bluuebunny/crossref_metadata_2025 huggingface dataset:
Minimizing Oxidative Stress in Oral Surgery: A Comparative Study of Laser-Assisted and Conventional Third Molar Extractions
Authors: Popa Paul Șerban , Popa-Cazacu Elisabeta Claudia , Zaharescu Anamaria , Popa Gabriel Valeriu , Matei Mădălina Nicoleta
Published: December 2024

Background/Objectives: This study aims to compare the effects of conventional surgical techniques and laser-assisted methods on salivary oxidative stress biomarkers following third molar extraction, in order to evaluate the potential benefits of laser surgery in reducing oxidative stress and promoting faster recovery. Methods: A total of 154 patients, aged 16–30, undergoing third molar extractions were included in the study. Patients were divided into two groups: conventional surgery (n = 75) and laser-assisted surgery (n = 79). Saliva samples were collected at baseline, and 24, 48, 72, and 168 h postoperatively. The levels of total antioxidant capacity (TAC), malondialdehyde (MDA), and 8-hydroxy-2′-deoxyguanosine (8-OHdG) were measured as indicators of oxidative stress. Results: Initial biomarker levels were similar across all participants. Postoperative oxidative stress increased in both groups, with significantly higher levels in the conventional surgery group at 48 and 72 h. Salivary biomarkers of oxidative stress were significantly lower in the laser group at 48 and 72 h post-surgery (p < 0.05), indicating a faster recovery. By 168 h, biomarker levels in the laser group had nearly returned to baseline, whereas levels in the conventional group remained slightly elevated. Conclusions: Laser-assisted surgery significantly reduces oxidative stress and promotes faster recovery when compared with conventional methods, as evidenced by the more rapid normalization of salivary biomarkers. These findings suggest that laser techniques may offer superior clinical outcomes in third molar extractions.
Challenges in Differential Diagnosis of Diffuse Gingival Enlargement: Report of Two Representative Cases and Literature Review
Authors: Papadopoulou Erofili , Kouri Maria , Andreou Anastasia , Diamanti Smaragda , Georgaki Maria , Katoumas Konstantinos , Damaskos Spyridon , Vardas Emmanouil , Piperi Evangelia , Nikitakis Nikolaos G.
Published: December 2024

Background/Objectives: The etiology of diffuse gingival enlargement is multifactorial, and the definitive diagnosis may be challenging. To highlight the nuances of the differential diagnosis, we present two cases of generalized gingival overgrowth and discuss the diagnostic dilemmas. Case description: In the first case, an 82-year-old male with a medical history of hypertension and prostatitis had a chief complaint of symptomatic oral lesions of a 20-day duration, accompanied by fever and loss of appetite. The clinical examination revealed diffusely enlarged, hemorrhagic, and focally ulcerative upper and lower gingiva, ecchymoses on the buccal mucosa, as well as bilateral cervical lymphadenitis. The histopathologic and immunohistochemical findings combined with the hematologic examination led to a final diagnosis of acute myeloid leukemia, and the patient was referred to a specialized hematology/oncology unit for further management. The second case was a 74-year-old female with a medical history of breast cancer (successfully managed in the past), type II diabetes mellitus, and cardiovascular disease, taking various medications. An intraoral examination revealed diffusely enlarged, erythematous, and hemorrhagic upper and lower gingiva. An incisional biopsy showed hyperplastic granulation and fibrous connective tissue with a predominantly chronic inflammatory infiltrate. Considering the patient’s medical history and current medications, the clinical and microscopic findings were in support of the diagnosis of drug-induced gingival overgrowth associated with calcium channel blocker (amlodipine), partially controlled diabetes serving as an additional predisposing factor. Gingivectomy and periodontal scaling, along with substitution of the offending medication, were curative, and better diabetic control was recommended. Conclusions: Diffuse gingival overgrowth may be caused by a variety of diverse conditions, ranging from an exuberant response to local factors, potentially exacerbated by hormonal influences (e.g., puberty or pregnancy), to drug side effects to genetic, systemic, or even neoplastic diseases. A careful evaluation of the medical and drug history and clinicopathologic correlation is essential for accurate diagnosis and appropriate management.
RBFNN-Based Adaptive Fixed-Time Sliding Mode Tracking Control for Coaxial Hybrid Aerial–Underwater Vehicles Under Multivariant Ocean Disturbances
Authors: Lu Mingqing , Yang Wei , Xiong Zhenyu , Liao Fei , Wu Shichong , Su Yumin , Wu Wenhua
Published: December 2024

