bluuebunny/crossref_metadata_2025 huggingface dataset:
The Influence of Different Pre-Treatments on the Quality and Nutritional Characteristics in Dried Undersized Yellow Kiwifruit
Authors: Mannozzi Cinzia , Tylewicz Urszula , Tappi Silvia , Dalla Rosa Marco , Rocculi Pietro , Romani Santina
Published: November 2020

Undersized kiwifruits are considered waste; therefore, there is a need to develop sustainable processing technologies for their valorization, in order to have a positive economic impact on their entire production chain. Therefore, the aim of this study was to apply pulsed electric fields (PEF) combined with osmotic dehydration (OD) and air drying (AD) to develop a novel yellow kiwifruit dried snack with high nutritional functionality. In particular, the effect of the different pre-treatments, PEF (200 V/cm) and/or OD (trehalose at 40%), on the color, bioactive compounds content and antioxidant activity (AA) was evaluated on kiwifruit chips air-dried at three different temperatures (50, 60, 70 °C). The results showed that better color maintenance was observed at the drying temperature of 60 °C. Concerning the bioactive compounds, a good retention in total polyphenols (TP), vitamin C content and AA with the DPPH method was obtained on OD and PEF kiwifruit dried snacks, similar to that of control samples. Instead, the ABTS method showed the best AA in PEF and OD/PEF samples. In general, a shorter drying time in the OD- and PEF-treated samples could contribute to the higher sustainability of the process.
Targeted Protein Degradation Tools: Overview and Future Perspectives
Authors: Prozzillo Yuri , Fattorini Gaia , Santopietro Maria Virginia , Suglia Luigi , Ruggiero Alessandra , Ferreri Diego , Messina Giovanni
Published: November 2020

Targeted protein inactivation (TPI) is an elegant approach to investigate protein function and its role in the cellular landscape, overcoming limitations of genetic perturbation strategies. These systems act in a reversible manner and reduce off-target effects exceeding the limitations of CRISPR/Cas9 and RNA interference, respectively. Several TPI have been developed and wisely improved, including compartment delocalization tools and protein degradation systems. However, unlike chemical tools such as PROTACs (PROteolysis TArgeting Chimeras), which work in a wild-type genomic background, TPI technologies require adding an aminoacidic signal sequence (tag) to the protein of interest (POI). On the other hand, the design and optimization of PROTACs are very laborious and time-consuming. In this review, we focus on anchor-away, deGradFP, auxin-inducible degron (AID) and dTAG technologies and discuss their recent applications and advances. Finally, we propose nano-grad, a novel nanobody-based protein degradation tool, which specifically proteolyzes endogenous tag-free target protein.
Label-Free Optical Biosensing Using Low-Cost Electrospun Polymeric Nanofibers
Authors: Martínez-Pérez Paula , Ponce-Alcántara Salvador , Murillo Nieves , Pérez-Márquez Ana , Maudes Jon , Peraile Inés , González-López Laura , Gil-García Matilde , Lorenzo-Lozano Paloma , García-Rupérez Jaime
Published: November 2020

Polymeric nanofiber matrices are promising structures to develop biosensing devices due to their easy and affordable large-scale fabrication and their high surface-to-volume ratio. In this work, the suitability of a polyamide 6 nanofiber matrix for the development of a label-free and real-time Fabry–Pérot cavity-based optical biosensor was studied. For such aim, in-flow biofunctionalization of nanofibers with antibodies, bound through a protein A/G layer, and specific biodetection of 10 µg/mL bovine serum albumin (BSA) were carried out. Both processes were successfully monitored via reflectivity measurements in real-time without labels and their reproducibility was demonstrated when different polymeric nanofiber matrices from the same electrospinning batch were employed as transducers. These results demonstrate not only the suitability of correctly biofunctionalized polyamide 6 nanofiber matrices to be employed for real-time and label-free specific biodetection purposes, but also the potential of electrospinning technique to create affordable and easy-to-fabricate at large scale optical transducers with a reproducible performance.
Modeling the Impacts of Climate Change on Crop Yield and Irrigation in the Monocacy River Watershed, USA
Authors: Paul Manashi , Dangol Sijal , Kholodovsky Vitaly , Sapkota Amy R. , Negahban-Azar Masoud , Lansing Stephanie
Published: November 2020

Crop yield depends on multiple factors, including climate conditions, soil characteristics, and available water. The objective of this study was to evaluate the impact of projected temperature and precipitation changes on crop yields in the Monocacy River Watershed in the Mid-Atlantic United States based on climate change scenarios. The Soil and Water Assessment Tool (SWAT) was applied to simulate watershed hydrology and crop yield. To evaluate the effect of future climate projections, four global climate models (GCMs) and three representative concentration pathways (RCP 4.5, 6, and 8.5) were used in the SWAT model. According to all GCMs and RCPs, a warmer climate with a wetter Autumn and Spring and a drier late Summer season is anticipated by mid and late century in this region. To evaluate future management strategies, water budget and crop yields were assessed for two scenarios: current rainfed and adaptive irrigated conditions. Irrigation would improve corn yields during mid-century across all scenarios. However, prolonged irrigation would have a negative impact due to nutrients runoff on both corn and soybean yields compared to rainfed condition. Decision tree analysis indicated that corn and soybean yields are most influenced by soil moisture, temperature, and precipitation as well as the water management practice used (i.e., rainfed or irrigated). The computed values from the SWAT modeling can be used as guidelines for water resource managers in this watershed to plan for projected water shortages and manage crop yields based on projected climate change conditions.
Genetic Differentiation and Population Structure of Threatened Prunus africana Kalm. in Western Cameroon Using Molecular Markers
Authors: Nzweundji Justine G. , Huewe Ulrike , Niemenak Nicolas , Donfagsiteli Néhémie T. , Eimert Klaus
Published: November 2020

