Miracle-dz/UniFAR-FTUs huggingface dataset:
Chitosan, Chitosan/IgG-Loaded, and N-Trimethyl Chitosan Chloride Nanoparticles as Potential Adjuvant and Carrier-Delivery Systems

This work proposes a feasible, reproducible, and low-cost modified method to manufacture chitosan, chitosan/IgG-protein-loaded, and trimethylated chitosan nanoparticles, using microfluidics combined with the microemulsion technique, which differs from the traditional batch process of chitosan-based nanoparticles. The synthesis process consists of generating microreactors of chitosan-based polymer in a poly-dimethylsiloxane ψ-shaped microfluidic device and then crosslinking with sodium tripolyphosphate outside the cell. Transmission electron microscopy demonstrates an improvement in size control and distribution of the solid-shape chitosan nanoparticles (~80 nm) compared to the batch synthesis. Regarding chitosan/IgG-protein-loaded nanoparticles, these presented a core-shell morphology having a diameter of close to 15 nm. Raman and X-ray photoelectron spectroscopies confirmed the ionic crosslinking between the amino groups of chitosan and the phosphate groups of sodium tripolyphosphate in the fabricated samples and the total encapsulation of IgG protein during the fabrication of chitosan/IgG-loaded nanoparticles. Then, an ionic crosslinking and nucleation-diffusion process of chitosan-sodium tripolyphosphate was carried out during the nanoparticle formation, with and without IgG protein loading. The use of N-trimethyl chloride chitosan nanoparticles in vitro on human-keratinocyte-derived cell line HaCaT did not show side effects independently of its concentration from 1 to 10 μg/mL. Therefore, the proposed materials could be used as potential carrier-delivery systems.
Cultivating Customer Purchase Intention through Meaningful Social Media Marketing Activities

This research was conducted in Bandung, Indonesia, to obtain empirical evidence regarding the variety of social media marketing activities that can significantly increase consumer purchasing intentions. This study uses a quantitative approach to the object of research in social media marketing activities and consumer purchasing intentions. This study uses an action research strategy through the stages of planning, action, observing, and reflecting for six months. The research participants consist of owners as researchers and consumers as respondents who will directly assess the results of the actions taken. Data collection related to the assessment of the action research results was carried out randomly using an online questionnaire as an instrument. The data analysis technique used descriptive analysis and verification analysis with SPSS20. Empirical evidence states that entertaining, interactive, up-to-date, campaign, and customized social media marketing activities can positively and significantly increase consumer purchasing intentions. The results of this study provide evidence that can help fashion businesspeople plan marketing strategies through their social media.
X-Rel: Energy-Efficient and Low-Overhead Approximate Reliability Framework for Error-Tolerant Applications Deployed in Critical Systems

Triple modular redundancy (TMR) is one of the most common techniques in fault-tolerant systems, in which the output is determined by a majority voter. However, the design diversity of replicated modules and/or soft errors that are more likely to happen in the nanoscale era may affect the majority voting scheme. Besides, the significant overheads of the TMR scheme may limit its usage in energy consumption and area-constrained critical systems. However, for most inherently error-resilient applications such as image processing and vision deployed in critical systems (such as autonomous vehicles and robotics), achieving a given level of reliability has more priority than precise results. Therefore, these applications can benefit from the approximate computing paradigm to achieve higher energy efficiency and a lower area. This article proposes an energy-efficient approximate reliability (X-Rel) framework to overcome the aforementioned challenges of the TMR systems and get the full potential of approximate computing without sacrificing the desired reliability constraint and output quality. The X-Rel framework relies on relaxing the precision of the voter based on a systematical error bounding method that leverages user-defined quality and reliability constraints. Afterward, the size of the achieved voter is used to approximate the TMR modules such that the overall area and energy consumption are minimized. The effectiveness of employing the proposed X-Rel technique in a TMR structure, for different quality constraints as well as with various reliability bounds, is evaluated in a 15-nm FinFET technology. The results of the X-Rel voter show delay, area, and energy consumption reductions of up to 86%, 87%, and 98%, respectively, when compared to those of the state-of-the-art approximate TMR voters. Also, the effectiveness of the proposed X-Rel-based TMR structure is assessed in four benchmark applications from different domains. For these benchmarks, the results show <inline-formula> <tex-math notation="LaTeX">$1.59\times $ </tex-math></inline-formula>, <inline-formula> <tex-math notation="LaTeX">$2.35\times $ </tex-math></inline-formula>, and <inline-formula> <tex-math notation="LaTeX">$3.39\times $ </tex-math></inline-formula> energy-delay-area-product (EDAP) reduction for less than 1%, 5%, and 10% output quality degradations, respectively. Finally, an image processing application is benchmarked to evaluate the X-Rel framework efficacy in the presence of errors, where the results show up to a <inline-formula> <tex-math notation="LaTeX">$4.78\times $ </tex-math></inline-formula> higher output image quality in comparison with the typical TMR voters.
Telling an Untold Story of Pedagogical Practices in Mathematics Education in Nepal: Envisioning an Empowering Pedagogy

