bluuebunny/crossref_metadata_2025 huggingface dataset:
Application of a Physiologically Based Pharmacokinetic Model to Develop a Veterinary Amorphous Enrofloxacin Solid Dispersion
Authors: Zhou Kaixiang , Huo Meixia , Ma Wenjin , Mi Kun , Xu Xiangyue , Algharib Samah Attia , Xie Shuyu , Huang Lingli
Published: April 2021

Zoonotic intestinal pathogens threaten human health and cause huge economic losses in farming. Enrofloxacin (ENR) shows high antibacterial activity against common intestinal bacteria. However, its poor palatability and low aqueous solubility limit the clinical application of ENR. To obtain an ENR oral preparation with good palatability and high solubility, a granule containing an amorphous ENR solid dispersion (ENR-SD) was prepared. Meanwhile, a PBPK model of ENR in pigs was built based on the physiological parameters of pigs and the chemical-specific parameters of ENR to simulate the pharmacokinetics (PK) of ENR-SD granules in the intestinal contents. According to the results of parameter sensitivity analysis (PSA) and the predicted PK parameters at different doses of the model, formulation strategies and potential dose regimens against common intestinal infections were provided. The DSC and XRD results showed that no specific interactions existed between the excipients and ENR during the compatibility tests, and ENR presented as an amorphous form in ENR-SD. Based on the similar PK performance of ENR-SD granules and the commercial ENR soluble powder suggesting continued enhancement of the solubility of ENR, a higher drug concentration in intestinal contents could not be obtained. Therefore, a 1:5 ratio of ENR and stearic acid possessing a saturated aqueous solubility of 1190 ± 7.71 µg/mL was selected. The predictive AUC24h/MIC90 ratios against Campylobacter jejuni, Salmonella, and Escherichia coli were 133, 266 and 8520 (>100), respectively, suggesting that satisfactory efficacy against common intestinal infections would be achieved at a dose of 10 mg/kg b.w. once daily. The PSA results indicated that the intestinal absorption rate constant (Ka) was negatively correlated with the Cmax of ENR in the intestine, suggesting that we could obtain higher intestinal Cmax using P-gp inducers to reduce Ka, thus obtaining a higher Cmax. Our studies suggested that the PBPK model is an excellent tool for formulation and dose design.
Culturable Yeasts as Biofertilizers and Biopesticides for a Sustainable Agriculture: A Comprehensive Review
Authors: Hernández-Fernández María , Cordero-Bueso Gustavo , Ruiz-Muñoz Marina , Cantoral Jesús M.
Published: April 2021

The extensive use of synthetic fertilizers and pesticides has negative consequences in terms of soil microbial biodiversity and environmental contamination. Faced with this growing concern, a proposed alternative agricultural method is the use of microorganisms as biofertilizers. Many works have been focused on bacteria, but the limited literature on yeasts and their potential ability to safely promote plant growth is gaining particular attention in recent years. Thus, the objective of this review is to highlight the application of yeasts as biological agents in different sectors of sustainable agricultural practices through direct or indirect mechanisms of action. Direct mechanisms include the ability of yeasts to provide soluble nutrients to plants, produce organic acids and phytohormones (indole-3-acetic acid). Indirect mechanisms involve the ability for yeasts to act as biocontrol agents through their high antifungal activity and lower insecticidal and herbicidal activity, and as soil bioremediating agents. They also act as protective agents against extreme environmental factors by activating defense mechanisms. It is evident that all the aspects that yeasts offer could be useful in the creation of quality biofertilizers and biopesticides. Hence, extensive research on yeasts could be promising and potentially provide an environmentally friendly solution to the increased crop production that will be required with a growing population.
Green Light Improves Photosystem Stoichiometry in Cucumber Seedlings (Cucumis sativus) Compared to Monochromatic Red Light
Authors: Claypool Nicholas B. , Lieth J. Heinrich
Published: April 2021

It has been shown that monochromatic red and blue light influence photosynthesis and morphology in cucumber. It is less clear how green light impacts photosynthetic performance or morphology, either alone or in concert with other wavelengths. In this study, cucumber (Cucumis sativus) was grown under monochromatic blue, green, and red light, dichromatic blue–green, red–blue, and red–green light, as well as light containing red, green, and blue wavelengths, with or without supplemental far-red light. Photosynthetic data collected under treatment spectra at light-limiting conditions showed that both red and green light enhance photosynthesis. However, photosynthetic data collected with a 90% red, 10% blue, 1000 µmol photons m−2 s−1, saturating light show significantly lower photosynthesis in the green, red, and red–green treatments, indicating a blue light enhancement due to photosystem stoichiometric differences. The red–green and green light treatments show improved photosynthetic capacity relative to red light, indicating partial remediation by green light. Despite a lower quantum efficiency and the lowest ambient photosynthesis levels, the monochromatic blue treatment produced among the tallest, most massive plants with the greatest leaf area and thickest stems.
Phytochemical Characterization and Screening of Antioxidant, Antimicrobial and Antiproliferative Properties of Allium × cornutum Clementi and Two Varieties of Allium cepa L. Peel Extracts
Authors: Fredotović Željana , Puizina Jasna , Nazlić Marija , Maravić Ana , Ljubenkov Ivica , Soldo Barbara , Vuko Elma , Bajić Danica
Published: April 2021

