bluuebunny/crossref_metadata_2025 huggingface dataset:
Effectiveness of Rice Germ Supplementation on Body Composition, Metabolic Parameters, Satiating Capacity, and Amino Acid Profiles in Obese Postmenopausal Women: A Randomized, Controlled Clinical Pilot Trial
Authors: Rondanelli Mariangela , Peroni Gabriella , Giacosa Attilio , Fazia Teresa , Bernardinelli Luisa , Naso Maurizio , Faliva Milena Anna , Tartara Alice , Gasparri Clara , Perna Simone
Published: January 2021

Rice germ (RG) may be a safe and effective dietary supplement for obesity in menopause, considering its high protein content and considerable amounts of essential amino acids, good fatty acids, and fiber. This pilot randomized, blinded, parallel-group, placebo-controlled pilot trial investigated the effectiveness of 4-weeks RG supplementation (25 g twice a day) on body composition, as primary outcome, measured by Dual Energy X-Ray Absorptiometry (DXA), and metabolic parameters, as secondary outcomes, like amino acid profiles and satiating capacity, in obese postmenopausal women following a tailored hypocaloric diet (25–30% less than daily energy requirements). Twenty-seven women were randomly assigned to the supplemented group (14) or placebo group (13). There was a significant interaction between time and group for body mass index (BMI) (p < 0.0001), waist (p = 0.002) and hip circumferences (p = 0.01), total protein (0.008), albumin (0.005), Homeostasis Model Assessment index score (p = 0.04), glycine (p = 0.002), glutamine (p = 0.004), and histidine (p = 0.007). Haber’s means over time showed a clearly greater feeling of satiety for the supplemented compared to the placebo group. These findings indicate that RG supplementation in addition to a tailored diet counterbalanced the metabolic changes typical of menopause, with improvements in BMI, body composition, insulin resistance, amino acid profiles, and satiety.
Do Chefs Value Health in Their Olive Oil Purchasing Decisions?
Authors: Gutierrez-Salcedo María , Parras-Rosa Manuel , Torres-Ruiz Francisco José , Vega-Zamora Manuela
Published: January 2021

Amidst the public’s growing preoccupation with healthy eating, both inside and outside the home; an increase in people eating out; and the importance that olive oil has acquired in the markets due to its health benefits, the aim of this study is to find out whether health is also a relevant criterion for chefs in their olive oil purchase decisions. To this end, a survey was conducted of 400 chefs in Spain belonging to the international chefs’ association Euro-Toques. The results show that only 2% of the sample consider health to be a relevant criterion in the purchase of olive oils and that the attribute of “health” is not used by restaurants as an element of differentiation by which to position themselves in the market. These results lead us to conclude that the consumer demand for healthy foods (in this case, olive oils) is not being met by the restaurant sector. Moreover, this raises the question as to whether chefs actually make good opinion leaders, with all that this social role implies.
Human Milk Oligosaccharide Concentrations and Infant Intakes Are Associated with Maternal Overweight and Obesity and Predict Infant Growth
Authors: Saben Jessica L. , Sims Clark R. , Abraham Ann , Bode Lars , Andres Aline
Published: January 2021

Human milk oligosaccharides (HMOs) are bioactive molecules playing a critical role in infant health. We aimed to quantify the composition of HMOs of women with normal weight (18.5–24.9 kg/m2), overweight (25.0–29.9 kg/m2), or obesity (30.0–60.0 kg/m2) and determine the effect of HMO intake on infant growth. Human milk (HM) samples collected at 2 months (2 M; n = 194) postpartum were analyzed for HMO concentrations via high-performance liquid chromatography. Infant HM intake, anthropometrics and body composition were assessed at 2 M and 6 M postpartum. Linear regressions and linear mixed-effects models were conducted examining the relationships between maternal BMI and HMO composition and HMO intake and infant growth over the first 6 M, respectively. Maternal obesity was associated with lower concentrations of several fucosylated and sialylated HMOs and infants born to women with obesity had lower intakes of these HMOs. Maternal BMI was positively associated with lacto-N-neotetraose, 3-fucosyllactose, 3-sialyllactose and 6-sialyllactose and negatively associated with disialyllacto-N-tetraose, disialyllacto-N-hexaose, fucodisialyllacto-N-hexaose and total acidic HMOs concentrations at 2 M. Infant intakes of 3-fucosyllactose, 3-sialyllactose, 6-sialyllactose, disialyllacto-N-tetraose, disialyllacto-N-hexaose, and total acidic HMOs were positively associated with infant growth over the first 6 M of life. Maternal obesity is associated with changes in HMO concentrations that are associated with infant adiposity.
Creatine in Health and Disease
Authors: Kreider Richard B. , Stout Jeffery R.
Published: January 2021