Genetic diversity of species is an important baseline for the domestication process. In Cameroon, Prunus africana, an important and threatened medicinal tree, is among the priority species for domestication. The bark extract has been used to treat various diseases; mainly benign prostatic hyperplasia which affects men above the age of 50. As little is known about the genetic diversity of P. africana in Cameroon, we aimed to determine the genetic diversity and differentiation of several P. africana populations in the western provinces, using sets of chloroplast DNA markers and nuclear microsatellites previously developed for Prunus species. Genetic diversity in the observed populations was considerable and genetic differentiation between populations proved substantial with 21% of the total observed variation detected among populations, revealing a distinct genetic structure among certain populations. However, the lack of correlation between genetic and geographic distances does not support isolation by distance (IBD). The analysis of chloroplast DNA haplotypes revealed no strong phylogeographic component in the genetic structure observed in the western populations of P. africana in Cameroon. The outcome of this study will contribute to improve the genetic characterization of P. africana for its better domestication and conservation in the Cameroon agroforestry system.
Development, Modeling and Control of a Dual Tilt-Wing UAV in Vertical Flight
Authors: Sanchez-Rivera Luz M. , Lozano Rogelio , Arias-Montano Alfredo
Published: November 2020

Hybrid Unmanned Aerial Vehicles (H-UAVs) are currently a very interesting field of research in the modern scientific community due to their ability to perform Vertical Take-Off and Landing (VTOL) and Conventional Take-Off and Landing (CTOL). This paper focuses on the Dual Tilt-wing UAV, a vehicle capable of performing both flight modes (VTOL and CTOL). The UAV complete dynamic model is obtained using the Newton–Euler formulation, which includes aerodynamic effects, as the drag and lift forces of the wings, which are a function of airstream generated by the rotors, the cruise speed, tilt-wing angle and angle of attack. The airstream velocity generated by the rotors is studied in a test bench. The projected area on the UAV wing that is affected by the airstream generated by the rotors is specified and 3D aerodynamic analysis is performed for this region. In addition, aerodynamic coefficients of the UAV in VTOL mode are calculated by using Computational Fluid Dynamics method (CFD) and are embedded into the nonlinear dynamic model. To validate the complete dynamic model, PD controllers are adopted for altitude and attitude control of the vehicle in VTOL mode, the controllers are simulated and implemented in the vehicle for indoor and outdoor flight experiments.
Integrated Outreach: Increasing Engagement in Computer Science and Cybersecurity
Authors: Wolf Shaya , Burrows Andrea Carneal , Borowczak Mike , Johnson Mason , Cooley Rafer , Mogenson Kyle
Published: November 2020

Research on innovative, integrated outreach programs guided three separate week-long outreach camps held across two summers (2018 and 2019). These camps introduced computer science through real-world applications and hands-on activities, each dealing with cybersecurity principles. The camps utilized low-cost hardware and free software to provide a total of 84 students (aged 10 to 18 years) a unique learning experience. Based on feedback from the 2018 camp, a new pre/post survey was developed to assess changes in participant knowledge and interest. Student participants in the 2019 iteration showed drastic changes in their cybersecurity content recall (33% pre vs. 96% post), cybersecurity concept identification within real-world scenarios, and exhibited an increased ability to recognize potential cybersecurity threats in their every-day lives (22% pre vs. 69% post). Finally, students’ self-reported interest-level before and after the camp show a positive increase across all student participants, with the number of students who where highly interested in cybersecurity more than doubling from 31% pre-camp to 65% post-camp. Implications for educators are large as these activities and experiences can be interwoven into traditional schooling as well as less formal camps as pure computer science or through integrated STEM.
Optimal Design of High-Frequency Induction Heating Apparatus for Wafer Cleaning Equipment Using Superheated Steam
Authors: Park Sang Min , Jang Eunsu , Park Joon Sung , Kim Jin-Hong , Choi Jun-Hyuk , Lee Byoung Kuk
Published: November 2020

In this study, wafer cleaning equipment was designed and fabricated using the induction heating (IH) method and a short-time superheated steam (SHS) generation process. To prevent problems arising from the presence of particulate matter in the fluid flow region, pure grade 2 titanium (Ti) R50400 was used in the wafer cleaning equipment for heating objects via induction. The Ti load was designed and manufactured with a specific shape, along with the resonant network, to efficiently generate high-temperature steam by increasing the residence time of the fluid in the heating object. The IH performance of various shapes of heating objects made of Ti was analyzed and the results were compared. In addition, the heat capacity required to generate SHS was mathematically calculated and analyzed. The SHS heating performance was verified by conducting experiments using the designed 2.2 kW wafer cleaning equipment. The performance of the proposed pure Ti-based SHS generation system was found to be satisfactory, and SHS with a temperature higher than 200 °C was generated within 10 s using this system.
Cost-Effective Outage Management in Smart Grid under Single, Multiple, and Critical Fault Conditions through Teaching–Learning Algorithm
Authors: S Thiruvenkadam , Ra In-Ho , Kim Hyung-Jin
Published: November 2020