Conventional mathematics education practice glorifies the hypothetico-deductive reasoning and accompanying reductionist and piecemeal pedagogy and pushes us into the grips of pouring and 'one-size-fits-all' approach (Freire, 1993; Luitel, 2009; Lamichhane, 2021). It is still being practiced and occupies the dominant role in our schools and universities. In this background, the objectives of this research were to explore the roles of existing pedagogy behind a formation of a transmissionist image of pedagogy, thereby envisioning empowering/ humanizing pedagogical practices. In so doing, I deployed an autoethnography research design (Bochner & Ellis, 2016) under interpretive, critical, and postmodern paradigms (Taylor, Taylor, & Luitel, 2012). Writing as a method of inquiry (Richardson & St. Pierre, 2017) has been used to generate field texts. To interpret and make meaning from the textual information, I have used Habermas's Knowledge Constitutive Interests (Habermas, 1972) and Jack Mezirow's Transformative Learning Theory (Mezirow, 1991) as theoretical referents. I have captured the pedagogical practices under three themes: -practice makes a man perfect! I am a successful teacher; he is our supporter! Please protect him! and I do not know anything! Prepare them for the exam. Likewise, a metaphor of empowering/humanizing pedagogy has been proposed as an inclusive pedagogy. Finally, I revealed that empowering/humanizing pedagogy supports connecting mathematical activities to the lifeworld of the learners. It promotes agentic aspects of the learners and helps them to become informed and conscious citizens so that they can contribute to creating an inclusive and socially just society.
A Global Assessment of the Controls on the Fractionation of Arc Magmas

During the differentiation of arc magmas, fractionating liquids follow a series of cotectics, where the co‐crystallization of multiple minerals control the melt compositional trajectories, commonly referred to as liquid lines of descent (LLD). These cotectics are sensitive to intensive properties, including fractionation pressure and melt H2O concentration, and changes in these variables produce systematic differences in the LLDs of arc lavas. Based on a compilation of experimental studies, we develop two major element proxies that exploit differences in LLDs to constrain the fractionation conditions of arc magmas. Near‐primary fractionating magmas evolve along the olivine‐clinopyroxene cotectic, which is pressure‐sensitive. We use this sensitivity to develop a proxy for early fractionation pressure based on the normative mineral compositions of melts with 8 ± 1 wt. % MgO. Fractionation in more evolved magmas is controlled by the clinopyroxene‐plagioclase cotectic, which is strongly sensitive to magmatic H2O contents. We use this relationship to develop an H2O proxy that is calibrated to the normative mineral components of melts with 2–4 wt. % MgO. These two proxies provide new tools for estimating the variations in pressure and temperature between magmatic systems. We applied these proxies to compiled major element data and phenocryst assemblages from modern volcanic arcs and show that in island arcs early fractionation is relatively shallow and magmas are dominantly H2O‐poor, while continental arcs are characterized by more hydrous and deeper early fractionation. These differences likely reflect variations in the relative contributions of decompression and flux melting in combination with distinct upper plate controls on arc melt generation.
Implementation Data Mining with Naive Bayes Classifier Method and Laplace Smoothing to Predict Students Learning Results

Abstract. The application of information technology in the field of education produces big data. It retains information that can be treated as useful. Having data mining, can be used to model highly useful student performance for educators performing corrective actions against weak students. Purpose: The study was to identify the application and accuracy algorithm Naive Bayes Classifier to predict students' study results. Methods: The prediction system for student learning outcomes was built using the Naive Bayes Classifier and Laplace Smoothing methods using a combination of two Information Gain and Chi Square feature selections. The experiment was carried out 2 times using different dataset comparisons. Result: In the first experiment using a dataset of 80:20, the accuracy Naive Bayes Classifier method with Laplace Smoothing and without Laplace Smoothing showed the same results as 94.937%. On the second experiment to equate dataset 60:40 results of the Naive Bayes Classifier accurate method without Laplace Smoothing only 86.076%, then score a 91.772% accuracy using the Laplace Smoothing. The improvement is caused by a probability of zero that can be worked out with Laplace Smoothing. Novelty: The selection feature process is very important in the classification process. Thus, in this study, information gain and chi square double selections of such features as information gain and so promote accuracy.
New genicular joint angle criteria for flexor muscle (Musculus Semimembranosus) during the terrestrial mammals walking

