bluuebunny/crossref_metadata_2025 huggingface dataset:
DT-RRNS: Routing Protocol Design for Secure and Reliable Distributed Smart Sensors Communication Systems
Authors: Gladkov Andrei , Shiriaev Egor , Tchernykh Andrei , Deryabin Maxim , Babenko Mikhail , Nesmachnow Sergio
Published: April 2023

A smart city has a complex hierarchical communication system with various components. It must meet the requirements of fast connection, reliability, and security without data compromise. Internet of Things technology is widely used to provide connectivity and control solutions for smart sensors and other devices using heterogeneous networking technologies. In this paper, we propose a routing solution for Wireless Sensor Networks (WSN) and Mobile Ad hoc NETworks (MANET) with increasing speed, reliability, and sufficient security. Many routing protocols have been proposed for WSNs and MANETs. We combine the Secret Sharing Schemes (SSS) and Redundant Residual Number Systems (RRNS) to provide an efficient mechanism for a Distributed dynamic heterogeneous network Transmission (DT) with new security and reliability routing protocol (DT-RRNS). We analyze the concept of data transmission based on RRNS that divides data into smaller encoded shares and transmits them in parallel, protecting them from attacks on routes by adaptive multipath secured transmission and providing self-correcting properties that improve the reliability and fault tolerance of the entire system.
Restoration of Spatially Variant Blurred Images with Wide-Field Telescope Based on Deep Learning
Authors: Tian Yingmei , Wang Jianli , Liu Junchi , Guo Xiangji
Published: April 2023

The wide-field telescope is a research hotspot in the field of aerospace. Increasing the field of view of the telescope can expand the observation range and enhance the observation ability. However, a wide field will cause some spatially variant optical aberrations, which makes it difficult to obtain stellar information accurately from astronomical images. Therefore, we propose a network for restoring wide-field astronomical images by correcting optical aberrations, called ASANet. Based on the encoder–decoder structure, ASANet improves the original feature extraction module, adds skip connection, and adds a self-attention module. With these methods, we enhanced the capability to focus on the image globally and retain the shallow features in the original image to the maximum extent. At the same time, we created a new dataset of astronomical aberration images as the input of ASANet. Finally, we carried out some experiments to prove that the structure of ASANet is meaningful from two aspects of the image restoration effect and quality evaluation index. According to the experimental results, compared with other deblur networks, the PSNR and SSIM of ASANet are improved by about 0.5 and 0.02 db, respectively.
On the Advantages of Microwave Photonic Interrogation of Fiber-Based Sensors: A Noise Analysis
Authors: Nordmeyer Ulrich , Thiel Torsten , Kojucharow Konstantin , Neumann Niels
Published: April 2023

Although microwave photonic approaches have been used for fiber sensing applications before, most contributions in the past dealt with evaluating the sensor signal’s amplitude. Carrying this topic on, the authors previously presented a scheme for the interrogation of fiber sensors that was based on a fiber Bragg grating’s phase response for the electrical signal. However, neither has the measurement setup been analyzed nor have the amplitude and phase-based approaches been compared in detail before. Hence, this paper picks up the previously proposed setup, which relies on an amplitude modulation of the optical signal and investigates for sources of signal degradation, an aspect that has not been considered before. Following the incorporation of the microwave signal, the setup is suitable not only for an amplitude-based evaluation of fiber Bragg gratings but also for a phase-based evaluation. In this context, the signal-to-noise ratios are studied for the conventional amplitude-based evaluation approach and for the recently developed phase-based approach. The findings indicate a strong advantage for the signal-to-noise ratio of the phase response evaluation; an 11 dB improvement at the least has been found for the examined setup. Further studies may investigate the consequences and additional benefits of this approach for radio-over-fiber sensing systems or general performance aspects such as achievable sensitivity and sampling rates.
Microstrip Copper Nanowires Antenna Array for Connected Microwave Liquid Sensors
Authors: Cardillo Emanuele , Tavella Francesco , Ampelli Claudio
Published: April 2023

In this contribution, a 25 GHz planar antenna, designed and realized in microstrip technology, is exploited as a lightweight and compact liquid sensor. The high working frequency allows minimization of the sensor dimension. Moreover, particular attention was paid to keeping the design cost low. Indeed, the frequency of 25 GHz is widely exploited for many applications, e.g., up to the last decade concerning radars and, recently, 5G technology. Available commercial antennas allowed minimization of the effort that is usually required to design the microstrip sensor. The antenna was in-house realized, and the microstrip Cu conductor was modified through controlled anodic oxidation in order to enhance the sensing features. The sensor capability of detecting the presence and concentration of ethanol in water was experimentally demonstrated. In detail, a sensitivity of 0.21 kHz/(mg/L) and an average quality factor of 117 were achieved in a very compact size, i.e., 18 mm × 19 mm, and in a cost-effective way. As a matter of fact, the availability of devices able to collect data and then to send the related information wirelessly to a remote receiver represents a key feature for the next generation of connected smart sensors.
Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review
Authors: Adli Hasyiya Karimah , Remli Muhammad Akmal , Wan Salihin Wong Khairul Nizar Syazwan , Ismail Nor Alina , González-Briones Alfonso , Corchado Juan Manuel , Mohamad Mohd Saberi
Published: April 2023

