bluuebunny/crossref_metadata_2025 huggingface dataset:
Carotenoid Profile in Maternal/Cord Plasma and Changes in Breast Milk along Lactation and Its Association with Dietary Intake: A Longitudinal Study in a Coastal City in Southern China
Authors: Dai Xinyao , Yin Huanhuan , Zhang Jing , Tian Fang , Cai Xiaokun , Mao Yingyi , Sun Hanxiao , Wang He , Li Xiang , Zhu Hui-Lian , Zhang Lishi , Chen Jinyao , Zhao Yanrong
Published: May 2022

In this study, changes of carotenoids in breast milk were observed longitudinally for up to one year. Our study aimed to analyze the profile of carotenoids in breast milk and maternal/cord plasma and its correlation with dietary intake in Guangzhou. Plasma and breast milk samples of five stages during lactation (i.e., colostrum; transitional milk; and early, medium, and late mature milk) were collected from lactating mothers. The food frequency questionnaire (FFQ) was used for collecting data on dietary intake in the corresponding stages. Levels of lutein, zeaxanthin, β-cryptoxanthin, β-carotene, and lycopene were analyzed by high-performance liquid chromatography. We found that the total carotenoid level decreased gradually with the extension of lactation and eventually stabilized. Among them, the content of lutein increased from colostrum to transitional milk and decreased thereafter until it plateaued in the mature milk. Furthermore, lutein was reported as the dominant nutrient in maternal plasma, cord plasma, transitional milk, and mature milk at up to 400 days postpartum, while beta-carotene was predominant in colostrum. The content of β-carotenoid in middle and late mature breast milk was related to dietary intake (r = 1.690, p < 0.05). Carotenoid level in cord blood was lower than that in the mother’s plasma and was related to the carotenoid intake in the mother’s diet. Correlation of carotenoids between maternal and umbilical cord blood, breast milk, and maternal blood could well reflect the transport of carotenoids. These findings may help to guide mothers’ diets during breastfeeding.
The Use of Probiotics as Adjuvant Therapy of Periodontal Treatment: A Systematic Review and Meta-Analysis of Clinical Trials
Authors: Hardan Louis , Bourgi Rim , Cuevas-Suárez Carlos Enrique , Flores-Rodríguez Maythé , Omaña-Covarrubias Arianna , Nicastro Marco , Lazarescu Florin , Zarow Maciej , Monteiro Paulo , Jakubowicz Natalia , Proc Patrycja , Lukomska-Szymanska Monika
Published: May 2022

For many years, the use of probiotics in periodontitis treatment was reflected in their abilities to control the immune response of the host to the presence of pathogenic microorganisms and to upset periodontopathogens. Accordingly, the aim of the present study was to assess the use of probiotics as adjuvant therapy on clinical periodontal parameters throughout a systematic review and meta-analysis. The literature was screened, up to 4 June 2021, by two independent reviewers (L.H. and R.B.) in four electronic databases: PubMed (MedLine), ISI Web of Science, Scielo, and Scopus. Only clinical trials that report the effect of the use of probiotics as adjuvants in the treatment of periodontal disease were included. Comparisons were carried out using Review Manager Software version 5.3.5 (The Nordic Cochrane Centre, The Cochrane Collaboration, Copenhagen, Denmark). A total of 21 studies were considered for the meta-analysis. For the index plaque, the use of probiotics did not improve this clinical parameter (p = 0.16). On the other hand, for the periodontal pocket depth, the clinical attachment loss, the bleeding on probing, and the use of probiotics as adjuvant therapy resulted in an improvement of these parameters, since the control group achieved statistically higher values of this parameter (p < 0.001; p < 0.001; and p = 0.005, respectively). This study suggests that the use of probiotics led to an improvement in periodontal pocket depth, clinical attachment loss, and bleeding on probing parameters. On the other hand, this protocol seems to not be beneficial for the index plaque parameter.
Melatonin-Eluting Contact Lenses Effect on Tear Volume: In Vitro and In Vivo Experiments
Authors: Serramito María , Pereira-da-Mota Ana F. , Carpena-Torres Carlos , Huete-Toral Fernando , Alvarez-Lorenzo Carmen , Carracedo Gonzalo
Published: May 2022

(1) Background: The purpose of this study was to synthesize melatonin-eluting contact lenses (CLs) and evaluate both the ocular kinetics of the released melatonin and its effect on tear volume and intraocular pressure. (2) Methods: In vitro, melatonin-eluting CLs were synthesized by using non-functionalized (HEMA) and functionalized (HEMA/APMA) monomers. In vivo, a short-term prospective and randomized study was performed on 15 rabbits divided into two groups: 12 rabbits wearing functionalized CLs and 3 rabbits without CLs as a control. The melatonin levels in tears, aqueous humor, vitreous body and retina, tear volume, and intraocular pressure were measured for 8 h. (3) Results: In vitro, both monomers did not show differences in terms of melatonin loading and release (p ≥ 0.05). In vivo, the melatonin concentration was elevated in tears and aqueous humor after 2 and 4 h of wearing CLs, respectively (p < 0.05). Additionally, the CLs increased tear volume for 2 h (p < 0.05). (4) Conclusions: The melatonin-eluting CLs released their content over the ocular surface for at least 2 h, which was associated with a secretagogue effect on tear volume. However, the increased amount of melatonin found in the aqueous humor had no effect on intraocular pressure.
In Silico Analysis of Plant Flavonoids as Potential Inhibitors of Newcastle Disease Virus V Protein
Authors: Sarwar Waseem , Liaqat Iram , Yasmeen Tahira , Nahid Nazia , Alkahtani Saad , Al-Qahtani Ahmed A. , Nawaz-ul-Rehman Muhammad Shah , Mubin Muhammad
Published: May 2022

