bluuebunny/crossref_metadata_2025 huggingface dataset:
Preparation of Well-Dispersed Chitosan/Alginate Hollow Multilayered Microcapsules for Enhanced Cellular Internalization
Authors: Ribeiro Carla , Borges João , Costa Ana , Gaspar Vítor , Bermudez Verónica , Mano João
Published: March 2018

Hollow multilayered capsules have shown massive potential for being used in the biomedical and biotechnology fields, in applications such as cellular internalization, intracellular trafficking, drug delivery, or tissue engineering. In particular, hollow microcapsules, developed by resorting to porous calcium carbonate sacrificial templates, natural-origin building blocks and the prominent Layer-by-Layer (LbL) technology, have attracted increasing attention owing to their key features. However, these microcapsules revealed a great tendency to aggregate, which represents a major hurdle when aiming for cellular internalization and intracellular therapeutics delivery. Herein, we report the preparation of well-dispersed polysaccharide-based hollow multilayered microcapsules by combining the LbL technique with an optimized purification process. Cationic chitosan (CHT) and anionic alginate (ALG) were chosen as the marine origin polysaccharides due to their biocompatibility and structural similarity to the extracellular matrices of living tissues. Moreover, the inexpensive and highly versatile LbL technology was used to fabricate core-shell microparticles and hollow multilayered microcapsules, with precise control over their composition and physicochemical properties, by repeating the alternate deposition of both materials. The microcapsules’ synthesis procedure was optimized to extensively reduce their natural aggregation tendency, as shown by the morphological analysis monitored by advanced microscopy techniques. The well-dispersed microcapsules showed an enhanced uptake by fibroblasts, opening new perspectives for cellular internalization.
Maternal Consumption of Low-Isoflavone Soy Protein Isolate Confers the Increased Predisposition to Alcoholic Liver Injury in Adult Rat Offspring
Authors: Won Sae , Kwon Young
Published: March 2018

Offspring of female rats fed either a casein (CAS) diet or a low-isoflavone soy protein isolate (SPI) diet were compared in an animal model of chronic ethanol consumption to investigate whether maternal diet regulates the adaptive responses of offspring to postnatal ethanol exposure and potentially affects the development of liver disease in later life. Female rats were fed either a CAS or an SPI diet before mating, and during pregnancy and lactation. Male offspring from the same litter were pair-fed either a control or ethanol diet for six weeks (CAS/CON, CAS/EtOH, SPI/CON, and SPI/EtOH groups). Serum aminotransferase activities and hepatic inflammatory indicators were higher in the SPI/EtOH group than in the CAS/EtOH group. Ethanol consumption increased serum homocysteine levels, hepatic S-adenosylmethionine:S-adenosylhomocysteine ratio, and hepatic endoplasmic reticulum stress only in offspring of SPI-fed female rats. Total and high-density lipoprotein (HDL) cholesterol levels and mRNA levels of hepatic genes involved in HDL cholesterol assembly were reduced in the SPI group in response to ethanol consumption. In conclusion, offspring of SPI-fed female rats were more susceptible to the later development of alcoholic liver disease than offspring of CAS-fed female rats. Furthermore, maternal SPI consumption altered one-carbon metabolism and cholesterol metabolism of offspring fed an ethanol diet.
Protein Supplementation During or Following a Marathon Run Influences Post-Exercise Recovery
Authors: Saunders Michael , Luden Nicholas , DeWitt Cash , Gross Melinda , Dillon Rios Amanda
Published: March 2018

The effects of protein supplementation on the ratings of energy/fatigue, muscle soreness [ascending (A) and descending (D) stairs], and serum creatine kinase levels following a marathon run were examined. Variables were compared between recreational male and female runners ingesting carbohydrate + protein (CP) during the run (CPDuring, n = 8) versus those that were consuming carbohydrate (CHODuring, n = 8). In a second study, outcomes were compared between subjects who consumed CP or CHO immediately following exercise [CPPost (n = 4) versus CHOPost (n = 4)]. Magnitude-based inferences revealed no meaningful differences between treatments 24 h post-marathon. At 72 h, recovery [Δ(72 hr-Pre)] was likely improved with CPDuring versus CHODuring, respectively, for Physical Energy (+14 ± 64 vs −74 ± 70 mm), Mental Fatigue (−52 ± 59 vs +1 ± 11 mm), and Soreness-D (+15 ± 9 vs +21 ± 70 mm). In addition, recovery at 72 h was likely-very likely improved with CPPost versus CHOPost for Physical Fatigue, Mental Energy, and Soreness-A. Thus, protein supplementation did not meaningfully alter recovery during the initial 24 h following a marathon. However, ratings of energy/fatigue and muscle soreness were improved over 72 h when CP was consumed during exercise, or immediately following the marathon.
Effects of Insect Protein Supplementation during Resistance Training on Changes in Muscle Mass and Strength in Young Men
Authors: Vangsoe Mathias , Joergensen Malte , Heckmann Lars-Henrik , Hansen Mette
Published: March 2018

