bluuebunny/crossref_metadata_2025 huggingface dataset:
Antimicrobial Resistance Patterns and Antibiotic Use during Hospital Conversion in the COVID-19 Pandemic
Authors: Martinez-Guerra Bernardo A. , Gonzalez-Lara Maria F. , de-Leon-Cividanes Nereyda A. , Tamez-Torres Karla M. , Roman-Montes Carla M. , Rajme-Lopez Sandra , Villalobos-Zapata G. Ivonne , Lopez-Garcia Norma I. , Martínez-Gamboa Areli , Sifuentes-Osornio Jose , Ortiz-Brizuela Edgar , Ochoa-Hein Eric , Galindo-Fraga Arturo , Bobadilla-del-Valle Miriam , Ponce-de-León Alfredo
Published: February 2021

Objective: To describe empirical antimicrobial prescription on admission in patients with severe COVID-19, the prevalence of Hospital-Acquired Infections, and the susceptibility patterns of the causing organisms. Methods: In this prospective cohort study in a tertiary care center in Mexico City, we included consecutive patients admitted with severe COVID-19 between March 20th and June 10th and evaluated empirical antimicrobial prescription and the occurrence of HAI. Results: 794 patients with severe COVID-19 were admitted during the study period. Empiric antibiotic treatment was started in 92% of patients (731/794); the most frequent regimes were amoxicillin-clavulanate plus atypical coverage in 341 (46.6%) and ceftriaxone plus atypical coverage in 213 (29.1%). We identified 110 HAI episodes in 74/656 patients (11.3%). Ventilator-associated pneumonia (VAP) was the most frequent HAI, in 56/110 (50.9%), followed by bloodstream infections (BSI), in 32/110 (29.1%). The most frequent cause of VAP were Enterobacteriaceae in 48/69 (69.6%), followed by non-fermenter gram-negative bacilli in 18/69 (26.1%). The most frequent cause of BSI was coagulase negative staphylococci, in 14/35 (40.0%), followed by Enterobacter complex in 7/35 (20%). Death occurred in 30/74 (40.5%) patients with one or more HAI episodes and in 193/584 (33.0%) patients without any HAI episode (p < 0.05). Conclusion: A high frequency of empiric antibiotic treatment in patients admitted with COVID-19 was seen. VAP and BSI were the most frequent hospital-acquired infections, due to Enterobacteriaceae and coagulase negative staphylococci, respectively.
Antioxidant and In Vitro Preliminary Anti-Inflammatory Activity of Castanea sativa (Italian Cultivar “Marrone di Roccadaspide” PGI) Burs, Leaves, and Chestnuts Extracts and Their Metabolite Profiles by LC-ESI/LTQOrbitrap/MS/MS
Authors: Cerulli Antonietta , Napolitano Assunta , Hošek Jan , Masullo Milena , Pizza Cosimo , Piacente Sonia
Published: February 2021

The Italian “Marrone di Roccadaspide” (Castanea sativa), a labeled Protected Geographical Indication (PGI) product, represents an important economic resource for the Italian market. With the aim to give an interesting opportunity to use chestnuts by-products for the development of nutraceutical and/or cosmetic formulations, the investigation of burs and leaves along with chestnuts of C. sativa, cultivar “Marrone di Roccadaspide”, has been performed. The phenolic, tannin, and flavonoid content of the MeOH extracts of “Marrone di Roccadaspide” burs, leaves, and chestnuts as well as their antioxidant activity by spectrophotometric methods (1,1-diphenyl-2-picrylhydrazyl (DPPH), Trolox Equivalent Antioxidant Capacity (TEAC), and Ferric Reducing Antioxidant Power (FRAP) have been evaluated. Furthermore, a cell-based antioxidant in vitro test along with in vitro assays for the evaluation of the ability to reduce nuclear factor-kappa B (NF-κB) activation and nitric oxide (NO) production have been carried out. In order to identify the secondary metabolites responsible for the high phenolic content and the strong antioxidant activity shown by leaves and burs extracts, and to highlight the differences between their chemical composition, the analysis of the metabolite profile of the MeOH extracts obtained from both by-products and chestnuts by liquid chromatography coupled to electrospray ionization and multiple-stage linear ion-trap and Orbitrap high-resolution mass spectrometry (LC-(-)ESI/LTQOrbitrap/MS/MS) has been performed. LC-MS analysis allowed the identification of different classes of specialized metabolites including hydrolyzable tannins, flavonoids, ellagic acid and phenol glucoside derivatives, and triterpenoids as well as polar lipids. Our results show how the antioxidant activity of the extracts can be correlated to their high tannins and flavonoids content while polar lipids occurring in the MeOH extract of the leaves could contribute to determining its higher anti-inflammatory activity.
Cycle Logistics Projects in Europe: Intertwining Bike-Related Success Factors and Region-Specific Public Policies with Economic Results
Authors: Giglio Carlo , Musmanno Roberto , Palmieri Roberto
Published: February 2021

