Miracle-dz/UniFAR-FTUs huggingface dataset:
Evaluation of the Progression of Periodontitis with the Use of Neural Networks

Periodontitis is an inflammatory disease of the tissues surrounding the tooth that results in loss of periodontal attachment detected as clinical attachment loss (CAL). The mildest form of periodontal disease is gingivitis, which is a necessary condition for periodontitis development. We can distinguish also some modifying factors which have an influence on the rate of development of periodontitis from which the most important are smoking and poorly controlled diabetes. According to the new classification from 2017, we can identify four stages of periodontitis and three grades of periodontitis. Grades tell us about the periodontitis progression risk and may be helpful in treatment planning and motivating the patients. Artificial neural networks (ANN) are widely used in medicine and in dentistry as an additional tool to support clinicians in their work. In this paper, ANN was used to assess grades of periodontitis in the group of patients. Gender, age, nicotinism approximal plaque index (API), bleeding on probing (BoP), clinical attachment loss (CAL), and pocket depth (PD) were taken into consideration. There were no statistically significant differences in the clinical periodontal assessment in relation to the neural network assessment. Based on the definition of the sensitivity and specificity in medicine we obtained 85.7% and 80.0% as a correctly diagnosed and excluded disease, respectively. The quality of the neural network, defined as the percentage of correctly classified patients according to the grade of periodontitis was 84.2% for the training set. The percentage of incorrectly classified patients according to the grade of periodontitis was 15.8%. Artificial neural networks may be useful tool in everyday dental practice to assess the risk of periodontitis development however more studies are needed.
Home-Based Sexuality Education in Ghana: The Perspectives of Adolescents and Parents

Abstract The extant literature has explored sexuality education from the perspectives of the adolescents, but the views of parents are largely neglected. The few studies that have examined the views of both parents and adolescents are selective in scope, coverage, and assessment. There is thus, a dearth of data on the type of topics discussed and the frequency of parent-adolescent sexual communication. The present study sought to explore adolescents’ lived experiences of sexuality education and its impact on their sexual and reproductive health. To achieve this, a qualitative research design with a semi-structured interview was employed to gather data from thirty parents and adolescents in Ablekuma South Metropolis. An Interpretative Phenomenological Analysis (IPA) was used in analyzing the data with each theme showing divergence categories of experiences of sexuality education although the views of both parents and adolescents on each category were similar. Parent-adolescent sex communication showed frequently discussed topics and the less discussed ones. Perceptions of sexuality education revealed both positive and negative perceptions. Perceived impact of sexuality education also brought to light both positive and negative impacts. It is recommended that stakeholders ought to institutionalize diverse behavior change interventions such as interpersonal communication and skills training aimed at empowering both parents and adolescents to communicate explicitly about sexuality rather than using euphemisms and timing techniques.
Using the Art of Questioning as Classroom Assessment for Learning English in Pre-service Teaching

Practice teaching is a salient phase for students deployed in the real school settings while they pursue a degree from a Teacher Education Institution (TEI). This mixed-method research examined the types and levels of classroom questioning of pre-service teachers of elementary English in a TEI in Mindanao. It also explored their perceptions and practices in questioning anchored on Kolb’s experiential learning theory. Through purposive sampling, 16 pre-service teachers taking-up Bachelor in English Education with certificate in teaching elementary participated in the study. Their actual classes were recorded and seven of them joined the 30-minute focus group discussion which was transcribed, translated, and analysed thematically. The identified questions were categorized according to the types of questions in classroom discourse and classified as to low and high levels through Bloom’s Revised Taxonomy. Based on the findings, the types of questions were retrieval style and yes or no questions which belonged to low cognitive levels. The participants developed practices to mitigate the challenges of questioning as classroom assessment. A wider exploration to compare results with other pre-service programs in the focused TEI is recommended as the study had relevant implications to teacher development.
Analysis factors that affect participant interest in cattle farm business insurance in Indonesia

The Cattle Business Insurance Program is a protection cow yields program launched by the government to anticipate the risk of loss of farmer due to crop failure. The government started this program in 2015 by working together with an insurance company PT. Jasindo. This program is beneficial for farmer in Indonesia. Unfortunately, the impact of this program is still having a negligible effect on society because there is still a lack of attraction from the farmer to follow this insurance program. This research has a purpose in analyzing factors that caused the farmer’s interest, making them want to join this insurance. We use a structural equation model (SEM) of data that has been obtained to provide the method. Based on the results, we can conclude that the accuracy factor is a dominant factor that influences the farmer’s decision to join the AUTS program. This insurance has been beneficial in developing a better Cattle business insurance program in the future and motivates farmer to join this insurance. For insurance companies, this research has provided information for companies interested in opening similar and better insurance programs to increase the enthusiasm of local farmer and national cattle productions.
A new alternating projection-based prediction–correction method for structured variational inequalities

