bluuebunny/crossref_metadata_2025 huggingface dataset:
Gut Microbiota, Probiotics and Psychological States and Behaviors after Bariatric Surgery—A Systematic Review of Their Interrelation
Authors: Cook Jessica , Lehne Christine , Weiland Alisa , Archid Rami , Ritze Yvonne , Bauer Kerstin , Zipfel Stephan , Penders John , Enck Paul , Mack Isabelle
Published: August 2020

The gastrointestinal (GI) microbiota plays an important role in health and disease, including brain function and behavior. Bariatric surgery (BS) has been reported to result in various changes in the GI microbiota, therefore demanding the investigation of the impact of GI microbiota on treatment success. The goal of this systematic review was to assess the effects of BS on the microbiota composition in humans and other vertebrates, whether probiotics influence postoperative health, and whether microbiota and psychological and behavioral factors interact. A search was conducted using PubMed and Web of Science to find relevant studies with respect to the GI microbiota and probiotics after BS, and later screened for psychological and behavioral parameters. Studies were classified into groups and subgroups to provide a clear overview of the outcomes. Microbiota changes were further assessed for whether they were specific to BS in humans through the comparison to sham operated controls in other vertebrate studies. Changes in alpha diversity appear not to be specific, whereas dissimilarity in overall microbial community structure, and increases in the abundance of the phylum Proteobacteria and Akkermansia spp. within the phylum Verrucomicrobia after surgery were observed in both human and other vertebrates studies and may be specific to BS in humans. Human probiotic studies differed regarding probiotic strains and dosages, however it appeared that probiotic interventions were not superior to a placebo for quality of life scores or weight loss after BS. The relationship between GI microbiota and psychological diseases in this context is unclear due to insufficient available data.
Eggs Are Cost-Efficient in Delivering Several Shortfall Nutrients in the American Diet: A Cost-Analysis in Children and Adults
Authors: Papanikolaou Yanni , Fulgoni Victor L.
Published: August 2020

The purpose of the current study was to examine the cost of eggs in relation to nutrient delivery in children and adults. The present analysis used dietary intake data from the National Health and Nutrition Examination Survey 2013–2016 (egg consumers: 2–18 years-old, N = 956; 19+ years-old, N = 2424). Inflation adjusted food cost and the cost of nutrients were obtained from the Center for Nutrition Promotion and Policy food cost database. Cost and nutrient profiles for What We Eat in America food categories were compared to whole eggs. Of the 15 main food groups examined, whole eggs ranked third for lowest cost per 100 g (excluding beverages), such that eggs cost 0.35 USD per 100 g, with dairy and grains representing the first and second most cost-efficient foods, at 0.23 USD and 0.27 USD per 100 g, respectively. In children and adults, eggs represented a cost-efficient food for protein delivery, such that eggs provided nearly 2.7% and 3.7% of all protein in the diet, respectively, at a cost of about 0.03 USD per g of protein. Eggs contributed 3.8% and 6.0% of all vitamin A in the diet of children and adults, at a cost of approximately 0.002 USD and 0.003 USD per RAE mcg of vitamin A, respectively. In children 2–18 years-old, nearly 12% of all choline in the diet is delivered from eggs, at a cost of approximately 0.002 USD per mg of choline. Similarly, in adults 19-years-old+, eggs provide nearly 15% of all dietary choline in the diet, at a cost of approximately 0.002 USD per mg of choline. Eggs provide nearly 5% and 9.5% of all vitamin D in the diet of children and adults, at a cost of approximately 0.21 USD and 0.22 USD per mcg of vitamin D, respectively. Overall, eggs ranked as the most cost-efficient food for delivering protein, choline, and vitamin A, second for vitamin E, and third for vitamin D in children. In adults, eggs ranked as the most cost-efficient food for delivering protein and choline, second for vitamin A, and third for vitamin D and vitamin E. In summary, eggs represent an economical food choice for the delivery of protein and several shortfall nutrients (choline, vitamin A, and vitamin D) in the American diet.
Silica Nanoparticles in Transmucosal Drug Delivery
Authors: M. Ways Twana Mohammed , Ng Keng Wooi , Lau Wing Man , Khutoryanskiy Vitaliy V.
Published: August 2020

Transmucosal drug delivery includes the administration of drugs via various mucous membranes, such as gastrointestinal, nasal, ocular, and vaginal mucosa. The use of nanoparticles in transmucosal drug delivery has several advantages, including the protection of drugs against the harsh environment of the mucosal lumens and surfaces, increased drug residence time, and enhanced drug absorption. Due to their relatively simple synthetic methods for preparation, safety profile, and possibilities of surface functionalisation, silica nanoparticles are highly promising for transmucosal drug delivery. This review provides a description of silica nanoparticles and outlines the preparation methods for various core and surface-functionalised silica nanoparticles. The relationship between the functionalities of silica nanoparticles and their interactions with various mucous membranes are critically analysed. Applications of silica nanoparticles in transmucosal drug delivery are also discussed.
Prediction of Drug-Induced Hyperbilirubinemia by In Vitro Testing
Authors: Tátrai Péter , Krajcsi Péter
Published: August 2020

