A semi-structured interview (SSI) is one of the essential tools in conduction qualitative research. This essay draws upon the pros and cons of applying semi-structured interviews (SSI) in the qualitative research method. Moreover, the challenges of SSI during the coronavirus pandemic are critically discussed to provide plausible recommendations.

The range of rating instruments in depression measurement and the depth of their analytical relevance constitutes a major development in this psychiatric and psychotherapeutic field of mental health. Though the competition is acute amongst these various instruments, the results for the public have been outstandingly positive. A depression rating scale is essentially a psychiatric measuring instrument utilized in the identification and ranking of depression severity within the patient. The scale provides the practitioner, psychiatrist or psychotherapist, with sufficient information to assess the severity of the depression plotted on the scale. Not used as a “diagnostic tool” itself, nevertheless, the depression rating scale does function as an effective device for designating and assigning a behavioral score which may, then, be used in establishing the severity of depression of value in the designation of a diagnosis and treatment formula. In this paper, we will take a close look at the leading depression rating scales and briefly summarize their scope of assessment value in rating depression.

In this paper, we will revisit the derivation of Heisenberg's uncertainty principle. We will see how the Heisenberg principle collapses at the Planck scale by introducing a minor modification. The beauty of our suggested modification is that it does not change the main equations in quantum mechanics; it only gives them a Planck scale limit where uncertainty collapses. We suspect that Einstein could have been right after all, when he stated, ``God does not throw dice." His now-famous saying was an expression of his skepticism towards the concept that quantum randomness could be the ruling force, even at the deepest levels of reality. Here we will explore the quantum realm with a fresh perspective, by re-deriving the Heisenberg principle in relation to the Planck scale. We will show how this idea also leads to an upper boundary on uncertainty, in addition to the lower boundary. These upper and lower boundaries are identical for the Planck mass particle; in fact, they are zero, and this highlights the truly unique nature of the Planck mass particle. Further, there may be a close connection between light and the Planck mass particle: In our model, the standard relativistic energy momentum relation also seems to apply to light, while in modern physics light generally stands outside the standard relativistic momentum energy relation. We will also suggest a new way to look at elementary particles, where mass and time are closely related, consistent with some of the recent work in experimental physics. Our model leads to a new time operator that does not appear to be in conflict with the Pauli objection. This indicates that both mass and momentum come in quanta, which are perfectly correlated to an internal Compton `clock' frequency in elementary particles.

ABSTRACT This study focused for socio-economic benefit of Western shoreline of Lake Ziway ecosystem. The data collected from two woredas they are Adami Tulu Jidu Kombolch (ATJK) and Dugda woreda of fishermen and small scale irrigation users. Lake Ziway great importance food and water for both groups of respondents and additionally sources of raw material, energy, cultivation, organic fertilizers, genetic and medicinal plants. Lake Ziway also has a major economic benefit for both groups of respondents. The sampled fishermen cached mean amount of 2,524Kg per year with minimum and maximum amount of fish 504Kg and 16,800Kg per year respectively and with this fish catching they got average income of 51,398 Birr ($2,570) per year with range of 7,200 Birr ($360) and 288,000 Birr ($14,400) per year. As like of fishermen small scale irrigation also got economic benefit with their production of cereal crops, fruits and vegetables. They produce in average 13.47Quintal of cereal crop and 69.56Quintal of fruits and vegetables per year and they got average income of 7,727 Birr ($386) and with range of 13,714 Birr ($686) per year respectively. this incurred that wetland ecosystem has a lot of socio-economic benefit for the people live near by specially for developing countries like Ethiopia they are more dependent on natural ecosystem like of Lake Ziway. Because of its high importance, we have to protect and conserve and use sustainably of Lake Ziway and similar wetland ecosystems. Key Words: Wetland ecosystem service; Lake Ziway; Socioeconomic benefit; Fishermen; Small scale irrigation users

The microbial contamination in food packaging have been a major concern that paved the way for the search for natural based new anti-microbial agents, such as modified α-mangostin. In the present work, twelve synthetic analogs were obtained via semi-synthetic modification of α-mangostin by Ritter reaction, reduction by palladium-carbon (Pd-C), alkylation, and acetylation. The evaluation of the anti-microbial potential of the synthetic analogs showed higher therapeutic value than the parent molecule. The anti-microbial studies proved that I E showed higher antibacterial activity whereas I I showed most significant antifungal activity. Due to their microbial properties, modified α-mangostin can be utilized as active anti-microbial agents in food packaging.

As early as February 2020, many countries have started imposing measures to curb the spread of Covid-19. Despite the right intention, it is a challenging moment for the people, especially the rural population living in the coastal areas. The document presents the preliminary findings on the impacts of Covid-19 on the small scale fisheries in Tun Mustapha Park, Sabah, Malaysia.

COVID-19 is now a major global health crisis, can lead to severe food crisis unless proper measures are not taken. Though a number of scientific studies have addressed the possible impacts of COVID-19 in Bangladesh on variety of issues, problems and food crises associated with aquatic resources and communities are missing. Therefore, this study aimed at bridging the gap in the existing situation and challenges of COVID-19 by linking its impact on aquatic food sector and small-scale fisheries with dependent population. The study was conducted based on secondary data analysis and primary fieldwork. Secondary data focused on COVID-19 overview and number of confirmed, recovered and death cases in Bangladesh; at the same time its connection with small-scale fisheries, aquatic food production, demand and supply was analyzed. Community perceptions were elicited to present how the changes felt and how they affected aquatic food system and small-scale fisheries and found devastating impact. Sudden illness, reduced income, complication to start production and input collection, labor crisis, transportation abstraction, complexity in food supply, weak value chain, low consumer demand, rising commodity prices, creditor’s pressure were identified as the primary affecting drivers. Dependent people felt the measures taken by the Government should be based on protecting the health and food security, although it could be detrimental to economic growth in the short term. The study provides insight into policies adopted by the policy makers to mitigate the effects of the pandemic on aquatic food sector and small-scale fisheries.

It is important to realize the transformation behavior of wüstite because it greatly affects the final structure of the oxide layer and the surface quality of the steel products. In the present study, the transformation behaviors of the wüstite layer are examined under nearly-oxygen-free conditions, to simulate the cooling processes after the hot rolled strip is coiled. As the single phase wüstite was prepared at 950˚C, the 460˚C transformed oxide layer was composed of a mixture of iron and magnetite formed through eutectoid reactions. For the 750˚C-fabricated wüstite, only magnetite was observed after transformation, without iron precipitates and residual wüstite. It is speculated that the unusual transformation behavior of the low-temperature-made wüstite results from the pseudo-structural intermediate phase transformation between wüstite and magnetite. This pseudo-structure is a pre-transformed wüstite and of various concentration of ferrous ion, which is determined by the fabrication conditions. During the hot strip mill process, the so-called wet scale, wüstite, is produced continuously from finish mill to laminar flow sections and ended at 570˚C. Consequently, the final eutectoid transformation below 570˚C is dominantly controlled by the surface temperature ranged from 750˚C to 950˚C for low carbon steel.

Properties of spatially explicit data are often ignored or inadequately handled in machine learning for spatial domains of application. At the same time, resources that would identify these properties and investigate their influence and methods to handle them in machine learning applications are lagging behind. In this survey of the literature, we seek to identify and discuss spatial properties of data that influence the performance of machine learning. We review some of the best practices in handling such properties in spatial domains and discuss their advantages and disadvantages. We recognize two broad strands in this literature. In the first, the properties of spatial data are developed in the spatial observation matrix without amending the substance of the learning algorithm; in the other, spatial data properties are handled in the learning algorithm itself. While the latter have been far less explored, we argue they offer the most promising prospects for the future of spatial machine learning.

With reference to Planck scale Hubble parameter, super luminal expansion speeds, super luminal rotation speeds, Mach’s principle and Holographic principle, we review the current cosmological observations with eight simple assumptions. By understanding Yuri N. Obukhov and V.A. Korotky proposed cosmic rotational effects of polarization of radiation due to massive bodies, to some extent cosmic rotation can be deep-rooted in an observational approach and the ratio of current angular velocity and Hubble parameter can be estimated. It is possible to show that, at H₀ =70 km/sec/Mpc, current cosmic temperature, age, radius, mass, mass density are 2.721 K, 4.41x10¹⁷ sec, 90 billion light years, 1.14654x10⁵⁴ kg, 0.0482 times the current critical density respectively. Clearly speaking, current universe seems to constitute 267 Hubble spheres. Important point to be noted is that, current rotational kinetic energy is 0.6667 times the current critical energy. Based on the estimated current mass density and current rotational kinetic energy, current cosmic dark matter density can be shown to be 0.2851 times the current critical density. These numerical coincidences cast serious doubt on the on the real existence of currently believed ‘dark energy’. Initial and current expansion speeds are 3x10⁸ m/sec and 3.56x10⁹ m/sec respectively. With increasing cosmic age and increasing cosmic expansion speed, current universe is expanding with a speed of 11.885c. By knowing the time to time future cosmic temperatures, future Hubble parameters and corresponding future cosmic expansion speeds can be estimated and thus future expansion speed can be understood. Starting from ‘speed of light’, our model assumes a continuous increase in expansion speed and attains a current radius of 90 billion light years (without inflationary concepts) and casts a serious doubt on the actuality of currently believed ‘inflation’.

The main foundations of the standard $\Lambda $CDM model of cosmology are that: 1) The redshifts of the galaxies are due to the expansion of the Universe plus peculiar motions; 2) The cosmic microwave background radiation and its anisotropies derive from the high energy primordial Universe when matter and radiation became decoupled; 3) The abundance pattern of the light elements is explained in terms of primordial nucleosynthesis; and 4) The formation and evolution of galaxies can be explained only in terms of gravitation within a inflation+dark matter+dark energy scenario. Numerous tests have been carried out on these ideas and, although the standard model works pretty well in fitting many observations, there are also many data that present apparent caveats to be understood with it. In this paper, I offer a review of these tests and problems, as well as some examples of alternative models.

The development of small scale hydroelectric power plants in Norway is determined by natural conditions, policies, attitudes and property rights. The owner of the river is the central decision maker. It is he who decides whether he will develop the power plant himself, Whether he wants to enter into a contract with an external investor and let him develop the power plant, whether he will sell his property rights or postpone the decisions. All available choices will involve risk. In order for him to make the best choice he must find the certainty equivalent to each of the choices and choose the one with the highest certainty equivalent. This is the first time the utility theory of John von Neumann and Oskar Morgenstern has been applied to decision makers in the hydro power industry in Norway.

This case study assessed marketing arrangements used by small scale farmers in the Lake Basin and Lower Eastern bean corridors of Kenya to determine which markets work for rural producers and what changes are needed to produce and supply sufficient quantities for trade. Using exploratory research, data was collected through focus group discussions with six farmer groups representing a total of 1255 bean farmers and key informant interviews with extension staff. The results indicated that 94% of the farmers produced beans before identifying buyers with only 6% participating in group marketing. Though spot-market transactions with brokers and traders provided ready cash for the farmers, formal buyers were perceived to be more reliable but difficult to find and, operated stringent requirements which were a barrier to entry. A theory of change to integrate smallholders into formal markets to sustainably produce and supply sufficient volumes for trade should entail a transformation agenda at four levels of the value chain: intensification of production through pure stand models with greater use of certified high yielding varieties; stable price guarantees; a market-driven research and extension service and; an enabling political, policy and business environment in the bean value chain. Further research is needed to pilot these changes in a case control study.

Accurate assessment of the breast cancer deterioration degree plays a crucial role in making medical plan, and the important basis for degree assessment is the number of mitoses in a given area of the pathological image. We utilized deep multi-scale fused fully convolutional neural network (MFF-CNN) combing with conditional random felid (CRF) to detect mitoses in hematoxylin and eosin stained histology image. Analyze the characteristics of mitotic detection ----scale invariance and sparsity, as well as the difficulties ---- small amount of data , inconsistent image staining and sample class unbalanced. Based on this, mitotic detection model is designed. In this paper, a tissue-based staining equalization method is used, and to establish an effective training sample set, we select training samples by using CNN. A mitotic detection model fusing multi-level and multi-scale features and context information was designed, and the corresponding training strategy was made to reduce over-fitting. As preliminarily validated on the public 2014 ICPR MITOSIS data, our method achieves a better performance in term of detection accuracy than ever recorded for this dataset.

This article concerns the adoption of small-scale irrigation farming as a climate-smart agriculture practice and its influence on household income in the Chinyanja Triangle. Chinyanja Triangle is a region that experiences mid-season dry spells and an increase in occurrences of drought due to low and erratic rainfall patterns which is attributed largely to climate variability and change. This poses high agricultural production risks, which aggravate poverty and food insecurity. For this region, adoption of small-scale irrigation farming as a climate-smart agriculture practice is very important. Through a binary logistic and ordinary least squares regression, the article determines factors that influence the adoption of small-scale irrigation farming as a climate-smart agriculture practice and its influence on income among smallholder farmers. The results show that off-farm employment, access to irrigation equipment, access to reliable water sources and awareness of water conservation practices, such as rainwater harvesting have a significant influence on the adoption of small-scale irrigation farming. On the other hand, the farmer’s age, distance travelled to the nearest market and nature of employment negatively influenced the adoption of small-scale irrigation farming decisions. Ordinary least squares regression results showed that the adoption of small-scale irrigation farming as a climate-smart agriculture practice has a significant positive influence on agricultural income. We therefore conclude that to empower smallholder farmers to quickly respond to climate variability and change, practices that will enhance adoption of small-scale irrigation farming in the Chinyanja Triangle are critical as this will significantly impact on agricultural income.

