bluuebunny/crossref_metadata_2025 huggingface dataset:
Development of resin‐based dental composites containing hydroxyapatite and zirconia nanoparticles
Authors: Tunca Taşkıran Senagül , Tanoğlu Metin , Çerci Nazife , Cevahir Aref , Türkdoğan Damar Ceren , Ünver Elçin , Aktaş Mustafa İlker
Published: May 2024

In clinical applications, resin‐based dental composites primarily face challenges with fractures and secondary caries. To overcome these issues, the physical characteristics of dental composites, especially mechanical properties, need to be improved. Hydroxyapatite (HA), present in the structure of the teeth, is preferred due to its biological properties, and zirconia (ZrO2) nanoparticles are known to enhance the mechanical properties of this type of composites. The aim of this study is to develop resin‐based dental composites containing HA and ZrO2 nanoparticles. The study also aims to explore the synergistic effect of these two nanoparticles on the physical properties of the developed composites. Composites with nine different compositions were prepared by mixing the components with the help of a mortar mill. The flexural and compressive strength, polymerization shrinkage, depth of cure and water sorption, and solubility properties of the prepared composites have been investigated. All composites have been found to meet the requirements of ISO 4049 standard. Among them, composite containing 5 wt. % HA and 1 wt. % ZrO2 (H5Z1) has exhibited the highest flexural strength with an increase of 58% compared to the control sample, and composite containing 3 wt. % HA and 2 wt. % ZrO2 (H3Z2) has exhibited the highest compressive strength with an increase of 22% compared to the control sample. Other physical properties of the composites have been found to be in an acceptable level.

Highlights

Dental composites with HA and ZrO2 fillers were developed by a mortar mill.

Synergistic effect of HA and ZrO2 nanoparticles was investigated.

Mechanical properties of dental composites were significantly improved.

Physical properties of dental composites were found to be at acceptable levels.

Depth of cure decreases with increasing HA and ZrO2 loading.
Shape recovery and energy absorption properties of 3D printed continuous ramie fiber reinforced thin‐walled biocomposite structures
Authors: Lin Hao , Cai Ruijun , Cheng Ping , Wang Jin , Rao Yanni , Peng Yong , Wang Kui , Ahzi Said , Yao Song
Published: May 2024

Continuous fiber reinforced composites are widely used in thin‐walled structures due to their high specific strength and stiffness. In this work, continuous natural fiber was introduced into thin‐walled biocomposite structures via 3D printing technique to enhance energy absorbing properties and promote ecological compatibility. The effects of varying configurations of printing speed, layer thickness, and path optimization on the deposition quality of continuous ramie fiber and polylactic acid matrix were explored. The results showed that reduced printing speed (100 mm/min) and optimal layer thickness (0.25 mm) effectively minimized structural forming defects. In addition, further enhancements in the printing quality could be achieved by smoothing the path with rounded corners. Based on optimal printing strategies, different configurations of thin‐walled biocomposite structures were fabricated. Lateral monotonic and cyclic load tests were performed to investigate their energy absorption and shape recovery capacities. When the loading displacement was 10 mm (strain was 20%), the circular structure presented good shape recovery capability, with measured recovery ratio remaining above 89%. The hexagonal structure showed a similar variation in shape recovery ratio as the quadrangular structure, both remaining above 75%. Moreover, the specific energy absorption of all the structures converged after two cycles, indicating their remarkable and stable repeatable load‐bearing capacity.

Highlights

Continuous ramie fiber reinforced thin‐walled structures were prepared.

The deformation patterns of structures under lateral compression were analyzed.

Energy absorption and shape recovery radio were studied under cycle loading.

Printed structures exhibited great and stable repeatable load‐bearing capacity.
The Euler Sombor index of a graph
Authors: Tang Zikai , Li Yunping , Deng Hanyuan
Published: May 2024

A novel geometric method is proposed for constructing vertex‐degree‐based molecular structure descriptors, which is the perimeter of an ellipse whose focal points represent the degree‐point and its dual‐point of a pair of adjacent vertices in a graph . We first analyze the chemical applicability of this elliptic Sombor index, and then establish its mathematical properties and determine the extremal values for this elliptic Sombor index among all (molecular) trees and characterize the corresponding extremal graphs.
Driving factors for the adoption of green finance in green building for sustainable development in developing countries: The case of Ghana
Authors: Debrah Caleb , Chan Albert Ping Chuen , Darko Amos , Ries Robert J. , Ohene Eric , Tetteh Mershack Opoku
Published: May 2024