As the most popular technologies of the 21st century, artificial intelligence (AI) and the internet of things (IoT) are the most effective paradigms that have played a vital role in transforming the agricultural industry during the pandemic. The convergence of AI and IoT has sparked a recent wave of interest in artificial intelligence of things (AIoT). An IoT system provides data flow to AI techniques for data integration and interpretation as well as for the performance of automatic image analysis and data prediction. The adoption of AIoT technology significantly transforms the traditional agriculture scenario by addressing numerous challenges, including pest management and post-harvest management issues. Although AIoT is an essential driving force for smart agriculture, there are still some barriers that must be overcome. In this paper, a systematic literature review of AIoT is presented to highlight the current progress, its applications, and its advantages. The AIoT concept, from smart devices in IoT systems to the adoption of AI techniques, is discussed. The increasing trend in article publication regarding to AIoT topics is presented based on a database search process. Lastly, the challenges to the adoption of AIoT technology in modern agriculture are also discussed.
Cloud Based Fault Diagnosis by Convolutional Neural Network as Time–Frequency RGB Image Recognition of Industrial Machine Vibration with Internet of Things Connectivity
Authors: Łuczak Dominik , Brock Stefan , Siembab Krzysztof
Published: April 2023

The human-centric and resilient European industry called Industry 5.0 requires a long lifetime of machines to reduce electronic waste. The appropriate way to handle this problem is to apply a diagnostic system capable of remotely detecting, isolating, and identifying faults. The authors present usage of HTTP/1.1 protocol for batch processing as a fault diagnosis server. Data are sent by microcontroller HTTP client in JSON format to the diagnosis server. Moreover, the MQTT protocol was used for stream (micro batch) processing from microcontroller client to two fault diagnosis clients. The first fault diagnosis MQTT client uses only frequency data for evaluation. The authors’ enhancement to standard fast Fourier transform (FFT) was their usage of sliding discrete Fourier transform (rSDFT, mSDFT, gSDFT, and oSDFT) which allows recursively updating the spectrum based on a new sample in the time domain and previous results in the frequency domain. This approach allows to reduce the computational cost. The second approach of the MQTT client for fault diagnosis uses short-time Fourier transform (STFT) to transform IMU 6 DOF sensor data into six spectrograms that are combined into an RGB image. All three-axis accelerometer and three-axis gyroscope data are used to obtain a time-frequency RGB image. The diagnosis of the machine is performed by a trained convolutional neural network suitable for RGB image recognition. Prediction result is returned as a JSON object with predicted state and probability of each state. For HTTP, the fault diagnosis result is sent in response, and for MQTT, it is send to prediction topic. Both protocols and both proposed approaches are suitable for fault diagnosis based on the mechanical vibration of the rotary machine and were tested in demonstration.
Development of a Target-to-Sensor Mode Multispectral Imaging Device for High-Throughput and High-Precision Touch-Based Leaf-Scale Soybean Phenotyping
Authors: Li Xuan , Chen Ziling , Wei Xing , Zhao Tianzhang , Jin Jian
Published: April 2023

Image-based spectroscopy phenotyping is a rapidly growing field that investigates how genotype, environment and management interact using remote or proximal sensing systems to capture images of a plant under multiple wavelengths of light. While remote sensing techniques have proven effective in crop phenotyping, they can be subject to various noise sources, such as varying lighting conditions and plant physiological status, including leaf orientation. Moreover, current proximal leaf-scale imaging devices require the sensors to accommodate the state of the samples during imaging which induced extra time and labor cost. Therefore, this study developed a proximal multispectral imaging device that can actively attract the leaf to the sensing area (target-to-sensor mode) for high-precision and high-throughput leaf-scale phenotyping. To increase the throughput and to optimize imaging results, this device innovatively uses active airflow to reposition and flatten the soybean leaf. This novel mechanism redefines the traditional sensor-to-target mode and has relieved the device operator from the labor of capturing and holding the leaf, resulting in a five-fold increase in imaging speed compared to conventional proximal whole leaf imaging device. Besides, this device uses artificial lights to create stable and consistent lighting conditions to further improve the quality of the images. Furthermore, the touch-based imaging device takes full advantage of proximal sensing by providing ultra-high spatial resolution and quality of each pixel by blocking the noises induced by ambient lighting variances. The images captured by this device have been tested in the field and proven effective. Specifically, it has successfully identified nitrogen deficiency treatment at an earlier stage than a typical remote sensing system. The p-value of the data collected by the device (p = 0.008) is significantly lower than that of a remote sensing system (p = 0.239).
Essential Oil Variability of Azorean Cryptomeria japonica Leaves under Different Distillation Methods, Part 2: Molluscicidal Activity and Brine Shrimp Lethality
Authors: Arruda Filipe , Lima Ana , Oliveira Luísa , Rodrigues Tânia , Janeiro Alexandre , Rosa José S. , Lima Elisabete
Published: April 2023