In 1990 the Malaysian Government launched Vision 2020 with the goal of Malaysia becoming a ‘fully developed country’ by the year 2020. In this drive for development the country has been examining many of its key natural assets, exploring how to both preserve them whilst ensuring that they make the maximum possible contribution to national development goals. Endau Rompin is one of these assets, being the second largest National Park in Peninsula Malaysia. The rich tropical rainforest flora and fauna of the Park and its hinterland, however, are threatened by various anthropogenic forces, most notably deforestation and poaching; both of which have taken the Park’s flagship species - the Tiger Panthera tigris jacksoni – towards the brink of local extinction. Malaysia’s statutory East Coast Economic Region Development Council commissioned a study to consider ways of increasing tourism revenues from the Park while at the same time reversing these threats. The key conclusion drawn is that a more holistic, landscape-scale approach should be adopted, with Endau Rompin forming part of a wider strategic economic zone based around sustainable tourism and land management. The proposed expanded zone extends eastwards beyond the confines of the Park, across the coastal plain to the South China Sea, and onwards to the neighbouring Mersing Islands. This expanded zone is referred to as Malaysia’s new ‘Rainforest to Reef Region’.

This paper describes the feasibility and probable benefits associated with greening the Tahliah Channel, a concrete drainage channel that was originally built to relieve urban flooding in Jeddah City, Saudi Arabia. It includes an estimation of irrigation needs for channel greening based on a standardized planting specification. The study also demonstrates alternative strategies for meeting the required irrigation demand, including water harvesting and graywater reuse on a residential scale. The study shows that greening Tahliah Channel is possible relying mainly on graywater reuse from the surrounding buildings. Also, the study shows that rainwater harvesting is not a reliable source for irrigation. Rather, it can cover only part of the irrigation needs (6%) and so can be used as a secondary supporting source. The positive results of this case study will be of interest to those in arid countries who are looking to upgrade and replace traditional, single function drainage infrastructure with more sustainable, green infrastructure systems. More specifically, the objectives of the study are consistent with the goals of the Saudi government’s ongoing initiative that advocates for more resilient and sustainable cities. (Vision 2030 year).

We evaluated the potential of using fish species and functional traits as indicators of land use impacts to fish assemblages. We used environmental data collected at multiple spatial scales (local, reach, and upstream catchment) for 19 tributary and main stem sites in the Nolichucky River watershed in Tennessee. Canonical correspondence analyses showed that temperature, elevation, specific conductivity, sediment yield, impervious surfaces, and row crop cover at the catchment scale were strongly associated with fish assemblage structure, as well as forest cover from all three spatial scales. Blocked indicator species analysis, with stream size as the block, showed that significantly strong indicators of the least-impacted riparian land use condition (≥60% forest cover) were Saffron Shiner (Notropis rubricroceus), Rainbow Trout (Oncorhyncus mykiss), Longnose Dace (Rhynichthys cataractae), Creek Chub (Semotilus atromaculatus), and Mottled Sculpin (Cottus bairdi). Traits indicative of the least-impacted sites were the herbivorous trophic guild, mean female age-at-maturity, longevity, rock-gravel spawners, montane geology and pelagic swimmers. Specific conductivity was strongly related to multiple catchment-scale land use variables, and was a strong local-scale influence on fish assemblage structure. Our results show promise for using a relatively common but endemic southern Appalachian fish species, the Saffron Shiner, as an indicator for land-use related impacts to these streams.

Face verification for unrestricted faces in the wild is a challenging task. This paper proposes a method based on two deep convolutional neural networks(CNN) for face verification. In this work, we explore to use identification signal to supervise one CNN and the combination of semi-verification and identification to train the other one. In order to estimate semi-verification loss at a low computation cost, a circle, which is composed of all faces, is used for selecting face pairs from pairwise samples. In the process of face normalization, we propose to use different landmarks of faces to solve the problems caused by poses. And the final face representation is formed by the concatenating feature of each deep CNN after PCA reduction. What's more, each feature is a combination of multi-scale representations through making use of auxiliary classifiers. For the final verification, we only adopt the face representation of one region and one resolution of a face jointing Joint Bayesian classifier. Experiments show that our method can extract effective face representation with a small training dataset and our algorithm achieves 99.71% verification accuracy on LFW dataset.

Estimating ground surface PM2.5 with fine spatiotemporal resolution is a critical technique for exposure assessments in epidemiological studies of its health risks. Previous studies have utilized monitoring, satellite remote sensing or air quality modeling data to evaluate the spatiotemporal variations of PM2.5 concentrations, but such studies rarely combined these data simultaneously. We develop a three-stage model to fuse PM2.5 monitoring data, satellite-derived aerosol optical depth (AOD) and community multi-scale air quality (CMAQ) simulations together and apply it to estimate daily PM2.5 at a spatial resolution of 0.1˚ over China. Performance of the three-stage model is evaluated using a cross-validation (CV) method step by step. CV results show that the finally fused estimator of PM2.5 is in good agreement with the observational data (RMSE = 23.00 μg/m^3 and R2 = 0.72) and outperforms either AOD-retrieved PM2.5 (R2 = 0.62) or CMAQ simulations (R2 = 0.51). According to step-specific CVs, in data fusion, AOD-retrieved PM2.5 plays a key role to reduce mean bias, whereas CMAQ provides all-spacetime-covered predictions, which avoids sampling bias caused by non-random incompleteness in satellite-derived AOD. Our fused products are more capable than either CMAQ simulations or AOD-based estimates in characterizing the polluting procedure during haze episodes and thus can support both chronic and acute exposure assessments of ambient PM2.5. Based on the products, averaged concentration of annual exposure to PM2.5 was 55.75 μg/m3, while averaged count of polluted days (PM2.5 > 75 μg/m3) was 81, across China during 2014. Fused estimates will be publicly available for future health-related studies.

In order to solve the problem of feature extraction of underwater acoustic signals in complex ocean environment, a new method for feature extraction from ship radiated noise is presented based on empirical mode decomposition theory and permutation entropy. It analyzes the separability for permutation entropies of the intrinsic mode functions of three types of ship radiated noise signals, and discusses the permutation entropy of the intrinsic mode function with the highest energy. In this study, ship radiated noise signals measured from three types of ships are decomposed into a set of intrinsic mode functions with empirical mode decomposition method. Then, the permutation entropies of all intrinsic mode functions are calculated with appropriate parameters. The permutation entropies are obviously different in the intrinsic mode functions with the highest energy, thus, the permutation entropy of the intrinsic mode function with the highest energy is regarded as a new characteristic parameter to extract the feature of ship radiated noise. After that, the characteristic parameters, namely, the energy difference between high and low frequency, permutation entropy, and multi-scale permutation entropy, are compared with the permutation entropy of the intrinsic mode function with the highest energy. It is discovered that the four characteristic parameters are at the same level for similar ships, however, there are differences in the parameters for different types of ships. The results demonstrate that the permutation entropy of the intrinsic mode function with the highest energy is better in separability as the characteristic parameter than the other three parameters by comparing their fluctuation ranges and the average values of the four characteristic parameters. Hence, the feature of ship radiated noise can be extracted efficiently with the method.

Full-scale/model test comparison studies to validate the traditional ABL wind tunnel simulation technique are reviewed. According to the literature review, notable discrepancies between full-scale measurement results and model test results were observed by most performed comparison studies, but the causes of the observed discrepancies were not revealed in a scientific way by those studies. In this regard, a new research scheme for future full-scale/model test comparison studies is proposed in this article, which utilizes the multiple-fan actively controlled wind tunnel simulation technique. With the new research scheme, future full-scale/model test comparison studies are expected to reasonably disclose the main problems with the traditional ABL wind tunnel simulation technique, and the technique can be improved correspondingly.

Indoor positioning based on the received signal strength (RSS) of the WiFi signal has become the most popular solution for indoor localization. In order to realize the rapid deployment of indoor localization systems, solutions based on crowdsourcing have been proposed. However, compared to conventional methods, crowdsourced RSS values are more erroneous and can result in large localization errors. To mitigate the negative effect of the erroneous measurements, a graph-based semi-supervised learning (G-SSL) method is used to exploit the correlation between the RSS values at nearby locations to estimate an optimal RSS value at each location. Before using the G-SSL method, the Linear Regression (LR) algorithm is proposed to solve the device diversity problem in crowdsourcing system. Since the spatial distribution of the APs is sparse, the Compressed Sensing (CS) method is applied to precisely estimate the location of the APs. Based on the location of the APs and a simple signal propagation model, the RSS difference between different locations is calculated and used as an additional constraint to improve the performance of G-SSL. Furthermore, to exploit the sparsity of the weights used in the G-SSL, we use the CS method to reconstruct these weights more accurately and make a further improvement on the performance of the G-SSL. Experimental results show improved results in terms of the smoothness of the radio map and the localization accuracy.

This study provides designs for a low-cost, easily replicable open source lab-grade digital scale that can be used as a precision balance. The design is such that it can be manufactured for use in most labs throughout the world with open source RepRap-class material extrusion-based 3-D printers for the mechanical components and readily available open source electronics including the Arduino Nano. Several versions of the design were fabricated and tested for precision and accuracy for a range of load cells. The results showed the open source scale was found to be repeatable within 0.1g with multiple load cells, with even better precision (0.01g) depending on load cell range and style. The scale tracks linearly with proprietary lab-grade scales, meeting the performance specified in the load cell data sheets, indicating that it is accurate across the range of the load cell installed. The smallest loadcell tested(100g) offers precision on the order of a commercial digital mass balance. The scale can be produced at significant cost savings compared to scales of comparable range and precision when serial capability is present. The cost savings increase significantly as the range of the scale increases and are particularly well-suited for resource-constrained medical and scientific facilities.

Artisanal and small-scale gold mining (ASGM) has been an important source of income for communities in the Madre de Dios River Basin in Peru for hundreds of years. However, in recent decades, the scale of ASGM activities in the region has increased dramatically, and exposures to a variety of occupational and environmental hazards related to ASGM, including mercury, are becoming more widespread. The aims of our study were to: (1) examine patterns in the total hair mercury level of human participants in several communities in the region and compare these results to the 2.2 µg/g total hair mercury level equivalent to the World Health Organization (WHO) Expert Committee of Food Additives (JECFA)’s Provisional Tolerable Weekly Intake (PTWI); and (2), to measure the mercury levels of paco (Piaractus brachypomus) fish raised in local aquaculture ponds, in order to compare these levels to the EPA Fish Tissue Residue Criterion of 0.3 µg Hg/g fish (wet weight). We collected hair samples from 80 participants in four communities (one control and three where ASGM activities occurred) in the region, and collected 111 samples from fish raised in 24 local aquaculture farms. We then analyzed the samples for total mercury. Total mercury levels in hair were statistically significantly higher in the mining communities than in the control community, and increased with increasing distance away from the Madre de Dios headwaters (as the crow flies), did not differ by sex, and frequently exceeded the reference level. Regression analyses indicated that higher hair mercury levels were associated with residence in ASGM communities. The analysis of paco fish samples found no samples that exceeded the EPA tissue residue criterion. Collectively, these results align with other recent studies showing that ASGM activities are associated with elevated human mercury exposure. The fish farmed through the relatively new process of aquaculture in ASGM areas appeared to have little potential to contribute to human mercury exposure. More research is needed on human health risks associated with ASGM to discern occupational, residential, and nutritional exposure, especially through tracking temporal changes in mercury levels as fish ponds age, and assessing levels in different farmed fish species. Additionally, research is needed to definitively determine that elevated mercury levels in humans and fish result from the elemental mercury from mining, rather than from a different source, such as the mercury released from soil erosion during deforestation events from mining or other activities.

This study presents a vibration control using actively tunable vibration absorbers (ATVA) to suppress vibration of a thin plate. The ATVA’s is made of a sandwich hollow structure embedded with the electrorheological fluid (ERF). ERF is considered to be one of the most important smart fluids and it is suitable to be embedded in a smart structure due to its controllable viscosity property. ERF’s apparent viscosity can be controlled in response to the electric field and the change is reversible in 10 microseconds. Therefore, the physical properties of the ERF-embedded smart structure, such as the stiffness and damping coefficients, can be changed in response to the applied electric field. A mathematical model is difficult to be obtained to describe the exact characteristics of the ERF embedded ATVA because of the nonlinearity of ERF’s viscosity. Therefore, a fuzzy modeling and experimental validations of ERF-based ATVA from stationary random vibrations of thin plates are presented in this study. Because Type-2 fuzzy sets generalize Type-1 fuzzy sets so that more modelling uncertainties can be handled, a semi-active vibration controller is proposed based on Type-2 fuzzy sets. To investigate the different performances by using different types of fuzzy controllers, the experimental measurements employing type-1 fuzzy and interval type-2 fuzzy controllers are implemented by the Compact RIO embedded system. The fuzzy modeling framework and solution methods presented in this work can be used for design, performance analysis, and optimization of ATVA from stationary random vibration of thin plates.

