bluuebunny/crossref_metadata_2025 huggingface dataset:
3D Object Detection via 2D Segmentation-Based Computational Integral Imaging Applied to a Real Video
Authors: Kadosh Michael , Yitzhaky Yitzhak
Published: April 2023

This study aims to achieve accurate three-dimensional (3D) localization of multiple objects in a complicated scene using passive imaging. It is challenging, as it requires accurate localization of the objects in all three dimensions given recorded 2D images. An integral imaging system captures the scene from multiple angles and is able to computationally produce blur-based depth information about the objects in the scene. We propose a method to detect and segment objects in a 3D space using integral-imaging data obtained by a video camera array. Using objects’ two-dimensional regions detected via deep learning, we employ local computational integral imaging in detected objects’ depth tubes to estimate the depth positions of the objects along the viewing axis. This method analyzes object-based blurring characteristics in the 3D environment efficiently. Our camera array produces an array of multiple-view videos of the scene, called elemental videos. Thus, the proposed 3D object detection applied to the video frames allows for 3D tracking of the objects with knowledge of their depth positions along the video. Results show successful 3D object detection with depth localization in a real-life scene based on passive integral imaging. Such outcomes have not been obtained in previous studies using integral imaging; mainly, the proposed method outperforms them in its ability to detect the depth locations of objects that are in close proximity to each other, regardless of the object size. This study may contribute when robust 3D object localization is desired with passive imaging, but it requires a camera or lens array imaging apparatus.
Machine-Aided Bridge Deck Crack Condition State Assessment Using Artificial Intelligence
Authors: Zhang Xin , Wogen Benjamin E. , Liu Xiaoyu , Iturburu Lissette , Salmeron Manuel , Dyke Shirley J. , Poston Randall , Ramirez Julio A.
Published: April 2023

The Federal Highway Administration (FHWA) mandates biannual bridge inspections to assess the condition of all bridges in the United States. These inspections are recorded in the National Bridge Inventory (NBI) and the respective state’s databases to manage, study, and analyze the data. As FHWA specifications become more complex, inspections require more training and field time. Recently, element-level inspections were added, assigning a condition state to each minor element in the bridge. To address this new requirement, a machine-aided bridge inspection method was developed using artificial intelligence (AI) to assist inspectors. The proposed method focuses on the condition state assessment of cracking in reinforced concrete bridge deck elements. The deep learning-based workflow integrated with image classification and semantic segmentation methods is utilized to extract information from images and evaluate the condition state of cracks according to FHWA specifications. The new workflow uses a deep neural network to extract information required by the bridge inspection manual, enabling the determination of the condition state of cracks in the deck. The results of experimentation demonstrate the effectiveness of this workflow for this application. The method also balances the costs and risks associated with increasing levels of AI involvement, enabling inspectors to better manage their resources. This AI-based method can be implemented by asset owners, such as Departments of Transportation, to better serve communities.
A Supervised Machine Learning Approach to Classify Brain Morphology of Professional Visual Artists versus Non-Artists
Authors: Grecucci Alessandro , Rastelli Clara , Bacci Francesca , Melcher David , De Pisapia Nicola
Published: April 2023

This study aimed to investigate whether there are structural differences in the brains of professional artists who received formal training in the visual arts and non-artists who did not have any formal training or professional experience in the visual arts, and whether these differences can be used to accurately classify individuals as being an artist or not. Previous research using functional MRI has suggested that general creativity involves a balance between the default mode network and the executive control network. However, it is not known whether there are structural differences between the brains of artists and non-artists. In this study, a machine learning method called Multi-Kernel Learning (MKL) was applied to gray matter images of 12 artists and 12 non-artists matched for age and gender. The results showed that the predictive model was able to correctly classify artists from non-artists with an accuracy of 79.17% (AUC 88%), and had the ability to predict new cases with an accuracy of 81.82%. The brain regions most important for this classification were the Heschl area, amygdala, cingulate, thalamus, and parts of the parietal and occipital lobes as well as the temporal pole. These regions may be related to the enhanced emotional and visuospatial abilities that professional artists possess compared to non-artists. Additionally, the reliability of this circuit was assessed using two different classifiers, which confirmed the findings. There was also a trend towards significance between the circuit and a measure of vividness of imagery, further supporting the idea that these brain regions may be related to the imagery abilities involved in the artistic process.
Seamless 5G Multi-Hop Connectivity Architecture and Trials for Maritime Applications
Authors: Lindenbergs Artürs , Muehleisen Maciej , Payaró Miquel , Kõrbe Kaare Kati , Zaglauer Helmut W. , Scholliers Johan , Sadam Arvi , Kuhi Kristjan , Nykanen Lasse
Published: April 2023

