Abstract: This study is an attempt to develop ecotourism in Nehbandan County, in the South Khorasan Province, Iran, by representing unknown areas that have tourism potential. The most important obstacle in the development of tourism industry is the lack of strong marketing plans, tourism management, accommodations for overnight and long stays, and medical and health clinic in the desert. This is a qualitative, exploratory case study investigating the status of environmental, sociocultural, and economic impacts of ecotourism development on the native people's livelihood in Nehbandan County in Iran. The methodology is based on field observations, secondary data sources, and field survey. It is an interpretive approach that avoids numbers but focuses on issues linked to culture and nature. In the present study, the grounded theory was used to perform data analysis. Based on the findings, ecotourism has undoubtedly proven to be an effective environmental conservation tool in the study site and enables local people to increase their livelihood security through employment in activities relating to ecotourism and the development of rural livelihood.

Abstract: Proton Induced X-ray Emission, (PIXE), is capable of high precision analysis for trace element components of aerosol particle size fractions sampled by cascade impactor. A statistical evaluation of data quality has been carried out in order to distinguish between analytical uncertainties in the PIXE procedure, errors caused by cascade impactor performance and by other factors in the sampling procedure, and geophysical causes of differences in composition and particle size distributions of the elements in aerosols. Replicate analyses and simultaneous samplings taken in north Florida and St. Louis have been used for the data evaluation. In addition to the analytical error the sampling procedure contributes an error of ~ 10% to be added quadratically. The resulting precision is sufficient to evaluate the data in geophysical terms. This is illustrated by means of sample sets taken simultaneously in an urban, forest and coastal environment of the same region.

Abstract: (0 0 1)-oriented 3 mol% yttria stabilized tetragonal zirconia (3Y-TZP) has been developed by reactive synthesis of undoped pure monoclinic zirconia and co-precipitated 8 mol% yttria-stabilized zirconia (8Y-ZrO2). The dispersed pure monoclinic ZrO2 powder, having magnetic anisotropy, was first aligned in a strong magnetic field and co-sintered in a randomly distributed cubic 8Y-ZrO2 fine matrix powder. The reactive sintering resulted in a 3Y-TZP ceramic with a (0 0 1) orientation. The (0 0 1)-oriented 3Y-TZP showed a substantial toughness anisotropy, i.e. the toughness along the [0 0 1] direction is 54% higher than that of its perpendicular direction. Moreover, the toughness along the [0 0 1] direction is 49% higher than that of a non-textured isotropic reactively synthesized 3Y-TZP and 110% higher than that of an isotropic co-precipitated powder based 3Y-TZP. The substantially enhanced toughness was interpreted in terms of the tetragonal to monoclinic martensitic phase transformability.

Abstract: Gielis curves (GC) can represent a wide range of shapes and patterns ranging from star shapes to symmetric and asymmetric polygons, and even self intersecting curves. Such patterns appear in natural objects or phenomena, such as flowers, crystals, pollen structures, animals, or even wave propagation. Gielis curves and surfaces are an extension of Lamé curves and surfaces (superquadrics) which have benefited in the last two decades of extensive researches to retrieve their parameters from various data types, such as range images, 2D and 3D point clouds, etc. Unfortunately, the most efficient techniques for superquadrics recovery, based on deterministic methods, cannot directly be adapted to Gielis curves. Indeed, the different nature of their parameters forbids the use of a unified gradient descent approach, which requires initial pre-processings, such as the symmetry detection, and a reliable pose and scale estimation. Furthermore, even the most recent algorithms in the literature remain extremely sensitive to initialization and often fall into local minima in the presence of large missing data. We present a simple evolutionary algorithm which overcomes most of these issues and unifies all of the required operations into a single though efficient approach. The key ideas in this paper are the replacement of the potential fields used for the cost function (closed form) by the shortest Euclidean distance (SED, iterative approach), the construction of cost functions which minimize the shortest distance as well as the curve length using R-functions, and slight modifications of the evolutionary operators. We show that the proposed cost function based on SED and R-function offers the best compromise in terms of accuracy, robustness to noise, and missing data.

Abstract: Biomass is expected to play an increasingly significant role in the greening of energy supply. Nevertheless, concerns are rising about the sustainability of large-scale energy crop production. Impacts must be assessed carefully before deciding whether and how this industry should be developed, and what technologies, policies and investment strategies should be pursued. There is need for a comprehensive and reliable sustainability assessment tool to evaluate the environmental, social and economic performance of biomass energy production. This paper paves the way for such a tool by analysing and comparing the performance and applicability of a selection of existing tools that are potentially useful for sustainability assessment of bioenergy systems. The selected tools are: Criteria And Indicators (C&I), Life Cycle Assessment (LCA), Environmental Impact Assessment (EIA), Cost Benefit Analysis (CBA), Exergy Analysis (EA) and System Perturbation Analysis (SPA). To evaluate the tools, a framework was constructed that consists of four evaluation levels: sustainability issues, tool attributes, model structure, area of application. The tools were then evaluated using literature data and with the help of a Delphi panel of experts. Finally, a statistical analysis was performed on the resulting data matrix to detect significant differences between tools. It becomes clear that none of the selected tools is able to perform a comprehensive sustainability assessment of bioenergy systems. Every tool has its particular advantages and disadvantages, which means that trade-offs are inevitable and a balance must be found between scientific accuracy and pragmatic decision making. A good definition of the assessment objective is therefore crucial. It seems an interesting option to create a toolbox that combines procedural parts of C&I and EIA, supplemented with calculation algorithms of LCA and CBA for respectively environmental and economic sustainability indicators. Nevertheless, this would require a more comprehensive interdisciplinary approach to align the different tool characteristics and focuses.