While there are many motivating factors for green finance (GF) implementation, a comprehensive taxonomy of these variables is lacking in the literature, especially for green buildings (GBs). This study aims to analyze the criticality and interdependence of GF‐in‐GB's driving factors. This study develops a valid set of factors to justify the interrelationships among the drivers. The drivers of GF‐in‐GB are qualitative in nature, and uncertainties exist among them due to linguistic preferences. This study applies the fuzzy Delphi method to validate eight drivers under uncertainties. Fuzzy Decision‐Making Trial and Evaluation Laboratory (FDEMATEL) with qualitative information is used to determine the interrelationships among the drivers. The drivers were grouped under two categories: prominent drivers and cause‐effect drivers. The findings revealed that “increased awareness of GF models in GB” and “preferential capital requirements for low‐carbon assets” are the top two most prominent/important drivers of GF‐in‐GB. In Ghana, the top three cause group drivers are “climate commitment,” “improved access to and lower cost of capital,” and “favorable macroeconomic conditions and investment returns.” Drivers with the highest prominence values have the potential to affect and/or be affected by other drivers; therefore, managers and policymakers should prioritize promoting or pursuing these drivers in the short term. On the other hand, it is important to pay more than equal attention to the drivers with the highest net cause values because they have the largest long‐term impact on the entire system. The theoretical and practical implications of the study are discussed, enhancing understanding and decision‐making in GF‐in‐GB.
Impact of renewable energy consumption on sustainable development in Central Asia
Authors: He Jiawen , Qin Yi , Wang Xiong
Published: May 2024

The energy transition in Central Asia faces multiple risks while lacking empirical assessment of renewable energy use from a sustainability perspective. This paper examined the relationship of renewable energy consumption with energy intensity and carbon intensity in Central Asia during 1993—2019, using the seemingly unrelated regression (SUR). Weighing the heterogeneity of countries in the region, the results showed that downstream countries build an inverted U‐shaped relationship between renewable energy consumption and carbon intensity, while the whole region indicates an inverted U‐shaped relationship between renewable energy consumption and energy intensity. Compared with hydrocarbon, nonfossil energy is expected to serve as a greater driving force for economic growth in the future, alleviating socio‐economic dependence on fossil fuels in downstream countries and generating additional revenues to ensure energy security in upstream countries. The findings suggest policymakers to considerably mitigate the risks of decarbonization across the region.
A Tunable Hydrophilic–Hydrophobic, Stimulus Responsive, and Robust Iridescent Structural Color Bionic Film with Chiral Photonic Crystal Nanointerface
Authors: Chen Huanghuang , Zhang Xufang , Zhou Tianchi , Hou Aiqin , Liang Jiahui , Ma Teng , Xie Kongliang , Gao Aiqin
Published: May 2024

Bio‐inspired in nature, using nanomaterials to fabricate the vivid bionic structural color and intelligent stimulus responsive interface as smart skin or optical devices are widely concerned and remain a huge challenge. Here, the bionic flexible film is designed and fabricated with chiral nanointerface and tunable hydrophilic–hydrophobic by the ultrasonic energy perturbation strategy and crosslinking of the cellulose nanocrystals (CNC). An intelligent nanointerface with adjustable hydrophilic and hydrophobic properties is constructed by the supramolecular assembly using a smart ionic liquid molecule. The bionic flexible film possessed the variable hydrophilic–hydrophobic, stimulus responsive, and robust iridescent structural color. The reflective wavelength and the helical pitch of the film can be easily modulated through the ultrasonic energy perturbation strategy. The bionic flexible film by covalent cross‐linking has excellent robustness, good elasticity and flexibility. The tunable brilliant structural color of the chiral nanointerface is attributed to the surface charge change of the CNC photonic crystal, which is disturbed by ultrasonic energy perturbation. The bionic flexible film with tunable structure color has intelligent hydrophilic and hydrophobic stimulus response properties. The chiral bionic materials have potential applications in smart skin, optical devices, bionic materials, robots, anti‐counterfeiting, colorful displays, and stealth materials.
Increased Deep Trap Density in Interfacial Engineered Nanocomposite Revealed by Sequential Kelvin Probe Force Microscopy for High Dielectric Energy Storage
Authors: Liu Kaixin , Zhang Fengyuan , Liu Zhigang , Song Chunlin , Zhang Lingyu , Ming Wenjie , Yang Lingyu , Wang Yao , Huang Boyuan , Li Jiangyu
Published: May 2024

Nanocomposites combining inorganic nanoparticles with high dielectric constant and polymers with high breakdown strength are promising for the high energy density storage of electricity, and carrier traps can significantly affect the dielectric breakdown process. Nevertheless, there still lacks direct experimental evidence on how nanoparticles affect the trap characteristics of nanocomposites, especially in a spatially resolved manner. Here, a technique is developed to image the trap distribution based on sequential Kelvin probe force microscopy (KPFM) in combination with the isothermal surface potential decay (ISPD) technique, wherein both shallow and deep trap densities and the corresponding energy levels can be mapped with nanoscale resolution. The technique is first validated using the widely‐used commercial biaxially oriented polypropylene, yielding consistent results with macroscopic ISPD. The technique is then applied to investigate polyvinylidene fluoride‐based nanocomposites filled with barium titanate nanoparticles, revealing higher deep trap density around surface‐modified nanoparticles, which correlates well with its increased breakdown strength. This technique thus provides a powerful spatially resolved tool for understanding the microscopic mechanism of dielectric breakdown of nanocomposites.
Management of bilateral lower eyelid entropion in a black Angus bull by temporary tacking and modified Hotz Celsus
Authors: Bedos Leila , Bowden Anna Catherine , Olivarez Jeff , Kubai Melissa A. , Allbaugh Rachel A.
Published: May 2024