Bilirubin, the end product of heme catabolism, is produced continuously in the body and may reach toxic levels if accumulates in the serum and tissues; therefore, a highly efficient mechanism evolved for its disposition. Normally, unconjugated bilirubin enters hepatocytes through the uptake transporters organic anion transporting polypeptide (OATP) 1B1 and 1B3, undergoes glucuronidation by the Phase II enzyme UDP glucuronosyltransferase 1A1 (UGT1A1), and conjugated forms are excreted into the bile by the canalicular export pump multidrug resistance protein 2 (MRP2). Any remaining conjugated bilirubin is transported back to the blood by MRP3 and passed on for uptake and excretion by downstream hepatocytes or the kidney. The bile salt export pump BSEP as the main motor of bile flow is indirectly involved in bilirubin disposition. Genetic mutations and xenobiotics that interfere with this machinery may impede bilirubin disposition and cause hyperbilirubinemia. Several pharmaceutical compounds are known to cause hyperbilirubinemia via inhibition of OATP1Bs, UGT1A1, or BSEP. Herein we briefly review the in vitro prediction methods that serve to identify drugs with a potential to induce hyperbilirubinemia. In vitro assays can be deployed early in drug development and may help to minimize late-stage attrition. Based on current evidence, drugs that behave as mono- or multispecific inhibitors of OATP1B1, UGT1A1, and BSEP in vitro are at risk of causing clinically significant hyperbilirubinemia. By integrating inhibition data from in vitro assays, drug serum concentrations, and clinical reports of hyperbilirubinemia, predictor cut-off values have been established and are provisionally suggested in this review. Further validation of in vitro readouts to clinical outcomes is expected to enhance the predictive power of these assays.
Preparation of Hot-Melt Extruded Dosage Form for Enhancing Drugs Absorption Based on Computational Simulation
Authors: Choi Sung-Min , Lee Sung-Hoon , Kang Chin-Yang , Park Jun-Bom
Published: August 2020

The aim of this study was to control the dissolution rate and permeability of cilostazol. To enhance the dissolution rate of the active pharmaceutical ingredient (API), hot-melt extrusion (HME) technology was applied to prepare a solid dispersion (SD). To control permeability in the gastrointestinal tract regardless of food intake, the HME process was optimized based on physiologically based pharmacokinetic (PBPK) simulation. The extrudates were produced using a laboratory-scale twin-screw hot-melt extruder with co-rotatory screws and a constant feeding rate. Next, for PBPK simulation, parameter-sensitive analysis (PSA) was conducted to determine the optimization approach direction. As demonstrated by the dissolution test, the solubility of extrudate was enhanced comparing cilostazol alone. Based on the PSA analysis, the surfactant induction was a crucial factor in cilostazol absorption; thus, an extrudate with an even distribution of lipids was produced using hot-melt extrusion technology, for inducing the bile salts in the gastrointestinal tract. In vivo experiments with rats demonstrated that the optimized hot-melt extruded formulation was absorbed more rapidly with lower deviation and regardless of the meal consumed when compared to marketed cilostazol formulations.
Exploiting Biological Nitrogen Fixation: A Route Towards a Sustainable Agriculture
Authors: Soumare Abdoulaye , Diedhiou Abdala G. , Thuita Moses , Hafidi Mohamed , Ouhdouch Yedir , Gopalakrishnan Subramaniam , Kouisni Lamfeddal
Published: August 2020

For all living organisms, nitrogen is an essential element, while being the most limiting in ecosystems and for crop production. Despite the significant contribution of synthetic fertilizers, nitrogen requirements for food production increase from year to year, while the overuse of agrochemicals compromise soil health and agricultural sustainability. One alternative to overcome this problem is biological nitrogen fixation (BNF). Indeed, more than 60% of the fixed N on Earth results from BNF. Therefore, optimizing BNF in agriculture is more and more urgent to help meet the demand of the food production needs for the growing world population. This optimization will require a good knowledge of the diversity of nitrogen-fixing microorganisms, the mechanisms of fixation, and the selection and formulation of efficient N-fixing microorganisms as biofertilizers. Good understanding of BNF process may allow the transfer of this ability to other non-fixing microorganisms or to non-leguminous plants with high added value. This minireview covers a brief history on BNF, cycle and mechanisms of nitrogen fixation, biofertilizers market value, and use of biofertilizers in agriculture. The minireview focuses particularly on some of the most effective microbial products marketed to date, their efficiency, and success-limiting in agriculture. It also highlights opportunities and difficulties of transferring nitrogen fixation capacity in cereals.
A New Active Substance Derived from Lyzed Willaertia magna C2c Maky Cells to Fight Grapevine Downy Mildew
Authors: Demanèche Sandrine , Mirabel Laurène , Abbe Olivier , Eberst Jean-Baptiste , Souche Jean-Luc
Published: August 2020

Downy mildew of grapevine is one of the most destructive grapevine diseases worldwide. Nowadays, downy mildew control relies almost exclusively on the use of chemical pesticides, including copper products, which are efficient but controversial due to their environmental toxicity. Natural plant protection products have become important solutions in the quest for the sustainable production of food and pest management. However, most biocontrol agents currently on the market, such as biofungicides or elicitors, have a limited efficacy; thus, they cannot replace chemical compounds in full. Our innovation is a natural active substance, which is a lysate of the amoeba Willaertia magna C2c Maky. This active substance is not only able to elicit grapevine defenses, but it also demonstrates direct fungicidal activity against Plasmopara viticola. The efficacy of this new natural substance was demonstrated both in a greenhouse and in a field. The amoeba lysate provided up to 77% protection to grapevine bunches in the field in a natural and safe way.
Genome-Wide Analysis Reveals Transcription Factors Regulated by Spider-Mite Feeding in Cucumber (Cucumis sativus)
Authors: He Jun , Bouwmeester Harro J. , Dicke Marcel , Kappers Iris F.
Published: August 2020