The aim of this paper is to investigate whether and which specific, distinctive characteristics of European cycle logistics projects and the corresponding supporting policies have an impact on their economic performances in terms of profit and profitability. First, we identify project success factors by geographic area and project-specific characteristics; then, we statistically test possible dependence relationships with supporting policies and economic results. Finally, we provide a value-based identification of those characteristics and policies which more commonly lead to better economic results. This way, our work may serve as a basis for the prioritization and contextualization of those project functionalities and public policies to be implemented in a European context. We found that cycle logistics projects in Europe achieve high profit and profitability levels, and the current policies are generally working well and supporting them. We also found that profit and profitability vary across the bike model utilized: mixing cargo bikes and tricycles generates the highest profit and profitability, whilst a trailer–tricycle–cargo bike mix paves the way for high volumes and market shares.
Smart Project Management: Interactive Platform Using Natural Language Processing Technology
Authors: Chen Jieh-Haur , Su Mu-Chun , Azzizi Vidya Trisandini , Wang Ting-Kwei , Lin Wei-Jen
Published: February 2021

Technological developments have made the construction industry efficient. The aim of this research is to solve communication interaction problems to build a project management platform using the interactive concept of natural language processing technology. A comprehensive literature review and expert interviews associated with techniques dealing with natural languages suggests the proposed system containing the Progressive Scale Expansion Network (PSENet), Convolutional Recurrent Neural Network (CRNN), and Bi-directional Recurrent Neutral Networks Convolutional Recurrent Neural Network (BRNN-CNN) toolboxes to extract the key words for construction projects contracts. The results show that a fully automatic platform facilitating contract management is achieved. For academic domains, the Contract Keyword Detection (CKD) mechanism integrating PSENet, CRNN, and BRNN-CNN approaches to cope with real-time massive document flows is novel in the construction industry. For practice, the proposed approach brings significant reduction for manpower and human error, an alternative for settling down misunderstanding or disputes due to real-time and precise communication, and a solution for efficient documentary management. It connects all contract stakeholders proficiently.
Deliquescence Behavior of Deep Eutectic Solvents
Authors: Palmelund Henrik , Rantanen Jukka , Löbmann Korbinian
Published: February 2021

Deep eutectic solvents (DESs) are formed by a hydrogen bond donor and an acceptor. The hydrogen bond interactions between these two components significantly depress the melting temperature of the mixture. DESs have been used as an alternative for organic solvents in various branches of the chemical industry. Many DESs are very hygroscopic and water is known to change the properties of DESs, but there has neven been a systematic study performed on the deliquesence behavior of DESs. Therefore, this study investigated the thermal and deliquescent behavior of four DESs. The DES mixtures were stored in desiccators at different relative humidities (RH) to investigate the critical RH (RH0) for deliquescence. It was found that, due to the formation of a eutonic mixture, the RH0 to induce deliquescence for a given DES mixture was lower compared to the individual components comprising the DES. The results showed that, even though all investigated DESs had eutectic melting temperatures above room temperature, but due to the low RH0, they were able to appear liquid at room temperature under ambient conditions. The eutonic and eutectic compositions were identified at different compositions for the DESs. The results emphasize that great care must be taken to control the process and storage conditions for DESs.
TOF-SIMS Molecular Imaging and Properties of pMDI-Bonded Particleboards Made from Cup-Plant and Wood
Authors: Klímek Petr , Wimmer Rupert , Meinlschmidt Peter
Published: February 2021

Cup-plant (Silphium perfoliatum L.) stalks were investigated as a potential wood-replacement in particleboards (PBs). Two types of PBs were produced—(1) single-layer and (2) three-layer boards. In the three-layer cup-plant PB, the core layer was made from cup-plant, while the surface layer consisted of spruce particles. The cup-plant as well as spruce control panels were produced with polymeric methylene diphenyl diisocyanate (pMDI) as the adhesive, with the physical and mechanical properties measured to meet class P1 of the European EN 312 standard. For the intrinsic morphology of the particleboards, scanning electron microscopy was applied. Wood-based and cup-plant-based particleboards indicated significant differences in morphology that affect the resulting properties of particleboards. Furthermore, an innovative approach was used in the determination of the pMDI bondline morphology. With a compact Time-of-Flight Secondary Ion Mass analyser, integrated in a multifunctional focused-ion beam scanning-electron-microscope, it was possible to show that the Ga+ ion source could be detect and visualize in 3D ion molecular clusters specific to pMDI adhesive and wood. Mechanical performance data showed that cup-plant particleboards performed well, even though their properties were below the spruce-made controls. Especially the modulus of rupture (MOR) of the cup-plant PB was lowered by 40%, as compared to the spruce-made control board. Likewise, thickness swelling of cup-plant made boards was higher than the control. Results were linked to the specific porous structure of the cup-plant material. In contrast, it was shown that three-layer cup-plant PB had a higher MOR and also a higher modulus of elasticity, along with lower thickness swelling, compared to its single-layer cup-plant counterpart. The industry relevant finding was that the three-layer PB made from cup-plant stalks fulfilled the EN 312 standard, class P1 (usage in dry conditions). It was shown that raw material mixtures could be useful to improve the mechanical panel performance, also with an altered vertical density profile.
Evaluation of Waste Blends with Sewage Sludge as a Potential Material Input for Pyrolysis
Authors: Kubonova Lenka , Janakova Iva , Malikova Petra , Drabinova Silvie , Dej Milan , Smelik Roman , Skalny Pavel , Heviankova Silvie
Published: February 2021

