Miracle-dz/UniFAR-FTUs huggingface dataset:
The Development of Numeracy Test Using Three-Dimensional Framework to Assess Numeracy Skills in Grade 7

A growing body of evidence including international level studies (e.g. PISA, TIMSS) demonstrate that numeracy skills (also known internationally by other terms such as mathematical literacy) is crucial for a person’s educational achievements and for informed and participatory citizenship. Early and successful interventions to improve students’ numeracy skills lie in developing and using valid and reliable diagnostic tests for numeracy skill assessment. This study explored how developing a numeracy test based on three-dimensional framework could be used for numeracy diagnostic purposes in grade 7. To achieve this, initially a three-dimensional numeracy framework based on 1) content knowledge of mathematics, 2) information literacy skills, 3) complexity levels of SOLO taxonomy, was prepared. Then the framework was used to construct a 32-item numeracy test assessing the ability to use relationships, functions and numerical information in different contexts including science. Next, the instrument was administered to 7th grade students (N = 205) in four schools who were asked to complete 3 hour-long tests. Such diagnostic data could inform teachers on students’ numeracy skills and prepare instructional materials that target specific weaknesses in class level. Further, such information could inform personalized student learning instruction and produce improved numeracy diagnostic tests for future use.
A 0.18 μm CMOS Millimeter Wave Antenna-on-Chip with Artificial Magnetic Conductor Design

This paper presents a small-size broadband slot monopole chip antenna for millimeter wave application. Using a 0.18 μm CMOS process, through metal_1, the artificial magnetic conductor (AMC) of the metal layer increased the impedance bandwidth of the chip antenna. The additional inverted C branch was used to achieve a better reflection coefficient. By adding an AMC and inverted C branch, the operating frequency of the chip antenna went to 33.8–110 GHz below the reflection coefficient of −10 dB, and its fractional bandwidth was 103.4%. The maximum gain was −6.3 dBi at 72 GHz. The overall chip size was 1.2 × 1.2 (mm2). Through measurement and verification, the proposed antenna reflection coefficient was close to the simulation trend and had better resonance. The frequency range of the chip antenna proposed in this paper covered the 5G NR FR2 band (24.2 GHz–52.6 GHz) and W-band (75 GHz–110 GHz). The proposed chip antenna can be applied to the Internet of Things, Industry 4.0, biomedical electronics, near field sensing and other related fields.
Sentiment Analysis of Cryptocurrency Trading Platform Service Quality on Playstore Data: A Case of Indodax

Indodax is one of the cryptocurrency trading platforms in Indonesia that has the highest sentiment for the quality they provide, good quality on a platform is an important factor in obtaining user satisfaction and will have an impact on the long-term success of a company. The importance of user satisfaction on cryptocurrency online trading platforms is a significant factor in increasing user loyalty in today's competition. This research was conducted to analyze the quality of existing cryptocurrency trading platform services so that they can be input for cryptocurrency trading service providers to improve the quality of their services, this information can also be considered by prospective platform users in choosing a trading platform that has the best quality of service to minimize losses that may be caused by the platform. In this study, sentiment analysis was used for indodax play store platform users and then processed using the lexicon classification method to produce sentiment analysis for each significant factor of service quality. From the results of the classification carried out in this study, the results of the analysis show that most users are satisfied and give positive sentiments related to security, namely 87.63%, positive sentiments related to the interface design 88.46%, positive sentiments related to service & convenience by 83%, but some users also gave a slightly positive sentiment related to administrative costs, namely 39%, and their negative sentiment was mostly related to the error & failure system, which received more than 80% sentiment. While the recall value is 38.07%, the precision is 56.69% and the f1-score is 45.55%. The results of this study can be concluded that there are still many important points that must be improved in quality by the indodax platform service providers so that they can be more attractive and used by everyone.
On an Efficient Technique to Solve Nonlinear Fractional-order Partial Differential Equations

This paper witnesses the combination of an efficient transformation and Exp-function method to construct generalized solitary wave solutions of the nonlinear Klein-Gordon equations of fractional-order. Computational work and subsequent numerical results re-confirm the efficiency of proposed algorithm. It is observed that suggested scheme is highly reliable and may be extended to other nonlinear differential equa- tions of fractional order.
Ground‐Validation and Error Attribution of Near‐Surface Air Temperature From AIRS in North America