During prolonged resistance training, protein supplementation is known to promote morphological changes; however, no previous training studies have tested the effect of insect protein isolate in a human trial. The aim of this study was to investigate the potential effect of insect protein as a dietary supplement to increase muscle hypertrophy and strength gains during prolonged resistance training in young men. Eighteen healthy young men performed resistance training four day/week for eight weeks. Subjects were block randomized into two groups consuming either an insect protein isolate or isocaloric carbohydrate supplementation within 1 h after training and pre-sleep on training days. Strength and body composition were measured before and after intervention to detect adaptions to the resistance training. Three-day weighed dietary records were completed before and during intervention. Fat- and bone- free mass (FBFM) improved significantly in both groups (Mean (95% confidence interval (CI))), control group (Con): (2.5 kg (1.5, 3.5) p < 0.01), protein group (Pro): (2.7 kg (1.6, 3.8) p < 0.01) from pre- to post-. Leg and bench press one repetition maximum (1 RM) improved by Con: (42.0 kg (32.0, 52.0) p < 0.01) and (13.8 kg (10.3, 17.2) p < 0.01), Pro: (36.6 kg (27.3, 45.8) p < 0.01) and (8.1 kg (4.5, 11.8) p < 0.01), respectively. No significant differences in body composition and muscle strength improvements were found between groups. In young healthy men, insect protein supplementation did not improve adaptations to eight weeks of resistance training in comparison to carbohydrate supplementation. A high habitual protein intake in both Con and Pro may partly explain our observation of no superior effect of insect protein supplementation.
Using Field Data for Energy Efficiency Based on Maintenance and Operational Optimisation. A Step towards PHM in Process Plants
Authors: Demichela Micaela , Baldissone Gabriele , Darabnia Behnoush
Published: March 2018

Energy saving is an important issue for any industrial sector; in particular, for the process industry, it can help to minimize both energy costs and environmental impact. Maintenance optimization and operational procedures can offer margins to increase energy efficiency in process plants, even if they are seldom explicitly taken into account in the predictive models guiding the energy saving policies. To ensure that the plant achieves the desired performance, maintenance operations and maintenance results should be monitored, and the connection between the inputs and the outcomes of the maintenance process, in terms of total contribution to manufacturing performance, should be explicit. In this study, a model for the energy efficiency analysis was developed, based on cost and benefits balance. It is aimed at supporting the decision making in terms of technical and operational solutions for energy efficiency, through the optimization of maintenance interventions and operational procedures. A case study is here described: the effects on energy efficiency of technical and operational optimization measures for bituminous materials production process equipment. The idea of the Conservation Supply Curve (CSC) was used to capture both the cost effectiveness of the measures and the energy efficiency effectiveness. The optimization was thus based on the energy consumption data registered on-site: data collection and modelling of the relevant data were used as a base to implement a prognostic and health management (PHM) policy in the company. Based on the results from the analysis, efficiency measures for the industrial case study were proposed, also in relation to maintenance optimization and operating procedures. In the end, the impacts of the implementation of energy saving measures on the performance of the system, in terms of technical and economic feasibility, were demonstrated. The results showed that maintenance optimization could help in reaching an energy costs recovery equal to the 10% of the total costs for an electric motor system.
Kairos and Carnival: Mikhail Bakhtin’s Rhetorical and Ethical Christian Vision
Authors: Bekker Ian
Published: March 2018

The term kairos has been used to mean, alternatively, right timing or proportion in Ancient Greek rhetoric, by Jesus to refer to the Christian eschaton and by Paul Tillich and modern liberation theologians to refer to the breakthrough of the divine into human history. Kairos, unlike chronos, is an intrinsically qualitative time and implies a consciousness of the present as well as the need for responsive action. This emphasis on action provides the link between kairos and virtue, the particular virtue in question being that of prudence (phronesis in Greek). The aim of this article is twofold: to highlight and make explicit the connections between the notion of kairos and the Russian literary-theorist and philosopher Mikhail Bakhtin’s rhetorical and ethical world, with particular emphasis on his notion of carnival; secondly, to further support a Christian reading of Bakthin’s work by making explicit the connections between his carnivalesque vision and a Christian reading of the ethical importance of kairos and its links with incarnation.
A Sliding Window-Based Joint Sparse Representation (SWJSR) Method for Hyperspectral Anomaly Detection
Authors: Soofbaf Seyyed , Sahebi Mahmod , Mojaradi Barat
Published: March 2018