In line with the requirements of the circular economy, the European Union’s waste management legislative changes also concern the treatment of sewage sludge. Although sewage sludge production cannot be prevented, its quantities may be reduced by the synergetic effect of energy recovery via choosing a proper technology. Sewage sludge is difficult to apply as fuel alone, because of its high moisture and ash content. However, its energy use will be increased by adding suitable waste materials (different types of plastics, waste tires and paper rejects). Most recently, the thermal utilization of sewage sludge via incineration or pyrolysis has grown in importance. This article describes the fuel parameters of particular waste materials and of their blends with sewage sludge in connection with laboratory-scale thermal decomposition in an inert atmosphere, for their potential use in a semi-pilot plant pyrolysis unit. For pyrolytic application, the results of thermogravimetric analysis are needed in order to know the maximal temperature of thermal decomposition in an inert atmosphere, maximal mass losses, and weight loss rates. The samples of different thermoplastics mixed with sewage sludge, and low-density polyethylene blends with sewage sludge, had the lowest residual masses (70–74%) and the highest weight loss rates (11–19%/min). On the other hand, the blend of polyester rejects from tire processing, paper rejects and sewage sludge had the second highest residual mass (60%) and the lowest weight loss rate (3%/min).
Interactive Effects of Scion and Rootstock Genotypes on the Root Microbiome of Grapevines (Vitis spp. L.)
Authors: Vink Stefanie Nicoline , Dini-Andreote Francisco , Höfle Rebecca , Kicherer Anna , Salles Joana Falcão
Published: February 2021

Diversity and community structure of soil microorganisms are increasingly recognized as important contributors to sustainable agriculture and plant health. In viticulture, grapevine scion cultivars are grafted onto rootstocks to reduce the incidence of the grapevine pest phylloxera. However, it is unknown to what extent this practice influences root-associated microbial communities. A field survey of bacteria in soil surrounding the roots (rhizosphere) of 4 cultivars × 4 rootstock combinations was conducted to determine whether rootstock and cultivar genotypes are important drivers of rhizosphere community diversity and composition. Differences in α-diversity was highly dependent on rootstock–cultivar combinations, while bacterial community structure primarily clustered according to cultivar differences, followed by differences in rootstocks. Twenty-four bacterial indicator genera were significantly more abundant in one or more cultivars, while only thirteen were found to be specifically associated with one or more rootstock genotypes, but there was little overlap between cultivar and rootstock indicator genera. Bacterial diversity in grafted grapevines was affected by both cultivar and rootstock identity, but this effect was dependent on which diversity measure was being examined (i.e., α- or β-diversity) and specific rootstock–cultivar combinations. These findings could have functional implications, for instance, if specific combinations varied in their ability to attract beneficial microbial taxa which can control pathogens and/or assist plant performance.
Proposal of a Monitoring System for Collaborative Robots to Predict Outages and to Assess Reliability Factors Exploiting Machine Learning
Authors: Aliev Khurshid , Antonelli Dario
Published: February 2021

Industry standards pertaining to Human-Robot Collaboration (HRC) impose strict safety requirements to protect human operators from danger. When a robot is equipped with dangerous tools, moves at a high speed or carries heavy loads, the current safety legislation requires the continuous on-line monitoring of the robot’s speed and a suitable separation distance from human workers. The present paper proposes to make a virtue out of necessity by extending the scope of on-line monitoring to predicting failures and safe stops. This has been done by implementing a platform, based on open access tools and technologies, to monitor the parameters of a robot during the execution of collaborative tasks. An automatic machine learning (ML) tool on the edge of the network can help to perform the on-line predictions of possible outages of collaborative robots, especially as a consequence of human-robot interactions. By exploiting the on-line monitoring system, it is possible to increase the reliability of collaborative work, by eliminating any unplanned downtimes during execution of the tasks, by maximising trust in safe interactions and by increasing the robot’s lifetime. The proposed framework demonstrates a data management technique in industrial robots considered as a physical cyber-system. Using an assembly case study, the parameters of a robot have been collected and fed to an automatic ML model in order to identify the most significant reliability factors and to predict the necessity of safe stops of the robot. Moreover, the data acquired from the case study have been used to monitor the manipulator’ joints; to predict cobot autonomy and to provide predictive maintenance notifications and alerts to the end-users and vendors.
On the Development of Thermochemical Hydrogen Storage: An Experimental Study of the Kinetics of the Redox Reactions under Different Operating Conditions
Authors: Gamisch Bernd , Gaderer Matthias , Dawoud Belal
Published: February 2021

This work aims at investigating the reduction/oxidation (redox) reaction kinetics on iron oxide pellets under different operating conditions of thermochemical hydrogen storage. In order to reduce the iron oxide pellets (90% Fe2O3, 10% stabilizing cement), hydrogen (H2) is applied in different concentrations with nitrogen (N2), as a carrier gas, at temperatures between between 700 ∘C and 900 ∘C, thus simulating the charging phase. The discharge phase is triggered by the flow of a mixture out of steam (H2O) and N2 at different concentrations in the same temperature range, resulting in the oxidizing of the previously reduced pellets. All investigations were carried out in a thermo-gravimetric analyzer (TGA) with a flow rate of 250mL/min. To describe the obtained kinetic results, a simplified analytical model, based on the linear driving force model, was developed. The investigated iron oxide pellets showed a stable redox performance of 23.8% weight reduction/gain, which corresponds to a volumetric storage density of 2.8kWh/(L bulk), also after the 29 performed redox cycles. Recalling that there is no H2 stored during the storage phase but iron, the introduced hydrogen storage technology is deemed very promising for applications in urban areas as day-night or seasonal storage for green hydrogen.
Nanomedicine Interventions in Clinical Trials for the Treatment of Metastatic Breast Cancer
Authors: Moreira Rita , Granja Andreia , Pinheiro Marina , Reis Salette
Published: February 2021

