bluuebunny/crossref_metadata_2025 huggingface dataset:
Soy, Rice and Oat Drinks: Investigating Chemical and Biological Safety in Plant-Based Milk Alternatives
Authors: Giugliano Roberta , Musolino Noemi , Ciccotelli Valentina , Ferraris Carla , Savio Valentina , Vivaldi Barbara , Ercolini Carlo , Bianchi Daniela Manila , Decastelli Lucia
Published: May 2023

During the last decades, plant-based milk has become very appreciated by consumers, becoming a staple ingredient, especially for alternative breakfasts. Milk contains lactose, which is a sugar hydrolysed by the lactase enzyme. Lactose intolerance and lactose malabsorption are very common food intolerances among individuals. However, a lot of consumers consider themselves as lactose intolerant on the basis of self-reported intolerance and start to avoid dairy products, ignoring that plant-based milk alternatives are not nutritionally comparable to animal milk, especially in terms of protein intake. The aim of this study is to grow folder knowledge of the security of plant-based drinks, helping competent authorities to issue a risk assessment and to apply national plans about consumer safety. Results show that proper sanitary practices, such as pasteurization, are necessary in plant-based milk alternatives as well as in dairy milk. Chemical analysis has highlighted that there are no pesticide risks for consumers.
Eight-Hour Time-Restricted Feeding: A Strong Candidate Diet Protocol for First-Line Therapy in Polycystic Ovary Syndrome
Authors: Feyzioglu Bihter Senem , Güven Cenk Mustafa , Avul Zerrin
Published: May 2023

We aimed to investigate the effects of a 6-week program of 8 h time-restricted feeding (TRF) diet in polycystic ovary syndrome (PCOS), as determined by anthropometric, hormonal, metabolic profiles, and fecal calprotectin level. Thirty women diagnosed with PCOS underwent a 6-week 8 h TRF diet intervention. Age, anthropometric features (body mass index (BMI), waist-to-hip ratio (WHR)) and biochemical results were recorded. Free androgen index (FAI, defining hyperandrogenism) and the homeostatic model assessment-insulin resistance (HOMA-IR) were calculated. Baseline (pre-diet) and 6-week post-diet findings were compared. Mean age was 25.57 ± 2.67 years. BMI (p < 0.001) and WHR (p = 0.001) were found to have significantly decreased after the diet, as well as the percentage of patients defined to have hyperandrogenism (p = 0.016). Reproductive hormone levels, FAI (p < 0.001) and HOMA-IR (p < 0.001) were improved significantly. Metabolic parameters associated with glucose and lipid profiles were also significantly improved after the diet. Additionally, fecal calprotectin levels demonstrated a significant decrease from pre-diet to post-diet (p < 0.001). In conclusion, a 6-week diet intervention with 8 h TRF may be a suitable and effective intermittent fasting protocol that can be used as a first-line option in PCOS.
Iron Deficiency and Iron Deficiency Anemia in Women with and without Obesity: NHANES 2001–2006
Authors: Aguree Sixtus , Owora Arthur , Hawkins Misty , Reddy Manju B.
Published: May 2023

Obesity has been linked to numerous health and nutritional problems, including impaired iron metabolism, a common cause of anemia. We aimed to determine the prevalence of anemia, iron deficiency (ID), and iron deficiency anemia (IDA) among women aged 20–49 years based on body mass index (BMI) status. We used measures of iron status and body mass index from the 2001–2006 National Health and Nutrition Examination Survey (NHANES). Mean serum ferritin, erythrocyte protoporphyrin, and soluble transferrin receptor were higher, while those of serum iron, percent transferrin saturation, and mean cell volume (MCV) were lower in women with obesity than those with normal weight (all p < 0.016). ID based on the ferritin model was 12.5 ± 1.0% vs. 22.9 ± 1.6% (p < 0.001); 9.0 ± 0.9% vs. 20.0 ± 1.3% (p < 0.001) based on the MCV model; and 8.1 ± 1.0% vs. 10.5 ± 1.2% (p > 0.05) based on the BII model for women with normal weight and women with obesity, respectively. Anemia prevalence was 5.5 ± 0.8% (normal) vs. 9.3 ± 1.0% (obese) (p = 0.005). The IDA estimates based on the ferritin and MCV models were similar but higher than that from the BII model (p < 0.001). Generally, the prevalence rates of ID and anemia (and IDA) were higher for women with obesity, but the method used to define deficiency mattered. The choice of iron indices is important for estimating ID and IDA in populations with obesity.
The van der Waals Hexaquark Chemical Potential in Dense Stellar Matter
Authors: Andrew Keith , Steinfelds Eric V. , Andrew Kristopher A.
Published: May 2023

