bluuebunny/crossref_metadata_2025 huggingface dataset:
Seasonal Coronaviruses and Other Neglected Respiratory Viruses: A Global Perspective and a Local Snapshot
Authors: Ljubin-Sternak Sunčanica , Meštrović Tomislav , Lukšić Ivana , Mijač Maja , Vraneš Jasmina
Published: July 2021

Respiratory viral infections are the leading cause of morbidity and mortality in the world; however, there are several groups of viruses that are insufficiently routinely sought for, and can thus be considered neglected from a diagnostic and clinical standpoint. Timely detection of seasonality of certain respiratory viruses (e.g., enveloped viruses such as seasonal coronaviruses) in the local context can aid substantially in targeted and cost-effective utilization of viral diagnostic approaches. For the other, non-enveloped and year-round viruses (i.e., rhinovirus, adenovirus, and bocavirus), a continuous virological diagnosis needs to be implemented in clinical laboratories to more effectively address the aetiology of respiratory infections, and assess the overall impact of these viruses on disease burden. While the coronavirus disease 2019 (COVID-19) pandemic is still actively unfolding, we aimed to emphasize the persistent role of seasonal coronaviruses, rhinoviruses, adenoviruses and bocaviruses in the aetiology of respiratory infections. Consequently, this paper concentrates on the burden and epidemiological trends of aforementioned viral groups on a global level, but also provides a snapshot of their prevalence patterns in Croatia in order to underscore the potential implications of viral seasonality. An overall global prevalence in respiratory tract infections was found to be between 0.5 and 18.4% for seasonal coronaviruses, between 13 and 59% for rhinoviruses, between 1 and 36% for human adenoviruses, and between 1 and 56.8% for human bocaviruses. A Croatian dataset on patients with respiratory tract infection and younger than 18 years of age has revealed a fairly high prevalence of rhinoviruses (33.4%), with much lower prevalence of adenoviruses (15.6%), seasonal coronaviruses (7.1%), and bocaviruses (5.3%). These insights represent a relevant discussion point in the context of the COVID-19 pandemic where the testing of non-SARS-CoV-2 viruses has been limited in many settings, making the monitoring of disease burden associated with other respiratory viruses rather difficult.
Risk Diagrams Based on Primary Care Electronic Medical Records and Linked Real-Time PCR Data to Monitor Local COVID-19 Outbreaks During the Summer 2020: A Prospective Study Including 7,671,862 People in Catalonia
Authors: Catala Marti , Coma Ermengol , Alonso Sergio , Álvarez-Lacalle Enrique , Cordomi Silvia , López Daniel , Fina Francesc , Medina-Peralta Manuel , Prats Clara , Prieto-Alhambra Daniel
Published: July 2021

Monitoring transmission is a prerequisite for containing COVID-19. We report on effective potential growth (EPG) as a novel measure for the early identification of local outbreaks based on primary care electronic medical records (EMR) and PCR-confirmed cases. Secondly, we studied whether increasing EPG precedes local hospital and intensive care (ICU) admissions and mortality. Population-based cohort including all Catalan citizens' PCR tests, hospitalization, intensive care (ICU) and mortality between 1/07/2020 and 13/09/2020; linked EMR covering 88.6% of the Catalan population was obtained. Nursing home residents were excluded. COVID-19 counts were ascertained based on EMR and PCRs separately. Weekly empirical propagation (ρ7) and 14-day cumulative incidence (A14) and 95% confidence intervals were estimated at care management area (CMA) level, and combined as EPG = ρ7 × A14. Overall, 7,607,201 and 6,798,994 people in 43 CMAs were included for PCR and EMR measures, respectively. A14, ρ7, and EPG increased in numerous CMAs during summer 2020. EMR identified 2.70-fold more cases than PCRs, with similar trends, a median (interquartile range) 2 (1) days earlier, and better precision. Upticks in EPG preceded increases in local hospital admissions, ICU occupancy, and mortality. Increasing EPG identified localized outbreaks in Catalonia, and preceded local hospital and ICU admissions and subsequent mortality. EMRs provided similar estimates to PCR, but some days earlier and with better precision. EPG is a useful tool for the monitoring of community transmission and for the early identification of COVID-19 local outbreaks.
EMERGE Modular Robot: A Tool for Fast Deployment of Evolved Robots
Authors: Moreno Rodrigo , Faiña Andres
Published: July 2021