In this study, the design of an adaptive neural network-based fixed-time control system for a novel coaxial trans-domain hybrid aerial–underwater vehicle (HAUV) is investigated. A radial basis function neural network (RBFNN) approximation strategy-based adaptive fixed-time terminal sliding mode control (AFTSMC) scheme is proposed to solve the problems of the dynamic nonlinearity, model parameter perturbation, and multiple external disturbances of coaxial HAUV trans-media motion. A complete six-degrees-of-freedom model for a continuous water–air cross-domain model is first established based on the hyperbolic tangent transition function, and, subsequently, based on a basic framework of FTSMC, a fixed-time and fast-convergence controller is designed to track the target position and attitude signals. To reduce the dependence of the control scheme on precise model parameters, an RBFNN approximator is integrated into the sliding mode controller for the online model identification of the aggregate uncertainties of the coaxial HAUV, such as nonlinear unmodeled dynamics and external disturbances. At the same time, an adaptive technique is used to approximate the upper bound of the robust switching term gain in the controller, which further offsets the estimation error of the RBFNN and effectively attenuates the chattering effect. Based on Lyapunov stability theory, it is proven that the tracking error can converge in a fixed time. The effectiveness and superiority of the proposed control strategy are verified by several sets of simulation results obtained under typical working conditions.
Reimagining Sustainable Development and Economic Performance Indicators: A Human-Centric Maslow–Bossel Blueprint
Authors: Panagiotopoulos Panagiotis , Vardopoulos Ioannis , Maialetti Marco , Ciaschini Clio , Koundouri Phoebe , Salvati Luca
Published: December 2024

Reflecting the shift from purely quantitative economic growth to broader socio-environmental sustainability, this study proposes a framework for assessing sustainable development (SD) by integrating Maslow’s hierarchy of needs with Bossel’s classification system. As economic development increasingly emphasizes sustainability, numerous organizations and agencies, including the United Nations, have developed indicators to measure sustainable progress. However, subjective dimensions of SD, grounded in individual values and needs, remain underexplored. This study operationalizes Maslow’s “pyramid of needs” alongside Bossel’s system to establish an “SD pyramid”, distinguishing dimensions and indicators that capture social, economic, and environmental complexity. By mapping human needs onto the Sustainable Development Goals (SDGs), this study contributes to delineating (i) the research areas uncovered (or partly covered) with relevant indicators, (ii) a significant lack or partial shortage of pertinent information, and (iii) a combination of a few basic indicators summarizing the necessary information into a unique measure of SD. The outcomes offer a foundation for a quali-quantitative assessment of SD, enhancing the monitoring tools focusing on subjective and contextual needs.
STEAM Architecture—A STEAM Project for Pre-University Studies to Connect the Curricula with Architectural Concepts
Authors: Martínez Judith , Montés Nicolás , Zapatera Alberto
Published: December 2024

This article presents STEAM Architecture, a STEAM project for all educational levels, from pre-school to high school, a project that links the learning of subjects with architectural concepts, thus trying to generate meaningful learning in students. The project is the result of an ERASMUS+ project (DART4City (2020-1-ES01-KA227-SCH-095545) Empowering Arts and creativity for the cities of tomorrow) in which a methodology was developed to extract STEAM projects from European curricula. This methodology has two variants: “forward” and “backward”. The “forward” variant analyzes the curriculum and found the areas of opportunity with more connections among the contents while the “backward” methodology proposes a specific theme to look for the connections. The “backward” variant allows finding a topic that may be of social interest. This is the variant we use in this article. We explore the “backward” methodology in order to find an area of opportunity in society, in particular related to architecture. A questionnaire is distributed to different sectors of people in society to find out whether the learning of different architectural concepts at pre-university levels is interesting. The results of these tests show the potential of a STEAM project related to architecture. The design of the STEAM architecture project shows how the subdivision is carried out from an educational point of view, and also from an architectural point of view. Both worlds agree on dividing space into micro-, meso- and macro-space depending on the scale of what is being treated. For this reason, the STEAM architecture project is subdivided into Room, House, Neighbourhood and City for each educational level: pre-school, primary school and high school (which is 4 years of secondary school (ESO) and the last 2 years of high school). At the end of the article, we show the different workshops that were held in order to analyze the goodness of the proposal.
A Machine-Learning Approach to Predicting the Achievement of Australian Students Using School Climate; Learner Characteristics; and Economic, Social, and Cultural Status
Authors: Khine Myint Swe , Liu Yang , Pallipuram Vivek K. , Afari Ernest
Published: December 2024

The Programme for International Student Assessment (PISA) is a global survey conducted by the Organisation for Economic Co-operation and Development (OECD) to assess educational systems by evaluating the academic performance of 15-year-old school students in mathematics, science, and reading. In PISA 2022, 13,437 students from Australia participated in the test. While the PISA main questionnaire assesses the subject knowledge, the student background questionnaire solicits contextual information such as school climate, learner characteristics, and socioeconomic status. This study analyses how these contextual variables predict student achievement using the machine-learning models Ridge Linear Regression, K-Nearest Neighbours, Decision Trees, eXtreme Gradient Boosting, and Support Vector Machines, and it reports the evaluation matrices and the most accurate model in predicting student achievement. The analysis shows that contextual variables are associated with student achievement and account for 42% of the variance in achievement. In addition to evaluating multiple machine-learning regressors, Shapley Additive Explanation (SHAP) analysis is conducted to explain the model predictions and evaluate feature importance. Using SHAP analysis, this paper demonstrates how educators and school administrators may effectively interpret the machine-learning results and devise strategies for student success.
STEM Language Literacy Learning in Engineering Education in Kazakhstan
Authors: Jantassova Damira , Churchill Daniel , Tentekbayeva Zhuldyz , Aitbayeva Saltanat
Published: December 2024