We explore the chemical potential of a QCD-motivated van der Waals (VDW) phase change model for the six-quark color-singlet, strangeness S = −2 particle known as the hexaquark with quark content (uuddss). The hexaquark may have internal structure, indicated by short range correlations that allow for non-color-singlet diquark and triquark configurations whose interactions will change the magnitude of the chemical potential. In the multicomponent VDW Equation of State (EoS), the quark-quark particle interaction terms are sensitive to the QCD color factor, causing the pairing of these terms to give different interaction strengths for their respective contributions to the chemical potential. This results in a critical temperature near 163 MeV for the color-singlet states and tens of MeV below this for various mixed diquark and triquark states. The VDW chemical potential is also sensitive to the number density, leading to chemical potential isotherms that exhibit spinodal extrema, which also depend upon the internal hexaquark configurations. These extrema determine regions of metastability for the mixed states near the critical point. We use this chemical potential with the chemical potential-modified TOV equations to investigate the properties of hexaquark formation in cold compact stellar cores in beta equilibrium. We find thresholds for hexaquark layers and changes in maximum mass values that are consistent with observations from high mass compact stellar objects such as PSR 09043 + 10 and GW 190814. In general, we find that the VDW-TOV model has an upper stability mass and radius bound for a chemical potential of 1340 MeV with a compactness of C~0.2.
RMAFF-PSN: A Residual Multi-Scale Attention Feature Fusion Photometric Stereo Network
Authors: Luo Kai , Ju Yakun , Qi Lin , Wang Kaixuan , Dong Junyu
Published: May 2023

Predicting accurate normal maps of objects from two-dimensional images in regions of complex structure and spatial material variations is challenging using photometric stereo methods due to the influence of surface reflection properties caused by variations in object geometry and surface materials. To address this issue, we propose a photometric stereo network called a RMAFF-PSN that uses residual multiscale attentional feature fusion to handle the “difficult” regions of the object. Unlike previous approaches that only use stacked convolutional layers to extract deep features from the input image, our method integrates feature information from different resolution stages and scales of the image. This approach preserves more physical information, such as texture and geometry of the object in complex regions, through shallow-deep stage feature extraction, double branching enhancement, and attention optimization. To test the network structure under real-world conditions, we propose a new real dataset called Simple PS data, which contains multiple objects with varying structures and materials. Experimental results on a publicly available benchmark dataset demonstrate that our method outperforms most existing calibrated photometric stereo methods for the same number of input images, especially in the case of highly non-convex object structures. Our method also obtains good results under sparse lighting conditions.
Extreme Refractive-, Diffractive- and Hybrid-Hyperchromats: Minimizing the Equivalent Abbe Number of a Two-Lens System
Authors: Werner Lukas , Förster Erik , Kraus Matthias , Hillmer Hartmut , Brunner Robert
Published: May 2023

This work provides a comprehensive analysis of the maximum chromatic axial split of two-element hyperchromats, with the distance between the two lenses being a key variable. Purely refractive and diffractive systems are considered, as well as hybrid layouts combining refractive and diffractive elements. In order to achieve extreme chromatic axial splitting and accordingly a minimum equivalent Abbe number for lens combinations, a three-step procedure was used. In the first paraxial step, purely optical quantities such as focal lengths of the lenses, inter-lens distances and dispersion properties of the lenses were investigated. In the second step, which also takes place in the paraxial domain, additional geometric boundary conditions such as the radii, diameters and thicknesses of the lenses are taken into account. The results of this step serve as an input for the final optimization using optical design software, which derives practical solutions for minimum equivalent Abbe numbers with diffraction-limited image quality. As a significant result, the comparison with directly cemented lens doublets shows that the introduction of a distance between the elements allows for a much stronger chromatic decomposition for refractive, diffractive and also hybrid combinations. Quantitatively, the minimum equivalent Abbe number for refractive systems is reduced from 2.5 (without spacing) to 1.79 (with spacing). For hybrid combinations, a corresponding reduction from 0.4 to 0.29 is achieved.
Blue Light and Eye Damage: A Review on the Impact of Digital Device Emissions
Authors: Hipólito Vladimiro , Coelho João M. P.
Published: May 2023

The pandemic and lockdown caused by COVID-19 accelerated digitalization. Personal digital devices, emitting high-energy light, namely in the blue wavelength, have raised concerns about possible harmful effects on users’ eyes. Scientific research history has shown a relationship between exposure to blue light and changes in ocular structures. The main goal of this review is to examine frequent and prolonged exposure to blue radiation from computers, tablets and smartphones and its consequences on vision and ocular structures. Bibliographic research was carried out on changes induced by blue light in ocular structures, the cornea, the crystalline lens and the retina based on the following scientific databases: BioOne Complete™; Google Scholar™; Paperity™; PubMed™; and ScienceOpen™. The most significant studies on blue light and ocular damage were selected and reviewed. The most relevant bibliographic data were analyzed and summarized and some gaps in the theme of blue light from digital devices were identified. The experimental need to acquire additional new data is suggested. The hypothesis that continued use of digital devices enriched with blue light may interfere with the biological tissues of the cornea, crystalline lens, or retina is not clarified in the available scientific evidence. Therefore, additional studies are needed to answer this problem.
Multi-User Nonlinear Optical Cryptosystem Based on Polar Decomposition and Fractional Vortex Speckle Patterns
Authors: Mandapati Vinny Cris , Vardhan Harsh , Prabhakar Shashi , Sakshi  , Kumar Ravi , Reddy Salla Gangi , Singh Ravindra P. , Singh Kehar
Published: May 2023