A distribution system becomes the most essential part of a power system as it links the utility and utility customers. Under abnormal conditions of the system, a definitive goal of the utility is to provide continuous power supply to the customers. This demands a fast restoration process and provision of optimal solutions without violating the power system operational constraints. The main objective of the proposed work is to reduce the service restoration cost (SRC) along with the elimination of the out-of-service loads. In addition, this work concentrates on the minimal usage and finding of optimal locations for additional equipment, such as capacitor placement (CP) and distributed generators (DGs). This paper proposes a two-stage strategy, namely, the service restoration phase and optimization phase. The first phase ensures the restoration of the system from the fault condition, and the second phase identifies the optimal solution with reconfiguration, CP, and DG placement. The optimization phase uses the teaching–learning algorithm (TLA) for optimal restructuring and optimal capacitor and DG placement. The robustness of the algorithm is validated by addressing the test cases under different fault conditions, such as single, multiple, and critical. The effectiveness of the proposed strategy is exhibited with the implementation to IEEE 33-bus radial distribution system (RDS) and 83-bus Taiwan Power Distribution Company (TPDC) System.
A Novel Analytical-ANN Hybrid Model for Borehole Heat Exchanger
Authors: Puttige Anjan Rao , Andersson Staffan , Östin Ronny , Olofsson Thomas
Published: November 2020

Optimizing the operation of ground source heat pumps requires simulation of both short-term and long-term response of the borehole heat exchanger. However, the current physical and neural network based models are not suited to handle the large range of time scales, especially for large borehole fields. In this study, we present a hybrid model for long-term simulation of BHE with high resolution in time. The model uses an analytical model with low time resolution to guide an artificial neural network model with high time resolution. We trained, tuned, and tested the hybrid model using measured data from a ground source heat pump in real operation. The performance of the hybrid model is compared with an analytical model, a calibrated analytical model, and three different types of neural network models. The hybrid model has a relative RMSE of 6% for the testing period compared to 22%, 14%, and 12% respectively for the analytical model, the calibrated analytical model, and the best of the three investigated neural network models. The hybrid model also has a reasonable computational time and was also found to be robust with regard to the model parameters used by the analytical model.
CO2 Injection and Enhanced Oil Recovery in Ohio Oil Reservoirs—An Experimental Approach to Process Understanding
Authors: Valluri Manoj Kumar , Zhou Jimin , Mishra Srikanta , Mohanty Kishore
Published: November 2020

Process understanding of CO2 injection into a reservoir is a crucial step for planning a CO2 injection operation. CO2 injection was investigated for Ohio oil reservoirs which have access to abundant CO2 from local coal-fired power plants and industrial facilities. In a first of its kind study in Ohio, lab-scale core characterization and flooding experiments were conducted on two of Ohio’s most prolific oil and gas reservoirs—the Copper Ridge dolomite and Clinton sandstone. Reservoir properties such as porosity, permeability, capillary pressure, and oil–water relative permeability were measured prior to injecting CO2 under and above the minimum miscibility pressure (MMP) of the reservoir. These evaluations generated reservoir rock-fluid data that are essential for building reservoir models in addition to providing insights on injection below and above the MMP. Results suggested that the two Ohio reservoirs responded positively to CO2 injection and recovered additional oil. Copper Ridge reservoir’s incremental recovery ranged between 20% and 50% oil originally in place while that of Clinton sandstone ranged between 33% and 36% oil originally in place. It was also deduced that water-alternating-gas injection schemes can be detrimental to production from tight reservoirs such as the Clinton sandstone.
Sustainable Anodes for Lithium- and Sodium-Ion Batteries Based on Coffee Ground-Derived Hard Carbon and Green Binders
Authors: Darjazi Hamideh , Staffolani Antunes , Sbrascini Leonardo , Bottoni Luca , Tossici Roberto , Nobili Francesco
Published: November 2020

The reuse and recycling of products, leading to the utilization of wastes as key resources in a closed loop, is a great opportunity for the market in terms of added value and reduced environmental impact. In this context, producing carbonaceous anode materials starting from raw materials derived from food waste appears to be a possible approach to enhance the overall sustainability of the energy storage value chain, including Li-ion (LIBs) and Na-ion batteries (NIBs). In this framework, we show the behavior of anodes for LIBs and NIBs prepared with coffee ground-derived hard carbon as active material, combined with green binders such as Na-carboxymethyl cellulose (CMC), alginate (Alg), or polyacrylic acid (PAA). In order to evaluate the effect of the various binders on the charge/discharge performance, structural and electrochemical investigations are carried out. The electrochemical characterization reveals that the alginate-based anode, used for NIBs, delivers much enhanced charge/discharge performance and capacity retention. On the other hand, the use of the CMC-based electrode as LIBs anode delivers the best performance in terms of discharge capacity, while the PAA-based electrode shows enhanced cycling stability. As a result, the utilization of anode materials derived from an abundant food waste, in synergy with the use of green binders and formulations, appears to be a viable opportunity for the development of efficient and sustainable Li-ion and Na-ion batteries.
Exergy Evaluation of a Water Distribution System
Authors: Bylka Jedrzej , Mróz Tomasz
Published: November 2020