Accurate estimation of near‐surface air temperature (TsurfAir) at fine spatiotemporal resolution is crucial for environmental applications, data assimilation into land surface models, and climate change studies. The Atmospheric Infrared Sounder (AIRS) on board the Aqua satellite measures TsurfAir twice a day at the global scale. In this study, the AIRS TsurfAir is validated using ground‐based weather stations in North America. Owing to the high density of weather stations, spatial heterogeneity (<1°) of TsurfAir is modeled using semi‐variograms and further used to calculate the validation reference via ordinary kriging at AIRS retrieval footprints. This analysis intends to reveal error characteristics in cold and hot seasons by selecting six months of data in January and July of three years, along with a case study on two extreme events. Furthermore, MODIS‐enabled land surface temperature and land cover are used to attribute the observed error in TsurfAir. Results show an overall warm bias of 0.11 K from AIRS TsurfAir and conditional bias over‐ and underestimating cold and hot temperatures, respectively. Spatial heterogeneity of TsurfAir is found to influence the variance of AIRS TsurfAir error. As a possible source of TsurfAir error, land surface temperatures (Tskin) from AIRS and MODIS are compared. Close match between the two Tskin products indicates a lesser influence of the Tskin difference on TsurfAir error. Overall, the ground validation of AIRS TsurfAir along with the error attribution can facilitate post‐processing of AIRS products and uncertainty analysis for the wide range of applications of AIRS TsurfAir.
Analisis Kemampuan Berpikir Kritis Matematis Melalui Pendekatan Problem Based Learning dalam Pembelajaran Matematika di SMP

Tujuan penelitian ini adalah untuk: (1) mengkaji bagaimana guru matematika kelas VIII SMP Negeri 2 Sidoharjo menerapkan pembelajaran berbasis masalah untuk membantu siswa mengembangkan kemampuan berpikir kritis; dan (2) meneliti bagaimana mereka menerapkan pembelajaran berbasis masalah untuk membantu siswa mengembangkan keterampilan berpikir kritis mereka. Dengan jumlah siswa kelas VIII-D sebanyak 30 orang, metodologi penelitian yang digunakan adalah penelitian observasional kualitatif. Tiga subjek penelitian sampel, atau mereka yang mencerminkan semua data penelitian, diberikan dalam penelitian ini. Metode pengumpulan data yang digunakan dalam penelitian ini meliputi tes soal terkait pola bilangan yang diberikan guru, observasi, wawancara, dan dokumentasi. Metode analisis data kajian meliputi strategi reduksi data, penyajian data, dan penarikan kesimpulan. Hasil penelitian menunjukkan, sebagian besar siswa belum menyelesaikan tugasnya menggunakan model pembelajaran berbasis masalah, terutama ketika analisis dan evaluasi proses pemecahan masalah terkait dengan indikator berpikir kritis, seperti mengevaluasi fakta dan menarik kesimpulan. Selain itu, ditemukan bahwa siswa kurang memperhatikan ketika mereka mengajukan pertanyaan. Hambatan lain untuk belajar adalah siswa takut untuk menyampaikan argumen kepada teman-teman dan guru.
NCCN Guidelines for Central Nervous System Cancers: Updates in the Treatment of Adult Patients With Glioma

In 2021, the WHO revised its classification of central nervous system (CNS) tumors, which has resulted in changes to both the diagnostic and treatment landscapes. At the NCCN 2023 Annual Conference, this tumor board–style presentation featured 4 case studies to demonstrate an evidence-based approach to the treatment of patients with various WHO-defined types of diffuse glioma. The NCCN Guidelines have been updated to reflect the WHO reclassification of CNS tumors and provide treatment recommendations accordingly.
The effects of fertility on female labour force participation in OECD countries: the role of education and health

Abstract The OECD countries have been experiencing fall in fertility and rise in female labour force participation. Based on panel regression analysis with interaction and mediation effect, this paper found that the negative impact of fertility on female labour force participation can be mitigated by the investment in education and health, with such investment having only a direct effect on female labour force participation without first influencing fertility. Female secondary school enrolment promotes female labour supply regardless of the level of education development. Therefore, policies on human capital investment and childrearing encouragement can be simultaneously implemented to promote female labour supply.
Comparison of Phenolic and Volatile Compounds in MD2 Pineapple Peel and Core