In this paper, we propose a new multiuser nonlinear optical cryptosystem using fractional-order vortex speckle (FOVS) patterns as security keys. In conventional optical cryptosystems, mostly random phase masks are used as the security keys which are prone to various attacks such as brute force attack. In the current study, the FOVSs are generated optically by the scattering of the fractional-order vortex beam, known for azimuthal phase and helical wavefronts, through a ground glass diffuser. FOVSs have a remarkable property that makes them almost impossible to replicate. In the input plane, the amplitude image is first phase encoded and then modulated with the FOVS phase mask to obtain the complex image. This complex image is further processed to obtain the encrypted image using the proposed method. Two private security keys are obtained through polar decomposition which enables the multi-user capability in the cryptosystem. The robustness of the proposed method is tested against existing attacks such as the contamination attack and known-plaintext attack. Numerical simulations confirm the validity and feasibility of the proposed method.
Evaluation of Cowpea Landraces under a Mediterranean Climate
Authors: Lazaridi Efstathia , Bebeli Penelope J.
Published: May 2023

Cowpea (Vigna unguiculata (L.) Walp.) yield is strongly influenced by environmental conditions. Average seed yield can decrease to a great extent when drought conditions occur, especially when they prevail during flowering and seed filling periods. Identifying genotypes presenting yield stability is one of the most important breeding goals. Local varieties or crop landraces are genetic resources that, despite exhibiting intermediate yield production capacity, present high yield stability in low-input cropping systems. The objective of this study was therefore to evaluate five selected cowpea landraces originated from different Greek islands under Mediterranean climatic conditions. A complete randomized block design with four replications was used during three consecutive cropping seasons. Many phenological and agronomic traits studied showed statistically significant genotype × experimental year interaction, while there was a strong experimental year effect. Among the landraces studied, local population VG23 from Kythira Island was the most productive under the experimental climatic and soil conditions, while local population VG2 from Lemnos Island was characterized by low seed productivity. Conclusively, our study showed that VG23 landrace is a promising genetic material to be used for seed yield improvement.
Pedestrian Smartphone Navigation Based on Weighted Graph Factor Optimization Utilizing GPS/BDS Multi-Constellation
Authors: Chen Chen , Zhu Jianliang , Bo Yuming , Chen Yuwei , Jiang Changhui , Jia Jianxin , Duan Zhiyong , Karjalainen Mika , Hyyppä Juha
Published: May 2023

Many studies have focused on the smartphone-based global navigation satellite system (GNSS) for its portability. However, complex urban environments, such as urban canyons and tunnels, can easily interfere with GNSS signal qualities. Current smartphone-based positioning technologies using the GNSS signal still pose great challenges. Since the last satellite of the BeiDou navigation system (BDS) was successfully launched on 23 June 2020, it is possible to use a low-cost Android device to realize the localization based on the BDS signals worldwide. This research focuses on smartphone-based outdoor pedestrian navigation utilizing the GPS/BDS multi-constellation system. To improve the localization accuracy, we proposed the Weighted Factor Graph Optimization localization model (W-FGO). In this paper, firstly, we evaluate the signal qualities of the BDS via the data collected by the static experiment. Then, we structure the cost function based on the pseudo-range and the time series data for the traditional Factor Graph Optimization (FGO). Finally, we design the weight model based on the signal quality of each satellite and the time fading factor to further improve the localization accuracy of the conventional FGO method. An Android smartphone is utilized to collect the GNSS data for the evaluation and the localization. The experiment results demonstrate the superior performance of the proposed method.
Improved Spectral Detection of Nitrogen Deficiency and Yellow Mosaic Disease Stresses in Wheat Using a Soil Effect Removal Algorithm and Machine Learning
Authors: Feng Ziheng , Zhang Haiyan , Duan Jianzhao , He Li , Yuan Xinru , Gao Yuezhi , Liu Wandai , Li Xiao , Feng Wei
Published: May 2023

Wheat yellow mosaic disease is a low-temperature and soil-borne disease. Crop infection by the yellow mosaic virus can lead to severe yield and economic losses. It is easily confused with nitrogen deficiency based on the plant’s morphological characteristics. Timely disease detection and crop management in the field require the precise identification of crop stress types. However, the detection of crop stress is often underappreciated. Wheat nitrogen deficiency and yellow mosaic disease were investigated in the field and wheat physiological and biochemical experiments were conducted to collect agronomic indicators, four years of reflectance spectral data at green-up and jointing were collected, and then studies for the detection of nitrogen deficiency and yellow mosaic disease stresses were carried out. The continuous removal (CR), first-order derivative (FD), standard normal variate (SNV), and spectral separation of soil and vegetation (3SV) preprocessing methods and 96 spectral indices were evaluated. The threshold method and variance inflation factor (TVIF) were used as feature selection methods combined with machine learning to develop a crop stress detection method. The results show that the most sensitive wavelengths are found in the 725–1000 nm region, while the sensitivity of the spectrum in the 400–725 nm region is lower. The PRI670,570, B, and RARSa spectral indices can detect nitrogen deficiency and yellow leaf disease stress, and the OA and Kappa values are 93.87% and 0.873, respectively, for PRI670,570, which is the best index. A 3SV-TVIF-SVM stress detection method was then proposed, using OA and Kappa values of 96.97% and 0.931, respectively, for field data validation. The results of the study can provide technical support and a theoretical basis for the accurate control of yellow mosaic disease and nitrogen fertilizer management in the field.
Two-Lane DNN Equalizer Using Balanced Random-Oversampling for W-Band PS-16QAM RoF Delivery over 4.6 km
Authors: Xu Sicong , Sang Bohan , Zeng Lingchuan , Zhao Li
Published: May 2023

