Miracle-dz/UniFAR-FTUs huggingface dataset:
Improving Pre-service Science Teachers’ Performance in Nomenclature of Aliphatic Hydrocarbons using Flipped Classroom Instruction

This paper reports on a study that sought to improve pre-service science teachers’ performance in the International Union of Pure and Applied Chemistry (IUPAC) nomenclature of aliphatic hydrocarbons using flipped classroom instructional approach (FCA). The study employed a single group pre- and post-test action research design. The sample size consisted of forty-five (45) 1st year pre-service science teachers of Foso College of Education (FOSCO) taking the Introduction to Organic Chemistry I course. A purposive sampling technique of the non-probability sampling procedure was used to select the pre-service science teachers in an intact class. Pre-Service Science Teachers’ Hydrocarbon Concept Diagnostic Test and Pre-Service Science Teachers’ Hydrocarbon Concept Achievement Test were the research instruments used to collect the data. The instruments were pilot-tested at St. Ambrose College of Education and the reliability index found to be 0.75 for the pre-intervention test and 0.78 for the post-intervention test. After 9 weeks of engaging pre-service science teachers through in-class face-to-face activities and out-of-class online interaction of teaching and learning IUPAC nomenclature of aliphatic hydrocarbons, it came to light that pre-service science teachers’ performance had improved greatly after they have been exposed to FCA as an intervention strategy. It was recommended that College of Education chemistry tutors should adopt newly interactive and innovative instructional strategies such as the FCA so as to help pre-service science teachers overcome challenging chemical concepts like the IUPAC nomenclature and other difficult chemistry concepts in and out of colleges or schools.
Simple Adaptive Control for Non-Minimum Phase Autopilot Design

A recent publication uses a difficult design example to show that fuzzy logic may have advantages when compared with classical compensator or with the ubiquitous PID design when uncertainty is concerned. Although in this particular case the application was shown to be successful, convergence of the fuzzy logic algorithm, as well as other time-varying controllers, cannot not be guaranteed unless some preliminary conditions are satisfied. This paper intends to show that further exploitation of the classical design can improve robust performance with uncertainty. This result is then used to create sufficient conditions that guarantee convergence with time-varying controllers, and the paper then shows that simple adaptive control methods can further improve performance and maintain it in changing environments. I. Introduction recent publication 1 has presented successful applications of fuzzy logic in non-minimum phase autopilot design. The authors use a difficult design case to show that fuzzy logic has advantages when compared with classical compensator or with the ubiquitous PID design when uncertainty is concerned. Although this particular fuzzy logic application was successful, convergence with the fuzzy logic algorithm or other adaptive controllers is not inherently guaranteed. This paper intends to show that further exploitation of the basic knowledge on the plant and the uncertainty can be used to create sufficient conditions that guarantee convergence of timevarying controllers. The results are presented here in connection with simple adaptive control that is shown to achieve improved performance along with the guarantee of stability. Successful implementations of simple direct adaptive control techniques in various domains of application have been presented over the last two decades in the technical literature 2-25 . This “simple adaptive control (SAC)” methodology have been introduced by Sobel, Kaufman and Mabus
A GaAs pHEMT MMIC Doherty Power Amplifier for 5G Mobile Handset

The design approach for a developed Doherty power amplifier (DPA) based on the WIN Semiconductors foundry's 0.1 m AlGaAs–InGaAs pHEMT technology is presented in this work. It is shown that altering a driver stage improves the DPA's gain performance. The wideband post-matching approach used here can minimise chip area while increasing average efficiency. The simulation results show that at 4V operation voltage, the monolithic drive load modulation PA produces a maximum output power of 29dBm at 1dB compression point. Over the frequency range of 25-27 GHz, the suggested DPA can give a 15dB power gain, as well as 35 percent PAE at peak power and 29 percent PAE at the 6dB OBO. The MMIC load modulation technique was created for 5G mobile handsets and takes up 4 mm2 of space.
Behavioral Patterns and Professional Attributes of Filipino Subject Teachers in Relation to Students’ Performance

The study generally aimed to determine the behavioral patterns and professional attributes of Filipino subject teachers in relation to students’ performance in selected secondary schools in Area III, Leyte Division. A standardized questionnaire was used to gather information from the Filipino subject teachers regarding their behavioral patterns and professional attributes in relation to the students’ performance. The data were analysed and interpreted with the aid of the statistical tool. Weighted mean was used in determining the behavioral patterns of Filipino subject teachers. As a result of the survey conducted data gathered were the following: Professional attributes of Filipino subject teachers in terms of educational attainment, majority had earned MA units; as to teaching experience, they have rendered 10-14 years; and relative to in-service training, majority of them attended at the division level. With regards to the behavioral patterns of Filipino subject teachers as evaluated by the students, it was perceived good. Further, on the level of students’ performance, they were rated satisfactory performance.
Tremella fuciformis Crude Polysaccharides Attenuates Steatosis and Suppresses Inflammation in Diet-Induced NAFLD Mice