Newcastle disease is a viral infection causing serious economic losses to the global poultry industry. The V protein of Newcastle disease virus (NDV) is a pathogenicity determinant having various functions such as the suppression of apoptosis and replication of the NDV. This study was designed to assess the resistance potential of plant flavonoids against the V protein of Newcastle disease virus. Sequence analysis was performed using EXPASY and ProtParam tools. To build the three-dimensional structure of V protein, a homology-modeling method was used. Plant flavonoids with formerly reported therapeutic benefits were collected from different databases to build a library for virtual screening. Docking analysis was performed using the modeled structure of V protein on MOE software. Interaction analysis was also performed by MOE to explain the results of docking. Sequence analysis and physicochemical properties showed that V protein is negatively charged, acidic in nature, and relatively unstable. The 3D structure of the V protein showed eight β-pleated sheets, three helices, and ten coiled regions. Based on docking score, ten flavonoids were selected as potential inhibitors of V protein. Furthermore, a common configuration was obtained among these ten flavonoids. The interaction analysis also identified the atoms involved in every interaction of flavonoid and V protein. Molecular dynamics (MD) simulation confirmed the stability of two compounds, quercetin-7-O-[α-L-rhamnopyranosyl(1→6)-β-D-galactopyranoside] and luteolin 7-O-neohesperidoside, at 100 ns with V protein. The identified compounds through molecular docking and MD simulation could have potential as NDV-V protein inhibitor after further validation. This study could be useful for the designing of anti-NDV drugs.
“Like Armageddon”: Kōfuku no Kagaku and the COVID-19 Pandemic
Authors: Pokorny Lukas K. , Mayer Patricia Sophie
Published: May 2022

Kōfuku no Kagaku is a most visible new religious actor in contemporary Japan thanks to the vast publishing activities of its founder and its widespread professional use of new media. This paper examines how Kōfuku no Kagaku engages with the COVID-19 pandemic in practical and doctrinal terms. Notably, early in the pandemic, Kōfuku no Kagaku’s international promotion of spiritual cures and vaccines even prompted The New York Times to feature the group in a widely circulated article in April 2020. This paper outlines these “spiritual technologies” and examines their doctrinal rationale as well as the wider doctrinal appropriation of the COVID-19 pandemic. It will be shown how the latter is instrumentalised to echo Kōfuku no Kagaku’s millenarian agenda.
A Context Feature Enhancement Network for Building Extraction from High-Resolution Remote Sensing Imagery
Authors: Chen Jinzhi , Zhang Dejun , Wu Yiqi , Chen Yilin , Yan Xiaohu
Published: May 2022

The complexity and diversity of buildings make it challenging to extract low-level and high-level features with strong feature representation by using deep neural networks in building extraction tasks. Meanwhile, deep neural network-based methods have many network parameters, which take up a lot of memory and time in training and testing. We propose a novel fully convolutional neural network called the Context Feature Enhancement Network (CFENet) to address these issues. CFENet comprises three modules: the spatial fusion module, the focus enhancement module, and the feature decoder module. First, the spatial fusion module aggregates the spatial information of low-level features to obtain buildings’ outline and edge information. Secondly, the focus enhancement module fully aggregates the semantic information of high-level features to filter the information of building-related attribute categories. Finally, the feature decoder module decodes the output of the above two modules to segment the buildings more accurately. In a series of experiments on the WHU Building Dataset and the Massachusetts Building Dataset, our CFENet balances efficiency and accuracy compared to the other four methods we compared, and achieves optimality on all five evaluation metrics: PA, PC, F1, IoU, and FWIoU. This indicates that CFENet can effectively enhance and fuse buildings’ low-level and high-level features, improving building extraction accuracy.
Augmentation-Based Methodology for Enhancement of Trees Map Detalization on a Large Scale
Authors: Illarionova Svetlana , Shadrin Dmitrii , Ignatiev Vladimir , Shayakhmetov Sergey , Trekin Alexey , Oseledets Ivan
Published: May 2022

Remote sensing tasks play a very important role in the domain of sensing and measuring, and can be very specific. Advances in computer vision techniques allow for the extraction of various information from remote sensing satellite imagery. This information is crucial in making quantitative and qualitative assessments for monitoring of forest clearing in protected areas for power lines, as well as for environmental analysis, in particular for making assessments of carbon footprint, which is a highly relevant task. Solving these problems requires precise segmentation of the forest mask. Although forest mask extraction from satellite data has been considered previously, no open-access applications are able to provide the high-detailed forest mask. Detailed forest masks are usually obtained using unmanned aerial vehicles (UAV) that set particular limitations such as cost and inapplicability for vast territories. In this study, we propose a novel neural network-based approach for high-detailed forest mask creation. We implement an object-based augmentation technique for a minimum amount of labeled high-detailed data. Using this augmented data we fine-tune the models, which are trained on a large forest dataset with less precise labeled masks. The provided algorithm is tested for multiple territories in Russia. The F1-score, for small details (such as individual trees) was improved to 0.929 compared to the baseline score of 0.856. The developed model is available in an SAAS platform. The developed model allows a detailed and precise forest mask to be easily created, which then be used for solving various applied problems.
A Novel Ultra−High Resolution Imaging Algorithm Based on the Accurate High−Order 2−D Spectrum for Space−Borne SAR
Authors: He Tao , Cui Lei , Wang Pengbo , Guo Yanan , Zhuang Lei
Published: May 2022

