bluuebunny/crossref_metadata_2025 huggingface dataset:
Pressure- and Temperature-Induced Insertion of N2, O2 and CH4 to Ag-Natrolite
Authors: Seoung Donghoon , Kim Hyeonsu , Kim Pyosang , Lee Yongmoon
Published: September 2020

This paper aimed to investigate the structural and chemical changes of Ag-natrolite (Ag16Al16Si24O80·16H2O, Ag-NAT) in the presence of different pressure transmitting mediums (PTMs), such as N2, O2 and CH4, up to ~8 GPa and 250 °C using in situ synchrotron X-ray powder diffraction and Rietveld refinement. Pressure-induced insertion occurs in two stages in the case of N2 and O2 runs, as opposed to the CH4 run. First changes of the unit cell volume in N2, O2 and CH4 runs are observed at 0.88(5) GPa, 1.05(5) GPa and 1.84(5) GPa with increase of 5.7(1)%, 5.5(1)% and 5.7(1)%, respectively. Subsequent volume changes of Ag-natrolite in the presence of N2 and O2 appear at 2.15(5) GPa and 5.24(5) GPa with a volume increase of 0.8(1)% and a decrease of 3.0(1)%, respectively. The bulk moduli of the Ag-NAT change from 42(1) to 49(7), from 38(1) to 227(1) and from 49(3) to 79(2) in the case of N2, O2 and CH4 runs, respectively, revealing that the Ag-NAT becomes more incompressible after each insertion of PTM molecules. The shape of the channel window of the Ag-NAT changes from elliptical to more circular after the uptake of N2, O2 and CH4. Overall, the experimental results of Ag-NAT from our previous data and this work establish that the onset pressure exponentially increases with the molecular size. The unit cell volumes of the expanded (or contracted) phases of the Ag-NAT have a linear relationship and limit to maximally expand and contract upon pressure-induced insertion.
Transmembrane Facilitation of Lactate/H+ Instead of Lactic Acid Is Not a Question of Semantics but of Cell Viability
Authors: Bader Annika , Beitz Eric
Published: September 2020

Transmembrane transport of monocarboxylates is conferred by structurally diverse membrane proteins. Here, we describe the pH dependence of lactic acid/lactate facilitation of an aquaporin (AQP9), a monocarboxylate transporter (MCT1, SLC16A1), and a formate–nitrite transporter (plasmodium falciparum FNT, PfFNT) in the equilibrium transport state. FNTs exhibit a channel-like structure mimicking the aquaporin-fold, yet act as secondary active transporters. We used radiolabeled lactate to monitor uptake via yeast-expressed AQP9, MCT1, and PfFNT for long enough time periods to reach the equilibrium state in which import and export rates are balanced. We confirmed that AQP9 behaved perfectly equilibrative for lactic acid, i.e., the neutral lactic acid molecule enters and passes the channel. MCT1, in turn, actively used the transmembrane proton gradient and acted as a lactate/H+ co-transporter. PfFNT behaved highly similar to the MCT in terms of transport properties, although it does not adhere to the classical alternating access transporter model. Instead, the FNT appears to use the proton gradient to neutralize the lactate anion in the protein’s vestibule to generate lactic acid in a place that traverses the central hydrophobic transport path. In conclusion, we propose to include FNT-type proteins into a more generalized, function-based transporter definition.
Comparison of Various Methods to Determine Added Sugars Intake to Assess the Association of Added Sugars Intake and Micronutrient Adequacy
Authors: Fulgoni Victor L. , Gaine P. Courtney , Scott Maria O.
Published: September 2020

Different methods for determining the effect of added sugars intake among children and adults on meeting recommended nutrient intakes were compared using 24 h dietary recall data from the National Health and Nutrition Examination Survey (NHANES) 2011–2014. Four methods were used to determine deciles of added sugars intake (as the percentage of total calories): 1 day intake, 2 day average intake, and individual usual intake (UI) determined with the National Cancer Institute (NCI) and the multivariate Markov Chain Monte Carlo methods. Percentages of the population below the Estimated Average Requirement (EAR) for calcium and vitamin D/above the Adequate Intake (AI) for potassium and dietary fiber for each decile of added sugars intake were assessed with the NCI method. Using regression analyses, added sugars intake deciles (by any method) in children were inversely associated (p < 0.001) with percentages below the EAR/above the AI of vitamin D, calcium, potassium, and fiber. In adults, added sugars intake deciles were inversely associated with meeting recommendations for vitamin D, potassium, and fiber. There were no significant between-method differences for regression coefficients for any nutrients investigated. Overall, these methods showed a similar association of added sugars intake with nutrient inadequacy/adequacy; therefore, method preference may depend more on practical reasons.
Evaluation of Food-Intake Behavior in a Healthy Population: Personalized vs. One-Size-Fits-All
Authors: Hoevenaars Femke P. M. , Berendsen Charlotte M. M. , Pasman Wilrike J. , van den Broek Tim J. , Barrat Emmanuel , de Hoogh Iris M. , Wopereis Suzan
Published: September 2020