For W-band long-range mm-wave wireless transmission systems, nonlinearity issues resulting from photoelectric devices, optical fibers, and wireless power amplifiers can be handled by deep learning equalization algorithms. In addition, the PS technique is considered an effective measure to further increase the capacity of the modulation-constraint channel. However, since the probabilistic distribution of m-QAM varies with the amplitude, there have been difficulties in learning valuable information from the minority class. This limits the benefit of nonlinear equalization. To overcome the imbalanced machine learning problem, we propose a novel two-lane DNN (TLD) equalizer using the random oversampling (ROS) technique in this paper. The combination of PS at the transmitter and ROS at the receiver improved the overall performance of the W-band wireless transmission system, and our 4.6-km ROF delivery experiment verified its effectiveness for the W-band mm-wave PS-16QAM system. Based on our proposed equalization scheme, we achieved single-channel 10-Gbaud W-band PS-16QAM wireless transmission over a 100 m optical fiber link and a 4.6 km wireless air-free distance. The results show that compared with the typical TLD without ROS, the TLD-ROS can improve the receiver‘s sensitivity by 1 dB. Furthermore, a reduction of 45.6% in complexity was achieved, and we were able to reduce training samples by 15.5%. Considering the actual wireless physical layer and its requirements, there is much to be gained from the joint use of deep learning and balanced data pre-processing techniques.
An Efficient Compressive Sensing Event-Detection Scheme for Internet of Things System Based on Sparse-Graph Codes
Authors: Cai Jun , Xu Xin , Zhu Hongpeng , Cheng Jian
Published: May 2023

This work studied the event-detection problem in an Internet of Things (IoT) system, where a group of sensor nodes are placed in the region of interest to capture sparse active event sources. Using compressive sensing (CS), the event-detection problem is modeled as recovering the high-dimensional integer-valued sparse signal from incomplete linear measurements. We show that the sensing process in IoT system produces an equivalent integer CS using sparse graph codes at the sink node, for which one can devise a simple deterministic construction of a sparse measurement matrix and an efficient integer-valued signal recovery algorithm. We validated the determined measurement matrix, uniquely determined the signal coefficients, and performed an asymptotic analysis to examine the performance of the proposed approach, namely event detection with integer sum peeling (ISP), with the density evolution method. Simulation results show that the proposed ISP approach achieves a significantly higher performance compared to existing literature at various simulation scenario and match that of the theoretical results.
Feed Conversion Ratio (FCR) and Performance Group Estimation Based on Predicted Feed Intake for the Optimisation of Beef Production
Authors: Davison Chris , Michie Craig , Tachtatzis Christos , Andonovic Ivan , Bowen Jenna , Duthie Carol-Anne
Published: May 2023

This paper reports on the use of estimates of individual animal feed intake (made using time spent feeding measurements) to predict the Feed Conversion Ratio (FCR), a measure of the amount of feed consumed to produce 1 kg of body mass, for an individual animal. Reported research to date has evaluated the ability of statistical methods to predict daily feed intake based on measurements of time spent feeding measured using electronic feeding systems. The study collated data of the time spent eating for 80 beef animals over a 56-day period as the basis for the prediction of feed intake. A Support Vector Regression (SVR) model was trained to predict feed intake and the performance of the approach was quantified. Here, feed intake predictions are used to estimate individual FCR and use this information to categorise animals into three groups based on the estimated Feed Conversion Ratio value. Results provide evidence of the feasibility of utilising the ‘time spent eating’ data to estimate feed intake and in turn Feed Conversion Ratio (FCR), the latter providing insights that guide farmer decisions on the optimisation of production costs.
Model and Methodology to Characterize Phosphor-Based White LED Visible Light Communication Links
Authors: Salvador Pau , Almenar Vicenç , Corral Juan Luis , Valls Javier , Canet Maria Jose
Published: May 2023

LED lighting has become the standard solution for illumination purposes thanks to its energy efficiency. Nowadays, there is growing interest in the use of LEDs for data transmission to develop future-generation communication systems. The low cost and widespread deployment of phosphor-based white LEDs make them the best candidate for visible light communications (VLC), although they have a limited modulation bandwidth. This paper presents a simulation model of a VLC link based on phosphor-based white LEDs and a method to characterize the VLC setup used to perform the data transmission experiments. Specifically, the simulation model incorporates the frequency response of the LED, the noise levels coming from the lighting source and the acquisition electronics, and the attenuation due to both the propagation channel and the angular misalignment between the lighting source and the photoreceiver. In order to validate the suitability of the model for VLC, carrierless amplitude phase (CAP) and orthogonal frequency division multiplexing (OFDM) modulation signals were employed for data transmission, and simulations with the proposed model and measurements over the equivalent scenario show high agreement.
The Convenience of Polydopamine in Designing SERS Biosensors with a Sustainable Prospect for Medical Application
Authors: Tian Lulu , Chen Cong , Gong Jing , Han Qi , Shi Yujia , Li Meiqi , Cheng Liang , Wang Lin , Dong Biao
Published: May 2023