Ultra−high spatial resolution, which can bring more detail to ground observation, is a constant pursuit of the modern space−borne synthetic aperture radar. However, the exact imaging in this case has always been a complex technical problem due to its complicated imaging geometry and signal structure. To achieve those applications’ strict requirements, a novel ultra−high resolution imaging algorithm based on an accurate high−order 2−D spectrum is presented in this paper. The only first two Doppler parameters needed as range models in the defective spectrum are replaced by a polynomial range model, which can derive coefficients from the relative motion between the radar and the targets. Then, the new spectrum is calculated through the Lagrange inversion formula. Based on this, the novel imaging algorithm is elaborated in detail as follows: The range high−order term of the spectrum is compensated completely, and the range chirp rate space variance is eliminated by the cubic phase term. Two steps of range cell migration correct are applied in this algorithm before and after the range compression; one is the traditional linear chirp scaling method, and another is the interpolation to correct the quadratic range cell migration introduced by the range chirp rate equalization. The simulation results illustrate that the proposed algorithm can handle the exact imaging processing with a 0.25 m resolution around the azimuth and range in 2 km × 6 km, which validates the feasibility of the proposed algorithm.
UAV-Borne Imagery Can Supplement Airborne Lidar in the Precise Description of Dynamically Changing Shrubland Woody Vegetation
Authors: Klouček Tomáš , Klápště Petr , Marešová Jana , Komárek Jan
Published: May 2022

Airborne laser scanning (ALS) is increasingly used for detailed vegetation structure mapping; however, there are many local-scale applications where it is economically ineffective or unfeasible from the temporal perspective. Unmanned aerial vehicles (UAVs) or airborne imagery (AImg) appear to be promising alternatives, but only a few studies have examined this assumption outside economically exploited areas (forests, orchards, etc.). The main aim of this study was to compare the usability of normalized digital surface models (nDSMs) photogrammetrically derived from UAV-borne and airborne imagery to those derived from low- (1–2 pts/m2) and high-density (ca. 20 pts/m2) ALS-scanning for the precise local-scale modelling of woody vegetation structures (the number and height of trees/shrubs) across six dynamically changing shrubland sites. The success of the detection of woody plant tops was initially almost 100% for UAV-based models; however, deeper analysis revealed that this was due to the fact that omission and commission errors were approximately equal and the real accuracy was approx. 70% for UAV-based models compared to 95.8% for the high-density ALS model. The percentage mean absolute errors (%MAE) of shrub/tree heights derived from UAV data ranged between 12.2 and 23.7%, and AImg height accuracy was relatively lower (%MAE: 21.4–47.4). Combining UAV-borne or AImg-based digital surface models (DSM) with ALS-based digital terrain models (DTMs) significantly improved the nDSM height accuracy (%MAE: 9.4–13.5 and 12.2–25.0, respectively) but failed to significantly improve the detection of the number of individual shrubs/trees. The height accuracy and detection success using low- or high-density ALS did not differ. Therefore, we conclude that UAV-borne imagery has the potential to replace custom ALS in specific local-scale applications, especially at dynamically changing sites where repeated ALS is costly, and the combination of such data with (albeit outdated and sparse) ALS-based digital terrain models can further improve the success of the use of such data.
Multi-Color Space Network for Salient Object Detection
Authors: Lee Kyungjun , Jeong Jechang
Published: May 2022

The salient object detection (SOD) technology predicts which object will attract the attention of an observer surveying a particular scene. Most state-of-the-art SOD methods are top-down mechanisms that apply fully convolutional networks (FCNs) of various structures to RGB images, extract features from them, and train a network. However, owing to the variety of factors that affect visual saliency, securing sufficient features from a single color space is difficult. Therefore, in this paper, we propose a multi-color space network (MCSNet) to detect salient objects using various saliency cues. First, the images were converted to HSV and grayscale color spaces to obtain saliency cues other than those provided by RGB color information. Each saliency cue was fed into two parallel VGG backbone networks to extract features. Contextual information was obtained from the extracted features using atrous spatial pyramid pooling (ASPP). The features obtained from both paths were passed through the attention module, and channel and spatial features were highlighted. Finally, the final saliency map was generated using a step-by-step residual refinement module (RRM). Furthermore, the network was trained with a bidirectional loss to supervise saliency detection results. Experiments on five public benchmark datasets showed that our proposed network achieved superior performance in terms of both subjective results and objective metrics.
Consequences of Patellar Tendinopathy on Isokinetic Knee Strength and Jumps in Professional Volleyball Players
Authors: Chantrelle Marie , Menu Pierre , Gernigon Marie , Louguet Bastien , Dauty Marc , Fouasson-Chailloux Alban
Published: May 2022