In public health initiatives, generic nutrition advice (GNA) from national guidelines has a limited effect on food-intake improvement. Personalized nutrition advice (PNA) may enable dietary behavior change. A monocentric, randomized, parallel, controlled clinical trial was performed in males (n = 55) and females (n = 100) aged 25 to 70 years. Participants were allocated to control, GNA or PNA groups. The PNA group consisted of automatically generated dietary advice based on personal metabolic health parameters, dietary intake, anthropometric and hemodynamic measures, gender and age. Participants who received PNA (n = 51) improved their nutritional intake status for fruits P (p < 0.0001), whole grains (p = 0.008), unsalted nuts (p < 0.0001), fish (p = 0.0003), sugar-sweetened beverages (p = 0.005), added salt (p = 0.003) and less unhealthy choices (p = 0.002), whereas no improvements were observed in the control and GNA group. PNA participants were encouraged to set a goal for one or multiple food categories. Goal-setting led to greater improvement of food categories within the PNA group including; unsalted nuts (p < 0.0001), fruits (p = 0.0001), whole grains (p = 0.005), fish (p = 0.0001), dairy (p = 0.007), vegetables (p = 0.01) and unhealthy choices (p = 0.02). In a healthy population, participants receiving PNA changed their food-intake behavior more favorably than participants receiving GNA or no advice. When personal goals were set, nutritional behavior was more prone to change.
Nutritional Intervention to Prevent the Functional Decline in Community-Dwelling Older Adults: A Systematic Review
Authors: Mareschal Julie , Genton Laurence , Collet Tinh-Hai , Graf Christophe
Published: September 2020

Aging is a global public health concern. From the age of 50, muscle mass, muscle strength and physical performance tend to decline. Sarcopenia and frailty are frequent in community-dwelling older adults and are associated with negative outcomes such as physical disability and mortality. Therefore, the identification of therapeutic strategies to prevent and fight sarcopenia and frailty is of great interest. This systematic review aims to summarize the impact of nutritional interventions alone or combined with other treatment(s) in older community-dwelling adults on (1) the three indicators of sarcopenia, i.e., muscle mass, muscle strength and physical performance; and (2) the hospitalization and readmission rates. The literature search was performed on Medline and included studies published between January 2010 and June 2020. We included randomized controlled trials of nutritional intervention alone or combined with other treatment(s) in community-living subjects aged 65 or older. In total, 28 articles were retained in the final analysis. This systematic review highlights the importance of a multimodal approach, including at least a combined nutritional and exercise intervention, to improve muscle mass, muscle strength and physical performance, in community-dwelling older adults but especially in frail and sarcopenic subjects. Regarding hospitalization and readmission rate, data were limited and inconclusive. Future studies should continue to investigate the effects of such interventions in this population.
Feasibility, Process, and Effects of Short-Term Calorie Reduction in Cancer Patients Receiving Chemotherapy: An Integrative Review
Authors: Tang Chia-Chun , Chen Hsi , Huang Tai-Chung , Wu Wei-Wen , Lin Jing-Mei , Tien Feng-Ming
Published: September 2020

Recent preclinical studies have shown the potential benefits of short-term calorie reduction (SCR) on cancer treatment. In this integrative review, we aimed to identify and synthesize current evidence regarding the feasibility, process, and effects of SCR in cancer patients receiving chemotherapy. PubMed, Cumulative Index to Nursing and Allied Health Literature, Ovid Medline, PsychINFO, and Embase were searched for original research articles using various combinations of Medical Subject Heading terms. Among the 311 articles identified, seven studies met the inclusion criteria. The majority of the reviewed studies were small randomized controlled trials or cohort study with fair quality. The results suggest that SCR is safe and feasible. SCR is typically arranged around the chemotherapy, with the duration ranging from 24 to 96 h. Most studies examined the protective effects of SCR on normal cells during chemotherapy. The evidence supports that SCR had the potential to enhance both the physical and psychological wellbeing of patients during chemotherapy. SCR is a cost-effective intervention with great potential. Future well-controlled studies with sufficient sample sizes are needed to examine the full and long-term effects of SCR and its mechanism of action.
Emulsifiers Impact Colonic Length in Mice and Emulsifier Restriction is Feasible in People with Crohn’s Disease
Authors: Sandall Alicia M. , Cox Selina R. , Lindsay James O. , Gewirtz Andrew T. , Chassaing Benoit , Rossi Megan , Whelan Kevin
Published: September 2020