The mastery of STEM (Science-Technology-Engineering-Mathematics) language literacy is essential for both engineering students and professionals as it enables effective communication using technical terminology and facilitates problem-solving, research, and innovation within the field. However, STEM language proficiency remains an area of improvement within Kazakhstan’s engineering education system. Our research focused on enhancing STEM language literacy learning for Bachelor of Engineering students in Kazakhstan, with a specific emphasis on leveraging digital technologies to support their learning. Our paper outlines the outcomes of the research project titled ‘Enhancing Scientific and Professional Language Learning for Engineering Students in Kazakhstan through Digital Technologies’, conducted at the Saginov Technical University (STU) in Kazakhstan and supported by the Science Committee of the Ministry of Science and Higher Education of the Republic of Kazakhstan (Grant No. AP19678460). This project holds significant promise for advancing engineering education in the country. Throughout this project, our team examined best practices for STEM literacy learning in engineering education globally. We also utilised a comprehensive SWOT analysis (Strengths, Weaknesses, Opportunities, and Threats) to identify effective approaches for STEM literacy learning and the successful integration of digital technologies. Ultimately, we developed a framework for enhancing STEM language literacy in engineering education at universities in Kazakhstan.
Integrating IoT and Image Processing for Crop Monitoring: A LoRa-Based Solution for Citrus Pest Detection
Authors: Quispe-Vilca Joel L. , Moreno-Cardenas Edison , Sacoto-Cabrera Erwin J. , Moreno-Cardenas Yackelin
Published: December 2024

Today, agriculture faces many challenges, such as the use of inefficient methods that affect crop quality. Precision agriculture (PA), combined with advanced technologies, improves monitoring, while the integration of wireless communication optimizes processes and resources. This work presents the design of a communication prototype applied in precision agriculture, which allows the acquisition, processing, and wireless transmission of information extracted from the Cotonet pest to The Things Network (TTN) cloud server. This prototype integrates technologies and protocols such as LoRaWAN, Message Queuing Telemetry Transport (MQTT), Internet of Things (IoT) sensors, and Computer Vision. This prototype employs a robust processing and segmentation algorithm, which allows the recognition of pests in citrus plants based on color. The results show that lighting conditions, weather, and time of day influence the quality of the captured images. The relationship between image resolution, brightness, and processing time shows that higher-resolution images (1920 × 1080 pixels per image) provide better detection of pest pixels (greater than 50% of the pest index) but require longer processing time (28.415 ms on average). Furthermore, the developed system effectively detects an index of affection of Planococcus citri (Cotonet) in agricultural plantations through an end-to-end technological implementation that integrates image processing, wireless communication, and IoT technologies.
Deep Contrastive Survival Analysis with Dual-View Clustering
Authors: Cui Chang , Tang Yongqiang , Zhang Wensheng
Published: December 2024

Survival analysis aims to analyze the relationship between covariates and events of interest, and is widely applied in multiple research fields, especially in clinical fields. Recently, some studies have attempted to discover potential sub-populations in survival data to assist in survival prediction with clustering. However, existing models that combine clustering with survival analysis face multiple challenges: incomplete representation caused by single-path encoders, the incomplete information of pseudo-samples, and misleading effects of boundary samples. To overcome these challenges, in this study, we propose a novel deep contrastive survival analysis model with dual-view clustering. Specifically, we design a Siamese autoencoder to construct latent spaces in two views and conduct dual-view clustering to more comprehensively capture patient representations. Moreover, we consider the dual views as mutual augmentations rather than introducing pseudo-samples and, based on this, triplet contrastive learning is proposed to fully utilize clustering information and dual-view representations to enhance survival prediction. Additionally, we employ a self-paced learning strategy in the dual-view clustering process to ensure the model handles samples from easy to hard in training, thereby avoiding the misleading effects of boundary samples. Our proposal achieves an average C-index and IBS of 0.6653 and 0.1786 on three widely used clinical datasets, both exceeding the existing best methods, which demonstrates its advanced discriminative and calibration performance.
Facial Biosignals Time–Series Dataset (FBioT): A Visual–Temporal Facial Expression Recognition (VT-FER) Approach
Authors: Souza João Marcelo Silva , Alves Caroline da Silva Morais , Cerqueira Jés de Jesus Fiais , Oliveira Wagner Luiz Alves de , Pires Orlando Mota , Santos Naiara Silva Bonfim dos , Wyzykowski Andre Brasil Vieira , Pinheiro Oberdan Rocha , Almeida Filho Daniel Gomes de , da Silva Marcelo Oliveira , Barbosa Josiane Dantas Viana
Published: December 2024