The objective was to evaluate the progression and management of eyelid tacking sutures before permanent eyelid surgical correction. A 1‐year‐old Aberdeen black Angus bull presented with a 1‐month history of bilateral corneal ulcers. Ophthalmic examination revealed an infected stromal corneal ulcer on the left eye and bilateral lower eyelid entropion. Lower eyelid tacking sutures were placed bilaterally to allow corneal healing, prevent recurrent corneal ulceration and allow resolution of concurrent moist dermatitis. Approximately 2 weeks after eyelid tacking, permanent entropion repair using a modified Hotz Celsus technique was performed on both lower eyelids. This report details the successful treatment of bilateral lower eyelid entropion in a bull using temporary tacking sutures to stabilise corneal and eyelid disease before permanent eyelid surgical correction.
Design of molecularly imprinted polymers (MIP) using computational methods: A review of strategies and approaches
Authors: Mohsenzadeh Enayat , Ratautaite Vilma , Brazys Ernestas , Ramanavicius Simonas , Zukauskas Sarunas , Plausinaitis Deivis , Ramanavicius Arunas
Published: May 2024

This paper focuses on the computationally assisted design of molecularly imprinted polymers (MIP), emphasizing the selected strategies and chosen methods of approach. In summary, this paper provides an overview of the MIP fabrication procedure, focusing on key factors and challenges, where the fabrication of MIP includes a step‐by‐step process with extensive experimental procedures. This brings challenges in optimizing experimental conditions, such as the selection of monomer, cross‐linker, and their relevant molar ratios to the template and solvent. Next, the principles of computational methods are elucidated to explore their potential applicability in solving the challenges. The computational approach can tackle the problems and optimize the MIP's design. Finally, the atomistic, quantum mechanical (QM), and combined methods in the recent research studies are overviewed with stress on strategies, analyses, and results. It is demonstrated that optimization of pre‐polymerization mixture by employing simulations significantly reduces the trial‐and‐error experiments. Besides, higher selectivity and sensitivity of MIP are observed. The polymerization and resulting binding sites by computational methods are considered. Several models of binding sites are formed and analyzed to assess the affinities representing the sensitivity and selectivity of modeled cavities. Combined QM/atomistic methods showed more flexibility and versatility for realistic modeling with higher accuracy. This methodological advancement aligns with the principles of green chemistry, offering cost‐effective and time‐efficient solutions in MIP design.

This article is categorized under:

Structure and Mechanism > Molecular Structures

Structure and Mechanism > Computational Materials Science

Molecular and Statistical Mechanics > Molecular Interactions
RETRACTED: Laminar single‐phase and two‐phase modeling of water/MgO nanofluid flow inside a rectangular microchannel with rhombic vortex generators
Authors: Faridzadeh Mohammad Reza , Toghraie Davood , Khalili Majid , Akbari Omid Ali , Ghajari Navid , Alizadeh As'ad
Published: May 2024

In the present numerical simulation, laminar single‐phase and two‐phase nanofluid flows are investigated inside a rectangular microchannel with the vortex generators. Rhombic vortex generators with different attack angles are used for a better mixture of fluid. Water/MgO nanofluid is used as the working fluid in the volume fractions of nanoparticles φ = 0‐4% in Reynolds numbers of Re = 1‐300 at the two‐dimensional space. The presence of vortex generators with attack angles of λ = 0‐45°, and simultaneous investigation of heat transfer and flow hydrodynamic parameters distinguish this research from other similar studies. Obtained results revealed that using nanofluid with higher volume fractions, slip boundary condition on the hot wall, and using vortex generator with higher λ lead to significant enhancement of heat transfer. Also, the value of pressure drop augmentation is caused by the increase of φ and λ is significant at higher Reynolds numbers. Unlike the increase of φ, by increasing Reynolds number, the effect of slip boundary condition becomes considerable on the reduction of entropy generation. The behavior of entropy generation graphs with slip velocity boundary condition on the wall is different from the no‐slip boundary condition at Re = 300. The behavior of average entropy generation is different in the various φ, Reynolds numbers, and λ in the no‐slip boundary condition for single‐phase and two‐phase models. Also, the two‐phase model estimates flow behavior with less irreversibility.
Older Adults´ Emotional User Experiences with Digital Health Services
Authors: Valkonen Paula , Kujala Sari
Published: May 2024