There is an association between food additive emulsifiers and the prevalence of Crohn’s disease. This study aimed to investigate: (i) the effect of different classes of emulsifiers on markers of intestinal inflammation in mice and (ii) the feasibility, nutritional adequacy and symptom impact of restricting all emulsifier classes in Crohn’s disease. Mice were exposed to different classes of emulsifiers (carboxymethycellose, polysorbate-80, soy lecithin, gum arabic) in drinking water for 12-weeks, after which markers of inflammation and metabolism were measured. A low emulsifier diet was developed to restrict all classes of emulsifiers and its feasibility measured over 14-days in 20 participants with stable Crohn’s disease. Crohn’s disease-related symptoms, disease control, body weight and composition, nutrient intake and food-related quality of life (QoL) were measured. All emulsifiers resulted in lower murine colonic length compared with control (mean 9.5 cm (SEM 0.20)), but this only reached significance for polysorbate-80 (8.2 cm (0.34), p = 0.024) and carboxymethylcellulose (8.0 cm (0.35), p = 0.013). All 20 participants completed the feasibility study. The frequency of consuming emulsifier-containing foods decreased by 94.6% (SD 10.3%). Food-related QoL improved between habitual (median 81.5 (IQR 25.0)) and low emulsifier diet (90.0 (24.0), p = 0.028). Crohn’s disease-related symptoms reduced (median 3.0 (IQR 5.3) vs. 1.4 (3.9), p = 0.006), and disease control scores improved (13.5 (IQR 6.0) vs. 15.5 (IQR 3.0), p = 0.026). A range of emulsifiers may influence intestinal inflammation in mice, and dietary restriction of emulsifiers is feasible. Trials investigating the efficacy of a low emulsifier diet in Crohn’s disease are warranted.
Clinical Evidence for Targeting NAD Therapeutically
Authors: Radenkovic Dina , Reason  , Verdin Eric
Published: September 2020

Nicotinamide adenine dinucleotide (NAD) pharmacology is a promising class of treatments for age-related conditions that are likely to have a favorable side effect profile for human use, given the widespread use of the NAD precursor vitamin B3 supplements. However, despite several decades of active investigation and numerous possible biochemical mechanisms of action suggested, only a small number of randomized and adequately powered clinical trials of NAD upregulation as a therapeutic strategy have taken place. We conducted a systematic review of the literature, following the PRISMA guidelines, in an attempt to determine whether or not the human clinical trials performed to date support the potential benefits of NAD supplementation in a range of skin, metabolic and age-related conditions. In addition, we sought medical indications that have yielded the most promising results in the limited studies to date. We conclude that promising, yet still speculative, results have been reported for the treatment of psoriasis and enhancement of skeletal muscle activity. However, further trials are required to determine the optimal method of raising NAD levels, identifying the target conditions, and comparisons to the present standard of care for these conditions. Lastly, pharmacological methods that increase NAD levels should also be directly compared to physiological means of raising NAD levels, such as exercise programs and dietary interventions that are tailored to older individuals, and which may be more effective.
Image-Based Artificial Intelligence Methods for Product Control of Tablet Coating Quality
Authors: Hirschberg Cosima , Edinger Magnus , Holmfred Else , Rantanen Jukka , Boetker Johan
Published: September 2020

Mimicking the human decision-making process is challenging. Especially, many process control situations during the manufacturing of pharmaceuticals are based on visual observations and related experience-based actions. The aim of the present work was to investigate the use of image analysis to classify the quality of coated tablets. Tablets with an increasing amount of coating solution were imaged by fast scanning using a conventional office scanner. A segmentation routine was implemented to the images, allowing the extraction of numeric image-based information from individual tablets. The image preprocessing was performed prior to utilization of four different classification techniques for the individual tablet images. The support vector machine (SVM) technique performed superior compared to a convolutional neural network (CNN) in relation to computational time, and this approach was also slightly better at classifying the tablets correctly. The fastest multivariate method was partial least squares (PLS) regression, but this method was hampered by the inferior classification accuracy of the tablets. Finally, it was possible to create a numerical threshold classification model with an accuracy comparable to the SVM approach, so it is evident that there exist multiple valid options for classifying coated tablets.
Development of a Surface Coating Technique with Predictive Value for Bead Coating in the Manufacturing of Amorphous Solid Dispersions
Authors: Boel Eline , Panini Piyush , Van den Mooter Guy
Published: September 2020

The aim of this paper was to investigate whether a surface coating technique could be developed that can predict the phase behavior of amorphous solid dispersions (ASDs) coated on beads. ASDs of miconazole (MIC) and poly(vinylpyrrolidone-co-vinyl acetate) (PVP-VA) in methanol (MeOH) were studied as a model system. First, the low crystallization tendency of the model drug in MeOH was evaluated and confirmed. In a next step, a drug loading screening was performed on casted films and coated beads in order to define the highest possible MIC loading that still results in a one-phase amorphous system. These results indicate that film casting is not suitable for phase behavior predictions of ASDs coated on beads. Therefore, a setup for coating a solid surface was established inside the drying chamber of a spray dryer and it was found that this surface coating technique could predict the phase behavior of MIC-PVP-VA systems coated on beads, in case an intermittent spraying procedure is applied. Finally, spray drying was also evaluated for its ability to manufacture high drug-loaded ASDs. The highest possible drug loadings that still result in a one-phase amorphous system were obtained for bead coating and its predictive intermittent surface coating technique, followed by spray drying and finally by film casting and the continuous surface coating technique, thereby underlining the importance for further research into the underexplored bead coating process.
Automated Polymer Purification Using Dialysis
Authors: Schuett Timo , Kimmig Julian , Zechel Stefan , Schubert Ulrich S.
Published: September 2020

