Miracle-dz/UniFAR-FTUs huggingface dataset:
An Analysis of Illocutionary Act in “Ratatouille” A Movie by Brad Brid

This study aimed to find out the type of illocutionary acts that is contained the utterance of the main character and to determine the most dominant illocutionary act that is used by the main character in the movie. This research use applies qualitative method. As the result there are 48 utterances that contain illocutionary act found in Ratatouille movie. The researcher found 4 classifications of illocutionary act by using Yule’s classification. The fourth types are; directives found 20 utterances, expressive found 11 utterances, representatives found 10 utterances and commissive found 6 utterances. The researcher not found the type of illocutionary act of declaration. The most dominant illocutionary act is directives.Key Words: Speech acts, Illocutionary acts, Ratatouille Movie
Temporal, Kinematic and Kinetic Variables Derived from a Wearable 3D Inertial Sensor to Estimate Muscle Power during the 5 Sit to Stand Test in Older Individuals: A Validation Study

The 5-Sit-to-stand test (5STS) is widely used to estimate lower limb muscle power (MP). An Inertial Measurement Unit (IMU) could be used to obtain objective, accurate and automatic measures of lower limb MP. In 62 older adults (30 F, 66 ± 6 years) we compared (paired t-test, Pearson’s correlation coefficient, and Bland-Altman analysis) IMU-based estimates of total trial time (totT), mean concentric time (McT), velocity (McV), force (McF), and MP against laboratory equipment (Lab). While significantly different, Lab vs. IMU measures of totT (8.97 ± 2.44 vs. 8.86 ± 2.45 s, p = 0.003), McV (0.35 ± 0.09 vs. 0.27 ± 0.10 m∙s−1, p < 0.001), McF (673.13 ± 146.43 vs. 653.41 ± 144.58 N, p < 0.001) and MP (233.00 ± 70.83 vs. 174.84 ± 71.16 W, p < 0.001) had a very large to extremely large correlation (r = 0.99, r = 0.93, and r = 0.97 r = 0.76 and r = 0.79, respectively, for totT, McT, McF, McV and MP). Bland–Altman analysis showed a small, significant bias and good precision for all the variables, but McT. A sensor-based 5STS evaluation appears to be a promising objective and digitalized measure of MP. This approach could offer a practical alternative to the gold standard methods used to measure MP.
Industrially Important Fungal Carotenoids: Advancements in Biotechnological Production and Extraction

Carotenoids are lipid-soluble compounds that are present in nature, including plants and microorganisms such as fungi, certain bacteria, and algae. In fungi, they are widely present in almost all taxonomic classifications. Fungal carotenoids have gained special attention due to their biochemistry and the genetics of their synthetic pathway. The antioxidant potential of carotenoids may help fungi survive longer in their natural environment. Carotenoids may be produced in greater quantities using biotechnological methods than by chemical synthesis or plant extraction. The initial focus of this review is on industrially important carotenoids in the most advanced fungal and yeast strains, with a brief description of their taxonomic classification. Biotechnology has long been regarded as the most suitable alternative way of producing natural pigment from microbes due to their immense capacity to accumulate these pigments. So, this review mainly presents the recent progress in the genetic modification of native and non-native producers to modify the carotenoid biosynthetic pathway for enhanced carotenoid production, as well as factors affecting carotenoid biosynthesis in fungal strains and yeast, and proposes various extraction methods to obtain high yields of carotenoids in an attempt to find suitable greener extraction methods. Finally, a brief description of the challenges regarding the commercialization of these fungal carotenoids and the solution is also given.
Image Matching Method Based on Improved SIFT Algorithm