Patellar tendinopathy (PT) in professional volleyball players can have an impact on their careers. We evaluated the impact of this pathology in this specific population in terms of isokinetic strength and jumping performances. Thirty-six professional male volleyball players (mean age: 24.8 ± 5.2) performed isokinetic knee assessments, single-leg countermovement jumps and one leg hop test. They filled out the Victorian Institute of Sport Assessment-Patella (VISA-P) score. Two groups were assessed: “PT group” (n = 15) and “control group” (n = 21). The VISA-P score was lower in the PT group (p < 0.0001). No difference was found between the isokinetic strength limb symmetry index and the jump performance limb symmetry index. The healthy legs of the control group were compared with the affected (PT+) and the unaffected legs (PT−) of the PT group. Compared with the healthy legs, both PT+ and PT− legs showed decreased values of quadriceps and hamstring strengths. Only PT+ legs scored lower than healthy legs in countermovement jumps and hop tests. No differences were found between PT+ and PT− legs for muscle strengths and jumps. A low correlation existed between quadriceps strength and jumping performances (r > 0.3; p < 0.001). Volleyball players with PT showed a decrease in the isokinetic knee strength. This strength deficit was found both on the symptomatic legs and the asymptomatic ones. Jumps were only significantly altered on the pathological legs. Highlighting that the unaffected limbs were also impaired in addition to the affected limbs may help provide a better adaptation of the rehabilitation management.
Dynamic Learning Framework for Smooth-Aided Machine-Learning-Based Backbone Traffic Forecasts
Authors: Hassan Mohamed Khalafalla , Syed Ariffin Sharifah Hafizah , Ghazali N. Effiyana , Hamad Mutaz , Hamdan Mosab , Hamdi Monia , Hamam Habib , Khan Suleman
Published: May 2022

Recently, there has been an increasing need for new applications and services such as big data, blockchains, vehicle-to-everything (V2X), the Internet of things, 5G, and beyond. Therefore, to maintain quality of service (QoS), accurate network resource planning and forecasting are essential steps for resource allocation. This study proposes a reliable hybrid dynamic bandwidth slice forecasting framework that combines the long short-term memory (LSTM) neural network and local smoothing methods to improve the network forecasting model. Moreover, the proposed framework can dynamically react to all the changes occurring in the data series. Backbone traffic was used to validate the proposed method. As a result, the forecasting accuracy improved significantly with the proposed framework and with minimal data loss from the smoothing process. The results showed that the hybrid moving average LSTM (MLSTM) achieved the most remarkable improvement in the training and testing forecasts, with 28% and 24% for long-term evolution (LTE) time series and with 35% and 32% for the multiprotocol label switching (MPLS) time series, respectively, while robust locally weighted scatter plot smoothing and LSTM (RLWLSTM) achieved the most significant improvement for upstream traffic with 45%; moreover, the dynamic learning framework achieved improvement percentages that can reach up to 100%.
A Two-Step Fusion Method of Wi-Fi FTM for Indoor Positioning
Authors: Xu Shenglei , Wang Yunjia , Si Minghao
Published: May 2022

The Wi-Fi fine time measurement (FTM) protocol specified in the IEEE 802.11-2016 standard provides a new two-way ranging approach to enhance positioning capability. Similar to other wireless signals, the accuracy of the real-time range measurement of FTM is influenced by various errors. In this work, the characteristics of the ranging errors is analyzed and an abstract ranging model is introduced. From the perspective of making full use of the range measurements from FTM, this paper designs two positioning steps and proposes a fusion method to refine the performance of indoor positioning. The first step is named single-point positioning, locating the position with the real-time range measurements based on the geometric principle. The second step is named the improved matching positioning, which constructs a distance database by utilizing the existing scene information and uses the modified matching algorithm to obtain the position. In view of the different positioning accuracies and error distributions from the results of the aforementioned two steps, a fusion method using the indirect adjustment principle is proposed to adjust the positioning results, and the advantages of the matching scene information and the range measurements are served simultaneously. Finally, a number of tests are conducted to assess the performance of the proposed method. The experimental results demonstrate that the precision and stability of indoor positioning are improved by the proposed fusion method.
Perimeter Intrusion Detection by Video Surveillance: A Survey
Authors: Lohani Devashish , Crispim-Junior Carlos , Barthélemy Quentin , Bertrand Sarah , Robinault Lionel , Tougne Rodet Laure
Published: May 2022

In recent times, we have seen a massive rise in vision-based applications, such as video anomaly detection, motion detection, object tracking, people counting, etc. Most of these tasks are well defined, with a clear idea of the goal, along with proper datasets and evaluation procedures. However, perimeter intrusion detection (PID), which is one of the major tasks in visual surveillance, still needs to be formally defined. A perimeter intrusion detection system (PIDS) aims to detect the presence of an unauthorized object in a protected outdoor site during a certain time. Existing works vaguely define a PIDS, and this has a direct impact on the evaluation of methods. In this paper, we mathematically define it. We review the existing methods, datasets and evaluation protocols based on this definition. Furthermore, we provide a suitable evaluation protocol for real-life application. Finally, we evaluate the existing systems on available datasets using different evaluation schemes and metrics.
Advanced Sensors and Systems Technologies for Indoor Positioning
Authors: Carotenuto Riccardo , Iero Demetrio , Merenda Massimo
Published: May 2022