The automated dialysis of polymers in synthetic robots is described as a first approach for the purification of polymers using an automated protocol. For this purpose, a dialysis apparatus was installed within a synthesis robot. Therein, the polymer solution could be transferred automatically into the dialysis tube. Afterwards, a permanent running dialysis could be started, enabling the removal of residual monomer. Purification efficiency was studied using chromatography and NMR spectroscopy, showing that the automated dialysis requires less solvent and is faster compared to the classical manual approach.
Investigation of Ultrasonic Treatment on Physicochemical, Structural and Morphological Properties of Sodium Alginate/AgNPs/Apple Polyphenol Films and Its Preservation Effect on Strawberry
Authors: Lan Wenting , Li Siying , Shama Shiti , Zhao Yuqing , Sameen Dur E. , He Li , Liu Yaowen
Published: September 2020

An antibacterial and anti-oxidation composite film was prepared by a casting method using sodium alginate (SA) and apple polyphenols (APPs) as the base material and glycerol as the plasticizer. Silver nanoparticles (AgNPs) were deposited by ultrasonic-assisted electrospray method. The degree of influence of the addition ratio of SA and AgNPs and different ultrasonic time on the mechanical properties, barrier properties, optical properties, and hydrophilicity of the composite film was explored. The composite films were characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) and scanning electron microscopy (SEM). The results showed that the SA: AgNPs ratio of 7:3 and the ultrasonic time for 30 min have the best comprehensive performance, and SA/AgNPs/APP films showed the lowest water vapor permeability value of 0.75 × 10−11 g/m·s·Pa. The composite film has good strength and softness, with tensile strength (TS) and elongation at break (E) at 23.94 MPa and 29.18%, respectively. SEM images showed that the surface of the composite film was smooth and the AgNPs’ distribution was uniform. The composite film showed broad antibacterial activity, and the antibacterial activity of Escherichia coli (92.01%) was higher than that of Staphylococcus aureus (91.26%). However, due to the addition of APP, its antioxidant activity can reach 98.39%, which has a synergistic effect on antibacterial activity. For strawberry as a model, the results showed that this composite film can prolong the shelf life of strawberries for about 8 days at 4 °C, effectively maintaining their storage quality. Compared with the commonly used PE(Polyethylene film) film on the market, it has a greater fresh-keeping effect and can be used as an active food packaging material.
Investigation of Roughness Correlation in Polymer Brushes via X-ray Scattering
Authors: Hildebrandt Marcus , Shin Eui-young , Yang Suan , Ali Wael , Altinpinar Sedakat , Gutmann Jochen S.
Published: September 2020

Thin polymer films and coatings are used to tailor the properties of surfaces in various applications such as protection against corrosion, biochemical functionalities or electronic resistors. Polymer brushes are a certain kind of thin polymer films, where polymer chains are covalently grafted to a substrate and straighten up to form a brush structure. Here we report on differences and similarities between polymer brushes and spin-coated polymer films from polystyrene and polymethyl methacrylate with special emphasis on surface roughness and roughness correlation. The phenomenon of roughness correlation or conformality describes the replication of the roughness profile from the substrate surface to the polymer surface. It is of high interest for polymer physics of brush layers as well as applications, in which a homogeneous polymer layer thickness is required. We demonstrate that spin-coated films as well as polymer brushes show roughness correlation, but in contrast to spin-coated films, the correlation in brushes is stable to solvent vapor annealing. Roughness correlation is therefore an intrinsic property of polymer brushes.
Quantum Information Hidden in Quantum Fields
Authors: Zizzi Paola
Published: September 2020

We investigate a possible reduction mechanism from (bosonic) Quantum Field Theory (QFT) to Quantum Mechanics (QM), in a manner that could explain the apparent loss of degrees of freedom of the original theory in terms of quantum information in the reduced one. This reduction mechanism consists mainly of performing an ansatz on the boson field operator, which takes into account quantum foam and non-commutative geometry. Through the reduction mechanism, QFT reveals its hidden internal structure, which is a quantum network of maximally entangled multipartite states. In the end, a new approach to the quantum simulation of QFT is proposed through the use of QFT’s internal quantum network. Finally, the entropic equilibrium of fully mixed and maximally entangled states in the quantum network seems to suggest that the black hole paradox of information loss might be solved under suitable conditions.
Between Love, Renunciation, and Compassionate Heroism: Reading Sanskrit Buddhist Literature through the Prism of Disgust
Authors: Li Shenghai
Published: September 2020

Disgust occupies a particular space in Buddhism where repulsive aspects of the human body are visualized and reflected upon in contemplative practices. The Indian tradition of aesthetics also recognizes disgust as one of the basic human emotions that can be transformed into an aestheticized form, which is experienced when one enjoys drama and poetry. Buddhist literature offers a particularly fertile ground for both religious and literary ideas to manifest, unravel, and entangle in a narrative setting. It is in this context that we find elements of disgust being incorporated into two types of Buddhist narrative: (1) discouragement with worldly objects and renunciation, and (2) courageous act of self-sacrifice. Vidyākara’s anthology of Sanskrit poetry (Subhāṣitaratnakoṣa) and the poetics section of Sa skya Paṇḍita’s introduction to the Indian systems of cultural knowledge (Mkhas pa rnams ’jug pa’i sgo) offer two rare examples of Buddhist engagement with aesthetics of emotions. In addition to some developed views of literary critics, these two Buddhist writers are relied on in this study to provide perspectives on how Buddhists themselves in the final phase of Indian Buddhism might have read Buddhist literature in light of what they learned from the theory of aesthetics.
Exploring Wetland Dynamics in Large River Floodplain Systems with Unsupervised Machine Learning: A Case Study of the Dongting Lake, China
Authors: Jing Lei , Zhou Yan , Zeng Qing , Liu Shuguang , Lei Guangchun , Lu Cai , Wen Li
Published: September 2020