This paper provides a study of the different alternatives that are being considered in the 5G-ROUTES project to establish seamless 5G connectivity in a maritime environment both from an architectural point of view and also from the definition of field trials to evaluate the performance and dependability of the proposed solution. As expected, the main challenge in providing 5G connectivity on the sea is to provide coverage over large areas of open water. Thus, as a starting point, this paper presents a measurement campaign that was conducted to assess the current coverage in the Baltic Sea, which concluded that the current terrestrial networks cannot guarantee sufficient coverage. Next, the solution architecture and trials proposed by 5G-ROUTES are described, which are based on the integration of satellite and leading-edge multi-hop connectivity in 5G networks. Utilizing satellite backhaul can potentially overcome the connectivity challenge from the terrestrial domain to the maritime domain, while multi-hop connectivity ensures that coverage is extended among the different ships that are navigating the sea. Furthermore, this paper describes how the project will evaluate, in field trials tailored to this maritime environment, common connectivity key performance indicators (KPIs) such as latency, throughput, availability and reliability. This paper concludes by providing a vision for applying the obtained results and insights to maritime transportation and other remote areas where the deployment of a suitable 5G infrastructure may be challenging or costly. The findings will be used to guide the design of future 5G networks for marine applications and to identify the most effective methods for providing secure and dependable communication in a maritime setting.
Development of a Mercury Bromide Birefringence Measurement System Based on Brewster’s Angle
Authors: Kwon Oh-Tae , Kim Geonwoo , Bae Hyungjin , Ryu Jaeyeol , Woo Sikwan , Cho Byoung-Kwan
Published: April 2023

Mercury bromide (Hg2Br2) has been used to develop acousto-optic tunable filters (AOTFs) because it has several advantages, including a high refractive index, a broad optical bandwidth, and a relatively high figure of merit. Therefore, the measurement of its birefringence is a highly important factor for ensuring AOTF quality. However, for single crystals, it is difficult (at the millimeter scale) to quantify the birefringence using an ellipsometer, as this equipment is only designed to conduct measurements on thin films. In this study, a simple birefringence measurement system for Hg2Br2 was developed based on Brewster’s angle at the millimeter scale. The planar distributions of the Hg2Br2 crystal along the (100), (010), and (001) planes were used in the experiments. The developed measurement system can measure the reflected light intensity of the Hg2Br2 crystal depending on the incidence angles (rotations at 0.01125° steps) and can calculate the ordinary and extraordinary refractive indices and birefringence. The calculated birefringence of the Hg2Br2 crystal was 0.8548; this value exhibits an error of 0.64% compared with a value of 0.86 reported in the literature. The developed measurement system demonstrates the ability to be used to evaluate the quality of birefringent single crystals.
Generalized Fringe-to-Phase Framework for Single-Shot 3D Reconstruction Integrating Structured Light with Deep Learning
Authors: Nguyen Andrew-Hieu , Ly Khanh L. , Lam Van Khanh , Wang Zhaoyang
Published: April 2023

Three-dimensional (3D) shape acquisition of objects from a single-shot image has been highly demanded by numerous applications in many fields, such as medical imaging, robotic navigation, virtual reality, and product in-line inspection. This paper presents a robust 3D shape reconstruction approach integrating a structured-light technique with a deep learning-based artificial neural network. The proposed approach employs a single-input dual-output network capable of transforming a single structured-light image into two intermediate outputs of multiple phase-shifted fringe patterns and a coarse phase map, through which the unwrapped true phase distributions containing the depth information of the imaging target can be accurately determined for subsequent 3D reconstruction process. A conventional fringe projection technique is employed to prepare the ground-truth training labels, and part of its classic algorithm is adopted to preserve the accuracy of the 3D reconstruction. Numerous experiments have been conducted to assess the proposed technique, and its robustness makes it a promising and much-needed tool for scientific research and engineering applications.
A Portable Tunnel Electromagnetic Impulse Shock Source
Authors: Hu Yuning , Wang Wei , Liu Wei , Chen Zihan , Zhou Jie , Fu Zhihong
Published: April 2023

Early seismic prediction in tunnels has become a necessary task to prevent construction risks. The type and performance of the seismic source are crucial factors that affect its efficiency and prediction accuracy. Among the existing main types of tunnel seismic sources, both explosive and spark sources require pre-drilling and pose safety hazards. In addition, explosive sources pose a risk of damage to tunnel structure walls. Spark sources must be used in a water medium. Artificial hammer sources have weak energy and short prediction distance. This paper proposes a portable tunnel electromagnetic impulse shock source that overcomes the deficiencies of the aforementioned seismic sources. This paper elaborates on the design and working principle of the electromagnetic impulse shock source, and analyzes the electromagnetic force exerted on the hammer body during acceleration. Through finite element simulation, this paper analyzes the multi-physical field changes of the entire electromagnetic acceleration system. Meanwhile, combining experimental testing, the design parameters and energy of the seismic source are optimized to finally design a portable electromagnetic impulse shock source. The engineering measurement data results show that the seismic source can stably generate an output energy of 1500 J, and the overall weight of the seismic source does not exceed 40 kg, with a single shot time less than 30 s and an effective prediction distance over 100 m. This work has significant practical value and superiority.
Glucose Concentration Measurement by All-Grating-Based System
Authors: Hsieh Hung-Chih , Lu Yi-Ming , Huang Ke-Cheng
Published: April 2023

