Miracle-dz/UniFAR-FTUs huggingface dataset:
Antifungal Effect of Polymethyl Methacrylate Resin Base with Embedded Au Nanoparticles

Full and partial restorations in dentistry must replicate the characteristics of the patient’s natural teeth. Materials must have good mechanical properties and be non-toxic and biocompatible. Microbes, which can form biofilms, are constantly in contact with restorations. In this study, we investigate how well Candida albicans adheres to a polymethyl methacrylate (PMMA) resin base with gold (Au) nanoparticles. We synthesized Au nanoparticles and characterized them. The average size of Au nanoparticles embedded in PMMA was 11 nm. The color difference ΔE between PMMA and PMMA/Au composites was 2.7 and was still esthetically acceptable to patients. PMMA/Au surfaces are smoother and more hydrophilic than pure PMMA surfaces, and the isoelectric point of both types of surfaces was 4.3. Above the isoelectric point, PMMA/Au surfaces are more negatively charged than PMMA surfaces. The added Au nanoparticles decreased the tensile strength, while the hardness did not change significantly. Adhesion measurements showed that PMMA surfaces modified with Au nanoparticles reduced the extent of microbial adhesion of Candida albicans.
The Effectiveness of Using Discovery Learning-Based Student Worksheets to Improve Students’ Critical Thinking Skills on Heat Transfer Topic

Critical thinking skills are one of the skills that are very important for students to have in the challenging 21st century education era. Therefore, critical thinking skills need to be provided to students through appropriate and well-organized learning processes. One of the learning components that is able to assist teachers in preparing teaching and learning activities in class is to provide teaching materials that are in accordance with the expected learning objectives. One teaching material that can assist teachers in providing critical thinking skills and organizing student learning in class is Discovery Learning-based Student Worksheets. The purpose of this study was to determine the effectiveness of Discovery Learning-based worksheets in an effort to improve the critical thinking skills of fifth grade elementary school students on the topic of heat transfer. This research is a type of pre-experimental research using a one group pre test – post test design. The research subjects consisted of 30 fifth grade elementary school students at SDN 38 Parepare. The sampling technique for this study used a purposive sampling technique with a population of 99 fifth grade students consisting of three classes. The research instrument is a Discovery Learning-based worksheet and a critical thinking skills- test. The analysis technique was in the form of descriptive statistics in the form of N-Gain, effect size, and t-test. Based on the results of the analysis of the three measurements, it can be concluded that the use of Discovery Learning-based student worksheet was significantly effective in improving students' critical thinking skills on the topic of heat transfer.
An Efficient Method for Calculation the Physical Optics Integral by Using Complex Source Beam for Electrically Large Reflector Antenna Applications

ABSTRACT The physical optics method is a widely used radiation and scattering estimation for electrically large-scaled objects, and it is finally reduced to the calculation of highly oscillatory integrals. In this article, the physical optics integrals over the reflecting surface for an incident complex source point is evaluated here in closed form. A complex source point can generate a beam field, which is employed to expand an arbitrary source via a complex extension of the surface equivalence principle. Then the complex source beam expansion method is applied to analyze the field of large reflector antennas via physical optics method. Numerical examples are presented to illustrate the accuracy and efficiency of this complex source beam-physical optics hybrid method for analyzing general parabolic reflectors.
Structural Design of Dual-Type Thin-Film Thermopiles and Their Heat Flow Sensitivity Performance

Aiming at the shortcomings of the traditional engineering experience in designing thin-film heat flow meters, such as low precision and long iteration time, the finite element analysis model of thin-film heat flow meters is established based on finite element simulation methods, and a double-type thin-film heat flow sensor based on a copper/concentrate thermopile is made. The influence of the position of the thermal resistance layer, heat flux density and thickness of the thermal resistance layer on the temperature gradient of the hot and cold ends of the heat flow sensor were comprehensively analyzed by using a simulation method. When the applied heat flux density is 50 kW/m2 and the thermal resistance layer is located above and below the thermopile, respectively, the temperature difference between the hot junction and the cold junction is basically the same, but comparing the two, the thermal resistance layer located above is more suitable for rapid measurements of heat flux at high temperatures. In addition, the temperature difference between the hot and cold contacts of the thin-film heat flux sensor increases linearly with the thickness of the thermal resistance layer. Finally, we experimentally tested the response–recovery characteristics of the sensors, with a noise of 2.1 μV and a maximum voltage output of 15 μV in a room temperature environment, respectively, with a response time of about 2 s and a recovery time of about 3 s. Therefore, the device we designed has the characteristic of double-sided use, which can greatly expand the scope of use and service life of the device and promote the development of a new type of heat flow meter, which will provide a new method for the measurement of heat flow density in the complex environment on the surface of the aero-engine.
Knowledge-guided golf course detection using a convolutional neural network fine-tuned on temporally augmented data