Older adults are at risk of being excluded from digital society. They do not always find digital health services appealing, or they may have challenges with them. We investigated older adults´ emotional user experiences with digital health services and aimed to give designers tools to make digital health services more appealing for older adults. We interviewed 16 older adults about their experiences with digital health services. The use of digital health services brought joy and increased self-confidence. On the other hand, older adults had many negative emotional user experiences, including fear of pressing buttons and embarrassment of incompetence. In the future, designers should actively look for solutions that alleviate older adults´ fears and further encourage them to use digital health services. To enable that, proposals are made for designing digital health services.
Near-Infrared Spectroscopic Study Towards Clinical Radiotherapy Treatment Monitoring
Authors: Karthikeyan Priya , Ferdinando Hany , Korhonen Vesa , Honka Ulriika , Lohela Jesse , Inget Kalle , Karhula Sakari , Nikkinen Juha , Myllylä Teemu
Published: May 2024

This study used near-infrared spectroscopy to monitor dynamic spectral effects to radiotherapy aiming to monitor spectral response for clinical radiotherapy. Twenty-four patients with total fractions of 96 measurements were measured to evaluate the dynamic spectral status of radiotherapy response. Dynamic responses from absorbance measurement were found to be associated with effects of induced radiation to skin and it linearly correlates to the dose given. Whereas significantly no response was found in ex vivo samples. A spectrometer was used in near infrared range between 650 nm and 1100 nm wavelength in absorbance mode. The absorbance spectral dynamics were measured using one light source-detector probe attached to the forehead in human patients and chicken samples to compare their responses to irradiation. The absorbance measurements of the forehead (skin) show absorbance increase throughout the spectra during irradiation in patients and confirmed with repeatability whereas in corresponding irradiation of ex vivo chicken samples, no absorbance changes were detected. Since spectral range of 650 nm–950 nm is dominantly affected by hemodynamical changes in tissue this indicates the oxygenation of blood in patients is strongly affected by irradiation. Furthermore, the irradiation caused absorbance changes also between 950 nm to 1100 nm range which is dominated by water in tissue, however in ex vivo chicken no visible effects of irradiation were detected in this range either.
Visual Modeling of Multiple Sclerosis Patient Pathways: The Healthcare Workers’ Perspectives
Authors: Bogale Binyam , Solem Ingrid Konstanse Ledel , Celius Elisabeth Gulowsen , Halvorsrud Ragnhild
Published: May 2024

Multiple Sclerosis (MS) necessitates tailored care along intricate pathways throughout a patient's lifetime. Visualizing these pathways enhances the collective understanding of care processes and fosters collaboration among stakeholders. This study employed a qualitative study to map and the Customer Journey Modeling Language (CJML) to model MS patient pathways. A total of six purposefully selected healthcare professionals working in specialized healthcare, at a hospital and separate rehabilitation center, contributed to the care process mapping, participating in both pre- and post-modeling in-depth interviews. CJML, designed to capture planned and actual journeys from the service users’ perspective was adapted in this study to showcase the service provider's viewpoints, revealing insights into the existing organization of MS care. Involving more than one service provision level in mapping and modeling care processes requires dealing with handovers and its associated challenges. The final visualizations illustrate potential areas for improvement, including the need for more standardized procedures, potentially leading to variations in the quality of care and/or inefficient processes. However, the mapping process highlighted the difficulties in visualizing the MS care pathway due to its highly personalized nature, including challenges with creating personas or case groups that would allow for a unified service model. Participants’ feedback on the visualizations was essential, illustrating the importance of member checking when dealing with complex concepts such as patient pathways and organization of care.
The Viewpoint of Informal Carers of People with Multiple Sclerosis in Digital Health Research: A Scoping Review
Authors: Yrttiaho Tiia , Mylonopoulou Vasiliki , Giunti Guido , Isomursu Minna
Published: May 2024

Multiple sclerosis (MS) is a common neurological disease that can impact not only individuals diagnosed with the condition but also their informal carers, i.e. family members and friends. This scoping review aimed to map the role that family members and friends of people with multiple sclerosis have had in digital health research. The scoping review was reported according to PRISMA-ScR. The search was done in Scopus, CINAHL, Pubmed, and Web of Science. A total of 14 studies met the inclusion criteria. These studies were about telemedicine, rehabilitative video games, online education, user research, and development. Usually, family members and friends had a side part in the research. One study focused exclusively on them, and in total, in eight studies family and friends were participants in the study. Otherwise, they were accompanying the person with multiple sclerosis, were seen as possible users of the digital solution or they appeared in results by someone else. In this scoping review, it was seen that informal carers can get support and information from digital sources, they are able to act as informal carers in digital environments, healthcare professionals can receive information from them and family and friends can help in remote assessments, and digital solutions can help informal carers and people with MS to connect in a new or better way. Our results highlight that digital health can bring benefits to family members, people with multiple sclerosis, and healthcare.
Passively Reconfigurable Antenna Using Gravitational Method
Authors: Satitchantrakul Thanatcha , Manapreecha Chanathan , Phongpatrawiset Sukrit , Soh Ping Jack
Published: May 2024