An accurate, easy setup, low-cost, and time-saving method for measuring glucose concentration was proposed. An all-grating-based glucose concentration measurement system contained moving-grating-based heterodyne interferometry and a grating-based self-align sensor. By combining the first-order diffraction lights from two separated moving gratings by a polarization beam splitter and creating S- and P-polarized light interference by an analyzer, the interference signal could be a heterodyne light source with a heterodyne frequency depending on the relative velocities of the two moving gratings. Next, a grating-based self-align sensor was used to make the optical configuration setup easy and accurate. Moreover, the sensor was deposited on GOx film to improve the measurement sensitivity and specificity for glucose. Finally, the phase change induced by the reaction of the sensor and glucose solutions was detected. The validity of this method was proved, and the measurement resolution can reach 2 mg/dL.
Biomagnetism: The First Sixty Years
Authors: Roth Bradley J.
Published: April 2023

Biomagnetism is the measurement of the weak magnetic fields produced by nerves and muscle. The magnetic field of the heart—the magnetocardiogram (MCG)—is the largest biomagnetic signal generated by the body and was the first measured. Magnetic fields have been detected from isolated tissue, such as a peripheral nerve or cardiac muscle, and these studies have provided insights into the fundamental properties of biomagnetism. The magnetic field of the brain—the magnetoencephalogram (MEG)—has generated much interest and has potential clinical applications to epilepsy, migraine, and psychiatric disorders. The biomagnetic inverse problem, calculating the electrical sources inside the brain from magnetic field recordings made outside the head, is difficult, but several techniques have been introduced to solve it. Traditionally, biomagnetic fields are recorded using superconducting quantum interference device (SQUID) magnetometers, but recently, new sensors have been developed that allow magnetic measurements without the cryogenic technology required for SQUIDs.
Hand Gesture Interface for Robot Path Definition in Collaborative Applications: Implementation and Comparative Study
Authors: Vysocký Aleš , Poštulka Tomáš , Chlebek Jakub , Kot Tomáš , Maslowski Jan , Grushko Stefan
Published: April 2023

The article explores the possibilities of using hand gestures as a control interface for robotic systems in a collaborative workspace. The development of hand gesture control interfaces has become increasingly important in everyday life as well as professional contexts such as manufacturing processes. We present a system designed to facilitate collaboration between humans and robots in manufacturing processes that require frequent revisions of the robot path and that allows direct definition of the waypoints, which differentiates our system from the existing ones. We introduce a novel and intuitive approach to human–robot cooperation through the use of simple gestures. As part of a robotic workspace, a proposed interface was developed and implemented utilising three RGB-D sensors for monitoring the operator’s hand movements within the workspace. The system employs distributed data processing through multiple Jetson Nano units, with each unit processing data from a single camera. MediaPipe solution is utilised to localise the hand landmarks in the RGB image, enabling gesture recognition. We compare the conventional methods of defining robot trajectories with their developed gesture-based system through an experiment with 20 volunteers. The experiment involved verification of the system under realistic conditions in a real workspace closely resembling the intended industrial application. Data collected during the experiment included both objective and subjective parameters. The results indicate that the gesture-based interface enables users to define a given path objectively faster than conventional methods. We critically analyse the features and limitations of the developed system and suggest directions for future research. Overall, the experimental results indicate the usefulness of the developed system as it can speed up the definition of the robot’s path.
A Compact Planar Monopole UWB MIMO Antenna for Short-Range Indoor Applications
Authors: Kolangiammal Shanmugam , Balaji Loganathan , Mahdal Miroslav
Published: April 2023

A compact, four-element planar MIMO (Multiple Input, Multiple Output) antenna that operates in an ultra-wideband is presented for diversity application. The orthogonal position of the unit cells replicates the single antenna thrice, thereby decreasing mutual coupling. A UWB MIMO antenna measuring 35 × 35 × 1.6 mm3 is built using a microstrip line (50 Ω impedance) on an FR4 substrate having a thickness of 1.6 mm. The ground plane and radiator of this antenna are adjusted in several ways to bring it within its operating constraints between the frequencies of 3.1 GHz and 10.6 GHz. This technique makes the antenna small and covers the entire ultra-wideband (UWB) frequency range. The NI USRP was used to test the proposed MIMO antenna to determine its real-time performance. Based on the computed results, we conclude that this proposed antenna has outstanding characteristics in terms of performance and is suitable for wireless ultra-wideband indoor communication and diversity utilization with a small size.
Metamaterials for Acoustic Noise Filtering and Energy Harvesting
Authors: Mir Fariha , Mandal Debdyuti , Banerjee Sourav
Published: April 2023