Nonalcoholic fatty liver disease (NAFLD) is a chronic liver disorder characterized by an enhanced accumulation of lipids, which affects around 40% of the world’s population. The T. fuciformis fungus possesses immunomodulatory activity and other beneficial properties that may alleviate steatosis through a different mechanism. The present study was designed to evaluate the effect T. fuciformis crude polysaccharides (TFCP) on inflammatory and lipid metabolism gene expression, oxidative stress, and lipid profile. Mice were divided into groups receiving (a) a normal chow diet (NCD), (b) a methionine–choline-deficient (MCD) diet, and (c) a MCD diet with TFCP. Liver histopathology was performed, and the hepatic gene expression levels were estimated using qRT-PCR. The lipid profiles, ALT, AST, and efficient oxidative enzymes were analyzed using ELISA. The TFCP administration in the MCD-fed mice suppressed hepatic lipid accumulation, lipid metabolism-associated genes (HMGCR, FABP, SREBP, ACC, and FAS), and inflammation-associated genes (IL-1β, TLR4, TNF-α, and IL-6) whilst enhancing the expression of HNF4α genes. TFCP mitigated against oxidative stress and normalized healthy lipid profiles. These results highlighted that TFCP prevents NAFLD through the inhibition of oxidative stress and inflammation, suggesting TFCP would potentially be an effective therapeutic agent against NAFLD progression.
Adolescent media use, parent involvement and health outcomes: a latent class analysis approach

ABSTRACT Media use among early adolescents is nearly ubiquitous and has been associated with important health outcomes such as physical activity, sleep and problematic internet use (PIU). Parent involvement has been recommended as a prevention strategy; it remains unclear how it is associated with media use and health outcomes. The purpose of this study was to develop profiles of media use, parent involvement and health outcomes among adolescents. Early adolescents were recruited to a cross-sectional online survey using the Qualtrics platform and panels. Media use measures included ownership and bedroom use of devices, social media platforms and video games. Parent media involvement assessed media rules and role-modeling. Health measures included physical activity, sleep and PIU. We used latent class analysis (LCA) to identify distinct profile groups across these three areas. The 1155 participants had a mean age of 13.6 years (SD = 1.1), of whom 49.7% were female, 73.7% were White and 61.1% had parent education with a college degree. We found that most participants owned personal media devices, including smartphones (81.4%), computers (64.6%) and video game systems (58.9%). The LCA identified three distinct profile groups: (1) Active Autonomous Media Users, (2) Young Low-Tech Sleepers and (3) Risky Regulated Media Users. Findings support that media use patterns vary across adolescents, suggesting different education and prevention approaches may be needed. Targeting educational messages to different media profiles may be an effective strategy to optimize productive media use and health.
Heterogeneous Skin Phantoms for Experimental Validation of Microwave-Based Diagnostic Tools

Considerable exploration has been done in recent years to exploit the reported inherent dielectric contrast between healthy and malignant tissues for a range of medical applications. In particular, microwave technologies have been investigated towards new diagnostic medical tools. To assess the performance and detection capabilities of such systems, tissue-mimicking phantoms are designed for controlled laboratory experiments. We here report phantoms developed to dielectrically represent malign skin lesions such as liposarcoma and nonsyndromic multiple basal cell carcinoma. Further, in order to provide a range of anatomically realistic scenarios, and provide meaningful comparison between different phantoms, cancer-mimicking lesions are inserted into two different types of skin phantoms with varying tumor–skin geometries. These configurations were measured with a microwave dielectric probe (0.5–26.5 GHz), yielding insight into factors that could affect the performance of diagnostic and detection tools.
LAGRANGIAN MULTIPLIER / MATRIX PARTITIONING APPROACH FOR THE SOLUTION OF THE MUSCLE LOAD DISTRIBUTION PROBLEM

The paper presents a musculoskeletal biomechanical model which resides in the Simulink / MATLAB environment and is suitable for the analysis of sporting activities. The model can be used to calculate ground reaction forces, muscles, joint and skeletal component loadings. The model is currently being used at over 150 research institutions and because of its short learning curve is especially suitable for undergraduate teaching. The calculation of the muscle loading distribution is calculated by minimising an objective function. The optimisation approach implemented uses a Lagrangian multiplier technique and is supplemented by a matrix partitioning method to apply inequality constraints. This technique is capable of calculating the muscle force distribution in near real time using the limited resources of a laptop computer.
Aesthetics as a Habit: Between Constraints and Freedom, Nudges and Creativity