To improve the resolution of different scales in different image matching accuracy and efficiency,this paper introduces an improved method based on scale invariant feature transform(SIFT) algorithm for image matching.SIFT feature matching algorithm is currently a hot research field,because it has good invariance of scale,rotation,illumination,based on analyzing the generating process of SIFT feature vectors,the quasi-Euclidean distance instead of Europe is as the similarity measure of feature descriptors to improve the SIFT feature matching efficiency.Experimental results show that under the condition of keeping the image matching rate and algorithm robust,the method can not only shorten the matching time,but also improve the matching accuracy.
進化型多目的最適化手法を用いたファジィルール選択;進化型多目的最適化手法を用いたファジィルール選択;Fuzzy Rule Selection Using Evolutionary Multiobjective Optimization Methods

One advantage of evolutionary multiobjective optimization (EMO) algorithms over classical approaches is that many non-dominated solutions can be simultaneously obtained by their single run. This paper shows how this advantage can be utilized in genetic rule selection for the design of fuzzy rule-based classification systems. Our genetic rule selection is a two-stage approach. In the first stage, a pre-specified number of candidate rules are extracted from numerical data using a data mining technique. In the second stage, an EMO algorithm is used for finding non-dominated rule sets with respect to three objectives. Since one of the three objectives is to maximize a classification rate on training patterns, the evolution of rule sets tends to overfit to training patterns. The question is whether the other two objectives with respect to complexity work as a safeguard against the over-fitting. In this paper, we examine the effect of the three-objective formulation on the generalization ability of obtained rule sets through computational experiments where many non-dominated rule sets are generated using an EMO algorithm for a number of high-dimensional pattern classification problems. Finally, we demonstrate that an ensemble of generated fuzzy rule-based systems leads to high generalization ability.
A Conceptual Study on Image Matching Techniques

Matching Is The Technique To Find Existence Of A Pattern Within A Given Description. Image Matching Is An Important Application Required In The Field Of Image Processing. Images Are Represented As N-Dimensional Feature Vectors. Objects Of Same Class Possess Same Features And Those Objects Which Are From Different Class Possess Different Features. In The Image Matching Process,Features Are Used To Detect Whether Images Are Similar Or Not. Even We Can Find Whether Pattern Image Is A Subset Of Original Image Or Not. To Find Similarity Among Various Images Their Feature Vectors Are Matched. An Efficient Matching Technique Should Find Similarity Or Dissimilarity In Lesser Time Period. A Lot Of Matching Techniques Have Been Developed Till Today And Still Research For Developing An Optimized Matching Technique Is Going On. Most Commonly Used Matching Technique Is Nearest Neighborhood Technique. It Is An Important Technique Used In Applications Where Objects To Be Matched Are Represented As N-Dimensional Vectors. Other Matching Techniques Used Are Least Square Method, Coefficient Of Correlation Technique, Relational Graph Isomorphism Technique, Approximate Nearest Neighbor Technique And Matching Using Simulated Annealing Etc. All Of These Matching Techniques Have Their Own Advantages And Disadvantages. The Matching Technique Should Be Chosen Depending Upon The Application Area In Which It Is To Be Applied.
Teacher Perceptions of Multicultural Education and Diversity Values in the School Environment

A comprehensive education system is essential to promote peace in a diverse, multicultural society. Teachers have a critical role in organizing the classroom environment, and it is vital to understand their perceptions of Multiculturalism and the extent to which educational programs adopt multicultural principles. This study investigated teachers' perceptions of multicultural education and diversity and evaluated their awareness of these issues. A qualitative research design with case studies was used, and six teachers from an elementary school in Surabaya were deliberately selected for this study. The data were collected through interviews, observation, and document analysis, and the results were analyzed using content analysis techniques. This study found that teachers have adequate knowledge about multicultural education and a positive attitude toward it. However, their understanding and prejudices related to specific concepts still need more. In addition, the inclusiveness of Multiculturalism in annual plans and teaching programs still needs to be improved. Learning transformation is required that encourages active student collaboration, such as the project-based learning (PjBL) model.
Two-Layers DDoS Attack Detection Model Using Machine Learning in Software Defined Networking