Although creatine has been mostly studied as an ergogenic aid for exercise, training, and sport, several health and potential therapeutic benefits have been reported. This is because creatine plays a critical role in cellular metabolism, particularly during metabolically stressed states, and limitations in the ability to transport and/or store creatine can impair metabolism. Moreover, increasing availability of creatine in tissue may enhance cellular metabolism and thereby lessen the severity of injury and/or disease conditions, particularly when oxygen availability is compromised. This systematic review assesses the peer-reviewed scientific and medical evidence related to creatine’s role in promoting general health as we age and how creatine supplementation has been used as a nutritional strategy to help individuals recover from injury and/or manage chronic disease. Additionally, it provides reasonable conclusions about the role of creatine on health and disease based on current scientific evidence. Based on this analysis, it can be concluded that creatine supplementation has several health and therapeutic benefits throughout the lifespan.
Consumption Preferences of Pulses in the Diet of Polish People: Motives and Barriers to Replace Animal Protein with Vegetable Protein
Authors: Śmiglak-Krajewska Magdalena , Wojciechowska-Solis Julia
Published: January 2021

Today, with easy access to information, people are aware of the health benefits of pulses and their significant role in sustainable consumption. Despite this, the consumption of pulses still remains low in many developed and developing countries. The authors of the study attempted to fill the gaps in knowledge about determinants that influence the consumption of pulses. The study was conducted to identify the motives and barriers which, according to a consumer, influence the level of consumption of pulses. An attempt was made to determine to what extent a consumer is influenced by culinary trends (using the multiple linear regression equation). The survey was conducted on a sample of 1067 Polish respondents. The sample was representative and selected to reflect the social demographic distribution of the respondents. In the research, descriptive statistics were used, as well as a t-test, linear regression statistics, and discriminant function analysis. Pulses are more often considered by women to be healthy and nutritious products as well as a good alternative to meat products. The price of pulses products is very important. Men also consider those qualities to be encouraging to consume pulses, but to a lesser extent than women. The lack of knowledge and skills to prepare tasty meals from pulses is one of the most important barriers which, both in the case of women and men, prevents consumers from eating pulses more often. Identified types of diets of the respondents in the research sample showed differences in the regularity of consumption of different selected pulse products. The obtained results indicated that Polish consumers are influenced by other cuisines of the world in their preferences. The most influential cuisines were the Middle Eastern and Mediterranean, with a variety of dishes that are prepared based on pulse products. It should be emphasized that to increase the consumption of pulses, it is necessary to continue educating society through various channels, e.g., culinary, health, information programs, or by inviting celebrities who enjoy the great trust of the society to take part in the advertisement.
The Protein-Binding Behavior of Platinum Anticancer Drugs in Blood Revealed by Mass Spectrometry
Authors: Wang Jingchen , Tao Jianmei , Jia Shuailong , Wang Meiqin , Jiang Hongliang , Du Zhifeng
Published: January 2021

Cisplatin and its analogues are widely used as chemotherapeutic agents in clinical practice. After being intravenously administrated, a substantial amount of platinum will bind with proteins in the blood. This binding is vital for the transport, distribution, and metabolism of drugs; however, toxicity can also occur from the irreversible binding between biologically active proteins and platinum drugs. Therefore, it is very important to study the protein-binding behavior of platinum drugs in blood. This review summarizes mass spectrometry-based strategies to identify and quantitate the proteins binding with platinum anticancer drugs in blood, such as offline high-performance liquid chromatography/inductively coupled plasma mass spectrometry (HPLC–ICP-MS) combined with electrospray ionization mass spectrometry (ESI-MS/MS) and multidimensional LC–ESI-MS/MS. The identification of in vivo targets in blood cannot be accomplished without first studying the protein-binding behavior of platinum drugs in vitro; therefore, relevant studies are also summarized. This knowledge will further our understanding of the pharmacokinetics and toxicity of platinum anticancer drugs, and it will be beneficial for the rational design of metal-based anticancer drugs.
The Role of Imaging in Planning Treatment for Central Serous Chorioretinopathy
Authors: Da Pozzo Stefano , Iacono Pierluigi , Arrigo Alessandro , Battaglia Parodi Maurizio
Published: January 2021

Central serous chorioretinopathy (CSC) is a controversial disease both in terms of clinical classification and choice of therapeutic strategy. Choroidal layers, retinal pigment epithelium (RPE), photoreceptors, and retina are involved to varying degrees. Beyond well-known symptoms raising the clinical suspect of CSC and slit-lamp fundus examination, multimodal imaging plays a key role in assessing the extent of chorioretinal structural involvement. Subretinal fluid (SRF) originating from the choroid leaks through one or multiple RPE defects and spreads into the subretinal space. Spontaneous fluid reabsorption is quite common, but in some eyes, resolution can be obtained only after treatment. Multiple therapeutic strategies are available, and extensive research identified the most effective procedures. Imaging has carved a significant role in guiding the choice of the most appropriate strategy for each single CSC eye. Multiple biomarkers have been identified, and all of them represent a diagnostic and prognostic reference point. This review aims to provide an updated and comprehensive analysis of the current scientific knowledge about the role of imaging in planning the treatment in eyes affected by CSC.
Polyvinylidene Fluoride Membrane Via Vapour Induced Phase Separation for Oil/Water Emulsion Filtration
Authors: Nawi Normi Izati Mat , Sait Nur Rifqah , Bilad Muhammad Roil , Shamsuddin Norazanita , Jaafar Juhana , Nordin Nik Abdul Hadi , Narkkun Thanitporn , Faungnawakij Kajornsak , Mohshim Dzeti Farhah
Published: January 2021