The peel and core discarded from the processing of MD2 pineapple have the potential to be valorized. This study evaluated the functional and volatile compounds in the extracts of MD pineapple peel and core (MD2-PPC). The total soluble solids, pH, titratable acidity, sweetness index, and astringency index were 9.34 °Brix, 4.00, 0.74%, 12.84, and 0.08, respectively, for the peel and 12.00 °Brix, 3.96, 0.32%, 37.66, and 0.03, respectively, for the core. The fat and protein contents of the peel and core were found to be significantly different (p < 0.05). The total phenolic (TPC) and flavonoid contents (TFC) were significantly higher in the peel. The peel also showed better antioxidant activity, with a half-maximal inhibitory concentration (IC50) of 0.63 mg/mL for DPPH free radical activity compared with the core. The TPC of different phenolic fractions from peel extract was highest in the glycosylated fraction, followed by the esterified, insoluble-bound, and free phenolic fractions. GC–MS analysis identified 38 compounds in the peel and 23 in the core. The primary volatile compounds were 2-furan carboxaldehyde, 5-(hydroxymethyl), and 2,3-dihydro-3,5-dihydroxy-6-methyl-4H-pyran-4-one (DDMP). The identification of phenolics and volatile compounds provides important insights into the valorization of (MD2-PPC) waste.
Sea Caves and Other Landforms of the Coastal Scenery on Gozo Island (Malta): Inventory and New Data on Their Formation

Sea caves are a type of cave formed primarily by the wave action of the sea. The coastal scenery of the Gozitan coast is very interesting in that sea caves and other coastal landforms, such as sea arches, develop at the sea level. We mapped seventy-nine semi-submerged sea caves opening at the sea level, five completely submerged sea caves, seven sea arches, one sea stack, and one shelter around the coast of Gozo, mainly in the Western and Eastern parts of the island, due to favorable lithological and topographical conditions. Additionally, we surveyed the topography of the emerged part of nine sea caves using the iPhone build-in LiDAR sensor, and eight sea caves in the submerged part using SCUBA equipment. This inventory represents the most detailed example of a database of coastal caves and related forms in the Mediterranean, mainly sourced from a swimming survey along the entire island. Thanks to the combination of outputs of the above-water emerged and submerged surveys, we defined three types of semi-submerged sea caves: (i) box caves, (ii) joint caves, and (iii) complex caves. Moreover, we added a cave-like landform above the sea level on calcarenites called shelter, or a little extended notch deeply carved into the cliff. The shape mainly depends on the structural and lithological setting of sea cliffs. In the Western sector of the island, we also discovered the only sea cave in Gozo, measuring 122 m in length and 10 m in width, with its floor developing above the mean sea level. This cave base is of interest due to rounded landforms related to marine erosion. In the innermost part of the cave, there is also a beach with rounded pebble at an elevation of about 7 m asl. Considering the tectonic stability of the island, it could be possibly related to the MIS 5.5 highstand.
Covid-19 associated coagulopathy (CAC): Global research output, 2020-2022