The water supply system is one of the most important elements in a city. Currently, many cities struggle with a water deficit problem. Water is a commonly available resource and constitutes the majority of land cover; however, its quality, in many cases, makes it impossible to use as drinking water. To treat and distribute water, it is necessary to supply a certain amount of energy to the system. An important goal of water utility operators is to assess the energy efficiency of the processes and components. Energy assessments are usually limited to the calculation of energy dissipation (sometimes called “energy loss”). From a physical point of view, the formulation of “energy loss” is incorrect; energy in water transport systems is not consumed but only transformed (dissipated) into other, less usable forms. In the water supply process, the quality of energy—exergy (ability to convert into another form)—is consumed; hence, a new evaluation approach is needed. The motivation for this study was the fact that there are no tools for exergy evaluation of water distribution systems. A model of the exergy balances for a water distribution system was proposed, which was tested for the selected case studies of a water supply system and a water treatment station. The tool developed allows us to identify the places with the highest exergy destructions. In the analysed case studies, the highest exergy destruction results from excess pressure (3939 kWh in a water supply system and 1082 kWh in a water treatment plant). The exergy analysis is more accurate for assessing the system compared to the commonly used energy-based methods. The result can be used for assessing and planning water supply system modernisation.
Prediction of Cooling Energy Consumption in Hotel Building Using Machine Learning Techniques
Authors: Borowski Marek , Zwolińska Klaudia
Published: November 2020

The diversification of energy sources in buildings and the interdependence as well as communication between HVAC installations in the building have resulted in the growing interest in energy load prediction systems that enable proper management of energy resources. In addition, energy storage and the creation of energy buffers are also important in terms of proper resource management, for which it is necessary to correctly determine energy consumption over time. It is obvious that the consumption of cooling energy depends on meteorological conditions. Knowing the parameters of the outside air and the number of users, it is, therefore, possible to determine the hourly energy consumption of a cooling system in a building with some accuracy. The article presents models of cooling energy prediction in summer for a hotel building in southern Poland. The paper presents two methods that are often used for energy prediction: neural networks and support vector machines. Meteorological data, time data, and occupancy level were used as input parameters. Based on the collected input and output data, various configurations were tested to identify the model with the best accuracy. As the analysis showed, higher prediction accuracy was obtained thanks to the use of neural networks. The best of the proposed models was characterized by the WAPE and CV coefficients of 19.93% and 27.03%, respectively.
Determination of Firebrand Characteristics Using Thermal Videos
Authors: Prohanov Sergey , Filkov Alexander , Kasymov Denis , Agafontsev Mikhail , Reyno Vladimir
Published: November 2020

Burning firebrands generated by wildland or prescribed fires may lead to the initiation of spot fires and fire escapes. At the present time, there are no methods that provide information on the thermal characteristics and number of such firebrands with high spatial and temporal resolution. A number of algorithms have been developed to detect and track firebrands in field conditions in our previous study; however, each holds particular disadvantages. This work is devoted to the development of new algorithms and their testing and, as such, several laboratory experiments were conducted. Wood pellets, bark, and twigs of pine were used to generate firebrands. An infrared camera (JADE J530SB) was used to obtain the necessary thermal video files. The thermograms were then processed to create an annotated IR video database that was used to test both the detector and the tracker. Following these studies, the analysis showed that the Difference of Gaussians detection algorithm and the Hungarian tracking algorithm upheld the highest level of accuracy and were the easiest to implement. The study also indicated that further development of detection and tracking algorithms using the current approach will not significantly improve their accuracy. As such, convolutional neural networks hold high potential to be used as an alternative approach.
Identification of the Volatile Compounds and Sensory Attributes of Long-Term Aging Vin Santo Wine from Malvasia di Candia Aromatic Grapes
Authors: Laureati Monica , Cattaneo Camilla , Tateo Fernando , Bononi Monica
Published: November 2020

In an effort to offer a contribution to fill the gap of knowledge about the relationship between the sensory properties and aromatic profile of Malvasia grapes, the present work was aimed at evaluating volatile compounds, aroma, and sensory attributes of long-term aging (15 years) Vin Santo wine obtained from Malvasia di Candia aromatica grapes. In this article, the aromatic profile are studied using gas chromatography-mass spectrometry (GC-MS), gas chromatography with flame ionization detection (GC-FID), and sensory analysis by involving a panel of trained assessors to explore the sensory profile resulting after long-term aging (up to 15 years). The GC-MS and GC-FID analyses of wines allowed the identification and semi-quantification of twenty-seven volatiles belonging to 12 conventional groups of compounds. From a sensory perspective, the Vin Santo wines analyzed in this study presented a very complex sensory profile characterized by 19 sensory descriptors of which 14 related to olfactory terms. The relationship between sensory and GC-FID data deduced from three samples representing nearly three years in the past 15 years was investigated by means of Partial Least Square (PLS) modeling, showing that specific volatile compounds could predict a specific orthonasal and/or retronasal odor perceived by the trained panel of assessors, clearly differentiating the Vin Santo vintages. Identifying the main volatiles and aromas of long-term Vin Santo wine may be helpful to winemakers, since wine aging sensory properties are often associated with a prestigious image and contribute to defining wine quality.
Starch Retrogradation in Rice Cake: Influences of Sucrose Stearate and Glycerol
Authors: Oh Seon-Min , Choi Hee-Don , Choi Hyun-Wook , Baik Moo-Yeol
Published: November 2020