To gain insight into the regulatory networks that underlie the induced defense in cucumber against spider mites, genes encoding transcription factors (TFs) were identified in the cucumber (Cucumissativus) genome and their regulation by two-spotted spider mite (Tetranychusurticae) herbivory was analyzed using RNA-seq. Of the total 1212 annotated TF genes in the cucumber genome, 119 were differentially regulated upon spider-mite herbivory during a period of 3 days. These TF genes belong to different categories but the MYB, bHLH, AP2/ERF and WRKY families had the highest relative numbers of differentially expressed genes. Correlation analysis of the expression of TF genes with defense-associated genes during herbivory and pathogen infestation, and in different organs resulted in the putative identification of regulators of herbivore-induced terpenoid and green-leaf-volatile biosynthesis. Analysis of the cis-acting regulatory elements (CAREs) present in the promoter regions of the genes responsive to spider-mite feeding revealed potential TF regulators. This study describes the TF genes in cucumber that are potentially involved in the regulation of induced defense against herbivory by spider mites.
Heteroaromatic Polyamides with Improved Thermal and Mechanical Properties
Authors: Trigo-López Miriam , Sanjuán Ana M. , Mendía Aranzazu , Muñoz Asunción , García Félix C. , García José M.
Published: August 2020

We prepared high-performance aromatic copolyamides, containing bithiazole and thiazolo-thiazole groups in their main chain, from aromatic diamines and isophthaloyl chloride, to further improve the prominent thermal behavior and exceptional mechanical properties of commercial aramid fibers. The introduction of these groups leads to aramids with improved strength and moduli compared to commercial meta-oriented aromatic polyamides, together with an increase of their thermal performance. Moreover, their solubility, water uptake, and optical properties were evaluated in this work.
Heat Shock Protein 90 (Hsp90)-Inhibitor-Luminespib-Loaded-Protein-Based Nanoformulation for Cancer Therapy
Authors: K. Rochani Ankit , Balasubramanian Sivakumar , Ravindran Girija Aswathy , Maekawa Toru , Kaushal Gagan , Kumar D. Sakthi
Published: August 2020

Drugs targeting heat shock protein 90 (Hsp90) have been extensively explored for their anticancer potential in advanced clinical trials. Nanoformulations have been an important drug delivery platform for the anticancer molecules like Hsp90 inhibitors. It has been reported that bovine serum albumin (BSA) nanoparticles (NPs) serve as carriers for anticancer drugs, which have been extensively explored for their therapeutic efficacy against cancers. Luminespib (also known as NVP-AUY922) is a new generation Hsp90 inhibitor that was introduced recently. It is one of the most studied Hsp90 inhibitors for a variety of cancers in Phase I and II clinical trials and is similar to its predecessors such as the ansamycin class of molecules. To our knowledge, nanoformulations for luminespib remain unexplored for their anticancer potential. In the present study, we developed aqueous dispensable BSA NPs for controlled delivery of luminespib. The luminespib-loaded BSA NPs were characterized by SEM, TEM, FTIR, XPS, UV-visible spectroscopy and fluorescence spectroscopy. The results suggest that luminespib interacts by non-covalent reversible interactions with BSA to form drug-loaded BSA NPs (DNPs). Our in vitro evaluations suggest that DNP-based aqueous nanoformulations can be used in both pancreatic (MIA PaCa-2) and breast (MCF-7) cancer therapy.
Low-Density Cardoon (Cynara cardunculus L.) Particleboards Bound with Potato Starch-Based Adhesive
Authors: Monteiro Sandra , Nunes Lina , Martins Jorge , D. Magalhães Fernão , Carvalho Luísa
Published: August 2020

In the present work, and for the first time, totally biosourced low-density particleboards were produced using cardoon particles (a no added value by-product from the Portuguese cheese making industry), bound with a potato starch adhesive. Different starch/cardoon ratios (0.6, 0.8, 1 and 1.2) were tested and the effect of different bio-based additives (chitosan, wood fiber and glycerol) on the performance of the adhesive system was evaluated. The best result was obtained for a formulation with a starch/cardoon mass ratio of 0.8, a chitosan/starch mass ratio of 0.05 and a water/starch mass ratio of 1.75. The particleboards produced had a density of 323 kg·m−3, internal bond strength of 0.35 N·mm−2 and thickness swelling of 15.2%. The values of density and internal bond strength meet the standard requirements of general-purpose lightweight boards for use in dry conditions according to CEN/TS 16368 specification. Moreover, the susceptibility of the formulations with best results was established against subterranean termites and one decay fungi.
Assessment of Leaf Chlorophyll Content Models for Winter Wheat Using Landsat-8 Multispectral Remote Sensing Data
Authors: Zhou Xianfeng , Zhang Jingcheng , Chen Dongmei , Huang Yanbo , Kong Weiping , Yuan Lin , Ye Huichun , Huang Wenjiang
Published: August 2020