Smart grid software interconnects multiple Engineering disciplines (power systems, communication, software and hardware technology, instrumentation, big data, etc.). The software architecture is an evolving concept in smart grid systems in which systematic architecture development is a challenging process. The architecture has to realize the complex legacy power grid systems and cope up with current Information and Communication Technologies (ICT). The distributed generation in smart grid environment expects the software architecture to be distributed and to enable local control. Smart grid architecture should also be modular, flexible and adaptable to technology upgrades. In this paper, the authors have made a comprehensive review on architecture for smart grids. An in depth analysis of layered and agent based architectures is presented and compared under various domains.

Bamboo agroforestry is currently being promoted as a viable land use option to reduce dependence on natural forest for wood fuels in Ghana. To align the design and introduction of bamboo agroforestry in conformity with farmers’ needs, perceptions, skills and local cultural practices, information on its acceptability and adoption potential among farmers is necessary. It is therefore the objective of this study to (1) describe bamboo ethnobotany and (2) assess socioeconomic factors that affect the acceptability and adoption of bamboo and its integration into farming practices. Accordingly, information has been collected from 200 farmers in the dry semi-deciduous forest zone of Ghana. The study identified the socioeconomic risks and uncertainties as well as biophysical factors that are likely to influence the potential adoption of bamboo agroforestry in the study region. Gender, age, farmers’ known uses of bamboo, the practice of leaving trees on farmlands, farmers’ networking and access to extension services, land availability and ownership by farmers were identified as suitable predictor variables for the adoption of bamboo agroforestry. It is envisaged that bamboo agroforestry is a good bet in the DSFZ though there is the need to explore domestic energy (fuelwood) provision and substitution potential in order to have a broader picture of the technology.

In this paper, a semi-empirical model of air waves induced by falling rock is described. The model is composed of a uniform motion phase (velocity close to 0 m·s^-1) and an acceleration movement phase. The uniform motion phase was determined based on experimentally and the acceleration movement phase was derived by theoretical analysis. A series of experiments were performed to verify the semi-empirical model and elucidated the law of the uniform motion phase. The acceleration movement phase accounted for a larger portion with a greater height of the falling rock. Experimental results of different falling heights of the goaf showed close agreement with theoretical analysis values. The semi-empirical model could accurately and conveniently estimate the velocity of air wave induced by falling rock. Thus, the semi-empirical model can provide a reference and basis for estimating the speed of air waves and designing protective measures in mines.

This paper evaluates the feasibility of applying Massive MIMO to tackle the uplink mixed-service communication problem. Under the assumption of an available physical narrowband shared channel (PNSCH), devised to exclusively consume data traffic from Machine Type Communications (MTC) devices, the capacity (i:e:, number of connected devices) of MTC networks and, in turn, that of the whole system, can be increased by clustering such devices and letting each cluster share the same time-frequency physical resource blocks. Following this research line, we study the possibility of employing sub-optimal linear detectors to the problem and present a simple and practical channel estimator that works without previous knowledge of the large-scale channel coefficients. Our simulation results suggest that the proposed channel estimator performs asymptotically as well as the MMSE estimator with respect to the number of antennas and the uplink transmission power. Furthermore, the results also indicate that, as the number of antennas is made progressively larger, the performance of sub-optimal linear detection methods approaches the perfect interference-cancellation bound. The findings presented in this paper shed light on and motivate for new and exciting research lines towards a better understanding of the use of massive MIMO in MTC networks.

After reviewing foundational literature by Snyder, I will demonstrate how hope theory has been used in psychological interventions and psychiatry, how hope influences learning and medical outcomes, and how hope can be applied to difficult life circumstances. Using this literature review, hope theory will be interrogated. I will argue that hope theory has developed its way through the years to garner many strengths, however a few weaknesses do exist and will be described. I will conclude with recommendations for using hope theory in practice, including the medical field, psychological interventions and counseling, and student development.

The quality of digital elevation models (DEMs) is inevitably affected by the limitations of the imaging modes and the generation methods. One effective way to solve this problem is to merge the available datasets through data fusion. In this paper, a fusion-based global DEM dataset (82°S-82°N) is introduced, which we refer to as GSDEM-30. This is a 30-m DEM mainly reconstructed from the unfilled SRTM1, AW3D30, and ASTER GDEM v2 datasets combining the multi-source and multi-scale fusion techniques. A comprehensive evaluation of the GSDEM-30 data, as well as the 30-m ASTER GDEM v2 and AW3D30 DEM, was presented. Global ICESat GLAS data and the local National Elevation Dataset (NED) were used as the reference for the vertical accuracy validation, while GlobeLand30 was introduced for the landscape analysis. Furthermore, we employed the maximum slope approach to detect the potential artefacts in the DEMs. The results show that the GDEM data are seriously affected by noise and artefacts. With the advantage of the multiple datasets and the refined post-processing, the GSDEM-30 are contaminated with fewer anomalies than both ASTER GDEM and AW3D30. The fusion techniques used can also be applied to the reconstruction of other fused DEM datasets.

Given the cross-scale interactions of agricultural ecosystems, it is important to collect ecosystem service data at the multiple spatial scales they operate at. Mapping of ecosystem services helps to assess their spatial and temporal distribution and is a popular communication tool of their availability and value. For example, maps can be used to quantify distance between areas of available ecosystem services and their beneficiaries and how services fluctuate with changes in land use patterns over time, allowing identification of synergies and trade-offs. However, a lack of local context and too large a resolution can reduce the utility of these maps, whilst masking heterogeneities in access due to equity dynamics. This review identifies and summarizes eight main methods of ESS mapping found in the literature—remote sensing, biophysical modelling, agent based modelling, economic valuation, expert opinion, user preference, participatory mapping, and photo-elicitation. We consider what spatial scales these methods are utilized at and the transferability of data created by each method. The analysis concludes with a methodological framework for mapping ecosystem services, intended to help researchers identify appropriate methods for a multi-scale research design. The framework is exemplified with an overview of a research project in Ethiopia.

Risk-averse areas such as the medical, aerospace and energy sectors have been somewhat slow towards accepting and applying Additive Manufacturing (AM) in many of their value chains. This is partly because there are still signicant uncertainties concerning the quality of AM builds. This paper introduces a machine learning algorithm for the automatic detection of faults in AM products. The approach is semi-supervised in that, during training, it is able to use data from both builds where the resulting components were certied and builds where the quality of the resulting components is unknown. This makes the approach cost ecient, particularly in scenarios where part certication is costly and time consuming. The study specically analyses Selective Laser Melting (SLM) builds. Key features are extracted from large sets of photodiode data, obtained during the building of 49 tensile test bars. Ultimate tensile strength (UTS) tests were then used to categorise each bar as `faulty' or `acceptable'. A fully supervised approach identied faulty specimens with a 77% success rate while the semi-supervised approach was able to consistently achieve similar results, despite being trained on a fraction of the available certication data. The results show that semi-supervised learning is a promising approach for the automatic certication of AM builds that can be implemented at a fraction of the cost currently required.

Most of the pore-scale imaging and simulations of non-Newtonian fluid are based on the simplifying geometry of network modeling and overlook the fluid rheology and heat transfer. In the present paper, we developed a non-isothermal and non-Newtonian numerical model of the flow properties at pore-scale by direct simulation of the 3D micro-CT images using a Finite Volume Method (FVM). The numerical model is based on the resolution of the momentum and energy conservation equations. Owing to an adaptive meshing technique and appropriate boundary conditions, rock permeability and mobility are accurately computed. A temperature and concentration-dependent power-law viscosity model in line with the experimental measurement of the fluid rheology is adopted. The model is first applied at isothermal condition to 2 benchmark samples, namely Fontainebleau sandstone and Grosmont carbonate, and is found to be in good agreement with the Lattice Boltzmann method (LBM). Finally, at non-isothermal conditions, an effective mobility is introduced that enables to perform a numerical sensitivity study to fluid rheology, heat transfer, and operating conditions. While the mobility seems to evolve linearly with polymer concentration, the effect of the temperature seems negligible by comparison. However, a sharp contrast is found between carbonate and sandstone under the effect of a constant temperature gradient. Besides concerning the flow index and consistency factor, a good master curve is derived when normalizing the mobility for both the carbonate and the sandstone.

Relying on Random Utility Theory (RUT) as the guiding mechanism for the Data Generating Process (DGP), this paper uses households consumption choices on cooking fuel, drinking water, and sanitation from the 2014 United States Agency for International Development's (USAID) Demographic and Health Survey (DHS) data on Burkina Faso, to characterize and investigate the inter-linkages between health consciousness and environmental consciousness, and their relationship with wealth in a low income country context. We achieve this by specifying sequentially three econometric modeling frameworks: the first one being independent binary probit (IBP) models to describe each choice process, followed by a fully parametric trivariate probit (FPTP) model to account for choice dependency, and finally by a semi-parametric trivariate probit (SPTP) model to further relax the linearity assumption. Based on the Akaike Information criteria (AIC) and the estimated Trivariate model correlation coefficients, the SPTP framework is found to be the best specification for describing the observed consumption behaviors. The results show that increased wealth level raises households health and environmental consciousness, while leaving the relative preference ordering over the elements in the household consumption basket unchanged.

This paper develops Bayesian inference in reliability of a class of scale mixtures of log-normal failure time (SMLNFT) models with stochastic (or uncertain) constraint in their reliability measures. The class is comprehensive and includes existing failure time (FT) models (such as log-normal, log-Cauchy, and log-logistic FT models) as well as new models that are robust in terms of heavy-tailed FT observations. Since classical frequency approaches to reliability analysis based on the SMLNFT model with stochastic constraint are intractable, the Bayesian method is pursued utilizing a Markov chain Monte Carlo (MCMC) sampling based approach. This paper introduces a two-stage maximum entropy (MaxEnt) prior, which elicits a priori uncertain constraint and develops Bayesian hierarchical SMLNFT model by using the prior. The paper also proposes an MCMC method for Bayesian inference in the SMLNFT model reliability and calls attention to properties of the MaxEnt prior that are useful for method development. Finally, two data sets are used to illustrate how the proposed methodology works.

Technology is in the way to reach in its climax but the basic understanding of science in many phenomena is still awaited even though the nature witnesses it. Scientific research reveals strong analogy between photon and electron. When an atom deals neutral state, it levitates electron of outer ring from the back surface while placing the bit-energy at front surface. Gravitation behavior of that electron starts at the centre of relaxation point by including the force of side pole where the pulling force of nearby unfilled state of that atom from the front surface results into depict forcing energy shape like Gaussian distribution symbol with both ends turned called unit photon. The inertia is being involved at each stage of changing direction of that electron by introducing the disappearances of forces of two poles against the appearances of forces of two opposite poles during rest to motion and motion to rest in the first half-cycle. The same is the case in the second half-cycle of that electron during rest to motion and motion to rest but it is under different introduction of the disappearances of forces against appearances of forces. However, at stage of levitating or gravitating period of electron, only one force is being involved at one time where the opposite force is disappeared. The uninterrupted confined inter-state electron-dynamics of atom under the availability of several bits of bit-energy results into generate forcing energy shape like a wave. Two bits of bit-energy where shape of bit for first half-cycle is like integral symbol and second half-cycle is like opposite integral symbol which are being placed along the configuring trajectory of inter-state electron-dynamics during forward-direction cycle and two bits of bit-energy shape in opposite order are being placed along the trajectory of inter-state electron-dynamics during back-direction cycle. Generating forcing energy of unit photon in each cycle is pushing to the rear side by remaining connected till the electron is not restoring the state of rest. Silicon atom is considered as a model system under neutral state. Uninterrupted confined inter-state electron-dynamics result into generate forcing energy that can travel immeasurable length and unavailability of necessitating bit-energy at any interrupted stage result into generate an overt photon. Inter-state electron-dynamics for at least two cycles generate an overt photon –a photon length twice to unit photon. Under certain interaction of unit photon, it divides equally into two bits of bit-energy instead of dividing into tits and bits of heat. The mechanism of generating photon characteristic current by the electron of neutral state atom validates that atoms are four-dimensional discs at centre of dealing no force. An isolated electron is being grounded under directed forcing energy to impinge a neutral state atom where the gained instantaneous velocity under merged energy resulting into distort atom at that point. Matter changes the role of energy and force under various sorts of interactions. Here, heat energy and photon energy explore matter at atomic and electron levels, thus, devise basis of science to describe.