Onions are one of the most widely grown vegetable crops. As production increases, so does the generation of waste from various parts of the onion, raising the need for efficient ecological disposal and use of such waste products. However, onion waste products are a rich source of antioxidants with a range of biological properties, therefore, they could potentially be used in food and pharmaceutical industries. In the present study, we identified the main flavonols and anthocyanins in peel extracts of Allium × cornutum Clement ex Visiani, 1842, and two varieties of Allium cepa L. and tested their antioxidant, antimicrobial and antiproliferative properties. Quercetin 3,4′-diglucolside, quercetin 4′-monoglucoside and quercetin are the most abundant flavonols in all onion extracts detected by high-performance liquid chromatography (HPLC) method. The composition of anthocyanins varied in all extracts. 2,2′-diphenyl-1-picrylhydrazyl (DPPH) and oxygen radical absorbance capacity (ORAC) assays showed that the triploid onion A. × cornutum had the highest antioxidant power. Evaluation of antimicrobial activity by broth microdilution assay also showed that A. × cornutum had higher antimicrobial activity compared to the red and yellow onion varieties. Comparable antiproliferative activity was confirmed for all onion extracts tested on three cancer cell lines: Hela (cervical cancer cell line), HCT116 (human colon cancer cell line) and U2OS (human osteosarcoma cell line). The most abundant onion flavonols (quercetin 3,4′-diglucoside and quercetin 4′-monoglucoside) showed weaker antimicrobial as well as antiproliferative properties compared to the extracts, leading to the conclusion that other phytochemicals besides flavonols contribute to the biological activity of onion peel extracts. The results demonstrate the antioxidant and antimicrobial properties of onion peels, which have promising potential as cancer cell proliferation inhibitors.
Recent 1D and 2D TD–NMR Pulse Sequences for Plant Science
Authors: Monaretto Tatiana , Moraes Tiago Bueno , Colnago Luiz Alberto
Published: April 2021

Time domain nuclear magnetic resonance (TD–NMR) has been widely applied in plant science in the last four decades. Several TD–NMR instruments and methods have been developed for laboratory, green-house, and field studies. This mini-review focuses on the recent TD–NMR pulse sequences applied in plant science. One of the sequences measures the transverse relaxation time (T2) with minimal sample heating, using a lower refocusing flip angle and consequently lower specific absorption rate than that of conventional CPMG. Other sequences are based on a continuous wave free precession (CWFP) regime used to enhance the signal-to-noise ratio, to measure longitudinal (T1) and transverse relaxation time in a single shot experiment, and as alternative 2D pulse sequences to obtain T1–T2 and diffusion-T1 correlation maps. This review also presents some applications of these sequences in plant science.
Preparation of Molded Fiber Products from Hydroxylated Lignin Compounded with Lewis Acid-Modified Fibers Its Analysis
Authors: Liu Tianhao , Wang Ying , Zhou Jin , Li Mengyang , Yue Jinquan
Published: April 2021

In this study, molded fiber products (MFPs) were prepared from lignin compounded with Lewis acid-modified fibers using enzymatic hydrolysis lignin (EHL) as a bio-phenol. The fibers were modified and compounded entirely through hot-pressing. To improve the reactivity of enzymatic lignin, hydroxylated enzymatic hydrolysis lignin (HEHL) was prepared by hydroxylation modification of purified EHL with hydrogen peroxide (H2O2) and ferrous hydroxide (Fe(OH)3). HEHL was mixed uniformly with Lewis acid-modified fibers on a pressure machine and modified during the molding process. The purpose of Lewis acid degradation of hemicellulose-converted furfural with HEHL was to generate a resin structure to improve the mechanical properties of a MFPs. The microstructure of the MFP was shown to be generated by resin structure, and it was demonstrated that HEHL was compounded on Lewis acid-modified fibers during the molding process. The thermal stability of the MFP with composite HEHL did not change significantly owing to the addition of lignin and had higher tensile strength (46.28 MPa) and flexural strength (65.26 MPa) compared to uncompounded and modified MFP. The results of this study are expected to promote the application of high lignin content fibers in molded fibers.
Influence of Carbon Nanotube-Pretreatment on the Properties of Polydimethylsiloxane/Carbon Nanotube-Nanocomposites
Authors: Diekmann Astrid , Omelan Marvin C. V. , Giese Ulrich
Published: April 2021

Incorporating nanofillers into elastomers leads to composites with an enormous potential regarding their properties. Unfortunately, nanofillers tend to form agglomerates inhibiting adequate filler dispersion. Therefore, different carbon nanotube (CNT) pretreatment methods were analyzed in this study to enhance the filler dispersion in polydimethylsiloxane (PDMS)/CNT-composites. By pre-dispersing CNTs in solvents an increase in electrical conductivity could be observed within the sequence of tetrahydrofuran (THF) > acetone > chloroform. Optimization of the pre-dispersion step results in an AC conductivity of 3.2 × 10−4 S/cm at 1 Hz and 0.5 wt.% of CNTs and the electrical percolation threshold is decreased to 0.1 wt.% of CNTs. Optimum parameters imply the use of an ultrasonic finger for 60 min in THF. However, solvent residues cause a softening effect deteriorating the mechanical performance of these composites. Concerning the pretreatment of CNTs by physical functionalization, the use of surfactants (sodium dodecylbenzenesulfonate (SDBS) and polyoxyethylene lauryl ether (“Brij35”)) leads to no improvement, neither in electrical conductivity nor in mechanical properties. Chemical functionalization enhances the compatibility of PDMS and CNT but damages the carbon nanotubes due to the oxidation process so that the improvement in conductivity and reinforcement is superimposed by the CNT damage even for mild oxidation conditions.
Optical Encryption Based on Computer Generated Holograms in Photopolymer
Authors: Wu Taihui , Ma Jianshe , Wang Chengchen , Wang Haibei , Cao Liangcai , Su Ping
Published: April 2021