In this paper, a new sliding window-based joint sparse representation (SWJSR) anomaly detector for hyperspectral data is proposed. The main contribution of this paper is to improve the judgments about the probability of anomaly presence in signals using the integration of information gathered during transition of sliding window for each pixel. In this method, each pixel experiences different spatial positions with respect to the spatial neighbors through the transition of this sliding window. In each position, an optimized local background dictionary is formed using a K-Singular Value Decomposition (K-SVD) algorithm and the recovery error of sparse estimation for each pixel is calculated using a simultaneous orthogonal matching pursuit algorithm (SOMP). Thus, the votes of each signal in terms of the anomaly presence in each spatial neighborhood are calculated and the variance of these recovery errors is considered as the detection criterion. The experimental results of the proposed SWJSR method on both synthetic and real datasets proved its higher performance compared to the Global RX (GRX), Local RX (LRX), Collaborative Representation Detector (CRD), Background Joint Sparse Representation (BJSR), Causal RX Detector (CR-RXD, CK-RXD), and Sliding Local RX(SLRX) detectors with an average efficiency improvement of about 7.5%, 14.25%, 8.2%, 8.25%, 6.45%, 6.5%, and 3.6%, respectively, in comparison to the mentioned algorithms.
Object-Based Mapping of Aboveground Biomass in Tropical Forests Using LiDAR and Very-High-Spatial-Resolution Satellite Data
Authors: Hirata Yasumasa , Furuya Naoyuki , Saito Hideki , Pak Chealy , Leng Chivin , Sokh Heng , Ma Vuthy , Kajisa Tsuyoshi , Ota Tetsuji , Mizoue Nobuya
Published: March 2018

Developing countries that intend to implement the United Nations REDD-plus (Reducing Emissions from Deforestation and forest Degradation, and the role of forest conservation, sustainable management of forests, and enhancement of forest carbon stocks) framework and obtain economic incentives are required to estimate changes in forest carbon stocks based on the IPCC guidelines. In this study, we developed a method to support REDD-plus implementation by estimating tropical forest aboveground biomass (AGB) by combining airborne LiDAR with very-high-spatial-resolution satellite data. We acquired QuickBird satellite images of Kampong Thom, Cambodia in 2011 and airborne LiDAR measurements in some parts of the same area. After haze reduction and atmospheric correction of the satellite data, we calibrated reflectance values from the mean reflectance of the objects (obtained by segmentation from areas of overlap between dates) to reduce the effects of the observation angle and solar elevation. Then, we performed object-based classification using the satellite data (overall accuracy = 77.0%, versus 92.9% for distinguishing forest from non-forest land). We used a two-step method to estimate AGB and map it in a tropical environment in Cambodia. First, we created a multiple-regression model to estimate AGB from the LiDAR data and plotted field-surveyed AGB values against AGB values predicted by the LiDAR-based model (R2 = 0.90, RMSE = 38.7 Mg/ha), and calculated reflectance values in each band of the satellite data for the analyzed objects. Then, we created a multiple-regression model using AGB predicted by the LiDAR-based model as the dependent variable and the mean and standard deviation of the reflectance values in each band of the satellite data as the explanatory variables (R2 = 0.73, RMSE = 42.8 Mg/ha). We calculated AGB of all objects, divided the results into density classes, and mapped the resulting AGB distribution. Our results suggest that this approach can provide the forest carbon stock per unit area values required to support REDD-plus.
Speckle Suppression Based on Sparse Representation with Non-Local Priors
Authors: Liu Shuaiqi , Hu Qi , Li Pengfei , Zhao Jie , Wang Chong , Zhu Zhihui
Published: March 2018

As speckle seriously restricts the applications of remote sensing images in many fields, the ability to efficiently and effectively suppress speckle in a coherent imaging system is indispensable. In order to overcome the over-smoothing problem caused by the speckle suppression algorithm based on classical sparse representation, we propose a non-local speckle suppression algorithm that combines the non-local prior knowledge of the image into the sparse representation. The proposed algorithm first applies shearlet to sparsely represent the input image. We then incorporate the non-local priors as constraints into the image sparse representation de-noising problem. The denoised image is obtained by utilizing an alternating minimization algorithm to solve the corresponding constrained de-noising problem. The experimental results show that the proposed algorithm can not only significantly remove speckle noise, but also improve the visual effect and retain the texture information of the image better.
Development of a Regional Lidar-Derived Above-Ground Biomass Model with Bayesian Model Averaging for Use in Ponderosa Pine and Mixed Conifer Forests in Arizona and New Mexico, USA
Authors: Tenneson Karis , Patterson Matthew , Mellin Thomas , Nigrelli Mark , Joria Peter , Mitchell Brent
Published: March 2018

Historical forest management practices in the southwestern US have left forests prone to high-severity, stand-replacement fires. Reducing the cost of forest-fire management and reintroducing fire to the landscape without negative impact depends on detailed knowledge of stand composition, in particular, above-ground biomass (AGB). Lidar-based modeling techniques provide opportunities to increase ability of managers to monitor AGB and other forest metrics at reduced cost. We developed a regional lidar-based statistical model to estimate AGB for Ponderosa pine and mixed conifer forest systems of the southwestern USA, using previously collected field data. Model selection was performed using Bayesian model averaging (BMA) to reduce researcher bias, fully explore the model space, and avoid overfitting. The selected model includes measures of canopy height, canopy density, and height distribution. The model selected with BMA explains 71% of the variability in field-estimates of AGB, and the RMSE of the two independent validation data sets are 23.25 and 32.82 Mg/ha. The regional model is structured in accordance with previously described local models, and performs equivalently to these smaller scale models. We have demonstrated the effectiveness of lidar for developing cost-effective, robust regional AGB models for monitoring and planning adaptively at the landscape scale.
Scene Classification Based on a Deep Random-Scale Stretched Convolutional Neural Network
Authors: Liu Yanfei , Zhong Yanfei , Fei Feng , Zhu Qiqi , Qin Qianqing
Published: March 2018

