and statistical distributions were endowed with a new meaning associated with asymptotic stability. Phenomena usually attributed exclusively to quantum physics have been shown to occur in this essentially classical environment. They coexist with, and in some cases, such as charge quantization, are related to the phenomenon of time dilation. The approach was applied to model vacuum self-organization. We have shown that under the ac-tion of competing forces, such as gravity and antigravity, a cascade of phase transitions can transform an unorganized vacuum into phases in which interactions, fields and waves resemble electromagnetic, weak, and strong, and their elements can be used as building blocks for prototype particles. In addition, some interrelation field parameters and probabilities of particle transmutations were calculated, which are not predicted by the standard model. The results are consistent with the experiment. The presented material and methodology may be of interest for studying self-organization in different environments.

Abstract: Background: The diagnosis of nasal airway disorders relies on questionnaires, subjective data, and objective data. Interpretation of objective data obtained from measurement technology is not well understood by providers and researchers who use the equipment to test nasal airway function, justifying the need to cre-ate a new clinical tool. The Davidson Airway Function & Nasal Evaluation (DAFNE) Scoring System is a web-based scoring system that allows healthcare providers (MDs, PAs, PTs, APRNs, DMDs, DDSs, SLPs, and DCs) and researchers who treat nasal obstruction and breathing disorders to make more accurate diagnostic decisions, select the appropriate treatment for individualized patient care, monitor treatment progression and outcomes, and show how to approach a collaborative care model with other healthcare professionals. The current technologies, such as 4-phase rhinomanometry, use a simple approach that relies on a measurement tracing intersecting a color-coded y-axis on a four-quadrant graph with diagnostic numeric data output de-scribing nasal airflow and resistance. This is a good source of biofeedback demonstrating abnormal nasal breathing patterns but lacks interpretation guidelines to describe the severity of disease. The more sophisti-cated proprietary DAFNE approach uses multiple parameters which include airflow restriction, speed, vol-ume, and patient characteristics to identify patients’ disease progression much more accurately. Additionally, it explains how to segregate patients into appropriate treatment options which minimizes risks and compli-cations associated with sleep and breathing disorders while improving patient outcomes. Methods: Electronic searches of PubMed, MEDLINE, EMBASE Cochrane Library, and Scopus of publications between 1988-2022 were necessary to identify studies which determined the ranges of nasal function measurement parameters among three airway measurement technologies used in writing the DAFNE Score algorithm. The performance of DAFNE was evaluated compared to the research data and patient demographics used in previous studies. Results: By using primary outcome measurements from the literature, we were able to create a reliable, re-peatable, and validated tool to facilitate patient identification, treatment stratification, and collaboration for sleep and nasal breathing dysfunction. Subsequently, we found DAFNE could be used to identify the appro-priateness of a sleep study. Conclusions: DAFNE Scoring System has demonstrated the ability to detect high risk patients in the pediatric and adult populations susceptible of sleep apnea and breathing dysfunction needing a sleep study and treatment to improve nasal airway function and sleep. DAFNE Scoring System should be used as an adjunct tool in routine clinical practice and research to further understand the technol-ogy data output, identify patients at risk, stratify treatment options, progress, and stabilization after treatment, and how to collaborate with other healthcare providers to improve patient outcomes.

Background: The Davidson Airway Function &amp; Nasal Evaluation (DAFNE) Scoring System was developed as an intuitive and research-based scoring system that could be validated through beta testing and easily introduced to healthcare providers of several subspecialties who treat nasal obstruction and breathing disorders (MDs, PAs, PTs, APRNs, DDSs, and DCs). This scoring system was shown to increase the knowledge of airway function, nasal measurement parameters, and identification of proper treatment options for sleep and breathing disorders. The basis for the DAFNE score was developed from a systematic review of nasal measurement data. Methods: Electronic searches of PubMed, MEDLINE, EMBASE Cochrane Library, and Scopus of publications between 1988-2022 were used to identify studies validating nasal function measurement parameters to create the algorithm for the DAFNE Score™. The systematic review was accomplished using the 2020 ‘Preferred Reporting Items for Systematic Reviews’ (PRISMA) guidelines. Results: Twenty studies met the inclusion criteria for systematic review. Primary outcomes measurements demonstrated reliability, repeatability and validity of the DAFNE measurement technologies, data and output. Conclusions: The data analysis and systematic review uncovered a need and framework to develop and validate a web-based software algorithm for global access to improve the understanding of data interpretation of nasal measurements from three nasal measurement technologies. DAFNE Scoring should be used as an adjunct tool in routine clinical practice and research to further understand the technology data output and how to collaborate with other healthcare providers to improve patient outcomes.