This study reports on the in vivo molluscicidal activity and Artemia salina lethality of Azorean Cryptomeria japonica leaf (CJL) essential oils (EOs) obtained by hydrodistillation (HD) and water-steam distillation (WSD) techniques, especially in light of the recent focus on the use of forestry and wood industry residues in a sustainable world economy. Molluscicidal activity was performed during several life stages of Radix peregra by the immersion method, under laboratory conditions. A first screening through a single-dose bioassay revealed that both EOs were highly active towards eggs, juveniles and adult snails (ca. 100% mortality). Concentration- and time-toxicity assays were carried out only on adult snails to determine the lethal parameters (LC50;90 and LT50;90). The LC50 values were 33 and 62 µg/mL for EO–WSD and EO–HD, respectively, after 48 h. The LT50 of EO–WSD required only 21 h for both 16 h and continous exposure periods, while that of EO–HD was slighty superior (21.8–25.6 h). Although not significant, EO–WSD was also slightly more toxic against A. salina than EO–HD (LC50 = 98 and 115 µg/mL after 24 h, respectively). In conclusion, Azorean CJL EOs, which are rich in α-pinene (mostly EO–WSD), have huge potential to be used as safe raw materials for the development of natural molluscicide products to control snails responsible for transmitting fascioliasis.
Quantitation of Ecdysterone and Targeted Analysis of WADA-Prohibited Anabolic Androgen Steroids, Hormones, and Metabolic Modulators in Ecdysterone-Containing Dietary Supplements
Authors: Pálinkás Zoltán , Békési Dániel , Utczás Margita
Published: April 2023

The aim of our research was to perform a comprehensive study of ecdysterone (ECD)-containing dietary supplements (DSs). Two analytical methods were optimised according to the expected concentration of the target compounds: quantitation of ECD by liquid chromatography (LC) coupled to diode array detector (DAD), and limit test for 47 World Anti-Doping Agency prohibited by LC coupled with tandem mass spectrometer (MS/MS). For quantitation of ECD, the method was fully validated with outstanding performance characteristics (LOD: 35 µg·g−1, LOQ: 115 µg·g−1, CV% < 5%), resulting in significantly lower LOD and shorter runtime than published previously. For limit tests, a chromatographic method was developed to obtain excellent separation, while MS/MS parameters were optimised to allow the lowest possible reporting limit (RL: 0.6–10 ng·g−1 or mL−1). Twenty-one ecdysterone-containing DSs from ten brands were analysed. In all cases, the measured ECD content was much lower than labelled, and 20% of the samples contained a prohibited substance. The concentration of ecdysterone and contaminations varied randomly from batch to batch. The developed methods help to prevent the use of contaminated or useless DSs.
A Framework to Develop Interventions to Address Labor Exploitation and Trafficking: Integration of Behavioral and Decision Science within a Case Study of Day Laborers
Authors: Kammer-Kerwick Matt , Yundt-Pacheco Mayra , Vashisht Nayan , Takasaki Kara , Busch-Armendariz Noel
Published: April 2023

This paper describes a process that integrates behavioral and decision science methods to design and evaluate interventions to disrupt illicit behaviors. We developed this process by extending a framework used to study systems with uncertain outcomes, where only partial information is observable, and wherein there are multiple participating parties with competing goals. The extended framework that we propose builds from artefactual data collection, thematic analysis, and descriptive analysis, toward predictive modeling and agent-based modeling. We use agent-based modeling to characterize and predict interactions between system participants for the purpose of improving our understanding of interventional targets in a virtual environment before piloting them in the field. We apply our extended framework to an exploratory case study that examines the potential of worker centers as a venue for deploying interventions to address labor exploitation and human trafficking. This case study focuses on reducing wage theft, the most prevalent form of exploitation experienced by day laborers and applies the first three steps of the extended framework. Specifically, the case study makes a preliminary assessment of two types of social interventions designed to disrupt exploitative processes and improve the experiences of day laborers, namely: (1) advocates training day laborers about their workers’ rights and options that they have for addressing wage theft and (2) media campaigns designed to disseminate similar educational messages about workers’ rights and options to address wage theft through broadcast channels. Applying the extended framework to this case study of day laborers at a worker center demonstrates how digital technology could be used to monitor, evaluate, and support collaborations between worker center staff and day laborers. Ideally, these collaborations could be improved to mitigate the risks and costs of wage theft, build trust between worker center stakeholders, and address communication challenges between day laborers and employers, in the context of temporary work. Based on the application of the extended framework to this case study of worker center day laborers, we discuss how next steps in the research framework should prioritize understanding how and why employers make decisions to participate in wage theft and the potential for restorative justice and equity matching as a relationship model for employers and laborers in a well-being economy.
Multi-Component Resilience Assessment Framework for a Supply Chain System
Authors: Zhao Jie , Lee Ji Yun , Camenzind Dane , Wolcott Michael , Lewis Kristin , Gillham Olivia
Published: April 2023