Breast cancer was responsible for the deaths of 626,679 women in 2018. After decades of research, the mortality rates remain high. While the barrier of selectively killing tumor cells is not yet overcome, the search for targeted therapeutics continues. The use of nanomedicine in cancer treatment has opened up new possibilities for more precise drug-delivery systems. This review aimed to gather information and analyze recent clinical trials evaluating the therapeutic effects of nanoparticles in the treatment of metastatic breast cancer. To accomplish this, the clinicaltrials.gov database was consulted, and after employing specific exclusion criteria, 11 clinical trials were selected. Nanoparticle albumin-stabilized paclitaxel was evaluated in ten clinical trials and paclitaxel-incorporating polymeric micelles were assessed in one clinical trial. Overall, this review confirmed a clinical benefit in the use of nanoparticle albumin-stabilized paclitaxel for the treatment of breast cancer, with reduced toxicity when compared to first-line treatments. Three studies did not meet the primary endpoint, however, and so the authors advised further evaluations. Although the use of nanomedicine is revolutionizing the cancer field, to integrate this regimen into generalized clinical treatment, additional clinical trials must be performed to achieve a favorable safety and efficacy profile.
Household Energy Management
Authors: Powroźnik Piotr , Szulim Robert , Miczulski Wiesław , Piotrowski Krzysztof
Published: February 2021

Ensuring flexibility and security in power systems requires the use of appropriate management measures on the demand side. The article presents the results of work related to energy management in households in which renewable energy sources (RES) can be installed. The main part of the article is about the developed elastic energy management algorithm (EEM), consisting of two algorithms, EEM1 and EEM2. The EEM1 algorithm is activated in time periods with a higher energy price. Its purpose is to reduce the power consumed by the appliances to the level defined by the consumer. In contrast, the EEM2 algorithm is run by the Distribution System Operator (DSO) when peak demand occurs. Its purpose is to reduce the power of appliances in a specified time period to the level defined by the DSO. The optimization tasks in both algorithms are based on the Greedy Randomized Adaptive Search Procedure (GRASP) metaheuristic algorithm. The EEM1 and EEM2 algorithms also provide energy consumer comfort. For this purpose, both algorithms take into account the smart appliance parameters proposed in the article: sections of the working devices, power reduction levels, priorities and enablingof time shifting devices. The EEM algorithm in its operation also takes into account the information about the production of power, e.g., generated by the photovoltaic systems. On this basis, it makes decisions on the control of smart appliances. The EEM algorithm also enables inverter control to limit the power transferred from the photovoltaic system to the energy system. Such action is taken on the basis of the DSO request containing the information on the power limits. Such a structure of EEM enables the balancing of energy demand and supply. The possibility of peak demand phenomenon will be reduced. The simulation and experiment results presented in the paper confirmed the rationality and effectiveness of the EEM algorithm.
High-Density Wi-Fi Based Sensor Network for Efficient Irrigation Management in Precision Agriculture
Authors: Jiménez-Buendía Manuel , Soto-Valles Fulgencio , Blaya-Ros Pedro José , Toledo-Moreo Ana , Domingo-Miguel Rafael , Torres-Sánchez Roque
Published: February 2021

The application of deficit irrigation techniques is essential in arid or semi-arid areas of the southeast of Spain, where water is a scarce and very costly resource. However, to apply these techniques, it is necessary to carry out preliminary tests on the specific crop in order to develop the models that allow the optimization of water use while achieving acceptable yields. The system proposed in this article demonstrates the feasibility of using wireless technologies available in most facilities (Wireless Fidelity) to deploy a high-density network of nodes with a variety of heterogeneous sensors to collect data from the soil, plant, and atmosphere. The data are sent and stored in a cloud server for real-time visualization from any mobile device and further analysis. The nodes have been developed using low-cost processors and are equipped with batteries and solar panels, allowing their autonomy to be virtually unlimited, as shown by the consumption studies and tests carried out.
Facile Hydrothermal and Solvothermal Synthesis and Characterization of Nitrogen-Doped Carbon Dots from Palm Kernel Shell Precursor
Authors: Newman Monday Yakubu , Abdullah Jaafar , Yusof Nor Azah , Abdul Rashid Suraya , Shueb Rafidah Hanim
Published: February 2021