Abstract: Spatially explicit, fine-grained datasets describing historical urban extents are rarely available prior to the era of operational remote sensing. However, such data are necessary to better understand long-term urbanization and land development processes and for the assessment of coupled nature-human systems, e.g., the dynamics of the wildland-urban interface. Herein, we propose a framework that jointly uses remote sensing derived human settlement data (i.e., the Global Human Settlement Layer, GHSL) and scanned, georeferenced historical maps to automatically generate historical urban extents for the early 20th century. By applying unsupervised color segmentation to the historical maps, spatially constrained to the urban extents derived from the GHSL, our approach generates historical settlement extents for seamless integration with the multi-temporal GHSL. We apply our method to study areas in countries across four continents, and evaluate our approach for two U.S. study sites against historical settlement extents derived from the Historical Settlement Data Compilation for the US, HISDAC-US, achieving Area-under-the-Curve values >0.9. Our results are largely in agreement with model-based urban areas from the HYDE database, and demonstrate that the integration of remote sensing derived observations and historical cartographic data sources opens up new, promising avenues for assessing urbanization, and long-term land cover change in countries where historical maps are available.

Multilingual classrooms are becoming more common worldwide due to increasing mobility. Teaching foreign languages using the mother tongue in multilingual classrooms has become problematic; some of the significant concerns in Japanese language acquisition – such as the high contextuality of the language, vocabulary and kanji learning – make the direct teaching method confusing for many students, especially at the beginner and elementary levels. This article provides the preliminary results of a study carried out as a component of a more extensive empirical research project on instructional languages in classrooms teaching Japanese as a foreign language. It aims to gather, analyse and synthesise data from a survey conducted at a supranational level. The results of the first two sections of a questionnaire containing closed and open-ended questions were used for a quantitative analysis of the profile of Japanese language instructors with a focus on finding possible connections. The wide geographic distribution of the respondents (274 teachers from fifty-seven countries and regions) made it possible to collect data from a more representative sample and draw meaningful conclusions about the spread of multilingual classrooms that would be impossible in smaller-scale research. The study’s primary results show the proportion of multilingual classrooms among countries in different regions and across different educational stages, the distribution of Japanese language instructors in various educational stages depending on the highest level of formal education attained, and the proportion of part-time instructors working in different academic institutions.

German noise action plans aim to reduce negative health outcomes from noise exposure and identify quiet areas free of noise pollution. Quiet area identification in German noise action plans is based primarily on noise mapping and spatial analysis and not empirical or qualitative data about acoustic environments, thus leaving a gap in the understanding of the quality of formally recognized quiet areas in noise action plans. This work presents a comparative empirical case study in Dortmund, Germany, with the aim to describe the diurnal dB(A) and biophonic properties of quiet areas versus noise 'hot spots'. Sound observations were collected (n=282,764) in five different natural or recreational land use patch types larger than four acres within 33 proposed quiet areas in Dortmund (n=70) and 23 noise hot spots between April 27^th, 2022 and March 2^nd, 2023. We find that quiet areas are on average more than 20 dB(A) quieter than noise hot spots almost every hour of the day. Forests, managed tree stands, cemeteries, and agriculture diel patterns are dominated by dawn dusk chorus in spring and summer, whereas sport and recreation as well as noise hot spots are dominated by traffic and human noise. A novel composite biophony mapping procedure is presented that finds distinct temporal distribution of biophony in forested and agriculture peri-urban locations positively associated with patch size, distance away from LDEN > 55, proximity to water, and the number of vegetation layers in the plant community. Anthrophony distribution dominates urban land uses in all hours of the day, but expands during day and evening and contracts at night and in dusk hours. The procedures presented here illustrate how qualitative information regarding quiet areas can be integrated into German noise action planning.

This research article investigates the effectiveness of digital forensics analysis (DFA) techniques in identifying patterns and trends in malicious failed login attempts linked to public data breaches or compromised email addresses in Microsoft 365 (M365) environments. Pattern recognition techniques are employed to analyze security logs, revealing insights into negative behavior patterns. The findings contribute to the literature on digital forensics, opposing behavior patterns, and cloud-based cybersecurity. Practical implications include the development of targeted defense strategies and the prioritization of prevalent threats. Future research should expand the scope to other cloud services and platforms, capture evolving trends through more prolonged, more extended analysis periods, and assess the effectiveness of specific mitigation strategies for identified tactics, techniques, and procedures (TTPs).

We report on the application of time-resolved inline digital holography to study the nonlinear optical properties of quantum dots deposited onto the sample glass. Fresnel diffraction patterns of the probe pulse due to noncollinear degenerate phase modulation induced by the femtosecond pump pulse were extracted from the set of inline digital holograms and analyzed. Absolute values of the nonlinear refractive index of both sample glass substrate and the deposited layer of quantum dots were evaluated using the proposed technique. To characterize the inhomogeneous distribution of samples’ nonlinear optical properties we proposed to plot an optical nonlinearity map calculated as a local standard deviation of diffraction patterns intensity induced by noncollinear degenerate phase modulation.