Software Defined Network (SDN) is a new architecture designed to make the network infrastructure more flexible and easier to manage. It allows network administrators to configure network parameters as well as integrating new functions using programming languages easily. Thanks to the centralized control paradigm, it is easier to collect information of the entire network, which facilitates the implementation of machine learning algorithms to detect anomaly traffic as well as network attacks. Recently, with the development of machine learning and artificial intelligence, several methods have been applied to detect and mitigate Distributed Denial of Service (DDoS) attacks. However, all of activities from monitoring data, detecting and mitigating the attack consume time and resources. To reduce unnecessary redundancy, in this paper, we divide attack detection into two phases, which are anomaly detection phase with lightweight machine learning algorithm and attack detection phase when anomaly behaviors have been detected. This reduces the in-depth analysis of normal traffic and helps to improve the use of computing resources and data transmission efficiency of the network. By setting up a testbed, we have successfully run this model as well as evaluated the accuracy of the model. The results show that our model can detect attacks quickly and accurately.
LASP1, CERS6, and Actin Form a Ternary Complex That Promotes Cancer Cell Migration

Simple Summary CERS6 is known to be associated with metastasis and poor prognosis in non-small cell lung cancer (NSCLC) patients because of C16 ceramide production, though the underlying mechanism remains largely unelucidated. In this study, CERS6 binding partners were identified by co-immunoprecipitation, as well as liquid chromatography and tandem mass spectrometry analysis. LASP1, one of the leading candidates, was found to play a role in cell migration, while CERS6 and LASP1 were shown to co-localize on lamellipodia and interact with actin. Silencing of CERS6 and/or LASP1 led to reduced levels of lamellipodia formation and cell migration. Furthermore, interaction of CERS6 or LASP1 with actin was dramatically decreased when the partner was depleted. Based on these findings, it is proposed that LASP1–CERS6 interaction promotes cancer cell migration. Abstract CERS6 is associated with metastasis and poor prognosis in non-small cell lung cancer (NSCLC) patients through d18:1/C16:0 ceramide (C16 ceramide)-mediated cell migration, though the detailed mechanism has not been elucidated. In the present study, examinations including co-immunoprecipitation, liquid chromatography, and tandem mass spectrometry analysis were performed to identify a novel binding partner of CERS6. Among the examined candidates, LASP1 was a top-ranked binding partner, with the LIM domain possibly required for direct interaction. In accord with those findings, CERS6 and LASP1 were found to co-localize on lamellipodia in several lung cancer cell lines. Furthermore, silencing of CERS6 and/or LASP1 significantly suppressed cell migration and lamellipodia formation, whereas ectopic addition of C16 ceramide partially rescued those phenotypes. Both LASP1 and CERS6 showed co-immunoprecipitation with actin, with those interactions markedly reduced when the LASP1–CERS6 complex was abolished. Based on these findings, it is proposed that LASP1–CERS6 interaction promotes cancer cell migration.
Novel Genetic Variants Expand the Functional, Molecular, and Pathological Diversity of KCNA1 Channelopathy

The KCNA1 gene encodes Kv1.1 voltage-gated potassium channel α subunits, which are crucial for maintaining healthy neuronal firing and preventing hyperexcitability. Mutations in the KCNA1 gene can cause several neurological diseases and symptoms, such as episodic ataxia type 1 (EA1) and epilepsy, which may occur alone or in combination, making it challenging to establish simple genotype–phenotype correlations. Previous analyses of human KCNA1 variants have shown that epilepsy-linked mutations tend to cluster in regions critical for the channel’s pore, whereas EA1-associated mutations are evenly distributed across the length of the protein. In this review, we examine 17 recently discovered pathogenic or likely pathogenic KCNA1 variants to gain new insights into the molecular genetic basis of KCNA1 channelopathy. We provide the first systematic breakdown of disease rates for KCNA1 variants in different protein domains, uncovering potential location biases that influence genotype–phenotype correlations. Our examination of the new mutations strengthens the proposed link between the pore region and epilepsy and reveals new connections between epilepsy-related variants, genetic modifiers, and respiratory dysfunction. Additionally, the new variants include the first two gain-of-function mutations ever discovered for KCNA1, the first frameshift mutation, and the first mutations located in the cytoplasmic N-terminal domain, broadening the functional and molecular scope of KCNA1 channelopathy. Moreover, the recently identified variants highlight emerging links between KCNA1 and musculoskeletal abnormalities and nystagmus, conditions not typically associated with KCNA1. These findings improve our understanding of KCNA1 channelopathy and promise to enhance personalized diagnosis and treatment for individuals with KCNA1-linked disorders.
Suggested Syllabus of English I for First Semester students of Islamic Education Department at STAI Al-Gazali Soppeng