Visual biosignals can be used to analyze human behavioral activities and serve as a primary resource for Facial Expression Recognition (FER). FER computational systems face significant challenges, arising from both spatial and temporal effects. Spatial challenges include deformations or occlusions of facial geometry, while temporal challenges involve discontinuities in motion observation due to high variability in poses and dynamic conditions such as rotation and translation. To enhance the analytical precision and validation reliability of FER systems, several datasets have been proposed. However, most of these datasets focus primarily on spatial characteristics, rely on static images, or consist of short videos captured in highly controlled environments. These constraints significantly reduce the applicability of such systems in real-world scenarios. This paper proposes the Facial Biosignals Time–Series Dataset (FBioT), a novel dataset providing temporal descriptors and features extracted from common videos recorded in uncontrolled environments. To automate dataset construction, we propose Visual–Temporal Facial Expression Recognition (VT-FER), a method that stabilizes temporal effects using normalized measurements based on the principles of the Facial Action Coding System (FACS) and generates signature patterns of expression movements for correlation with real-world temporal events. To demonstrate feasibility, we applied the method to create a pilot version of the FBioT dataset. This pilot resulted in approximately 10,000 s of public videos captured under real-world facial motion conditions, from which we extracted 22 direct and virtual metrics representing facial muscle deformations. During this process, we preliminarily labeled and qualified 3046 temporal events representing two emotion classes. As a proof of concept, these emotion classes were used as input for training neural networks, with results summarized in this paper and available in an open-source online repository.
Development and Application of a Safety-Related Control System Implementing a Safety Function for a CNC Milling Machine
Authors: Brtiš Jozef , Ždánsky Juraj , Hrbček Jozef , Rástočný Karol
Published: December 2024

The safety of small CNC (Computer Numerical Control) milling machines is typically ensured through organizational measures. However, when such a CNC milling machine is used in a manner that may involve contact with untrained individuals or children (e.g., for demonstration purposes), it becomes essential to ensure safety through appropriate technical measures. The required safety can be achieved by implementing safety functions to mitigate identified hazards. This paper addresses the design and application of a Safety-Related Control System (SRCS) that implements safety functions for a small CNC milling machine. A notable aspect of this implementation is that commonly available sensors (e.g., optical barriers) with a defined Safety Integrity Level (SIL) are unsuitable for small CNC milling machines in size, cost, and performance parameters. For instance, these sensors might fail to detect the entry of a child’s hand. Consequently, it was necessary to design suitable custom sensors for realizing an SRCS. The paper also demonstrates the achieved SIL for the implemented safety functions.
Comprehensive Technical Inspection of a Medieval Bridge (Ponte de Vilanova, in Allariz) Using Microtechnological Tools
Authors: Elizalde Rubén Rodríguez
Published: December 2024

Ponte de Vilanova, a masonry bridge, was built in Allariz, Galicia in the 13th–14th centuries. It is still standing. The structure, generally well preserved, shows minor deformations and wear signs caused by environmental factors. To conduct a comprehensive assessment without impacting the bridge’s integrity, drones equipped with thermal and underwater imaging technology were employed. Aerial inspections revealed vegetation growth and minor efflorescence (salt deposits) in some areas, while aerial thermography detected temperature variations along the stone joints, indicating the presence of moisture. The granite blocks comprising the bridge showed consistent quality and preservation. The underwater inspection confirmed that the bridge’s piers are well set on the riverbed, with no major damage observed, ruling out the immediate need for repair. This approach allowed a thorough evaluation of submerged parts without requiring divers, enhancing safety and reducing costs.
Effect of the Extruded Pea Hulls on Physicochemical and Sensory Properties of Wheat Bread
Authors: Klava Dace , Galoburda Ruta , Gramatina Ilze , Straumite Evita , Staugis Agris , Reidzane Sanita
Published: December 2024

Incorporating extruded pea hulls (EPH) into wheat bread increases its nutritional value by increasing dietary fiber content, which in turn influences the physicochemical properties and sensory attributes of bread. This study aimed to assess the effect of varying EPH levels on the rheological properties of wheat dough, as well as on the physical and sensory attributes of wheat bread, providing insight into the optimal EPH inclusion level. Farinograph analysis indicated that the inclusion of extruded pea hulls progressively increased the water absorption capacity. At higher EPH replacement levels, bread exhibited decreased specific volume, increased hardness, reduced porosity, darker color, and pronounced sensory attributes of pea aroma and pea taste. Bread with 5–15% EPH retained physical qualities comparable to bread without EPH, with 5% EPH replacement particularly improving specific volume, porosity, and texture. However, 20–30% EPH significantly impaired bread quality, resulting in denser crumb, darker crumb color, and intensified pea aroma. These findings suggest that moderate EPH inclusion (up to 15%) is optimal for enhancing fiber content without compromising bread quality, while higher levels (20% and more) may negatively affect both physical and sensory attributes.
Complex Death Associated with Intra-Hospital Adverse Events and SARS-CoV-2 Pneumonia: Court-Appointed Medico-Legal Evaluation
Authors: Basile Giuseppe , Pisano Graziano , Bolcato Vittorio , Fassina Giovanni , Tronconi Livio Pietro
Published: December 2024