Objective. This study examined the Covid-19 associated coagulopathy (CAC) publication and citation trends, focusing on the top authors, countries, organizations, journals, collaboration, subject areas, keywords, and high-cited articles. Design/Methodology/Approach. Publications data on Covid-19 associated coagulopathy (CAC) were identified and extracted from the Scopus database. Data analysis has been performed using VOS viewer software, Biblioshiny, and MS Excel Software. Results/Discussion. The study identified 1740 articles on Covid-19 associated coagulopathy from the Scopus database, which received 47,502 citations, averaging 27.3 citations per paper. In all, 905 authors from 601 organizations originating in 96 countries participated in research and published in 776 journals. United States, Italy, and China contributed the most publications (498, 258, and 164 papers). While China (73.43 and 2.69), France (57.60 and 2.11,) and Germany (50.13 and 1.84) registered the highest citation impact by CPP and RCI. Harvard Medical School, USA, Huazhong University of S&T, China, and Tongji Medical College, China, lead with most of the publications (4,4, 41, and 39 papers). In contrast, Tongji Medical College, China (198.31 and 7.26), Huazhong University of S&T, China (198.15 and 7.26), and University College Hospital NHS Foundation Trust, U.K (129.23 and 4.73) lead in citation impact. J.H. Levy, T. Iba and M. Levy contributed to most of the publications (27, 25, and 20), while N. Tag (804.75 and 29.48), A. Tripodi (157.83 and 5.78), and J. Thachil (154.17 and 5.65) registered the highest citation impact by CPP and RCI. Journal of Thrombosis and Haemostasis, Journal of Thrombosis and Thrombolysis, and Thrombosis Research were the most productive ones (with 55, 51, and 46 publications). At the same time, Medical Hypotheses (1222), Blood (355.71) and Thrombosis Journal (233.86) were the most impactful journals. The top 9 keywords were Covid-19 (1681 occurrences), Blood Clotting (952), D Dimer (652), C (628), Coagulopathy (628), Thrombosis (584), blood (506), Anticoagulants (499), Blood Coagulation (426) and Fibrinogen (376). Conclusions. Global research on Covid-19 associated coagulopathy since the pandemic was considered for scientometric assessment for the first time, combining the productivity and citation measures to present an overall picture of the literature in this area. Such an analysis will provide scholars and policy-makers with a meaningful reference for further exploration of topical issues and research trends in the field.
Object Play and Autism Spectrum Disorders Symptoms in Toddlers Aged 12–37 Month at Risk of Developmental Disorders

Various studies have shown a relationship between the development of language and object play in children. Children with Autism spectrum disorder (ASD) show difficulties in both of these areas of functioning. But the knowledge about the relationships between the severity of ASD symptoms and object play in children at risk of developmental disorders remains limited. To explore these relationships, 44 children aged 13–37 months took part in this study. Object play and ASD symptoms were assessed in two age groups (13–18 months and 24–37 months). The results show that ASD symptom intensity is related to object play complexity in children at risk of developmental disorders. However, these relationships are different depending on the age of the children.
Neoadjuvant Treatment Approaches for Stage II–III Rectal Cancer

Excellent long-term outcomes are being achieved with contemporary treatment strategies for localized rectal cancer. A “watch-and-wait” nonoperative strategy seems to be a safe option for patients experiencing a complete clinical response. Total neoadjuvant therapy (TNT) has shown many advantages over standard chemoradiotherapy, although the optimal sequencing—with induction or consolidation chemotherapy—is still debated. The use of FOLFIRINOX can boost the benefit of TNT. Of note, in the small subset of patients whose tumors have mismatch repair deficiency, checkpoint inhibition has led to responses in most patients, eliminating the need for further treatment.
Improvement of Classification Performance in High-Dimension Low-Sample-Size Modeling by Sparse Functional Connectivity States in Subjects with Attention Deficit-Hyperactivity Disorder and Healthy Controls

Background: The precise identification of attention deficit-hyperactivity disorder (ADHD) is one of the challenging clinical processes. Disorganizations in functional neural networks revealed via functional magnetic resonance imaging have recently been contributing. Machine learning approaches, particularly classification methods, have commonly been employed as a framework for diverse data analysis, indicating promising medical diagnosis results. However, as the neuroimaging data are high-dimensional with a low sample size (the current dataset), this study aimed to evaluate the classification performance of the models by considering the specific contribution of the sparsity of data matrices. Methods: This cross-sectional study analyzed the preprocessed data from the 2011 ADHD-200 Global Competition. A total of 768 and 171 data items were considered training and test, respectively. The diagnosis status was used as a response variable. Age, gender, hand dominance, and activity relationship between 116 brain regions derived from inverse covariance matrix and inverse sparse covariance matrix were used as predictive variables. Accordingly, this study compared the performance of three models, namely support vector machine (SVM), distance-weighted discrimination (DWD), and data maximum dispersion classifier (DMDC) for ADHD categorization. Results: The highest value for the total accuracy was reported for the SVM model on the sparse covariance matrix. Moreover, the highest values for the balanced classification rate (BCR) (59%) and sensitivity (64%) were reported for DMDC on the sparse covariance matrix. The best level of specificity (99%) was obtained from DWD using the sparse covariance matrix. The highest levels of the values (i.e., total accuracy and BCR) were achieved through the model fitting on the sparse matrices. Among the six models, the DMDC model on sparse covariance matrix was the most optimal algorithm due to the superiority of the two indices (i.e., accuracy: 60% and BCR: 60%) and the favorable balance between sensitivity and specificity values. Conclusions: Among the current studied three models, DMDC performance, applying the sparse data, remarkably improved the results of classification processes. Based on the present findings, the neuronal connectivity among subcortical structures comprising parts of the basal ganglia and cerebellum provides a distinction between ADHD subjects and healthy controls.
Self-Labeling Framework for Open-Set Domain Adaptation With Few Labeled Samples