There is an increasing interest about indoor positioning, which is an emerging technology with a wide range of applications [...]
Pedestrian Safety at Midblock Crossings on Dual Carriageway Roads in Polish Cities
Authors: Szagala Piotr , Brzezinski Andrzej , Kiec Mariusz , Budzynski Marcin , Wachnicka Joanna , Pazdan Sylwia
Published: May 2022

Road crossings across two or more lanes in one direction are particularly dangerous due to limited sight distance and high vehicle speeds. To improve their safety, road authorities should provide safety treatments. These may include additional measures to reduce speed and narrow the road cross-section and the introduction of active pedestrian crossings. Equipped with flashing lights activated automatically when a pedestrian is detected, the crossings are painted red and have an anti-skid surface on approaches. The article presents an analysis of road user behaviour at pedestrian crossings on dual carriageways with a varying provision of road safety measures in some Polish cities. It also evaluates the effectiveness of the measures over time. The study was conducted before, immediately after and one year after the additional signage was introduced. The evaluation is based on how vehicle speeds changed before the pedestrian crossing, how pedestrians behaved versus the vehicle and their readiness to cross the street. The number of conflicts on selected crossings was also evaluated. The safety treatments under analysis were found to be less effective than the traditional pedestrian safety measures such as speed cushions or roads narrowed to one lane. This suggests that if used on dual carriageways the measures should only be temporary and should ultimately be replaced with traffic lights or a grade separated solution (a footbridge or tunnel) on exits from urban areas. No clear-cut conclusions about pedestrian safety can be drawn based on the traffic conflicts in question. The article is divided into the following sections: introduction with a review of the literature on pedestrian and driver behaviour studies at pedestrian crossings, including midblock crossings and dual carriageways; a description of the research method and test sites, the results, discussion of the results and conclusion.
Numerical Comparison of the Hydrological Response of Different Permeable Pavements in Urban Area
Authors: Ciriminna Diego , Ferreri Giovanni Battista , Noto Leonardo Valerio , Celauro Clara
Published: May 2022

Floods are becoming more frequent, especially in urban environments where most of the surface is waterproofed. Permeable pavement (PP) can be applied as low impact development (LID) systems for runoff mitigation in urban areas. Their effectiveness can be assessed, case by case, by numerical simulations. In this study, the effectiveness of mitigating runoff of different permeable pavements has been evaluated. In particular, porous asphalt (PA), pervious concrete (PC), permeable interlocking concrete pavement (PICP) and grid pavement (GP) have been investigated using EPA Storm Water Management Model (SWMM) software. To this aim, a car parking area located in the University Campus of Palermo (Italy) has been taken as a case study, considering several scenarios, each having a different percentage and planimetric layout of a PP type combined with an impermeable pavement. All the scenarios were tested assuming four synthetic rainfall events, referring to return periods of 5, 10, 50 and 100 years, and a real high return period event that occurred in Palermo in 2020. The results showed that amongst the different PPs considered, only the PA, bounded at the bottom by an impermeable layer, was practically ineffective. The other three PPs, proved to be effective in a noticeable way and furthermore for each scenario studied, they proved to bear almost the same mitigated runoff. The results proved appreciable differences in runoff as a function of the location of the PP over the study area.
The Sustainability Evaluation of Masks Based on the Integrated Rank Sum Ratio and Entropy Weight Method
Authors: Lu Honglei , Zhu Chunxiao , Cao Xin , Hsu Yen
Published: May 2022

Due to the seriousness of COVID-19, masks are considered to be as a key and effective device to cut off the spread of viruses and are widely used by people, such as doctors and patients. Hundreds of millions of masks used worldwide in daily life will inevitably cause huge pollution and damage to the environment. However, existing research has not yet provided a method to simultaneously evaluate the economic, environmental, and social aspects of sustainable design of masks, which brings great barriers and challenges for designers to make sustainability decisions on masks and consumers’ behavioral decisions on mask purchases. Consequently, on the basis of principles of sustainability evaluation of masks, this work evaluates ten masks of different materials (including two newly designed masks) by using a novel hybrid of rank-sum ratio and entropy weight method. The results indicate that some disposable masks also show better sustainability than reusable masks, and in addition, the integrated rank-sum ratio and entropy weight method can effectively realize the sustainability evaluation of masks. The main contribution is to furnish an effective decision-making reference for sustainability evaluation of masks while greatly reducing the negative impacts of masks on the environment during the epidemic.
Unmanned Aerial Vehicles (UAV) Integration with Digital Technologies toward Construction 4.0: A Systematic Literature Review
Authors: Rachmawati Titi Sari Nurul , Kim Sunkuk
Published: May 2022