Polydopamine (PDA) is a multifunctional biomimetic material that is friendly to biological organisms and the environment, and surface-enhanced Raman scattering (SERS) sensors have the potential to be reused. Inspired by these two factors, this review summarizes examples of PDA-modified materials at the micron or nanoscale to provide suggestions for designing intelligent and sustainable SERS biosensors that can quickly and accurately monitor disease progression. Undoubtedly, PDA is a kind of double-sided adhesive, introducing various desired metals, Raman signal molecules, recognition components, and diverse sensing platforms to enhance the sensitivity, specificity, repeatability, and practicality of SERS sensors. Particularly, core-shell and chain-like structures could be constructed by PDA facilely, and then combined with microfluidic chips, microarrays, and lateral flow assays to provide excellent references. In addition, PDA membranes with special patterns, and hydrophobic and strong mechanical properties can be used as independent platforms to carry SERS substances. As an organic semiconductor material capable of facilitating charge transfer, PDA may possess the potential for chemical enhancement in SERS. In-depth research on the properties of PDA will be helpful for the development of multi-mode sensing and the integration of diagnosis and treatment.
A Predictable Obstacle Avoidance Model Based on Geometric Configuration of Redundant Manipulators for Motion Planning
Authors: Ju Fengjia , Jin Hongzhe , Wang Binluan , Zhao Jie
Published: May 2023

When a manipulator works in dynamic environments, it may be affected by obstacles and may cause danger to people around. This requires the manipulator to be able to plan the obstacle avoidance motion in real time. Therefore, the problem solved in this paper is dynamic obstacle avoidance with the whole body of the redundant manipulator. The difficulty of this problem is how to model the manipulator to reflect the motion relationship between the manipulator and the obstacle. In order to describe accurately the occurrence conditions of the collision, we propose the triangular collision plane, a predictable obstacle avoidance model based on the geometric configuration of the manipulator. Based on this model, three cost functions, including the cost of the motion state, the cost of a head-on collision, and the cost of the approach time, are established and regarded as optimization objectives in the inverse kinematics solution of the redundant manipulator combined with the gradient projection method. The simulations and experiments on the redundant manipulator and the comparison with the distance-based obstacle avoidance point method show that our method improves the response speed of the manipulator and the safety of the system.
On the Challenges of Acoustic Energy Mapping Using a WASN: Synchronization and Audio Capture
Authors: García-Unzueta Emiliano Ehecatl , Mendez-Monroy Paul Erick , Rascon Caleb
Published: May 2023

Acoustic energy mapping provides the functionality to obtain characteristics of acoustic sources, as: presence, localization, type and trajectory of sound sources. Several beamforming-based techniques can be used for this purpose. However, they rely on the difference of arrival times of the signal at each capture node (or microphone), so it is of major importance to have synchronized multi-channel recordings. A Wireless Acoustic Sensor Network (WASN) can be very practical to install when used for mapping the acoustic energy of a given acoustic environment. However, they are known for having low synchronization between the recordings from each node. The objective of this paper is to characterize the impact of current popular synchronization methodologies as part of the WASN to capture reliable data to be used for acoustic energy mapping. The two evaluated synchronization protocols are: Network Time Protocol (NTP) y Precision Time Protocol (PTP). Additionally, three different audio capture methodologies were proposed for the WASN to capture the acoustic signal: two of them, recording the data locally and one sending the data through a local wireless network. As a real-life evaluation scenario, a WASN was built using nodes conformed by a Raspberry Pi 4B+ with a single MEMS microphone. Experimental results demonstrate that the most reliable methodology is using the PTP synchronization protocol and audio recording locally.
Weakly Hard Real-Time Model for Control Systems: A Survey
Authors: Salamun Karla , Pavić Ivan , Džapo Hrvoje , Čuljak Ivana
Published: May 2023

The concept of weakly hard real-time systems can be used to model real-time systems that may tolerate occasional deadline misses in a bounded and predictable manner. This model applies to many practical applications and is particularly interesting in the context of real-time control systems. In practice, applying hard real-time constraints may be too rigid since a certain amount of deadline misses is acceptable in some applications. In order to maintain system stability, limitations on the amount and distribution of violated deadlines need to be imposed. These limitations can be formally expressed as weakly hard real-time constraints. Current research in the field of weakly hard real-time task scheduling is focused on designing scheduling algorithms that guarantee the fulfillment of constraints, while aiming to maximize the total number of timely completed task instances. This paper provides an extensive literature review of the work related to the weakly hard real-time system model and its link to the field of control systems design. The weakly hard real-time system model and the corresponding scheduling problem are described. Furthermore, an overview of system models derived from the generalized weakly hard real-time system model is provided, with an emphasis on models that apply to real-time control systems. The state-of-the-art algorithms for scheduling tasks with weakly hard real-time constraints are described and compared. Finally, an overview of controller design methods that rely on the weakly hard real-time model is given.
Prediction of Diabetes Mellitus Progression Using Supervised Machine Learning
Authors: Chauhan Apoorva S. , Varre Mathew S. , Izuora Kenneth , Trabia Mohamed B. , Dufek Janet S.
Published: May 2023