This paper proposes a passive reconfigurable antenna by using liquid metal and gravity mechanism. When the antenna rotates to different angles, the liquid metal will flow to the lowest point of the container due to gravitational force, thereby acting as a reflector to redirect the main antenna radiation pattern at predefined angles at 5.8 GHz (ISM band). The upper section patterns can be maintained when antenna is tilted at 45°, 90°, 135°, 225°, 275° and 315° whereas the rotated antenna at 0° and 180° causes a forward radiation. More importantly, additional directors surrounding the main patch can be used to increase the directivity of these radiation patterns. Simulation results in terms of reflection coefficient, radiation patterns and gain indicate that the proposed antenna operated passively with a consistent bandwidth of approximately 400 MHz.
Computed Tomography Artefact Detection Using Deep Learning—Towards Automated Quality Assurance
Authors: Inkinen S. I. , Kotiaho A. O. , Hanni M. , Nieminen M. T. , Brix M. A. K.
Published: May 2024

Image artefacts in computed tomography (CT) limit the diagnostic quality of the images. The objective of this proof-of-concept study was to apply deep learning (DL) for automated CT artefact classification. Openly available Head CT data from Johns Hopkins University was used. Three common artefacts (patient movement, beam hardening, and ring artefacts (RAs)) and artefact free images were simulated using 2D axial slices. Simulated data were split into a training set (Ntrain = 1040 × 4(4160)), two validation sets (Nval1 = 130 × 4(520) and Nval2 = 130 × 4(520)), and a separate test set (Ntest = 201 × 4(804); two individual subjects). VGG-16 model architecture was used as a DL classifier, and the Grad-CAM approach was used to produce attention maps. Model performance was evaluated using accuracy, average precision, area under the receiver operating characteristics (ROC) curve, precision, recall, and F1-score. Sensitivity analysis was performed for two test set slice images in which different RA radiuses (4 pixels to 245) and movement artefacts, i.e., head tilt with rotation angles (0.2° to 3°), were generated. Artefact classification performance was excellent on the test set, as accuracy, average precision, and ROC area under curve over all classes were 0.91, 0.86, and 0.99, respectively. The precision, recall, and F1-scores were over 0.84, 0.71, and 0.85 for all class-wise cases. Sensitivity analysis revealed that the model detected movement at all rotation angles, yet it failed to detect the smallest RAs (4-pixel radius). DL can be used for effective detection of CT artefacts. In future, DL could be applied for automated quality assurance of clinical CT.
The Effects of Robotic Training on Walking and Functional Independence of People with Spinal Cord Injury: A Systematic Review, Meta-analysis and Meta-regression
Authors: Köyhäjoki Anna , Korpi Hilkka , Yli-Ikkelä Riku , Hakonen Harto , Kantola Mirjami , Rintala Aki , Honkanen Sari , Ilves Outi , Sjögren Tuulikki , Karvanen Juha , Aartolahti Eeva
Published: May 2024

Evidence on the effects of robotic technology is required to develop rehabilitation services. This study aimed to evaluate the effects of robot-assisted walking training on walking and functional independence in everyday life in persons with spinal cord injury (SCI) and explore the covariates associated with these effects.

We searched the MEDLINE (Ovid), CINAHL, PsycINFO, and ERIC databases until March 25, 2022. Two reviewers independently assessed the studies for inclusion. We included RCTs on people with SCI receiving robotic training. The Cochrane RoB2, meta-analysis, meta-regression, and Grading of Recommendations Assessment, Development, and Evaluation were performed.

We included 23 RCTs focusing on SCI with outcomes of walking or functional independence, of which 14 were included in the meta-analysis and meta-regression analyses. Small improvements were observed in functional independence in favor of robot-assisted walking training compared to other physical exercises (Hedges’ g 0.31, 95% CI 0.02 to 0.59; I2 = 19.7%, 9 studies, 419 participants, low certainty evidence). There were no significant differences in walking ability, speed, endurance, or independence between the groups.

Robot-assisted walking training may slightly improve functional independence, but its effects on walking ability in SCI patients is uncertain compared to other exercise. Evidence suggests little to no difference in walking independence, and the effects on walking speed and endurance are unclear. No clear evidence exists whether positive effects are linked to personal, clinical, or intervention characteristics. Robot-assisted gait training may be a viable option for improving functional independence in individuals with SCI.
Assessment of Parkinson’s Disease Severity Using Gait Data: A Deep Learning-Based Multimodal Approach
Authors: Faiem Nabid , Asuroglu Tunc , Acici Koray , Kallonen Antti , van Gils Mark
Published: May 2024

The ability to regularly assess Parkinson’s disease (PD) symptoms outside of complex laboratories supports remote monitoring and better treatment management. Multimodal sensors are beneficial for sensing different motor and non-motor symptoms, but simultaneous analysis is difficult due to complex dependencies between different modalities and their different format and data properties. Multimodal machine learning models can analyze such diverse modalities together, thereby enhancing holistic understanding of the data and overall patient state. The Unified Parkinson’s Disease Rating Scale (UPDRS) is commonly used for PD symptoms severity assessment. This study proposes a Perceiver-based multimodal machine learning framework to predict UPDRS scores.