Abstract: Comparing outcrop data to laboratory results is important to verify and validate experiments of analogue and reservoir materials especially regarding conditions for deformation experiments. This is important better understand highly complex carbonate reservoir strata and their response to changes in subsurface conditions, reducing subsurface uncertainty. This study develops methods to allow for a more straightforward comparison of outcrop data (m-scale) with experimentally created fracture arrays developed in cylindrical samples (cm-scale). The main objective is to assess usefulness of experimentally-produced fracture networks as analogues for subsurface structures, typically at the meter and above scale by developing new techniques to use the lab deformation. It analyses key characteristics of laboratory-induced fracture networks by adapting scanline methods to use with x-ray tomography (XRT) images to allow for comparison with outcrop and field data. To test and verify these new methods two low permeability carbonate samples were used for deformation testing and analysis. Applying the different scanline methods we show that they can be used to analyse lab induced fractures (mm to cm-scale) identified in XRT images for comparison with outcrop data (m-scale). In addition, these methods also allow for quantification of fracture network attributes e.g. fracture spacing, fracture apertures, orientation. This new data bridges the gap between micro-scanlines using thin sections and outcrop scanlines.

This paper considers a two-way relay network, where two source nodes exchange messages through several relays in the presence of an eavesdropper, and the channel state information (CSI) of the eavesdropper is imperfectly known. The amplify-and-forward relay protocol is used and the relay beamforming weights are designed. The model is built up to minimize the total relay transmit power while guaranteeing the quality of service at users and preventing the eavesdropper from decoding the signals. Due to the imperfect CSI, a semi-infinite programming problem is obtained. An algorithm is proposed to solve the problem, and the iterative points are updated through the linesearch technique, where the feasibility are preserved during iterations. The optimality property is analyzed. The obtained subproblems are quadratic constrained quadratic programming problems, either with less than $4$ constraints or with only one variable, which are solved optimally. Simulation results demonstrate the importance of the proposed model, and imply that the proposed algorithm is efficient and converges very fast, where more than 85% of the problems are solved optimally.

Semi-solid feedstock of AZ80 magnesium alloy modified by minor rare-earth Y element (0, 0.2, 0.4, 0.8 wt.%) were fabricated by strain induces melting activated (SIMA) in the form of extrusion and partial remelting. The effect of Y addition on the microstructure evolution of extruded and isothermal treated alloy was observed by optical microscope (OM), scanning electron microscope (SEM), X-ray diffraction (XRD) and quantitative analysis. The results show that the Y addition can refine the microstructure and make the β-Mg17Al12 phases agglomerating. During the subsequent isothermal treatment at 570℃, the average solid grain size, shape factor and liquid fractions increased with prolonged soaking time. Smaller spheroidal solid grains and the larger shape factor were obtained due to Y addition. The coalescence and Ostwald ripening of solid grains operated the coarsening process simultaneously. The coarsening rate constants of AZ80M1 (0.2 wt.% Y addition) of 164.22 μm3s-1 was approximately four times less than the un-modified AZ80 alloy of 689.44 μm3s-1. In contrast, the desirable semi-solid structure featured by fine, well globular solid grains and appropriate liquid fractions and shape factor was achieved in AZ80M1 alloy treated at 570℃ for 20-30 min.

This paper describes how to construct a low-cost magnetic levitation system (MagLev). The MagLev has been intensively used in the engineering education, allowing instructors and students to learn through hands-on experiments essential concepts, such as electronics, electromagnetism, and control systems. Built from scratch, the proposed MagLev depends only on simple, low-cost components readily available on the market. In addition to showing how to construct the MagLev, this paper presents a semi-active control strategy which seems novel when applied in the MagLev. Experiments performed in the laboratory have compared the proposed control scheme with the classical PID control. The corresponding real-time experiments illustrate both the effectiveness of the approach and the potential of the MagLev for education.

The key to simulating soil erosion is to calculate the vegetation cover (C) factor. Methods that apply remote sensing to calculate C factor at regional scale cannot directly use the C factor formula. That is because the C factor formula is obtained by experiment, and needs the coverage ratio data of croplands, woodlands and grasslands at standard plot scale. In this paper, we present a C factor conversion method from a standard plot to a km-sized grid based on large sample theory and multi-scale remote sensing. Results show that: 1) Compared with the existing C factor formula, our method is based on the coverage ratio of croplands, woodlands and grasslands on a km-sized grid, takes the C factor formula obtained from the standard plot experiment and applies it to regional scale. This method improves the applicability of the C factor formula, and can satisfy the need to simulate soil erosion in large areas. 2) The vegetation coverage obtained by remote sensing interpretation is significantly consistent (paired samples t-test, t = −0.03, df = 0.12, 2-tail significance p < 0.05) and significantly correlated with the measured vegetation coverage. 3) The C factor of the study area is smaller in the middle, southern and northern regions, and larger in the eastern and western regions. The main reason for that is the distribution of woodlands, the Hunshandake and Horqin sandy lands and the valleys affected by human activities. 4) The method presented in this paper is more meticulous than the C factor method based on the vegetation index, improves the applicability of the C factor formula, and can be used to simulate soil erosion on large scale and provide strong support for regional soil and water conservation planning.

Global climate change requires urgent solutions. Ambitious tree-planting initiatives, many already underway, aim to sequester enormous quantities of carbon, partly compensating for the anthropogenic CO₂ emissions that are a major cause of rising global temperatures. However, poorly planned and executed tree-planting could actually increase CO₂ emissions and have long-term, deleterious impacts on biodiversity, landscapes and livelihoods. Here, we highlight the main environmental risks of large-scale tree planting and propose ten golden rules, based on some of the most recent ecological research, to implement forest ecosystem restoration that maximizes rates of both carbon sequestration and biodiversity recovery, while simultaneously improving livelihoods. These are: i) Protect existing forest first; ii) Work together (involving all stakeholders); iii) Maximize biodiversity recovery to meet multiple goals; iv) Select appropriate areas; v) Use natural regeneration wherever possible; vi) Select species to maximise biodiversity; vii) Use resilient plant material (with appropriate genetic variability and provenance); viii) Plan ahead for infrastructure, capacity and seed supply; ix) Learn by doing (using an adaptive management approach); and x) Make it pay (ensuring the economic sustainability of the project). We focus on the design of long-term strategies to tackle the climate and biodiversity crises and support livelihood needs. We emphasize the role of local communities and their dependence on benefits from successful reforestation programmes that restore ecosystem functioning and deliver a diverse range of forest products and services. While there is no simple and universal recipe for forest restoration, it is now crucial to build on the public and private interest in this topic to ensure interventions provide effective, long-term carbon sinks and maximise benefits for biodiversity and people.

Local air quality is a major concern for the population regularly exposed to high levels of air pollution. The airport, mainly due to its aircraft engines activities during taxiing and take off, is often submitted to heterogeneous but important concentrations of NOx and PM. The study suggests an innovative approach to determine the air traffic impact on air quality at the scale of the airport, its runways and terminals, in order to be able to locate the persistent high concentrations spots. The pollutants concentrations at 10 m resolution and 1 s time step are calculated in order to identify the most affected areas of an airport platform. A real day of air traffic on a regional airport is simulated, using real data as aircraft trajectories (from radar streams). In order to estimate the aircraft emissions, the Air Transport Systems Evaluation Infrastructure (IESTA) is used. Regarding local air quality, IESTA relies on the non-hydrostatic meso-scale atmospheric model Meso-NH using grid-nesting capabilities with 3 domains, for this study. The detailed cartography of the airport distinguishes between grassland, parking and terminals, allowing to compute exchanges of heat, water and momentum between the different types of surfaces and the atmosphere as well as the interactions with the building using a drag force. The dynamic parameters like wind, temperature, turbulent kinetic energy and pollutants concentration are computed at 10 m resolution over the 2 × 4 km airport domain. The pollutants are considered in this preliminary study as passive tracers, without chemical reactions. This preliminary study aims at proving the feasibility of high scale modelling over an airport with state of the art physical models.

In daily living environments, an individual’s state influences spatial perception. The current study, based on Attention Restoration Theory, aimed to explore differences in the health utility of nature according to individual differences in spatial perception. Cognitive mapping and the Perceived Restorativeness Scale (PRS) were used to assess spatial perception ranges and the restorative effect of the environment. Two spatial perceptual groups were defined: one describing only the internal area of a green space, and another illustrating the external area of this green space on a larger scale. The former had higher overall PRS, Being Away, Fascination, and Compatibility scores. The latter had higher scores only on the Coherence subscale. These results illustrate that frequency of nature visits and time spent traveling to do so differently influence the two groups’ attentional restoration, which has great implications for landscape planning in highly stressful urban environments.

Vacuum drying can dehydrate materials further than dry heat methods while protecting sensitive materials from thermal degradation. Many industries have shifted to vacuum drying as cost- or time-saving measures. Small-scale vacuum drying, however, has been limited by high costs of specialty scientific tools. To make vacuum drying more accessible, this study provides design and performance information for a small-scale open source vacuum oven, which can be fabricated from off-the-shelf and 3-D printed components. The oven is tested for drying speed and effective-ness on both waste plastic polyethylene terephthalate (PET) and a consortium of bacteria developed for bioprocessing of terephthalate wastes to assist in distributed recycling of PET for both additive manufacturing as well as potential food. Both materials can be damaged when exposed to high temperatures, making vacuum drying a desirable solution. The results showed the open source vacuum oven was effective at drying both plastic and biomaterials, drying at a higher rate than a hot-air dryer for small samples or for low volumes of water. The system can be constructed for less than 20% of commercial vacuum dryer costs for several laboratory-scale applications including dehydration of bio-organisms, drying plastic for distributed recycling and additive manufacturing, and chemical processing.

Both climate change and anthropogenic activities contribute to the deterioration of terrestrial water resources and ecosystems worldwide. Central Asian endorheic basins are among the most affected regions through both climate and human impacts. Here, we used a digital elevation model, digitized bathymetry maps and Landsat images to estimate the areal water cover extent and volumetric storage changes in small terminal lakes in Burabay National Nature Park (BNNP), located in Northern Central Asia (CA), for the period of 1986 to 2016. Based on the analysis of long-term climatic data from meteorological stations, short-term hydrometeorological network observations, gridded climate datasets (CRU) and global atmospheric reanalysis (ERA Interim), we have evaluated the impacts of historical climatic conditions on the water balance of BNNP lake catchments. We also discuss the future based on regional climate model projections. We attribute the overall decline of BNNP lakes to long-term deficit of water balance with lake evaporation loss exceeding precipitation inputs. Direct anthropogenic water abstraction has a minor importance in water balance. However, the changes in watersheds caused by the expansion of human settlements and roads disrupting water drainage may play a more significant role in lake water storage decline. More precise water resources assessment at the local scale will be facilitated by further development of freely available higher spatial resolution remote sensing products. In addition, the results of this work can be used for the development of lake/reservoir evaporation models driven by remote sensing and atmospheric reanalysis data without the direct use of ground observations.

Cancer is one of the leading causes of death and morbidity with a complex pathophysiology. Traditional cancer therapies include chemotherapy, radiation therapy, targeted therapy, and immunotherapy. However, limitations such as lack of specificity, cytotoxicity, and multi-drug resistance pose a substantial challenge for favorable cancer treatment. The advent of nanotechnology has revolutionized the arena of cancer diagnosis and treatment. Nanoparticles (1-100nm) can be used in the treatment of cancer owing to their specific advantages such as biocompatibility, reduced toxicity, more excellent stability, enhanced permeability and retention effect, and precise targeting. Nanoparticles are classified into several main categories. The nanoparticle drug delivery system is particular and utilizes tumor and tumor environment characteristics. Nanoparticles not only solve the limitations of conventional cancer treatment but also overcome multidrug resistance. Additionally, as new multidrug resistance mechanisms are unraveled and studied, nanoparticles are being investigated more vigorously. Various therapeutic implications of nano-formulations have created brand new perspectives for cancer treatment. However, a majority of the research is limited to in vivo and in vitro studies, and the number of nano-drugs that are approved has not much amplified over the years. In this review, we discuss numerous types of nanoparticles, targeting mechanisms along with approved nanotherapeutics for oncological implications in cancer treatment. Further, we also summarize the current perspective, advantages, and challenges in clinical translation.

Small-scale fishers are considered as one of the most vulnerable communities in Bangladesh but very few studies focused on the livelihood sustainability and vulnerabilities of this professional group. A fieldwork in lower Padma and upper Meghna hilsa sanctuaries identifies different livelihood characters and associated vulnerabilities of the fishers. A conceptual framework known as Sustainable Livelihood Approaches (SLA) has been introduced to analyses the qualitative and quantitative data. The insights of the livelihood strategies provide on small-scale fishers and fisheries management have been explained and explored. Fishers are found solely dependent on fishing, economically insolvent and neglected. In addition, some socio-economic abstractions such as low income, credit insolvency, lack of substitute earning flexibility make them more vulnerable. A number of effective suggestions are elicited from fishers’ perceptions, the implementation of which is crucial to ensure livelihood sustainability of the small-scale fishers.