With the large number of high-resolution images now being acquired, high spatial resolution (HSR) remote sensing imagery scene classification has drawn great attention but is still a challenging task due to the complex arrangements of the ground objects in HSR imagery, which leads to the semantic gap between low-level features and high-level semantic concepts. As a feature representation method for automatically learning essential features from image data, convolutional neural networks (CNNs) have been introduced for HSR remote sensing image scene classification due to their excellent performance in natural image classification. However, some scene classes of remote sensing images are object-centered, i.e., the scene class of an image is decided by the objects it contains. Although previous methods based on CNNs have achieved comparatively high classification accuracies compared with the traditional methods with handcrafted features, they do not consider the scale variation of the objects in the scenes. This makes it difficult to directly utilize CNNs on those remote sensing images belonging to object-centered classes to extract features that are robust to scale variation, leading to wrongly classified scene images. To solve this problem, scene classification based on a deep random-scale stretched convolutional neural network (SRSCNN) for HSR remote sensing imagery is proposed in this paper. In the proposed method, patches with a random scale are cropped from the image and stretched to the specified scale as the input to train the CNN. This forces the CNN to extract features that are robust to the scale variation. Furthermore, to further improve the performance of the CNN, a robust scene classification strategy is adopted, i.e., multi-perspective fusion. The experimental results obtained using three datasets—the UC Merced dataset, the Google dataset of SIRI-WHU, and the Wuhan IKONOS dataset—confirm that the proposed method performs better than the traditional scene classification methods.
Measurements by A LEAP-Based Virtual Glove for the Hand Rehabilitation
Authors: Placidi Giuseppe , Cinque Luigi , Polsinelli Matteo , Spezialetti Matteo
Published: March 2018

Hand rehabilitation is fundamental after stroke or surgery. Traditional rehabilitation requires a therapist and implies high costs, stress for the patient, and subjective evaluation of the therapy effectiveness. Alternative approaches, based on mechanical and tracking-based gloves, can be really effective when used in virtual reality (VR) environments. Mechanical devices are often expensive, cumbersome, patient specific and hand specific, while tracking-based devices are not affected by these limitations but, especially if based on a single tracking sensor, could suffer from occlusions. In this paper, the implementation of a multi-sensors approach, the Virtual Glove (VG), based on the simultaneous use of two orthogonal LEAP motion controllers, is described. The VG is calibrated and static positioning measurements are compared with those collected with an accurate spatial positioning system. The positioning error is lower than 6 mm in a cylindrical region of interest of radius 10 cm and height 21 cm. Real-time hand tracking measurements are also performed, analysed and reported. Hand tracking measurements show that VG operated in real-time (60 fps), reduced occlusions, and managed two LEAP sensors correctly, without any temporal and spatial discontinuity when skipping from one sensor to the other. A video demonstrating the good performance of VG is also collected and presented in the Supplementary Materials. Results are promising but further work must be done to allow the calculation of the forces exerted by each finger when constrained by mechanical tools (e.g., peg-boards) and for reducing occlusions when grasping these tools. Although the VG is proposed for rehabilitation purposes, it could also be used for tele-operation of tools and robots, and for other VR applications.
Identification of Nitrogen, Phosphorus, and Potassium Deficiencies Based on Temporal Dynamics of Leaf Morphology and Color
Authors: Sun Yuanyuan , Tong Cheng , He Shan , Wang Ke , Chen Lisu
Published: March 2018

Non-destructive nutrition diagnosis provides effective technological support for agricultural sustainability. According to the plant nutrition mechanism, leaf characteristics displays different changing trends under nitrogen (N), phosphorus (P), and potassium (K) nutrition stress. In this study, the dynamic capture of rice leaf by scanning was used to research the changing regulation of leaf characteristics under nutrition stress. The leaf characteristics were extracted by mean value and regionprops functions in MATLAB, and the leaf dynamics were quantified by calculating the relative growth rate. Stepwise discriminant analysis and leave one out cross validation were applied to identify NPK deficiencies. The results indicated that leaves with N deficiency presented the lowest extension rate and the fastest wilt rate, followed by P and K deficiencies. During the identification, both morphological and color indices of the first incomplete leaf were effective indices for identification, but for the third fully expanded leaf, they were mainly color indices. Moreover, the first incomplete leaf had comparative advantage in early diagnosis (training accuracy 73.7%, validation accuracy 71.4% at the 26th day after transplantation), and the third fully expanded leaf generated higher accuracy at later stage. Overall, dynamic analysis expanded the application of leaf characteristics in identification, which contributes to improving the diagnostic effect.
Energy Use and Perceived Indoor Environment in a Swedish Multifamily Building before and after Major Renovation
Authors: La Fleur Lina , Rohdin Patrik , Moshfegh Bahram
Published: March 2018