Large river floodplain systems (LRFS) are among the most diverse and dynamic ecosystems. Accurately monitoring the dynamics of LRFS over long time series is fundamental and essential for their sustainable development. However, challenges remain because the spatial distribution of LRFS is never static due to inter- and intra-annual changes in environmental conditions. In this study, we developed and tested a methodological framework to re-construct the long-term wetland dynamics in Dongting Lake, China, utilizing an unsupervised machine-learning algorithm (UMLA) on the basis of MODIS (Moderate Resolution Imaging Spectroradiometer) EVI (Enhanced Vegetation Index) time series. Our results showed that the UMLA achieved comparable performance to the time-consuming satellite image segmentation method with a Kappa coefficient of agreement greater than 0.75 and an overall accuracy over 85%. With the re-constructed annual wetland distribution maps, we found that 31.35% of wet meadows, one of most important ecological assets in the region, disappeared at an average rate of c.a. 1660 ha year−1 during the past two decades, which suggests that the Dongting Lake is losing its ecological function of providing wintering ground for migratory water birds, and remediation management actions are urgently required. We concluded that UMLA offers a fast and cost-efficient alternative to monitor ecological responses in a rapidly changing environment.
Power and/or Penury of Visualizations: Some Thoughts on Remote Sensing Data and Products in Archaeology
Authors: Rączkowski Włodzimierz
Published: September 2020

Airborne and spaceborne remote sensing in archaeology generates at least two important issues for discussion: technology and visualization. Technology seems to open new cognitive perspectives for archaeology and keeps researchers increasingly fascinated in its capabilities (archaeological science being a case in point). Acquired data, especially via remote sensing methods, can be studied after processing and visualizing. The paper raises several issues related to the new cognitive situation of archaeologists facing the development of new technologies within remote sensing methods. These issues are discussed from ontological, epistemological, and discursive perspectives, supporting an exploration of the role of technology and visualization. The ontological perspective places the visualization of remote sensing data in the context of understanding Virtual Reality and Jean Baudrillard’s simulacra. The epistemological perspective generates questions related to visualization as mimesis, the issue of cultural neutrality, and the use of sophisticated classifications and analytical techniques. The level of discursiveness of visualization includes categories such as persuasion, standardization, and aesthetics. This discussion is framed in relation to Martin Heidegger’s understanding of technology and a dichotomy of naturalism versus antinaturalism.
Investigation of Chromatic Aberration and Its Influence on the Processing of Underwater Imagery
Authors: Helmholz Petra , Lichti Derek D.
Published: September 2020

The number of researchers utilising imagery for the 3D reconstruction of underwater natural (e.g., reefs) and man-made structures (e.g., shipwrecks) is increasing. Often, the same procedures and software solutions are used for processing the images as in-air without considering additional aberrations that can be caused by the change of the medium from air to water. For instance, several publications mention the presence of chromatic aberration (CA). The aim of this paper is to investigate CA effects in low-cost camera systems (several GoPro cameras) operated in an underwater environment. We found that underwater and in-air distortion profiles differed by more than 1000 times in terms of maximum displacement and in terms of curvature. Moreover, significant CA effects were found in the underwater profiles that did not exist in-air. Furthermore, the paper investigates the effect of adjustment constraints imposed on the underwater self-calibration and the reliability of the interior orientation parameters. The analysis of the precision shows that in-air RMS values are just due to random errors. In contrast, the underwater calibration RMS values are 3x-6x higher than the exterior orientation parameter (EOP) precision, so these values contain both random error and the systematic effects from the CA. The accuracy assessment shows significant differences.
An Effective Method for Detecting Clouds in GaoFen-4 Images of Coastal Zones
Authors: Wang Zheng , Du Jun , Xia Junshi , Chen Cheng , Zeng Qun , Tian Liqiao , Wang Lihui , Mao Zhihua
Published: September 2020

Cloud-cover information is important for a wide range of scientific studies, such as the studies on water supply, climate change, earth energy budget, etc. In remote sensing, correct detection of clouds plays a crucial role in deriving the physical properties associated with clouds that exert a significant impact on the radiation budget of planet earth. Although the traditional cloud detection methods have generally performed well, these methods were usually developed specifically for particular sensors in a particular region with a particular underlying surface (e.g., land, water, vegetation, and man-made objects). Coastal regions are known to have a variety of underlying surfaces, which represent a major challenge in cloud detection. Therefore, there is an urgent requirement for developing a cloud detection method that could be applied to a variety of sensors, situations, and underlying surfaces. In the present study, a cloud detection method based on spatial and spectral uniformity of clouds was developed. In addition to having a spatially uniform texture, a spectrally approximate value was also present between the blue and green bands of the cloud region. The blue and green channel data appeared more uniform over the cloudy region, i.e., the entropy of the cloudy region was lower than that of the cloud-free region. On the basis of this difference in entropy, it would be possible to categorize the satellite images into cloud region images and cloud-free region images. Furthermore, the performance of the proposed method was validated by applying it to the data from various sensors across the coastal zone of the South China Sea. The experimental results demonstrated that compared to the existing operational algorithms, EN-clustering exhibited higher accuracy and scalability, and also performed robustly regardless of the spatial resolution of the different satellite images. It is concluded that the EN-clustering algorithm proposed in the present study is applicable to different sensors, different underlying surfaces, and different regions, with the support of NDSI and NDBI indices to remove the interference information from snow, ice, and man-made objects.
A Fast and Effective Method for Unsupervised Segmentation Evaluation of Remote Sensing Images
Authors: Zhao Maofan , Meng Qingyan , Zhang Linlin , Hu Die , Zhang Ying , Allam Mona
Published: September 2020