An optical encryption method based on computer generated holograms printing of photopolymer is presented. Fraunhofer diffraction is performed based on the Gerchberg-Saxton algorithm, and a hologram of the Advanced Encryption Standard encrypted Quick Response code is generated to record the ciphertext. The holograms of the key and the three-dimensional image are generated by the angular spectrum diffraction algorithm. The experimental results show that large-size encrypted Quick Response (QR) code and miniature keys can be printed in photopolymers, which has good application prospects in optical encryption. This method has the advantages of high-density storage, high speed, large fault tolerance, and anti-peeping.
A Composite Nanosystem as a Potential Tool for the Local Treatment of Glioblastoma: Chitosan-Coated Solid Lipid Nanoparticles Embedded in Electrospun Nanofibers
Authors: Vigani Barbara , Valentino Caterina , Sandri Giuseppina , Listro Roberta , Fagiani Francesca , Collina Simona , Lanni Cristina , Bonferoni Maria Cristina , Caramella Carla M. , Rossi Silvia , Ferrari Franca
Published: April 2021

Glioblastoma multiforme (GBM) is one of the most prevalent and aggressive brain tumors for which there is currently no cure. A novel composite nanosystem (CN), consisting of chitosan-coated Solid Lipid Nanoparticles (c-SLN) embedded in O-carboxymethyl chitosan (O-CMCS)-containing nanofibers (NFs), was proposed as a potential tool for the local delivery of lipophilic anti-proliferative drugs. Coacervation was selected as a solvent-free method for the preparation of stearic acid (SA) and behenic acid (BA)-based SLN (SA-SLN and BA-SLN respectively). BA-SLN, containing 0.75% w/w BA sodium salt and 3% w/w poly(vinyl alcohol) (PVA), were selected for the prosecution of the work since they are characterized by the lowest size functional to their subsequent coating and incorporation in nanofibers. BA-SLN were coated with chitosan (CS) by means of a two-step coating method based on the physical absorption of positively charged CS chains on the SLN negative surface. Nile Red (NR), chosen as the hydrophobic model dye, was dissolved in a micellar solution of BA sodium salt and then added with a coacervating solution until pH ≅ 2.5 was reached. Immunocytochemistry analyses highlighted that CS-coated BA-SLN (c-BA-SLN) exhibited a higher accumulation in human glioblastoma cells (U-373) after 6 h than CS-free BA-SLN. Finally, the c-BA-SLN dispersion was blended with a solution consisting of freely soluble polymers (O-CMCS, poly(ethylene oxide) and poloxamer) and then electrospun to obtain NFs with a mean diameter equal to 850 nm. After the NFs dissolution in an aqueous media, c-BA-SLN maintained their physicochemical properties and zeta potential.
Strontium Aluminate-Based Long Afterglow PP Composites: Phosphorescence, Thermal, and Mechanical Characteristics
Authors: Poulose Anesh Manjaly , Anis Arfat , Shaikh Hamid , Alhamidi Abdullah , Siva Kumar Nadavala , Elnour Ahmed Yagoub , Al-Zahrani Saeed M.
Published: April 2021

A tremendous potential has been observed in the designing of long afterglow materials for sensing, bioimaging, and encryption applications. In this study, two different strontium aluminate-based luminescent materials; SrAl2O4: Eu, Dy (S1), and Sr4Al14O25: Eu, Dy (S2) were melt-mixed with polypropylene (PP) matrix, and the phosphorescence properties were evaluated. After excitation at 320 nm, the PP/S1 composite exhibited a green emission and the PP/S2 generated a blue emission at 520 nm and 495 nm, respectively. The emission spectra intensity increased by increasing the content of these luminescent fillers. The attenuated total reflection-Fourier transform infrared (ATR-FTIR) experiments show that no chemical reaction occurred during the melt-mixing process. The differential scanning calorimetry (DSC) results revealed that the total crystallinity of the composites reduced by increasing the amount of the fillers; however, no changes in the temperature of melting (Tm) and crystallization (Tc) of PP were observed. Both fillers improved the impact strength of the composites, but the tensile strength (TS) and modulus (TM) decreased. Poly (ethylene glycol) dimethyl ether (P) plasticizer was used to improve the filler-matrix interaction and its dispersion; nevertheless, it adversely affected the intensity of the luminescence emissions.
Real-Time Detection of Daytime and Night-Time Fire Hotspots from Geostationary Satellites
Authors: Engel Chermelle B. , Jones Simon D. , Reinke Karin J.
Published: April 2021