Artificial methods for noise filtering are required for the twenty-first century’s Factory vision 4.0. From various perspectives of physics, noise filtering capabilities could be addressed in multiple ways. In this article, the physics of noise control is first dissected into active and passive control mechanisms and then further different physics are categorized to visualize their respective physics, mechanism, and target of their respective applications. Beyond traditional passive approaches, the comparatively modern concept for sound isolation and acoustic noise filtering is based on artificial metamaterials. These new materials demonstrate unique interaction with acoustic wave propagation exploiting different physics, which is emphasized in this article. A few multi-functional metamaterials were reported to harvest energy while filtering the ambient noise simultaneously. It was found to be extremely useful for next-generation noise applications where simultaneously, green energy could be generated from the energy which is otherwise lost. In this article, both these concepts are brought under one umbrella to evaluate the applicability of the respective methods. An attempt has been made to create groundbreaking transformative and collaborative possibilities. Controlling of acoustic sources and active damping mechanisms are reported under an active mechanism. Whereas Helmholtz resonator, sound absorbing, spring-mass damping, and vibration absorbing approaches together with metamaterial approaches are reported under a passive mechanism. The possible application of metamaterials with ventilation while performing noise filtering is reported to be implemented for future Smart Cities.
Detecting Movement Changes in Children with Hemiparesis after Upper Limb Therapies: A Responsiveness Analysis of a 3D Bimanual Protocol
Authors: Cacioppo Marine , Lempereur Mathieu , Houx Laetitia , Bouvier Sandra , Bailly Rodolphe , Brochard Sylvain
Published: April 2023

The “Be an Airplane Pilot” (BE API) protocol was developed to evaluate upper limb (UL) kinematics in children with unilateral cerebral palsy (uCP) during bimanual tasks. The aim of this study was to investigate the responsiveness of this protocol to changes in kinematics and movement quality after UL therapies, using individual and group analyses, and to analyse the relationships between kinematic and functional changes in these children. Twenty children with uCP (5–15 years old) either participated in bimanual intensive therapy or received UL botulinum toxin injections. All the children performed the BE API protocol and functional assessments (Assisting Hand Assessment [AHA]) before and after the interventions. The individual analyses found kinematic changes in 100% of the children after therapy. The group analysis found significantly higher trunk and shoulder deviations after the intensive therapy. No significant changes were found for smoothness or trajectory straightness. The changes in the kinematic deviations were moderately correlated with the changes in the AHA scores. This study confirmed the responsiveness of the BE API protocol to change after therapy; therefore, the protocol is now fully validated and can be implemented in clinical practice. Its use should help in the accurate identification of impairments so that individualized treatments can be proposed.
Development of a Pavement-Embedded Piezoelectric Harvester in a Real Traffic Environment
Authors: Heller Lucas Fraporti , Brito Lélio Antônio Teixeira , Coelho Marcos Antônio Jeremias , Brusamarello Valner , Nuñez Washington Peres
Published: April 2023

Road pavements are spread over large areas and convey various possibilities for energy sources such as high thermal gradients due to their materials and colors, wind corridors, large flat areas for solar harvesting, and heavy loading from traffic. The latest advances in road energy generation have been discretely implemented and have mainly focused on photovoltaic surface applications; other studies have explored the use of piezoelectric transducers with high stresses for better energy-production performance but limited life span. This study explores the stresses on pavement surfaces from traffic loading shockwaves that yield to the natural frequency vibration a piezoelectric harvester using a cantilever array. The passing vehicles triggered 16 piezoelectric sensors divided into four embedded steel profiles. The peak electrical power obtained in the experiment was 55.6 µW with a single transducer using a tip mass of 16 g. The proposed harvester demonstrated potential for applications in micro-generation of energy with limited infrastructure modification and high endurance under traffic loading over time. Its generation capacity is around 50 mWh a month with 16 piezoelectric cantilevers installed (for a commercial traffic volume of 1500 vehicles a day), enough to power a 200 m flashing LED raised marker strip to guide drivers for lane alignment during night shifts.
Characterizing the Change of Annual Cone Production in Longleaf Pine Forests
Authors: Chen Xiongwen , Willis John L.
Published: April 2023

Sporadic cone (or seed) production challenges longleaf pine forest restoration. Characterizing annual cone production change from long-term monitored data provides functional information on the foundational species of this imperiled ecosystem. In this study, permutation entropy (PE) and phase change were used to analyze longleaf pine annual cone production based on cone counts from four sites (Escambia Experimental Forest, Blackwater River State Forest, The Jones Center at Ichauway, and Sandhills State Forest). PE is an analytical tool to measure the complexity of a dynamic system while phase change characterizes the stage of self-organization. Results indicate that PE at each site was close to 1.0 (largely random changes in annual cone production) and generally increased with time. The positive association between the permutation entropy of cone production and average air temperature at different times was significant at two sites (Blackwater River State Forest and The Jones Center at Ichauway). The frequency distribution of phases (e.g., Poor (P), Fair (F), Good (G), Bumper (B)) in cone production followed negative power laws. Phase P could transition to any stage, but more than 50% remained in P across sites. For phase G, it would revert to P more than 50% of the time. Phase B would shift to P, except at Sandhills State Forest. The average lasting time of phase P was approximately 3.7 years. The overall relationship between the interval time of phase B and cone production was not statistically significant. Similarly, the overall relationship between cone production in phase B and the phase change times between consecutive B phases was not statistically significant. These results provide information on the ecological complexity of cone (or seed) production. Our methods can be helpful for estimating the occurrence of bumper cone (or seed) production, the lasting period between phase changes, and providing a tool for predicting natural regeneration potential over time for longleaf pine and other tree species (e.g., masting species).
Phenolic Profile of Castanea Bee Pollen from the Northwest of the Iberian Peninsula
Authors: Rodríguez-Flores María Shantal , Escuredo Olga , Seijo María Carmen , Rojo Sergio , Vilas-Boas Miguel , Falcão Soraia I.
Published: April 2023