Carbon dots (CDs), a nanomaterial synthesized from organic precursors rich in carbon content with excellent fluorescent property, are in high demand for many purposes, including sensing and biosensing applications. This research focused on preparing CDs from natural and abundant waste, palm kernel shells (PKS) obtained from palm oil biomass, aiming for sensing and biosensing applications. Ethylenediamine and L-phenylalanine doped CDs were produced via the hydrothermal and solvothermal methods using one-pot synthesis techniques in an autoclave batch reactor. The as-prepared N-CDs shows excellent photoluminescence (PL) property and a quantum yield (QY) of 13.7% for ethylenediamine (EDA) doped N-CDs (CDs-EDA) and 8.6% for L-phenylalanine (L-Ph) doped N-CDs (CDs-LPh) with an excitation/emission wavelength of 360 nm/450 nm. The transmission electron microscopy (TEM) images show the N-CDs have an average particle size of 2 nm for both CDs. UV-Visible spectrophotometric results showed C=C and C=O transition. FTIR results show and confirm the presence of functional groups, such as -OH, -C=O, -NH2 on the N-CDs, and the X-ray diffraction pattern showed that the N-CDs were crystalline, depicted with sharp peaks. This research work demonstrated that palm kernel shell biomass often thrown away as waste can produce CDs with excellent physicochemical properties.
An Experience Transfer Approach for the Initial Data of Iterative Learning Control
Authors: Liu Shaozhe , Liu Zuojun , Zhang Jie , Hu Dong
Published: February 2021

Iterative learning control (ILC) requires that the operating conditions of the controlled system must remain unchanged in the repetitive learning process. If the parameters of system change, the former control experience of ILC would not be effective anymore. A new process of iterative learning has to restart, which will exhaust more time and resource. Compared with learning from zero experience, appropriate initial data for the first iteration could reduce the turns of iterations to achieve the target tracking accuracy. When the parameters of a linear system change, its structure and nature are still intrinsically related to the original system. So, if the experience obtained from original ILC could be correspondingly adjusted according to the difference of new and original system, and use the adjusted experience as the initial data in the new iterative learning process, it would reduce the time and save the resource in the new ILC. Based on the idea of experience inheritance and transform, an experience transfer approach for the initial data of ILC is proposed in reference to the relation between the new and original systems. In this paper, via the method of recombining, translational and amplitude adjusting, the experience of former ILC is transferred as the initial control data of new ILC. Simulation shows that the convergence iteration of ILC with experience transfer approach reduces 55–75%, which demonstrates the effectiveness and advantages of the approach proposed in this paper. Both the deviation of the first iteration in ILC and the turns of iterations for achieving desired accuracy are reduced greatly.
Review on Complete Mueller Matrix Optical Scanning Microscopy Imaging
Authors: Le Gratiet Aymeric , Mohebi Ali , Callegari Fabio , Bianchini Paolo , Diaspro Alberto
Published: February 2021

Optical scanning microscopy techniques based on the polarization control of the light have the capability of providing non invasive label-free contrast. By comparing the polarization states of the excitation light with its transformation after interaction with the sample, the full optical properties can be summarized in a single 4×4 Mueller matrix. The main challenge of such a technique is to encode and decode the polarized light in an optimal way pixel-by-pixel and take into account the polarimetric artifacts from the optical devices composing the instrument in a rigorous calibration step. In this review, we describe the different approaches for implementing such a technique into an optical scanning microscope, that requires a high speed rate polarization control. Thus, we explore the recent advances in term of technology from the industrial to the medical applications.
Plot Structure Decomposition in Narrative Multimedia by Analyzing Personalities of Fictional Characters
Authors: Lee O-Joun , You Eun-Soon , Kim Jin-Taek
Published: February 2021

This study aims to decompose plot structures of stories in narrative multimedia (i.e., creative works that contain stories and are distributed through multimedia). Since a story is interwoven with main plots and subplots (i.e., primary and ancillary story lines), decomposing a story into multiple story lines enables us to analyze how events in the story are allocated and logically connected. For the decomposition, the existing studies employed character networks (i.e., social networks of characters that appeared in a story) and assumed that characters’ social relationships are consistent in a story line. However, these studies overlooked that social relationships significantly change around major events. To solve this problem, we attempt to use the changes for distinguishing story lines rather than suffer from the changes. We concentrate on the changes in characters’ social relationships being the result of changes in their personalities. Moreover, these changes gradually proceed within a story line. Therefore, we first propose features for measuring changes in personalities of characters: (i) Degrees of characters in character networks, (ii) lengths of dialogues spoken by characters, and (iii) ratios of out-degrees for in-degrees of characters in character networks. We supposed these features reflect importance, inner/outer conflicts, and activeness of characters, respectively. Since characters’ personalities gradually change in a story line, we can suppose that the features also show gradual story developments in a story line. Therefore, we conduct regression for each feature to discover dominant tendencies of the features. By filtering scenes that do not follow the tendencies, we extract a story line that exhibits the most dominant personality changes. We can decompose stories into multiple story lines by iterating the regression and filtering. Besides, personalities of characters change more significantly in major story lines. Based on this assumption, we also propose methods for discriminating main plots. Finally, we evaluated the accuracy of the proposed methods by applying them to the movies, which is one of the most popular narrative multimedia.
Reliability Verification of Existing RC Structures Using Partial Factors Approaches and Site-Specific Data
Authors: Lara Carlos , Tanner Peter , Zanuy Carlos , Hingorani Ramon
Published: February 2021