Membrane-based technology is an attractive option for the treatment of oily wastewater because of its high oil removal efficiency, small footprint and operational simplicity. However, filtration performance is highly restricted by membrane fouling, especially when treating oil/water emulsion as a result of strong interaction between oil droplets and the hydrophobic property of the membrane. This study explores the fabrication of polyvinylidene fluoride (PVDF)-based membrane via the vapour induced phase separation (VIPS) method while incorporating polyvinyl pyrrolidone (PVP) as a hydrophilic additive to encounter membrane fouling issues and improve membrane filterability. The resulting membranes were characterized and tested for oil/water emulsion filtration to evaluate their hydraulic, rejection and anti-fouling properties. Results show that the changes in membrane morphology and structure from typical macrovoids with finger-like substructure to cellular structure and larger membrane pore size were observed by the prolonged exposure time from 0 to 30 min through the VIPS method. The enhanced clean water permeability is attributed to the addition of PVP–LiCl in the dope solution that enlarges the mean flow pore size from 0.210 ± 0.1 to 7.709 ± 3.5 µm. The best performing membrane was the VIPS membrane with an exposure time of 5 min (M-5), showing oil/water emulsion permeability of 187 Lm−2 h−1 bar−1 and oil rejection of 91.3% as well as an elevation of 84% of clean water permeability compared to pristine PVDF developed using a typical non-solvent induced phase separation (NIPS) method. Despite the relatively high total fouling, M-5 was able to maintain its high permeability by water flushing as a simple operation for membrane fouling control. The performance was achieved thanks to combination of the large mean flow pore size and hydrophilic property from residual PVP in the membarne matrix. Overall, the results demonstrate the potential of the optimum VIPS method in the presence of PVP and LiCl additives for oil/water emulsion treatment.
Recycling of Chrome-Tanned Leather and Its Utilization as Polymeric Materials and in Polymer-Based Composites: A Review
Authors: Parisi Mariafederica , Nanni Alessandro , Colonna Martino
Published: January 2021

Tanneries generate large amounts of solid and liquid wastes, which contain harmful chemical compounds in the environment, such as chromium, that is used in the tanning process. Until now, they have been almost completely dumped in landfills. Thus, finding eco-sustainable and innovative alternatives for the management and disposal of these wastes is becoming a huge challenge for tanneries and researchers around the world. In particular, the scientific and industrial communities have started using wastes to produce new materials exploiting the characteristics of leather, which are strongly connected with the macromolecular structure of its main component, collagen. None of the reviews on leather waste management actually present in the scientific literature report in detail the use of leather to make composite materials and the mechanical properties of the materials obtained, which are of fundamental importance for an effective industrial exploitation of leather scraps. This comprehensive review reports for the first time the state of the art of the strategies related to the recovery and valorization of both hydrolyzed collagen and leather waste for the realization of composite materials, reporting in detail the properties and the industrial applications of the materials obtained. In the conclusion section, the authors provide practical implications for industry in relation to sustainability and identify research gaps that can guide future authors and industries in their work.
Effect of Nanoclay Particles on the Performance of High-Density Polyethylene-Modified Asphalt Concrete Mixture
Authors: Moussa Ghada S. , Abdel-Raheem Ashraf , Abdel-Wahed Talaat
Published: January 2021

Utilizing polymers for asphalt concrete (AC) mixture modification has many drawbacks that hinder its wide implementations for roadway construction. Recently, research on employing complementary materials, such as nanomaterials, to balance negative impacts of polymers while enhancing the AC mixture’s performance has received great attention. This study aimed to investigate the effect of incorporating nanoclay (NC) particles on the performance of a high-density polyethylene (HDPE)-modified AC mixture. A 60/70 asphalt binder was first modified with HDPE, and then NC particles were gradually added at a concentration of 1–4% by weight of the asphalt binder. The binders’ physical characteristics, storage stability, and chemical change were scrutinized. AC mixture performance, including pseudo-stiffness, moisture damage resistance, stripping susceptibility, and rutting tendency, was investigated. A statistical analysis on the experimental results was conducted using Kruskal–Wallis and Dunn tests. Test results showed that employing NC/HDPE significantly increased penetration index and thereby enhanced binder temperature sensitivity. Moreover, it prevented oxidation action and separation and, therefore, enhanced binder storage stability. Furthermore, incorporating NC amplified pseudo-stiffness and significantly improved resistance against moisture damage and stripping of HDPE-modified mixtures. Moreover, it improved both elastic (recoverable) and plastic (unrecoverable) deformations of mixtures. The most satisfactory results were attained when incorporating 3% of NC.
Tiny Cold Atmospheric Plasma Jet for Biomedical Applications
Authors: Chen Zhitong , Obenchain Richard , Wirz Richard E.
Published: January 2021