Abstract. The tremendous success of deep learning models such as convolutional neural networks (CNNs) in computer vision provides a method for similar problems in the field of remote sensing. Although research on repurposing pretrained CNN to remote sensing tasks is emerging, the scarcity of labeled samples and the complexity of remote sensing imagery still pose challenges. We developed a knowledge-guided golf course detection approach using a CNN fine-tuned on temporally augmented data. The proposed approach is a combination of knowledge-driven region proposal, data-driven detection based on CNN, and knowledge-driven postprocessing. To confront data complexity, knowledge-derived cooccurrence, composition, and area-based rules are applied sequentially to propose candidate golf regions. To confront sample scarcity, we employed data augmentation in the temporal domain, which extracts samples from multitemporal images. The augmented samples were then used to fine-tune a pretrained CNN for golf detection. Finally, commission error was further suppressed by postprocessing. Experiments conducted on GF-1 imagery prove the effectiveness of the proposed approach.
Graphene on mica probed by scanning tunneling microscopy: networks of ABA and ABC stacked graphene and corrugation of the monolayer

Graphene flakes are prepared on freshly cleaved mica by exfoliation in different environments and studied by scanning tunneling microscopy in ultra high vacuum down to the atomic length scale. On the monolayer, we observed an overall roughness of about 60 pm, after heating the sample to 180{\deg}C which is larger than on similarly prepared multilayers (24 pm) and larger than on monolayers which have been mapped recently by atomic force microscopy without heating (24 pm). A slight preference for a distinct wave length ({\lambda}\simeq8 nm) of corrugations could be determined using an autocorrelation analysis. On few-layer graphene, a triangular network of partial dislocations separating ABC stacked and ABA stacked graphene was found similar to the networks occasionally visible on freshly cleaved HOPG. We found differences in the electronic structure of ABC and ABA stacked areas by scanning tunneling spectroscopy, i.e., a pronounced peak at 0.25 eV above the Fermi level exclusively in the ABA areas, which is largely responsible for the different apparent heights.
Breaking Barriers: Artificial Intelligence Interpreting the Interplay between Mental Illness and Pain as Defined by the International Association for the Study of Pain

Low back pain is one of the main causes of motor disabilities and psychological stress, with the painful process encompassing sensory and affective components. Noxious stimuli originate on the periphery; however, the stimuli are recombined in the brain and therefore processed differently due to the emotional environment. To better understand this process, our objective was to develop a mathematical representation of the International Association for the Study of Pain (IASP) model of pain, covering the multidimensional representation of this phenomenon. Data from the Oswestry disability index; the short form of the depression, anxiety, and stress scale; and pain catastrophizing daily questionnaires were collected through online completion, available from 8 June 2022, to 8 April 2023 (1021 cases). Using the information collected, an artificial neural network structure was trained (based on anomaly detection methods) to identify the patterns that emerge from the relationship between the variables. The developed model proved to be robust and able to show the patterns and the relationship between the variables, and it allowed for differentiating the groups with altered patterns in the context of low back pain. The distinct groups all behave according to the main finding that psychological and pain events are directly associated. We conclude that our proposal is effective as it is able to test and confirm the definition of the IASP for the study of pain. Here we show that the fiscal and mental dimensions of pain are directly associated, meaning that mental illness can be an enhancer of pain episodes and functionality.
Coaching to strengthen critical success factors in integrative care for chronic fatigue patients: the Patient Needs-Resources Model

Theoretical and empirical studies discover that an integrative approach is particularly important in chronic disorders and multiple long-term conditions, such as chronic fatigue. Chronic fatigue syndrome (CFS) is a classic example of a potentially severe, multisystemic illness with a wide diversity of symptoms and the corresponding diagnostic complexity. The prevalence of CFS-like syndromes expanded in the context of the COVID-19 pandemic, increasing the disorder and treatment burden. Thus, this article aimed to draw attention to the possibilities to strengthen the integrative approach to diagnosing and treating chronic disorders and multiple long-term conditions. The main critical success factors identified for integrative approaches were: a holistic approach, that provides a more comprehensive diagnostic and personalized treatment strategy, a multidisciplinary team, and patient engagement. The strengths and weaknesses of these factors were explored and coaching was identified as a potential unifying and reinforcing element. Coaching has a wide spectrum of manifestations clearly representing a holistic approach, that has been successfully used in multidisciplinary team building. Moreover, coaching exposes support addressing the patient engagement issues identified by the Patient Needs-Resources Model (PN-R Model) such as low levels of self-efficacy, optimism, and subjective well-being. Coaching may assist patients to identify and prioritize their goals, becoming aware of their personal resources, developing strategies for managing symptoms, and building skills to increase their self-efficacy and active engagement in the treatment process. Therefore, the authors emphasize coaching as a perspective element of optimization of patient care, that requires additional theoretical and long-term empirical research.
Construction of Facial Skin Temperature-Based Anomaly Detection Model for Daily Fluctuations in Health Conditions