Retrogradation properties and kinetics of rice cakes with the addition of glycerol (GLY) and sucrose fatty acid ester (SE) were investigated. In hardness, both rice cakes with glycerol (RGLY) and rice cakes with sucrose fatty acid ester (RSE) showed lower initial hardening compared with the control for up to 5 days. X-ray diffraction (XRD) pattern of RSE showed a B+V-type pattern, and the relative crystallinity showed that GLY and SE lowered the initial and final crystallization of rice cake. Both GLY and SE affected the retrogradation enthalpy, glass transition temperature, and ice melting enthalpy in differential scanning calorimeter (DSC). However, 1H NMR relaxation time (T2) of rice cake decreased regardless of additives. From these results, the addition of glycerol and sucrose stearate inhibits the retrogradation process of rice cakes, which will solve industrial problems. Applying the Avrami equation for retrogradation kinetics of rice cake was suitable in XRD and DSC with high coefficient of determination (0.9 < R2). Meanwhile, the other retrogradation index improved the R2 when the exponential rise to maximum equation was used. This suggests that there is an alternative of Avrami equation to predict the retrogradation.
Response to Padilla Peralta, Dan-el. Citizenship’s Insular Cases, from Ancient Greece and Rome to Puerto Rico. Humanities 2019, 8, 134
Authors: Thomas Lorrin
Published: November 2020

Dan-el Padilla Peralta’s exquisite exploration of citizenship and displacement across two millennia draws on sources from ancient Greece and Rome as well as modern empires, including the U.S., and proposes two creative heuristic devices—the “insular scheme” and “radical inclusion”—that enable us to better understand both the marginalizing experience and the animating possibilities of immigrant citizenship. In my response to his piece, I assess the relevance of these ideas to the history of Puerto Ricans in relation to the United States. Puerto Ricans, caught in the “insular scheme” of U.S. citizenship since American citizenship was imposed on them in 1917, are the most obvious exemplars of “differentiated citizens” in the nation and have struggled in multiple ways with the question of inclusion as citizens. I examine the ways that Puerto Ricans have used the language of recognition as a way to explain the aspiration of equitable citizenship, a vision of belonging in the nation that sounds much like Padilla Peralta’s “radical inclusion.”
Correlation between the DJSI Chile and the Financial Indices of Chilean Companies
Authors: Chahuán-Jiménez Karime
Published: November 2020

The Dow Jones Sustainability Index Chile (DJSI Chile) is made up of leading sustainability companies that are investing great effort into sustainable management. This study correlates the DJSI Chile with the financial indices (return on equity (ROE), return on assets (ROA), market value, earnings, and leverage) of companies that belong to the General Stock Price Index (IGPA) in Chile. The methodology used was quantitative, considering Chilean companies in the IGPA, including companies belonging to the DJSI Chile, applying a normality and correlation test based on the results. In conclusion, the study shows that in the results for the ROE, ROA, and leverage variables, there is no positive correlation with the DJSI Chile. However, the DJSI Chile is correlated with market value (for approximately 80% of the companies), and with earnings, there is a slightly higher correlation for the companies that belong to the DJSI Chile than for the remaining companies in the IGPA, thus if there exists a correlation between the DJSI Chile index and the variables market value and earnings, the index enables the prediction of those financial variables or predicts the finance indices (value market and earnings) of the companies that make up the DJSI Chile basing in the DJSI Chile index.
Developing Versatile Graphic Map Load Metrics
Authors: Barvir Radek , Vozenilek Vit
Published: November 2020

Graphic map load is a property of a map quantifying the amount of map content. It indicates the visual complexity of the map and helps cartographers to adapt maps and other geospatial visualizations to accomplish their purpose. Generally, map design needs to enable the user to quickly, comprehensively, and intuitively obtain the relevant spatial information from a map. Especially, this applies in cases like crisis management, immunology and military. However, there are no widely applicable metrics to assess the complexity of cartographic products. This paper evaluates seven simple metrics for graphic map load calculation based on image analytics using the set of 50 various maps on an easily understandable scale of 0–100%. The metrics are compared to values of user-perceived map load survey joined by 62 respondents. All the suggested metrics are designed for calculation with easy-accessible software and therefore suitable for use in any user environment. Metrics utilizing the principle of edge detection have been found suitable for a diversity of geospatial visualizations providing the best results among other metrics.
Expression of Main Toll-Like Receptors in Patients with Different Types of Colorectal Polyps and Their Relationship with Gut Microbiota
Authors: Rezasoltani Sama , Ghanbari Reza , Looha Mehdi Azizmohammad , Mojarad Ehsan Nazemalhosseini , Yadegar Abbas , Stewart Delisha , Aghdaei Hamid Asadzadeh , Zali Mohammad Reza
Published: November 2020