This work presents a platform for evolution of morphology in full cycle reconfigurable hardware: The EMERGE (Easy Modular Embodied Robot Generator) modular robot platform. Three parts necessary to implement a full cycle process, i.e., assembling the modules in morphologies, testing the morphologies, disassembling modules and repeating, are described as a previous step to testing a fully autonomous system: the mechanical design of the EMERGE module, extensive tests of the modules by first assembling them manually, and automatic assembly and disassembly tests. EMERGE modules are designed to be easy and fast to build, one module is built in half an hour and is constructed from off-the-shelf and 3D printed parts. Thanks to magnetic connectors, modules are quickly attached and detached to assemble and reconfigure robot morphologies. To test the performance of real EMERGE modules, 30 different morphologies are evolved in simulation, transferred to reality, and tested 10 times. Manual assembly of these morphologies is aided by a visual guiding tool that uses AprilTag markers to check the real modules positions in the morphology against their simulated counterparts and provides a color feedback. Assembly time takes under 5 min for robots with fewer than 10 modules and increases linearly with the number of modules in the morphology. Tests show that real EMERGE morphologies can reproduce the performance of their simulated counterparts, considering the reality gap. Results also show that magnetic connectors allow modules to disconnect in case of being subjected to high external torques that could damage them otherwise. Module tracking combined with their easy assembly and disassembly feature enable EMERGE modules to be also reconfigured using an external robotic manipulator. Experiments demonstrate that it is possible to attach and detach modules from a morphology, as well as release the module from the manipulator using a passive magnetic gripper. This shows that running a completely autonomous, evolution of morphology in full cycle reconfigurable hardware of different topologies for robots is possible and on the verge of being realized. We discuss EMERGE features and the trade-off between reusability and morphological variability among different approaches to physically implement evolved robots.
A Porphyromonas gingivalis Capsule-Conjugate Vaccine Protects From Experimental Oral Bone Loss
Authors: Rocha Fernanda G. , Berges Aym , Sedra Angie , Ghods Shirin , Kapoor Neeraj , Pill Lucy , Davey Mary Ellen , Fairman Jeff , Gibson Frank C.
Published: July 2021

Periodontal diseases are chronic inflammatory diseases of the periodontium that result in progressive destruction of the soft and hard tissues supporting the teeth, and it is the most common cause of tooth loss among adults. In the US alone, over 100 million individuals are estimated to have periodontal disease. Subgingival bacteria initiate and sustain inflammation, and, although several bacteria have been associated with periodontitis,Porphyromonas gingivalishas emerged as the key etiological organism significantly contributing to the disease. Currently, intensive clinical maintenance strategies are deployed to mitigate the further progression of disease in afflicted individuals; however, these treatments often fail to stop disease progression, and, as such, the development of an effective vaccine for periodontal disease is highly desirable. We generated a conjugate vaccine, comprising of the purified capsular polysaccharide ofP. gingivalisconjugated to eCRM®, a proprietary and enhanced version of the CRM197 carrier protein with predetermined conjugation sites (Pg-CV). Mice immunized with alum adjuvanted Pg-CV developed robust serum levels of whole organism-specific IgG in comparison to animals immunized with unconjugated capsular polysaccharide alone. Using the murine oral bone loss model, we observed that mice immunized with the capsule-conjugate vaccine were significantly protected from the effects ofP. gingivalis-elicited oral bone loss. Employing a preclinical model of infection-elicited oral bone loss, our data support that a conjugate vaccine incorporating capsular polysaccharide antigen is effective in reducing the main clinical endpoint of periodontal disease—oral bone destruction. Further development of aP. gingivaliscapsule-based conjugate vaccine for preventing periodontal diseases is supported.
Inside Humans: Creating a Simple Layered Anatomical Model from Human Surface Scans
Authors: Komaritzan Martin , Wenninger Stephan , Botsch Mario
Published: July 2021

3D morphable models are widely used to describe the variation of human body shapes. However, these models typically focus on the surface of the human body, since the acquisition of the volumetric interior would require prohibitive medical imaging. In this paper we present a novel approach for creating a volumetric body template and for fitting this template to the surface scan of a person in a just a few seconds. The body model is composed of three surface layers for bones, muscles, and skin, which enclose the volumetric muscle and fat tissue in between them. Our approach includes a data-driven method for estimating the amount of muscle mass and fat mass from a surface scan, which provides more accurate fits to the variety of human body shapes compared to previous approaches. We also show how to efficiently embed fine-scale anatomical details, such as high resolution skeleton and muscle models, into the layered fit of a person. Our model can be used for physical simulation, statistical analysis, and anatomical visualization in computer animation and medical applications, which we demonstrate on several examples.
Data and Information Systems Management for the Urban Water Infrastructure Condition Assessment
Authors: Carriço Nelson , Ferreira Bruno
Published: July 2021

Most of urban water infrastructure around the world were built several decades ago and nowadays they are deteriorated. So, the assets that constitute these infrastructures need to be rehabilitated. Since most of the assets are buried, water utilities face the challenge of deciding how, where and when to rehabilitate. Condition assessment is a vital component on plan rehabilitation actions and is mostly based on the data collected from the managed networks. This collected data need to be put together in order to be transformed into useful information. Nonetheless, the large amount of assets and data involved makes data and information management a challenging task for water utilities, especially in those with as lower digital maturity level. This paper highlights the importance of data and information systems' management for urban water infrastructure condition assessment based on the authors' experience.
Gendered Social Norms Change in Water Governance Structures Through Community Facilitation: Evaluation of the UPWARD Intervention in Tanzania
Authors: Eaton Jacob , Krishna Aditi , Sudi Christina , George Janeth , Magomba Christopher , Eckman Anne , Houck Frances , Taukobong Hannah
Published: July 2021

Background:In rural Tanzania, women and girls disproportionately bear the burden of water scarcity. Gendered social norms on the acceptability of women’s participation in the public sphere limit their decision-making power within local water governance structures. The UPWARD (Uplifting Women’s Participation in Water-Related Decision-Making) intervention sought to understand how a community-based gendered social norms approach using organized diffusion can lead to changes in the gendered social norms impacting women's participation in water-related governance structures.