Bee pollen is a rich bee product, from the point of view of its nutritional and functional chemical characteristics. The chemical composition of bee pollen and its properties make this product an excellent food supplement for the human diet, due to its various functional bioactivities, such as having antioxidant, antibacterial, antifungal, and anti-inflammatory properties. These properties depend on the botanical origin of the bee pollen. Castanea sativa bee pollen is one of the most important types of pollen collected in the northwest of the Iberian Peninsula. Thus, the phenolic profile of Castanea bee pollen was featured in this study. For this, 11 samples of Castanea were selected through prior colorimetric separation using the CIELab* scale and verified with palynological analysis. Identification of the main phenol compounds was performed through LC/DAD/ESI-MSn analysis. The phenols compounds were quantified using calibration curves for caffeic acid, quercetin, and naringenin. The main results showed a profile formed of 19 compounds for all samples, although quantitative differences were found. Most of these compounds were phenolamides, with N1, N5, and N10-tricaffeoylspermidine being significantly (p < 0.05) the most abundant. Three isorhamnetin glycoside derivatives and one naringenin were also identified. The richness in phenolamides of Castanea bee pollen identified in this study suggests Castanea bee pollen as a functional food, owing to its healthy properties.
Green Extraction of Phenolic Compounds from Lotus (Nelumbo nucifera Gaertn) Leaf Using Deep Eutectic Solvents: Process Optimization and Antioxidant Activity
Authors: Yang Jiwei , Yan Zhi , Li Lingna , Zhang Lifen , Zhao Mengjian , Yi Huixiang , Wang Ziying , Li Gang , Wang Zhenhua , Li Mei , Ma Chengjun
Published: April 2023

Natural deep eutectic solvents (NDESs) were used to extract flavonoids and polyphenols from lotus (Nelumbo nucifera Gaertn.) leaves at the same time, and the extraction process was optimized to provide reference for the effective development and utilization of lotus leaves. The deep eutectic solvents (DESs) with the highest yield of flavonoids and polyphenols were screened out from 19 different NDES combinations. The response surface method was employed to optimize the extraction process. After a rational design, a lactic acid/glycerol (molar ratio 1:2) DES was chosen as the optimal extraction solvent, and the optimum extraction parameters were as follow: water content (29%), liquid–solid ratio (37:1 mL/g), extraction time (61 min), and extraction temperature (53 °C). Compared with traditional water extraction or ethanol extraction, it improved the yield of flavonoids (126.10 mg/g) and polyphenols (126.10 mg/g). By LC–MS analysis, 19 flavonoids or organic acid compounds with known compound structural formulae were identified in the DES extract of lotus leaves. By comparing the free radical scavenging ability and total reducing ability, the extraction of lotus leaves using the NDES method was superior to both ethanol extraction and water extraction. It is a green, environmentally friendly, and efficient extraction method for antioxidants from leaves of Nelumbo nucifera Gaertn.
Method Development and Validation for the Simultaneous Quantitation of Pentoxifylline, Its Pharmacologically Active Metabolites, and Donepezil Using LC-MS/MS in Rat Plasma: Its Application to a Pharmacokinetic Study
Authors: Choi Sanghee , Shim Wang-Seob , Yoon Jiyoung , Choi Doowon , Song Eunseo , Choi Yeo Jin , Paik Soo-Heui , Lee Kyung-Tae
Published: April 2023