Recently, some proximal-based alternating direction methods and alternating projection-based prediction–correction methods were proposed to solve the structured variational inequalities in Euclidean space . We note that the proximal-based alternating direction methods need to solve its subproblems exactly. However, the subproblems of the proximal-based alternating direction methods are too difficult to be solved exactly in many practical applications. We also note that the existing alternating projection based prediction–correction methods just can cope with the case that the underlying mappings are Lipschitz continuous. However, it could be difficult to verify their Lipschitz continuity condition, provided that the available information is only the mapping values. In this paper, we present a new alternating projection-based prediction–correction method for solving the structured variational inequalities, where the underlying mappings are continuous. In each iteration, we first employ a new Armijo linesearch to derive the predictors, and then update the next iterate via some minor computations. Under some mild assumptions, we establish the global convergence theorem of the proposed method. Preliminary numerical results are also reported to illustrate the effectiveness of the proposed method.
Transcriptomic Analysis of Human Keratinocytes Treated with Galactomyces Ferment Filtrate, a Beneficial Cosmetic Ingredient

Galactomyces ferment filtrate (GFF, Pitera™) is a cosmetic ingredient known to have multiple skin care benefits, such as reducing redness and pore size via the topical application of its moisturizer form. Although GFF is known to act partly as an antioxidative agonist for the aryl hydrocarbon receptor (AHR), its significance in keratinocyte biology is not fully understood. In this study, we conducted a transcriptomic analysis of GFF-treated human keratinocytes. Three different lots of GFF consistently modulated 99 (22 upregulated and 77 downregulated) genes, including upregulating cytochrome P450 1A1 (CYP1A1), a specific downstream gene for AHR activation. GFF also enhanced the expression of epidermal differentiation/barrier-related genes, such as small proline-rich proteins 1A and 1B (SPRR1A and SPRR1B), as well as wound healing-related genes such as serpin B2 (SERPINB2). Genes encoding components of tight junctions claudin-1 (CLDN1) and claudin-4 (CLDN4) were also target genes upregulated in the GFF-treated keratinocytes. In contrast, the three lots of GFF consistently downregulated the expression of inflammation-related genes such as chemokine (C-X-C motif) ligand 14 (CXCL14) and interleukin-6 receptor (IL6R). These results highlight the beneficial properties of GFF in maintaining keratinocyte homeostasis.
Off-Road Construction and Agricultural Equipment Electrification: Review, Challenges, and Opportunities

Though the current wave of electric vehicles is transforming the on-road passenger and commercial vehicle fleets, similar attempts in the off-road equipment sector appear to be lacking. Because of the diverse equipment categories and varied applications, electrifying off-road equipment requires significant research and development. A successful electrification of such equipment can offer an array of benefits, including reduced air and noise pollution, higher energy efficiency, and increased productivity. This paper provides a review of the current state of technology in off-road equipment electrification, with a focus on the equipment used in construction and agricultural applications. The paper also discusses advantages of, and challenges associated with, electrifying off-road construction and agricultural equipment. In addition, potential solutions for overcoming these challenges as well as opportunities to facilitate the electrification of off-road construction and agricultural equipment are identified.
Fusidic Acid/Tea-Tree Oil Nanoemulsions: A Potentially Safe and Effective Anti MRSA/MSSA Topical Agent for Chronic Wound Healing

Fusidic acid (FA) is clinically used as an antibacterial agent for the treatment of Gram-positive bacterial infections. It interferes with bacterial protein synthesis, specifically by preventing the translocation of the elongation factor G on the ribosome. In the present work, oil-in-water nanoemulsion (NE) was developed as a carrier for the transdermal delivery of FA. Different oils, surfactants and co-surfactants were screened. The solubility of FA, the emulsifying capacity of the surfactants and phase diagrams for each oil and surfactant mix were constructed. From the analysis, eight stable NE formulations were chosen, and their physicochemical properties were further evaluated. The antibacterial activity against methicillin-resistant Staphylococcus aureus (MRSA) and methicillin-sensitive Staphylococcus aureus (MSSA) were also evaluated, and cytotoxicity was conducted on HS-27 cell line to determine the safety of the formula. It was found that the NE produced from tea tree oil has the most optimal stability with promising antibacterial activity against MRSA as compared to a commercially available product. The safety profile of the NE was also comparable to the commercial product; thus, the formulated FA-NE is promising for clinical use.
Hands-on engagement online: using a randomised control trial to estimate the impact of an at-home lab kit on student attitudes and achievement in a MOOC