Methods:As part of WARIDI, a 5-years integrated water resource management (IWRM) program, a gendered-social norms change (GSNC) activity (UPWARD: Uplifting Women’s Participation in Water-Related Decision-Making) was implemented in two villages in Iringa and Kilombero districts. Encouraging organized diffusion, UPWARD promoted gender-equitable norms among a critical mass of community members. WARIDI identified and trained a Community Facilitation Team (CFT) of three women and men to lead a series of education and empowerment sessions in two communities. The intervention reached >300 individuals directly (∼10% of total village population). Changes in social norms were assessed through social norms analysis plots (SNAP) delivered in focus group discussions (FGDs) of 8–12 participants.

Results:At baseline, most participants reported that women’s involvement in water-related decision-making was restricted to household decisions. Men viewed themselves as primary decision-makers in water governance. Women who spoke in village meetings experienced sanctions for disrespect and outspokenness; their husbands were teased for being “controlled.” At endline, participants reported fewer instances of ridicule towards women’s participation. Women expressed a greater sense of solidarity with each other; men reported greater respect for men whose wives contribute. The intervention’s effects appeared more pronounced in areas with greater cultural heterogeneity, suggesting norm change may be harder to affect where norms are tighter.

Conclusion:UPWARD provides evidence that gendered social norms change programs can have identifiable impacts on women’s participation in water-related decision-making over a short time. While other interventions have used larger, multi-level strategies to affect gender norms, UPWARD has shown that community mobilization with brief (∼4 months) but concentrated engagement with communities can promote changes in social norms that persist at least 6 months after intervention’s end.
Playing-Side Analytics in Team Sports: Multiple Directions, Opportunities, and Challenges
Authors: Foster George , O'Reilly Norm , Naidu Zachary
Published: July 2021

This paper describes developments in the player-side analytics in major team sports. We take a decision-making lens to the role of analytics in player decisions by general managers and coaches. We outline key accelerators and inhibitors to the wider adoption and acceptance of data analytics playing a greater role in the decisions of clubs.
Puerto Rican Farmers' Obstacles Toward Recovery and Adaptation Strategies After Hurricane Maria: A Mixed-Methods Approach to Understanding Adaptive Capacity
Authors: Rodríguez-Cruz Luis Alexis , Moore Maya , Niles Meredith T.
Published: July 2021

Farmers across the globe are experiencing compounding shocks that make evident the need to better understand potential drivers and barriers to strengthen adaptive capacity. This is especially true in the context of a disaster, where a disruption in the natural and built environment hinders livelihood strategies and exposes the underlying dynamics that perpetuate vulnerability to natural hazards. As such, the interconnections of structural and individual attributes must be considered when evaluating adaptive capacity. This paper uses a convergent mixed-methods approach to assess Puerto Rican farmers' actual and intended adoption of adaptation practices, in light of the obstacles they faced toward recovery after 2017's category four Hurricane Maria, to contribute to better understanding adaptive capacity. This study uses data from 405 farmers across Puerto Rico (87% response rate), surveyed 8 months after Maria by agricultural agents of the Extension Service of the University of Puerto Rico at Mayagüez. Quantitative data was assessed through negative binomial regressions (actual adoption) and generalized linear models (intended adoption), while qualitative data (reported obstacles) were analyzed through thematic analysis. This study found that almost half of farmers adopted an adaptation practice after Maria, and that in many cases, broader structures, such as systems of governance, farmers' social networks, and infrastructure, affect adaptive capacity more than individual perceptions of capacity. Future adaptation strategies and interventions, especially in the context of disaster, should consider the extent to which structural factors hinder individuals' ability to prepare for, respond, and recover from the impacts of these shocks. Our results show that there might be opportunity to enact new systems in light of catastrophic events, but this does not solely depend on individual actions. The mixed-methods approach used can inform future studies in better assessing adaptive capacity from a standpoint that incorporates individual and structural components.
Developmental Exposure to Endocrine Disrupting Chemicals and Its Impact on Cardio-Metabolic-Renal Health
Authors: Singh Radha Dutt , Koshta Kavita , Tiwari Ratnakar , Khan Hafizurrahman , Sharma Vineeta , Srivastava Vikas
Published: July 2021

Developmental origin of health and disease postulates that the footprints of early life exposure are followed as an endowment of risk for adult diseases. Epidemiological and experimental evidence suggest that an adverse fetal environment can affect the health of offspring throughout their lifetime. Exposure to endocrine disrupting chemicals (EDCs) during fetal development can affect the hormone system homeostasis, resulting in a broad spectrum of adverse health outcomes. In the present review, we have described the effect of prenatal EDCs exposure on cardio-metabolic-renal health, using the available epidemiological and experimental evidence. We also discuss the potential mechanisms of their action, which include epigenetic changes, hormonal imprinting, loss of energy homeostasis, and metabolic perturbations. The effect of prenatal EDCs exposure on cardio-metabolic-renal health, which is a complex condition of an altered biological landscape, can be further examined in the case of other environmental stressors with a similar mode of action.
Impact of Quantisal® Oral Fluid Collection Device on Drug Stability
Authors: Riggio Michela , Dave Keyur A. , Koscak Branko , Blakey Mark , Appleton Charles
Published: July 2021