Improved energy efficiency in the building sector is a central goal in the European Union and renovation of buildings can significantly improve both energy efficiency and indoor environment. This paper studies the perception of indoor environment, modelled indoor climate and heat demand in a building before and after major renovation. The building was constructed in 1961 and renovated in 2014. Insulation of the façade and attic and new windows reduced average U-value from 0.54 to 0.29 W/m2·K. A supply and exhaust ventilation system with heat recovery replaced the old exhaust ventilation. Heat demand was reduced by 44% and maximum supplied heating power was reduced by 38.5%. An on-site questionnaire indicates that perceived thermal comfort improved after the renovation, and the predicted percentage dissatisfied is reduced from 23% to 14% during the heating season. Overall experience with indoor environment is improved. A sensitivity analysis indicates that there is a compromise between thermal comfort and energy use in relation to window solar heat gain, internal heat generation and indoor temperature set point. Higher heat gains, although reducing energy use, can cause problems with high indoor temperatures, and higher indoor temperature might increase thermal comfort during heating season but significantly increases energy use.
Do Temporary Creative Clusters Promote Innovation in an Emerging Economy?—A Case Study of the Beijing Design Week
Authors: Zhu Huasheng , Chen Kebi , Lian Yunlong
Published: March 2018

Extant research indicates that temporary clusters, such as trade fairs and exhibitions, play a significant role in knowledge dissemination and innovation by creating global buzz, so they are beneficial to building global pipelines. However, these findings are mainly based on the experiences in the manufacturing sectors of developed countries. This paper, however, chooses Beijing as a case to examine whether or not international exhibitions in creative industries contribute to innovation in emerging economies. Based on questionnaire surveys and semi-structured interviews conducted in 2015–2016, this paper uses a structural equation model (SEM), with three latent variables related to global buzz, global pipelines, and information acquisition, to identify the internal patterns of exhibition innovation. The results indicate that there exists innovation generated from temporary clusters in knowledge-intensive sectors as well as emerging economies. Global buzz and global pipelines construct a favorable interaction ecology. However, global buzz plays a greater role than global pipelines. This insight should help organizers improve creative exhibitions in terms of innovation and provide a deeper understanding of the relationships between innovation, global buzz, and global pipelines in temporary clusters.
Influence of Technological Assets on Organizational Performance through Absorptive Capacity, Organizational Innovation and Internal Labour Flexibility
Authors: García-Sánchez Encarnación , García-Morales Víctor J. , Martín-Rojas Rodrigo
Published: March 2018

Organizational innovation is increasingly mandatory for firms to overcome their competitors. Organizational innovation is especially relevant in today’s dynamic and turbulent environments, where other internal variables—such as technological assets, employee training, coordination of new management capabilities, and new flexible human resources and more adaptable organizational designs—must be encouraged to create value and competitive advantage. The purpose of our research is to analyse whether technological assets influence absorptive capacity (potential and realized absorptive capacity) and how absorptive capacity influences internal labour flexibility, organizational innovation and performance. We achieve these goals by analysing the interrelations among internal labour flexibility, organizational innovation and performance, using the theory of resources and capabilities. A quantitative study was carried out with data gathered by personal interview using a structured questionnaire. Relationships proposed in the theoretical model were estimated through a structural equation model, using a sample of 160 European technology companies. The results show that support for technology and improvement of technological skills and technological distinctive competencies promote improvement in organizational performance through their positive influence on the processes of potential and realized absorption capacity. Potential absorptive capacity influences realized absorptive capacity, which impacts not only internal labour flexibility but also organizational innovation and organizational performance. Further, internal labour flexibility influences organizational performance through organizational innovation. This issue is of particular interest when considering the dynamic nature of turbulent technological environments in which the organization operates. Technological assets thus identify new sources of flexibility and organizational innovation based on deeper contextual knowledge and tools that aid knowledge capacity in the company.
Spatio-Temporal Variation of Land-Use Intensity from a Multi-Perspective—Taking the Middle and Lower Reaches of Shule River Basin in China as an Example
Authors: Ma Libang , Cheng Wenjuan , Bo Jie , Li Xiaoyang , Gu Yuan
Published: March 2018

The long-term human activities could influence land use/cover change and sustainability. As the global climate changes, humans are using more land resources to develop economy and create material wealth, which causes a tremendous influence on the structure of natural resources, ecology, and environment. Interference from human activities has facilitated land utilization and land coverage change, resulting in changes in land-use intensity. Land-use intensity can indicate the degree of the interference of human activities on lands, and is an important indicator of the sustainability of land use. Taking the middle and lower reaches of Shule River Basin as study region, this paper used “land-use degree (LUD)” and “human activity intensity (HAI)” models for land-use intensity, and analyzed the spatio-temporal variation of land-use intensity in this region from a multi-perspective. The results were as follows: (1) From 1987 to 2015, the land use structure in the study region changed little. Natural land was always the main land type, followed by semi-natural land and then artificial land. (2) The LUD in the study region increased by 35.36 over the 29 years. It increased the most rapidly from 1996 to 2007, and after 2007, it still increased, but more slowly. A spatial distribution pattern of “low land-use degree in east and west regions and high land-use degree in middle region” changed to “high land-use degree in east and middle regions and low land-use degree in west region”. (3) The human activity intensity of artificial lands (HAI-AL) in the study region decreased from 1987 to 1996, and then increased from 1996 to 2015. The human activity intensity of semi-artificial lands (HAL-SAL) in the study region increased over the 29 years, and more rapidly after 1996. (4) 1996–2007 was a transition period for the land-use intensity in the study region. This was related to the implementation of the socio-economy, policies such as “Integrated Development of Agricultural Irrigation and Immigrant Settlement in Shule River Basin (1996–2006)”, and technologies.
Adjustable Model of Renewable Energy Projects for Sustainable Development: A Case Study of the Nišava District in Serbia
Authors: Dimić Violeta , Milošević Mimica , Milošević Dušan , Stević Dragan
Published: March 2018