The assessment of an existing structure to determine its suitability for present and future use entails different sorts of problems than encountered when designing new structures. The differences revolve essentially around the nature of the information available. In existing structures, deteriorated or otherwise, the accuracy of the models used for such assessments can usually be improved by acquiring more data. The most accurate way to find actual load and resistance would be to conduct a probabilistic analysis using site data. This is a time-consuming process, however, calling for a working knowledge of probabilistic methods that may not be suited to everyday use by practising engineers. For this reason, in the past few years various studies have been conducted to develop assessment approaches, compatible with Eurocodes, which include the same verification format as normally applied for designing new structures. In this paper, the application of several of these approaches is illustrated by means of the reliability verification of one of the main beams of the reinforced concrete structure of an industrial building from the 1940s, recently transformed into a cultural centre. The obtained results are discussed and compared to the findings of a full probabilistic analysis.
A Multi-Criteria Decision Support Concept for Selecting the Optimal Contractor
Authors: Marović Ivan , Perić Monika , Hanak Tomaš
Published: February 2021

A way to minimize uncertainty and achieve the best possible project performance in construction project management can be achieved during the procurement process, which involves selecting an optimal contractor according to “the most economically advantageous tender.” As resources are limited, decision-makers are often pulled apart by conflicting demands coming from various stakeholders. The challenge of addressing them at the same time can be modelled as a multi-criteria decision-making problem. The aim of this paper is to show that the analytic hierarchy process (AHP) together with PROMETHEE could cope with such a problem. As a result of their synergy, a decision support concept for selecting the optimal contractor (DSC-CONT) is proposed that: (a) allows the incorporation of opposing stakeholders’ demands; (b) increases the transparency of decision-making and the consistency of the decision-making process; (c) enhances the legitimacy of the final outcome; and (d) is a scientific approach with great potential for application to similar decision-making problems where sustainable decisions are needed.
Acoustic Characterization of Rooms Using Reverberation Time Estimation Based on Supervised Learning Algorithm
Authors: Ciaburro Giuseppe , Iannace Gino
Published: February 2021

The measurement of reverberation time is an essential procedure for the characterization of the acoustic performance of rooms. The values returned by these measurements allow us to predict how the sound will be transformed by the walls and furnishings of the rooms. The measurement of the reverberation time is not an easy procedure to carry out and requires the use of a space in an exclusive way. In fact, it is necessary to use instruments that reproduce a sound source and instruments for recording the response of the space. In this work, an automatic procedure for estimating the reverberation time based on the use of artificial neural networks was developed. Previously selected sounds were played, and joint sound recordings were made. The recorded sounds were processed with the extraction of characteristics, then they were labeled by associating to each sound the value of the reverberation time in octave bands of that specific room. The obtained dataset was used as input for the training of an algorithm based on artificial neural networks. The results returned by the predictive model suggest using this methodology to estimate the reverberation time of any closed space, using simple audio recordings without having to perform standard measurements or calculate the integration explicitly.
Evaluating the Urban Canopy Scheme TERRA_URB in the COSMO Model for Selected European Cities
Authors: Garbero Valeria , Milelli Massimo , Bucchignani Edoardo , Mercogliano Paola , Varentsov Mikhail , Rozinkina Inna , Rivin Gdaliy , Blinov Denis , Wouters Hendrik , Schulz Jan-Peter , Schättler Ulrich , Bassani Francesca , Demuzere Matthias , Repola Francesco
Published: February 2021

The increase in built surfaces constitutes the main reason for the formation of the Urban Heat Island (UHI), that is a metropolitan area significantly warmer than its surrounding rural areas. The urban heat islands and other urban-induced climate feedbacks may amplify heat stress and urban flooding under climate change and therefore to predict them correctly has become essential. Currently in the COSMO model, cities are represented by natural land surfaces with an increased surface roughness length and a reduced vegetation cover, but this approach is unable to correctly reproduce the UHI effect. By increasing the model resolution, a representation of the main physical processes that characterize the urban local meteorology should be addressed, in order to better forecast temperature, moisture and precipitation in urban environments. Within the COSMO Consortium a bulk parameterization scheme (TERRA_URB or TU) has been developed. It parametrizes the effects of buildings, streets and other man-made impervious surfaces on energy, moist and momentum exchanges between the surface and atmosphere, and additionally accounts for the anthropogenic heat flux as a heat source from the surface to the atmosphere. TU implements an impervious water-storage parameterization, and the Semi-empirical Urban canopy parametrization (SURY) that translates 3D urban canopy into bulk parameters. This paper presents evaluation results of the TU scheme in high-resolution simulations with a recent COSMO model version for selected European cities, namely Turin, Naples and Moscow. The key conclusion of the work is that the TU scheme in the COSMO model reasonably reproduces UHI effect and improves air temperature forecasts for all the investigated urban areas, despite each city has very different morphological characteristics. Our results highlight potential benefits of a new turbulence scheme and the representation of skin-layer temperature (for vegetation) in the model performance. Our model framework provides perspectives for enhancing urban climate modelling, although further investigations in improving model parametrizations, calibration and the use of more realistic urban canopy parameters are needed.
Retrospective Modeling of NO2 and PM10 Concentrations over the Lyon Metropolitan Area (France), 1990–2010—Performance Evaluation, Exposure Assessment and Correlation between Pollutants
Authors: Coudon Thomas , Nguyen Chi Vuong , Volta Perrine , Grassot Lény , Couvidat Florian , Soulhac Lionel , Gulliver John , Mancini Francesca Romana , Fervers Béatrice , Salizzoni Pietro
Published: February 2021