Abstract: This work presents the results of a novel application for the fast on-site screening of cocaine and its main cutting agents in suspicious and confiscated samples. The methodology behind the novel application consists of portable electrochemical detection coupled with a peak-recognition algorithm for automated result output generation, validated both in laboratory and field settings. Currently used field tests, predominantly colorimetric tests, are lacking accuracy, often giving false positive or negative results. This presses the need for alternative approaches to field testing. By combining portable electrochemical approaches with peak-recognition algorithms, an accuracy of 98.4% concerning the detection of cocaine was achieved on a set of 374 powder samples. In addition, the approach was tested on multiple 'smuggled', colored cocaine powders and cocaine mixtures in solid and liquid states, typically in matrices such as charcoal, syrup and clothing. Despite these attempts to hide cocaine, our approach succeeded in detecting cocaine during on-site screening scenarios. This feature presents an advantage over colorimetric and optical detection techniques, which can fail with colored sample matrices. This enhanced accuracy on smuggled samples will lead to increased efficiency in confiscation procedures in the field, thus significantly reducing societal economic and safety concerns and highlighting the potential for electrochemical approaches in on-the-spot identification of drugs of abuse.

Abstract: Immunogenic cell death is characterized by the emission of danger signals that facilitate activation of an adaptive immune response against dead-cell antigens. In the case of cancer therapy, tumor cells undergoing immunogenic death promote cancer-specific immunity. Identification, characterization, and optimization of stimuli that induce immunogenic cancer cell death has tremendous potential to improve the outcomes of cancer therapy. In this study, we show that non-thermal, atmospheric pressure plasma can be operated to induce immunogenic cell death in an animal model of colorectal cancer. In vitro, plasma treatment of CT26 colorectal cancer cells induced the release of classic danger signals. Treated cells were used to create a whole-cell vaccine which elicited protective immunity in the CT26 tumor mouse model. Moreover, plasma treatment of subcutaneous tumors elicited emission of danger signals and recruitment of antigen presenting cells into tumors. An increase in T cell responses targeting the colorectal cancer-specific antigen guanylyl cyclase C (GUCY2C) were also observed. This study provides the first evidence that non-thermal plasma is a bone fide inducer of immunogenic cell death and highlights its potential for clinical translation for cancer immunotherapy.

Abstract: Combining partial nitrification, granular activated carbon (GAC) filtration, and distillation is a well-studied approach to convert urine into a fertilizer. To evaluate the environmental sustainability of a technology, the operational carbon footprint and therefore nitrous oxide (N2O) emissions should be known, but N2O emissions from urine nitrification have not been assessed yet. Therefore, N2O emissions of a decentralized urine nitrification reactor were monitored for 1 month. During nitrification, 0.4-1.2% of the total nitrogen load was emitted as N2O-N with an average N2O emission factor (EFN2O) of 0.7%. Additional N2O was produced during anoxic storage between nitrification and GAC filtration with an estimated EFN2O of 0.8%, resulting in an EFN2O of 1.5% for the treatment chain. N2O emissions during nitrification can be mitigated by 60% by avoiding low dissolved oxygen or anoxic conditions and nitrite concentrations above 5 mg-N L-1. Minimizing the hydraulic retention time between nitrification and GAC filtration can reduce N2O formation during intermediate storage by 100%. Overall, the N2O emissions accounted for 45% of the operational carbon footprint of 14 kg-CO2,equiv kg-N-1 for urine fertilizer production. Using electricity from renewable sources and applying the proposed N2O mitigation strategies could potentially lower the carbon footprint by 85%.

Abstract: Laser microprobe mass analysis was applied to study the chemical composition of spheroliths in the Bowman's membrane of patients suffering from primary atypical bandkeratopathy. The inclusions appear to consist mainly of calcium phosphate.

Abstract: The ability to detect low concentrations of protein biomarkers is crucial for the early-stage detection of many diseases and therefore indispensable for improving diagnostic devices for healthcare. Here, we demonstrate that by integrating DNA nanotechnologies like DNA origami and aptamers, we can design innovative biosensing concepts for reproducible and sensitive detection of specific targets. DNA origami structures decorated with aptamers were studied as a novel tool to structure the biosensor surface with nanoscale precision in a digital detection bioassay, enabling control of the density, orientation, and accessibility of the bioreceptor to optimize the interaction between target and aptamer. DNA origami was used to control the spatial distribution of an in-house-generated aptamer on superparamagnetic microparticles, resulting in an origami-linked digital aptamer bioassay to detect the main peanut antigen Ara h1 with 2-fold improved signal-to-noise ratio and 15-fold improved limit of detection compared to a digital bioassay without DNA origami. Moreover, the sensitivity achieved was 4 orders of magnitude higher than commercially available and literature-reported enzyme-linked immunosorbent assay techniques. In conclusion, this novel and innovative approach to engineer biosensing interfaces will be of major interest to scientists and clinicians looking for new molecular insights and ultrasensitive detection of a broad range of targets, and, for the next generation of diagnostics.