Diabetic peripheral neuropathy (DN) is a serious complication of diabetes mellitus (DM) that can lead to foot ulceration and eventual amputation if not treated properly. Therefore, detecting DN early is important. This study presents an approach for diagnosing various stages of the progression of DM in lower extremities using machine learning to classify individuals with prediabetes (PD; n = 19), diabetes without (D; n = 62), and diabetes with peripheral neuropathy (DN; n = 29) based on dynamic pressure distribution collected using pressure-measuring insoles. Dynamic plantar pressure measurements were recorded bilaterally (60 Hz) for several steps during the support phase of walking while participants walked at self-selected speeds over a straight path. Pressure data were grouped and divided into three plantar regions: rearfoot, midfoot, and forefoot. For each region, peak plantar pressure, peak pressure gradient, and pressure–time integral were calculated. A variety of supervised machine learning algorithms were used to assess the performance of models trained using different combinations of pressure and non-pressure features to predict diagnoses. The effects of choosing various subsets of these features on the model’s accuracy were also considered. The best performing models produced accuracies between 94–100%, showing the proposed approach can be used to augment current diagnostic methods.
The Metaverse as a Virtual Model of Platform Urbanism: Its Converging AIoT, XReality, Neurotech, and Nanobiotech and Their Applications, Challenges, and Risks
Authors: Bibri Simon Elias
Published: May 2023

With their exponentially rising computational power, digital platforms are heralding a new era of hybrid intelligence. There has recently been much enthusiasm and hype that the Metaverse has the potential to unlock hybrid intelligence. This is premised on the idea that the Metaverse represents an applied convergence of Artificial Intelligence of Things (AIoT) and Extended Reality (XR) that intersects with urbanism in terms of the distinctive features of platform-mediated everyday life experiences in cities. However, social interaction and its resulting social organization in the Metaverse are mediated and governed by algorithms and thus submitted to—a dream of—complete logical ordering. This raises a plethora of concerns related to the systemic collection and algorithmic processing of users’ personal, brain, and biometric data, i.e., profound societal—and the hardest to predict ethical—implications. Therefore, this study analyzes and synthesizes a large body of scientific literature on the unfolding convergence of AIoT and XR technologies, neurotechnology, and nanobiotechnology in the realm of the Metaverse in order to derive a novel conceptual framework for the Metaverse as an envisioned virtual model of platform urbanism. Further, it examines the key challenges and risks of these converging technologies in relation to the Metaverse and beyond. This study employs thematic analysis and synthesis to cope with multidisciplinary literature. The analysis identifies seven themes: (1) Platformization, (2) platform urbanism, (3) virtual urbanism, (4) XR technologies, (5) AIoT technologies, (6) neurotechnology, and (7) nanobiotechnology. The synthesized evidence reveals that, while neurotechnology and nanobiotechnology have numerous benefits and promising prospects, they raise contentions and controversies stemming from their potential use to inflict harm to human users—if left unchecked—through the black box of the algorithmic mediation underpinning the Metaverse. The findings serve to steer the Metaverse to contribute to human flourishing and wellbeing by adhering to and upholding ethical principles as well as leveraging its underlying disruptive technologies in meaningful ways. They also aid scholars, practitioners, and policymakers in assessing the pros and cons of these technologies, especially their inevitable ramifications.
Posttraumatic Growth and Resilience on Conflict-Related Sexual Violence: A Set of Systematic Reviews of Literature
Authors: Botero-García Carolina , Rocha Daniela , Rodríguez María Alejandra , Rozo Ana María
Published: May 2023

Sexual violence is highly prevalent in sociopolitical conflict contexts. Even though its negative effects are well documented, further research is needed on how community experiences of social growth and rebuilding could positively impact victims of sexual violence in these contexts. As a starting point, we conducted a two-phase systematic review. The first phase focused on the relationships between sociopolitical conflict, sexual violence, and psychological effects or trauma (2010–2017), and, in addition to the deep negative psychological effects, it also found reports of posttraumatic growth in victims. This led to a second phase that related sexual violence in sociopolitical conflict contexts to posttraumatic growth and resilience (2017–2022). We found nine publications documenting experiences of resilience and posttraumatic growth in victims of sexual violence in sociopolitical conflicts. Interestingly, resilience and posttraumatic growth were shown not only in victims but also in communities and new generations, which is relevant to understanding the long-lasting effects of violence in contexts of sociopolitical conflict.
Factors Affecting Taiwanese Consumers’ Intention to Purchase Abnormally Shaped Produce
Authors: Su Yen-Lun , Ngamsom Pongsakorn , Wang Jen-Hung
Published: May 2023