The stability of drugs can affect drug tests and interpretations. A comprehensive study to verify drug stability in Quantisal® oral fluid (OF) collection device was undertaken in accordance with Australian standard, AS/NZS 4760:2019 (SAI-Global, 2019). The evaluation was performed for the following drugs: (±) amphetamine, (±) methylamphetamine, (±) 3,4-methylenedioxymethylamphetamine (MDMA), (−)Δ9-tetrahydrocannabinol (THC), cocaine, benzoylecgonine, morphine, codeine, and oxycodone. Stability was assessed at four different storage temperatures over seven time points at ±50% cut-off concentrations (Appendix A, Para A4-4.1, AS/NZS 4760:2019) (SAI-Global, 2019). All drugs were found to be significantly more stable at 4 and –20°C, with stability spanning at least 14 days with percentage change within ±20% from the cut-off concentrations (SAI-Global, 2019). In addition, we report a variation trend with cocaine and benzoylecgonine at elevated temperatures, suggesting hydrolytic decomposition of cocaine and a concomitant increase in benzoylecgonine quantitative values. We confirm the cross-talk by showing that the percentage change in the profile of average cocaine-benzoylecgonine measurement is within the acceptance concentration range of ±20%. This finding highlights the importance of precaution during storage and careful considerations during subsequent interpretation of liquid chromatography-mass spectrometry (LCMS) measurements.
Liver-Metastasis-Related Genes are Potential Biomarkers for Predicting the Clinical Outcomes of Patients with Pancreatic Adenocarcinoma
Authors: Dong Yinlei , Tian Junjie , Yan Bingqian , Lv Kun , Li Ji , Fu Deliang
Published: July 2021

It is widely acknowledged that metastasis determines the prognosis of pancreatic adenocarcinoma (PAAD), and the liver is the most primary distant metastatic location of PAAD. It is worth exploring the value of liver-metastasis-related genetic prognostic signature (LM-PS) in predicting the clinical outcomes of PAAD patients post R0 resection. We collected 65 tumors and 165 normal pancreatic data from The Cancer Genome Atlas (TCGA) and the Genotype-Tissue Expression project (GTEx), respectively. Differentially expressed genes (DEGs) between primary tumor and normal pancreatic samples were intersected with DEGs between primary tumor samples with liver metastasis and those without new tumor events. The intersected 45 genes were input into univariate Cox regression analysis to identify the prognostic genes. Thirty-three prognostic liver-metastasis-related genes were identified and included in least absolute shrinkage and selection operator (LASSO) analysis to develop a seven-gene LM-PS, which included six risk genes (ANO1, FAM83A, GPR87, ITGB6, KLK10, and SERPINE1) and one protective gene (SMIM32). The PAAD patients were grouped into low- and high-risk groups based on the median value of risk scores. The LM-PS harbored an independent predictive ability to distinguish patients with a high-risk of death and liver metastasis after R0 resection. Moreover, a robust prognostic nomogram based on LM-PS, the number of positive lymph nodes, and histologic grade were established to predict the overall survival of PAAD patients. Besides, a transcription factor‐microRNA coregulatory network was constructed for the seven LM-PS genes, and the immune infiltration and genomic alterations were systematically explored in the TGCA-PAAD cohort.
A Sensitivity Analysis of the SPACSYS Model
Authors: Shan Yan , Huang Mingbin , Harris Paul , Wu Lianhai
Published: July 2021

A sensitivity analysis is critical for determining the relative importance of model parameters to their influence on the simulated outputs from a process-based model. In this study, a sensitivity analysis for the SPACSYS model, first published in Ecological Modelling (Wu, et al., 2007), was conducted with respect to changes in 61 input parameters and their influence on 27 output variables. Parameter sensitivity was conducted in a ‘one at a time’ manner and objectively assessed through a single statistical diagnostic (normalized root mean square deviation) which ranked parameters according to their influence of each output variable in turn. A winter wheat field experiment provided the case study data. Two sets of weather elements to represent different climatic conditions and four different soil types were specified, where results indicated little influence on these specifications for the identification of the most sensitive parameters. Soil conditions and management were found to affect the ranking of parameter sensitivities more strongly than weather conditions for the selected outputs. Parameters related to drainage were strongly influential for simulations of soil water dynamics, yield and biomass of wheat, runoff, and leaching from soil during individual and consecutive growing years. Wheat yield and biomass simulations were sensitive to the ‘ammonium immobilised fraction’ parameter that related to soil mineralization and immobilisation. Simulations of CO2 release from the soil and soil nutrient pool changes were most sensitive to external nutrient inputs and the process of denitrification, mineralization, and decomposition. This study provides important evidence of which SPACSYS parameters require the most care in their specification. Moving forward, this evidence can help direct efficient sampling and lab analyses for increased accuracy of such parameters. Results provide a useful reference for model users on which parameters are most influential for different simulation goals, which in turn provides better informed decision making for farmers and government policy alike.
Deep Learning-Based Estimation of Crop Biophysical Parameters Using Multi-Source and Multi-Temporal Remote Sensing Observations
Authors: Bahrami Hazhir , Homayouni Saeid , Safari Abdolreza , Mirzaei Sayeh , Mahdianpari Masoud , Reisi-Gahrouei Omid
Published: July 2021