Big data has revolutionised science and technology leading to the transformation of our societies. High Performance Computing (HPC) provides the necessary computational power for big data analysis using artificial intelligence and methods. Traditionally HPC and big data had focused on different problem domains and had grown into two different ecosystems. Efforts have been underway for the last few years on bringing the best of both paradigms into HPC and big converged architectures. Designing HPC and big data converged systems is a hard task requiring careful placement of data, analytics, and other computational tasks such that the desired performance is achieved with the least amount of resources. Energy efficiency has become the biggest hurdle in the realisation of HPC, big data, and converged systems capable of delivering exascale and beyond performance. Data locality is a key parameter of HPDA system design as moving even a byte costs heavily both in time and energy with an increase in the size of the system. Performance in terms of time and energy are the most important factors for users, particularly energy, due to it being the major hurdle in high performance system design and the increasing focus on green energy systems due to environmental sustainability. Data locality is a broad term that encapsulates different aspects including bringing computations to data, minimizing data movement by efficient exploitation of cache hierarchies, reducing intra- and inter-node communications, locality-aware process and thread mapping, and in-situ and in-transit data analysis. This paper provides an extensive review of the cutting-edge on data locality in HPC, big data, and converged systems. We review the literature on data locality in HPC, big data, and converged environments and discuss challenges, opportunities, and future directions. Subsequently, using the knowledge gained from this extensive review, we propose a system architecture for future HPC and big data converged systems. To the best of our knowledge, there is no such review on data locality in converged HPC and big data systems.

Combining wind and solar photovoltaic (PV) generation can provide complementary renewable power production, but depends on correlated resources. This study analyzed 10 years of wind data from Naama, Algeria to evaluate the potential for evening wind generation to offset the loss of solar at sunset. Average wind speeds showed a distinct increase during evening hours, coinciding with the decrease in solar irradiance. Wind turbine simulations using a 1.5 MW turbine and the wind data showed sufficient resources for profitable power production after sunset. Statistical analyses confirmed significantly higher wind speeds and simulated power output in evening vs daylight periods (p&lt;0.05). The Pearson correlation coefficient between evening wind speeds and decreasing solar irradiance was 0.63, supporting a strong positive relationship. These findings indicate Naama has adequate wind resources to deploy economically viable wind power capacity that can complement existing solar infrastructure and provide renewable electricity after dark , .

This paper presents an approach to the application of the Model-Based Systems Engineering (MBSE) and Model-Based Systems Architecting (MBSA) principles to develop a Model-Based Pattern Language (MBPL). It takes too long for systems engineers and architects to develop a new system from scratch, particularly new space-based systems derived from the existing space systems architectures. A pattern language is a holistic view of reusable logical model artifacts; many are interdisciplinary and introductory, if at all. The results are mostly a combination of the application-specific logical solution, which further results in the best possible overall solution. The main benefit of the pattern language is reducing the time and validation required to generate a new space-based system architecture; this approach will develop top-level requirements in the initial phase of the system development. The rationale of the methodology proposed by the paper is as follows, collect, and decompose published literature and other open-source information available on space system architectures and system models; develop SysML models for systems, subsystems, products, assembly, subassembly level, and mission-specific requirements using CAMEO SysML software. Arrange these patterns to develop a functional ontology and construct a logical architecture pattern library. This approach created, updated, and managed SysML pattern language, which evaluated the expedited new model construction. Again, our objective is to develop a logical pattern language using public domain information and evaluate patterns by constructing a new space mission concept—for example, planetary surface habitat.

Structural self-organizing and pattern formation are universal and key phenomena observed during growth and cluster-assembling of the carbyne-enriched nanostructured metamaterials at the ion-assisted pulse-plasma deposition. Fine tuning these universal phenomena opens access to designing the properties of the growing carbyne-enriched nano-matrix. The structure of bonds in the grown carbyne-enriched nano-matrices can be programmed by the processes of self-organization and auto-synchronization of nanostructures. We propose the innovative concept, connected with application of the universal Cymatics phenomena during the predictive growth of the carbyne-enriched nanostructured metamaterials. We also propose the self-organization approach for increase stability of the long linear carbon chains. The main idea of suggested concept is manipulating by the self-organized wave patterns excitation phenomenon and their distribution by the spatial structure and properties of the nanostructured metamaterial grows region through the new synergistic effect. Mentioned effect will be provided through the vibration-assisted self-organized wave patterns excitation along with simultaneous manipulating by their properties through the electric field. We propose to use acoustic activation of the plasma zone of nano-matrix growing. Interaction between the inhomogeneous electric field distribution generated on the vibrating layer and the plasma ions will serve as the additional energizing factor controlling the local pattern formation and self-organizing of the nano-structures. Suggested concept makes it possible to provide precise predictive designing the spatial structure and properties of the advanced carbyne-enriched nanostructured metamaterials.