This study examines the effects of produce shape abnormality, organic labeling, and discounts on consumers’ intention to purchase produce. Two studies were conducted. In Study 1, a 3 (normal, moderate, and extreme shape abnormality) × 2 (with and without organic labeling) between-subjects design was used. In Study 2, a 2 (moderate and extreme shape abnormality) × 5 (discount: 30%, 40%, 50%, 60%, and 70%) between-subjects design was used. A total of 480 valid responses to questionnaires were collected. Study 1 revealed that the interaction between produce shape abnormality and organic labeling significantly affects purchase intention. Study 2 revealed that the interaction between produce shape abnormality and discount significantly affected purchase intentions. For a 30% discount, the results indicate no difference in intention to purchase moderately or extremely abnormally shaped produce. For 40%, 50%, 60%, and 70% discounts, intention to purchase moderately abnormally shaped produce was stronger than that for extremely abnormally shaped produce. This study discusses the implications of the findings, limitations, and recommendations for future research.
Embedded Hybrid Model (CNN–ML) for Fault Diagnosis of Photovoltaic Modules Using Thermographic Images
Authors: Benghanem Mohamed , Mellit Adel , Moussaoui Chourouk
Published: May 2023

In this paper, a novel hybrid model for the fault diagnosis of photovoltaic (PV) modules was developed. The model combines a convolutional neural network (CNN) with a machine learning (ML) algorithm. A total of seven defects were considered in this study: sand accumulated on PV modules, covered PV modules, cracked PV modules, degradation, dirty PV modules, short-circuited PV modules, and overheated bypass diodes. First, the hybrid CNN–ML has been developed to classify the seven common defects that occur in PV modules. Second, the developed model has been then optimized. Third, the optimized model has been implemented into a microprocessor (Raspberry Pi 4) for real-time application. Finally, a friendly graphical user interface (GUI) has been designed to help users analyze their PV modules. The proposed hybrid model was extensively evaluated by a comprehensive database collected from three regions with different climatic conditions (Mediterranean, arid, and semi-arid climates). Experimental tests showed the feasibility of such an embedded solution in the diagnosis of PV modules. A comparative study with the state-of-the-art models and our model has been also presented in this paper.
Socio-Professional Implications of Sports Events: A Perspective from Dual-Career Students
Authors: Buhaș Raluca , Ilieș Alexandru , Săveanu Sorana , Szabo-Alexi Paul , Szabo-Alexi Mariana , Buhaș Sorin
Published: May 2023

Background: The organization of a sports event can be analyzed from the perspective of its impact on the participants, organizers and community. University championships have a sustainable character, with several tournaments being planned over time, receiving increased interest from all stakeholders. Methods: This research aimed to describe aspects regarding the organization and planning of sports events, the academic and professional profiles of student-athletes and the implications of their participation in championships. We used two research methods: one based on geography, and another based on a sociological survey of 139 dual-career students participating in the national university championship of men’s football and women’s volleyball organized by the University of Oradea (Romania). Results: The research results show that academic studies provide professional competencies, while participation in sports events contributes to students’ personal and professional development. The results highlight that dual-career students are more prone to develop their sports careers; therefore, participation in these types of events represents a milestone in their careers. Conclusions: Our study can be considered when organizing these types of sports events and can provide directions for the development of sustainable strategies and programs to support students with dual careers.
Factors Influencing Game-Based Learning in the Colombian Context: A Mixed Methods Study
Authors: Aguilar-Cruz Paola Julie , Wang Peiyu , Xiang Zongping , Luo Heng
Published: May 2023

Game-based learning (GBL) places high demand on educational resources and has been widely practiced in classrooms in many developed countries; however, few studies on GBL and its influencing factors have been conducted in developing countries. To address this research gap, a mixed-methods study was conducted in a state high school in the Amazon region of Colombia with 64 tenth-graders who were learning English as a foreign language to identify the factors that affect learners’ learning outcomes when serious games are applied to vocabulary learning, with a specific focus on learning engagement. This study drew on both quantitative and qualitative data collected from surveys, interviews, and pre- and post-tests. The results showed that engagement and prior knowledge can positively predict GBL outcomes, while contextual factors and family condition had an adverse impact on GBL outcomes (Adjusted R2 = 0.635, p < 0.01). The results also indicated that a male student with a higher level of prior knowledge would be more likely to achieve good grades in GBL. Based on the study results, several implications are proposed for incorporating serious games for vocabulary learning in less-developed regions. This study results provide important practical implications for high schools in developing countries to implementing GBL.
Experimental Investigations on the Tensile Mechanical Behavior of HDPE Geocell Strip
Authors: Zuo Zheng , Hao Xiuqiang , Li Huiqiang , Wang Wei , Yang Guangqing , Liu Ying
Published: May 2023