Unsupervised domain adaptation (UDA) is extremely effective for transferring knowledge from a label-rich source domain to a label-scarce target domain. Because the target domain is unlabeled and may contain additional novel classes, open-set domain adaptation (ODA) has been suggested as a possible solution to detect these novel classes in the training phase. However, existing ODA methods rely heavily on abundant fully labeled source data, which are expensive to collect in specific applications and may also contain novel classes. In this study, we propose a novel self-labeling framework with prototypical contrastive learning and mutual information maximization to achieve ODA even when the amount of labeled data is very small, which is a new problem setting named few-shot ODA (FODA). We use self-supervised prototypical contrastive learning to train the network to learn the representations of source and target samples and maximize the mutual information between labels and input data to simultaneously recognize known and novel classes in the source and target domains. We evaluated our strategy in several domain adaptation environments and found that our method performed far better than existing approaches.
The common solution of the pair of fuzzy matrix equations

In this paper, we investigate the common solution pair of the fuzzy matrix equations. The Kronecker product and Vec-operator for transforming system of fuzzy linear matrix equation to fuzzy linear system are employed. A new iterative method for solving two non-square m × n system instead of one 2m × 2n system is presented. Examples are provided to illustrate the developed theory.
A 3.58 nJ/Node Dual Cross Correlation Analog-Front-End Circuit With ADC for Mutual Capacitive Panel

This article presents a dual cross correlation analog-front-end (DCC-AFE) circuit for a mutual capacitive panel. The DCC-AFE circuit solves the problem of reduced recognition ability owing to the phase difference variation between the transmitted and received signals for a large load panel. A sparse collection algorithm is adopted to reduce the number of analog-to-digital converter (ADC) collections and microcontroller unit (MCU) operations in the proposed touch system. Only a 12-bit successive-approximation-register voltage-controlled-oscillator (SAR-VCO) ADC could meet the requirement. Based on this algorithm, both the power consumption and die area of the proposed analog-front-end (AFE) are significantly reduced. Moreover, we propose a calibration algorithm to improve the accuracy of the ADC. The proposed state-of-art touch integrated circuit (IC) was fabricated via a 110 nm CMOS process. The proposed AFE achieves 46.1 and 50.2 dB signal-to-noise ratio (SNR) with 384 and 128 Hz frame rates, respectively. The active area of the 64-channel AFE with ADC on the chip is 0.988 mm2, which only occupies a small area. The touch IC has an energy consumption of 3.58 nJ/node.
Introducing mechanics by tapping core causal knowledge

This article concerns an outline of an introductory mechanics course. It is based on the argument that various uses of the concept of force (e.g. from Kepler, Newton and everyday life) share an explanatory strategy based on core causal knowledge. The strategy consists of (a) the idea that a force causes a deviation from how an object would move of its own accord (i.e. its force-free motion), and (b) an incentive to search, where the motion deviates from the assumed force-free motion, for recurring configurations with which such deviations can be correlated (interaction theory). Various assumptions can be made concerning both the force-free motion and the interaction theory, thus giving rise to a variety of specific explanations. Kepler’s semi-implicit intuition about the force-free motion is rest, Newton’s explicit assumption is uniform rectilinear motion, while in everyday explanations a diversity of pragmatic suggestions can be recognized. The idea is that the explanatory strategy, once made explicit by drawing on students’ intuitive causal knowledge, can be made to function for students as an advance organizer, in the sense of a general scheme that they recognize but do not yet know how to detail for scientific purposes.