This paper is a preliminary attempt to bring to the fore some questions and issues regarding the role of habits in aesthetics. Indeed, much attention has recently been given to habits across a wide range of fields of inquiry: philosophers turn to the concept to investigate its significance to the historical development of Western thought; neuroscientists look into the role that habits play in the functioning of the human mind and identify the neural and psychological underpinnings of habitual behavior; anthropologists, political scientists and sociologists tap into habits as a key notion to explain social dynamics and collective behavior. For all of these waves that the notion has made in other parts of the humanities and social sciences, there have been so far, however, only a few sustained discussions of habits in conjunction with aesthetics. What is the role of habits in aesthetic experience? How do habits influence and regulate artistic creative processes?
GasBotty: Multi-Metric Extraction in the Wild

The lived environment, particularly when proximal to roadways, is filled with multi-digit and multi-numbered values corresponding to advertised commodities. The reliable detection of single multi-digit values from natural imagery has been widely studied through the last decade (e.g. Street View House Numbers SVHN); however, extraction and assignment of the contextual meaning of those values are far more difficult given the diversity and unstructured nature of advertisements. To operationalize information extracted from detected values in the wild, the contextual meaning that those values represent is critical. To our knowledge, no large-scale visual dataset comprising multi-digit, multi-number values with associated context labels exists; we denote this class of problems as "multi-metric extraction in the wild". In this work, we focus on the accurate detection and reading of gas prices, and their contextual association to gas grade and payment type. We provide complete annotations for the Gas Prices of America (GPA) dataset, comprising 2,048 training and 512 test images sampled across the United States including over 2,600 signs, 6,000 prices, 27,000 digits, and 7,800 gas grade and payment type labels. With these data, we develop the GasBotty predictor, a composite neural network model, and evaluate it over eight benchmark tasks of increasing difficulty. Finally, we define a new highly stringent, binary-type metric, denoted "All-or-Nothing Accuracy" (ANA), requiring that a predictor perfectly extract and correctly associate all information in a gas sign. Our proposed model achieves 72.9% ANA over the independent test set of 512 images, where conventional state-of-the-art models object detection models and both a uniform random and biased random predictor would all tend towards 0% ANA. GasBotty and the GPA dataset will serve as a valuable benchmark for the development of future multi-metric extraction in the wild systems.
The PM6-FGC Method: Improved Corrections for Amines and Amides

Recently, we reported a new approach to develop pairwise analytical corrections to improve the description of noncovalent interactions, by approximate methods of electronic structures, such as semiempirical quantum mechanical (SQM) methods. In particular, and as a proof of concept, we used the PM6 Hamiltonian and we named the method PM6-FGC, where the FGC acronym, corresponding to Functional Group Corrections, emphasizes the idea that the corrections work for specific functional groups rather than for individual atom pairs. The analytical corrections were derived from fits to B3LYP-D3/def2-TZVP (reference). PM6 interaction energy differences, evaluated for a reduced set of small bimolecular complexes, were chosen as representatives of saturated hydrocarbons, carboxylic, amine and, tentatively, amide functional groups. For the validation, the method was applied to several complexes of well-known databases, as well as to complexes of diglycine and dialanine, assuming the transferability of amine group corrections to amide groups. The PM6-FGC method showed great potential but revealed significant inaccuracies for the description of some interactions involving the –NH2 group in amines and amides, caused by the inadequate selection of the model compound used to represent these functional groups (an NH3 molecule). In this work, methylamine and acetamide are used as representatives of amine and amide groups, respectively. This new selection leads to significant improvements in the calculation of noncovalent interactions in the validation set.
‘The Talk’: Risk, Racism and Family Relationships

Parents employ a wide range of anticipatory strategies to prepare their children for, and protect them against, risks of racism. This article argues that, while black children need to be equipped with the skills and understanding to navigate racist societies, these practices are also the site of a significant injustice for minority families. Specifically, the imperative to take strategic steps to protect children against threats of racism creates unfair barriers to the enjoyment of some valuable relationship-based goods. In advancing this argument, the article brings recent philosophical work on the family into dialogue with a rapidly developing body of empirical research on racial and ethnic socialization. I show that Brighouse and Swift’s ‘familial relationship goods’ framework generates a valuable new perspective on some contested empirical terrain. But I also highlight, and seek to begin to redress, a problematic silence on race within contemporary philosophy of the family.
Laser-based techniques for micro-optics and photonics