This paper explores and ranks the key performance indicators of multi-criteria decision-making in the process of selecting renewable energy sources (RES). Different categories of factors (e.g., political, legal, technological, economic and financial, sociocultural, and physical) are crucial for the analysis of such projects. In this paper, we apply the fuzzy analytic hierarchy process (fuzzy AHP) method—a mathematical method—in order to analyze the main criteria for such projects, which include the environment, the organizational management structure, project participants, and participants’ relationship with the performance indicators. In order of ranking, the indicators are the following: time, costs, quality, monitoring the project’s sustainability, user feedback, and users’ health and safety. The aim of this paper is to point out the necessity of creating an adjustable model for renewable energy projects in order to proceed with the sustainable development of the southeast part of Serbia. This model should lead the creation process for such a project, with the aim of increasing its energy efficiency.
Links between Climate Change Mitigation, Adaptation and Development in Land Policy and Ecosystem Restoration Projects: Lessons from South Africa
Authors: Favretto Nicola , Dougill Andrew , Stringer Lindsay , Afionis Stavros , Quinn Claire
Published: March 2018

Links between climate change adaptation, mitigation and development co-benefits in land policy and ecosystem restoration projects are hampered by limited understanding of how multi-faceted policy, institutions and projects interact. This paper explores perceptions of co-benefits produced by two community-level projects that pursue ecosystem restoration in South Africa. It develops a new analytical framework to assess the enabling and constraining factors in delivering triple wins for adaptation, mitigation and development. The aim is to investigate the potential for integrating community perspectives into policy and project development and implementation. Data collected through mixed-methods (policy analysis, semi-structured interviews, participatory site visits and focus groups) are analysed using thematic analysis. We find that while the projects investigated have potential to deliver triple wins, siloed approaches presently hinder effective implementation. In particular, project focus on job creation hampers the achievement of longer-term mitigation and adaptation benefits. Operational flexibility, long-term goals, multi-sectoral cooperation and enabling frameworks are imperative to the achievement of triple wins. Findings provide valuable lessons that can be applied across sub-Saharan Africa towards achieving triple wins in climate and development policy and practice, especially those developed with job creation and ecological restoration aims.
Management Innovation for Environmental Sustainability in Seaports: Managerial Accounting Instruments and Training for Competitive Green Ports beyond the Regulations
Authors: Di Vaio Assunta , Varriale Luisa
Published: March 2018

In the last 30 years, environmental sustainability has been receiving increasing attention by scholars and operators. All the seaport stakeholders, including port authorities (PAs), policy-makers, port users, any port stakeholders, and local communities, must invest substantial resources to achieve high competitiveness with respect of the environment. Drawing from the extant regulations system and conducting a deep review of the main contributions on the phenomenon, this conceptual study suggests managerial accounting instruments and training, which are still under-researched, as effective measures for enforcing and encouraging green port development. This three-step study consists of a systematic review of the regulatory frameworks and literature on the phenomenon, and an outline of the gap of the legislative framework and research, from a management innovation perspective, where effective managerial practices for environmental sustainability are not successfully suggested and implemented within seaports. On the one hand, the Balanced Scorecard and Tableau de Bord are identified and proposed as managerial accounting instruments for assessing, monitoring, measuring, controlling, and reporting the organizational processes of port players, mainly PAs, for developing competitive green ports. On the other hand, training has been suggested to educate and guide the human resources at all organizational levels within seaports, for supporting and developing awareness and behavioral attitudes in the direction of environmental sustainability.
Dietary Cadmium Intake and Its Effects on Kidneys
Authors: Satarug Soisungwan
Published: March 2018