Conventional plasma jets for biomedical applications tend to have several drawbacks, such as high voltages, high gas delivery, large plasma probe volume, and the formation of discharge within the organ. Therefore, it is challenging to employ these jets inside a living organism’s body. Thus, we developed a single-electrode tiny plasma jet and evaluated its use for clinical biomedical applications. We investigated the effect of voltage input and flow rate on the jet length and studied the physical parameters of the plasma jet, including discharge voltage, average gas and subject temperature, and optical emissions via spectroscopy (OES). The interactions between the tiny plasma jet and five subjects (de-ionized (DI) water, metal, cardboard, pork belly, and pork muscle) were studied at distances of 10 mm and 15 mm from the jet nozzle. The results showed that the tiny plasma jet caused no damage or burning of tissues, and the ROS/RNS (reactive oxygen/nitrogen species) intensity increased when the distance was lowered from 15 mm to 10 mm. These initial observations establish the tiny plasma jet device as a potentially useful tool in clinical biomedical applications.
The Air and Sewage Pollutants from Biological Waste Treatment
Authors: Wiśniewska Marta , Szyłak-Szydłowski Mirosław
Published: January 2021

The mechanical-biological waste treatment plants (MBTP), which include the municipal waste biogas plants, have an important role in sustainable urban development. Some plants are equipped with a sewage pre-treatment plant, which is then directed to the sewerage system and the treatment plant. Others, on the other hand, have only a non-drainage tank. The parameters of technological sewage (TS) or processing technology could reduce sewage contamination rates. In addition to the quality of sewage from waste treatment plants, the emission of odours is also an important problem, as evidenced by the results obtained over the sewage pumping station tank. The conducted statistical analysis shows a significant positive correlation between odour concentration (cod) and volatile organic compounds (VOCs). Analysing the individual compounds, a high positive correlation was also found—the strongest being between H2S, NH3 and VOCs. In the case of sewage compounds, the insignificant correlation between P total and other parameters was found. For the rest of the compounds, the highest positive correlation was found between COD and BOD and N-NO2 and N-NH3 as well as COD and N-NO2. The dilution of sewage is only an ad hoc solution to the problem. Further work should be aimed at reducing sewage pollution rates. The obtained results indicate large pollution of technological sewage and a high level of odour and odorants concentration. The novelty and scientific contribution presented in the paper are related to analyses of various factors on technological sewage parameters and odour and odorant emission from TS tank at biogas plant processing municipal waste, which may be an important source of knowledge on the management of TS, its disposal and minimisation of emitted compound emissions.
Cavitation Prevention Potential of Hydromechanical Pressure Compensation Independent Metering System with External Active Load
Authors: Liu Kailei , Kang Shaopeng , Qiang Hongbin , Yu Chengtao
Published: January 2021

This article studies the cavitation performance and preventing method of the hydromechanical pressure compensation independent metering system (HPCIMS). Compared with the conventional load sensing system (CLSS), the meter-in and meter-out orifices of HPCIMS can be regulated independently. A quasi-static behavior analysis of cavitation performance was applied to the HPCIMS and CLSS. The meter-in pressure equation of HPCIMS showed that keeping the ratio of the meter-in and meter-out orifices greater than the minimum value can avoid the cavitation phenomenon. Systems parameters were then kept as constant, and the key parameters related to cavitation performance of the two systems were compared by varying external force. Comparison results show that the cavitation phenomenon in the meter-in chamber of CLSS with the external active load is inevitable, but in HPCIMS, it can prevent the cavitation phenomenon by changing the ratio of the meter-in and meter-out orifices, so the HPCIMS has the cavitation prevention potential.
Energy Management in Smart Building by a Multi-Objective Optimization Model and Pascoletti-Serafini Scalarization Approach
Authors: Foroozandeh Zahra , Ramos Sérgio , Soares João , Vale Zita
Published: January 2021

Generally, energy management in smart buildings is formulated by mixed-integer linear programming, with different optimization goals. The most targeted goals are the minimization of the electricity consumption cost, the electricity consumption value from external power grid, and peak load smoothing. All of these objectives are desirable in a smart building, however, in most of the related works, just one of these mentioned goals is considered and investigated. In this work, authors aim to consider two goals via a multi-objective framework. In this regard, a multi-objective mixed-binary linear programming is presented to minimize the total energy consumption cost and peak load in collective residential buildings, considering the scheduling of the charging/discharging process for electric vehicles and battery energy storage system. Then, the Pascoletti-Serafini scalarization approach is used to obtain the Pareto front solutions of the presented multi-objective model. In the final, the performance of the proposed model is analyzed and reported by simulating the model under two different scenarios. The results show that the total consumption cost of the residential building has been reduced 35.56% and the peak load has a 45.52% reduction.
Bodies of Knowledge: Bodily Perfection in Tantric Buddhist Practice
Authors: Gray David B.
Published: January 2021

This essay explores conflicting attitudes toward the body in Buddhist literature, with a focus on the tantric Buddhist traditions of yoga and meditation, which advanced the notion that the body was an innately pure site for realization while nonetheless still encumbered with earlier notions of the body as an impure obstacle to be overcome. Looking closely at a short meditation text attributed to the female Indian saints Mekhalā and Kanakhalā, the author argues that the body plays a central role in the creative re-envisioning of the self that characterizes tantric Buddhist practice.
Modelling Daily Gross Primary Productivity with Sentinel-2 Data in the Nordic Region–Comparison with Data from MODIS
Authors: Cai Zhanzhang , Junttila Sofia , Holst Jutta , Jin Hongxiao , Ardö Jonas , Ibrom Andreas , Peichl Matthias , Mölder Meelis , Jönsson Per , Rinne Janne , Karamihalaki Maria , Eklundh Lars
Published: January 2021