Unmanned Aerial Vehicles (UAVs) have been employed in the construction industry in the last decade for various purposes such as progress monitoring and building inspection. Recently, there has been a rising trend of employing UAVs with other digital technologies (DTs), such as Building Information Modeling and Extended Reality. The integration of these technologies encourages automation and digitization toward better project performance. However, little is known about the implementation of UAVs in conjunction with other DTs. Therefore, this study performs a systematic literature review to determine application areas and technology trends regarding UAVs’ integration with other DTs. The search yielded 287 articles, of which 36 satisfied the established inclusion criteria and formed the foundation of this systematic review. Seven application areas of UAV integration with other DTs were identified: progress monitoring, historic building conservation, information management, construction safety, construction education, structural and infrastructure inspection, and transportation. This study also revealed UAV technology trends encouraging automation and digitization: automated progress monitoring, automated UAV inspection planning, real-time video streaming, and parametric model development of historicbuildings. This study is expected to be a starting point of future in-depth research by providing a general understanding of the current applications of UAVs integration with other DTs.
Investigation of Combined Heating and Cooling Systems with Short- and Long-Term Storages
Authors: Shakerin Mohammad , Eikeskog Vilde , Li Yantong , Harsem Trond Thorgeir , Nord Natasa , Li Haoran
Published: May 2022

Modern buildings in cold climates, like Norway, may have simultaneous heating and cooling demands. For these buildings, integrated heating and cooling systems with heat pumps, as well as short-term and long-term thermal storage, are promising solutions. Furthermore, combining this integrated system with renewables aids in the transition to future sustainable building energy systems. However, cost-effectively designing and operating such a complicated system is challenging and rarely addressed. Therefore, this research proposed an integrated heating and cooling system that incorporated a short-term water tank and a long-term borehole thermal storage. Meanwhile, three operating modes: heating, cooling, and free cooling were defined based on different heating and cooling load conditions. A detailed system model was developed in MATLAB using heat pump manufacture data as well as simulated and measured building loads. Following that, sensitivity studies were performed to investigate the impacts of ground properties, thermal storage size, setpoint temperature, heat pump characteristics, and load conditions. The findings identified the crucial factors that influence the system’s overall energy efficiency and the functioning of the key system components. Particularly, it revealed that low cooling to heating ratios caused an imbalance in charging and discharging, further reducing the ground temperature and degrading the heat pump’s performance.
Entrepreneurs’ Life Satisfaction Built on Satisfaction with Job and Work–Family Balance: Embedded in Society in China, Finland, and Sweden
Authors: Gao Junguang , Chen Tao , Schøtt Thomas , Gu Fuzhen
Published: May 2022

Entrepreneurs are known to be more satisfied than employees, with their life satisfaction being built on their satisfaction with their job and work–family balance. We argue that effects differ among societies, drawing on theories about self-determination and culture. Representative samples of 1276 entrepreneurs and 3821 employees in traditional China and modern Finland and Sweden were surveyed by the Global Entrepreneurship Monitor (GEM), which is amenable to multivariate analyses. The effects of occupation upon satisfaction were found to differ among the societies, consistent with their cultural differences. These findings contribute to contextualizing theories about satisfaction being embedded in society and culture.
Quantitative Ground Risk Assessment for Urban Logistical Unmanned Aerial Vehicle (UAV) Based on Bayesian Network
Authors: Han Peng , Yang Xinyue , Zhao Yifei , Guan Xiangmin , Wang Shengjie
Published: May 2022

The Unmanned Aerial Vehicle (UAV) has been used for the delivery of medical supplies in urban logistical distribution, due to its ability to reduce human contact during the global fight against COVID-19. However, due to the reliability of the UAV system and the complex and changeable operation scene and population distribution in the urban environment, a few ground-impact accidents have occurred and generated enormous risks to ground personnel. In order to reduce the risk of UAV ground-impact accidents in the urban logistical scene, failure causal factors, and failure modes were classified and summarized in the process of UAV operation based on the accumulated operation data of more than 20,000 flight hours. The risk assessment model based on the Bayesian network was built. According to the established network and the probability of failure causal factors, the probabilities of ground impact accidents and intermediate events under different working conditions were calculated, respectively. The posterior probability was carried out based on the network topology to deduce the main failure inducement of the accidents. Mitigation measures were established to achieve the equivalent safety level of manned aviation, aiming at the main causes of accidents. The results show that the safety risk of the UAV was reduced to 3.84 × 10−8 under the action of risk-mitigation measures.
Socio-Economic Life Cycle-Based Framework for Safe and Sustainable Design of Engineered Nanomaterials and Nano-Enabled Products
Authors: Stoycheva Stella , Zabeo Alex , Pizzol Lisa , Hristozov Danail
Published: May 2022

This manuscript describes an innovative approach to socio-economic assessment of (advanced) engineered nanomaterials and nano-enabled products (NEPs) to support safe-and-sustainable-by-design (SSbD) decision making by industries in the early stages of product development. This semi-quantitative methodology is based on a sound conceptual framework grounded in the combination of social life cycle analysis and multi-criteria decision analysis methods and supports decision making based upon socio-economic impacts assessed over the full life cycle of a product. To facilitate its application by industries, the methodology was implemented as an Excel-based self-assessment tool. This easy-to-use, cost- and time-efficient tool can guide users through their SSbD decision making regarding newly developed nanomaterials and NEPs and can also be applied to re-evaluate existing materials and NEPs in order to improve their sustainability from a socio-economic perspective. The relatively low requirements of this tool regarding the level of efforts and expert knowledge needed for its application make it a good starting point for initial assessment to highlight socio-economic issues in the value chain. The results of this initial screening can be further used for more detailed analysis in the later stages of product development by performing a full social life cycle assessment (S-LCA).
Establishing a Deep End GP group: a scoping review
Authors: Butler Daniel , O'Donovan Diarmuid , Johnston Jennifer , Hart Nigel D
Published: May 2022

Background

GPs working in deprived areas, where all-cause mortality rates are higher compared to less deprived areas, face unique challenges. Despite 50 years passing since Tudor Hart’s seminal ‘inverse care law’ paper, the health inequities gap remains wide. Deep End GP groups are frontline GP-led initiatives working to close this gap and improve the health and lives of those most in need.