The goal of this paper is to develop a quantitative resilience assessment framework for a supply chain system exposed to multiple risk factors. Most existing studies on supply chain resilience have primarily focused on assessing the system’s ability to withstand and recover from disruptions caused by a single type of hazard. However, a supply chain system is exposed to multiple exogenous and endogenous events and conditions over a planning horizon, and a comprehensive assessment of resilience should take into account multiple risk factors. Moreover, contrary to the conventional resilience assessment methods focusing on the short duration during which the system is impacted by a disaster event, the proposed framework measures the resilience capacities of the system over a long-term horizon through multi-risk assessment and multi-component resilience assessment. Specifically, a new multi-component resilience index is proposed to measure (a) hazard-induced cumulative loss of functionality, (b) opportunity-induced cumulative gain of functionality, and (c) non-hazard-induced cumulative loss of functionality. The case study results indicate that all three types of risk factors contribute to the overall resilience index significantly and ignoring any one of them may result in inaccurate supply chain performance and resilience assessment.
Early Childhood Learning Losses during COVID-19: Systematic Review
Authors: Uğraş Mustafa , Zengin Erdal , Papadakis Stamatis , Kalogiannakis Michail
Published: April 2023

The global education system has been significantly disrupted by COVID-19, and researchers are concerned with the impact this has had on students who have experienced learning loss. This study aims to systematically review the articles published in Science Direct, Wiley Online Library, SpringerLink, Sage Journals, Taylor & Francis Online, ERIC, JSTOR and Google Scholar on learning loss experienced by students in early childhood during the COVID-19 pandemic between 2020 and 2023. We conducted a systematic literature review of 33 articles published in the Web of Science (WOS), ERIC and Google Scholar electronic databases between 2020 and 2023. The review found a significant increase in early childhood learning losses. In addition, the present study found an increase in inequality, while certain demographic groups experienced more learning loss than others.
Marketing Sustainable Fashion: Trends and Future Directions
Authors: Ray Subhasis , Nayak Lipsa
Published: April 2023

The fashion industry is one of the largest contributors to greenhouse gas emissions and climate change. Sustainable fashion (SF) aims to address this issue by designing, creating, and marketing socially and environmentally responsible products. This paper provides a broad overview of the extant literature on SF marketing to understand the trends and future directions. The paper starts with a discussion on sustainable consumption and marketing in the particular context of fashion and ends with potential research gaps, which have scope for further work. For the analysis, 97 research papers were selected based on a structured, systematic search with a particular set of keywords. The review finds that marketing SF from a customer’s perspective has been emphasized in the existing literature. Widely studied topics include consumer behavior, purchase behavior, and the attitude–behavior gap. Further research is required to explore how SF can gain from B2B marketing, circular economy, sustainability-oriented innovations, and subsistence markets, particularly in emerging economies. This paper contributes to theory and practice by providing state-of-the-art sustainable fashion marketing research, identifying research gaps, and providing future research directions.
Research on Power System Day-Ahead Generation Scheduling Method Considering Combined Operation of Wind Power and Pumped Storage Power Station
Authors: Zhang Zhi , Xu Dan , Chan Xuezhen , Xu Guobin
Published: April 2023

In the proposed wind-storage combined operation technology, the storage side is foreseen to play a significant role in power system day-ahead generation scheduling. Based on the operational characteristics of pumped storage power stations, the day-ahead dispatching method of a power system with wind farms and pumped storage power stations is studied. The dispatching mode that aims at the lowest operating cost is proposed, taking into consideration the coordination relationship between the scheduling benefit of pumped storage power stations and the total peak-shaving economy of the system and the fluctuation of new energy output. First, taking the constraint of reservoir capacity, the output power, and the daily pumping power of the pumped storage power station into account, a day-ahead generation scheduling model is constructed, with the objective of minimizing costs. Then, the imperial competition algorithm is applied to the proposed model. Finally, the algorithm is compared with the standard particle swarm optimization algorithm. The simulation results based on standard 4-unit and 10-unit systems indicate that the proposed method is effective and robust for a power system with wind power and pumped storage power stations.
Evaluation of Fiscal and Non-Fiscal Policies for Electric Vehicles—A Multi-Criterion Sorting Approach
Authors: Clímaco Isabel , Henggeler Antunes Carlos
Published: April 2023