Background The genicular or knee joint angles of terrestrial mammals remain constant during the stance phase of walking; however, the angles differ among taxa. The knee joint angle is known to correlate with taxa and body mass among extant mammals, yet several extinct mammals, such as desmostylians, do not have closely related descendants. Furthermore, fossils lose their soft tissues by the time they are unearthed, making body mass estimates difficult. These factors cause significant problems when reconstructing the proper postures of extinct mammals. Terrestrial mammals use potential and kinetic energy for locomotion; particularly, an inverted pendulum mechanism is used for walking. This mechanism requires maintaining the rod length constant, therefore, terrestrial mammals maintain their joint angle in a small range. A muscle reaction referred to as co-contraction is known to increase joint stiffness; both the agonist and antagonist muscles work simultaneously on the same joint at the same time. The musculus semimembranosus flexes the knee joint and acts as an antagonist to muscles that extend it. Methods Twenty-one species of terrestrial mammals were examined to identify the elements that constitute the angle between the m. semimembranosus and the tibia based on the period between the hindlimb touching down and taking off from the ground. Measurements were captured from videos in high-speed mode (420 fps), selecting 13 pictures from the first 75% of each video while the animals were walking. The angles between the main force line of the m. semimembranosus and the tibia, which were defined as θsm−t, were measured. Results The maximum and minimum angles between the m. semimembranosus and the tibia (θsm−t) of the stance instance (SI) were successfully determined for more than 80% of the target animals (17 out of 21 species) during SI-1 to SI-13 within ±10° from the mean. The difference between each successive SI was small and, therefore, the θsm−t transition was smooth. According to the results of the total stance differences among the target animals, θsm−t was relatively constant during a stance and, therefore, average θsm−t (θave) can represent each animal. Only Carnivora had a significant difference in the correlation between body mass and θave. In addition, there were significant differences in θave between plantigrade and unguligrade locomotion. Conclusion Our measurements show that θave was 100 ± 10° regardless taxon, body mass, and locomotor mode. Thus, only three points on skeletons need to be measured to determine θave. This offers a new approximation approach for understanding hindlimb posture that could be applied to the study of the hindlimbs of extinct mammals with no closely related extant descendants.
Random Time Division Multiplexing Based MIMO Radar Processing with Tensor Completion Approach

Automotive radar pursues low cost and high performance, and especially hopes to improve the angular resolution under the condition of a limited number of multiple-input–multiple-output (MIMO) radar channels. Conventional time division multiplexing (TDM) MIMO technology has a limited ability to improve the angular resolution without increasing the number of channels. In this paper, a random time division multiplexing MIMO radar is proposed. First, the non-uniform linear array (NULA) and random time division transmission mechanism are combined in the MIMO system, and then a three-order sparse receiving tensor of a range-virtual aperture-pulse sequence is obtained during echo receiving. Next, this sparse three-order receiving tensor is recovered by using tensor completion technology. Finally, the range, velocity and angle measurements are completed for the recovered three-order receiving tensor signals. The effectiveness of this method is verified via simulations.
Predictors of Decreased Quality of Life in Breast Cancer Survivors Five Years After Diagnosis

Purpose Due to improved therapy, early diagnosis, and growing incidence rates, the number of long-term breast cancer survivors is increasing. Survivors can still be affected by aftercare, resulting in reduced quality of life (QoL). Thus, in this study, we investigated possible predictors of decreased physical and social functioning in breast cancer survivors. Methods In a German multicenter prospective study, we enrolled 759 female patients with breast cancer before surgery (t1), and contacted them again 5 years after surgery (t4). Data on QoL were assessed at t4 using the European Organization for Research and Treatment of Cancer QoL Core Questionnaire (EORTC QLQ-C30) and its breast cancer module EORTC QLQ-BR23. Predictors of decreased physical and social functioning were analyzed using logistic regression with odds ratios as effect estimates and 95% confidence intervals. Thresholds for the clinical importance of detrimental effects on QoL were defined according to Giesinger. Results Questionnaires from 759 patients were retrieved at t1. Of these, 456 participated in the study at t4. Poor QoL 5 years after diagnosis was reported by 20%–50% of the participants. Age, mastectomy, chemotherapy, education, employment, cohabitation, psychiatric comorbidities at t1, anxiety, depression, and intensity of physical activity emerged as predictors of decreased physical and social functioning 5 years after diagnosis. Conclusion Relief of symptoms and improvement in the QoL should be priorities in aftercare. Detecting patients with a decreased QoL is a rising challenge. Healthcare providers should take special care of patients aged 50–59 years, patients with psychiatric comorbidities and depression, and patients who have undergone mastectomy.
Effect of Grape Pomace Varieties and Soil Characteristics on the Leaching Potential of Total Carbon, Nitrogen and Polyphenols