Remote sensing data are considered as one of the primary data sources for precise agriculture. Several studies have demonstrated the excellent capability of radar and optical imagery for crop mapping and biophysical parameter estimation. This paper aims at modeling the crop biophysical parameters, e.g., Leaf Area Index (LAI) and biomass, using a combination of radar and optical Earth observations. We extracted several radar features from polarimetric Synthetic Aperture Radar (SAR) data and Vegetation Indices (VIs) from optical images to model crops’ LAI and dry biomass. Then, the mutual correlations between these features and Random Forest feature importance were calculated. We considered two scenarios to estimate crop parameters. First, Machine Learning (ML) algorithms, e.g., Support Vector Regression (SVR), Random Forest (RF), Gradient Boosting (GB), and Extreme Gradient Boosting (XGB), were utilized to estimate two crop biophysical parameters. To this end, crops’ dry biomass and LAI were estimated using three input data; (1) SAR polarimetric features; (2) spectral VIs; (3) integrating both SAR and optical features. Second, a deep artificial neural network was created. These input data were fed to the mentioned algorithms and evaluated using the in-situ measurements. These observations of three cash crops, including soybean, corn, and canola, have been collected over Manitoba, Canada, during the Soil Moisture Active Validation Experimental 2012 (SMAPVEX-12) campaign. The results showed that GB and XGB have great potential in parameter estimation and remarkably improved accuracy. Our results also demonstrated a significant improvement in the dry biomass and LAI estimation compared to the previous studies. For LAI, the validation Root Mean Square Error (RMSE) was reported as 0.557 m2/m2 for canola using GB, and 0.298 m2/m2 for corn using GB, 0.233 m2/m2 for soybean using XGB. RMSE was reported for dry biomass as 26.29 g/m2 for canola utilizing SVR, 57.97 g/m2 for corn using RF, and 5.00 g/m2 for soybean using GB. The results revealed that the deep artificial neural network had a better potential to estimate crop parameters than the ML algorithms.
In Silico Analysis of Extended-Spectrum β-Lactamases in Bacteria
Authors: Mlynarcik Patrik , Chudobova Hana , Zdarska Veronika , Kolar Milan
Published: July 2021

The growing bacterial resistance to available β-lactam antibiotics is a very serious public health problem, especially due to the production of a wide range of β-lactamases. At present, clinically important bacteria are increasingly acquiring new elements of resistance to carbapenems and polymyxins, including extended-spectrum β-lactamases (ESBLs), carbapenemases and phosphoethanolamine transferases of the MCR type. These bacterial enzymes limit therapeutic options in human and veterinary medicine. It must be emphasized that there is a real risk of losing the ability to treat serious and life-threatening infections. The present study aimed to design specific oligonucleotides for rapid PCR detection of ESBL-encoding genes and in silico analysis of selected ESBL enzymes. A total of 58 primers were designed to detect 49 types of different ESBL genes. After comparing the amino acid sequences of ESBLs (CTX-M, SHV and TEM), phylogenetic trees were created based on the presence of conserved amino acids and homologous motifs. This study indicates that the proposed primers should be able to specifically detect more than 99.8% of all described ESBL enzymes. The results suggest that the in silico tested primers could be used for PCR to detect the presence of ESBL genes in various bacteria, as well as to monitor their spread.
The Anxiolytic and Antidepressant Effects of Diallyl Disulfide and GYY4137 in Animals with Chronic Neuropathic Pain
Authors: Bai Xue , Batallé Gerard , Pol Olga
Published: July 2021

When neuropathic pain is maintained long term, it can also lead to the development of emotional disorders that are even more intense than pain perception and difficult to treat. Hydrogen sulfide (H2S) donors relieve chronic pain, but their effects on the associated mood disorders are not completely elucidated. We evaluated if treatment with DADS (diallyl disulfide) or GYY4137 (morpholin-4-ium 4-methoxyphenyl(morpholino) phosphinodithioate dichloromethane complex), two slow-releasing H2S donors, inhibits the anxiety- and depressive-like behaviors that concur with chronic neuropathic pain generated by sciatic nerve injury in mice. The modulatory role of these drugs in the inflammatory, apoptotic, and oxidative processes implicated in the development of the affective disorders was assessed. Our results revealed the anxiolytic, antidepressant, and antinociceptive properties of DADS and GYY4137 during neuropathic pain by inhibiting microglial activation and the up-regulation of phosphoinositide 3-kinase/phosphorylated protein kinase B and BAX in the amygdala (AMG) and/or periaqueductal gray matter (PAG). Both treatments also normalized and/or activated the endogenous antioxidant system, but only DADS blocked ERK 1/2 phosphorylation. Both H2S donors decreased allodynia and hyperalgesia in a dose-dependent manner by activating the Kv7 potassium channels and heme oxygenase 1 signaling pathways. This study provides evidence of the anxiolytic and antidepressant properties of DADS and GYY4137 during neuropathic pain and reveals their analgesic actions, suggesting that these therapeutic properties may result from the inhibition of the inflammatory, apoptotic, and oxidative responses in the AMG and/or PAG. These findings support the use of these treatments for the management of affective disorders accompanying chronic neuropathic pain.
Impact of View-Dependent Image-Based Effects on Perception of Visual Realism and Presence in Virtual Reality Environments Created Using Multi-Camera Systems
Authors: de Dinechin Grégoire Dupont , Paljic Alexis , Tanant Jonathan
Published: July 2021