This work presents a multi-criterion approach to evaluate the performance of countries regarding fiscal and non-fiscal policies for promoting electric vehicles. The ELECTRE TRI method is used to classify the performance of countries into categories according to the degree of fulfilment of those policies. This multi-criterion decision analysis method assigns the entities under evaluation to predefined ordered categories of merit (sorting problem). This is accomplished by comparing the entities under evaluation with reference profiles that establish the frontiers between the categories. The model considers fiscal (vehicle registration tax benefits, taxation of internal combustion engine company cars, consumer purchase incentives, tax shares in consumer prices of gasoline vs. electricity) and non-fiscal (traffic regulation incentives, charging infrastructure) potential policies to define a comprehensive set of evaluation criteria. The ELECTRE TRI method allows for robust conclusions by enabling the comparison of results obtained with different preference expression parameters, according to the distinct aims and scope of the decision problem. Illustrative results are presented allowing for the assessment of each country’s performance in this setting.
The Influential Factors on the Attraction of Outstanding Scientific and Technological Talents in Developed Cities in China
Authors: Luo Jianwen , Zhu Kaikai
Published: April 2023

With the rapid development of science and technology, the demand for talents in developed countries and regions has been focused on the outstanding scientific and technological talents. How to reflect the city’s attraction and effectively implement related policies to attract, cultivate, and retain outstanding scientific and technological talents has become one of the essential development strategies. This paper investigates the factors attracting outstanding scientific and technological talents in developed cities in China with an evaluation system composed by 8 sub-criteria indicators and 25 index indicators. The results show that the urban ecological attraction level is much higher than that of human resource ecological development. A good public service system and a standardized management platform are important factors influencing the concentration of top talents. In addition, it is important to provide related policies to support innovative companies to create a better environment that can tolerate failures.
Betting Scenario for the Management of University Professional Practices from the Conformation of Intersectoral Cooperation Networks
Authors: Marín-González Freddy , Pérez-González Judith , Senior-Naveda Alexa , Narváez-Castro Mercy , Moganadas Sharmila Rani , Garcés-Rosendo Eduardo
Published: April 2023

The professional practices represent a space for interorganizational and intersectoral alliances that contribute to the development of localities and regions. From this referent, the design and validation of intersectoral cooperation networks is considered pertinent for the effective management of professional practices. Therefore, this article is oriented towards the construction of the ideal scenario where a universitygovernmentcompany intersectoral cooperation network can operate on a horizon of 2030. Foresight is used as a research and planning method, in conjunction with the consultation of experts from different social sectors that lead to obtaining sixteen scenarios of probable occurrence. For this, techniques, such as the prospective workshop, Delphi method, structural analysis (MICMAC) and scenario analysis (SMIC), are used. The results show a bet scenario where the four finally selected events occur, with a probability of occurrence of 35.7%, which would allow establishing future strategies that allow the network to be operational. It is concluded that the formation of a cooperation network for the management of university professional practices represents in itself a strategy to strengthen the curriculum and guide the achievement of common objectives in the intersectoral context studied. The contribution of the article to the study of sustainability sciences stands out, since it addresses a theme that leads to the description, explanation and understanding of the sustainable development of localities and regions from an educational dimension. In this sense, the contribution is synthesized from three planes of reflection and analysis: firstly, the understanding of sustainability as a multidimensional construct, where education is a key dimension to consolidate sustainable development processes; secondly, the management of interorganizational and intersectoral networks as a cooperation strategy that promotes sustainable development; and thirdly, prospective as a planning method that leads to delineating betting scenarios for sustainability management from an educational perspective, more specifically from the university curriculum.
A Machine Learning-Enhanced 3D Reverse Design Approach to Personalized Garments in Pursuit of Sustainability
Authors: Wang Zhujun , Tao Xuyuan , Zeng Xianyi , Xing Yingmei , Xu Zhenzhen , Bruniaux Pascal
Published: April 2023

The fashion industry is facing increasing pressure to move toward sustainable development, especially with concern to cost and environmental sustainability. Innovative digital technologies are regarded as a promising solution for fashion companies to resolve this issue. In this context, this paper put forth a new 3D reverse garment design approach embedded with a garment fit prediction and structure self-adaptive adjustment mechanism, using machine learning (ML) techniques. Initially, the 3D basic garment was drawn directly on the scanned mannequin of a specific consumer. Next, a probabilistic neural network (PNN) was employed to predict the garment’s fit. Afterwards, genetic algorithms (GA) and support vector regression (SVR) were utilized to estimate and control the garment structural parameters following the feedback of fit evaluation and the consumer’s personalized needs. Meanwhile, a comprehensive evaluation was constructed to characterize the quantitative relationships between the consumer profile and the designed garment profile (garment fit and styles). Ultimately, the desired garment which met the consumer’s needs was obtained by performing the routine of “design–fit evaluation–pattern adjustment–comprehensive evaluation”, iteratively. The experimental results show that the proposed approach provides a new solution to develop quality personalized fashion products (garments) more accurately, economically, and in an environmentally friendly way. It is feasible to facilitate the sustainable development of fashion companies by simultaneously reducing costs and negative impacts on the environment.
Picture Fuzzy Soft Prioritized Aggregation Operators and Their Applications in Medical Diagnosis
Authors: Ahmmad Jabbar , Mahmood Tahir
Published: April 2023