The segmentation of remote sensing images with high spatial resolution is important and fundamental in geographic object-based image analysis (GEOBIA), so evaluating segmentation results without prior knowledge is an essential part in segmentation algorithms comparison, segmentation parameters selection, and optimization. In this study, we proposed a fast and effective unsupervised evaluation (UE) method using the area-weighted variance (WV) as intra-segment homogeneity and the difference to neighbor pixels (DTNP) as inter-segment heterogeneity. Then these two measures were combined into a fast-global score (FGS) to evaluate the segmentation. The effectiveness of DTNP and FGS was demonstrated by visual interpretation as qualitative analysis and supervised evaluation (SE) as quantitative analysis. For this experiment, the ‘‘Multi-resolution Segmentation’’ algorithm in eCognition was adopted in the segmentation and four typical study areas of GF-2 images were used as test data. The effectiveness analysis of DTNP shows that it can keep stability and remain sensitive to both over-segmentation and under-segmentation compared to two existing inter-segment heterogeneity measures. The effectiveness and computational cost analysis of FGS compared with two existing UE methods revealed that FGS can effectively evaluate segmentation results with the lowest computational cost.
Incorporating Deep Features into GEOBIA Paradigm for Remote Sensing Imagery Classification: A Patch-Based Approach
Authors: Liu Bo , Du Shihong , Du Shouji , Zhang Xiuyuan
Published: September 2020

The fast and accurate creation of land use/land cover maps from very-high-resolution (VHR) remote sensing imagery is crucial for urban planning and environmental monitoring. Geographic object-based image analysis methods (GEOBIA) provide an effective solution using image objects instead of individual pixels in VHR remote sensing imagery analysis. Simultaneously, convolutional neural networks (CNN) have been widely used in the image processing field because of their powerful feature extraction capabilities. This study presents a patch-based strategy for integrating deep features into GEOBIA for VHR remote sensing imagery classification. To extract deep features from irregular image objects through CNN, a patch-based approach is proposed for representing image objects and learning patch-based deep features, and a deep features aggregation method is proposed for aggregating patch-based deep features into object-based deep features. Finally, both object and deep features are integrated into a GEOBIA paradigm for classifying image objects. We explored the influences of segmentation scales and patch sizes in our method and explored the effectiveness of deep and object features in classification. Moreover, we performed 5-fold stratified cross validations 50 times to explore the uncertainty of our method. Additionally, we explored the importance of deep feature aggregation, and we evaluated our method by comparing it with three state-of-the-art methods in a Beijing dataset and Zurich dataset. The results indicate that smaller segmentation scales were more conducive to VHR remote sensing imagery classification, and it was not appropriate to select too large or too small patches as the patch size should be determined by imagery and its resolution. Moreover, we found that deep features are more effective than object features, while object features still matter for image classification, and deep feature aggregation is a critical step in our method. Finally, our method can achieve the highest overall accuracies compared with the state-of-the-art methods, and the overall accuracies are 91.21% for the Beijing dataset and 99.05% for the Zurich dataset.
Comparison of Different Missing-Imputation Methods for MAIAC (Multiangle Implementation of Atmospheric Correction) AOD in Estimating Daily PM2.5 Levels
Authors: Chen Zhao-Yue , Jin Jie-Qi , Zhang Rong , Zhang Tian-Hao , Chen Jin-Jian , Yang Jun , Ou Chun-Quan , Guo Yuming
Published: September 2020