Numerous cancers develop years after subjects have been exposed to chemical compounds. Thus, environmental epidemiological studies need to accurately reconstruct exposures over long periods. To estimate exposure to NO2 and PM10 concentrations, we modelled ground-level air concentrations, at very fine temporal (1 h) and spatial (10 m) resolutions, over a large European metropolitan area and at subject’s address of a French national cohort, for five different years (1990, 1995, 2000, 2005 and 2010). Model performances were assessed by comparing the annual modelled concentration against monitoring station measurements. As input data, we used background concentrations from a large-scale dispersion model. The relevance of our approach was assessed by comparing results in 2010, with a modelling using monitoring values as background data. The comparison with measurement data showed good performance of the model for the majority of the period, with a performance declined in 1990. Concentrations at the subject’s residence decreased by 45% for PM10 and 38% for NO2. The proportion of subjects exposed above the WHO recommendations declined from 100% to 50% for PM10 and from 79% to 16% for NO2. The results of this study would provide a reference for future models to assess chronic exposures to PM10 and NO2 on a larger scale.
Structural Aspects of Potential Endocrine-Disrupting Activity of Stereoisomers for a Common Pesticide Permethrin against Androgen Receptor
Authors: Sheikh Ishfaq Ahmad , Beg Mohd Amin
Published: February 2021

Endocrine-disrupting chemicals (EDCs) are a serious global public health and environmental concern. Pyrethroids are insecticide chemicals that are extensively used for crop protection and household purposes but have been identified as EDCs. On account of their ubiquitous environmental presence, human exposure occurs via food, dermal, or inhalation routes and is associated with health problems, including reproductive dysfunction. Permethrin is the most commonly used pyrethroid, and with two chiral centers in its structure, it has four stereoisomeric forms (two enantiomer pairs), i.e., permethrin (1R,3R)-cis, permethrin (1R,3S)-trans, permethrin (1S,3S)-cis, and permethrin (1S,3R)-trans. The current study was performed for predicting the potential endocrine-disrupting activity of the aforementioned four stereoisomers of permethrin against the androgen receptor (AR). The structural binding characterization and binding energy estimations in the AR binding pocket were done using induced fit docking. The structural binding data indicated that all stereoisomers were placed stably in the AR binding pocket and that the estimated binding energy values were comparable to the AR native ligand, except for permethrin (1S,3S)-cis. Furthermore, the commonality in the amino acid interactions to that of the AR native ligand and the binding energy values suggested the potential AR-disrupting activity of all the stereoisomers; however, stereoselective differences were not observed. Taken together, the results suggest that human exposure to permethrin, either as a racemate mixture or in individual stereoisomer form, could potentially interfere with AR function, which may lead to male reproductive dysfunction.
Lipoprotein(a) and Cardiovascular Outcomes after Revascularization of Carotid and Lower Limbs Arteries
Authors: Ezhov Marat V. , Tmoyan Narek A. , Afanasieva Olga I. , Afanasieva Marina I. , Pokrovsky Sergei N.
Published: February 2021

Background: Despite high-intensity lipid-lowering therapy, there is a residual risk of cardiovascular events that could be associated with lipoprotein(a) (Lp(a)). It has been shown that there is an association between elevated Lp(a) level and cardiovascular outcomes in patients with coronary heart disease. Data about the role of Lp(a) in the development of cardiovascular events after peripheral revascularization are scarce. Purpose: To evaluate the relationship of Lp(a) level with cardiovascular outcomes after revascularization of carotid and lower limbs arteries. Methods: The study included 258 patients (209 men, mean age 67 years) with severe carotid and/or lower extremity artery disease, who underwent successful elective peripheral revascularization. The primary endpoint was the composite of nonfatal myocardial infarction, nonfatal stroke, or cardiovascular death. The secondary endpoint was the composite of primary endpoint and repeated revascularization. Results: For 36-month follow-up, 29 (11%) primary and 128 (50%) secondary endpoints were registered. There was a greater risk of primary (21 (8%) vs. 8 (3%); hazard ratio (HR), 3.0; 95% confidence interval (CI) 1.5–6.3; p < 0.01) and secondary endpoints (83 (32%) vs. 45 (17%), HR, 2.8; 95% CI 2.0–4.0; p < 0.01) in patients with elevated Lp(a) level (≥30 mg/dL) compared to patients with Lp(a) < 30 mg/dL. Multivariable-adjusted Cox regression analysis revealed that Lp(a) was independently associated with the incidence of cardiovascular outcomes. Conclusions: Patients with peripheral artery diseases have a high risk of cardiovascular events. Lp(a) level above 30 mg/dL is significantly and independently associated with cardiovascular events during 3-year follow-up after revascularization of carotid and lower limbs arteries.
177Lu-PSMA-617 Therapy in Mice, with or without the Antioxidant α1-Microglobulin (A1M), Including Kidney Damage Assessment Using 99mTc-MAG3 Imaging
Authors: Kristiansson Amanda , Örbom Anders , Ahlstedt Jonas , Karlsson Helena , Zedan Wahed , Gram Magnus , Åkerström Bo , Strand Sven-Erik , Altai Mohamed , Strand Joanna , Vilhelmsson Timmermand Oskar
Published: February 2021