Abnormal activation of Toll-like receptor (TLRs) signaling can result in colon cancer development. The aim of this study was to investigate the expression of important TLRs in different histological types of colorectal polyps and evaluate their relationship with intestinal microbiota. The expression levels of TLR2, 3, 4, and 5 were analyzed in intestinal biopsy specimens of 21 hyperplastic polyp (HP), 16 sessile serrated adenoma (SSA), 29 tubular adenoma (TA), 21 villous/tubulovillous (VP/TVP) cases, and 31 normal controls. In addition, selected gut bacteria including Streptococcus bovis, Enterococcus faecalis, Enterotoxigenic Bacteroides fragilis (ETBF), Fusobacterium nucleatum, Porphyromonas spp., Lactobacillus spp., Roseburia spp., and Bifidobacterium spp. were quantified in fecal samples using absolute qRT PCR, and, finally, the association between TLRs and these gut microbiota- was evaluated by Spearman’s correlation coefficient. Higher expression of TLR2 and TLR4 in VP/TVP and TA, and lower expression levels of TLR3 and TLR5 in all type of polyps were observed. The differences in TLR expression patterns was not only dependent on the histology, location, size, and dysplasia grade of polyps but also related to the intestinal microbiota patterns. TLR2 and TLR4 expression was directly associated with the F. nucleatum, E. faecalis, S. bovis, Porphyromonas, and inversely to Bifidobacterium, Lactobacillus, and Roseburia quantity. Furthermore, TLR3 and TLR5 expression was directly associated with Bifidobacterium, Roseburia, and Lactobacillus quantity. Our results suggest a possible critical role of TLRs during colorectal polyp progression. An abnormal regulation of TLRs in relation to gut microbial quantity may contribute to carcinogenesis.
The Weight of IgA Anti-β2glycoprotein I in the Antiphospholipid Syndrome Pathogenesis: Closing the Gap of Seronegative Antiphospholipid Syndrome
Authors: Cabrera-Marante Oscar , Rodríguez de Frías Edgard , Serrano Manuel , Lozano Morillo Fernando , Naranjo Laura , Gil-Etayo Francisco J. , Paz-Artal Estela , Pleguezuelo Daniel E. , Serrano Antonio
Published: November 2020

The specific value of IgA Anti-β2glycoprotein I antibodies (aB2GP1) in the diagnosis and management of antiphospholipid syndrome (APS) is still controversial and a matter of active debate. The relevance of the IgA aB2GP1 isotype in the pathophysiology of APS has been increasingly studied in the last years. There is well know that subjects with multiple positive APS tests are at increased risk of thrombosis and/or miscarriage. However, these antibodies are not included in the 2006 APS classification criteria. Since 2010 the task force of the Galveston International Congress on APS recommends testing IgA aB2GP1 isotype in patients with APS clinical criteria in the absence of criteria antibodies. In this review, we summarize the molecular and clinical “state of the art” of the IgA aB2GP in the context of APS. We also discuss some of the characteristics that may help to evaluate the real value of the IgA aB2GP1 determination in basic research and clinical practice. The scientific community should be aware of the importance of clarifying the role of IgA aB2GP1 in the APS diagnosis.
Autophagy and Autophagy-Related Diseases: A Review
Authors: Ichimiya Tadashi , Yamakawa Tsukasa , Hirano Takehiro , Yokoyama Yoshihiro , Hayashi Yuki , Hirayama Daisuke , Wagatsuma Kohei , Itoi Takao , Nakase Hiroshi
Published: November 2020

Autophagy refers to the process involving the decomposition of intracellular components via lysosomes. Autophagy plays an important role in maintaining and regulating cell homeostasis by degrading intracellular components and providing degradation products to cells. In vivo, autophagy has been shown to be involved in the starvation response, intracellular quality control, early development, and cell differentiation. Recent studies have revealed that autophagy dysfunction is implicated in neurodegenerative diseases and tumorigenesis. In addition to the discovery of certain disease-causing autophagy-related mutations and elucidation of the pathogenesis of conditions resulting from the abnormal degradation of selective autophagy substrates, the activation of autophagy is essential for prolonging life and suppressing aging. This article provides a comprehensive review of the role of autophagy in health, physiological function, and autophagy-related disease.
Understanding and Treating Niemann–Pick Type C Disease: Models Matter
Authors: Pallottini Valentina , Pfrieger Frank W.
Published: November 2020

Biomedical research aims to understand the molecular mechanisms causing human diseases and to develop curative therapies. So far, these goals have been achieved for a small fraction of diseases, limiting factors being the availability, validity, and use of experimental models. Niemann–Pick type C (NPC) is a prime example for a disease that lacks a curative therapy despite substantial breakthroughs. This rare, fatal, and autosomal-recessive disorder is caused by defects in NPC1 or NPC2. These ubiquitously expressed proteins help cholesterol exit from the endosomal–lysosomal system. The dysfunction of either causes an aberrant accumulation of lipids with patients presenting a large range of disease onset, neurovisceral symptoms, and life span. Here, we note general aspects of experimental models, we describe the line-up used for NPC-related research and therapy development, and we provide an outlook on future topics.
Design, Synthesis and Evaluation of New Bioactive Oxadiazole Derivatives as Anticancer Agents Targeting Bcl-2
Authors: Hamdy Rania , Elseginy Samia A. , Ziedan Noha I. , El-Sadek Mohamed , Lashin Elsaid , Jones Arwyn T. , Westwell Andrew D.
Published: November 2020