Due to its spatio-temporal variability, the mismatch between the weather and demand patterns challenges the design of highly renewable energy systems. A principal component analysis is applied to a simplified networked European electricity system with a high share of wind and solar power generation. It reveals a small number of important mismatch patterns, which explain most of the system's required backup and transmission infrastructure. Whereas the first principal component is already able to reproduce most of the temporal mismatch variability for a solar dominated system, a few more principal components are needed for a wind dominated system. Due to its monopole structure the first principal component causes most of the system's backup infrastructure. The next few principal components have a dipole structure and dominate the transmission infrastructure of the renewable electricity network.

In order to coordinate the damping performance and energy regenerative performance of energy regenerative suspension, this paper proposes a structure of vehicle semi-active energy regenerative suspension with electro-hydraulic actuator (EHA). In light of the proposed concept, a specific energy regenerative scheme is designed and the mechanical properties test is carried out. Based on the test results, the parameter identification for the system model is conducted using recursive least squares algorithm. On the basis of system principle, the nonlinear model of the semi-active energy regenerative suspension with EHA is built. Meanwhile, LQG control strategy of the system is designed. And then the influence of the main parameters of EHA on the damping performance and energy regenerative performance of suspension is analyzed. Finally, the main parameters of EHA actuator are optimized via genetic algorithm. The test results show that when sinusoidal is input at the frequency of 2Hz and the amplitude of 30mm, the spring mass acceleration RMS value of optimized EHA semi-active energy regenerative suspension is reduced by 22.23% and energy regenerative power RMS value is increased by 40.51%, which means while meeting the requirements of certain vehicle ride comfort and driving safety, energy regenerative performance is improved significantly.

In previous researches, Job Crafting questionnaire to develop is consists of 3 factors which are Task Crafting, Cognitive Crafting, and Relationship Crafting with 12 to 17 items. The purpose of study is to develop JCQ for leisure sports instructor of Korean. 274 valid samples are used for analysis. Data collecting is purposeful sampling. At result, for Korean Sports Instructor Job Crafting Scale is constructed 3 factors with 12 items is constructed by 3 step procedure. KSIJCQ is confirmed on convergent discriminant validity evidence. In conclusion, KSIJCQ is a valid scale of the measuring and distributes Job Crafting of generalization in sports.

Digital Elevation Models (DEMs) are widely used in geographic and environmental studies. In the current work, the fusion of multi-source DEMs is investigated to improve the overall accuracy of public domain DEMs. Multi-scale decomposition is an important analytical method in data fusion. Three multi-scale decomposition methods – the wavelet transform (WT), bidimensional empirical mode decomposition (BEMD) and nonlinear adaptive multi-scale decomposition (N-AMD) - are applied to the 1-arc-second Shuttle Radar Topography Mission Global digital elevation model (SRTM-1 DEM) and the Advanced Land Observing Satellite World 3D – 30 m digital surface model (AW3D30 DSM) in China. Of these, the WT and BEMD are popular image fusion methods. A new approach for DEM fusion is developed using N-AMD (which is originally invented to remove the cycle from sunspots). Subsequently, a window-based rule is proposed for the fusion of corresponding frequency components obtained by these methods. Quantitative results show that N-AMD is more suitable for multi-scale fusion of multi-source DEMs, taking the ice cloud and land elevation satellite (ICESat) global land surface altimetry data as a reference. The vertical accuracy of the fused DEM shows significant improvements of 29.6% and 19.3% in a mountainous region and 27.4% and 15.5% in a low-relief region, compared to the SRTM-1 and AW3D30 respectively. Furthermore, a slope position-based linear regression method is developed to calibrate the fused DEM for different slope position classes, by investigating the distribution of the fused DEM error with topography. The results indicate that the accuracy of the DEM calibrated by this method is improved by 16% and 13.6%, compared to the fused DEM in the mountainous region and low-relief region respectively, proving that it is a practical and simple means of further increasing the accuracy of the fused DEM.

We mainly describe the influence factors of captured power by huge wave energy harvesters, which the vertical motion of buoy can transform ocean’s potential energy into piezoelectric energy power by waves. By means of semi-analytical solutions and theoretical analysis, related environmental coefficients are analyzed firstly and find the most appropriate wave frequency and geometric structure as reference. Secondly, the numerical results also discuss the impact trend of hydrodynamic parameters and geometric volume on motion, voltage and power with qualitative agreement. The simulation data confirm that structure parameters of the modified model could markedly deliver sufficient power to ocean high electrical equipment with long-time stability.

Objective: The goal of this study was to analyse the attitudes and perceptions of emergency and mental health nurses through the validation of the SM-GIBED scale in specialised care in Spain on alcoholics and other drug-dependent patients. Design and Setting: This cross-sectional study was developed using the Spanish hospital version of the Seaman-Mannello scale to denominate the SM-GIBED scale. Participants: 170 Emergency and Mental Health Nursing from five Spanish Hospitals. Intervention: Self-administered questionnaire to analiyse the perceptions and attitudes about the drug addict and the alcoholic. Primary and Secondary Outcome Measures: A descriptive and inferential analysis of the study variables was carried out. A psychometric analysis was performed to validate the scale. Results: A total of 170 questionnaires were collected from 257 healthcare workers. Overall, 99.1% of the participants had contact with drug-dependent patients during their professional experience. Nearly 75% had difficulties in treating them. The psychometric analysis of the SM-GIBED scale in the Spanish context obtained values of KMO = 0.655 and Bartlett's test p < 0.000. Cronbach's alpha of 0.738 was obtained from the reliability analysis. A reliability analysis of each of the SM-GIBED questions found no case with an alpha lower than 0.71. In conclusion, positive aspects include an ingratiating attitude and subject-to-subject communication when nurses self-define as empathic and non-paternalistic. Among the negative aspects, there is a lack of communication skills and assertiveness with these patients. This highlights a certain degree of resignation and dissatisfaction when working with drug addicts.

Increased attention has been paid to the influence of coal mining subsidence on ecological environment. Restoration of ecosystem in damaged mining area is critical for restoring disturbed environment. The comparing of plant communities and microbial communities in the artificial restoration and natural restoration areas provides an effective method for evaluating the restoration effects. However, such studies are limited in coal mining subsidence restoration areas. Subsidence area in Shendong mining area, located in the semi-arid region of Western China, was restored from 2003 with 5 ecological restoration plant species. In July 2017, the comparison and analysis of plant and microbial communities were conducted at the artificial restoration areas (AR) and the natural remediation areas (NR). The results showed that the artificial ecological restoration in Shendong mining area has achieved some success, but it has not recovered to a similar ecosystem before the destruction. A higher plant species, coverage and bacterial community diversity were observed in AR. However, these features have lower similarity compared with those in NR sites. Potential soil factors, such as pH, moisture content, total carbon content, organic matter, nitrogen and bulk density, have a greater impact on soil bacterial community structure and diversity. In the ecological restoration of the mining area, attention should be paid to the restoration of soil properties in the mining area. This study can provide theoretical guidance for more scientific ecological restoration in the damaged mining area.

The objective of this research is to develop an experimental-theoretical analysis about the influence of the cooling medium and the geometry of the welding bead profile in fatigue life and associated parameters with structural integrity of welded joints. A welded joint with cruciform geometry is considered using SMAW, plates in structural steel ASTM A36 HR of 8 mm of thickness and E6013 electrode input. A three-dimensional computational model of the cruciform joint was created using the finite element method. For this model, the surface undulation of the cord and differentiation in the mechanical properties of the fusion zone were considered, the heat-affected zone (HAZ) and base material, respectively. In addition, an initial residual stress field which was established experimentally was considered. The results were a set of analytical expressions for the weld magnification factor Mk. It was found that values for the latter decrease markedly in function of the intensity of the cooling medium used in the post welding cooling phase, mainly due to the effect of the residual compressive stresses. The obtained models of behavior of the weld magnification factor are compared with the results from other researchers with some small differences, mainly due to the inclusion of the cooling effect of the post weld and the variation of the leg of the weld bead. The obtained analytical equations in the present research for Mk can be used in management models of life and structural integrity for this type of welded joint.

We focus on macromolecules which are modelled as sequentially growing dual scale-free networks. The dual networks are built by replacing star-like units of the primal treelike scale-free networks through rings, which are then transformed in a small-world manner up to the complete graphs. In this respect, the parameter γ describing the degree distribution in the primal treelike scale-free networks regulates the size of the dual units. The transition towards the networks of complete graphs is controlled by the probability p of adding link between non-neighbouring nodes of the same initial ring. The relaxation dynamics of the polymer networks is studied in the framework of generalized Gaussian structures by using the full eigenvalue spectrum of the Laplacian matrix. The dynamical quantities on which we focus here are the averaged monomer displacement and the mechanical relaxation moduli. For several intermediate values of the parameter’s set (γ, p) we encounter for these dynamical properties regions of constant in-between slope.

The world is currently, subjected to the worst health crisis documented in modern history; an epidemic led by the novel coronavirus disease 2019 (COVID-19). At the epicenter of this crisis, healthcare professionals continue working to safeguard our well-being. To the regular high levels of stress, COVID new heights even more to healthcare professionals so depending on the area, specialty, and type of work. Here we investigated what are the tendencies, or areas most affected. Through an adaptation of the original COVID-stress scale, we developed a remote, fast test designed for healthcare professionals of the Northeastern part of Mexico, an important part of the country with economic and cultural ties to the US. Our results showed 4 key correlations as highly dependent: Work area – Xenophobia (p &lt; 0.045), Work with COVID patients - Traumatic stress (p &lt; 0.001) and Total number of COVID patients per day – Traumatic stress (p &lt; 0.027), and Total number of COVID patients - Compulsive checking and reassurance. Overall concluding that normal levels of stress have increased (mild – moderate). Additionally, we further determine that the fear of being an asymptomatic patient (potential to spread without knowing) continues being a concern.

Remote sensing technology provides a new way to explore the earth for geoscience applications. In the context of continuous deepening of geological research and the vigorous development of geospatial information science, 3D geological modeling technology has become a research hotspot in the intersection of earth science and information science. The traditional 3D geological modeling technology refers to underground 3D modeling using geological data. This modeling method can only display the underground scene in 3D visualization, but cannot display the surface in detail. In this study, remote sensing technology is adopted to improve the traditional 3D geological modeling method, so that geological modeling can be integrated with remote sensing image, and a new 3D geological modeling method based on remote sensing technology is developed. This method can perform integrated 3D visualization of underground and aboveground scenes, which provides a new way for disaster prevention and reduction, geological prospecting and tectonic interpretation. The new 3D geological modeling method is mainly applied in the geological field, and has made new progress in multi-source heterogeneous geological data fusion, large-scale high-precision modeling, geological grid subdivision, attribute modeling technology, remote sensing image fusion and other aspects. Taking the Ya'an area as an example, this paper makes use of the new generation of 3D geological modeling technology to carry out 3D geological modeling and visual display. The 3D visualization in Ya'an area verifies the feasibility and effectiveness of the new 3D geological modeling method based on remote sensing technology in the current data environment.

Mechanical recycling of solid plastic wastes on a small-scale level can be accomplished with the correct approaches. Thermoplastics are mostly considered for mechanical recycling because of their physical properties and ease of reprocessing. This paper reviews the mechanical reprocessing techniques of selected thermoplastics (polyethylene terephthalate and polyolefins) since they constitute a significant proportion of plastics used commercially. Furthermore, necessary considerations for effective operation of small-scale plants, including energy requirements of machinery and optimisation in order to improve efficiency and product quality, are discussed. A clearer understanding and addressing of the process-related challenges will lead to successful establishment and management of small-scale mechanical recycling facilities to benefit communities. Efficient small-scale mechanical reprocessing establishments have become essential in reducing the environmental impacts of solid plastic wastes and for energy conservation.

Women have been leading organizations and communities for centuries, but their journeys in leadership have sometimes been challenging. This paper aims to reflect on women's positive and negative experiences in leadership roles and understand the factors contributing to their successes and challenges.To explore these issues, we will draw on various academic literature, including studies on gender and leadership and case studies of women in leadership positions. We will also examine the cultural and social factors that affect women's experiences in leadership, including bias and discrimination, societal expectations, and work-life balance challenges.One key theme from this analysis is the importance of role models and support networks in helping women succeed in leadership roles. Women with access to mentorship, sponsorship, and peer networks are more likely to thrive in their roles and overcome the challenges they may face. However, lacking female role models and mentors can make it difficult for women to advance in their careers and contribute to feelings of isolation and imposter syndrome.Another important theme is the need for organizations and society to address systemic biases and discrimination that prevent women from reaching their full potential. This can include initiatives such as unconscious bias training, flexible work arrangements, and policies that support gender diversity and inclusion.In conclusion, this paper highlights women's positive and negative experiences in leadership roles and emphasizes the need for ongoing efforts to support and empower women in leadership. By addressing the challenges women face and building a culture of inclusion and support, organizations and society can help unlock the full potential of women leaders and create a more equitable and just world.