The high-resolution Sentinel-2 data potentially enable the estimation of gross primary productivity (GPP) at finer spatial resolution by better capturing the spatial variation in a heterogeneous landscapes. This study investigates the potential of 10 m resolution reflectance from the Sentinel-2 Multispectral Instrument to improve the accuracy of GPP estimation across Nordic vegetation types, compared with the 250 m and 500 m resolution reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS). We applied linear regression models with inputs of two-band enhanced vegetation index (EVI2) derived from Sentinel-2 and MODIS reflectance, respectively, together with various environmental drivers to estimate daily GPP at eight Nordic eddy covariance (EC) flux tower sites. Compared with the GPP from EC measurements, the accuracies of modelled GPP were generally high (R2 = 0.84 for Sentinel-2; R2 = 0.83 for MODIS), and the differences between Sentinel-2 and MODIS were minimal. This demonstrates the general consistency in GPP estimates based on the two satellite sensor systems at the Nordic regional scale. On the other hand, the model accuracy did not improve by using the higher spatial-resolution Sentinel-2 data. More analyses of different model formulations, more tests of remotely sensed indices and biophysical parameters, and analyses across a wider range of geographical locations and times will be required to achieve improved GPP estimations from Sentinel-2 satellite data.
Improving the Retrieval of Crop Canopy Chlorophyll Content Using Vegetation Index Combinations
Authors: Sun Qi , Jiao Quanjun , Qian Xiaojin , Liu Liangyun , Liu Xinjie , Dai Huayang
Published: January 2021

Estimates of crop canopy chlorophyll content (CCC) can be used to monitor vegetation productivity, manage crop resources, and control disease and pests. However, making these estimates using conventional ground-based methods is time-consuming and resource-intensive when deployed over large areas. Although vegetation indices (VIs), derived from satellite sensor data, have been used to estimate CCC, they suffer from problems related to spectral saturation, soil background, and canopy structure. A new method was, therefore, proposed for combining the Medium Resolution Imaging Spectrometer (MERIS) terrestrial chlorophyll index (MTCI) and LAI-related vegetation indices (LAI-VIs) to increase the accuracy of CCC estimates for wheat and soybeans. The PROSAIL-D canopy reflectance model was used to simulate canopy spectra that were resampled to match the spectral response functions of the MERIS carried on the ENVISAT satellite. Combinations of the MTCI and LAI-VIs were then used to estimate CCC via univariate linear regression, binary linear regression and random forest regression. The accuracy using the field spectra and MERIS data was determined based on field CCC measurements. All the MTCI and LAI-VI combinations for the selected regression techniques resulted in more accurate estimates of CCC than the use of the MTCI alone (field spectra data for soybeans and wheat: R2 = 0.62 and RMSE = 77.10 μg cm−2; MERIS satellite data for soybeans: R2 = 0.24 and RMSE = 136.54 μg cm−2). The random forest regression resulted in better accuracy than the other two linear regression models. The combination resulting in the best accuracy was the MTCI and MTVI2 and random forest regression, with R2 = 0.65 and RMSE = 37.76 μg cm−2 (field spectra data) and R2 = 0.78 and RMSE = 47.96 μg cm−2 (MERIS satellite data). Combining the MTCI and a LAI-VI represents a further step towards improving the accuracy of estimation CCC based on multispectral satellite sensor data.
Unsupervised Multitemporal Building Change Detection Framework Based on Cosegmentation Using Time-Series SAR
Authors: Zhang Kaiyu , Fu Xikai , Lv Xiaolei , Yuan Jili
Published: January 2021

Building change detection using remote sensing images is essential for various applications such as urban management and marketing planning. However, most change detection approaches can only detect the intensity or type of change. The aim of this study is to dig for more change information from time-series synthetic aperture radar (SAR) images, such as the change frequency and the change moments. This paper proposes a novel multitemporal building change detection framework that can generate change frequency map (CFM) and change moment maps (CMMs) from multitemporal SAR images. We first give definitions of CFM and CMMs. Then we generate change feature using four proposed generators. After that, a new cosegmentation method combining raw images and change feature is proposed to divide time-series images into changed and unchanged areas separately. Secondly, the proposed cosegmentation and the morphological building index (MBI) are combined to extract changed building objects. Then, the logical conjunction between the cosegmentation results and the binarized MBI is performed to recognize every moment of change. In the post-processing step, we use fragment removal to increase accuracy. Finally, we propose a novel accuracy assessment index for CFM. We call this index average change difference (ACD). Compared to the traditional multitemporal change detection methods, our method outperforms other approaches in terms of both qualitative results and quantitative indices of ACD using two TerraSAR-X datasets. The experiments show that the proposed method is effective in generating CFM and CMMs.
PointNet++ Network Architecture with Individual Point Level and Global Features on Centroid for ALS Point Cloud Classification
Authors: Chen Yang , Liu Guanlan , Xu Yaming , Pan Pai , Xing Yin
Published: January 2021