Here, the structures fabricated using direct laser writing and interference lithography techniques are demonstrated. By the tightly focused femtosecond laser beam in the thin gold film, various structures such as the gold bumps, needles, or cones can be fabricated. The shape of the gold structures depends on the used laser pulse energy. By the treatment of the thin films using nanosecond laser pulses, the direct synthesis of nanoparticles on the glass substrate can be realized. The laser processing of photopolymers enables the formation of structures suitable for micro-optics.
Fast extraction of winter wheat planting area in Huang-Huai-Hai Plain using high-resolution satellite imagery on a cloud computing platform

: To extract regional winter wheat planting area using higher-resolution satellite imagery still faces many challenges due to large data size and long processing time in traditional remote sensing classification. Google Earth Engine (GEE), a cloud computing analysis platform based on global geospatial analysis, provides a new opportunity for rapid analysis of remote sensing data. In this study, high-quality Landsat-8 imagery was used to extract the winter wheat planting area from the Huang-Huai-Hai Plain in China. The random forest algorithm was used to identify and map the winter wheat sown in 2019 and harvested in 2020, and Sentinel-2 imagery was used to verify the results. The spectral indices, texture, and terrain features of the image were derived, and their contribution to the classification accuracy of winter wheat was evaluated by scoring. Then the top nine features were selected to form an optimal feature subset. Comparing the set of thirty-four features and the optimized feature subset as the input variables of the random forest classifier, the results show that the accuracy difference between the two feature classification schemes is small, but the classification effect of all feature sets is slightly better than the optimal feature subset. The overall classification accuracy of sample plots verification was 86%-95%, the Kappa coefficient was between 0.70 and 0.85, and the percentage error of the total area was 5.42%. The research demonstrates a reliable method for mapping a wide range of winter wheat planting area, and provides a good prospect for exploring the precise mapping of other crops, which is of great significance to crop monitoring and agricultural development. Fast extraction of winter wheat planting area in using high-resolution satellite imagery on a cloud computing platform.
Determination of the Antimethanogenic Properties of Sumac Leaves (Rhus coriaria L.) Subsitution at Different Ratios İnstead of Corn Silage in Sheep Rations by in Vitro Gas Production Method

This study was carried out to determine the effects of different doses (10, 20 and 30%) of sumac shrub leaf substitution instead of corn silage in sheep rations on in vitro gas and methane production, metabolic energy (ME), net energy lactation (NEL) and organic matter digestion degree. Sheep ration consisting of corn silage (20%), alfalfa straw (22.5%), dry meadow grass (20%), and commercial feed (37.5%) constituted the control group. The experimental groups were formed by substituting 10 (S1), 20 (S2) and 30 (S3) percent sumac shrub leaves for corn silage in the control (C) group formed the experimental groups. The effect of sumac shrub leaf substitution on in vitro gas and methane production, metabolic energy, net energy lactation, and organic matter digestion degree was found to be significant. The 24-hour in vitro gas production values of rations ranged between 43.11- 46.77 ml/200 mg DM, methane production values 6.8-7.48 ml, metabolic energy values 8.91-9.41 MJ/kg DM, net energy lactation, 5.59-5.95 MJ/kg DM and organic matter digestion degree values found between 64.25 and 67.61%. As a result, it was determined that increasing doses of sumac shrub leaf substitute reduced gas and methane production. In addition, it was concluded that the data obtained should be supported by determining the microorganism counts, feed consumption amounts, and feed efficiency coefficients with in vivo studies.
Role of Late Gadolinium Enhancement in the Assessment of Myocardial Viability

Background: Prior to any revascularization procedure for coronary artery disease, it is essential to identify viable myocardium which will likely benefit from it. In such a situation, delayed enhanced cardiac MRI is beneficial. Methods: Our study consisted of 50 patients with at least a one-month prior history of myocardial infarction (MI), abnormal findings on electrocardiography (ECG), and 2D-echocardiography (2D-ECHO), who were subjected to cardiac MRI performed on a 3T MRI machine. The MRI scans were evaluated for anatomical and especially functional characteristics of the heart, such as wall motion. On late gadolinium enhancement (LGE), the diseased segments were classified into two categories: < 50% LGE (viable) and > 50% LGE (non-viable). Results: Of the 378 diseased segments detected on LGE, 137 (36.2%) segments showed < 50% LGE and 241 (63.8%) segments showed > 50% LGE. The segments showing < 50% LGE showed normokinesia or hypokinesia, with none of the segments showing akinesia or dyskinesia, whereas the segments showing > 50% LGE showed akinesia or dyskinesia predominantly. This was found to be statistically highly significant (p-value < 0.001). Conclusion: Delayed enhanced-cardiac magnetic resonance (DE-CMR) imaging in patients with ischemic heart disease (IHD) helps evaluate the severity of the infarcted myocardium by classifying the diseased myocardium into viable and non-viable, as viable myocardium is more likely to regain functional recovery than non-viable myocardium. It also predicts the functional recovery of the myocardium after revascularization therapy.