This study developed a simple, rapid, reproducible, and analytical method using liquid chromatography and electrospray ionization (ESI) with tandem mass spectrometry (LC-MS/MS) to simultaneously quantify pentoxifylline (PTX), its pharmacological active metabolites, lisofylline (PTX-M1) and 1-(3-carboxypropyl)-3,7-dimethylxanthine (PTX-M5), and donepezil (DNP) in rat plasma, using PTX-d6 and DNP-d7 as the internal standards. The LC-MS/MS procedure was performed at the ESI interface, operating in positive ionization and multiple reaction monitoring (MRM) modes; the monitoring of transitions comprised m/z 279.3 > 181.1 for PTX, m/z 281.1 > 263.1 > 160.90 for PTX-M1, m/z 267.1 > 249.0 > 220.9 for PTX-M5, m/z 380.3 > 90.9 for DNP, m/z 285.3 > 187.1 for PTX-d6 (IS1), and m/z 387.3 > 98.3 for DNP-d7 (IS2). After plasma protein precipitation (PP) with methanol, chromatographic separation was performed with an Imtakt Cadenza® CD-C18 (100 × 3 mm, 3 µm) column, using an isocratic mobile phase consisting of 0.1% formic acid in water and methanol (20:80, v/v) at a flow rate of 0.2 mL/min. The retention times of DNP, PTX-M5, PTX, and PTX-M1 were 2.24, 2.50, 2.68, and 2.72 min, respectively, with a total run time of 5 min. This method was validated over a linear concentration range of 5–8000, 10–5000, 20–15,000, and 2–500 ng mL−1 for PTX, PTX-M1, PTX-M5, and DNP, respectively, with a high correlation coefficient (r2 ≥ 0.99). The established method was fully validated in terms of selectivity, the lower limit of quantitation, precision, accuracy, recovery, matrix effect, stability, and dilution integrity according to the regulatory guidelines from the U.S. Food and Drug Administration and the Korea Ministry of Food and Drug Safety. The validated method was successfully applied to a pharmacokinetic study on the concurrent administration of DNP and PTX in rats.
Graphical User Interface for the Development of Probabilistic Convolutional Neural Networks
Authors: Chaves Aníbal , Mendonça Fábio , Mostafa Sheikh Shanawaz , Morgado-Dias Fernando
Published: April 2023

Through the development of artificial intelligence, some capabilities of human beings have been replicated in computers. Among the developed models, convolutional neural networks stand out considerably because they make it possible for systems to have the inherent capabilities of humans, such as pattern recognition in images and signals. However, conventional methods are based on deterministic models, which cannot express the epistemic uncertainty of their predictions. The alternative consists of probabilistic models, although these are considerably more difficult to develop. To address the problems related to the development of probabilistic networks and the choice of network architecture, this article proposes the development of an application that allows the user to choose the desired architecture with the trained model for the given data. This application, named “Graphical User Interface for Probabilistic Neural Networks”, allows the user to develop or to use a standard convolutional neural network for the provided data, with networks already adapted to implement a probabilistic model. Contrary to the existing models for generic use, which are deterministic and already pre-trained on databases to be used in transfer learning, the approach followed in this work creates the network layer by layer, with training performed on the provided data, originating a specific model for the data in question.
Intelligent and Environmentally Friendly Solutions in Smart Cities’ Development—Empirical Evidence from Poland
Authors: Janik Agnieszka , Ryszko Adam , Szafraniec Marek
Published: April 2023

This study presents a comprehensive analysis aiming to identify the implementation level of intelligent and environmentally friendly solutions (IEFS) in cities in Poland, and barriers impeding their development. Based on a representative sample of 280 cities, it was evident that the implementation level of IEFS in Poland is relatively very low. The most common barriers to IEFS implementation as indicated by representatives of city authorities were high costs, lack of adequate funds, and lack of awareness of benefits resulting from applying IEFS. Nevertheless, regression analyses showed that the IEFS implementation level was mostly affected by cities’ population size and perception of individual IEFS as integral elements of the smart city concept. It was also revealed that the high costs of implementing IEFS, the lack of their inclusion in local development strategies, the lack of appropriate legal regulations, the lack of widespread good practices, and the resistance of inhabitants to change and to new technologies perceived as impediments had significant negative effects on the implementation level of specific IEFS. Furthermore, the analyses demonstrated that perceiving certain issues as barriers did not hinder the implementation of such solutions. Based on a discussion of the results, relevant recommendations and directions for future research are proposed.
The Entropy of Romanian Economists into the Labour Market
Authors: Simionescu Mihaela
Published: April 2023

The rate of unemployment for higher educated people has increased in Romania in the last few decades. The aim of this paper is to analyse survey data from master’s students in Economics from some private and public universities in Bucharest. The study uses ANOVA/linear Dependent Dirichlet Process mixture model to explain the scores from these surveys. The results suggest that the causes of interview rejections for master’s students are due to gender, work seniority, type of university attended, and the requirements of employers in the field. In addition, a rank ordered probit model is used to assess the importance assigned by managers to recommendations to improve university education. The results confirm the rigidities of the Romanian labour market and the necessity to design more and better internships that support policy recommendations for better school-to-work transition.
The Influence of Migration Patterns on Regional Demographic Development in Germany
Authors: Ernst Julian , Dräger Sebastian , Schmaus Simon , Weymeirsch Jan , Alsaloum Ahmed , Münnich Ralf
Published: April 2023