The leaf chlorophyll content (LCC) is a critical index to characterize crop growth conditions, photosynthetic capacity, and physiological status. Its dynamic change characteristics are of great significance for monitoring crop growth conditions and understanding the process of material and energy exchange between crops and the environment. Extensive research has focused on LCC retrieval with hyperspectral data onboard various sensor platforms. Nevertheless, limited attention has been paid to LCC inversion from multispectral data, such as the data from Landsat-8, and the potentials and capabilities of the data for crop LCC estimation have not been fully explored. The present study made use of Landsat-8 Operational Land Imager (OLI) imagery and the corresponding field experimental data to evaluate their capabilities and potentials for LCC modeling using four different retrieval methods: vegetation indices (VIs), machine learning regression algorithms (MLRAs), lookup-table (LUT)-based inversion, and hybrid regression approaches. The results showed that the modified triangular vegetation index (MTVI2) exhibited the best estimate accuracy for LCC retrieval with a root mean square error (RMSE) of 5.99 μg/cm2 and a relative RMSE (RRMSE) of 10.49%. Several other vegetation indices that were established from red and near-infrared (NIR) bands also exhibited good accuracy. Models established from Gaussian process regression (GPR) achieved the highest accuracy for LCC retrieval (RMSE = 5.50 μg/cm2, RRMSE = 9.62%) compared with other MLRAs. Moreover, red and NIR bands outweighed other bands in terms of GPR modelling. LUT-based inversion methods with the “K(x) = −log (x) + x” cost function that belongs to the “minimum contrast estimates” family showed the best estimation results (RMSE = 8.08 μg/cm2, RRMSE = 14.14%), and the addition of multiple solution regularization strategies effectively improved the inversion accuracy. For hybrid regression methods, the use of active learning (AL) techniques together with GPR for LCC modelling significantly increased the estimation accuracy, and the combination of entropy query by bagging (EQB) AL and GPR had the best accuracy for LCC estimation (RMSE = 12.43 μg/cm2, RRMSE = 21.77%). Overall, our study suggest that Landsat-8 OLI data are suitable for crop LCC retrieval and could provide a basis for LCC estimation with similar multispectral datasets.
OpenSWAP, an Open Architecture, Low Cost Class of Autonomous Surface Vehicles for Geophysical Surveys in the Shallow Water Environment
Authors: Stanghellini Giuseppe , Del Bianco Fabrizio , Gasperini Luca
Published: August 2020

OpenSWAP is a class of innovative open architecture, low cost autonomous vehicles for geological/geophysical studies of shallow water environments. Although they can host different types of sensors, these vehicles were specifically designed for geophysical surveys, i.e., for the acquisition of bathymetric and stratigraphic data through single- and multibeam echosounders, side-scan sonars, and seismic-reflection systems. The main characteristic of the OpenSWAP vehicles is their ability of following pre-defined routes with high accuracy under acceptable weather and sea conditions. This would open the door to 4D (repeated) surveys, which constitute a powerful tool to analyze morphological and stratigraphic changes of the sediment/water interface and of the shallow substratum eventually caused by sediment dynamics (erosion vs. deposition), slumps and gravitative failures, earthquakes (slip along seismogenic faults and secondary effects of shaking), tsunamis, etc. The low cost and the open hardware/software architectures of these systems, which can be modified by the end users, lead for planning and execution of cooperative and adaptive surveys with different instruments not yet implemented or tested. Together with a technical description of the vehicles, we provide different case studies where they were successfully employed, carried out in environments not, or very difficultly accessed through conventional systems.
Recent Development and Challenges in Spectroscopy and Machine Vision Technologies for Crop Nitrogen Diagnosis: A Review
Authors: Li Daoliang , Zhang Pan , Chen Tao , Qin Wei
Published: August 2020

Recent development of non-destructive optical techniques, such as spectroscopy and machine vision technologies, have laid a good foundation for real-time monitoring and precise management of crop N status. However, their advantages and disadvantages have not been systematically summarized and evaluated. Here, we reviewed the state-of-the-art of non-destructive optical methods for monitoring the N status of crops, and summarized their advantages and disadvantages. We mainly focused on the contribution of spectral and machine vision technology to the accurate diagnosis of crop N status from three aspects: system selection, data processing, and estimation methods. Finally, we discussed the opportunities and challenges of the application of these technologies, followed by recommendations for future work to address the challenges.
An Optimized Filtering Method of Massive Interferometric SAR Data for Urban Areas by Online Tensor Decomposition
Authors: You Yanan , Wang Rui , Zhou Wenli
Published: August 2020