Several recent works have presented image-based methods for creating high-fidelity immersive virtual environments from photographs of real-world scenes. In this paper, we provide a user-centered evaluation of such methods by way of a user study investigating their impact on viewers’ perception of visual realism and sense of presence. In particular, we focus on two specific elements commonly introduced by image-based approaches. First, we investigate the extent to which using dedicated image-based rendering algorithms to render the scene with view-dependent effects (such as specular highlights) causes users to perceive it as being more realistic. Second, we study whether making the scene fade out beyond a fixed volume in 3D space significantly reduces participants’ feeling of being there, examining different sizes for this viewing volume. To provide details on the virtual environment used in the study, we also describe how we recreated a museum gallery for room-scale virtual reality using a custom-built multi-camera rig. The results of our study show that using image-based rendering to render view-dependent effects can effectively enhance the perception of visual realism and elicit a stronger sense of presence, even when it implies constraining the viewing volume to a small range of motion.
Compact Photonic-Crystals Based Isolator Using Ni–Zn Gyromagnetic Ferrite Posts
Authors: Wang Yong , Xu Biaogang , Zhang Dengguo , He Wenlong , Ian Hou
Published: July 2021

A Faraday rotation isolator is conventionally achieved by connecting a matched load to a three-port circulator. It obtains superior performance (isolation > 20 dB) at the inevitable cost of non-ideal size. In order to adapt to the miniaturizations and integrations required for future 5G communication systems, it is particularly important to reduce the size of the devices. This work demonstrates a photonic crystal-based isolator design, comprising a unique reflecting cavity and a built-in fan-shaped coupler, where four Ni–Zn ferrite posts achieve the rotations. The design with the compact size of about 46.6 × 41.6 × 4.32 mm3 obtains excellent forward transmission efficiency and reverse isolation of 0.50 dB and 44.20 dB, respectively.
Automated Extraction and Time-Cost Prediction of Contractual Reporting Requirements in Construction Using Natural Language Processing and Simulation
Authors: Jafari Parinaz , Al Hattab Malak , Mohamed Emad , AbouRizk Simaan
Published: July 2021

Due to a lack of suitable methods, extraction of reporting requirements from lengthy construction contracts is often completed manually. Because of this, the time and costs associated with completing reporting requirements are often informally approximated, resulting in underestimations. Without a clear understanding of requirements, contractors are prevented from implementing improvements to reporting workflows prior to project execution. This study developed an automated reporting requirement identification and time–cost prediction framework to overcome this challenge. Reporting requirements are extracted using Natural Language Processing (NLP) and Machine Learning (ML), and stochastic simulations are used to predict overhead costs and durations associated with report preparation. Functionality and validity of the framework were demonstrated using real contracts, and an accuracy of over 95% was observed. This framework provides a tool to rapidly and efficiently retrieve requirements and quantify the time and costs associated with reporting, in turn providing necessary insights to streamline reporting workflows.
Low-Voltage Ride-Through of the Novel Voltage Source-Controlled PMSG-Based Wind Turbine Based on Switching the Virtual Resistor
Authors: Sang Shun , Pei Binhui , Huang Jiejie , Zhang Lei , Xue Xiaocen
Published: July 2021

Voltage source (VS) control based on inertia synchronization is a novel phase lock loop (PLL)-less autonomous grid-synchronization control strategy suitable for the permanent magnet synchronous generator (PMSG)-based wind turbine. It can autonomously sense grid frequency fluctuations by adopting the dynamics of DC-link capacitor, and it has the advantage of stable operation in an extremely weak grid. This paper further studies the low-voltage ride-through (LVRT) of the PMSG-based wind turbine under the VS control, and presents a wind turbine structure with the additional energy storage battery on the DC side, which not only improves its LVRT capability but also enables the wind turbine to participate in the grid primary frequency regulation. The transient characteristics of VS-controlled wind turbines after the occurrence of the short-circuit fault are analyzed, and a current suppression strategy via switching the virtual resistor in the control loop of the grid-side converter (GCS) is presented. Through coordination with the energy storage battery, the LVRT of the PMSG-based wind turbine is realized, which has the advantage of withstanding a long-time short-circuit fault. Finally, based on the PSCAD/EMTDC simulation platform, the feasibility of the control strategy and the correctness of the theoretical analysis are verified.
Effect of the Location of Strut Chordae Insertion on Computational Modeling and Biomechanical Evaluation of Mitral Valve Dynamics
Authors: Hong Woojae , Jeong Soohwan , Ko Minsung , Kim Hyun Hak , Kim Hyunggun
Published: July 2021

The strut chordae (SC) have a unique structure and play an important role in reinforcing the tunnel-shaped configuration of the mitral valve (MV) at the inflow and outflow tracts. We investigated the effect of varying the SC insertion location on normal MV function and dynamics to better understand the complex MV structures. A virtual parametric MV model was designed to replicate a normal human MV, and a total of nine MV modes were created from combinations of apical and lateral displacements of the SC insertion location. MV function throughout the full cardiac cycle was simulated using dynamic finite element analysis for all MV models. While the leaflet stress distribution and coaptation showed similar patterns in all nine MV models, the maximum leaflet stress values increased in proportion to the width of the SC insertion locations. A narrower SC insertion location resulted in a longer coaptation length and a smaller anterior coaptation angle. The top-narrow MV model demonstrated the shortest anterior leaflet bulging distance, lower stresses across the anterior leaflet, and the lowest maximum stresses. This biomechanical evaluation strategy can help us better understand the effect of the SC insertion locations on mechanism, function, and pathophysiology of the MV.
Semi-Quantitative Analysis of Major Elements and Minerals: Clues from a Late Pleistocene Core from Campos Basin
Authors: Pedrão Guilherme A. , Costa Karen B. , Toledo Felipe A. L. , Tomazella Mariana O. , Jovane Luigi
Published: July 2021