Background: Among the deaths recorded during the COVID-19 pandemic, some were caused by clinical manifestations of venous thromboembolic disease, mainly pulmonary embolism. Several litigations were settled worldwide for professional malpractice associated with COVID-19 and anticoagulant therapy management. The authors aimed to discuss, as court-appointed consultants in civil court, a case settled for compensation against a healthcare facility associated with SARS-CoV-2 infection. Case report: We described the case of an old patient in therapy with a direct oral anticoagulant for thrombotic diathesis, hospitalized for COVID-19 pneumonia, who died after two intra-hospital adverse events influencing coagulation imbalance. Discussion: Two health professionals’ malpractice hypotheses were discussed related to the adverse events’ occurrence: one related to the administration of an enema, resulting in rectal perforation, and the other related to proper anticoagulant prophylaxis and comprehensive coagulation imbalance management after the rectal perforation in a patient at high risk of venous thromboembolic disease. Intra-hospital adverse events complicated the hospitalization and then significantly reduced the concrete possibility, even uncertain in terms of time and extent, of the patient’s living longer, representing the damage of reduced possibilities of survival, also called loss-of-chance damage. Conclusions: The case discussed as court advisors, characterized by clinical and legal complexity, together with SARS-CoV-2 infection, underscores the vital role of forensic examiners in cause-of-death ascertainment and as interpreters of statistical-probabilistic data according to naturalistic, logical, and scientific criteria.
Two-Valued Strongly Group Strategy-Proof Social Choice Functions
Authors: De Simone Anna , Bhaskara Rao K. P. S.
Published: December 2024

We present simple and direct arguments to characterize strongly group strategy-proof social choice functions whose range is of cardinality two. The underlying society is of arbitrary cardinality, and agents can be indifferent among alternatives.
Swelling Behavior of Anionic Hydrogels: Experiments and Modeling
Authors: De Piano Raffaella , Caccavo Diego , Barba Anna Angela , Lamberti Gaetano
Published: December 2024

Polyelectrolyte hydrogels are smart materials whose swelling behavior is governed by ionizable groups on their polymeric chains, making them sensitive to pH and ionic strength. This study combined experiments and modeling to characterize anionic hydrogels. Mechanical tests and gravimetric analyses were performed to track hydrogel mass over time and at a steady state under varying pH and salt concentrations. The swelling ratio exhibited a bell-shaped curve with pH, reaching 120 in pure water, and decreased with increasing salt concentrations. Transient regimes showed slower swelling (~40 h) under pH stimulation compared to faster deswelling (~20 h) induced by salt. A fully coupled model integrating mass transport and solid mechanics was developed, with solvent diffusivity as the sole adjustable parameter in transient simulations. In conclusion, this study combined experiments and modeling to uncover complex mechanisms in PE behavior under two external stimuli, providing insights essential for designing advanced hydrogels.
Geochemical Characteristics of Modern River-Sand and Its Bearing on the Mineral Exploration in the Manufahi Area, Timor-Leste
Authors: Vilanova Vital , Ohtani Tomoyuki , Kojima Satoru , Yatabe Kazuma , Moniz Elizario
Published: December 2024

Geochemical mapping of river sands in the Manufahi area of Timor-Leste revealed potential areas for future mineral exploration. River sand samples from the study area were collected and geochemically analyzed to identify anomalous concentration distributions of several valuable elements and locate potential target areas and geological formations that may host mineral deposits. The 26 major and minor elements were identified using wavelength-dispersive X-ray fluorescence. The river sands exhibited varying elemental concentrations, with Cr, Cu, Zn, and Ba showing deviations from the normal distribution patterns. Identification of geochemical anomalies is an important task in mineral exploration geochemistry. The mean+2 standard deviations (mean+2STD), median+2 median absolute deviations (median+2MAD), and Tukey’s inner fence (TIF) methods were used to determine the geochemical thresholds. This study shows that TIF and principal component analysis (PCA) methods are highly effective in calculating appropriate threshold values and identifying relevant elemental associations. These approaches have proven useful for delineating target areas for mineral deposits, resulting in reliable outcomes. Four predicted target areas with high potential for deposits and mineralization anomalies of Cr, Cu, Ni, and Ba were delineated in the study area.
The Effects of Facies Variability and Bioturbation Intensity on Permeability in a Mixed Siliciclastic–Carbonate Core from the Upper Strawn Group, Katz Field, Eastern Shelf of the Permian Basin, Texas, USA
Authors: Jensen Jerry L. , Flaig Peter P. , Hattori Kelly E.
Published: December 2024