A medical diagnosis is one the most efficient processes of determining a disease based on a person’s symptoms and signs. In recent days, due to the complexities of the same type of diseases, it is very difficult to diagnose a disease by using old methods and techniques. In this way, new and efficient medical diagnosis methods can help a lot in reaching an accurate conclusion, depending upon the timing and sequences of symptoms and medical history. The physician relies on other clues like medical tests and imaging tests. So, in this way, a list of possible diagnoses can be determined, which are referred to as different diagnoses. To handle these types of issues in this manuscript, additional information is identified, and possible disease is confirmed. Under the consideration of classical data, it is a very difficult task to deal with complex and asymmetric sorts of data. Fuzzy set theory has a wide range of applications, from engineering to the medical field. Different methods and techniques have been proposed to support the decision-making process in medical fields. Picture fuzzy soft sets are more generalized structures and efficient tools to formalize the information more decently and accurately. So, devoted from this notion, in this article based on picture fuzzy soft settings, we firstly have established some basic operational laws for picture fuzzy soft number; then based on these operational laws, we have developed some aggregation operators named as picture fuzzy soft prioritized average and geometric aggregation operators. In real-world problems, these operators can be useful in analyzing uncomfortable and asymmetric information. Furthermore, some basic properties of the introduced operators have been initiated and discussed briefly. Moreover, to show the effective use of this developed approach to medical diagnoses, we have proposed an algorithm, along with a descriptive example. Additionally, a comparative analysis of the proposed work shows the superiority and effectiveness of the introduced approach.
An Infrastructure Cost and Benefits Evaluation Framework for Blockchain-Based Applications
Authors: Pincheira Miguel , Donini Elena , Vecchio Massimo , Giaffreda Raffaele
Published: April 2023

Blockchain is currently a core technology for developing new types of decentralized applications. With the unique properties of blockchain, unique challenges and characteristics are introduced to the system. Among these characteristics, the infrastructure costs and benefits of the system are critical to evaluate the feasibility of any system and have yet to be addressed in the current literature. This work presents a framework for evaluating blockchain applications’ infrastructure costs and benefits. The framework includes a taxonomy to classify the related transactions, a model to evaluate the infrastructure costs and benefits in applications using public or private blockchains, and a methodology to guide the use of the model. The model is based on simple parameters that describe the systems, and the methodology helps to identify and estimate these parameters at any stage of the application life cycle. We quantitatively analyze three real use cases to demonstrate the framework’s merit. The analyses highlight the model’s accuracy by achieving the same results presented in the use cases. Furthermore, the use-case analyses emphasize the framework’s potential to evaluate different scenarios across the entire life cycle of blockchain-based applications.
Visual Performance and Perceptual–Motor Skills of Late Preterm Children and Healthy Controls Using the TVPS-3rd and VMI-6th Editions
Authors: Ibrahimi Danjela , Mendiola Santibañez Jorge D. , Rodríguez-Reséndiz Juvenal
Published: April 2023

Background: The visual system is key to the learning process, preterm births are commonly followed by visual dysfunctions and other neurological conditions. Objective: to measure, analyze and compare the visual efficacy, visual–perceptual, and visual–motor skills of 20 late preterm children (34–36 weeks) born by caesarean section and appropriate weight for gestational age with 20 healthy controls born at full term by natural birth, age 5 to 12 years, from Querétaro, México. Methods: This was an observational, transverse, and prospective study. Parametric and non-parametric tests were performed using the SPSS 25.0. The visual acuity at distance and near, the phoria state, and the degree of stereopsis were analyzed. The Test of Visual-Perceptual Skills, Third Edition, was used to assess the overall performance, basic, sequencing, and complex processes. Fine motor skills were evaluated using the Visual–Motor Integration Test of Beery, Sixth Edition. Results: Visual acuity at distance and near (p<0.001), stereopsis (p<0.001), and the amount of exophoria at distance (p=0.01) showed statistically significant differences between the groups. The overall performance (p=0.006), basic processes (p=0.001), sequencing processes (p=0.02), and General and Motor VMI (p<0.001 and 0.002, respectively) presented lower values in children born preterm. Conclusion: This research showed that even late preterm children present visual deficiencies and are at risk of delays on perceptual–motor skills. Early evaluation of their visual and motor abilities should be considered in order to help improve their cognitive functioning.
Effect of Prepartum Magnesium Butyrate Supplementation on Rumination Time, Milk Yield and Composition, and Blood Parameters in Dairy Cows
Authors: Fébel Hedvig , Edwards Joan , Pajor Ferenc , Jurkovich Viktor , Bakony Mikolt , Kovács Levente
Published: April 2023