Grape pomace (GP) has an added value because of its contribution to carbon (C) and nitrogen (N) in soils when applied as an organic fertilizer. Macronutrients from GP are translocated into the soil after amendment, but little is known about the factors that may influence the mobility of C, N and bioactive molecules, i.e., polyphenols, in the soil column. We investigated the mobility of the macronutrient content of GP, derived from two red (Dornfelder and Pinot noir) and two white grape varieties (Riesling and Pinot blanc). For that, three different soils (loamy sand RefeSol01A, silt loam RefeSol02A and a vineyard soil) were evaluated in a column model using a GP application rate of 30 t ha−1. The three-step lab-scale approach included the analysis of total C, N and polyphenols expressed as total polyphenolic content (TPC) in: (a) the fresh GP, representing the total amount of C, N and TPC; (b) the mobility with rainwater, representing the aqueous extractable fraction and (c) the mobility in the soil column and leaching potential. Our results showed that total C/N ratios were wider in the white GP varieties compared with the red ones. Higher TPC values were measured in Dornfelder and Pinot noir compared with white varieties. Analysis of the water-extractable fraction showed that the C recovery may reach up to 48% in Pinot blanc, which also corresponds to the highest N contribution. Extractable polyphenols were higher in the red compared with the white varieties by a factor of 2.4. C and N were mobilized with rainwater from the GP through the soil column. However, the application rate used in the experiment was not indicative of an accumulation in the soil. Compared with the control (no GP application), C values were significantly higher in the leachates from GP-treated soils, in contrast to N values. Up to 10% of the TPC of the pomace was leached into the soil. The TPC recovery in the soils strongly depended on the combination of soil type and GP variety. Generally, the sandy and more acidic soil showed an even distribution of phenolics with a high recovery rate (up to 92%) compared with more neutral and silty soil. Most of the polyphenol content could accumulate in the upper soil layer (0–10 cm). These results provide the first insights on the mobility of macronutrients in the soil using a column model and point out the need to relate those experiments to soil and GP properties in order to avoid the accumulation of nutrients in soil or mobility to adjacent ecosystems.
Design of an Intrusion Detection Model for IoT-Enabled Smart Home

Machine learning (ML) provides effective solutions to develop efficient intrusion detection system (IDS) for various environments. In the present paper, a diversified study of various ensemble machine learning (ML) algorithms has been carried out to propose design of an effective and time-efficient IDS for Internet of Things (IoT) enabled environment. In this paper, data captured from network traffic and real-time sensors of the IoT-enabled smart environment has been analyzed to classify and predict various types of network attacks. The performance of Logistic Regression, Random Forest, Extreme Gradient Boosting, and Light Gradient Boosting Machine classifiers have been benchmarked using an open-source largely imbalanced dataset ‘DS2OS’ that consists of ‘normal’ and ‘anomalous’ network traffic. An intrusion detection model “LGB-IDS” has been proposed using the LGBM library of ML after validating its superiority over other algorithms using ensemble techniques and on the basis of majority voting. The performance of the proposed intrusion detection system is suitably validated using certain performance metrics of machine learning such as train and test accuracy, time efficiency, error-rate, true-positive rate (TPR), and false-negative rate (FNR). The experimental results reveal that XGB and LGBM have almost equal accuracy, but the time efficiency of LGBM is much better than RF, and XGB classifiers. The main objective of the present paper is to propose a design of an efficient intrusion detection model with high accuracy, better time efficiency, and reduced false alarm rate. The experimental results show that the proposed model achieves an accuracy of 99.92% and the time efficiency comes to be much higher than other prevalent algorithms-based models. The threat detection rate is greater than 90% and less than 100%. Time complexity of LGBM is also very much low as compared to other ML algorithms.
Global judgments of caloric information in younger and older adults

ABSTRACT Viewing sets of food products is common in consumer environments. Previous research on visual perception suggests the phenomena of global judgements (or summary statistical representation), which means that people often extract summary statistical information of multiple objects (e.g., average size, hue) at a glance. Consumers may form summary statistical representations of food products. Despite the growing number of studies on the cognitive processing of food products, global judgements of caloric information and how differences in age influence the global judgements remain unexplored. Here, we aimed to reveal global judgements of caloric perception in younger and older adults. Across two studies, participants (adults in Study 1 and younger and older adults in Study 2) viewed food image sets (single, two, four, or six images) and estimated the average caloric counts. The results revealed that the participants could accurately estimate the average caloric counts to some extent at two set sizes. Moreover, the participants were less able to extract global judgements of caloric information at four and six set sizes. Overall, our findings reveal limited cognitive processing for assessing average caloric content, and age differences modulate the estimation accuracy.