The filtering of multi-pass synthetic aperture radar interferometry (InSAR) stack data is a necessary preprocessing step utilized to improve the accuracy of the object-based three-dimensional information inversion in urban area. InSAR stack data is composed of multi-temporal homogeneous data, which is regarded as a third-order tensor. The InSAR tensor can be filtered by data fusion, i.e., tensor decomposition, and these filters keep balance in the noise elimination and the fringe details preservation, especially with abrupt fringe change, e.g., the edge of urban structures. However, tensor decomposition based on batch processing cannot deal with few newly acquired interferograms filtering directly. The filtering of dynamic InSAR tensor is the inevitable challenge when processing InSAR stack data, where dynamic InSAR tensor denotes the size of InSAR tensor increases continuously due to the acquisition of new interferograms. Therefore, based on the online CANDECAMP/PARAFAC (CP) decomposition, we propose an online filter to fuse data and process the dynamic InSAR tensor, named OLCP-InSAR, which performs well especially for the urban area. In this method, CP rank is utilized to measure the tensor sparsity, which can maintain the structural features of the InSAR tensor. Additionally, CP rank estimation is applied as an important step to improve the robustness of Online CP decomposition - InSAR(OLCP-InSAR). Importing CP rank and outlier’s position as prior information, the filter fuses the noisy interferograms and decomposes the InSAR tensor to acquire the low rank information, i.e., filtered result. Moreover, this method can not only operate on tensor model, but also efficiently filter the new acquired interferogram as matrix model with the assistance of chosen low rank information. Compared with other tensor-based filters, e.g., high order robust principal component analysis (HoRPCA) and Kronecker-basis-representation multi-pass SAR interferometry (KBR-InSAR), and the widespread traditional filters operating on a single interferometric pair, e.g., Goldstein, non-local synthetic aperture radar (NL-SAR), non-local InSAR (NL-InSAR), and InSAR nonlocal block-matching 3-D (InSAR-BM3D), the effectiveness and robustness of OLCP-InSAR are proved in simulated and real InSAR stack data. Especially, OLCP-InSAR can maintain the fringe details at the regular building top with high noise intensity and high outlier ratio.
Analyzing the Uncertainty of Degree Confluence Project for Validating Global Land-Cover Maps Using Reference Data-Based Classification Schemes
Authors: Qian Tana , Kinoshita Tsuguki , Fujii Minoru , Bao Yuhai
Published: August 2020

Global land-cover products play an important role in assisting the understanding of climate-related changes and the assessment of progress in the implementation of international initiatives for the mitigation of, and adaption to, climate change. However, concerns over the accuracies of land-cover products remain, due to the issue of validation data uncertainty. The volunteer-based Degree Confluence Project (DCP) was created in 1996, and it has been used to provide useful ground-reference information. This study aims to investigate the impact of DCP-based validation data uncertainty and the thematic issues on map accuracies. We built a reference dataset based on the DCP-interpreted dataset and applied a comparison for three existing global land-cover maps and DCP dataset-based probability maps under different classification schemes. The results of the obtained confusion matrices indicate that the uncertainty, including the number of classes and the confusion in mosaic classes, leads to a decrease in map accuracy. This paper proposes an informative classification scheme that uses a matrix structure of unaggregated land-cover and land-use classes, and has the potential to assist in the land-cover interpretation and validation processes. The findings of this study can potentially serve as a guide to select reference data and choose/define appropriate classification schemes.
An INS and UWB Fusion-Based Gyroscope Drift Correction Approach for Indoor Pedestrian Tracking
Authors: Tian Qinglin , Wang Kevin I-Kai , Salcic Zoran
Published: August 2020

Information fusion combining inertial navigation and radio frequency (RF) technologies, is commonly applied in indoor positioning systems (IPSs) to obtain more accurate tracking results. The performance of the inertial navigation system (INS) subsystem is affected by sensor drift over time and the RF-based subsystem aims to correct the position estimate using a fusion filter. However, the inherent sensor drift is usually not corrected during fusion, which leads to increasingly erroneous estimates over a short period of time. Among the inertial sensor drifts, gyroscope drift has the most significant impact in determining the correct orientation and accurate tracking. A gyroscope drift correction approach is proposed in this study and is incorporated in an INS and ultra-wideband (UWB) fusion IPS where only distance measurements from UWB subsystem are used. The drift correction approach is based on turn detection to account for the fact that gyroscope drift is accumulated during a turn. Practical pedestrian tracking experiments are conducted to demonstrate the accuracy of the drift correction approach. With the gyroscope drift corrected, the fusion IPS is able to provide more accurate tracking performance and achieve up to 64.52% mean position error reduction when compared to the INS only tracking result.
A Joint Constraint Incentive Mechanism Algorithm Utilizing Coverage and Reputation for Mobile Crowdsensing
Authors: Zhang Jing , Yang Xiaoxiao , Feng Xin , Yang Hongwei , Ren An
Published: August 2020

Selection of the optimal users to maximize the quality of the collected sensing data within a certain budget range is a crucial issue that affects the effectiveness of mobile crowdsensing (MCS). The coverage of mobile users (MUs) in a target area is relevant to the accuracy of sensing data. Furthermore, the historical reputation of MUs can reflect their previous behavior. Therefore, this study proposes a coverage and reputation joint constraint incentive mechanism algorithm (CRJC-IMA) based on Stackelberg game theory for MCS. First, the location information and the historical reputation of mobile users are used to select the optimal users, and the information quality requirement will be satisfied consequently. Second, a two-stage Stackelberg game is applied to analyze the sensing level of the mobile users and obtain the optimal incentive mechanism of the server center (SC). The existence of the Nash equilibrium is analyzed and verified on the basis of the optimal response strategy of mobile users. In addition, mobile users will adjust the priority of the tasks in time series to enable the total utility of all their tasks to reach a maximum. Finally, the EM algorithm is used to evaluate the data quality of the task, and the historical reputation of each user will be updated accordingly. Simulation experiments show that the coverage of the CRJC-IMA is higher than that of the CTSIA. The utility of mobile users and SC is higher than that in STD algorithms. Furthermore, the utility of mobile users with the adjusted task priority is greater than that without a priority order.
A Deep-Learning Approach for Foot-Type Classification Using Heterogeneous Pressure Data
Authors: Chae Jonghyeok , Kang Young-Jin , Noh Yoojeong
Published: August 2020