Element and mineral associations are fundamental parameters for palaeoceanographical reconstructions but laboratory methodologies are expensive, time-consuming and need a lot of material. Here, we investigate the quality and reliability of XRF measurements of major elements (Fe, Ti and Ca) using BTX II Benchtop, by comparing them with previous ICP-OES elemental analysis for a set of Late Pleistocene marine sediments from Campos Basin. Although the numerical values of the logarithmic form of the elementary ratios were different, the lnTi/Ca and lnFe/Ca ratios measured by both techniques (XRF and ICP-OES) presented similar downcore results. To correct the XRF intensity data, a linear regression model was calculated and, based on the linear equation generated, the logarithmic values of the elementary XRF ratios were corrected. After the correction, One-Sample t-test and Bland–Altman plot show that both techniques obtained similar results. In addition, a brief paleoceanographic interpretation, during the MIS 5 and MIS 4 periods, was conducted by comparing mineralogical and elementary analysis aiming to reconstruct the variations of the terrigenous input to the studied area. As a conclusion, the results from XRF measurements (BTX II) presented to confirm the viability of such a technique, showing that analysis using BTX II is a reliable, cheap, rapid and non-destructive option for obtaining elementary ratios and mineralogical downcore results at high resolution, allowing stratigraphic and paleoceanographic interpretations.
Nasopharyngeal Microbiome Community Composition and Structure Is Associated with Severity of COVID-19 Disease and Breathing Treatment
Authors: Feehan Amy K. , Rose Rebecca , Nolan David J. , Spitz Austin M. , Graubics Karlis , Colwell Rita R. , Garcia-Diaz Julia , Lamers Susanna L.
Published: July 2021

Viral infections are known to modulate the upper respiratory tract microbiome, but few studies have addressed differences in the nasopharyngeal microbiome following SARS-CoV-2 infection. Using nasopharyngeal swab medical waste samples from 79 confirmed SARS-CoV-2 positive and 20 SARS-CoV-2 negative patients, we assessed microbiome composition with metagenomic sequencing. COVID-19 status and breathing assistive device use was associated with differences in beta diversity, principal component analyses, community composition and abundance of several species. Serratia more frequently appeared in COVID-19 patient samples compared to negative patient samples, and Serratia, Streptococcus, Enterobacter, Veillonella, Prevotella, and Rothia appeared more frequently in samples of those who used breathing assistive devices. Smoking and age were associated with differences in alpha diversity. Cross-sectional differences in the microbiome were apparent with SARS-CoV-2 infection, but longitudinal studies are needed to understand the dynamics of viral and breathing treatment modulation of microbes.
Comparison of CMIP5 and CMIP6 Multi-Model Ensemble for Precipitation Downscaling Results and Observational Data: The Case of Hanjiang River Basin
Authors: Wang Dong , Liu Jiahong , Shao Weiwei , Mei Chao , Su Xin , Wang Hao
Published: July 2021

Evaluating global climate model (GCM) outputs is essential for accurately simulating future hydrological cycles using hydrological models. The GCM multi-model ensemble (MME) precipitation simulations of the Climate Model Intercomparison Project Phases 5 and 6 (CMIP5 and CMIP6, respectively) were spatially and temporally downscaled according to a multi-site statistical downscaling method for the Hanjiang River Basin (HRB), China. Downscaled precipitation accuracy was assessed using data collected from 14 meteorological stations in the HRB. The spatial performances, temporal performances, and seasonal variations of the downscaled CMIP5-MME and CMIP6-MME were evaluated and compared with observed data from 1970–2005. We found that the multi-site downscaling method accurately downscaled the CMIP5-MME and CMIP6-MME precipitation simulations. The downscaled precipitation of CMIP5-MME and CMIP6-MME captured the spatial pattern, temporal pattern, and seasonal variations; however, precipitation was slightly overestimated in the western and central HRB and precipitation was underestimated in the eastern HRB. The precipitation simulation ability of the downscaled CMIP6-MME relative to the downscaled CMIP5-MME improved because of reduced biases. The downscaled CMIP6-MME better simulated precipitation for most stations compared to the downscaled CMIP5-MME in all seasons except for summer. Both the downscaled CMIP5-MME and CMIP6-MME exhibit poor performance in simulating rainy days in the HRB.
Oxidative Stress and Mitochondrial Damage in Dry Age-Related Macular Degeneration Like NFE2L2/PGC-1α -/- Mouse Model Evoke Complement Component C5a Independent of C3
Authors: Sridevi Gurubaran Iswariyaraja , Heloterä Hanna , Marry Stephen , Koskela Ali , Hyttinen Juha M. T. , Paterno Jussi J. , Urtti Arto , Chen Mei , Xu Heping , Kauppinen Anu , Kaarniranta Kai
Published: July 2021