A series of 2-(1H-indol-3-yl)-5-substituted-1,3,4-oxadiazoles, 4a–m, were designed, synthesized and tested in vitro as potential pro-apoptotic Bcl-2 inhibitory anticancer agents based on our previously reported hit compounds. Synthesis of the target 1,3,4-oxadiazoles was readily accomplished through a cyclization reaction of indole carboxylic acid hydrazide 2 with substituted carboxylic acid derivatives 3a–m in the presence of phosphorus oxychloride. New compounds 4a–m showed a range of IC50 values concentrated in the low micromolar range selectively in Bcl-2 positive human cancer cell lines. The most potent candidate 4-trifluoromethyl substituted analogue 4j showed selective IC50 values of 0.52–0.88 μM against Bcl-2 expressing cell lines with no inhibitory effects in the Bcl-2 negative cell line. Moreover, 4j showed binding that was two-fold more potent than the positive control gossypol in the Bcl-2 ELISA binding affinity assay. Molecular modeling studies helped to further rationalize anti-apoptotic Bcl-2 binding and identified compound 4j as a candidate with drug-like properties for further investigation as a selective Bcl-2 inhibitory anticancer agent.
Convolutional Support Vector Models: Prediction of Coronavirus Disease Using Chest X-rays
Authors: Maia Mateus , Pimentel Jonatha S. , Pereira Ivalbert S. , Gondim João , Barreto Marcos E. , Ara Anderson
Published: November 2020

The disease caused by the new coronavirus (COVID-19) has been plaguing the world for months and the number of cases are growing more rapidly as the days go by. Therefore, finding a way to identify who has the causative virus is impressive, in order to find a way to stop its proliferation. In this paper, a complete and applied study of convolutional support machines will be presented to classify patients infected with COVID-19 using X-ray data and comparing them with traditional convolutional neural network (CNN). Based on the fitted models, it was possible to observe that the convolutional support vector machine with the polynomial kernel (CSVMPol) has a better predictive performance. In addition to the results obtained based on real images, the behavior of the models studied was observed through simulated images, where it was possible to observe the advantages of support vector machine (SVM) models.
Frequency of Additional Congenital Dental Anomalies in Children with Cleft Lip, Alveolar and Palate
Authors: Pastuszak Przemysław , Dunin-Wilczyńska Izabella , Lasota Agnieszka
Published: November 2020

The aim of the study was to assess the risk of incidence of additional congenital dental anomalies in children with nonsyndromic cleft lip, alveolar and/without palate (CL/P). Hypodontia, hyperdontia and canines impaction was recognized. From patients with CL/P treated at the Clinic of Congenital Facial Deformities in Chair and Department of Jaw Orthopedics Medical University of Lublin, 56 subjects were randomly selected. On the panoramic radiographs taken at the age of 8–12 years, the angle of upper unerupted canines was measured using Westerlund’s recommendations. The supernumerary teeth and hypodontia were checked. The procedures: maxillary expansion, secondary alveolar bone graft (SABG) and extraction of primary canines were noted. The frequency of canines impaction was 5.36%. Hypodontia was found in 37.5% of patients; hyperdontia was present in 23.21% of patients. No influence of procedures (expansion of the maxilla, SABG, deciduous canines extraction) on permanent maxillary canine eruption was proved. Patients with CL/P are exposed to the unfavorable position of unerupted maxillary canines most frequently in the cleft area of complete cleft. Maxillary lateral incisor on the cleft side is most frequently affected with congenital anomaly. Hypodontia and hyperdontia do not influence maxillary canine impaction. Good clinical result was achieved with an applied approach, which should be widely introduced.
Multidisciplinary Analysis of Cystoseira sensu lato (SE Spain) Suggest a Complex Colonization of the Mediterranean
Authors: Jódar-Pérez Ana Belén , Terradas-Fernández Marc , López-Moya Federico , Asensio-Berbegal Leticia , López-Llorca Luis Vicente
Published: November 2020

Cystoseira sensu lato (sl) are three genera widely recognized as bioindicators for their restricted habitat in a sub-coastal zone with low tolerance to pollution. Their ecological, morphological and taxonomic features are still little known due to their singular characteristics. We studied seven species of Cystoseira sl spp. in Cabo de las Huertas (Alicante, SE Spain) and analyzed their distribution using Permutational Analysis of Variance (PERMANOVA) and Principal Component Ordination plots (PCO). A morphological cladogram has been constructed using fifteen phenotypic taxonomic relevant characters. We have also developed an optimized Cystoseira sl DNA extraction protocol. We have tested it to obtain amplicons from mt23S, tRNA-Lys and psbA genes. With these sequence data, we have built a phylogenetic supertree avoiding threatened Cystoseira sl species. Cartography and distribution analysis show that the response to hydrodynamism predicts perennial or seasonal behaviors. Morphological cladogram detects inter-specifical variability between our species and reference studies. Our DNA phylogenetic tree supports actual classification, including for the first-time Treptacantha sauvageauana and Treptacantha algeriensis species. These data support a complex distribution and speciation of Cystoseira sl spp. in the Mediterranean, perhaps involving Atlantic clades. The high ecological value of our area of study merits a future protection status as a Special Conservation Area.
On the Comparative Seakeeping Analysis of the Full Scale KCS by Several Hydrodynamic Approaches
Authors: Pacuraru Florin , Domnisoru Leonard , Pacuraru Sandita
Published: November 2020