The human foot is easily deformed owing to the innate form of the foot or an incorrect walking posture. Foot deformations not only pose a threat to foot health but also cause fatigue and pain when walking; therefore, accurate diagnoses of foot deformations are required. However, the measurement of foot deformities requires specialized personnel, and the objectivity of the diagnosis may be insufficient for professional medical personnel to assess foot deformations. Thus, it is necessary to develop an objective foot deformation classification model. In this study, a model for classifying foot types is developed using image and numerical foot pressure data. Such heterogeneous data are used to generate a fine-tuned visual geometry group-16 (VGG16) and K−nearest neighbor (k-NN) models, respectively, and a stacking ensemble model is finally generated to improve accuracy and robustness by combining the two models. Through k-fold cross-validation, the accuracy and robustness of the proposed method have been verified by the mean and standard deviation of the f1 scores (0.9255 and 0.0042), which has superior performance compared to single models generated using only numerical or image data. Thus, the proposed model provides the objectivity of diagnosis for foot deformation, and can be used for analysis and design of foot healthcare products.
Design and Characterization of a Novel Biaxial Bionic Hair Flow Sensor Based on Resonant Sensing
Authors: Liang Zhuoyue , Guo Xin , Yang Bo , Zhang Ting
Published: August 2020

This paper presents the design, theoretical analysis, simulation verification, fabrication and prototype characterization of a novel biaxial bionic hair flow sensor based on resonant sensing. Firstly, the device architecture, mainly consists of a polymer hair post, a silicon micro signal transducer and a glass substrate, is described, the theoretical simplified model is established and the mechanical sensitivity to air flow is deducted. Then, the structure simulations based on Ansys software are implemented to preliminarily verify the feasibility of the proposed sensor conception and optimize the structure parameters simultaneously. Subsequently, a closed-loop control scheme based on digital phase-locked loop and an amplitude demodulation algorithm of oscillatory flow velocity based on the least mean square method are proposed to transform and extract the air flow signal, and then verify it by circuit simulations based on SIMULINK. Finally, the fabricated prototype is illustrated and comprehensively tested. The tested prototype possesses an x-axis scale factor of 1.56 Hz/(m/s)2 and a y-axis scale factor of 1.81 Hz/(m/s)2 for the steady air flow and an x-axis detection threshold of 43.27 mm/s and a y-axis detection threshold of 41.85 mm/s for the oscillatory air flow.
Localization of Biobotic Insects Using Low-Cost Inertial Measurement Units
Authors: Cole Jeremy , Bozkurt Alper , Lobaton Edgar
Published: August 2020

Disaster robotics is a growing field that is concerned with the design and development of robots for disaster response and disaster recovery. These robots assist first responders by performing tasks that are impractical or impossible for humans. Unfortunately, current disaster robots usually lack the maneuverability to efficiently traverse these areas, which often necessitate extreme navigational capabilities, such as centimeter-scale clearance. Recent work has shown that it is possible to control the locomotion of insects such as the Madagascar hissing cockroach (Gromphadorhina portentosa) through bioelectrical stimulation of their neuro-mechanical system. This provides access to a novel agent that can traverse areas that are inaccessible to traditional robots. In this paper, we present a data-driven inertial navigation system that is capable of localizing cockroaches in areas where GPS is not available. We pose the navigation problem as a two-point boundary-value problem where the goal is to reconstruct a cockroach’s trajectory between the starting and ending states, which are assumed to be known. We validated our technique using nine trials that were conducted in a circular arena using a biobotic agent equipped with a thorax-mounted, low-cost inertial measurement unit. Results show that we can achieve centimeter-level accuracy. This is accomplished by estimating the cockroach’s velocity—using regression models that have been trained to estimate the speed and heading from the inertial signals themselves—and solving an optimization problem so that the boundary-value constraints are satisfied.
One-Step Assembly of Fluorescence-Based Cyanide Sensors from Inexpensive, Off-The-Shelf Materials
Authors: Fernandes Gregory E. , Chang Ya-Wen , Sharma Akash , Tutt Sarah
Published: August 2020

We report a simple and versatile approach to assemble sensitive and selective fluorescence “turn-on” sensors for cyanide by combining three off-the-shelf materials; namely fluorescent dye, 1-vinyl imidazole polymer, and cupric chloride. The cyanide-sensing species is a non-fluorescent fluorophore-polymer-Cu2+ complex; which forms as a result of the imidazole polymer’s ability to bind both fluorophore and fluorescence quencher (Cu2+). Cyanide removes Cu2+ from these complexes; thereby “turning-on” sensor fluorescence. These sensors are water-soluble and have a detection limit of ~2.5 μM (CN−) in water. Our ternary complex-based sensing approach also enables facile emission tuning; we demonstrate the convenient, synthesis-free preparation of blue and green-emitting sensors using distyrylbiphenyl and fluorescein fluorophores, respectively. Furthermore; these ternary complexes are easily immobilized using agarose to create cyanide-sensing hydrogels; which are then used in a simple; novel microdiffusion apparatus to achieve interference-free cyanide analysis of aqueous media. The present study provides an inexpensive approach for portable; interference-free cyanide detection.
Glucose Biosensor Based on Disposable Activated Carbon Electrodes Modified with Platinum Nanoparticles Electrodeposited on Poly(Azure A)
Authors: Jiménez-Fiérrez Francisco , González-Sánchez María Isabel , Jiménez-Pérez Rebeca , Iniesta Jesús , Valero Edelmira
Published: August 2020