A method for estimating health conditions is required to monitor daily health conditions. Various types of data have been used in healthcare studies; however, imaging data are superior because they allow quick and remote measurements. Thermal face images can be measured safely and economically using infrared thermography. Many physiological and psychological states have been evaluated based on the data from these images. A previous study, using short-term experiments, confirmed that an anomaly detection model constructed using a variational autoencoder enables the detection of anomalous states of thermal face images. A long-term experiment is essential to estimate long-term fluctuating human states, such as health conditions. The purpose of this study is to construct a facial skin temperature-based anomaly detection model for human health conditions. The authors obtained thermal face images with health condition questionnaires for approximately a year. Based on the questionnaire responses, the thermal images in good and poor health conditions were labeled “normal state” and “anomaly state,” respectively. The facial skin temperature-based anomaly detection model for health conditions was constructed using a variational autoencoder with only thermal face images in the normal state. The AUC, which represents anomaly detection performance, was 0.70. In addition, an increasing trend of the performance of the model by learning a wider area of skin temperature was confirmed.
Communication and Decision-making in Public and Private Organisations in Bulgaria

Abstract: Decision-making is a current topic in the management of internal communications in public and private organizations. In the classical concept, decisions are taken independently by the manager, but nowadays it is common for other employees to participate in this process as well. This article represents the results from an empirical study conducted in Bulgarian public and private organizations operating on the territory of the city of Sofia. More than 80 people took park in the survey and a questionnaire for determining the decision-making style GDMSI (General Decision Making Style Inventory) was used. The results show that management and executive personnel have a highly pronounced dependent decision-making style. Managers transfer the responsibility for the decision to other employees in the organizations - the experts. This implies new approaches to communications - to target both experts and managers in an attempt to influence the decision-making process. The research was conducted in the conditions of the Bulgarian cultural environment. Keywords: communications, decision-maker, decision making style, occupation, public organizations, private organizations.
Perceived importance of weight loss and exercise among endometrial cancer survivors with overweight or obesity: Implications for lifestyle modification interventions

Type 1 endometrial cancer (EC) survivors who are overweight or obese are at increased risk of comorbidities and reduced quality of life. Lifestyle modification interventions (e.g., healthy eating, exercise) may help these women reduce excess weight and improve their quality of life. However, existing interventions have shown limited success. Guided by Self‐Determination Theory, the proposed study sought to identify factors associated with perceived importance of weight loss and exercise as well as interest in lifestyle modification interventions (components of extrinsic and intrinsic motivation) among EC survivors with overweight or obesity to inform future intervention development.
Prevention of Inflammation Initiation on Acetic Acid-Induced Ulcerative Colitis in Rats by Malva nicaeensis All.

BACKGROUND Aerial parts of Malva nicaeensis All. are preferred in the prevention and treatment of intestinal infections and hemorrhoids in Turkish traditional medicine. This study is planned to evaluate the pharmacological activity of M. nicaeensis extracts on rats with acetic acid-induced colitis. METHODS The plant material was subsequently extracted with n-hexane, ethanol, and water, respectively. All of these extracts were tested for efficacy in the acetic acid-induced rat colitis model. The aqueous and polysaccharide extracts regulated cytokine levels and antioxidant parameters. Furthermore, the aqueous extract in particular regulated myeloperoxidase and caspase-3 levels in this rat model. In addition, the polysaccharide-rich fraction was separated from the aqueous extract. RESULTS The polysaccharide-rich fraction and aqueous extract regulated cytokine levels and antioxidant parameters. The aqueous extract also positively affected myeloperoxidase and caspase-3 levels. The phytochemical studies revealed that the aqueous extract had the highest phenolic content. In addition, the polysaccharide fraction was found to contain total sugars, sulfated groups, uronic acids, and total proteins in 78.4%, 0.9%, 1.5%, and 14.7%, respectively, and was rich in monosaccharide-type compounds, especially galactose (36.4%). CONCLUSIONS M. nicaeensis was discovered to be a drug lead in the future treatment of irritable bowel diseases or as a complementary therapeutic agent that aided conventional treatments.
Sexual functioning and marital satisfaction among endometriosis patients in Malaysia: a cross-sectional study