The main transport channel of the global economy is represented by shipping. Engineers and hull designers are more preoccupied in ensuring fleet safety, the proper operation of the ships, and, more recently, compliance with International Maritime Organization (IMO) regulatory incentives. Considerable efforts have been devoted to in-depth understanding of the hydrodynamics mechanism and prediction of ship behavior in waves. Prediction of seakeeping performances with a certain degree of accuracy is a demanding task for naval architects and researchers. In this paper, a fully numerical approach of the seakeeping performance of a KRISO (Korea Research Institute of Ships and Ocean Engineering, Daejeon, South Korea) container ship (KCS) container vessel is presented. Several hydrodynamic methods have been employed in order to obtain accurate results of ship hydrodynamic response in regular waves. First, an in-house code DYN (Dynamic Ship Analysis, “Dunarea de Jos” University of Galati, Romania), based on linear strip theory (ST) was used. Then, a 3D fully nonlinear time-domain Boundary Element Method (BEM) was implemented, using the commercial code SHIPFLOW (FLOWTECH International AB, Gothenburg, Sweden). Finally, the commercial software NUMECA (NUMECA International, Brussels, Belgium) was used in order to solve the incompressible unsteady Reynolds-averaged Navier–Stokes equation (RANSE) flow at ship motions in head waves. The results obtained using these methods are represented and discussed, in order to establish a methodology for estimating the ship response in regular waves with accurate results and the sensitivity of hydrodynamical models.
Long-Term Performance of Mega-Nourishments: Role of Directional Wave Climate and Initial Geometry
Authors: Arriaga Jaime , Ribas Francesca , Falqués Albert , Rutten Jantien , Ruessink Gerben
Published: November 2020

Concentrated mega-nourishments, built as coastal protection measures for decadal time scales, are intended to diffuse, that is to erode and to supply sand to the nearby beaches and dunes by profiting of the natural drivers. Here, we aim to quantify the role of the wave incidence angle and initial geometry on the long-term evolution of mega-nourishments, in particular the Zandmotor (the Netherlands), using a nonlinear morphodynamic model for large-scale shoreline dynamics. Synthetic wave climates based on measurements are created to systematically vary the wave conditions. Simulations show that mega-nourishment diffusivity decreases linearly with an increasing percentage of high-angle waves (>45° incidence with respect to the global shoreline orientation in deep water). For wave climates with more than 80% of high-angle waves, erosional hotspots develop at the sides of the mega-nourishment. In unimodal high-angle wave climates, hotspot growth rates are large and alongshore migration of the nourishment can increase up to 40 m/year. The role of initial geometry is studied by creating synthetic nourishments that vary in shape, asymmetry, and volume. Slender initial shapes are less diffusive than wider shapes. The initial asymmetry influences the asymmetry in sand feeding to adjacent beaches throughout 50 years, which for symmetric nourishments is controlled by the imbalance in the wave climate. Smaller nourishments than the Zandmotor are more diffusive. This work contributes to a more general understanding of mega-nourishment evolution and may serve as guide for future mega-nourishment design.
Targeted Disruption of Scytalone Dehydratase Gene Using Agrobacterium tumefaciens-Mediated Transformation Leads to Altered Melanin Production in Ascochyta lentis
Authors: Debler Johannes W. , Henares Bernadette M.
Published: November 2020

Sustainable crop production is constantly challenged by the rapid evolution of fungal pathogens equipped with an array of host infection strategies and survival mechanisms. One of the devastating fungal pathogens that infect lentil is the ascomycete Ascochyta lentis which causes black spot or ascochyta blight (AB) on all above ground parts of the plant. In order to explore the mechanisms involved in the pathogenicity of A. lentis, we developed a targeted gene replacement method using Agrobacterium tumefaciens mediated transformation (ATMT) to study and characterize gene function. In this study, we investigated the role of scytalone dehydratase (SCD) in the synthesis of 1,8-dihydroxynaphthalene (DHN)-melanin in AlKewell. Two SCD genes have been identified in AlKewell, AlSCD1 and AlSCD2. Phylogenetic analysis revealed that AlSCD1 clustered with the previously characterized fungal SCDs; thus, AlSCD1 was disrupted using the targeted gene replacement vector, pTAR-hyg-SCD1. The vector was constructed in a single step process using Gibson Assembly, which facilitated an easy and seamless assembly of multiple inserts. The resulting AlKewell scd1::hyg transformants appeared light brown/brownish-pink in contrast to the dark brown pycnidia of the WT strain and ectopic transformant, indicating an altered DHN-melanin production. Disruption of AlSCD1 gene did not result in a change in the virulence profile of AlKewell towards susceptible and resistant lentil varieties. This is the first report of a targeted gene manipulation in A. lentis which serves as a foundation for the functional gene characterization to provide a better understanding of molecular mechanisms involved in pathogen diversity and host specificity.