Airborne laser scanning (ALS) point cloud has been widely used in the fields of ground powerline surveying, forest monitoring, urban modeling, and so on because of the great convenience it brings to people’s daily life. However, the sparsity and uneven distribution of point clouds increases the difficulty of setting uniform parameters for semantic classification. The PointNet++ network is an end-to-end learning network for irregular point data and highly robust to small perturbations of input points along with corruption. It eliminates the need to calculate costly handcrafted features and provides a new paradigm for 3D understanding. However, each local region in the output is abstracted by its centroid and local feature that encodes the centroid’s neighborhood. The feature learned on the centroid point may not contain relevant information of itself for random sampling, especially in large-scale neighborhood balls. Moreover, the centroid point’s global-level information in each sample layer is also not marked. Therefore, this study proposed a modified PointNet++ network architecture which concentrates the point-level and global features on the centroid point towards the local features to facilitate classification. The proposed approach also utilizes a modified Focal Loss function to solve the extremely uneven category distribution on ALS point clouds. An elevation- and distance-based interpolation method is also proposed for the objects in ALS point clouds which exhibit discrepancies in elevation distributions. The experiments on the Vaihingen dataset of the International Society for Photogrammetry and Remote Sensing and the GML(B) 3D dataset demonstrate that the proposed method which provides additional contextual information to support classification achieves high accuracy with simple discriminative models and new state-of-the-art performance in power line categories.
Mapping Essential Urban Land Use Categories in Beijing with a Fast Area of Interest (AOI)-Based Method
Authors: Li Xiaoting , Hu Tengyun , Gong Peng , Du Shihong , Chen Bin , Li Xuecao , Dai Qi
Published: January 2021

Urban land use mapping is critical to understanding human activities in space. The first national mapping result of essential urban land use categories of China (EULUC-China) was released in 2019. However, the overall accuracies in some of the plain cities such as Beijing, Chengdu, and Zhengzhou were lower than 50% because many parcel-based mapping units are large with mixed land uses. To address this shortcoming, we proposed an area of interest (AOI)-based mapping approach, choosing Beijing as our study area. The mapping process includes two major steps. First, grids with different sizes (i.e., 300 m, 200 m, and 100 m) were derived from original land parcels to obtain classification units with a suitable size. Then, features within these grids were extracted from Sentinel-2 spectral data, point of interest (POI), and Tencent Easygo crowdedness data. These features were classified using a random forest (RF) classifier with AOI data, resulting in a 10-category map of EULUC. Second, we superimposed the AOIs layer on classified units to do some rectification and offer more details at the building scale. The overall accuracy of the AOI layer reached 98%, and the overall accuracy of the mapping results reached 77%. This study provides a fast method for accurate geographic sample collection, which substantially reduces the amount of fieldwork for sample collection and improves the classification accuracy compared to previous EULUC mapping. The detailed urban land use map could offer more support for urban planning and environmental policymaking.
A New Individual Tree Species Recognition Method Based on a Convolutional Neural Network and High-Spatial Resolution Remote Sensing Imagery
Authors: Yan Shijie , Jing Linhai , Wang Huan
Published: January 2021

Tree species surveys are crucial to forest resource management and can provide references for forest protection policy making. The traditional tree species survey in the field is labor-intensive and time-consuming, supporting the practical significance of remote sensing. The availability of high-resolution satellite remote sensing data enable individual tree species (ITS) recognition at low cost. In this study, the potential of the combination of such images and a convolutional neural network (CNN) to recognize ITS was explored. Firstly, individual tree crowns were delineated from a high-spatial resolution WorldView-3 (WV3) image and manually labeled as different tree species. Next, a dataset of the image subsets of the labeled individual tree crowns was built, and several CNN models were trained based on the dataset for ITS recognition. The models were then applied to the WV3 image. The results show that the distribution maps of six ITS offered an overall accuracy of 82.7% and a kappa coefficient of 0.79 based on the modified GoogLeNet, which used the multi-scale convolution kernel to extract features of the tree crown samples and was modified for small-scale samples. The ITS recognition method proposed in this study, with multi-scale individual tree crown delineation, avoids artificial tree crown delineation. Compared with the random forest (RF) and support vector machine (SVM) approaches, this method can automatically extract features and outperform RF and SVM in the classification of six tree species.
A Genetically Encoded Bioluminescence Intracellular Nanosensor for Androgen Receptor Activation Monitoring in 3D Cell Models
Authors: Calabretta Maria Maddalena , Lopreside Antonia , Montali Laura , Cevenini Luca , Roda Aldo , Michelini Elisa
Published: January 2021