Aim

To use scoping methodology to map out the process of creating a Deep End GP group.

Design & setting

A scoping review using Arksey and O’Malley’s framework.

Method

MEDLINE, Embase, Web of Science, and CINAHL databases, as well as non-peer reviewed publications, were searched and articles extracted, reviewed, and analysed according to iterative inclusion criteria.

Results

From an initial search number of 35 articles, 16 articles were included in the final analysis. Key steps in starting a Deep End GP group were: quantifying patients and practices in areas of deprivation; establishing GP-led objectives at an initial meeting; regular steering group meetings with close collaboration between academic and frontline general practice, as well as the wider multidisciplinary team; and adopting a local Deep End logo.

Conclusion

Deep End GP groups have made advances to reduce health impacts of systemic health inequities. Starting a Deep End GP group involves a multidisciplinary approach, beginning with the identification of patients and practices in areas of highest need. The findings and key themes identified in this scoping review will guide interested parties to start the journey to do the same in their locality and to join the Deep End movement.
Development of an In-house Indirect ELISA Test as a Diagnostic Tool for Bovine Leptospirosis
Authors: Bakhshandeh Nina , Tebianian Majid , Khaki Pejvak , Esmaelizad Majid , Saadatmand Sara
Published: May 2022

Background: Leptospirosis is one of the most common zoonotic diseases, which is caused by a Spiral shaped bacterium called Leptospira. The recommended diagnosis method is to perform microscopic agglutination test (MAT) which is both hazardous, due to using live bacteria, and time-consuming. As a result, many attempts have been recently made to develop other serological methods, such as ELISA. Objective: This study aimed to develop an indirect ELISA method using leptospiral whole antigens for diagnosing pathogenic Leptospira. Materials and Methods: In this study, four pathogenic serovars of Leptospira were used and cultured in selective culture medium. The cultured bacteria were sonicated and the extracted antigens were used as captured antigen in ELISA method. A total of 74 samples from bovine suspected to leptospirosis and 43 samples from healthy animals were examined by MAT method. Results: According to the study results, 42 samples (56.7%) out of 74 suspected ones were found positive while 32 ones (43.2%) were determined negative by MAT analysis. All of the 43 negative control samples were found negative after performing MAT. The sensitivity and specificity of ELISA, compared to those of MAT, were measured as 87.5% and 84.2%, respectively. Conclusion: Taking into account the high sensitivity and appropriate specificity of the developed indirect ELISA method, it was recommended that ELISA be employed as an accurate method for early and rapid diagnosis of bovine leptospirosis.
Symbols
Authors: Zender Mike
Published: May 2022

Numerous studies support the thesis that icons frequently fail to communicate because designers have not appreciated that icons combine multiple symbols which interact to evoke meaning. Because symbols interact, a designer must know which symbols to combine and how to draw each symbol so that icons communicate clearly. This article brings together numerous research studies that explored new methods for designing icons based on the interaction of symbols.
Análisis de sentimientos en torno a Marco Denevi y sus textos:
Authors: Rodrigo Andrea Fernanda
Published: May 2022

El desarrollo de la argumentación constituye sin dudas una de las mayores dificultades en la enseñanza-aprendizaje de la lengua. A menudo en la clase se utilizan guías para la comprensión de textos, lo que por un lado facilita el trabajo de los estudiantes, pero por el otro, no contribuye a estimular la reflexión crítica propia de la argumentación. Aquí nos abocamos a analizar un corpus conformado por un conjunto de producciones tomado de las redes Facebook y Twitter, entendiendo que reflejan lo que lo usuarios sienten y piensan en torno a una infinidad de tópicos diversos. La extrema simplicidad con que se expresan dichas opiniones y sentimientos resulta útil a los fines didácticos, ya que pueden ser fácilmente comprendidas por los estudiantes. Pretendemos hacer un análisis de sentimientos en torno a los textos de Marco Denevi, una figura central de la literatura argentina. Estos se reflejan en un variado y nutrido uso de adjetivos que en muchos casos sintetizan una expresión argumentativa. Tomamos al adjetivo como un primer paso para la reflexión argumentativa, no a los fines del marketing sino desde una perspectiva diferente, pensados directamente desde lo que pueden aportar en la enseñanza-aprendizaje de la lengua. Para analizar dichas opiniones y sentimientos en torno a Marco Denevi utilizamos la plataforma NooJ creada por Max Silberztein. (2015) (2016). En este caso, nos valemos de nuestros diccionarios y gramáticas flexivas de modo que sea factible diseñar una gramática sintáctica. Esta gramática nos permite la extracción y generación de expresiones en español.
Recuerdos de un pasado presente: reflexiones estéticas, etnográficas y narrativas entorno a la película "Mi Socio"
Authors: Calvimontes Díaz Vanessa
Published: May 2022