The immense problem of missing satellite aerosol retrievals (Aerosol Optical Depth, (AOD)) detrimentally affects the prediction ability of ground-level PM2.5 concentrations and may lead to unavoidable biases. An appropriate missing-imputation method has not been well developed to date. This study developed a two-stage approach (AOD-imputation stage and PM2.5-prediction stage) to predict short-term PM2.5 exposure in mainland China from 2013–2018. At the AOD-imputation stage, geostatistical methods and machine learning (ML) algorithms were examined to interpolate 1 km satellite aerosol retrievals. At the PM2.5-prediction stage, the daily levels of PM2.5 were predicted at a resolution of 1 km, based on interpolated AOD and meteorological data. The statistical performances of the different interpolation methods were comprehensively compared at each stage. The original coverage of retrieved AOD was 15.46% on average. For the AOD-imputation stage, ML methods produced a higher coverage (98.64%) of AOD than geostatistical methods (21.43–87.31%). Among ML algorithms, random forest (RF) or extreme gradient boosted (XG-interpolated) AOD produced better interpolated quality (CV R2 = 0.89 and 0.85) than other algorithms (0.49–0.78), but XGBoost required only 15% of the computing time of RF. For the PM2.5 predicted stage, neither RF-AOD nor XG-AOD could guarantee higher accuracy in PM2.5 estimations (CV R2 = 0.88 (RF or XG-AOD) compared to 0.85 (original)), or more stable spatial and temporal extrapolation (spatial, (temporal) CV R2 = 0.83 (0.83), 0.82 (0.82), and 0.65 (0.61) for RF, XG, and original). For the AOD-imputation stage, the missing-filled efficiency depended more on external information, while the missing-filled accuracy relied more on model structure. For the PM2.5 predicted stage, efficient AOD interpolation (or the ability to eliminate the missing data) was a precondition for the stable spatial and temporal extrapolation, while the quality of interpolated AOD showed less significant improvements. It was found that XG-AOD is a better choice to estimate daily PM2.5 exposure in health assessments.
A Highly Accurate, Polynomial-Based Digital Temperature Compensation for Piezoresistive Pressure Sensor in 180 nm CMOS Technology
Authors: Ali Imran , Asif Muhammad , Shehzad Khuram , Rehman Muhammad Riaz Ur , Kim Dong Gyu , Rikan Behnam Samadpoor , Pu YoungGun , Yoo Sang Sun , Lee Kang-Yoon
Published: September 2020

Recently, piezoresistive-type (PRT) pressure sensors have been gaining attention in variety of applications due to their simplicity, low cost, miniature size and ruggedness. The electrical behavior of a pressure sensor is highly dependent on the temperature gradient which seriously degrades its reliability and reduces measurement accuracy. In this paper, polynomial-based adaptive digital temperature compensation is presented for automotive piezoresistive pressure sensor applications. The non-linear temperature dependency of a pressure sensor is accurately compensated for by incorporating opposite characteristics of the pressure sensor as a function of temperature. The compensation polynomial is fully implemented in a digital system and a scaling technique is introduced to enhance its accuracy. The resource sharing technique is adopted for minimizing controller area and power consumption. The negative temperature coefficient (NTC) instead of proportional to absolute temperature (PTAT) or complementary to absolute temperature (CTAT) is used as the temperature-sensing element since it offers the best temperature characteristics for grade 0 ambient temperature operating range according to the automotive electronics council (AEC) test qualification ACE-Q100. The shared structure approach uses an existing analog signal conditioning path, composed of a programmable gain amplifier (PGA) and an analog-to-digital converter (ADC). For improving the accuracy over wide range of temperature, a high-resolution sigma-delta ADC is integrated. The measured temperature compensation accuracy is within ±0.068% with full scale when temperature varies from −40 °C to 150 °C according to ACE-Q100. It takes 37 µs to compute the temperature compensation with a clock frequency of 10 MHz. The proposed technique is integrated in an automotive pressure sensor signal conditioning chip using a 180 nm complementary metal–oxide–semiconductor (CMOS) process.
Hybrid Attention Network for Language-Based Person Search
Authors: Li Yang , Xu Huahu , Xiao Junsheng
Published: September 2020

Language-based person search retrieves images of a target person using natural language description and is a challenging fine-grained cross-modal retrieval task. A novel hybrid attention network is proposed for the task. The network includes the following three aspects: First, a cubic attention mechanism for person image, which combines cross-layer spatial attention and channel attention. It can fully excavate both important midlevel details and key high-level semantics to obtain better discriminative fine-grained feature representation of a person image. Second, a text attention network for language description, which is based on bidirectional LSTM (BiLSTM) and self-attention mechanism. It can better learn the bidirectional semantic dependency and capture the key words of sentences, so as to extract the context information and key semantic features of the language description more effectively and accurately. Third, a cross-modal attention mechanism and a joint loss function for cross-modal learning, which can pay more attention to the relevant parts between text and image features. It can better exploit both the cross-modal and intra-modal correlation and can better solve the problem of cross-modal heterogeneity. Extensive experiments have been conducted on the CUHK-PEDES dataset. Our approach obtains higher performance than state-of-the-art approaches, demonstrating the advantage of the approach we propose.
CoNTe: A Core Network Temporal Blockchain for 5G
Authors: Platt Steven , Sanabria-Russo Luis , Oliver Miquel
Published: September 2020

Virtual Network Functions allow the effective separation between hardware and network functionality, a strong paradigm shift from previously tightly integrated monolithic, vendor, and technology dependent deployments. In this virtualized paradigm, all aspects of network operations can be made to deploy on demand, dynamically scale, as well as be shared and interworked in ways that mirror behaviors of general cloud computing. To date, although seeing rising demand, distributed ledger technology remains largely incompatible in such elastic deployments, by its nature as functioning as an immutable record store. This work focuses on the structural incompatibility of current blockchain designs and proposes a novel, temporal blockchain design built atop federated byzantine agreement, which has the ability to dynamically scale and be packaged as a Virtual Network Function (VNF) for the 5G Core.
Risk Assessment and Monitoring of Green Logistics for Fresh Produce Based on a Support Vector Machine
Authors: Zhang Guoquan , Li Guohao , Peng Jing
Published: September 2020