Herein, a novel electrochemical glucose biosensor based on glucose oxidase (GOx) immobilized on a surface containing platinum nanoparticles (PtNPs) electrodeposited on poly(Azure A) (PAA) previously electropolymerized on activated screen-printed carbon electrodes (GOx-PtNPs-PAA-aSPCEs) is reported. The resulting electrochemical biosensor was validated towards glucose oxidation in real samples and further electrochemical measurement associated with the generated H2O2. The electrochemical biosensor showed an excellent sensitivity (42.7 μA mM−1 cm−2), limit of detection (7.6 μM), linear range (20 μM–2.3 mM), and good selectivity towards glucose determination. Furthermore, and most importantly, the detection of glucose was performed at a low potential (0.2 V vs. Ag). The high performance of the electrochemical biosensor was explained through surface exploration using field emission SEM, XPS, and impedance measurements. The electrochemical biosensor was successfully applied to glucose quantification in several real samples (commercial juices and a plant cell culture medium), exhibiting a high accuracy when compared with a classical spectrophotometric method. This electrochemical biosensor can be easily prepared and opens up a good alternative in the development of new sensitive glucose sensors.
An Analysis Scheme of Balancing Energy Consumption with Mobile Velocity Control Strategy for Wireless Rechargeable Sensor Networks
Authors: Zhang Shun-Miao , Gao Sheng-Bo , Dao Thi-Kien , Huang De-Gen , Wang Jin , Yao Hong-Wei , Alfarraj Osama , Tolba Amr
Published: August 2020

Wireless Rechargeable Sensor Networks (WRSN) are not yet fully functional and robust due to the fact that their setting parameters assume fixed control velocity and location. This study proposes a novel scheme of the WRSN with mobile sink (MS) velocity control strategies for charging nodes and collecting its data in WRSN. Strip space of the deployed network area is divided into sub-locations for variant corresponding velocities based on nodes energy expenditure demands. The points of consumed energy bottleneck nodes in sub-locations are determined based on gathering data of residual energy and expenditure of nodes. A minimum reliable energy balanced spanning tree is constructed based on data collection to optimize the data transmission paths, balance energy consumption, and reduce data loss during transmission. Experimental results are compared with the other methods in the literature that show that the proposed scheme offers a more effective alternative in reducing the network packet loss rate, balancing the nodes’ energy consumption, and charging capacity of the nodes than the competitors.
The Synergy of Thermally Reduced Graphene Oxide in Amperometric Urea Biosensor: Application for Medical Technologies
Authors: Razumiene Julija , Gureviciene Vidute , Sakinyte Ieva , Rimsevicius Laurynas , Laurinavicius Valdas
Published: August 2020

Thermally reduced graphene oxide (TRGO) is a graphene-based nanomaterial that has been identified as promising for the development of amperometric biosensors. Urease, in combination with TRGO, allowed us to create a mediator-free amperometric biosensor with the intention of precise detection of urea in clinical trials. Beyond simplicity of the technology, the biosensor exhibited high sensitivity (2.3 ± 0.1 µA cm−2 mM−1), great operational and storage stabilities (up to seven months), and appropriate reproducibility (relative standard deviation (RSD) about 2%). The analytical recovery of the TRGO-based biosensor in urine of 101 ÷ 104% with RSD of 1.2 ÷ 1.7% and in blood of 92.7 ÷ 96.4%, RSD of 1.0 ÷ 2.5%, confirmed that the biosensor is acceptable and reliable. These properties allowed us to apply the biosensor in the monitoring of urea levels in samples of urine, blood, and spent dialysate collected during hemodialysis. Accuracy of the biosensor was validated by good correlation (R = 0.9898 and R = 0.9982) for dialysate and blood, utilizing approved methods. The advantages of the proposed biosensing technology could benefit the development of point-of-care and non-invasive medical instruments.
Financial Diversity and the Development Process: Case study of Rural Communes of Eastern Poland in 2009–2018
Authors: Dziekański Paweł , Prus Piotr
Published: August 2020

In the modern state, the role and importance of communes is growing. They can carry out their tasks when equipped with stable and efficient sources of income. Financial resources are the basis for the operation and implementation of current and development tasks. Their analysis makes it possible to assess the budget structure and provides information on the state of the local economy or endogenous growth potentials. The aim of the article is to assess the diversity of the financial situation of rural communes using a synthetic measure. In addition, using the econometric models, the impact of socio-economic factors on the diversity of the measure of synthetic financial situation was examined. In order to build synthetic measures, the Technique for Order Preference by Similarity to an Ideal Solution method and based on distance in real space with Euclidean metrics were used. The aggregated value of the synthetic variable facilitates the comparison of objects in multidimensional spaces, but also makes it possible to order them due to the examined phenomenon. Empirical data were collected in spatial terms of 484 rural communes in the Eastern Poland region. In the case of municipalities, the choice of variables was largely determined by the availability of secondary data collected in a municipal system at the Local Data Bank of the Central Statistical Office for 2009–2018. The analysis showed that the rural communes of eastern Poland are characterized by significant disproportions in terms of financial standing. Rural communes with the best financial condition were characterized by a higher share of own revenues in total revenues, a higher level of income from local taxes and obtained from the share in the tax on natural and legal persons. It seems that the main reason for the relatively small impact of financial conditions on economic and social development is their strong dependence on transfer revenues transferred from the state budget and the amount of current expenditure. The above circumstances stiffen and stabilize the financial economy, making it relatively less susceptible to the influence of other factors. The obtained results may constitute for the local authorities an important source of information on the disproportions occurring between units on setting out potential directions for optimizing the structure of local finances.
Mineral Fertilizer Demand for Optimum Biological Nitrogen Fixation and Yield Potentials of Legumes in Northern Ethiopia
Authors: Mesfin Shimbahri , Gebresamuel Girmay , Haile Mitiku , Zenebe Amanuel , Desta Girma
Published: August 2020