Postpartum depression (PPD) has serious effects on maternal and infant morbidity and mortality. This study aimed to determine the prevalence of postpartum depression in mothers of under-twos in military barracks in Lagos. The Edinburgh Postnatal Depression Scale (EPDS) and a modified version of the General Help-Seeking questionnaire (GHSQ) were administered to 316 mothers of under-twos in 3 of 12 military barracks in Lagos, Nigeria to determine PPD and major depressive events (MDE). Risk of PPD was established at EPDS scores of >12. Good help-seeking practices were ascribed to scores of 20 or more on the GHSQ. Risk of PPD was found in 15.5% of respondents, and good help-seeking in 3.8% and 11.4% for personal/emotional and harming self/baby respectively. Bivariate analysis using Chi square showed statistically significant positive associations between lower scores for EPDS and higher educational levels of respondents, perception of partner support and being in lower wealth quintiles (p<0.05). Use of the EPDS was accepted among mothers of children aged under two years. Opportunities to educate pregnant women and new mothers about PPD using existing social networks, perinatal and infant screening programmes in the barracks can be leveraged upon to improve mental health delivery as part of maternity care.

In common model testing practise, the measured values of the self propulsion test are split into the characteristics of the hull, the propeller and into the interaction factors. These coefficients are scaled separately to the respective full scale values and subsequently reassembled to give the power prediction. The accuracy of this power prediction depends {\em inter alia} on the accuracy of the measured values and the scaling procedure. An inherent problem of this approach is, that it is virtually impossible to verify each single step, because of the complex nature of the underlying problem. In recent years the scaling of the open-water characteristics of propeller model tests attracted a renewed interest, fuelled by competitive tests, which became the norm due to requests of the customer. This paper will show the influence of different scaling procedures on the predicted power. The prediction is compared to the measured trials data and the quality of the prediction will be judged. The procedures examined are the standard ITTC~1978 procedure plus derivatives of it: the Meyne, the strip method and the βᵢ-method.

Electric vehicles, being able to reduce pollutant and greenhouse gas emissions and shift the economy away from oil products, can play a major role in the transition towards low-carbon energy systems. However, the related increase in electricity demand inevitably affects the strategic planning of the overall energy system as well as the definition of the optimal power generation mix. With this respect, the impact of electric vehicles may vary significantly depending on the composition of both total primary energy supply and electricity generation. In this study, Italy and Germany are compared to highlight how a similarity in their renewable shares not necessarily leads to a CO₂ emissions reduction. Different energy scenarios are simulated with the help of EnergyPLAN software assuming a progressive increase in renewable energy sources capacity and electric vehicles penetration. Results show that, for the German case, the additional electricity required leads to a reduction in CO₂ emissions only if renewable capacity increases significantly, whereas the Italian energy system benefits from transport electrification even at low renewable capacity. Smart charging strategies are also found to foster renewable integration; however, power curtailments are still significant at high renewable capacity in the absence of large-scale energy storage systems.

ETS exposure has been shown as an important environmental risk factor in vulnerable population groups. The aim of the project is to analyze the relationships among the ETS and behavior and health in 6−15-year-old children in Slovakia. The status of physical and mental health of children in relation to exposure to tobacco smoke was examined in the representative group of 1478 school children. The methods used, included anonymous questionnaires filled in by parents, Columbia Impairment Scale (CIS), Behavior Problem Index (BPI) and anthropometry. The prevalence of passive smoking is the highest in the capital (27%) and southern cities. Significant relationships have been confirmed between ETS and the age, socio-economic status, the incompleteness of the family, the level of mother's education and the significantly higher prevalence of respiratory diseases (26.7%).The relationships of ETS with emotional (CIS scores ≥16) and behavioral functions (BPI score ≥14) were significant in children exposed to mother‘s and father‘s smoking at home. In the multivariate analysis this association was not significant; the factors such as income and completeness of the family were dominant. The results confirmed the impact of ETS and social factors on health state and health behavior and could be the argumentation for legislative changes.

This paper is devoted to the study of reproducing kernels on 2-inner product Hilbert spaces. We focus on a new structure to produce reproducing kernel Hilbert and Banach spaces. According to multi-variable computing, this structures can be useful in electrocardiographs, machine learning and economy

Soil salinity, whether natural or human induced, is a major geo-hazard in arid and semi-arid landscapes. In agricultural lands, it negatively affects plant growth, crop yields, whereas in semi-arid and arid non-agricultural areas it affects urban structures due to subsidence, corrosion and ground water quality, leading to further soil erosion and land degradation Accurately mapping soil salinity through remote sensing techniques has been an active area of research in the past few decades particularly for agricultural lands. Most of this research has focused on the utilization and development of salinity indices for properly mapping and identifying saline agricultural soils. This research study develops a soil salinity index and model using Landsat 8 OLI image data from the near infra-red and shortwave infra-red spectral information with emphasis on soil salinity mapping and assessment in non-agricultural desert arid and semi-arid surfaces. The developed index when integrated into a semi-empirical model outperformed in its soil salinity mapping overall accuracy (60%) in comparison to other salinity indices (~50%). The newly developed index further outperformed other indices in its accuracy in mapping and identifying high saline soils (67%) and excessively high saline soils (90%).

A radical, albeit pragmatic protocol for experimental access to putative String/M-theoretic, Einstein Unified Field Mechanical (UFM) additional dimensionality (XD) of the brane-bouquet bulk is presented. If successful, results demonstrate the existence dimensionality beyond the metric of observed physical reality provided by the Standard Model (SM) of particle physics and Cosmology. Quantum Mechanics (QM), as well-known is incomplete and further, should no longer be considered the basement of reality; meaning, Locality and Unitarity – the fundaments of quantum theory are an insufficient basis for extending the representation of reality. A seminal model of Tight Bound States (TBS) below the lowest Bohr orbit in the hydrogen atom, proposed by Vigier, is extended to a Kaluza-Klein-like (KK) cyclical tier of XD hyperspherical cavities defined within a manifold of uncertainty (MOU) of finite radius up to the semi-quantum limit, predicting, within its domain, new spectral lines in Hydrogen. The proposed protocol for this process, with phase modifications, provides efficacy of large-scale additional dimensionality (LSXD) of the brane bulk; XD-LSXD incursion duality accesses nonlocal Einsteinian UFM phenomena, leading to myriad new classes of technological innovation.

The ecological background condition of the semi-arid steppe region (SASR) is extremely fragile. It is recognized that the development of coal and electricity power is a kind of strong human interference behavior for regional landscape ecology. Landscape ecological classification (LEC) is the premise of landscape ecology research of the mining area. The current research on the SASR and grassland LEC of coal-power base is relatively less, but still remains uncertainty concerning how to stratify and classify urban mining landscapes into units of ecological significance at spatial scales appropriate for management. This study is based on hierarchy theory, scale theory, landscape process, the patch-corridor-matrix model, the network, the theory of multiple planning integration and the principle of remote sensing. According to the comprehensive principle, principles of the combining of structure and function, principle of the combining human-ominated and natural landscape, principle of emphasis, and principle of combining qualitative analysis with quantitative research of LEC in large-scale coal-power base(LSCPB). On the basis of occurrence method land classification, fully consider the ecological attributes of the land, integration pattern, processes and function theory of the landscape ecology, the LEC system of the LSCPB in the SASR has been constructed by using top-down decomposition classification method. Empirical research of the Victory and Mindong No.1 mining areas of Shenhua Group shows that the classification system constructed in this paper can meet the requirements of LEC and fully reflect the status of landscape ecology of LSCPB in SASR. This study can provide theoretical guidance for the landscape ecology of LSCPB, while also supporting a theoretical reference for the LEC research.

The research sought to investigate the long term characteristics of wind in the Kisii region (elevation 1710m above sea level, 0.68^oS, 34.79^o E). Wind speeds were analyzed and characterized on short term (per month for a year) and then simulated for long term (ten years) measured hourly series data of daily wind speeds at a height of 10m. The analysis included daily wind data which was grouped into discrete data and then calculated to represent; the mean wind speed, diurnal variations, daily variations as well as the monthly variations. The wind speed frequency distribution at the height 10 m was found to be 2.9ms^-1 with a standard deviation of 1.5. Based on the two month’s data that was extracted from the AcuRite 01024 Wireless Weather Stations with 5-in-1 Weather Sensor experiments set at three sites in the region, averages of wind speeds at hub heights of 10m and 13m were calculated and found to be 1.7m/s, 2.0m/s for Ikobe station, 2.4m/s, 2.8m/s for Kisii University stations, and 1.3m/s, 1.6m/s for Nyamecheo station respectively. Then extrapolation was done to determine average wind speeds at heights (20m, 30m, 50m, and 70m) which were found to be 85.55W/m², 181.75W/m², 470.4W/m² and 879.9W/m² respectively. The wind speed data was used statistically to model a Weibull probability density function and used to determine the power density for Kisii region.

Insufficient mixing in large-scale bioreactors, provokes gradient zones of substrate, dissolved oxygen, pH and other parameters. E. coli responds to a high glucose, low oxygen feeding zone with the accumulation of mixed acid fermentation products, especially formate, but also with the synthesis of non-canonical amino acids, such as norvaline, norleucine and -methyl-norleucine. These amino acids can be mis-incorporated into recombinant products, which causes a problem for pharmaceutical production whose solution is not trivial. While these effects can also be observed in scale down bioreactor systems, these are challenging to operate. Especially the high-throughput screening of clone libraries is not easy, as fed-batch cultivations would need to be controlled via repeated glucose pulses with simultaneous oxygen limitation, as has been demonstrated in well controlled robotic systems. Here we show that not only glucose pulses in combination with oxygen limitation can provoke the synthesis of these non-canonical branched-chain amino acids, but also that pyruvate pulses produce the same effect. Therefore we combined the enzyme based glucose delivery method Enbase® in a PALL24 mini-bioreactor system and combined repeated pyruvate pulses with simultaneous reduction of the aeration rate. These cultivation conditions, produced an increase in the non-canonical branched chain amino acids norvaline and norleucine in both the intracellular soluble protein and inclusion body fractions with mini-proinsulin as an example product, and this effect was verified in a 15 L stirred tank bioreactor. To our opinion this cultivation strategy is easy to apply for the screening of strain libraries under standard laboratory conditions if no complex robotic and well controlled parallel cultivation devices are available.

In advanced world stroke is one of the disabling cause of death that can be managed with thrombolysis if presents early despite further risk of intracerebral haemorrhage. Secondary prevention is an important objective in ischaemic stroke where recurrence is very high with subsequent stroke. Carotid End Arterectomy impact a definitive and effective role for both symptomatic and asymptomatic carotid stenosis for secondary stroke prevention in selective cases. Thrombolysis is a potential primary management for certain group whereas carotid surgery employs secondary preventative measure in a specified ischaemic stroke group.

Depletion of ore deposits, increasing demand for raw materials, the need to process low-grade, complex and finely disseminated ores and the reprocessing of tailings are challenges, especially for froth flotation separation technologies. Even though capable of handling relatively fine grain sizes the flotation separation of very fine and ultrafine particles faces many problems still. Further, the flotation of low-contrast semi-soluble salt-type minerals with very similar surface properties, many complex interactions between minerals, reagents and dissolved species often result in poor selectivity. This study investigates the flotation beneficiation of ultrafine magnesite rich in dolomite from de-sliming, currently reported to the tailings. The paper especially focuses on the impact of the depressant sodium hexametaphosphate (SHMP) on: (i) the froth properties using dynamic froth analysis (DFA), (ii) the separation between magnesite and dolomite/calcite and (iii) its effect on the entrainment. Furthermore, the application of 1-hydroxyethylene-1,1-diphosphonic acid (HEDP) is a more environmentally friendly and low-cost alternative to SHMP is presented and discussed. The paper contributes to understanding on the complexity of depressant responses in froth flotation.

Compressive residual stresses in thin films can inhibit crack propagation under normal or sliding contact loading, with associated enhancement of the coating apparent toughness, load bearing capacity and wear resistance. This study investigates the influence of residual stress distributions on the thin film/substrate adhesion using a nanoindenter coupled with scanning electron microscope (SEM) investigations of indentation induced failure modes. Reactive and un-reactive magnetron sputtering with ion plating was used to coat a (100) silicon substrate with aluminum nitride (AlN) with and without an aluminum (Al) adhesion layer. The presence of an Al bond layer gives additional interfacial tensile stress because of the difference in thermal expansion coefficient. Additionally, a different magnitude of residual stresses in the AlN coating was achieved by changing the applied bias voltage onto the substrate. Wafer curvature method and incremental focused ion beam (FIB) milling, combined with high-resolution in situ scanning electron microscopy (SEM) imaging and full field strain analysis by digital image correlation (DIC), were used to measure the average and in-depth stress residual stress distribution in the produced coatings. The adhesion energy was then quantified by using a nanoindentation based model. Results demonstrate that the additional tensile residual stress in the aluminum adhesion layer decrease significantly the coating adhesion, even in presence of a higher compressive stress state in the AlN top-layer. Therefore, the coatings without Al-layer showed better adhesion because of a more homogeneous compressive residual stress in comparison with the coating having Al layer, even though both groups of coatings are produced under same bias voltage. Results are discussed, and some general suggestions are made on the correlation between coating/substrate property combination and the adhesion energy of multilayer stacks. The results suggested that Al bond-layer and inhomogeneous residual stresses affected the adhesion of AlN negatively to a substrate like silicon.