This study investigates the needs of English I for first-semester students at the Islamic Education Department and suggests an English I syllabus based on needs analysis for Islamic Education Department at STAI Al-GAzali Soppeng. This study employed a development research design and simple random and purposive sampling data from 50 students, five graduates, two lecturers, and one curriculum coordinator. The instruments for this study were questionnaires and interviews. The data were gathered through questionnaires by implementing Scala-Likert and were descriptively analyzed. The result shows that (1) students’ ability to learn English I is “poor” in pronunciation. (2) Students’ problems are complex in an oral presentation on learning speaking skills, difficult to understand native speakers on learning the listening skills, difficult to guess the core meaning of the text on learning reading skills, and difficult to compose correct sentences on learning writing. (3) Students prioritize learning preference, preferred topic, and learning style. Dialogue is speaking learning preference. The translation is reading learning preferences, learning from the rules of authorship is writing learning preferences, and listening and practising are listening learning preferences. The preferred topic is Islamic education and the discussion on learning style.
Structure of and Light Emission in Matrix-Free Germanium Quantum Dots.

The connection between light emission and structure of Germanium nanoparticles (3-10 nm) prepared by top-down (etching) and bottom-up (sol-gel and colloidal synthesis) has been investigated using Raman spectroscopy, TEM, x-ray absorption spectroscopy (XAS), x-ray diffraction (XRD), and photoluminescence (PL). It was found that TEM, Raman spectroscopy, PL, and XRD techniques all result in differing values for the nanoparticle size which don’t all agree in the limit of experimental error. Several structural models have been proposed and tested by high pressure Raman measurements. It was found that a Raman peak corresponding to diamond-type Ge structure is observed well above the transition pressure of both amorphous (≈ six GPa) and crystalline (≈ 11 GPa) Ge. The pressure dependence of the Raman signal peak position was observed to follow an unexpected non-linear shift with a corresponding increase in peak width (FWHM). Possible structural origins of these trends have been investigated by adapting the widely used phonon confinement model to high pressure conditions and comparing experimental data with the model behaviour under assumptions of constant, and size-dependent bulk modulus. Considered collectively with the ambient structural data, the results of the analysis of the high pressure behaviour point to the phenomenon of gradual surface induced amorphisation under pressure in matrix-free Ge nanoparticles. The best structural model to describe this is a core-shell with the small crystalline core and a disordered surface layer. The local structure of samples was investigated using XAS, while opticallydetected XAS, using x-ray excited optical luminescence (XEOL), was used to link structure with optical emission. The emission was found to depend on surface termination; in oxygen terminated nanoparticles the oxide rich regions are responsi-
Molecular genetics of primary open-angle glaucoma