Aging-associated chronic oxidative stress and inflammation are known to be involved in various diseases, e.g., age-related macular degeneration (AMD). Previously, we reported the presence of dry AMD-like signs, such as elevated oxidative stress, dysfunctional mitophagy and the accumulation of detrimental oxidized materials in the retinal pigment epithelial (RPE) cells of nuclear factor erythroid 2-related factor 2, and a peroxisome proliferator-activated receptor gamma coactivator 1-alpha (NFE2L2/PGC1α) double knockout (dKO) mouse model. Here, we investigated the dynamics of inflammatory markers in one-year-old NFE2L2/PGC1α dKO mice. Immunohistochemical analysis revealed an increase in levels of Toll-like receptors 3 and 9, while those of NOD-like receptor 3 were decreased in NFE2L2/PGC1α dKO retinal specimens as compared to wild type animals. Further analysis showed a trend towards an increase in complement component C5a independent of component C3, observed to be tightly regulated by complement factor H. Interestingly, we found that thrombin, a serine protease enzyme, was involved in enhancing the terminal pathway producing C5a, independent of C3. We also detected an increase in primary acute phase C-reactive protein and receptor for advanced glycation end products in NFE2L2/PGC1α dKO retina. Our main data show C5 and thrombin upregulation together with decreased C3 levels in this dry AMD-like model. In general, the retina strives to mount an orchestrated inflammatory response while attempting to maintain tissue homeostasis and resolve inflammation.
β-Lactamases: Sequence, Structure, Function, and Inhibition
Authors: Oelschlaeger Peter
Published: July 2021

β-Lactams were the first class of antibiotics to be discovered and the second to be introduced into the clinic in the 1940s [...]
Measurement of Low Concentration of Micro-Plastics by Detection of Bioaffinity-Induced Particle Retention Using Surface Plasmon Resonance Biosensors
Authors: Huang Chen-Ji , Narasimha Gudivada Vijaya , Chen Yu-Cheng , Chen Jen-Kun , Dong Guo-Chung
Published: July 2021

The issue of micro-plastics is becoming more and more important due to their ubiquity and the harm they cause to the human body. Therefore, evaluating the biological–physical interaction of micro-plastics with health cells has become the focus of many research efforts. This study focuses on the movement mode and low concentration detection development for micro-plastics in surface plasmon resonance (SPR). Firstly, 20-micrometer micro-plastics were prepared by grinding and filtering, and the movement mode was explored; then, the characteristics were investigated by SPR. Chromatographic analysis showed that the surface charge of micro-plastics dominated the elution time, and estrogen receptors (ERs) played a supporting role. A difference of micro-plastics in SPR sensorgram was observed, inferring the micro-plastics’ movement in rolling mode on the ERs. Characteristics analysis indicated that the low particle number of micro-plastics on SPR showed a linear relationship with the response unit (RU). When ERs were immobilized on the biosensor, the force of the binding of micro-plastics to ERs under an ultra-low background was equivalent to the dissociation rate constant shown as follows: PS (0.05 nM) > PVC (0.09 nM) > PE (0.14 nM). The ELISA-like magnetic beads experiment verified the specificity between ERs and micro-plastics. Therefore, by using the SPR technique, a biological-derived over-occupation of PS was found via higher binding force with ERs and longer retention time. In the future, there will be considerable potential for micro-plastics issues, such as identification in natural samples, biomarking, real-time detection in specific environments/regions and human health subject.
The Scavenging Effect of Myoglobin from Meat Extracts toward Peroxynitrite Studied with a Flow Injection System Based on Electrochemical Reduction over a Screen-Printed Carbon Electrode Modified with Cobalt Phthalocyanine: Quantification and Kinetics
Authors: Hosu Ioana Silvia , Constantinescu-Aruxandei Diana , Oancea Florin , Doni Mihaela
Published: July 2021

The scavenging activity of myoglobin toward peroxynitrite (PON) was studied in meat extracts, using a new developed electrochemical method (based on cobalt phthalocyanine-modified screen-printed carbon electrode, SPCE/CoPc) and calculating kinetic parameters of PON decay (such as half-time and apparent rate constants). As reactive oxygen/nitrogen species (ROS/RNS) affect the food quality, the consumers can be negatively influenced. The discoloration, rancidity, and flavor of meat are altered in the presence of these species, such as PON. Our new highly thermically stable, cost-effective, rapid, and simple electrocatalytical method was combined with a flow injection analysis system to achieve high sensitivity (10.843 nA µM−1) at a nanomolar level LoD (400 nM), within a linear range of 3–180 µM. The proposed biosensor was fully characterized using SEM, FTIR, Raman spectroscopy, Cyclic Voltammetry (CV), Differential Pulse Voltammetry (DPV), and Linear Sweep Voltammetry (LSV). These achievements were obtained due to the CoPc-mediated reduction of PON at very low potentials (around 0.1 V vs. Ag/AgCl pseudoreference). We also proposed a redox mechanism involving two electrons in the reduction of peroxynitrite to nitrite and studied some important interfering species (nitrite, nitrate, hydrogen peroxide, dopamine, ascorbic acid), which showed that our method is highly selective. These features make our work relevant, as it could be further applied to study the kinetics of important oxidative processes in vivo or in vitro, as PON is usually present in the nanomolar or micromolar range in physiological conditions, and our method is sensitive enough to be applied.