For oil and gas reservoir characterization, permeability prediction is indispensable because it helps identify potential flow pathways and lowers risk. Estimating permeability in heterogeneous media is challenging due to the limited number of measurement tools, low-resolution sampling methods, and sampling bias. To combat these issues, we employed a probe permeameter to produce a high-resolution (4 in [10 cm] spacing) permeability dataset for cores from the Strawn Formation, Katz Field, Permian Basin, Texas, USA. We structured our sampling to record permeability changes related to facies variability and fluctuating bioturbation intensity. We compared probe permeameter data to wireline logs and core-plug porosity and permeability data recorded at larger spacings. The results show that permeability is affected by facies type, bioturbation intensity, and cementation. The effects of bioturbation are non-linear; in our study, moderate bioturbation enhances permeability by improving connections between sands while intense bioturbation decreases permeability by redistributing fines. Core-plug and probe measurements gave similar permeability values, but the number of core plugs taken in the finer-grained intervals was insufficient. The probe, however, provided better resolution and gave larger net-to-gross sand ratios than core-plug-based evaluations. Using only the core-plug porosity–permeability relationship with wireline density log porosities led to permeability predictions too large by a factor of three or more compared to averaged probe permeameter values.
Bedrock Origins from Petrology and Geochemistry: Volcanic Gravel Clasts from the Rawhide Terrace in the Pleistocene Ancestral Mississippi River Pre-Loess Terrace Deposits
Authors: Pizarro Maxwell G. , Gifford Jennifer N. , Starnes James E. , Platt Brian F.
Published: December 2024

Situated throughout the southeastern United States within the Laurentian craton are occurrences of various aged deposits (Late Proterozoic to Early Paleogene) that contain volcanics spanning from lamprophyres to carbonatites and basalts to rhyolites. Several are intrusive, while others have been reworked detritally, deposited as river gravels out onto the Gulf Coastal Plain. The earliest occurrence of igneous gravel clasts in the coastal plain of the lower Mississippi Valley lie along the Mississippi River’s eastern valley wall in the ancestral Mississippi River’s pre-loess terrace deposits (PLTDs). The coarse clastics of the PLTDs are dominantly chert gravels derived from Paleozoic carbonate bedrock, but also include clasts of Precambrian Sioux Quartzite, glacially faceted and striated stones, and ice-rafted boulders, which indicate a direct relationship between the PLTDs and glacial outwash during the cyclic glaciation of the Pleistocene Epoch. The PLTDs also contain the oldest known examples of igneous gravels exposed at the surface in Mississippi. An understanding of their igneous bedrock provenance and the timing of their contribution to the sedimentary record of the lower Mississippi River Valley sheds a valuable light onto the geologic history and evolution of the ancestral Mississippi River during the Pleistocene Epoch. The use of fusion inductively coupled plasma mass-spectroscopy (ICP-MS) in the identification of the igneous suites of one of the pre-loess terraces, well-delineated by geologic mapping, adds important geochemical source data from the gravel constituents for the further interpretation and correlation of the individual PLTD allounits. Gravel constituent geochemistry also offers a better understanding of the evolution of the ancestral Mississippi River watershed and the contributions of bedrock sources during Pleistocene glaciation. This petrological study suggests that the igneous gravels sampled from within the Rawhide PLTD allounit originated from the St. Francois Mountains (SFMs) in southwestern Missouri, with the implications that the SFM igneous terrain was in the direct path of the Independence “Kansan” glaciation. This could indicate a glacial extent further southwest than previously documented.
Prevalence of Maternal Anemia in Southern Jordan: Findings from a Cross-Sectional Study and 5-Year Review
Authors: Al-Kharabsheh Ahlam M. , Alahmad Israa F. , Al-Tamimi Malak M. , Abufraijeh Seham M. , Alnawaiseh Nedal
Published: December 2024

Background: The literature underrepresents maternal anemia in southern Jordan, and national studies often have small sample sizes. According to the 2019 Jordan National Micronutrient Survey, maternal anemia in Jordan accounted for 19.1% of cases, with the majority experiencing mild anemia (17.1%). Among the 29 pregnant women recruited from the southern region, 56.5% had anemia, of which 34.8% had mild and 21.7% had moderate anemia. The current study provides an update on the prevalence of anemia during pregnancy in southern Jordan. Methods: This cross-sectional study was conducted at a government referral hospital in southern Jordan. Pregnant women who visited outpatient clinics were included in the study. Data were collected through face-to-face interviews, and blood samples were collected to measure hemoglobin levels. Descriptive analyses of continuous and categorical variables were performed. Maternal anemia risk factors were assessed using the chi-square test, Fisher’s exact test, and multivariate logistic regression analysis. Statistical significance was defined at p < 0.05. Results: Of the 474 pregnant women who agreed to participate, 36.8% had anemia. Education, income, diet (number of meals and meat consumption), regularity of antenatal care, and supplement use were factors that significantly affected hemoglobin levels (p < 0.05). The adolescent pregnancy rate was 5.3%, and 48% had mild to moderate anemia. Conclusions: Maternal anemia rates in southern Jordan remained high, despite a slow decline. Reducing this burden requires improved access to healthcare and health education, particularly for rural residents who are at greater risk of disease.
Influences of Drying Conditions on Quality Attributes, Taste and Volatile Compounds of Celery Leaves
Authors: Du Yamin , Zhao Yuhan , Zhao Tao , Yang Xiaoying , Qin Ying , Fu Maorun
Published: December 2024