Geocells are commonly adopted in various engineering constructions, such as railways and ports. Currently, the reinforcement effects and mechanisms of geocells in engineering is being widely studied, while limited studies have been performed on the mechanical behavior of geocell strips. Uncertainties regarding their performance have impeded the wide application of geocells in engineering fields. In this paper, a series of tensile tests and trapezoidal tests were performed on high-density polyethylene (HDPE) geocell strips. The effects regarding specimen shape, specimen width, and welding junction on the tensile mechanical behavior of HDPE geocell strips were investigated. Additionally, the results of the tensile test and trapezoidal test were also compared. The test results showed that the tensile strength of a HDPE geocell strip was less affected by the specimen shape and specimen width, within 5%. However, the elongation of HDPE strips was sensitive to the specimen shape, and the difference between type I dumbbell and type II rectangular was up to 38%. The effect of the welding junction on the HDPE strip cannot be ignored, the strength retention rate of the welding junction was 76.3%. The curve of the trapezoidal test was similar to that of the tensile test, and the force of trapezoidal test was 0.87 times that of the tensile test. The test results can provide a reference for the testing of strip performance and structural design.
New Horizons in Bank Mergers: A Quantum Spherical Fuzzy Decision-Making Framework for Analyzing Islamic and Conventional Bank Mergers and Enhancing Resilience
Authors: Al-Binali Tamy , Aysan Ahmet Faruk , Dinçer Hasan , Unal Ibrahim Musa , Yüksel Serhat
Published: May 2023

This study explores the implications of merging two fundamentally different types of banks: Islamic and conventional banks. The research aims to provide insight into the unique opportunities and challenges presented by such a merger and to offer strategic guidance for future mergers. A balanced scorecard-based strategic analysis using a Quantum Spherical Fuzzy Decision-Making Approach was used to develop short- and long-term strategic plans for the merged bank. The balanced scorecard included 12 key performance indicators (KPIs) in 4 groups, and the methodology incorporated several questions to guide the analysis. The results of the study offer valuable insights into the potential opportunities and challenges of merging these two types of banks, as well as strategic recommendations for stakeholders at all levels. The study serves as a useful guideline for future mergers between similar or different types of banks. Overall, the findings suggest that a well-planned merger strategy is essential for avoiding challenges and maximizing the benefits of merging Islamic and conventional banks. By integrating the strengths of both types of banks, a merged entity could create a competitive advantage and potentially improve financial performance. However, this requires careful consideration of cultural differences, regulatory challenges, and other factors that could impact on the success of the merger.
Water Use Efficiency and Productivity of Irrigated Rice Cultivation in Nigeria: An Application of the Stochastic Frontier Approach
Authors: Wudil Abdulazeez Hudu , Ali Asghar , Mushtaq Khalid , Baig Sajjad Ahmad , Radulescu Magdalena , Prus Piotr , Usman Muhammad , Vasa László
Published: May 2023

In the face of declining water resources and low agricultural water productivity, it is vital to increase agricultural production efficiency and efficiency of water usage. The efficacy of irrigating rice fields in Nigeria is evaluated here using a stochastic frontier analysis. This is a parametric frontier that is assumed to have half-normal distribution, allowing the model to be separated from normal errors in a composite error model. Samples of 382 surveys were used in the study; out of the total number, 361 surveys were retrieved and used for the analysis. The analytical tools used in the study are: gross margin, water productivity analysis, and stochastic frontier approach. The results indicate an average yield of 4.69 and 4.94 tons/hectare, and net farm income of $415 and $364 for the farmers using canal irrigation and farmers using tube wells, respectively. The results also showed physical and economic water productivity of 0.51 kg/m3 and $0.11/m3 for canal water users, and 0.568 kg/m3 and $0.10/m3 for tube well users. The canal water users had a mean irrigation water use efficiency of 0.76, compared to 0.70 for the tube well users. The study recommends that effective extension services and their coverage be enhanced to provide adequate training to rice farmers on water use efficiency and the transfer of innovations and farming technologies to farmers.
Stressors and Resilience within the Cassava Value Chain in Nigeria: Preferred Cassava Variety Traits and Response Strategies of Men and Women to Inform Breeding
Authors: Olaosebikan Olamide , Bello Abolore , Utoblo Obaiya , Okoye Benjamin , Olutegbe Nathaniel , Garner Elisabeth , Teeken Béla , Bryan Elizabeth , Forsythe Lora , Cole Steven , Kulakow Peter , Egesi Chiedozie , Tufan Hale , Madu Tessy
Published: May 2023

This study investigated the trait preferences for cassava in the context of climate change and conflict stressors among value-chain actors in Nigeria to strengthen social inclusion and the community-resilience outcomes from breeding programs. Multi-stage sampling procedures were used to select and interview male and female value-chain participants in the Osun, Benue and Abia States. The results indicated that farmers preferred cassava traits such as drought tolerance, early bulking, multiple-product use and in-ground storability to strengthen resilience. Climate change and challenges related to social change shaped the response strategies from both genders, and influenced trait preferences, including the early re-emergence of cassava leaves, stems that had ratooning potential, and especially the root milking that was important among female respondents. The major response strategies employed by men included frequent farm visits to prevent theft and engaging in non-agricultural livelihoods. Those employed by women included backyard farming, early harvesting, having preferences for food with fewer processing steps, and depending on remittances. The resilience capacity was higher for men than for women due to their better access to assets, as well as their abilities to relocate their farms and out-migrate in search of other livelihoods. Considering gendered cassava traits, and enhancing their resilience and response strategies, can complement efforts to make breeding more socially inclusive, resilient, and anticipatory to future challenges created by climate and related social changes.