In recent years, there has been an increasing demand for predictive and sensitive in vitro tools for drug discovery. Split complementation assays have the potential to enlarge the arsenal of in vitro tools for compound screening, with most of them relying on well-established reporter gene assays. In particular, ligand-induced complementation of split luciferases is emerging as a suitable approach for monitoring protein–protein interactions. We hereby report an intracellular nanosensor for the screening of compounds with androgenic activity based on a split NanoLuc reporter. We also confirm the suitability of using 3D spheroids of Human Embryonic Kidney (HEK-293) cells for upgrading the 2D cell-based assay. A limit of detection of 4 pM and a half maximal effective concentration (EC50) of 1.7 ± 0.3 nM were obtained for testosterone with HEK293 spheroids. This genetically encoded nanosensor also represents a new tool for real time imaging of the activation state of the androgen receptor, thus being suitable for analysing molecules with androgenic activity, including new drugs or endocrine disrupting molecules.
Application of Laser Vibrometry to Assess Defects in Ship Hull’s Welded Joints’ Technical Condition
Authors: Szeleziński Adam , Muc Adam , Murawski Lech , Kluczyk Marcin , Muchowski Tomasz
Published: January 2021

The paper presents the measurement process and test results for six thin-walled plates with different dynamic characteristics caused by different defects of welded joints. The tests were carried out using non-destructive testing (NDT). The authors made an attempt to determine the validity of the use and degree of effectiveness of the tests based on laser vibrometry in detecting defects in welded joints. The tests of welded plates were carried out using displacement laser sensors and piezoelectric accelerometers, while the source of vibration extortion was a modal hammer. In the adopted measurement methodology, the application of accelerometers was to obtain the reference data, which allowed for comparison with the measurement data obtained from the laser vibrometer. The analysis of the obtained measurement data, in the fields of time and frequency, made it possible to verify the correctness of the data obtained by means of laser vibrometry and to determine the requirements which are necessary for the correct performance of NDT tests and in the future structural health monitoring (SHM) system of welded joints with the use of a laser vibrometer. The mathematical model developed in the MSC software Pastran-Nastran was also used in the work. The model was developed for the purpose of mutual verification of the measurement and calculation tests. At the present stage of work, it can be stated that the results obtained by laser vibrometry methods should be treated as a supplement to the research conducted with traditional piezoelectric accelerometers. In certain situations, they can be used as an alternative to accelerometers, due to the fact that laser sensors do not require direct contact with the examined object. Where the object under test may be in a strong electromagnetic field, optical sensors are better suited than contact sensors.
Improving Resolution of Dual-Comb Gas Detection Using Periodic Spectrum Alignment Method
Authors: Yu Haoyang , Zhou Qian , Li Xinghui , Wang Xiaohao , Wang Xilin , Ni Kai
Published: January 2021

Dual-comb spectroscopy has been an infusive spectroscopic tool for gas detection due to its high resolution, high sensitivity, and fast acquisition speed over a broad spectral range without any mechanical scanning components. However, the complexity and cost of high-performance dual-comb spectroscopy are still high for field-deployed applications. To solve this problem, we propose a simple frequency domain post-processing method by extracting the accurate position of a specific absorption line frame by frame. After aligning real-time spectra and averaging for one second, the absorbance spectrum of H13C14N gas in the near-infrared is obtained over 1.1 THz spectral range. By using this method, the standard deviation of residual error is only ~0.002, showing great agreement with the conventional correction method. In addition, the spectral resolution is improved from 13.4 GHz to 4.3 GHz compared to direct spectrum averaging. Our method does not require a specially designed common-mode suppression comb, rigorous frequency control system, or complicated computational algorithm, providing a cost-effective scheme for field-deployed Doppler-limited spectroscopy applications.
Validity of a Non-Proprietary Algorithm for Identifying Lying Down Using Raw Data from Thigh-Worn Triaxial Accelerometers
Authors: Hettiarachchi Pasan , Aili Katarina , Holtermann Andreas , Stamatakis Emmanuel , Svartengren Magnus , Palm Peter
Published: January 2021

Body postural allocation during daily life is important for health, and can be assessed with thigh-worn accelerometers. An algorithm based on sedentary bouts from the proprietary ActivePAL software can detect lying down from a single thigh-worn accelerometer using rotations of the thigh. However, it is not usable across brands of accelerometers. This algorithm has the potential to be refined. Aim: To refine and assess the validity of an algorithm to detect lying down from raw data of thigh-worn accelerometers. Axivity-AX3 accelerometers were placed on the thigh and upper back (reference) on adults in a development dataset (n = 50) and a validation dataset (n = 47) for 7 days. Sedentary time from the open Acti4-algorithm was used as input to the algorithm. In addition to the thigh-rotation criterion in the existing algorithm, two criteria based on standard deviation of acceleration and a time duration criterion of sedentary bouts were added. The mean difference (95% agreement-limits) between the total identified lying time/day, between the refined algorithm and the reference was +2.9 (−135,141) min in the development dataset and +6.5 (−145,159) min in the validation dataset. The refined algorithm can be used to estimate lying time in studies using different accelerometer brands.
Emergent Biosensing Technologies Based on Fluorescence Spectroscopy and Surface Plasmon Resonance
Authors: Camarca Alessandra , Varriale Antonio , Capo Alessandro , Pennacchio Angela , Calabrese Alessia , Giannattasio Cristina , Murillo Almuzara Carlos , D’Auria Sabato , Staiano Maria
Published: January 2021