Celery leaves account for 5–10% of the celery weight and are rich in nutrients, but they are usually discarded as waste. To explore this resource, hot-air drying (HA), intermittent hot-air drying (IHA-A and B), vacuum hot-drying and freeze-drying (VH and VF) were used to systematically investigate the effects of drying conditions on quality attributes, taste and volatile compounds of celery leaves. VF could better maintain the quality attributes, while IHA-B leaves were rich in taste and volatile components. The results indicated that both drying temperature and vacuum environment had significant effects on quality attributes. In terms of taste, reducing the drying temperature enriched the taste of celery leaves; however, in vacuum drying, the high temperature could contribute to increase the contents of total free amino acids and bitter amino acids. For volatile compounds, different drying conditions gave celery leaves different aromas, and IHA treatments resulted in a significantly higher content of volatile compounds than other treatments.
Brazil’s Daily Precipitation Concentration Index (CI) Using Alternative Fitting Equation and Ensemble Data
Authors: Núñez-González Gerardo
Published: December 2024

In recent years, precipitation concentration indices have become popular, and the daily precipitation concentration index has been widely used worldwide. This index is based on the Lorenz curve fitting. Recently, some biases in the fitting process have been observed in some research. Therefore, this research’s objective consisted of testing the performance of one alternative equation for fitting the Lorenz curve through the analysis of the daily precipitation concentration in Brazil. Daily precipitation data from 735 time series were used to fit the Lorenz curve and calculate the concentration index. Therefore, the goodness of fit was evaluated to determine which equation better describes the empirical data. Results show that the mean value for the concentration index based on Equation (1) was 0.650 ± 0.079, while the mean value based on Equation (2) was 0.624 ± 0.070. The results of the fitting performance show a better fitting with Equation (2) compared to Equation (1) as indicated by R2, RSS, and RMSE values, R2 = 0.9959 for Equation (1) versus 0.9996 for Equation (2), RSS = 252.78 versus 22.66, and RMSE = 1.5092 versus 0.0501. Thus, Equation (2) can be considered an alternative to improve the calculation of the concentration index.
The First Use of the Washington Group Short Set in a National Survey of Japan: Characteristics of the New Disability Measure in Comparison to an Existing Disability Measure
Authors: Saito Takashi , Imahashi Kumiko , Yamaki Chikako
Published: December 2024

A Japanese national representative survey—the comprehensive survey of living conditions (CSLC)—included the Washington Group Short Set (WGSS) in 2022. This study aimed to characterize the WGSS in comparison to an existing disability measure (EDM), regarding the difference between disability prevalence defined by these two measures and the factors attributable to disagreements between them. A cross-sectional analysis using secondary data from the CSLC (n = 32,212) was conducted. The disability prevalences and their ratios (WGSS to EDM) were computed overall and by demographic sub-groups. Binomial logistic regression analyses were performed to explore factors relating to disagreements that functioned to relatively lower/increase the prevalence defined by the WGSS. Consequently, the prevalences defined by the WGSS and EDM were 10.7% (95% confidence interval (CI): 10.4–11.1) and 13.1% (95%CI: 12.7–13.5), respectively. The ratios by the sub-groups were around 0.80–0.90, with the exception of the age-defined sub-group, whose ratios were 0.63 (older sub-group) to 1.23 (child sub-group). Age was the only independent factor associated with two types of disagreements: older age (odds ratios: 1.23–1.80) was associated with disagreement functioning to relatively lower the prevalence defined by the WGSS, and similarly, younger age (ORs: 1.42–2.79) increased the figure. The WGSS may be characterized as being less susceptible to the influence of aging compared to the EDM.
Exploring the Activity-Travel Patterns of Multi-Purpose Commuters on Workdays Based on Activity Chains and Time Allocation: Evidence from Kunming, China
Authors: He Mingwei , Chen Na , He Yueren , Li Jianbo , Liu Yang
Published: December 2024

Understanding activity-travel patterns and their determinants with regard to multi-purpose commuters is essential for enhancing commuting efficiency and ensuring equal participation in activities. This study applies sequence analysis and hierarchical clustering to identify distinct activity-travel patterns of Kunming commuters using 2016 Household Travel Survey data. Subsequently, a multinomial logistic regression model (MNL) examines the factors influencing these patterns. The results reveal significant heterogeneity across four activity-travel patterns: the fixed commuter pattern (FCP), characterized by pronounced morning and evening peaks with minimal non-commuting activities; the balanced commuter pattern (BCP), where commuters participate in non-commuting activities after afternoon work; the restricted commuter pattern (RCP), with non-commuting activities occurring after midday work; and the flexible commuter pattern (FLCP), featuring a late-start work pattern where some commuters go to work after 5 pm. Additionally, the study finds that female commuters and those with longer commuting and working hours tend to have simpler time allocation. Conversely, male commuters, those from complex family structures, car-owning households, and residents in areas with abundant activity opportunities actively engage in non-commuting activities. These findings can help policymakers optimize travel services and develop heterogeneous commuting and transportation policies.
UniFlow: Unified Normalizing Flow for Unsupervised Multi-Class Anomaly Detection
Authors: Zhong Jianmei , Song Yanzhi
Published: December 2024