We selected a gait dataset of 93 PD patients and 73 control subjects from the PhysioNet repository. This dataset includes two-minute walks from each participant using 16 Ground Reaction Force (GRF) sensors, placing eight on each foot. This experiment used both raw gait timeseries signals and extracted features from these GRF sensors. The Perceiver architecture’s hyperparameters were selected manually and through Genetic Algorithms (GA). The performance of the framework was evaluated using Mean Absolute Error (MAE), Root Mean Square Error (RMSE) and linear Correlation Coefficient (CC).

Our multimodal approach achieved a MAE of 2.23 ± 1.31, a RMSE of 5.75 ± 4.16 and CC of 0.93 ± 0.08 in predicting UPDRS scores, outperforming previous studies in terms of MAE and CC.

This multimodal framework effectively integrates different data modalities, in this case illustrating by predicting UPDRS scores using sensor data. It can be applied to diverse decision support applications of similar natures where multimodal analysis is needed.
Digital Services in the Welfare, Social and Health Sector Organizations of the South Ostrobothnia Region
Authors: Hoffrén-Mikkola Merja
Published: May 2024

Digital services in healthcare and social services have increased due to national promotion and Covid19 pandemic. However, the regional differences may exist. Successful implementation and sustainability of digital services requires that attention is paid to addressing barriers and supporting facilitators at all levels in health care provision.

The purpose of this study was to investigate the effects of employee status, form of organization and organizational size on the views related to current state and the role of digital services, development barriers, development plans and the support needed for development in welfare, social and health service organizations operating in the South Ostrobothnia region. The study was carried out in the era of exceptional circumstances created by the Covid19 pandemic in the summer of 2021. The study was a quantitative cross-sectional study using an electronic survey. Respondents (n = 121) were managers, entrepreneurs and employees of welfare, social and health service organizations operating in the South Ostrobothnia region.

The results suggested that in more than four out of five welfare, social and health service organizations operating in the region of South Ostrobothnia, part of the services were already digital in the summer of 2021. These services had been extensively developed during the previous year, which was lived in exceptional circumstances caused by the Covid19 pandemic. Digital services were seen to function especially as enablers of customers in exceptional circumstances. However, managers or entrepreneurs also saw digital services as reaching new customers more important than employees. The acquisition of technology and human resources were felt to be the most significant barriers in the development of digital services, regardless of the employee status, form of organization and organization size. Regarding the use and development of digital services, information was felt to be necessary, especially about the characteristics of digital services, and financial support was also felt to be necessary for the development. However, the support needs were significant in many aspects related to digital service development. In particular, large organizations needed information on the cost-effectiveness of digital services.

The results can be used to support welfare, social and health service organizations in digital service development.
Contractive Multivariate Zipper Fractal Interpolation Functions
Authors: Miculescu Radu , Pasupathi R.
Published: May 2024

In this paper we introduce a new general multivariate fractal interpolation scheme using elements of the zipper methodology. Under the assumption that the corresponding Read-Bajraktarevic operator is well-defined, we enlarge the previous frameworks occurring in the literature, considering the constitutive functions of the iterated function system whose attractor is the graph of the interpolant to be just contractive in the last variable (so, in particular, they can be Banach contractions, Matkowski contractions, or Meir-Keeler contractions in the last variable). The main difficulty that should be overcome in this multivariate framework is the well definedness of the above mentioned operator. We provide three instances when it is guaranteed. We also display some examples that emphasize the generality of our scheme.
Advancements in Continuum Mechanics and Electrodynamics by a spacetime geometric approach
Authors: Romano Giovanni , Barretta Raffaele
Published: May 2024

Results achieved by the authors in the course of research activity on continuum mechanics and electrodynamics (CME) during the past twenty years are illustrated, revised and discussed. Adoption of a geometric approach leads to renewal of concepts and methods of classical CME and to formulation in Euclid (3+1)D ambient spacetime wherein innovation, clarity and depth of a geometric treatment naturally emerge. The dissemination of novel concepts and methods in CME is not delayable, with critical revisitation of problematic notions, analyses and results still currently on the scene. Material frame indifference, equilibrium in a reference configuration, extremality principles in Dynamics, finite elasticity, chain decomposition of finite strain in elasto-thermo-plasticity, variance of electro-magnetic induction laws under frame changes, action on electric charges moving in a magnetic field, are under the spotlight of innovation and advancement. Fostering basic knowledge of Differential Geometry and application of geometric notions and methods contribute effective tools in formulating meaningful rules, amending misstatements and dimming debates based on vague affirmations.
Characterization and classification of ductal carcinoma tissue using four channel based stokes-mueller polarimetry and machine learning
Authors: KU Spandana , Kaniyala Melanthota Sindhoora , U Raghavendra , Rai Sharada , Mahato K. K. , Mazumder Nirmal
Published: May 2024