While deforestation rates decline globally they are rising in the Western Amazon. Artisanal-scale gold mining (ASGM) is a large cause of this deforestation and brings with it extensive environmental, social, governance, and public health impacts, including large carbon emissions and mercury pollution. Underlying ASGM is a broad network of factors that influence its growth, distribution, and practices such as poverty, flows of legal and illegal capital, conflicting governance, and global economic trends. Despite its central role in land use and land cover change in the Western Amazon and the severity of its social and environmental impacts, it is relatively poorly studied. While ASGM in Southeastern Peru has been quantified previously, doing so is difficult due to the heterogeneous nature of the resulting landscape. Using a novel approach to classify mining that relies on a fusion of CLASlite and the Global Forest Change dataset, two Landsat-based deforestation detection tools, we sought to quantify ASGM-caused deforestation in the period 1984–2017 in the southern Peruvian Amazon and examine trends in the geography, methods, and impacts of ASGM across that time. We identify nearly 100,000 ha of deforestation due to ASGM in the 34-year study period, an increase of 21% compared to previous estimates. Further, we find that 10% of that deforestation occurred in 2017, the highest annual amount of deforestation in the study period, with 53% occurring since 2011. Finally, we demonstrate that not all mining is created equal by examining key patterns and changes in ASGM activity and techniques through time and space. We discuss their connections with, and impacts on, socio-economic factors, such as land tenure, infrastructure, international markets, governance efforts, and social and environmental impacts.

This article proposes the use of a multi-scale and multi-sensor approach to collect and modelling 3D data concerning wide and complex areas in order to obtain a variety of metric information in the same 3D archive, based on a single coordinate system. The employment of these 3D georeferenced products is multifaceted and the fusion or integration among different sensors data, scales and resolutions is promising and could be useful for the generation of a model that could be defined as hybrid. The correct geometry, accuracy, radiometry and weight of the data models are hereby evaluated comparing integrated processes and results from Terrestrial Laser Scanner (TLS), Mobile Mapping System (MMS), Unmanned Aerial Vehicle (UAV), terrestrial photogrammetry, using Total Station (TS) and Global Navigation Satellite System (GNSS) as topographic survey. The entire analysis underlines the potentiality of the integration and fusion of different solutions and is a crucial part of the “Torino 1911” project whose main purpose is mapping and virtually reconstructing the 1911 Great Exhibition settled in the Valentino Park in Turin (Italy).

Microbes do not live in isolation but in microbial communities. The relevance of microbial communities is increasing due to the awareness about their biotechnological influences in a huge number of environmental, health and industrial processes. Hence, being able to control and engineer the output of both natural and synthetic communities would be of great interest. However, most of the available methods and biotechnological applications (both in vivo and in silico) have been developed in the context of isolated microbes. In vivo microbial consortia development, i.e. to reproduce the community life conditions in the wet-lab, is extremely difficult and expensive requiring of computational approaches to advance knowledge about microbial communities, mainly with descriptive modelling, and further with engineering modelling. In this review we provide a detailed compilation of available examples of engineered microbial communities as a launch pad for an exhaustive and historical revision of those computational methods devoted so far toward the better understanding, and rational engineering of natural and synthetic microbial communities.

Mixture of abramis brama (freshwater bream), carassius carassius (crucian carp), and sander lucioperca (pike perch) scales was used for the preparation of fish scale powder containing about 26.5 wt. % of removed when heating components preferably of organic nature, and 63.5 wt. % of mineral components. Fish scale powder enriched with inorganic components was prepared from washed, dried, and ground fish scale mixture using vibration sieving. Inorganic powders consisting of hydroxyapatite and magnesium whitlockite were obtained via heat treatment of this fish scale powder at 800-1000 oC. Particles of these inorganic powders consisted of sintered grains with dimensions less than 100 nm after heat treatment at 800 oC, less than 200 nm after heat treatment at 900 oC, and 100-500 nm after heat treatment at 1000 oC. Fish scale powder enriched with inorganic components as well as heat-treated inorganic powders consisting of hydroxyapatite and magnesium whitlockite can be recommended for the production of different materials such as ceramics or composites.

Fluctuations of protein three-dimensional structures and large-scale conformational transitions are crucial for the biological function of proteins and their complexes. Experimental studies of such phenomena remain very challenging and therefore molecular modeling can be a good alternative or a valuable supporting tool for the investigation of large molecular systems and long-time events. In this mini-review, we present two alternative approaches to the coarse-grained (CG) modeling of dynamic properties of protein systems. We discuss two CG representations of polypeptide chains used for Monte Carlo dynamics simulations of protein local dynamics and conformational transitions and, on other hand, highly simplified structure-based Elastic Network Models of protein flexibility. In contrast to classical Molecular Dynamics the modeling strategies discussed here allow quite accurate modeling of much larger systems and longer time dynamic phenomena. We briefly describe the main features of these models and outline some of their applications, including modeling of near-native structure fluctuations, sampling of large regions of the protein conformational space, or possible support for the structure prediction of large proteins and their complexes.

Light and heat resources are ample in Xinjiang plain oasis region. Planting structure is single in irrigation area, which leads to severe seasonal water shortages due to high concentration of water utilization. Therefore, how to make full use of light and heat resources to develop oasis agriculture without expanding planting scale has become the focus of research. The biannual cropping patterns are possible solutions to the problem. Manas River Irrigation area, which is located on the northern slope of Tianshan Mountain in Xinjiang in China is regarded as a typical case study to analyze the suitable planting structure and planting scale for biannual cropping pattern. The effects of optimizing planting patterns on alleviating the contradiction between water supply and water need，and the efficiency of water resources utilization was also studied. The results of the study show that：(1) the suitable planting scales of Manas River irrigation area in wet year (P = 25%), normal year (P = 50%), and low flow year (P = 75%) are about 72.66%, 78.73% and 83.91% of the current planting scale. (2) After the planting structure was optimized, the water use process in the irrigation area extends from May to August at present to April to November. The water use ratio at the peak period of water use decreased from 0.847 to 0.601, and the water use peak was significantly dispersed. (3) Economic benefits per cubic metre of water of the biannual cropping patterns increased from 8.65 yuan·m⁻³ at present to 9.45 yuan·m⁻³, 10.31 yuan·m⁻³ and 11.43 yuan·m⁻³ in wet year (P = 25%), in normal year (P = 50%) and low flow year (P = 75%) respectively, which proved that replanting crops could improve the efficiency of water resources utilization in irrigated areas. Therefore, the optimal planting pattern can be implemented to improve the utilization efficiency of soil and water resources in irrigation area in the arid oasis with single planting pattern with excessive concentration of water use peak and serious water shortage.

Background: Social Anxiety Disorder (SAD) is among the most common anxiety disorders worldwide with data largely emerging from the Euro-American and Pacific Rim populations. In contrast, there is a dearth of studies among the populations of Arabian Gulf countries including Oman. This study has two interrelated aims: (i) to explore the prevalence of SAD among Omani adults, and (ii) to tease out the links between sociodemographic factors and SAD in Oman. Methods: A cross-sectional study via an online survey was conducted among 1019 adult Omani nationals residing in Oman. The presence of SAD was assessed using the Arabic version of the Liebowitz Social Anxiety Scale (LSAS). Result: Nearly half the participants (45.9%, n=468) endorsed themselves as having features of SAD as defined by LSAS. In the multivariate logistic analysis, participants below 40 years of age were 1.6 times (OR=1.568, p=0.026) more likely to have SAD than those who were 40 and older. Women were 1.3 times (OR=1.348, p=0.038) more likely to endorse SAD than men. Participants who had secondary or undergraduate education were respectively 1.5 times (OR=1.45, p=0.014) and 2.5 times (OR=2.509, p<.001) to have SAD than who were postgraduates. Conclusion: The present data suggest that 45.9% of the participants reached the cut-off for case-ness in LSAS, which is high compared to reports from other populations. As online survey respondents tend to belong to similar demographics, the current results need not be representative of the Omani adult population, which calls for studies that adopt more inclusive survey methods.

Financial capacity instruments are psychometric tools designed to evaluate individual decisional capacity based on financial decisions. As tests are complex and need special conditions for administration and evaluation, it is difficult to use them in daily geriatric clinics. Our scoping review objective was to evaluate existing financial capacity instruments from the perspective of simplicity and portability. We evaluated one English speaking knowledge database (Medline) using a dedicated MeSH terminology. The review yielded one independent instrument, The Semi-Structured Clinical Interview for Financial Capacity, that can be easy adapted for every-day clinical use. It is simple to understand and perform and do not need trained personnel for administration. It can be finalized in 15 minutes. Initially validated on 261 subjects (with different forms of cognitive impairment), it showed good accuracy and precision mainly in subjects with cognitive impairment. The test is less apt to detect early or fluctuating cognitive impairment. Simplicity, the main advantage of the test, allows gamification fact that increases portability. Familiar images (coins, money) that are used for performing simple tasks does not need complex translation and adaptation. In form of a game, the test is suitable for serial administration, increasing the chance for early capacity reduction detection. Results reflect a physician judgement related to the subjects’ capacity to understand and execute simple financial instructions and not financial proficiency scores. The main limitation of our review is that we investigated only one, English speaking, knowledge database. The scoping strategy generated a financial capacity instrument that can be used in geriatric clinics for early diagnostic of decisional capacity reduction. Further studies are needed to evaluate the reliability and validity of the test in conditions of serial administration and in populations having various financial experience.

With the rise of long-read sequencers and long-range technologies, delivering high-quality plant genome assemblies is no longer reserved to large consortia. Indeed, sequencing techniques but also computer algorithms have reached a point where the reconstruction of assemblies at the chromosome-scale is now feasible at the laboratory scale. Current technologies, and especially long-range technologies, are numerous and selecting the most promising one for the genome of interest is crucial to obtain optimal results. In this study, we resequenced the genome of the yellow sarson, Brassica rapa cv. Z1, using the Oxford Nanopore PromethION sequencer and assembled the sequenced data using current assemblers. To reconstruct complete chromosomes, we used and compared three long-range techniques, optical mapping, Omni-C and Pore-C sequencing libraries commercialized by Bionano Genomics, Dovetail Genomics and Oxford Nanopore Technologies respectively, or a combination of the three, in order to evaluate the capability of each technology.

Environmental conditions, such as temperature, carbon dioxide, and nutrient availability, are altered by urban conditions at regional scales with potential for impact on tree leaf structure. Our goal was to compare leaf morphological characteristics driven by physiological acclimation in red maple (Acer rubrum L.) trees in deciduous forests embedded in a small (Newark, DE) and a large (Philadelphia, PA) city. The study was conducted in six urban forests on eighteen mature red maple trees in a long-term urban forest network. We hypothesized that red maples in Philadelphia forests compared to Newark forests will have a thicker upper epidermal layer, spongy palisade and mesophyll layer, longer and wider stomates, and lower stomate density. Additionally, we hypothesized that red maples in Philadelphia forests compared to Newark forests will have lower leaf water content and specific leaf area, and greater leaf thickness, fresh leaf weight, dry leaf weight, and leaf dry matter content. Our results for stomate length and stomate width supported our predictions; red maple leaves had longer and wider stomates in Philadelphia forests than in Newark forests. The increased stomate size in red maple trees suggests potential altered gas exchange behavior and mutual abiotic stress mitigation responses in red maple to greater urbanization impacts in Philadelphia forests. This supports previous findings of possible physiological and biochemical acclimation of red maple trees to urban conditions. Furthermore, the findings from this study suggest red maple trees may be a good biomonitor of regional scale impacts in urban environments.

Based on 541 Landsat images between 1988 and 2016, the normalized difference vegetation indices (NDVIs) of the wetland vegetation at Xitugou (XTG) and Wowachi (WWC) inside the Dunhuang Yangguan National Nature Reserve (YNNR) in northwest China were calculated for assessing impacts of climate change on wetland vegetation in the YNNR. It was found that the wetland vegetation at the XTG and WWC both had shown a significant increasing trend in the past 30 years, and the increase in both annual mean temperature and peak snow depth over the Altun Mountains led to the increase of wetland vegetation. The influence of local precipitation on the XTG wetland vegetation was greater than on the WWC wetland vegetation, which demonstrates that in extremely arid regions, the major constrain to the wetland vegetation is water availability in soils which is greatly related to the surface water detention and discharge of groundwater. At both XTG and WWC, snowmelt from the Altun Mountains is the main contributor to the groundwater discharge, while local precipitation plays a less role in influencing the wetland vegetation at the WWC than at the XTG, because the wetland vegetation grows on a relatively flat terrain at the WWC, while in a stream channel at the XTG.