The purpose of this work is to provide an exhaustive overview of the emerging biosensor technologies for the detection of analytes of interest for food, environment, security, and health. Over the years, biosensors have acquired increasing importance in a wide range of applications due to synergistic studies of various scientific disciplines, determining their great commercial potential and revealing how nanotechnology and biotechnology can be strictly connected. In the present scenario, biosensors have increased their detection limit and sensitivity unthinkable until a few years ago. The most widely used biosensors are optical-based devices such as surface plasmon resonance (SPR)-based biosensors and fluorescence-based biosensors. Here, we will review them by highlighting how the progress in their design and development could impact our daily life.
Realworld 3D Object Recognition Using a 3D Extension of the HOG Descriptor and a Depth Camera
Authors: Vilar Cristian , Krug Silvia , O’Nils Mattias
Published: January 2021

3D object recognition is an generic task in robotics and autonomous vehicles. In this paper, we propose a 3D object recognition approach using a 3D extension of the histogram-of-gradients object descriptor with data captured with a depth camera. The presented method makes use of synthetic objects for training the object classifier, and classify real objects captured by the depth camera. The preprocessing methods include operations to achieve rotational invariance as well as to maximize the recognition accuracy while reducing the feature dimensionality at the same time. By studying different preprocessing options, we show challenges that need to be addressed when moving from synthetic to real data. The recognition performance was evaluated with a real dataset captured by a depth camera and the results show a maximum recognition accuracy of 81.5%.
Stochastic Decision Fusion of Convolutional Neural Networks for Tomato Ripeness Detection in Agricultural Sorting Systems
Authors: Ko KwangEun , Jang Inhoon , Choi Jeong Hee , Lim Jeong Ho , Lee Da Uhm
Published: January 2021

Advances in machine learning and artificial intelligence have led to many promising solutions for challenging issues in agriculture. One of the remaining challenges is to develop practical applications, such as an automatic sorting system for after-ripening crops such as tomatoes, according to ripeness stages in the post-harvesting process. This paper proposes a novel method for detecting tomato ripeness by utilizing multiple streams of convolutional neural network (ConvNet) and their stochastic decision fusion (SDF) methodology. We have named the overall pipeline as SDF-ConvNets. The SDF-ConvNets can correctly detect the tomato ripeness by following consecutive phases: (1) an initial tomato ripeness detection for multi-view images based on the deep learning model, and (2) stochastic decision fusion of those initial results to obtain the final classification result. To train and validate the proposed method, we built a large-scale image dataset collected from a total of 2712 tomato samples according to five continuous ripeness stages. Five-fold cross-validation was used for a reliable evaluation of the performance of the proposed method. The experimental results indicate that the average accuracy for detecting the five ripeness stages of tomato samples reached 96%. In addition, we found that the proposed decision fusion phase contributed to the improvement of the accuracy of the tomato ripeness detection.
An Indoor Visible Light Positioning System Using Tilted LEDs with High Accuracy
Authors: Chaudhary Neha , Younus Othman Isam , Alves Luis Nero , Ghassemlooy Zabih , Zvanovec Stanislav , Le-Minh Hoa
Published: January 2021

The accuracy of the received signal strength-based visible light positioning (VLP) system in indoor applications is constrained by the tilt angles of transmitters (Txs) and receivers as well as multipath reflections. In this paper, for the first time, we show that tilting the Tx can be beneficial in VLP systems considering both line of sight (LoS) and non-line of sight transmission paths. With the Txs oriented towards the center of the receiving plane (i.e., the pointing center F), the received power level is maximized due to the LoS components on F. We also show that the proposed scheme offers a significant accuracy improvement of up to ~66% compared with a typical non-tilted Tx VLP at a dedicated location within a room using a low complex linear least square algorithm with polynomial regression. The effect of tilting the Tx on the lighting uniformity is also investigated and results proved that the uniformity achieved complies with the European Standard EN 12464-1. Furthermore, we show that the accuracy of VLP can be further enhanced with a minimum positioning error of 8 mm by changing the height of F.
Association of Genetic Variances in ADRB1 and PPARGC1a with Two-Kilometre Running Time-Trial Performance in Australian Football League Players: A Preliminary Study
Authors: Jacob Ysabel , Anderton Ryan S. , Cochrane Wilkie Jodie L. , Rogalski Brent , Laws Simon M. , Jones Anthony , Spiteri Tania , Hart Nicolas H.
Published: January 2021

Genetic variants in the angiotensin-converting enzyme (ACE) (rs4343), alpha-actinin-3 (ACTN3) (rs1815739), adrenoceptor-beta-1 (ADRB1) (rs1801253), and peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PPARGC1A) (rs8192678) genes have previously been associated with elite athletic performance. This study assessed the influence of polymorphisms in these candidate genes towards endurance test performance in 46 players from a single Australian Football League (AFL) team. Each player provided saliva buccal swab samples for DNA analysis and genotyping and were required to perform two independent two-kilometre running time-trials, six weeks apart. Linear mixed models were created to account for repeated measures over time and to determine whether player genotypes are associated with overall performance in the two-kilometre time-trial. The results showed that the ADRB1 Arg389Gly CC (p = 0.034) and PPARGC1A Gly482Ser GG (p = 0.031) genotypes were significantly associated with a faster two-kilometre time-trial. This is the first study to link genetic polymorphism to an assessment of endurance performance in Australian Football and provides justification for further exploratory or confirmatory studies.