Farmers in Northern Ethiopia integrate legumes in their cropping systems to improve soil fertility. However, biological nitrogen fixation (BNF) potentials of different legumes and their mineral nitrogen (N) and phosphorus (P) demands for optimum BNF and yields are less studied. This study aimed to generate the necessary knowledge to enable development of informed nutrient management recommendations, guide governmental public policy and assist farmer decision making. The experiment was conducted at farmers’ fields with four N levels, three P levels, and three replications. Nodule number and dry biomass per plant were assessed. Nitrogen difference method was used to estimate the amount of fixed N by assuming legume BNF was responsible for differences in plant N and soil mineral N measured between legume treatments and wheat. The result revealed that the highest grain yields of faba bean (2531 kg ha−1), field pea (2493 kg ha−1) and dekeko (1694 kg ha−1) were recorded with the combined application of 20 kg N ha−1 and 20 kg P ha−1. Faba bean, field pea and dekeko also fixed 97, 38 and 49 kg N ha−1, respectively, with the combined application of 20 kg N ha−1 and 20 kg P ha−1; however, lentil fixed 20 kg ha−1 with the combined application of 10 kg N ha−1 and 10 kg P ha−1. The average BNF of legumes in the average of all N and P interaction rates were 67, 23, 32 and 16 kg N ha−1 for faba bean, field pea, dekeko and lentil, respectively. Moreover, faba bean, field pea, dekeko and lentil accumulated a surplus soil N of 37, 21, 26 and 13 kg ha−1, respectively, over the wheat plot. The application of 20 kg N ha−1 and 20 kg P ha−1 levels alone and combined significantly (p < 0.05) increased the nodulation, BNF and yield of legumes; however, 46 kg N ha-1 significantly decreased BNF. This indicated that the combination of 20 kg N ha−1 and 20 kg P ha−1 levels is what mineral fertilizer demands to optimize the BNF and yield of legumes. The results of this study can lead to the development of policy and farmer guidelines, as intensification of the use of legumes supplied with starter N and P fertilizers in Northern Ethiopian cropping systems has the multiple benefits of enhancing inputs of fixed N, improving the soil N status for following crops, and becoming a sustainable option for sustainable soil fertility management practice.
A Review of Balcony Impacts on the Indoor Environmental Quality of Dwellings
Authors: Ribeiro Catarina , Ramos Nuno M. M. , Flores-Colen Inês
Published: August 2020

Balconies are an ancient architectural archetype that are being increasingly considered in multi-family buildings of high-density cities. This paper aims to provide a comprehensive review of the impacts of balcony types on the indoor environmental quality (IEQ) and energy consumption of dwellings. Of the reviewed studies, 69% were published during the last decade, making it evident that awareness of the positive impact of balcony spaces is continuously increasing. The literature review allowed us to identify three balcony spaces according to their morphology and their boundary system: open balcony (OB), glazed balcony (GB), and eliminate balcony (EB). It was concluded that these balcony types produce relevant impacts in four factors that contribute to the indoor environmental quality: thermal comfort, indoor air quality, visual comfort, and acoustic comfort. Practical design recommendations and constraints were provided according to distinct climatic conditions and building technologies. This review also explored the assessment methodologies used for the optimization of the balconies on the design process. The literature highlighted the lack of a comprehensive study about the impact of balconies in mild and Mediterranean climates, as well as the knowledge limitations concerning the balance between the impacts on IEQ factors.
Technopreneurial Intentions among Bulgarian STEM Students: The Role of University
Authors: Yordanova Desislava , Filipe José António , Pacheco Coelho Manuel
Published: August 2020

Entrepreneurship, innovation and technology are essential to the economic development of societies. Universities are increasingly involved in creating an internal favourable environment supporting entrepreneurship and innovation. In our work, we aimed to study the role of university for the development of technopreneurial intentions in a sample of Bulgarian STEM (STEM refers to any subjects that fall under the disciplines of science, technology, engineering or mathematics.) students exhibiting entrepreneurial intentions. The empirical findings of the study are in line with previous empirical evidence about the role of university support for entrepreneurial intentions among students; results also show that students in universities with better research in their scientific field of study are more likely to exhibit technopreneurial intention. Determinants of entrepreneurial intentions identified in the literature such as entrepreneurial role models, perceived support from social networks, willingness to take risks and gender may not be relevant specifically for technopreneurial intentions. The results of the study have important practical implications.