This paper introduces an enhanced version of the Biogeographical Region and Individual Geostationary HHMMSS Threshold (BRIGHT) algorithm. The algorithm runs in real-time and operates over 24 h to include both daytime and night-time detections. The algorithm was executed and tested on 12 months of Himawari-8 data from 1 April 2019 to 31 March 2020, for every valid 10-min observation. The resulting hotspots were compared to those from the Visible Infrared Imaging Radiometer Suite (VIIRS) and the Moderate Resolution Imaging Spectroradiometer (MODIS). The modified BRIGHT hotspots matched with fire detections in VIIRS 96% and MODIS 95% of the time. The number of VIIRS and MODIS hotspots with matches in the coincident modified BRIGHT dataset was lower (at 33% and 46%, respectively). This paper demonstrates a clear link between the number of VIIRS and MODIS hotspots with matches and the minimum fire radiative power considered.
A Two-Stage Data Association Approach for 3D Multi-Object Tracking
Authors: Dao Minh-Quan , Frémont Vincent
Published: April 2021

Multi-Object Tracking (MOT) is an integral part of any autonomous driving pipelines because it produces trajectories of other moving objects in the scene and predicts their future motion. Thanks to the recent advances in 3D object detection enabled by deep learning, track-by-detection has become the dominant paradigm in 3D MOT. In this paradigm, a MOT system is essentially made of an object detector and a data association algorithm which establishes track-to-detection correspondence. While 3D object detection has been actively researched, association algorithms for 3D MOT has settled at bipartite matching formulated as a Linear Assignment Problem (LAP) and solved by the Hungarian algorithm. In this paper, we adapt a two-stage data association method which was successfully applied to image-based tracking to the 3D setting, thus providing an alternative for data association for 3D MOT. Our method outperforms the baseline using one-stage bipartite matching for data association by achieving 0.587 Average Multi-Object Tracking Accuracy (AMOTA) in NuScenes validation set and 0.365 AMOTA (at level 2) in Waymo test set.
Electromyographic Assessment of the Efficacy of Deep Dry Needling versus the Ischemic Compression Technique in Gastrocnemius of Medium-Distance Triathletes
Authors: Benito-de-Pedro María , Calvo-Lobo César , López-López Daniel , Benito-de-Pedro Ana Isabel , Romero-Morales Carlos , San-Antolín Marta , Vicente-Campos Davinia , Rodríguez-Sanz David
Published: April 2021

Several studies have shown that gastrocnemius is frequently injured in triathletes. The causes of these injuries are similar to those that cause the appearance of the myofascial pain syndrome (MPS). The ischemic compression technique (ICT) and deep dry needling (DDN) are considered two of the main MPS treatment methods in latent myofascial trigger points (MTrPs). In this study superficial electromyographic (EMG) activity in lateral and medial gastrocnemius of triathletes with latent MTrPs was measured before and immediately after either DDN or ICT treatment. Taking into account superficial EMG activity of lateral and medial gastrocnemius, the immediate effectiveness in latent MTrPs of both DDN and ICT was compared. A total of 34 triathletes was randomly divided in two groups. The first and second groups (n = 17 in each group) underwent only one session of DDN and ICT, respectively. EMG measurement of gastrocnemius was assessed before and immediately after treatment. Statistically significant differences (p = 0.037) were shown for a reduction of superficial EMG measurements differences (%) of the experimental group (DDN) with respect to the intervention group (ICT) at a speed of 1 m/s immediately after both interventions, although not at speeds of 1.5 m/s or 2.5 m/s. A statistically significant linear regression prediction model was shown for EMG outcome measurement differences at V1 (speed of 1 m/s) which was only predicted for the treatment group (R2 = 0.129; β = 8.054; F = 4.734; p = 0.037) showing a reduction of this difference under DDN treatment. DDN administration requires experience and excellent anatomical knowledge. According to our findings immediately after treatment of latent MTrPs, DDN could be advisable for triathletes who train at a speed lower than 1 m/s, while ICT could be a more advisable technique than DDN for training or competitions at speeds greater than 1.5 m/s.
Sensitivity of Field-Effect Transistor-Based Terahertz Detectors
Authors: Javadi Elham , But Dmytro B. , Ikamas Kęstutis , Zdanevičius Justinas , Knap Wojciech , Lisauskas Alvydas
Published: April 2021

This paper presents an overview of the different methods used for sensitivity (i.e., responsivity and noise equivalent power) determination of state-of-the-art field-effect transistor-based THz detectors/sensors. We point out that the reported result may depend very much on the method used to determine the effective area of the sensor, often leading to discrepancies of up to orders of magnitude. The challenges that arise when selecting a proper method for characterisation are demonstrated using the example of a 2×7 detector array. This array utilises field-effect transistors and monolithically integrated patch antennas at 620 GHz. The directivities of the individual antennas were simulated and determined from the measured angle dependence of the rectified voltage, as a function of tilting in the E- and H-planes. Furthermore, this study shows that the experimentally determined directivity and simulations imply that the part of radiation might still propagate in the substrate, resulting in modification of the sensor effective area. Our work summarises the methods for determining sensitivity which are paving the way towards the unified scientific metrology of FET-based THz sensors, which is important for both researchers competing for records, potential users, and system designers.
An Algorithm to Minimize Energy Consumption and Elapsed Time for IoT Workloads in a Hybrid Architecture
Authors: dos Anjos Julio C. S. , Gross João L. G. , Matteussi Kassiano J. , González Gabriel V. , Leithardt Valderi R. Q. , Geyer Claudio F. R.
Published: April 2021