Political decision-making related to future challenges, for example in the fields of medical care, the housing market or education highly depend on valid estimates of the future population size and structure. However, such developments are usually heterogeneous throughout a country making subnational projections necessary. It is well-known that these regional differences are highly influenced by both internal and external migration processes. In this paper, we investigate the consequences of different migration assumptions on regional development in Germany using a spatial dynamic microsimulation. We find that migration assumptions have a strong direct influence on the future population and composition at the regional level and, therefore, require special attention. Depending on the scenario selected, very different socio-demographic trends may emerge in specific districts or even district types. We also demonstrate that migration assumptions affect non-demographic indicators such as the participation rate, albeit to a lesser extent. The findings are relevant to understanding the sensitivity of population projections to migration assumptions both on the national and regional level. This also paves the way to analyze how potential political interventions behave under those assumed future migration processes.
Towards an Exploration of the Significance of Community Participation in the Integrated Development Planning Process in South Africa
Authors: Mamokhere John , Meyer Daniel Francois
Published: April 2023

The IDP serves as a comprehensive plan that outlines development priorities for a municipality’s jurisdiction. Its aim is to coordinate the efforts of all levels of government in order to improve the quality of life for residents in a particular area. The plan is developed based on the needs and priorities of the community, with opportunities for community involvement in identifying the most pressing needs. All stakeholders are invited to participate in the creation and execution of the plan. This study seeks to explore the significance of community participation in the IDP, using the Tzaneen municipal area as a case study. Despite various challenges, such as a lack of resources and protests, active participation in the IDP process can lead to improved service delivery, enhanced democracy, accountability, responsiveness, and community empowerment. This study adopted a convergent parallel mixed-method research approach. The study was conducted in the Tzaneen municipal area, South Africa, and four hundred and ten (410) participants were sampled in the area through probability and non-probability sampling techniques. The data were collected and analysed until saturation was reached. An online, closed-ended, structured questionnaire and face-to-face semi-structured interviews to collect empirical data were used in addition to a review of the existing literature. The study found a continuous lack of community participation in municipal affairs. The service delivery backlog is still a challenge despite the constitutional mandates and democratic principles. The participants indicated that they are unable to hold municipal officials accountable. Lastly, there is a lack of political willingness to partake in the IDP process. Thus, this study concludes by recommending that municipal policies ought to be influenced by community participation. The study found that democratic principles are still weakened. Thus, the study recommends that the Greater Tzaneen Municipality’s officials and politicians (Councillors/Ward Committee members) should always uphold democratic principles as stated in the Constitution of 1996 by ensuring active public participation, transparency, and accountable governance.
Effects of Irrigation Regimes and Rice Varieties on Methane Emissions and Yield of Dry Season Rice in Bangladesh
Authors: Habib Muhammad Ashraful , Islam S. M. Mofijul , Haque Md. Ashraful , Hassan Lutful , Ali Md. Zulfiker , Nayak Swati , Dar Manzoor Hussain , Gaihre Yam Kanta
Published: April 2023

Adoption of the right rice variety and water-saving irrigation method could reduce greenhouse gas (GHG) emissions in lowland rice cultivation. A study was conducted at the research farm of Bangladesh Agricultural University, Mymensingh, Bangladesh, in 2019 during the Boro (dry) season to determine the impacts of different rice varieties (BRRI dhan29, BRRI dhan47, BRRI dhan69, Binadhan-8, Binadhan-10, and Binadhan-17) on methane (CH4) emissions under two irrigation methods, i.e., alternate wetting and drying (AWD) and continuous flooding (CF). The treatments were laid out in a split-plot design, considering water regime as the main plots and rice variety as the sub-plots. The emission rates of CH4 were determined by collecting air samples using the closed chamber technique and measuring the concentrations using a gas chromatograph. CH4 emission rates varied with the growth and development of the rice varieties. The lowest cumulative CH4 emission rate was observed in Binadhan-17, particularly under AWD irrigation. Across the rice varieties, AWD irrigation significantly reduced the cumulative CH4 emissions by about 35% compared with CF. No significant variation in rice yield was observed between AWD (5.38 t ha−1) and CF (5.16 t ha−1). This study suggests that the cultivation of Binadhan-17 under AWD irrigation could be effective at reducing the carbon footprint of lowland rice fields.
Factors Influencing Customer Preference and Adoption of Electric Vehicles in India: A Journey towards More Sustainable Transportation
Authors: Chawla Udit , Mohnot Rajesh , Mishra Varsha , Singh Harsh Vikram , Singh Ayush Kumar
Published: April 2023

This study examines the impact of ecological awareness on Electric Vehicle (EV) acceptance and usage in light of the ecosystem advantages, and its changing focus from “traditionally perceived usefulness” to “green perceived usefulness”. The purpose of this study is to analyze public perceptions of autonomous driving and automotive tracking systems. Furthermore, it helps to comprehend why people adopt new technology and offers some recommendations for the global growth of EVs. We used factor analysis considering six distinct factors including Charging Time, Innovation, Perceived Quality, Perceived Affordability, Awareness, and Comfort. Our results indicate that elements including consumer loyalty, power efficiency, charging system, and consumer acceptance have a moderate effect, indicating that these factors do play an important role in influencing consumers’ behaviors when it comes to adopting EVs.
Assessment of Correction Methods Applied to BEMT for Predicting Performance of Horizontal-Axis Wind Turbines
Authors: Oliveira Hércules Araújo , de Matos José Gomes , Ribeiro Luiz Antonio de Souza , Saavedra Osvaldo Ronald , Vaz Jerson Rogério Pinheiro
Published: April 2023