ABSTRACT A shortcoming of Massive Open Online Courses (MOOCs) is the lack of substantive integration of hands-on activities into online classrooms. We conducted a randomised control trial (RCT) in a MOOC where we sent the treatment group at-home lab kits with which they could perform experiments in their own homes. In our intervention research, we found that, at the end of the course, students in the treatment group had significantly higher exam scores and levels of self-efficacy to perform in the topic area than their control group counterparts. Students’ growth in self-concept was not significantly different. Findings have implications for distance courses in engineering and other science, technology, engineering, and math areas that traditionally have laboratory components. Furthermore, our findings illustrate the potential amplifying effect of this learning environment configuration for engineering instructors. Finally, this study illustrates how the dispersed nature of MOOCs facilitates RCTs and a recursive process linking theory and practice.
Surgical Reconstruction with Tendon Allografting Following Iatrogenic Rupture of the Plantar Fascia: A Case Report

Plantar fasciitis is a common cause of heel pain, and the disorder is generally self-limiting after adequate conservative treatment. When conservative treatment is unsuccessful, surgical release is an effective treatment option. Here we report a case of iatrogenic plantar fascia rupture after surgical release for treatment of recalcitrant plantar fasciitis. Preoperative MRI revealed a 4.2 cm gap between the distal fascia stump and the calcaneal tuberosity in the sagittal view at 8 months post-injury. To circumvent the possibility of rupture site retear or poor tissue healing by direct repair, we used tendon allografting for the reconstruction of the chronic plantar fascia rupture. The patient gradually recovered after the surgery. Complications of plantar fascia rupture after surgical release is a potential risk but rarely observed. Chronic plantar fascia rupture with medial arch collapse is difficult to treat. We used a tendon allograft to reconstruct the plantar fascia, restoring its function and mechanical strength. After 5 years of follow-up, no complications were reported, and magnetic resonance imaging indicated the reconstructed plantar fascia tissue to be in good condition.
On the Mechanical Properties of Hybrid Dental Materials for CAD/CAM Restorations

Two hybrid dental materials available for computer-aided design and manufacturing (CAD/CAM) dental restorations have been selected to explore their potential. On the one hand, the scarcely investigated polymer-based material Vita Enamic® (VE) and, on the other hand, the leucite-based material IPS Empress® CAD (EC). Their micro-structure and mechanical performance were analyzed in two environments: directly as received by the manufacturer (AR), and after immersion and storage in artificial saliva (AS) for 30 days to determine the influence of the saliva effect. To avoid an inappropriate selection of materials for clinical use, a full understanding of their mechanical behavior is essential. Therefore, this investigation aims to determine the micro-structural and chemical composition by field emission scanning electron microscopy (FE-SEM) and X-ray fluorescence analysis, establishing the density, micro- and nano-hardness, the nano-elastic modulus, and the flexural strength and fracture toughness (by introducing a femto-laser notch to replicate a real crack). In addition, fracture surfaces of the broken samples were analyzed to correlate the failure micro-mechanisms with their mechanical properties. Results indicate that while the crystalline phase of the materials is very similar (composed of SiO2 and Al2O3), the micro-structure and mechanical behavior is not. The material EC, with finer micro-structure, exhibits a higher mechanical performance but with greater variability of results. Furthermore, the material VE, with a 25 vol.% polymer phase, shows a mechanical performance similar to enamel and dentin and therefore more similar to human behavior.
FULLY 3D FLUID OUTFLOW FROM A SPHERICAL SOURCE

Abstract We consider fully three-dimensional time-dependent outflow from a source into a surrounding fluid of different density. The source is distributed over a sphere of finite radius. The nonlinear problem is formulated using a spectral approach in which two streamfunctions and the density are represented as a Fourier-type series with time-dependent coefficients that must be calculated. Linearized theories are also discussed and an approximate stability condition for early stages in the outflow is derived. Nonlinear solutions are presented and different outflow shapes adopted by the fluid interface are investigated.
Permanent Magnet Generator with the Tooth-Coil Winding and Saturation Magnetization of the Magnetic Core