Advances in communication technologies have made the interaction of small devices, such as smartphones, wearables, and sensors, scattered on the Internet, bringing a whole new set of complex applications with ever greater task processing needs. These Internet of things (IoT) devices run on batteries with strict energy restrictions. They tend to offload task processing to remote servers, usually to cloud computing (CC) in datacenters geographically located away from the IoT device. In such a context, this work proposes a dynamic cost model to minimize energy consumption and task processing time for IoT scenarios in mobile edge computing environments. Our approach allows for a detailed cost model, with an algorithm called TEMS that considers energy, time consumed during processing, the cost of data transmission, and energy in idle devices. The task scheduling chooses among cloud or mobile edge computing (MEC) server or local IoT devices to achieve better execution time with lower cost. The simulated environment evaluation saved up to 51.6% energy consumption and improved task completion time up to 86.6%.
Character Recognition of Components Mounted on Printed Circuit Board Using Deep Learning
Authors: Gang Sumyung , Fabrice Ndayishimiye , Chung Daewon , Lee Joonjae
Published: April 2021

As the size of components mounted on printed circuit boards (PCBs) decreases, defect detection becomes more important. The first step in an inspection involves recognizing and inspecting characters printed on parts attached to the PCB. In addition, since industrial fields that produce PCBs can change very rapidly, the style of the collected data may vary between collection sites and collection periods. Therefore, flexible learning data that can respond to all fields and time periods are needed. In this paper, large amounts of character data on PCB components were obtained and analyzed in depth. In addition, we proposed a method of recognizing characters by constructing a dataset that was robust with various fonts and environmental changes using a large amount of data. Moreover, a coreset capable of evaluating an effective deep learning model and a base set using n-pick sampling capable of responding to a continuously increasing dataset were proposed. Existing original data and the EfficientNet B0 model showed an accuracy of 97.741%. However, the accuracy of our proposed model was increased to 98.274% for the coreset of 8000 images per class. In particular, the accuracy was 98.921% for the base set with only 1900 images per class.
Land-Use Change Impacts from Sustainable Hydropower Production in EU28 Region: An Empirical Analysis
Authors: Alsaleh Mohd , Abdulwakil Muhammad Mansur , Abdul-Rahim Abdul Samad
Published: April 2021

Under the current European Union (EU) constitution approved in May 2018, EU countries ought to guarantee that estimated greenhouse-gas releases from land use, land-use change, or forestry are entirely compensated by an equivalent accounted removal of carbon dioxide (CO2) from the air during the period between 2021 and 2030. This study investigates the effect of sustainable hydropower production on land-use change in the European Union (EU28) region countries during 1990–2018, using the fully modified ordinary least squares (FMOLS). The results revealed that land-use change incline with an increase in hydropower energy production. In addition, economic growth, carbon dioxide emissions, and population density are found to be increasing land-use changes, while institutional quality is found to be decreasing land-use change significantly. The finding implies that land-use change in EU28 region countries can be significantly increased by mounting the amount of hydropower energy production to achieve Energy Union aims by 2030. This will finally be spread to combat climate change and environmental pollution. The findings are considered robust as they were checked with DOLS and pooled OLS. The research suggests that the EU28 countries pay attention to the share of hydropower in their renewable energy combination to minimize carbon releases. Politicians and investors in the EU28 region ought to invest further in the efficiency and sustainability of hydropower generation to increase its production and accessibility without further degradation of forest and agricultural conditions. The authorities of the EU28 region should emphasize on efficiency and sustainability of hydropower energy with land-use management to achieve the international commitments for climate, biodiversity, and sustainable development, reduce dependence on fossil fuel, and energy insecurity.
Forecasting Rainfed Agricultural Production in Arid and Semi-Arid Lands Using Learning Machine Methods: A Case Study
Authors: Rezapour Shahram , Jooyandeh Erfan , Ramezanzade Mohsen , Mostafaeipour Ali , Jahangiri Mehdi , Issakhov Alibek , Chowdhury Shahariar , Techato Kuaanan
Published: April 2021

With the rising demand for food products and the direct impact of climate change on food production in many parts of the world, recent years have seen growing interest in the subject of food security and the role of rainfed farming in this area. Machine learning methods can be used to predict crop yield based on a combination of remote sensing data and data collected by ground weather stations. This paper argues that forecasting drylands farming yield can be reliable for management purpose under uncertain conditions using machine learning methods and remote sensing data and determines which indicators are most important in predicting the yield of chickpea. In this study, the yield of rainfed chickpea farms in 11 top chickpea producing counties in Kermanshah province, Iran, was predicted using three machine learning methods, namely support vector regression (SVR), random forest (RF), and K-nearest neighbors (KNN). To improve prediction accuracy, for each county, remote sensing data were overlaid by the satellite images of rainfed farms with a suitable slope and altitude for rainfed farming. An integrated database was created by combining weather data, remote sensing data, and chickpea yield statistics. The methods were evaluated using the leave-one-out cross-validation (LOOCV) technique and compared in terms of multiple measures. Given the sensitivity of rainfed chickpea yield to the time of data, the predictions were made in two scenarios: (1) using the averages of the data of all growing months, and (2) using the data of a combination of months. The results showed that RF provides more accurate yield predictions than other methods. The predictions of this method were 7–8% different from the statistics reported by the Statistical Center and the Ministry of Agriculture of Iran. It was found that for pre-harvest prediction of rainfed chickpea yield, using the data of the March–April period (the averages of two months) offers the best result in terms of the correlation coefficient for the relationship between the yield and the predictor indices.
The Ideal Debt Ratio of an Agricultural Enterprise
Authors: Kučera Jiří , Vochozka Marek , Rowland Zuzana
Published: April 2021