Cadmium (Cd) is a food-chain contaminant that has high rates of soil-to-plant transference. This phenomenon makes dietary Cd intake unavoidable. Although long-term Cd intake impacts many organ systems, the kidney has long been considered to be a critical target of its toxicity. This review addresses how measurements of Cd intake levels and its effects on kidneys have traditionally been made. These measurements underpin the derivation of our current toxicity threshold limit and tolerable intake levels for Cd. The metal transporters that mediate absorption of Cd in the gastrointestinal tract are summarized together with glomerular filtration of Cd and its sequestration by the kidneys. The contribution of age differences, gender, and smoking status to Cd accumulation in lungs, liver, and kidneys are highlighted. The basis for use of urinary Cd excretion to reflect body burden is discussed together with the use of urinary N-acetyl-β-d-glucosaminidase (NAG) and β2-microglobulin (β2-MG) levels to quantify its toxicity. The associations of Cd with the development of chronic kidney disease and hypertension, reduced weight gain, and zinc reabsorption are highlighted. In addition, the review addresses how urinary Cd threshold levels have been derived from human population data and their utility as a warning sign of impending kidney malfunction.
Functional Characterization of the alb1 Orthologue Gene in the Ochratoxigenic Fungus Aspergillus carbonarius (AC49 strain)
Authors: Gerin Donato , González-Candelas Luis , Ballester Ana-Rosa , Pollastro Stefania , De Miccolis Angelini Rita , Faretra Francesco
Published: March 2018

Aspergillus carbonarius, belonging to the group Nigri, is the main species responsible for contamination by ochratoxin A (OTA) in grapes and derivative products. OTA can accumulate in the mycelium and in black conidia of the fungus and released into the matrix. Here, we have deleted in A. carbonarius the alb1 orthologue gene of A. fumigatus, involved in melanin biosynthesis. Three A. carbonarius Δalb1 mutants were characterized for morphologic traits and OTA production on different media and temperatures. Δalb1 mutants showed a fawn color of conidia associated with a significant reduction of the conidiogenesis and a statistically significant increase (p ≤ 0.01) of total OTA production as compared to the wild type (WT) strain. The alb1 gene somehow affected OTA partitioning since in Δalb1 mutants OTA amount was lower in conidia and was more abundantly secreted into the medium as compared to the WT. On grape berries the Δalb1 mutants and the WT caused lesions with similar sizes but OTA amount in berry tissues was higher for the mutants. These results demonstrate that A. carbonarius conidia pigmentation is largely dependent on polyketide biosynthesis. The gene is not directly involved in virulence and its deletion affects morphological features and OTA production in the fungus.
Trade-off Analysis of Ecosystem Services in a Mountainous Karst Area, China
Authors: Lang Yanqing , Song Wei
Published: March 2018

Diversity in ecosystem services and variation in land use by humans leads to reciprocal trade-offs or synergistic relationships between different ecosystem services. To achieve the dual goals of improving human welfare and developing sustainable ecosystems, understanding and clarifying these relationships is an important step. This study selected a mountainous karst area of China as a study area and used the InVEST (Integrate Valuation of Ecosystem Services and Trade-offs) model and the production possibility frontier analysis method to evaluate the spatio-temporal variations in ecosystem services and analyze the trade-off or synergic relationship between different services. The results showed that from 1990 to 2010, the percentage variations in annual mean water yield, soil conservation, carbon storage, and nutrient retention in the mountainous karst area were 2.47, 39.43, −0.34, and −1.16%, respectively. Water yield had trade-off relationships with soil conservation, nutrient retention, and carbon storage, increasing water yields were correlated with decreases in soil conservation, nutrient retention, and carbon storage. Soil conservation and nutrient retention also showed a trade-off relationship, decreasing soil conservation was correlated with gradually increasing nutrient retention. Carbon storage had synergic relationships with nutrient retention and soil conservation, continuous increases in carbon storage were correlated with incremental increases in nutrient retention and gradual decreases in soil conservation.
Water Temperature, pH, and Road Salt Impacts on the Fluvial Erosion of Cohesive Streambanks
Authors: Hoomehr Siavash , Akinola Akinrotimi , Wynn-Thompson Theresa , Garnand Waverly , Eick Matthew
Published: March 2018

Increasing human populations and global climate change will severely stress our water resources. One potential unforeseen consequence of these stressors is accelerated stream channel erosion due to increased stream temperatures and changes in stream chemistry, which affect the surface potential and hence the stability of soil colloids. The objectives of this study were to determine the effect of water temperature, pH, and salinity on streambank erosion rates; determine how erosion rates vary with clay mineralogy; and, explore the relationship between zeta potential and erosion rate. Remolded samples of natural montmorillonite- and vermiculite-dominated soils were eroded in a recirculating hydraulic flume under multiple shear stresses (0.1–20 Pa) with different combinations of water temperature (10, 20, and 30 °C), pH (6 and 8), and deicing salt (0 and 5000 mg/L). The results show that erosion rates significantly increased with increasing water temperature: a 10 °C increase in water temperature increased median erosion rates by as much as a factor of eight. Significant interactions between water pH and salinity also affected erosion rates. In freshwater, erosion rates were inversely related to pH; however, at high salt concentrations, the influence of pH on erosion rates was reduced. Results of this study clearly indicate water chemistry plays a critical role in the fluvial erosion of cohesive streambanks and suggest that channel protection efforts should include controls for stream temperature, in addition to peak flow rates, to maintain channel stability.
NN-Based Implicit Stochastic Optimization of Multi-Reservoir Systems Management
Authors: Sangiorgio Matteo , Guariso Giorgio
Published: March 2018