This paper considers the advantages and disadvantages of using electric generators with high-coercivity permanent magnets and a tooth-coil winding as a power source in hybrid power plant systems. The requirements of such power generators are considered. In this paper, a special topology of an electric generator with high-coercivity permanent magnets with the use of an additional winding is proposed. The features of the proposed generator topology are shown and its mathematical description is given. For the study of electromagnetic processes, a computer simulation of the proposed generator was performed and the results of modeling were presented. To verify the calculated values of the generator and the results of computer simulation, an experimental study on a prototype of the proposed electric generator with high-coercive permanent magnets was carried out. The results of the experimental study showed high accuracy of computer simulation and numerical calculation.
Congestion-Aware Critical Gradient Scheduling for Distributed Machine Learning in Data Center Networks

Distributed Machine Learning (DML) is proposed not only to accelerate the training of machine learning, but also to solve the inadequate ability for handling a large amount of training data. It adopts multiple computing nodes in data center to collaboratively work in parallel at the cost of high communication overhead. Gradient Compression (GC) is introduced to reduce the communication overhead by reducing the number of synchronized gradients among computing nodes. However, existing GC solutions suffer from varying network congestion. To be specific, when some computing nodes experience high network congestion, their gradient transmission process could be significantly delayed, slowing down the entire training process. To solve the problem, we propose FLASH, a congestion-aware GC solution for DML. FLASH accelerates the training process by jointly considering the iterative approximation of machine learning and dynamic network congestion scenarios. It can maintain good training performance by adaptively adjust and schedule the number of synchronized gradients among computing nodes. We evaluate the effectiveness of FLASH using AlexNet and Resnet18 under different network congestion scenarios. Simulation results show that under the same number of training epochs, FLASH reduces training time 22-71%, maintains good accuracy, and low loss, compared with the existing memory top-K GC solution.
Diagnostics and Identification of Injection Duration of Common Rail Diesel Injectors

Abstract In this paper, we study the diagnostics and identification of injection duration of common rail (CR) diesel pilot injectors of dual-fuel engines. In these pilot injectors, the injected volume is small and the repeatability of the injections and identification of the drifts of the injectors are important factors, which need to be taken into account in achieving good repeatability (shot-to-shot with every cylinder) and therefore a well-balanced engine and reduced overall wear. A diagnostics method based on analysis of CR pressure signal with experimental verification results is presented. Using the developed method, the relative duration of injection events can be identified. In the method, the pressure signal during the injection is first extracted after the control of each injection event. After that, the signal is normalized and filtered. Then a derivative of the filtered signal is calculated. Change in the derivative of the filtered signal larger than a predefined threshold indicates an injection event which can be detected and its relative duration can be identified. The efficacy of the proposed diagnostics method is presented with the experimental results, which show that the developed method detects drifts in injection duration and the magnitude of drift. According to the result, ≥ 10 μs change (2%, 500 μs) in injection time can be identified.
Stability, Antioxidant Activity and Intestinal Permeation of Oleuropein Inclusion Complexes with Beta-Cyclodextrin and Hydroxypropyl-Beta-Cyclodextrin

Compared to beta-cyclodextrins (beta-CD), hydroxypropyl-beta-cyclodextrins (HP-beta-CD) are a more popular material used to prepare inclusion complexes due to their superior solubility and intestinal absorption. In this study, oleuropein (OL) inclusion complexes with beta-CD (beta-CD:OL) and HP-beta-CD (HP-beta-CD:OL) were prepared and the formation of inclusion complexes was validated by IR, PXRD, and DSC. A phase solubility test showed that the lgK (25 °C) and binding energy of beta-CD:OL and HP-beta-CD:OL was 2.32 versus 1.98, and −6.1 versus −24.66 KJ/mol, respectively. Beta-CD:OL exhibited a more powerful effect than HP-beta-CD:OL in protecting OL from degradation upon exposure to light, high temperature and high humidity. Molecular docking, peak intensity of carbonyls in IR, and ferric reducing power revealed that beta-CD:OL formed more hydrogen bonds with the unstable groups of OL. Both inclusion complexes significantly enhanced the solubility, intestinal permeation and antioxidant activity of OL (p < 0.05). Though HP-beta-CD:OL had higher solubility and intestinal absorption over beta-CD:OL, the difference was not significant (p > 0.05). The study implies that lower binding energy is not always associated with the higher stability of a complex. Beta-CD can protect a multiple-hydroxyl compound more efficiently than HP-beta-CD with the intestinal permeation comparable to HP-beta-CD complex.