The objective of the contribution is to propose a new methodology for determining the optimal credit absorption capacity of an enterprise while maintaining the positive function of financial leverage, i.e., the maximum possible loan that would continuously bring benefit to the enterprise. The proposed methodology determines the credit absorption capacity of an enterprise according to EVA Equity and EVA Entity. Based on a theoretical analysis of both indicators, the possibility of applying the proposed methodology for this purpose was proved. To verify the theoretical assumptions, the optimal credit absorption capacity of enterprises operating in the agricultural sector of the CR was determined. The data used for the purposes of the contribution were obtained from the Albertina database for the years 2012–2018. The credit absorption capacity of the monitored enterprises ranged from CZK 6.88 million to CZK 9.6 million. The article also determines the optimal ratio of equity to debt capital.
Capability Assessment toward Sustainable Development of Business Incubators: Framework and Experience Sharing
Authors: Gerdsri Nathasit , Iewwongcharoen Boonkiart , Rajchamaha Kittichai , Manotungvorapun Nisit , Pongthanaisawan Jakapong , Witthayaweerasak Watcharin
Published: April 2021

Business incubators have been widely developed to advise, support, promote, and provide a nurturing environment for new business start-ups and entrepreneurs. The development of a framework for capability assessment allows the management of each incubator to understand its strengths and room for further improvement. Moreover, assessment results across a community, such as a nation or state, can provide insights into resource allocation and various management policies so that policymakers can support the development of business incubators under their supervision. This article describes the development of a capability assessment framework for business incubators (BIs) in Thailand. A case study demonstrating how the capability assessment is analyzed is also presented in the article.
A C-Vine Copula-Based Quantile Regression Method for Streamflow Forecasting in Xiangxi River Basin, China
Authors: Li Huawei , Huang Guohe , Li Yongping , Sun Jie , Gao Pangpang
Published: April 2021

In this study, a C-vine copula-based quantile regression (CVQR) model is proposed for forecasting monthly streamflow. The CVQR model integrates techniques for vine copulas and quantile regression into a framework that can effectively establish relationships between the multidimensional response-independent variables as well as capture the upper tail or asymmetric dependence (i.e., upper extreme values). The CVQR model is applied to the Xiangxi River basin that is located in the Three Gorges Reservoir area in China for monthly streamflow forecasting. Multiple linear regression (MLR) and artificial neural network (ANN) are also compared to illustrate the applicability of CVQR. The results show that the CVQR model performs best in the calibration period for monthly streamflow prediction. The results also indicate that MLR has the worst effects in extreme quantile (flood events) and confidence interval predictions. Moreover, the performance of ANN tends to be overestimated in the process of peak prediction. Notably, CVQR is the most effective at capturing upper tail dependences among the hydrometeorological variables (i.e., floods). These findings are very helpful to decision-makers in hydrological process identification and water resource management practices.
Retrieval and Evaluation of Chlorophyll-A Spatiotemporal Variability Using GF-1 Imagery: Case Study of Qinzhou Bay, China
Authors: Na Ze-Lin , Yao Huan-Mei , Chen Hua-Quan , Wei Yi-Ming , Wen Ke , Huang Yi , Liao Peng-Ren
Published: April 2021

Chlorophyll-a (Chl-a) concentration is a measure of phytoplankton biomass, and has been used to identify ‘red tide’ events. However, nearshore waters are optically complex, making the accurate determination of the chlorophyll-a concentration challenging. Therefore, in this study, a typical area affected by the Phaeocystis ‘red tide’ bloom, Qinzhou Bay, was selected as the study area. Based on the Gaofen-1 remote sensing satellite image and water quality monitoring data, the sensitive bands and band combinations of the nearshore Chl-a concentration of Qinzhou Bay were screened, and a Qinzhou Bay Chl-a retrieval model was constructed through stepwise regression analysis. The main conclusions of this work are as follows: (1) The Chl-a concentration retrieval regression model based on 1/B4 (near-infrared band (NIR)) has the best accuracy (R2 = 0.67, root-mean-square-error = 0.70 μg/L, and mean absolute percentage error = 0.23) for the remote sensing of Chl-a concentration in Qinzhou Bay. (2) The spatiotemporal distribution of Chl-a in Qinzhou Bay is varied, with lower concentrations (0.50 μg/L) observed near the shore and higher concentrations (6.70 μg/L) observed offshore, with a gradual decreasing trend over time (−0.8).
Neighbourhood Modelling for Urban Sustainability Assessment
Authors: Orozco-Messana Javier , Iborra-Lucas Milagro , Calabuig-Moreno Raimon
Published: April 2021