Anti-prostate specific membrane antigen (PSMA) radioligand therapy is promising but not curative in castration resistant prostate cancer. One way to broaden the therapeutic index could be to administer higher doses in combination with radioprotectors, since administered radioactivity is kept low today in order to avoid side-effects from a high absorbed dose to healthy tissue. Here, we investigated the human radical scavenger α1-microglobulin (A1M) together with 177-Lutetium (177Lu) labeled PSMA-617 in preclinical models with respect to therapeutic efficacy and kidney toxicity. Nude mice with subcutaneous LNCaP xenografts were injected with 50 or 100 MBq of [177Lu]Lu-PSMA-617, with or without injections of recombinant A1M (rA1M) (at T = 0 and T = 24 h). Kidney absorbed dose was calculated to 7.36 Gy at 4 days post a 100 MBq injection. Activity distribution was imaged with Single-Photon Emission Computed Tomography (SPECT) at 24 h. Tumor volumes were measured continuously, and kidneys and blood were collected at termination (3–4 days and 3–4 weeks after injections). In a parallel set of experiments, mice were given [177Lu]Lu-PSMA-617 and rA1M as above and dynamic technetium-99m mercaptoacetyltriglycine ([99mTc]Tc-MAG3) SPECT imaging was performed prior to injection, and 3- and 6-months post injection. Blood and urine were continuously sampled. At termination (6 months) the kidneys were resected. Biomarkers of kidney function, expression of stress genes and kidney histopathology were analyzed. [177Lu]Lu-PSMA-617 uptake, in tumors and kidneys, as well as treatment efficacy did not differ between rA1M and vehicle groups. In mice given rA1M, [99mTc]Tc-MAG3 imaging revealed a significantly higher slope of initial uptake at three months compared to mice co-injected with [177Lu]Lu-PSMA-617 and vehicle. Little or no change compared to control was seen in urine albumin, serum/plasma urea levels, RT-qPCR analysis of stress response genes and in the kidney histopathological evaluation. In conclusion, [99mTc]Tc-MAG3 imaging presented itself as a sensitive tool to detect changes in kidney function revealing that administration of rA1M has a potentially positive effect on kidney perfusion and tubular function when combined with [177Lu]Lu-PSMA-617 therapy. Furthermore, we could show that rA1M did not affect anti-PSMA radioligand therapy efficacy.
The Influence of Coumestrol on Sphingolipid Signaling Pathway and Insulin Resistance Development in Primary Rat Hepatocytes
Authors: Zywno Hubert , Bzdega Wiktor , Kolakowski Adrian , Kurzyna Piotr , Harasim-Symbor Ewa , Sztolsztener Klaudia , Chabowski Adrian , Konstantynowicz-Nowicka Karolina
Published: February 2021

Coumestrol is a phytoestrogen widely known for its anti-diabetic, anti-oxidant, and anti-inflammatory properties. Thus, it gets a lot of attention as a potential agent in the nutritional therapy of diseases such as obesity and type 2 diabetes. In our study, we evaluated whether coumestrol affects insulin resistance development via the sphingolipid signaling pathway in primary rat hepatocytes. The cells were isolated from the male Wistar rat’s liver with the use of collagenase perfusion. Next, we incubated the cells with the presence or absence of palmitic acid and/or coumestrol. Additionally, some groups were incubated with insulin. The sphingolipid concentrations were assessed by HPLC whereas the expression of all the proteins was evaluated by Western blot. Coumestrol markedly reduced the accumulation of sphingolipids, namely, ceramide and sphinganine through noticeable inhibition of the ceramide de novo synthesis pathway in insulin-resistant hepatocytes. Moreover, coumestrol augmented the expression of fatty acid transport proteins, especially FATP5 and FAT/CD36, which also were responsible for excessive sphingolipid accumulation. Furthermore, coumestrol altered the sphingolipid salvage pathway, which was observed as the excessive deposition of the sphingosine-1-phosphate and sphingosine. Our study clearly showed that coumestrol ameliorated hepatic insulin resistance in primary rat hepatocytes. Thus, we believe that our study may contribute to the discovery of novel preventive and therapeutic methods for metabolic disorders.
Surgery for Colorectal Cancer: A Trigger for Liver Metastases Development? New Insights into the Underlying Mechanisms
Authors: Grewal Simran , Oosterling Steven J. , van Egmond Marjolein
Published: February 2021

Surgery is a crucial intervention and provides the best chance of cure for patients with colorectal cancer. Experimental and clinical evidence, however, suggests that paradoxically surgery itself may precipitate or accelerate tumor recurrence and/or liver metastasis development. This review addresses the various aspects of surgery-induced metastasis formation and sheds light on the role of inflammation as potential trigger for metastasis development. Understanding these mechanisms may provide potential new perioperative interventions to improve treatment outcomes, and as such could transform the perioperative timeframe from a facilitator of metastatic progression to a window of opportunity to reduce the risk of liver metastasis development. Ultimately, this can potentially improve long-term survival rates and quality of life in patients with colorectal cancer.