Background: Magnesium butyrate (MgB) supplementation of dairy cows during the three-week close-up period was tested for its effects on blood energy analytes, rumination time, inflammation, and lactation performance. Methods: Daily milk yield was recorded and weekly milk samples collected for the first 70 days of lactation from MgB supplemented (MgB, n = 34), and unsupplemented (Control, n = 31) multiparous Holstein-Friesian cows. During a period from week 3 to week 10 postpartum, blood samples were taken and analyzed for various parameters, and ruminant activity was measured. Results: The MgB group yielded 25.2% more milk than the Control during week 1, and had increased milk fat and protein concentrations over a longer duration. Somatic cell counts (SCC) were decreased in the MgB group independent of days in milk. No differences were observed between groups in terms of plasma non-esterified fatty acids, β-hydroxybutyrate, glucose, or blood iCa levels. The MgB group had lower haptoglobin (Hp) levels during lactation relative to the Control group. Time spent ruminating increased after calving with MgB due to a shorter post calving rumination delay relative to the Control group. Conclusions: Prepartum MgB supplementation improved lactation performance without affecting blood energy analytes. The basis by which MgB also improved rumination activity remains to be determined, as DMI could not be assessed. As MgB lowered SCC and Hp concentrations, it is speculated that MgB may help minimize postpartum inflammatory processes.
Numerical Study on the Influence of Rivers on the Urban Microclimate: A Case Study in Chengdu, China
Authors: Qi Xuejun , Zhao Xing , Fu Bin , Xu Lanjing , Yu Haibin , Tao Shuyan
Published: April 2023

The urban heat island phenomenon in large cities is becoming increasingly serious as urbanization continues to develop, seriously affecting the lives of urban residents. Rivers can effectively alleviate urban heat islands and improve the thermal comfort of riverfront space in summer. Thus, the effect of rivers on the urban microclimate environment is studied in this work. A section of the Fu River in the inland city of Chengdu was selected as the research object, and a combination of experimental and numerical simulation methods was employed. ENVI-met software was used to study the river’s influence on the air temperature, relative air humidity, and the thermal comfort of the riverfront space. The measured experimental parameters are first used to verify the accuracy of the ENVI-met software simulation results, which are then employed to carry out simulation research. The simulation results suggest that the different types of underlying surfaces have varying impacts on the air temperature and relative air humidity. Rivers have a significant cooling effect on the regional thermal environment, and roads have a warming effect on the air temperature. The order of influence of different underlying surfaces on air temperature is as follows: rivers > roads > trees. Rivers have an obvious humidifying effect on the air, and roads have little effect on relative air humidity. The order of influence of different underlying surfaces on relative air humidity is as follows: rivers > trees > roads. The results of the outdoor predicted mean vote (PMV) reveal that rivers, trees, and green plants can effectively improve the comfort of individuals downwind.
Improvement of Hargreaves–Samani Reference Evapotranspiration Estimates in the Peruvian Altiplano
Authors: Lujano Apolinario , Sanchez-Delgado Miguel , Lujano Efrain
Published: April 2023

The FAO 56 Penman–Monteith equation (PM) is considered the most accurate method for estimating reference evapotranspiration (ETo). However, PM requires a large amount of data that is not always available. Thus, the objective of this study is to improve the Hargreaves–Samani (HS) reference evapotranspiration estimates in the Peruvian Altiplano (PA) by calibrating the radiation coefficient KRS. The results show modified HS (HSM) ETo estimates at validation after KRS calibration, revealing evident improvements in accuracy with Nash–Sutcliffe efficiency (NSE) between 0.58 and 0.93, percentage bias (PBIAS) between −0.58 and 1.34%, mean absolute error (MAE) between −0.02 and 0.05 mm/d, and root mean square error (RMSE) between 0.14 and 0.25 mm/d. Consequently, the multiple linear regression (MLR) model was used to regionalize the KRS for the PA. It is concluded that, in the absence of meteorological data, the HSM equation can be used with the new values of KRS instead of HS for the PA.
Macrozoobenthos Structure and Dynamics in a Mediterranean Hypersaline Ecosystem with Implications for Wetland Conservation
Authors: Bonifazi Andrea , Galli Simone , Gravina Maria Flavia , Ventura Daniele
Published: April 2023

Within the framework of hypersaline environments, the Saline di Tarquinia salterns (Latium, Italy) represent an interesting case study from ecological, naturalistic, and conservationist perspectives. We studied macrozoobenthic community zonation related to the main environmental parameters, with particular emphasis on the beetle species Nebrioporus ceresyi (Aubé, 1836), one of the few Dytiscidae among Italian fauna particularly adapted to brackish and hypersaline waters. In this study, we report the structure and seasonal dynamics of the macrozoobenthic community, the spatial and temporal distribution of both larvae and adults of N. ceresyi, and the size–frequency distribution of the larvae. The results add new information on the macrozoobenthic assemblage of the Saline di Tarquinia salterns and the life cycle of this water beetle in the hypersaline habitat. A possible hypothesis about the discontinuous geographical distribution of the species of Dytiscidae investigated is also provided. Finally, N. ceresyi is proposed as an indicator species useful in characterizing the environmental zonation of hypersaline habitats.
Implicaciones teóricas de la administración financiera
Authors: Vázquez-Vidal Verónica
Published: April 2023