Climate change is becoming a dominant concern for advanced countries. The Paris Agreement sets out a global framework whose implementation relates to all human activities and is commonly guided by the United Nations Sustainable Development Goals (UN SDGs), which set the scene for sustainable development performance configuring all climate action related policies. Fast control of CO2 emissions necessarily involves cities since they are responsible for 70 percent of greenhouse gas emissions. SDG 11 (Sustainable cities and communities) is clearly involved in the deployment of SDG 13 (Climate Action). European Sustainability policies are financially guided by the European Green Deal for a climate neutral urban environment. In turn, a common framework for urban policy impact assessment must be based on architectural design tools, such as building certification, and common data repositories for standard digital building models. Many Neighbourhood Sustainability Assessment (NSA) tools have been developed but the growing availability of open data repositories for cities, together with big-data sources (provided through Internet of Things repositories), allow accurate neighbourhood simulations, or in other words, digital twins of neighbourhoods. These digital twins are excellent tools for policy impact assessment. After a careful analysis of current scientific literature, this paper provides a generic approach for a simple neighbourhood model developed from building physical parameters which meets relevant assessment requirements, while simultaneously being updated (and tested) against real open data repositories, and how this assessment is related to building certification tools. The proposal is validated by real data on energy consumption and on its application to the Benicalap neighbourhood in Valencia (Spain).
Nationwide Distribution of Dengue Virus Type 3 (DENV-3) Genotype I and Emergence of DENV-3 Genotype III during the 2019 Outbreak in Bangladesh
Authors: Titir Snigdha Rahman , Paul Shyamal Kumar , Ahmed Salma , Haque Nazia , Nasreen Syeda Anjuman , Hossain Khondoker Shoaib , Ahmad Fahim Uddin , Nila Sultana Shabnam , Khanam Jobyda , Nowsher Neaz , Al Amin Abu Mohammod Mayeenuddin , Khan Amdad Ullah , Aung Meiji Soe , Kobayashi Nobumichi
Published: April 2021

Bangladesh is an endemic region of dengue fever and experienced an unprecedented large outbreak with more than 100,000 confirmed cases in 2019. To understand the prevalence of dengue antibody in patients and molecular epidemiological characteristics of dengue virus (DENV) in this outbreak, a total of 179 blood samples were collected from patients in 10 districts (seven divisions) covering nearly the whole country from August to December 2019. DENV NS-1 was detected in 162 samples, among which DENV-specific IgM was positive in 119 samples (73.5%), including 60.5% samples also positive for DENV-specific IgG. Sequencing of the partial C-prM gene and its phylogenetic analysis revealed predominance of DENV type 3 genotype I, accounting for 93% of samples examined. DENV-3 genotype III was identified in two samples from separate districts, and only one DENV-2 cosmopolitan genotype was found in the capital city, Dhaka. These findings suggest the predominance of DENV-3 genotype I and occurrence of DENV-3 genotype III, associated with increased incidence of recent secondary infection in Bangladesh in 2019.
AGB Winds with Gas-Dust Drift in Stellar Evolution Codes
Authors: Mattsson Lars , Sandin Christer
Published: April 2021

A significant fraction of new metals produced in stars enter the interstellar medium in the form of dust grains. Including dust and wind formation in stellar evolution models of late-stage low- and intermediate-mass stars provides a way to quantify their contribution to the cosmic dust component. In doing so, a correct physical description of dust formation is of course required, but also a reliable prescription for the mass-loss rate. Here, we present an improved model of dust-driven winds to be used in stellar evolution codes and insights from recent detailed numerical simulations of carbon-star winds including drift (decoupling of dust and gas). We also discuss future directions for further improvement.
Variational Principles in Teleparallel Gravity Theories
Authors: Hohmann Manuel
Published: April 2021

We study the variational principle and derivation of the field equations for different classes of teleparallel gravity theories, using both their metric-affine and covariant tetrad formulations. These theories have in common that, in addition to the tetrad or metric, they employ a flat connection as additional field variable, but dthey iffer by the presence of absence of torsion and nonmetricity for this independent connection. Besides the different underlying geometric formulation using a tetrad or metric as fundamental field variable, one has different choices to introduce the conditions of vanishing curvature, torsion, and nonmetricity, either by imposing them a priori and correspondingly restricting the variation of the action when the field equations are derived, or by using Lagrange multipliers. Special care must be taken, since these conditions form non-holonomic constraints. Here, we explicitly show that all of the aforementioned approaches are equivalent, and that the same set of field equations is obtained, independently of the choice of the geometric formulation and variation procedure. We further discuss the consequences arising from the diffeomorphism invariance of the gravitational action, and show how they establish relations between the gravitational field equations.
Ar baigėsi posocializmas Lietuvoje? Antropologija ir posocializmo transformacijų etnografija
Authors: Šliavaitė Kristina
Published: April 2021