Blade Element Momentum Theory (BEMT) is the most used method to design horizontal-axis wind turbines worldwide. This is because BEMT has a low computational cost and easy numerical implementation. Additionally, it is demonstrated in the literature that the prediction of output power using BEMT agrees well with experimental data. Another important feature of the BEMT is its applicability to small, medium, and large-sized turbines. However, BEMT models are usually implemented and adjusted for a specific power range turbine, and they are not applied in a more general form. Thus, this article presents an analysis of additional correction methods for tip and root losses, high values of the axial induction factor, and high angle of attack to better represent horizontal-axis turbines in terms of numerical stability. The approach has the intention of combining several complementary correction methods strategically inserted in the BEMT in order to compile an algorithm that is more general, stable, and workable for any turbine size. The main contribution of this work is to propose a stable BEMT numerical algorithm through the assessment of the combination of the correction methods available in the literature, i.e., classical and modern ones. The algorithm ensures applicability for small, medium, and large-sized wind turbines, as well as being fast and easy to implement in any computer and extendable even to turbines with a diffuser. This approach is validated by comparing the results with experimental data from four turbines of different power ranges (1.9 kW to 7.3 MW). The results show the best approximations for performance power curves against the measured values of all turbines. Moreover, it is effective, less complex, and quick in analyzing the performance of those turbines. Furthermore, the need for high-performance computers to analyze the performance of horizontal-axis turbines is avoided.
Why Gender Matters in Breeding: Lessons from Cooking Bananas in Uganda
Authors: Nasirumbi Sanya Losira , Ssali Reuben Tendo , Namuddu Mary Gorreth , Kyotalimye Miriam , Marimo Pricilla , Mayanja Sarah
Published: April 2023

This study examined the gender-differentiated trait preferences of cooking banana (matooke) for farmers and consumers in Central Uganda to inform banana-breeding strategies. Women and men banana farmers might have differing production objectives, norms, and values which drive decisions on which varieties to adopt and grow. However, breeders rarely consider this in their variety development programs, leading to lost opportunities for equitable breeding. An exploratory sequential mixed-method approach was used to obtain a richer understanding of the trait preferences of women and men, which explains the acceptability of cooking bananas. Consumer preference tests for the candidate banana varieties and released hybrids were also conducted. The results showed that the universal attributes for variety selection were bunch size, taste, resistance to pests and diseases, drought tolerance, food texture/softness, maturity period, and finger size. Men appreciated agronomic and market-related traits, such as tolerance to drought and poor soils, bunch size and compactness, maturity period, and shelf life, while women valued processing and cooking traits such as flavour, food colour, ease of peeling, finger size, and agronomic traits such as plant height. These are plausible attributes for the gender-responsive breeding of bananas. The findings highlight the need to redesign the banana-breeding pipeline and process in Uganda to deliver varieties with attributes desired by women and men along this commodity value chain. A participatory demand-driven and gender-responsive process involving stepwise selection criteria that commences with quality traits followed by production traits while integrating gender-specific preferences should be employed to ensure the acceptability of cooking banana hybrids by women and men end users. This requires integrating different disciplines, including social scientists and gender experts, along the entire breeding process for more inclusive products and equitable outcomes.
Understanding Smart City Practice in Urban China: A Governance Perspective
Authors: Han Yan , Cai Jianming , Ma Enpu , Du Shanshan , Lin Jing
Published: April 2023

Through an evolution from an emerging marketing narrative to a geographical fact around the globe, smart city is increasingly understood as a city’s effort to make itself smart. There seems no single city in the world to be commonly recognized as a real smart city yet, albeit many cities have already tried hard in this missionary commitment. Yet some common features can still be seen and identified, particularly from the urban governance perspective. This article explores the practice of smart city construction in China through a lens of governance by observing the interactive involvement of key stakeholders in the process. By taking three cities (Hangzhou, Wuhan, and Shanghai) in China as study cases, a conceptual framework is established in which three sets of actors, i.e., ICT-related enterprises, government, and civil society, and, accordingly, three types of approaches, i.e., ICT-led, planning-led, and place-making-and-community-oriented, are identified. It is found that the evolution of smart city construction rather follows a nonlinear trajectory and is very dependent on whether or not the primary actors and related stakeholders can form an affirmative acting power in triggering the city’s implementation. In other words, there is no “one-size-fits-all” approach to smart city construction. Each city may have its specialization in smartness based on awareness of and respecting its unique existing setting. The empirical study also shows that smart city construction tends to be converged in recognition that the core of smart city is not the smartness of technology but the smartness of all institutions and people enabled to utilize smart tools properly and efficiently in pursuit of people’s well-being, institutional capacity building, and better spatial arrangement towards a sustainable, resilient, and inclusive city in and for the future. From a geographical perspective, that is how to build a smart urban space to make the city a better place to not just accommodate but facilitate and meet people’s increasing demand for a better life in their living places.