Interaction of polarized light with healthy and abnormal regions of tissue reveals structural information associated with its pathological condition. Even a slight variation in structural alignment can induce a change in polarization property, which can play a crucial role in the early detection of abnormal tissue morphology. We propose a transmission-based Stokes-Mueller microscope for quantitative analysis of the microstructural properties of the tissue specimen. The Stokes-Mueller based polarization microscopy provides significant structural information of tissue through various polarization parameters such as degree of polarization (DOP), degree of linear polarization (DOLP), and degree of circular polarization (DOCP), anisotropy (r) and Mueller decomposition parameters such as diattenuation, retardance and depolarization. Further, by applying a suitable image processing technique such as Machine learning (ML) output images were analysed effectively. The support vector machine image classification model achieved 95.78% validation accuracy and 94.81% testing accuracy with polarization parameter dataset. The study's findings demonstrate the potential of Stokes-Mueller polarimetry in tissue characterization and diagnosis, providing a valuable tool for biomedical applications.
Big data in transportation: a systematic literature analysis and topic classification
Authors: Tzika-Kostopoulou Danai , Nathanail Eftihia , Kokkinos Konstantinos
Published: May 2024

This paper identifies trends in the application of big data in the transport sector and categorizes research work across scientific subfields. The systematic analysis considered literature published between 2012 and 2022. A total of 2671 studies were evaluated from a dataset of 3532 collected papers, and bibliometric techniques were applied to capture the evolution of research interest over the years and identify the most influential studies. The proposed unsupervised classification model defined categories and classified the relevant articles based on their particular scientific interest using representative keywords from the title, abstract, and keywords (referred to as top words). The model’s performance was verified with an accuracy of 91% using Naïve Bayesian and Convolutional Neural Networks approach. The analysis identified eight research topics, with urban transport planning and smart city applications being the dominant categories. This paper contributes to the literature by proposing a methodology for literature analysis, identifying emerging scientific areas, and highlighting potential directions for future research.
The role of taxation in an integrated economic-environmental model: a dynamical analysis
Authors: Cavalli Fausto , Mainini Alessandra , Visetti Daniela
Published: May 2024

We propose a model with economic and environmental domains that interact with each other. The economic sphere is described by a Solow growth model, in which productivity is not exogenous but negatively affected by the stock of pollution that stems from the production process. A regulator can charge a tax on production, and the resources collected from taxation are used to reduce pollution. The resulting model consists of a two dimensional discrete dynamical system, and we study the role of taxation from both a static and a dynamical point of view. The focus is on the determination of the conditions under which taxation has a positive effect on the environment and leads to economic growth. Moreover, we show that a suitable environmental policy can allow recovering both local and global stability of the steady states. On the contrary, we show that, if the policy is not adequate, the system can exhibit endogenous oscillating and chaotic behavior and multistability phenomena.
Assessing paddy methane emissions through the identification of rice and winter crop areas using Sentinel-2 imagery in Korea
Authors: Jang Seongju , Park Jinseok , Lee Hyeokjin , Gou Jaejun , Song Inhong
Published: May 2024

The global efforts on reducing methane (CH4) emissions was emphasized in COP 28 and the potential for improved estimation became feasible through bottom-up data acquisition with advanced remote sensing technology. The objectives of this study were to extract summer rice and winter crop cultivation areas based on satellite images and to incorporate into estimating CH4 emissions in South Korea for the year 2020. Satellite images of Sentinel-1 and Sentinel-2 were acquired from European Space Agency. Rice paddy was classified with backscattering coefficient from Sentinel-1 images, while the normalized difference vegetation index from Sentinel-2 images was used to identify winter cropping field. The equation of IPCC guidelines was used to estimate CH4 emissions by incorporating the areas of rice paddy and winter crop extracted with the respective satellite image. National farming statistics were used to determine the scaling factors for paddy organic matter and water management practices. The estimated areas for rice paddy and winter crop cultivation were 712,237 ha and 117,840 ha, respectively. The rice paddy areas were primarily concentrated in the western regions of the Korean peninsula, whereas winter crop cultivation was predominantly found in southern part of the country. The total amount of CH4 emissions was 6272 Gg CO2 eq./yr when considering rice straw and winter cropping practices into estimation (modified Tier 2 method). This represents a 7% increase compared to the method that considered solely the rice straw incorporation (current Tier 2 method). The CH4 emissions per unit area were also 8.82 tons CO2 eq./ha/yr with the modified Tier 2 method, indicating a 10% greater compared to the current Tier 2 method. Substantial CH4 emissions were primarily concentrated in western regions where extensive rice paddy cultivation occurs, while greater CH4 emissions per unit area were predominantly found in southern regions with substantial winter crop cultivation. The study findings hold importance for improving the accuracy of CH4 emissions estimation by employing bottom-up approach that utilizes satellite imagery to assess rice paddy and winter cropping areas. Further study would be needed to incorporate field-based data on rice crop management practices, such as rice straw and water management, to further refine CH4 emission estimation method.
Tense in Mathematical English
Authors: Inglis Matthew , Strauss Jacob
Published: May 2024