La administración financiera es cuya diciplina se encarga de la planificación, organización y control de los recursos financieros, es decir, se encarga de las tomas de decisiones sobre financiamientos, inversiones, ahorros y presupuestos, etcétera.  Pues sus implicaciones consisten en obtener una función operativa dedicada a la estructura, la gestión de la liquidez y los activos financieros en materia. Para poder entenderla es necesario hacer hincapié en la finalidad que tiene la misma, esta es la planificación, la cual se encargará de aquellos acuerdos económicos a largo y corto plazo, con el fin de reducir riesgos y con ello incrementar el valor de la compañía, tomando en cuenta el desarrollo del mercado, por ende, incluye todas las decisiones financieras de inversión, como lo son la financiación, programación y control de proyectos de inversión, políticas en inversión entre otras.

Los objetivos de la administración financiera incluyen principalmente el mantenimiento de los recursos, entender y manejar de forma óptima los riesgos (principalmente en las inversiones), buscar la maximización de las utilidades o ingresos y finalmente, el mejoramiento de la utilización de los recursos financieros ya sean de un particular o de una empresa.

El presente articulo nos permitirá conocer los conocimientos básicos de “las implicaciones teóricas de la administración financiera”, para así implementar un plan de acción a la hora de hacer inversiones, y con ello la planificación adecuada para la mejora de los gastos, de forma tal que se cree un buen presupuesto y se maximicen las utilidades. Los recursos financieros de la empresa son fundamentales, de ello la idea que un buen manejo de estos lleve al éxito, dentro de la administración financiera se maneja el estudio eficiente del dinero.
Impacto de las redes sociales en la gestión de proyectos sociales.
Authors: Hernandez Hector Andres , Mercado-Mulcue Gerson Rubén , Gil-Niño John Alejandro , Salas-Tosne Deyby Sebastián
Published: April 2023

El mundo actualmente valora la importancia de la adaptación de las herramientas tecnológicas y portales web (web 2.0) con la gestión de proyectos, sobre todo enfocados en la sociedad. La comunicación tiene un rol fundamental en la sociedad. Las redes sociales han marcado un alto impacto en las empresas, en sus diferentes departamentos, entre ellos la oficina de gestión de proyectos (PMO), un área que constantemente debe comunicar e informar de lo que ocurre con su portafolio de proyectos, implementar estas nuevas estrategias de comunicación generan un gran beneficio hacia la comunidad interesada (Stakeholders) de un determinado proyecto. Generando valor durante toda la gestión y ejecución de este por lo que el objetivo de este artículo es analizar el impacto de las redes sociales en la gestión de proyectos sociales.
Integrating Symbol Similarities with Knowledge Graph Embedding for Entity Alignment: An Unsupervised Framework
Authors: Jiang Tingting , Bu Chenyang , Zhu Yi , Wu Xindong
Published: April 2023

Entity alignment refers to discovering identical entity pairs in 2 knowledge graphs, which is a significant task in knowledge fusion. Early automated entity alignment techniques are based mainly on similarity calculation and comparing symbolic features, i.e., entity names, between entities. Nevertheless, such methods’ performance would reduce significantly when the difference between knowledge graphs is enormous because of relying on predefined comparison rules. Recently, embedding-based methods calculate the similarity between entity pairs through vector embeddings and thus can deal with different knowledge graphs. However, embedding-based methods mostly require humans to annotate data, which is laborious. Therefore, we learn from each other to propose an unsupervised entity alignment framework in this work, which can generate initial alignment seeds automatically by considering symbolic similarities. It can effectively avoid the waste of human resources and is suitable for handling multiple types of knowledge graphs. In addition, we investigate improving the quality and quantity of initial alignment by integrating multiple symbolic similarity features of entities and dealing with the situation of entity information missing better. Experimental results on 3 real datasets demonstrate its state-of-the-art performance.
It’s all about Priorities: Tips for Successfully Implementing Gender Equality Actions
Authors: Sangiuliano Maria , Karydou Kyriaki , Kyrkou Danai
Published: April 2023

The adoption of an inclusive Gender Equality Plan (iGEP) in Research Performing Organisations (RPO) and Research Funding Organisations (RFO) is a dynamic process that mobilises knowledge and skills, and at the same time creates challenges in each step. The Horizon 2020 CALIPER project supports seven RPOs and two RFOs across Europe in implementing iGEPs, focusing on the STEM fields. At this stage, CALIPER partners completed the first iteration phase of their iGEP implementation lasting 12 months. This work-in-progress paper presents practical examples from their GEP experience so far, focusing on the activities/steps an institution can put in place to adopt an inclusive approach to the GEP process. The “tips” are grounded in the formative evaluation reports, drafted by the CALIPER RPOs/RFOs after the end of the first implementation iteration. This action-oriented paper targets practitioners, active in Gender Equality (GE) in Research and Innovation (R&I).