En 1982, la película Mi Socio maravilló a los espectadores con su lenguaje simple, sus imágenes imponentes y su narrativa bien desarrollada. Casi 40 años después, el director de aquella travesía reúne nuevamente al elenco y lanza una nueva propuesta: Mi socio 2.0. Este artículo pretende analizar cómo narra la Bolivia de hoy un director Italiano que llegó hace 40 años al país. Nos basamos en una metodología de análisis cinematográfico que profundiza en rasgos estéticos, etnográficos y narrativos.
Comunicación interna y redes sociales en tiempos del SARS-CoV-2
Authors: Otazú Salazar María Delina , Palacios Dávalos Dino David
Published: May 2022

La pandemia de covid-19 cambió a las organizaciones y la forma en la que sus trabajadores se relacionan entre sí. El distanciamiento físico, el confinamiento, el temor y la incertidumbre permiten pensar a la comunicación interna como un área dentro las organizaciones con importantes desafíos para el futuro, pero por ahora su uso está limitado la improvisación. Las redes sociales generalistas y las corporativas son instrumentos que fueron desarrollados hace décadas, pero que fueron “re-encontrados” durante los primeros meses de la pandemia para intentar conectar a las personas, informar e idealmente mantener el compromiso, el sentido de pertenencia y la motivación.
El examen PISA en La Folha de São Paulo
Authors:   , Pedra Marcelo Camilo
Published: May 2022

Esta tesis tiene como objetivo investigar las publicaciones del periódico de mayor circulación en Brasil, Folha de São Paulo, sobre los resultados del Programa Internacional de Evaluación de Estudiantes (PISA, por sus siglas en inglés) desde su primera aplicación en 2000 hasta 2016. Este estudio se desarrolló para analizar y comparar material documental cualitativo de los artículos periodísticos destinados a difundir el desempeño de Brasil y de otros países en la prueba aplicada por la OCDE (Organización para la Cooperación y el Desarrollo Económico). El estudio utilizó herramientas de análisis del discurso (ADC) para descubrir las posturas del periódico sobre el tema de la educación y el papel de las evaluaciones educativas. De esa forma, la investigación pudo revelar con más fuerza cómo la revista ve los problemas educativos en Brasil y sus posibles formas de remediarlos. Debido a un análisis superficial de los resultados de PISA y las debilidades de la educación en Brasil, Folha contribuye poco a un debate más constructivo en la búsqueda por propuestas efectivas de soluciones que contribuyan al desarrollo de la educación nacional. Además, al reproducir solo el discurso de esos grupos que representa económicamente, no aprovecha la oportunidad de dar voz a quienes deberían participar directamente en las decisiones educativas en Brasil.
The Mantic Evolution and Cognitive Analysis of Sentence Pattern “VP buguo”
Authors:   The Society For Chinese Humanities In Korea, . . , . . , . .
Published: May 2022

The sentence pattern “VP buguo” are widely used no matter in pre-modern Chinese (from Tang and Five Dynasties to Qing Dynasty) or modern Chinese (from the late Qing dynasty to this day).Many scholars have made a grammatical analysis of “buguo” complement structure, and divided it into potential complement, resultative complement, degree complement, and state complement. Most of the diachronic studies focus on the grammaticalization process of the degree complement sentences, and there is no research on the diachronic evolution of the “buguo complement structure ” as a whole. By searching and analyzing the relevant sentence patterns of the BCC corpus and the “Compilation of Pre-modern Chinese Grammar Materials” in the Tang, Song, Yuan, Ming and Qing dynasties, this paper classifies “VP buguo” into different types from the perspective of semantics, including purpose realization, comparison and confrontation, persistence and tolerance, and FangRao (let off). It is concluded that the sentence pattern of “VP buguo” originated in the Tang Dynasty. The purpose realization class appeared first, followed by the comparison and confrontation class and the persistence and tolerance class, the FangRao (let off) class and degree class appeared last. Then the paper analyzes the causes and paths of various “VP buguo” by metaphor theory.
Klasifikasi Penyakit Daun Jagung Menggunakan Metode Convolutional Neural Network
Authors: Putra Ivan Pratama , Rusbandi Rusbandi , Alamsyah Derry
Published: May 2022

Jagung merupakan tanaman pangan utama ketiga setelah padi dan terigu di dunia dan  menempati posisi kedua setelah padi di Indonesia. Penyakit tanaman sering kali disebabkan  oleh aktifitas atau serangan organism di dalam bagian tubuh tanaman, di luar tubuh, atau di  sekitarnya. Penelitian ini bertujuan untuk mengklasifikasikan penyakit daun jagung  menggunakan metode convolutional neural network (CNN) dengan arsitektur Resnet 50 dengan  optimizer Adam, Nadam dan SGD. Dataset terdapat 4225 citra di pisahkan menjadi 3380 data  train, 845 data test. Citra yang digunakan di resize menjadi ukuran 224x224. Pada penelitian  ini mendapatkan hasil tingkat akurasi tertinggi untuk arsitektur Resnet 50 dengan  menggunakan optimizer Adam didapatkan tingkat akurasi sebesar 98,4%.