Many authors have commented on the relative frequency of the present tense—and the relative infrequency of the past tense—in mathematical writing. However, none (to our knowledge) have provided an estimate for the size of this effect or explored how universal it is. In this short note we report an analysis of corpora of mathematical and day-to-day English. We conclude that the present-to-past ratio of tenses is at least 3:1 in mathematical English, compared to approximately 5:7 in day-to-day English. Further, we show that this tendency to favour the present tense is almost universally present in written mathematics.
Takotsubo cardiomyopathy mimicking an apical hypertrophic cardiomyopathy
Authors: Maurizi N. , Antiochos P. , Monney P.
Published: May 2024

A 45-years old woman presented for dyspnea and cardiac chest pain. ECG showed deep T-wave inversion while CMR showed normal ejection fraction, hypertrophy and systolic obliteration of the apex suggesting apical HCM. Myocardial oedema was noted at the apex. Complete regression of hypertrophy and myocardial edema was observed after 2 months, and a final diagnosis of subacute Takotsubo was made.
Multi-objective generalized normal distribution optimization: a novel algorithm for multi-objective problems
Authors: Khodadadi Nima , Khodadadi Ehsan , Abdollahzadeh Benyamin , EI-Kenawy El-Sayed M. , Mardanpour Pezhman , Zhao Weiguo , Gharehchopogh Farhad Soleimanian , Mirjalili Seyedali
Published: May 2024

This study introduces the Multi-objective Generalized Normal Distribution Optimization (MOGNDO) algorithm, an advancement of the Generalized Normal Distribution Optimization (GNDO) algorithm, now adapted for multi-objective optimization tasks. The GNDO algorithm, previously known for its effectiveness in single-objective optimization, has been enhanced with two key features for multi-objective optimization. The first is the addition of an archival mechanism to store non-dominated Pareto optimal solutions, ensuring a detailed record of the best outcomes. The second enhancement is a new leader selection mechanism, designed to strategically identify and select the best solutions from the archive to guide the optimization process. This enhancement positions MOGNDO as a cutting-edge solution in multi-objective optimization, setting a new benchmark for evaluating its performance against leading algorithms in the field. The algorithm's effectiveness is rigorously tested across 35 varied case studies, encompassing both mathematical and engineering challenges, and benchmarked against prominent algorithms like MOPSO, MOGWO, MOHHO, MSSA, MOALO, MOMVO, and MOAOS. Utilizing metrics such as Generational Distance (GD), Inverted Generational Distance (IGD), and Maximum Spread (MS), the study underscores MOGNDO's ability to produce Pareto fronts of high quality, marked by exceptional precision and diversity. The results affirm MOGNDO's superior performance and versatility, not only in theoretical tests but also in addressing complex real-world engineering problems, showcasing its high convergence and coverage capabilities. The source codes of the MOGNDO algorithm are publicly available at https://nimakhodadadi.com/algorithms-%2B-codes.
Consideration of the Accuracy of Empirical and Indirect Laboratory Methods for the Characterisation of Tension Strength
Authors: Sainsbury B. , McDonald A.
Published: May 2024

This research explores the results of the most common laboratory based indirect tension strength methods over the range of UCS strengths 0.1 MPa (cemented paste backfill) to 100 MPa (concrete). The accuracy of each of the methods is considered through a comparison with direct strength measurements completed on the same material. The results of 241 individual tests suggest that the use of indirect tension methods to determine tension strength for all geo-material strength ranges may provide misleading results unless a correction-factor is applied. Correction factors that relate splitting and flexure results to direct tension results are provided. The correction factors are based on the characteristic UCS of the material. A comparison of the traditional empirical relationship to derive tension from UCS is presented and an updated relationship is proposed that is relevant over the UCS strength range 0.1–100 MPa.
The “Turning Point” for the Fall Goose Hunt in Eeyou Istchee: A Social-Ecological Regime Shift from an Indigenous Knowledge Perspective
Authors: Idrobo C. Julián , Leblanc Mélanie-Louise , O’Connor Mary I.
Published: May 2024

We present a perspective on how the Eeyou (James Bay Cree) from Eeyou Istchee (Eastern James Bay, Québec) understand the transformation of their traditional fall goose hunt system as a consequence of social and environmental changes across marine and terrestrial ecosystems with drivers operating at the local, regional and continental scales. Eeyou land users from the Chisasibi and Wemindji First Nations report that their traditional fall goose hunt underwent a “turning point” during the early 2000s. Not only did the abundance of Canadian geese reach a historical low, but their feeding and migratory behavior became unpredictable. Eeyou land users associate such abrupt changes with the massive eelgrass die-off of the late 1990s, the onset of the effects of climate change on coastal habitats experienced since the 1970s, and agricultural development along geese flyways. This manuscript is an outcome of the Eeyou Knowledge component of the Coastal Habitat Comprehensive Research Project (2016–2022) and followed a community-based case study approach that included 28 semi-structured interviews and 14 mapping interviews with Eeyou research contributors. The findings presented here underscore the capacity of Indigenous knowledge to make sense of the multifaceted impacts of environmental change across various dimensions and layers of their social-ecological system, including management strategies and values.