In proteomics, it is essential to quantify proteins in absolute terms if we wish compare results among studies and integrate high-throughput biological data into genome-scale metabolic models. While labeling target peptides with stable isotopes allows protein abundance to be accurately quantified, the utility of this technique is constrained by the low number of quantifiable proteins that it yields. Recently, label-free shotgun proteomics has become the “gold standard” for carrying out global assessments of biological samples containing thousands of proteins. However, this tool must be further improved if we wish to accurately quantify absolute levels of proteins. Here, we used different label-free quantification techniques to estimate absolute protein abundance in the model yeast Saccharomyces cerevisiae. More specifically, we evaluated the performance of seven different quantification methods, based either on spectral counting (SC) or extracted-ion chromatogram (XIC), which were applied to samples from five different proteome backgrounds. We also compared the accuracy and reproducibility of two strategies for transforming relative abundance into absolute abundance: a UPS2-based strategy and the total protein approach (TPA). This study mentions technical challenges related to UPS2 use and proposes ways of addressing them, including utilizing a smaller, more highly optimized amount of UPS2. Overall, three SC-based methods (PAI, SAF, and NSAF) yielded the best results because they struck a good balance between experimental performance and protein quantification.

Staphylococcus aureus is a high-priority pathogen causing severe infections with high morbidity and mortality worldwide. Many S. aureus strains are methicillin-resistant (MRSA) or even multi-drug resistant. It is one of the most successful and prominent modern pathogens. An effective fight against S. aureus infections requires novel targets for antimicrobial and antistaphylococcal therapies. Recent advances in whole-genome sequencing and high-throughput techniques facilitate the generation of genome-scale metabolic models (GEMs). Among the multiple applications of GEMs is drug-targeting in pathogens. Hence, comprehensive and predictive metabolic reconstructions of S. aureus could facilitate the identification of novel targets for antimicrobial therapies. This review aims at giving an overview of all available GEMs of multiple S. aureus strains. We downloaded all 114 available GEMs of S. aureus for further analysis. The scope of each model was evaluated, including the number of reactions, metabolites, and genes.Furthermore, all models were quality-controlled using Mᴇᴍᴏᴛᴇ, an open-source application with standardized metabolic tests. Growth capabilities and model similarities were examined. This review should lead as a guide for choosing the appropriate GEM for a given research question. With the information about the availability, the format, and the strengths and potentials of each model, one can either choose an existing model or combine several models to create models with even higher predictive values. This facilitates model-driven discoveries of novel antimicrobial targets to fight multi-drug resistant S. aureus strains.

In this study, a composite flame retardant was created by combining fish scale (FS), fishery waste, and ammonium polyphosphate (APP), a commercially available flame retardant. The composite flame retardant was added to epoxy resin (EP) to form an EP/APP/FS composite that prevents burns and is environmentally friendly. The use of FS conforms to the concept of circular economy and lowers costs by reducing the consumption of APP. Thermogravimetric analysis (TGA), integral procedural decomposition temperature (IPDT), pyrolysis kinetics, limiting oxygen index (LOI), the Underwriters Laboratories 94 (UL94) flammability test, scanning election microscopy, Raman spectroscopy, and energy-dispersive X-ray spectroscopy were used to determine the thermal properties, flame retardant properties, flame retardant mechanism, char morphology, and composition of the composites. The TGA results indicated that the addition of 40% flame retardant raised the char residue from 16.45 wt% (pure EP) to 36.07 wt%, IPDT from 685.6 °C (pure EP) to 1143.1°C, LOI from 21% (pure EP) to 30%, and UL94 classification from fail (pure EP) to V-0. These results suggest an increase in char residue, which indicates better protection of the polymer matrix material. The improvements in IPDT, LOI, and UL94 classification, which indicate greater thermal stability, lower flammability (from flammable to fireproof), and higher flammability rating (from fail to V-0), respectively, suggest that the composite material has favorable thermal properties and is less inflammable.

This article presents the study of religious pluralism and decolonization of Indian mind in Russia. The paper analyzes the investigation results concerning psychological features of modern Indian students from universities in Russia and India. For measuring of connection between religious pluralism and decolonization of Indian mind we made socio-psychological investigation of Indian students. We made 254 semi-structured interview with Indian students who are studying in Russia and India. According to the result of investigation that decolonization of Indian mind is connected with the level of religious pluralism. Among the values principles of religious pluralism get more significance and importance in decolonizing mind of Indian students.

A new model of cosmology is proposed, where the state of high energy density commonly associated with the big bang is generated by the collapse of an antineutrino star that has exceeded its Chandrasekhar limit. To allow the first neutrino stars and antineutrino stars to form naturally from an initial quantum vacuum state, matter and antimatter are assumed to gravitationally repel. In this scenario, a degenerate antineutrino star in effective hydrostatic equilibrium has a density that is similar to the dark energy density of the ΛCDM model. When viewed from the core, such a star could today accelerate matter radially and emit the isothermal cosmic microwave background radiation, which addresses the horizon and flatness problems. This model and the ΛCDM model are in similar quantitative agreement with supernova distance measurements. The presented model is also in qualitative agreement with observed large-scale anisotropy and inhomogeneity, which distinguishes it from the ΛCDM model.

In the context of improving the comfort and dynamics of the vehicle, the suspension system has been continuously developed and improved, especially using magnetorheological (MR) shock absorbers. The development of this technology which is relatively new has not been easy. Thus, the first widespread commercial use of MR fluid in a semi-active suspension system was implemented in passenger cars. The magnetorheological shock absorber can combine the comfort with the dynamic driving, because it allows the damping characteristic to be adapted to the road profile. The main objective of the paper is to analyze the dynamic behavior of the magnetorheological shock absorber in the semi-active suspension. In this sense, the author carried out a set of experimental measurements with a damping test bench, specially built and equipped with modern equipment. The results obtained from the experimental determinations show a significantly improved comfort when using a magnetorheological shock absorber, compared to a classic one, by the fact that the magnetorheological shock absorber allows to modify the damping coefficient according to the road conditions, thus maintaining the permanent contact between the tire and the road due to increased damping force.

Carbon nanotubes (CNTs) are effective supports for nano metals and together they represent hybrids that combine unique properties of both. A microwave induced reaction was used to deposit nano palladium on carboxylated and octadecylamine functionalized multiwall CNTs, which were used to carry out C-C coupling reactions in DMF and toluene. These hybrids showed excellent catalytic activity with yield as high as 99.8% while its enhancement with respect to commercially available Pd/C catalyst reached as high as 109%, and the reactions times were significantly lower. Polarity of the functionalized form was found to be a significant factor with the polar carboxylated CNT showing better activity in DMF while the relatively nonpolar octadecyl amine was better in toluene. The results suggest the possibility of tailor making functionalized CNT when used as catalyst supports

There have been several cases of large-scale wind generators (WGs) tripping off caused by untimely fault removing in recent years. Currently, the discoordination between the box-type transformer fuse protection (BTFP) and two-section collecting line current protection (CLCP) brings a security risk to wind farm. In order to ensure the selectivity, the first section (Sec-I) CLCP should be set a enough interval that is longer than the fuse melting time, and another interval is set for the Sec-II CLCP, which weakens the speed of the CLCP. When a fault occurs on the collecting line, there is no doubt that WGs cannot work too long in abnormal operation, which may cause WGs to be placed off the grid. For a power system with high penetration of wind power, large-scale WGs tripping off will cause a great power shortage, and affect the stability of the power system. The selectivity and sensitivity of the CLCP is analyzed in detail to make the CLCP speed better. Considering the fault ride-through ability of WGs, the fault clear time is an important factor to lead to large-scale WGs tripping off. Two main works are done in this paper. The first is to accelerate the speed of the Sec-I CLCP though reducing the protection zone. Another one is introduce the risk assessment module into the CLCP, which not only improve the speed of the CLCP but also ensure the safety of the wind farm during faults. According to the deference in trip-off causes of WGs, the matching functions are created to assess the trip-off risk of WGs on the spot. In the case of fault, the trip-off risk indicators of WGs are timely updated to data sharing center and open to the CLCPs. The set of risk indicators is divided into several subsets according to the risk range. The dynamic changes of the subsets during fault help to improved CLCP scheme. This scheme can accelerate protection speed based on the increasing risk of large-scale WGs tripping off in wind farms. Compared with traditional CLCP, this approach can make the CLCP combines selectivity and speed better based on the analysis of the ride- through ability of WGs.

Complex systems can be described as the network of interactions between their components. In directed networks, information, energy and matter flow in dominant directions. Undirected networks, on the other hand, cannot easily capture these asymmetries. The local flow of information depends on the node spin, which is a function of the number of incoming and outgoing links attached to it. And yet, how the heterogeneous association between in-degree and out-degree constraints global dynamics remains poorly understood. Here, we develop a new theoretical model to study the relationship between node directionality and global flow dynamics. Our computational analysis of random and scale-free directed networks indicates that structural diversity constrains the dimensionality of reachable dynamical space. These results suggest how local directionality might be an universal driver of global dynamics in many systems, from social networks, to technological systems to the connectome.

Many complex behaviours in biological systems emerge from large populations of interacting molecules or cells, generating functions that go beyond the capabilities of the individual parts. Such collective phenomena are of great interest to bioengineers due to their robustness and scalability. However, engineering emergent collective functions is difficult because they arise as a consequence of complex multi-level feedback, which often spans multiple length-scales. Here, we present a perspective on how some of these challenges could be overcome by using multi-agent modelling as a design framework within synthetic biology. Using case studies covering the construction of synthetic ecologies to biological computation and synthetic cellularity, we show how multi-agent modelling can capture the core features of complex multi-scale systems and provide novel insights into the underlying mechanisms which guide emergent functionalities across scales. The ability to unravel design rules underpinning these behaviours offers a means to take synthetic biology beyond single molecules or cells and towards the creation of systems with functions that can only emerge from collectives at multiple scales.

Location-and-scale transformation of a random variable underpins normal distribution, but it is however fundamentally incorrect for scale estimation such as relative dispersion. In this paper, a parametrized alternative to a normal distribution, called scaloc-normal distribution, is proposed that efficiently works and is fundamentally correct with absolute and relative dispersion estimators. The Monte Carlos simulation experiment was used to generate a total of 600,000 artificial datasets in 600 different simulation scenarios from loc-normal (normal) and scaloc-normal distributions. The absolute and relative dispersion were estimated and compared from the two distributions. The results show that scaloc-normal distribution is a good parametrized alternative to loc-normal distribution, fundamentally correct and efficient with both standard deviation and coefficient of variation. The key statistical advancement from loc-normal to scaloc-normal distribution is its fundamental correctness (i.e., scale-invariant property) with an efficient relative estimator of dispersion (i.e., coefficient of variation). Parametrically, the loc-normal and scaloc-normal distributions are very different, but both have linear transformations.

Perovskite based solar cells have achieved tremendous progress reaching record efficiency in the past 5 years. Numerous new processes and chemistry have been reported and contribute to the perovskite rapid progress. Continuous efficiency improvements are still necessary for perovskite solar cells, and an exploratory data analysis on devices performance over multiple studies could boost the technology development. Such analysis could identify patterns or provide insights that are not obvious in a single study. Here we present a high quality dataset containing only independently certified Pb-based perovskite solar cells summarizing their efficiency, relevant I-V metrics, manufacturing processes and materials used. Analysis over the dataset provides insights on how aperture size, perovskite deposition methods and materials used in each functional layer affect the final solar cell efficiency and I-V metrics. Future directions are also suggested for efficiency improvements.

The classical Rotational Isomeric State (RIS) model, originally proposed by Flory, has been used to rationalize a wide range of physicochemical properties of neutral polymers. However, many weak polyelectrolytes of interest are able to regulate their charge depending on the conformational state of the bonds. Recently, it has been shown that the RIS model can be coupled with the Site Binding (SB) model, for which the ionizable sites can adopt two states: protonated or deprotonated. The resulting combined scheme, the SBRIS model, allows to analyse ionization and conformational equilibria on the same foot. In the present work this approach is extended to include pH-dependent electrostatic Long Range (LR) interactions, ubiquitous in weak polyelectrolytes at moderate and low ionic strengths. With this aim the original LR interactions are taken into account by defining effective Short Range (SR) and pH-dependent parameters, such as effective microscopic protonation constants and rotational bond energies. The new parameters are systematically calculated using variational methods. The machinery of statistical mechanics for SR interactions, including the powerful and fast transfer matrix methods, can then be applied. The resulting technique, to which we will refer as Local Effective Interaction Parameters (LEIP) method, is illustrated with a minimal model of a flexible linear polyelectrolyte containing only one type of rotating bonds. LEIP reproduces very well the pH dependence of the degree of protonation and bond probabilities obtained by semi-grand canonical Monte Carlo simulations, where LR interactions are taken explicitly into account. The reduction in the computational time in several orders of magnitude suggests that the LEIP technique could be useful in a range of areas involving linear weak polyelectrolytes, allowing direct fitting of the relevant physical parameters to the experimental quantities.