Has Post-Socialism Ended in Lithuania? The Anthropology and Ethnography of Post-Socialist Transformations The main aim of the paper is to overview ethnographic research on post-socialist transformations in Lithuania by contextualising it within the broader framework of the field of anthropology of post-socialism. The author refers to numerous discussions in the field on the validity of the use of the term post-socialism long after the collapse of the Soviet system (Sampson 1999; Humphrey 2002; Műller 2019, etc), and discusses whether and how selected ethnographies on social cultural transformations in Lithuania after the 1990s and later use the term postsocialism, and how the period is defined conceptually and chronologically. The first part of the paper introduces discussions in anthropology on challenges in defining the post-socialist region and the chronology of post-socialism (Humphrey 2002; Buyandelgeriyn 2008; Frederiksen, Knudsen 2015; Műller 2019; Нильсен 2004, etc), as well as reflections on issues of the representation and unequal relations between the West and the East in studies of post-socialist European countries (Thelen 2011; Buchowski 2012; Cervinkova 2012; Klumbytė, Sharafutdinova 2013b; Frederiksen, Knudsen 2015, etc). These critical studies indicate that ethnographies of socialist and post-socialist East Central Europe constructed it as the ‘other’, different to the western part of the region (Thelen 2011; Buchowski 2012; Cervinkova 2012; Klumbytė, Sharafutdinova 2013b; Frederiksen, Knudsen 2015; Műller 2019; etc), and that the term post-socialist/post-socialism refers to these unequal relations between the West and the East (Cervinkova 2012; Frederiksen, Knudsen 2015; Műller 2019; etc). However, disregarding certain conceptual challenges, it is agreed that the ethnographies of social cultural transformations in post-socialist European countries are unique and important, due to their methodological approach (long-term fieldwork), and focus on people’s everyday lives and the emphasis on the interrelations of cultural, social and economic processes (Burawoy, Verdery 1999; Hann 2002; Hőrschelmann, Stenning 2008, etc).
Liderazgo pedagógico y el desempeño docente: la imagen de instituciones educativas privadas
Authors: Vásquez Villanueva Salomón , Vásquez Campos Salomón Axel , Vásquez Villanueva Lizardo , Carranza Quevedo Michel Francisco , Vásquez-Villanueva Carlos Alberto , Terry-Ponte Otto Franklin
Published: April 2021

La investigación fue diseñada para lograr el objetivo: determinar la relación entre el liderazgo pedagógico y el desempeño docente, realizada en la Asociación Educativa Adventista Nor Oriental, del Perú, en 75 participantes, quienes contestaron los dos instrumentos, para medir las dos variables, en un diseño descriptivo y correlacional, con enfoque cuantitativo. El análisis estadístico de correlación de Rho Spearman presenta el resultado de 0,543 y un p valor igual a 0.000 (p valor < 0,05); en conclusión, el liderazgo pedagógico se relaciona significativamente con el desempeño docente; dicho de otro modo, la relación entre las variables estudiadas es directa; es decir, a mejor liderazgo pedagógico, mejor será el desempeño docente.
Modelo de gestión universitaria complejo
Authors: Álvarez Sierra Yamilet
Published: April 2021

El artículo es resultado de una investigación sobre la ineficiencia en la gestión institucional del sistema universitario boliviano. Se presenta un análisis del proceso de gestión, a partir de la sistematización de fundamentos epistemológicos que permitieron la elaboración de un modelo propio de gestión universitaria. El estudio trata los antecedentes de los procesos de Administración, Gestión, Organización académica y económica; y se precisan sus dimensiones, variables e indicadores. Los métodos de investigación desarrollados son: dialéctico - complejo, a través de la Teoría de los Procesos Conscientes del Dr. Cs. Carlos M. Álvarez de Zayas. La investigación es actual y pertinente, y responde a los desafíos de la Gestión Universitaria; propone un modelo de gestión, orientado a alcanzar la efectividad en dichas Instituciones, de acuerdo con la realidad de la sociedad boliviana y la necesidad de formar profesionales competentes, ante la exigencia de integración y globalización.
Síntese e caracterização de polímeros de coordenação envolvendo metais da primeira série de transição e ligantes N-e O-doadores
Authors:   , Silva Junior Carlos Magno Dias da
Published: April 2021

Este trabalho descreve a síntese e caracterização de quatro polímeros de coordenação, [Cu4(fum)(μ-OH)5].(H2O)2,5n(CMD01), [Cu2(glu)4(HMT)2]n(CMD02),[Co(aze)3(HMT)(H-2O)2]n(CMD03)e[Cu(H2O)2(μ-fum)(fum)2].H2On(CMD04)contendo ligantes dicarboxílicos classificados como ligantes O-doadores e dois deles contendo também ligantes N-doadores junto a centros metálicos de Cu2+e Co3+, na tentativa de obter redes de coordenação com ligantes mistos. Os ligantes O-doadores utilizados foram, ácido azeláico (AcAz), ácido fumárico (AcFu) e ácido glutárico (AcGl)e oN-doador utilizado foi a hexametilenotetramina (HMT).Todos os compostos obtidos são inéditos, sendo CMD01e CMD04contendo apenas ligantes carboxílicos e CMD02e CMD03O-e N-doadores. Dentre as técnicas disponíveis,nas quais alguns compostos foram caracterizados estão a análise elementar CHN, análise térmica (TG), espectroscopia vibracional na região do infravermelho (IV), difração de raios X por policristal (DRXP) e monocristal (DRXM).Os polímeros obtidos não possuem relação estrutural entre si, não sendo possível estabelecer uma relação comparativa entre eles. Os compostos CMD01, CMD02e CMD03se expandem tridimensionalmente através de seus ligantes dicarboxílicos e, no caso dos dois últimos, também com os nitrogenados. Já o CMD04é um polímero de coordenação 1D através de seus ligantes dicarboxílicos com arranjo supramolecular tridimensional regido pelas ligações de hidrogênio do tipo OH···O. Outras ligações de hidrogênio convencionais e não-convencionais estão presentes nos demais compostos.Foi feita a análise topológica dos compostos, mas somente CMD02e CMD03obtiveram uma rede topológica simplificada, sendo elas do tipo pcue sqc, respectivamente. As demais ainda estão em estudo devido à complexidade de suas redes