Multi-class anomaly detection is more efficient and less resource-consuming in industrial anomaly detection scenes that involve multiple categories or exhibit large intra-class diversity. However, most industrial image anomaly detection methods are developed for one-class anomaly detection, which typically suffer significant performance drops in multi-class scenarios. Research specifically targeting multi-class anomaly detection remains relatively limited. In this work, we propose a powerful unified normalizing flow for multi-class anomaly detection, which we call UniFlow. A multi-cognitive visual adapter (Mona) is employed in our method as the feature adaptation layer to adapt image features for both the multi-class anomaly detection task and the normalizing flow model, facilitating the learning of general knowledge of normal images across multiple categories. We adopt multi-cognitive convolutional networks with high capacity to construct the coupling layers within the normalizing flow model for more effective multi-class distribution modeling. In addition, we employ a multi-scale feature fusion module to aggregate features from various levels, thereby obtaining fused features with enhanced expressive capabilities. UniFlow achieves a class-average image-level AUROC of 99.1% and a class-average pixel-level AUROC of 98.0% on MVTec AD, outperforming the SOTA multi-class anomaly detection methods. Extensive experiments on three benchmark datasets, MVTec AD, VisA, and BTAD, demonstrate the efficacy and superiority of our unified normalizing flow in multi-class anomaly detection.
The Influence of Physical Therapists’ Beliefs and Attitudes About Ageing on Expectations About Outcomes in a Hypothetical Patient
Authors: Hartley Gregory W. , Serrano Mateo , Roach Kathryn E.
Published: December 2024

Background: The aim of this study was to analyze the influence of beliefs and attitudes of practicing physical therapists (PTs) about aging on their expectations concerning the behavior and outcomes of patients with orthopedic conditions. We hypothesized that some beliefs and attitudes would be related to expectations of worse outcomes in older patients compared to clinically identical younger patients. Methods: Seventy-one (71) practicing PTs with a mean age of 40 years (±10.44, range 24–67) were recruited via snowball sampling and asked to participate in a three-part online questionnaire. For part 1, participants were randomly assigned a hypothetical case involving either a 42-year-old or an 85-year-old patient s/p surgical repair of a femoral shaft fracture. Thirty-five (35) participants were randomly assigned to the young case group (YCG) and 37 to the old case group (OCG). Participants were asked questions related to their expectations concerning the patient’s clinical and functional potential, response and adherence to physical therapy, and patient responsibility for their own outcomes. For part 2, all participants completed the Kogan Attitude Toward Old People Scale consisting of 34 paired (positive/negative) statements. Part 3 consisted of subject demographics. Results: Participants in the YCG and the OCG were similar in age (41 vs. 40 years), PT experience (16.7 vs. 14.8 years), gender (82.9% vs. 86.5% female), and positive Kogan score (69.5 vs. 68.2). The groups differed in belief the patient would return to their prior level of function. YCG believed it was “extremely likely”, while the OCG believed it was “moderately likely”. In the OCG, greater likelihood that the patient would return to prior level of function was related to stronger belief that “Most ageing adults are really no different from anybody else” (r = 0.35). Conclusion: In general, physical therapist participants in this study agreed with positive attitudes and beliefs about aging adults as measured by total positive Kogan score. The only outcome expectation that appeared to be influenced by the age of hypothetical patient was return to prior level of function. Although some specific age-related beliefs were correlated to expectation of return to prior level of function, the positive Kogan score was not. It is possible that age related differences in expectations of return to prior level of function were influenced by clinical experience rehabilitating older patients rather than negative attitudes and beliefs about aging.
Australians’ Well-Being and Resilience During COVID-19: The Role of Trust, Misinformation, Intolerance of Uncertainty, and Locus of Control
Authors: Denson Nida , Dunn Kevin M. , Kamp Alanna , Ben Jehonathan , Pitman Daniel , Sharples Rachel , Lim Grace , Paradies Yin , McGarty Craig
Published: December 2024

Background/Objectives: In response to the COVID-19 pandemic, Australian state and federal governments enacted boarder closures, social distancing measures, and lockdowns. By the end of October 2020, the 112-day lockdown in the Australian state of Victoria was the longest continuous lockdown period internationally. Previous studies have examined how the COVID-19 pandemic and government restrictions have affected Australians’ mental health and well-being; however, less is known about the relationship between psychological variables and well-being. Methods: We administered a national survey of Australians aged 16 years and over (N = 1380) in November 2020 to examine the psychological factors that promoted and hindered Australians’ well-being and resilience during the first year of the pandemic. Results: Our study found that Australians reported normal to moderate levels of anxiety, moderate stress, mild depression, and moderate to high loneliness. Interpersonal trust was consistently a protective factor for well-being and resilience and was associated with less depression, anxiety, stress, and loneliness, and greater resilience. Participants with greater inhibitory anxiety (intolerance of uncertainty) and an external locus of control were more likely to be depressed, anxious, stressed, and lonely, and less resilient, compared with those with less inhibitory anxiety and those who believed that these outcomes were determined by their own actions. COVID-19 beliefs were associated with more depression, anxiety, stress, and resilience. Conclusions: This study seeks to inform the development of mental-health, well-being, and resilience strategies by government agencies, non-government organisations, and healthcare providers in times of crisis and in “ordinary” times.