The sustainability and profitability of fresh produce supply chains are contingent upon several risk factors. This work, therefore, examines several risk indicators that affect the quality and safety of fresh produce in transit, including technological, biological, sustainability, environmental, and emergency risks. Then, we developed a risk assessment and monitoring model that employs a machine learning algorithm, a support vector machine, based on historical monitoring data. The proposed methodology was then applied to simulation and numerical analysis to assess the risks incurred in the strawberry cold chain. After training, the algorithm predicted the risks incurred during transportation with an average accuracy of 90.4%. Therefore, the developed methodology can effectively and accurately perform a risk assessment. Furthermore, the risk assessment model can be applied to other fresh produce due to comprehensive risk indicators. Decision-makers in fresh produce logistics companies can use the developed methodology to identify and mitigate risks incurred, thus improving food safety, reducing product loss, maximizing profits, and realizing sustainable development.
Improving Water Distribution Uniformity by Optimizing the Structural Size of the Drive Spoon Blades for a Vertical Impact Sprinkler
Authors: Tang Pan , Chen Chao , Li Hong
Published: September 2020

The aim of this study is to improve the water distribution uniformity of a vertical impact sprinkler and explore the design method of the drive spoon blades. The width of straight blades (h1), the width of curved blades (h2) and number of blades (s) were chosen as the experiential variables. The suitable ranges of three variables for response surface method were determined initially by one-factor experimental design method, and 17 different drive spoons were designed according to response surface methodology. The results showed that in the one-factor experimental condition, the CU (Christiansen’s uniformity coefficient) values first increased and decreased slightly when h1 exceeded 3 mm with the increase of h1 within the variation range of the experimental factor. The CU values firstly increased and then decreased with the increase of h2. The CU values decreased rapidly when s was less than 3 or greater than 6. The relationship between CU values and h1, h2 and s was established using response surface methodology. The p-values for h1, h2 and s were 0.0359, 0.0092, 0.0212, and all of the selected factors were significant on CU. The order of parameters affecting CU were h2, h1 and s. The ideal parameters for the drive spoon blades were h1 = 6 mm, h2 = 4 mm, and s = 3. CU was greatly improved after the optimization of structure for the drive spoon blades, which increased to 87.96% from 73.12%. After optimization, the application rates within 1 to 5 m were improved and increased from 10% to 15% with an average of 10.7% under different operating pressures. The maximum application rates decreased from 9.3, 9.3, 9.4 and 8.4 mm·h−1 to 8.5, 8.4, 8.5 and 7.9 mm·h−1 with operating pressures of 300, 400, 500 and 600 kPa, respectively. The maximum application rates in the overlap area were decreased from 18, 16, 16 and 15 mm·h−1 to 16, 14, 14 and 12 mm·h−1 with operating pressures of 300, 400, 500 and 600 kPa, respectively.
SME Default Prediction Framework with the Effective Use of External Public Credit Data
Authors: Luo Zhichao , Hsu Pingyu , Xu Ni
Published: September 2020

Traditional default prediction models mainly rely on financial data. However, financial data on small and medium-sized enterprises (SMEs) are difficult to obtain, and even when they are available, their opaqueness may hinder analysis. Therefore, traditional prediction models encounter serious problems when being utilized to predict the defaulting of SMEs. In this paper, a novel prediction framework utilizing only external public credit data is proposed. The external public credit data used include SMEs’ basic information (BI), credit information from the government (CIG), and court verdict information (CVI), which can be collected from publicly accessible websites. Records on 15,605 sample companies were collected from approximately 300,000 companies. Among them, 8183 have defaulted. The empirical data were applied to construct prediction models using logistic regression, the classification and regression tree (CART) model, and LightGBM. The best results achieved 0.87 accuracy and 0.92 area under receiver operating characteristic (AUC). The results show that the model only uses the external credit data proven to have significant predict ability, and CIG variables offer the best prediction capacities.
Exploring Paradoxical Tensions in Circular Business Models—Cases from North Europe
Authors: Huerta Morales Alberto
Published: September 2020

Circular Business Models (CBMs) are a tool that allows private sector organizations to reconcile circularity (i.e., narrowing, slowing and closing resource flows) and commercial value creation. However, these two elements are not always aligned; they can be contradictory. This makes the relationship between circularity and commercial value creation, in the context of CBMs, a paradoxical tension. These types of tensions are particularly challenging since the elements that create the tension cannot be removed, instead, both elements must remain in place and the tension between them must be continuously managed. This article explores the main paradoxical tensions and management strategies in the context of CBMs through an integrative literature review as well as an empirical study. The integrative review helped identify three literature streams that provide key insights regarding paradoxical tensions of CBMs, namely corporate sustainability, servitization and circular economy. The empirical study suggested six paradoxical tensions inherent to CBMs: (1) using waste as a resource; (2) design of circular products; (3) improving aesthetics of used products; (4) matching supply and demand; (5) Balancing costs in circular activities; and (6) managing resistance from the value chain. The findings from the literature review as well as the empirical study are compared and discussed. Overall, this article sheds light on the paradoxical tension between circularity and commercial value creation that sits at the core of CBMs as well as the potential managerial strategies suitable for dealing with this tension.