Endometriosis affects the sexual functioning and marital satisfaction of couples in a complex manner due to its clinical presentation of the disease. This study aimed to evaluate the prevalence of sexual dysfunction and marital disharmony among women with endometriosis beyond their diagnosis and treatment. A cross-sectional online survey was conducted among women with endometriosis in an endometriosis society at a Malaysian university hospital. Sociodemographic and clinical data were collected. Sexual function was measured using the Malay Version Female Sexual Function Index (MVFSFI), while marital satisfaction was evaluated with the Malay Version Golombok Rust Inventory for Marital Satisfaction (MVGRIMS). A total of 166 patients participated in this survey. The median age was 35 years (Interquartile range, IQR:32.00–39.25 years); 91.6% of participants were Malay. The median score of MVFSFI was 56.00 (IQR: 34.75–68.00). Most of the study subjects (n = 96) reported poor to very severe marital satisfaction problems, equivalent to MVGRIMS transformed score of more than 5. High levels of MVGRIMS scores have a moderately strong negative correlation with lower scores for most domains of the MVFSFI. In the stepwise multiple logistic regression, only MVFSFI total scores (p = 0.029), MVFSFI lubrication scores (p = 0.009), and MVFSFI satisfaction (p = 0.010) scores were significantly associated with poor marital satisfaction. Both sexual dysfunction and marital satisfactions commonly affect women with endometriosis and are closely interlinked. Targeted efforts should be made in multiple aspects to improve the quality of sexual functioning and marital satisfaction among endometriosis patients.
Adaptive Algorithms for Batteryless LoRa-Based Sensors

Ambient energy-powered sensors are becoming increasingly crucial for the sustainability of the Internet-of-Things (IoT). In particular, batteryless sensors are a cost-effective solution that require no battery maintenance, last longer and have greater weatherproofing properties due to the lack of a battery access panel. In this work, we study adaptive transmission algorithms to improve the performance of batteryless IoT sensors based on the LoRa protocol. First, we characterize the device power consumption during sensor measurement and/or transmission events. Then, we consider different scenarios and dynamically tune the most critical network parameters, such as inter-packet transmission time, data redundancy and packet size, to optimize the operation of the device. We design appropriate capacity-based storage, considering a renewable energy source (e.g., photovoltaic panel), and we analyze the probability of energy failures by exploiting both theoretical models and real energy traces. The results can be used as feedback to re-design the device to have an appropriate amount energy storage and meet certain reliability constraints. Finally, a cost analysis is also provided for the energy characteristics of our system, taking into account the dimensioning of both the capacitor and solar panel.
Quantifying the role of photoacclimation and self-facilitation for seagrass resilience to light deprivation

Introduction Light gradients are ubiquitous in marine systems as light reduces exponentially with depth. Seagrasses have a set of mechanisms that help them to cope with light stress gradients. Physiological photoacclimation and clonal integration help to maximize light capture and minimize carbon losses. These mechanisms can shape plants minimum light requirements (MLR), which establish critical thresholds for seagrass survival and help us predict ecosystem responses to the alarming reduction in light availability. Methods Using the seagrass Cymodocea nodosa as a case study, we compare the MLR under different carbon model scenarios, which include photoacclimation and/or self-facilitation (based on clonal integration) and that where parameterized with values from field experiments. Results Physiological photoacclimation conferred plants with increased tolerance to reducing light, approximately halving their MLR from 5-6% surface irradiance (SI) to ≈ 3% SI. In oligotrophic waters, this change in MLR could translate to an increase of several meters in their depth colonization limit. In addition, we show that reduced mortality rates derived from self-facilitation mechanisms (promoted by high biomass) induce bistability of seagrass meadows along the light stress gradient, leading to abrupt shifts and hysteretic behaviors at their deep limit. Discussion The results from our models point to (i) the critical role of physiological photoacclimation in conferring greater resistance and ability to recover (i.e., resilience), to seagrasses facing light deprivation and (ii) the importance of self-facilitating reinforcing mechanisms in driving the resilience and recovery of seagrass systems exposed to severe light reduction events.
Exploring Preschool Parents’ Understanding of Play-based Learning and its Importance in Early Childhood Education

Play, a context identified by Article 31 of the United Nations Convention on the Rights of the Child (CRC) as a human right, contributes significantly to a child’s optimal growth and development. Although play-based learning (PBL) is known as the very core of the “Developmentally Appropriate Practice” (DAP) that is currently observed at the Malaysian preschool context, many preschools do not address play as a critical component for early childhood development. One of the major reasons cited by school administrators is that preschools are pressured by parents and stakeholders for producing high academic achievers and primary-level ready students. The purpose of this study hence was to explore preschool parents itself, to identify further their understanding of play-based learning and their view on the importance of PBL in the early childhood education context. Through the “maximum variation” sampling technique, eighteen parents were selected from seven different states in Malaysia to obtain their views on PBL. Findings from this qualitative study steered six major themes for discussion which include contextualizing the term ‘play’ and ‘play - based learning’, their awareness about PBL as a teaching method, preschool’s initiatives on injecting awareness about play-based learning, their recognition that play-based learning can holistically develop children, their acceptance on PBL as a pedagogy for a child’s development and their concerns of PBL on children’s primary level school readiness.