Multi-reservoir systems management is complex because of the uncertainty on future events and the variety of purposes, usually conflicting, of the involved actors. An efficient management of these systems can help improving resource allocation, preventing political crisis and reducing the conflicts between the stakeholders. Bellman stochastic dynamic programming (SDP) is the most famous among the many proposed approaches to solve this optimal control problem. Unfortunately, SDP is affected by the curse of dimensionality: computational effort increases exponentially with the complexity of the considered system (i.e., number of reservoirs), and the problem rapidly becomes intractable. This paper proposes an implicit stochastic optimization approach for the solution of the reservoir management problem. The core idea is using extremely flexible functions, such as artificial neural networks (NN), for designing release rules which approximate the optimal policies obtained by an open-loop approach. These trained NNs can then be used to take decisions in real time. The approach thus requires a sufficiently long series of historical or synthetic inflows, and the definition of a compromise solution to be approximated. This work analyzes with particular emphasis the importance of the information which represents the input of the control laws, investigating the effects of different degrees of completeness. The methodology is applied to the Nile River basin considering the main management objectives (minimization of the irrigation water deficit and maximization of the hydropower production), but can be easily adopted also in other cases.
Energetic, Exergetic, and Economic Analysis of MED-TVC Water Desalination Plant with and without Preheating
Authors: Eshoul Nuri , Almutairi Abdulrahman , Lamidi Rasaq , Alhajeri Hamad , Alenezi Abdulrahman
Published: March 2018

Desalination is the sole proven technique that can provide the necessary fresh water in arid and semi-arid countries in sufficient quantities and meet the modern needs of a growing world population. Multi effect desalination with thermal vapour compression (MED-TVC) is one of most common applications of thermal desalination technologies. The present paper presents a comprehensive thermodynamic model of a 24 million litres per day thermal desalination plant, using specialised software packages. The proposed model was validated against a real data set for a large-scale desalination plant, and showed good agreement. The performance of the MED-TVC unit was investigated using different loads, entrained vapour, seawater temperature, salinity and number of effects in two configurations. The first configuration was the MED-TVC unit without preheating system, and the second integrated the MED-TVC unit with a preheating system. The study confirmed that the thermo-compressor and its effects are the main sources of exergy destruction in these desalination plants, at about 40% and 35% respectively. The desalination plant performance with preheating mode performs well due to high feed water temperature leading to the production of more distillate water. The seawater salinity was proportional to the fuel exergy and minimum separation work. High seawater salinity results in high exergy efficiency, which is not the case with membrane technology. The plant performance of the proposed system was enhanced by using a large number of effects due to greater utilisation of energy input and higher generation level. From an economic perspective, both indicators show that using a preheating system is more economically attractive.
Stellar Populations of over 1000 z ∼ 0.8 Galaxies from LEGA-C: Ages and Star Formation Histories from Dn4000 and Hδ
Authors: Wu 吳柏 Po-Feng 鋒 , Wel Arjen van der , Gallazzi Anna , Bezanson Rachel , Pacifici Camilla , Straatman Caroline , Franx Marijn , Barišić Ivana , Bell Eric F. , Brammer Gabriel B. , Calhau Joao , Chauke Priscilla , Houdt Josha van , Maseda Michael V. , Muzzin Adam , Rix Hans-Walter , Sobral David , Spilker Justin , Sande Jesse van de , Dokkum Pieter van , Wild Vivienne
Published: March 2018

Drawing from the LEGA-C data set, we present the spectroscopic view of the stellar population across a large volume- and mass-selected sample of galaxies at large look-back time. We measure the 4000 Å break (D
n
4000) and Balmer absorption line strengths (probed by Hδ) from 1019 high-quality spectra of z = 0.6–1.0 galaxies with M
* = 2 × 1010
M
⊙ to 3 × 1011
M
⊙. Our analysis serves as a first illustration of the power of high-resolution, high signal-to-noise ratio continuum spectroscopy at intermediate redshifts as a qualitatively new tool to constrain galaxy formation models. The observed D
n
4000–EW(Hδ) distribution of our sample overlaps with the distribution traced by present-day galaxies, but z ∼ 0.8 galaxies populate that locus in a fundamentally different manner. While old galaxies dominate the present-day population at all stellar masses >2 × 1010
M
⊙, we see a bimodal D
n
4000–EW(Hδ) distribution at z ∼ 0.8, implying a bimodal light-weighted age distribution. The light-weighted age depends strongly on stellar mass, with the most massive galaxies >1 × 1011
M
⊙ being almost all older than 2 Gyr. At the same time, we estimate that galaxies in this high-mass range are only ∼3 Gyr younger than their z ∼ 0.1 counterparts, at odds with purely passive evolution given a difference in look-back time of >5 Gyr; younger galaxies must grow to >1011
M
⊙ in the meantime, or small amounts of young stars must keep the light-weighted ages young. Star-forming galaxies at z ∼ 0.8 have stronger Hδ absorption than present-day galaxies with the same D
n
4000, implying larger short-term variations in star formation activity.