Glaucoma is a series of linked optic diseases resulting in progressive vision loss and total blindness due to the acquired loss of retinal ganglion cells. This harm to the optic nerve results in visual impairment and, ultimately, total blindness if left untreated. Primary open-angle glaucoma (POAG) is the most frequent variety within the large family of glaucoma. It is a multifaceted and heterogeneous condition with several environmental and genetic variables aiding in its etiology. By 2040, there will be 111.8 million glaucoma patients globally, with Asia and Africa accounting for the vast majority. The goal of this review is to elaborate on the role of genes (nuclear and mitochondrial) as well as their variants in the pathogenesis of POAG. PubMed and Google Scholar databases were searched online for papers until September 2022. Prevalence and inheritance patterns vary significantly across different ethnic and geographic populations. Numerous causative genetic loci may exist; however, only a few have been recognized and characterized. Further investigation into the genetic etiology of POAG is expected to uncover novel and intriguing causal genes, allowing for a more precise pathogenesis pattern of the disease.
Integrated transrectal probe for translational ultrasound-photoacoustic imaging

A compact photoacoustic transrectal probe is constructed for improved imaging in brachytherapy treatment. A 192 element 5 MHz linear transducer array is mounted inside a small 3D printed casing along with an array of optical fibers. The device is fed by a pump laser and tunable NIR-optical parametric oscillator with data collected by a Verasonics ultrasound platform. This assembly demonstrates improved imaging of brachytherapy seeds in phantoms with depths up to 5 cm. The tuneable excitation in combination with standard US integration provides adjustable contrast between the brachytherapy seeds, blood filled tubes and background tissue.
Is It True That Some People Just Can't Do Math?

Answer: While it is true that some people are better at math than others—just like some are better than others at writing or building cabinets or anything else—it is also true that the vast majority of people are fully capable of learning K–12 mathematics. Learning mathematics does not come as naturally as learning to speak, but our brains do have the necessary equipment. So, learning math is somewhat like learning to read: we can do it, but it takes time and effort, and requires mastering increasingly complex skills and content. Just about everyone will get to the point where they can read a serious newspaper, and just about everyone will get to the point where they can do high school–level algebra and geometry—even if not everyone wants to reach the point of comprehending James Joyce’s Ulysses or solving partial differential equations.
Bayesian regression models adjusting for unidirectional covariate misclassification

In this article we consider unidirectional covariate misclassification, meaning that the direction of classification error is known. We investigate the identifiability of Bayesian regression models when a binary covariate is subject to unidirectional misclassification. In the Bayesian framework we consider whether knowledge of the direction of error suffices, so that adjustment for misclassification can be undertaken without any source of information on the magnitude of error. Although measurement error models are generally non‐identified without such information, for the case of unidirectional misclassification, we do obtain model identifiability when the response variable is non‐binary. For the binary response model that is non‐identified we examine the extent of partial identification. The limiting posterior distributions of the parameters are obtained for this partially identified model, for two different prior distributions. We perform computational studies that illustrate statistical learning, for the three cases where the model is easily identified, weakly identified, and partially identified. A case study is performed using real data. The Canadian Journal of Statistics 44: 198–218; 2016 © 2016 Statistical Society of Canada
The Late Effects of Cancer Treatment on Female Fertility and the Current Status of Fertility Preservation—A Narrative Review

Fertility counseling should be offered to all individuals of young reproductive age early in the patient’s trajectory following a cancer diagnosis. Systemic cancer treatment and radiotherapy often have an inherent gonadotoxic effect with the potential to induce permanent infertility and premature ovarian failure. For the best chances to preserve a patient’s fertility potential and to improve future quality of life, fertility preservation methods should be applied before cancer treatment initiation, thus multidisciplinary team-work and timely referral to reproductive medicine centers specialized in fertility preservation is recommended. We aim to review the current clinical possibilities for fertility preservation and summarize how infertility, as a late effect of gonadotoxic treatment, affects the growing population of young female cancer survivors.
Challenge of Media Noise Suppression With Oxidation Control in Granular Structure for CoPtCr-Based Sputtered Tape Toward 400 Gb/in2

A sputtered tape that uses a CoPtCr-based granular recording layer consisting of magnetic grains and grain boundary oxides was developed for practical applications in next-generation large-capacity magnetic tapes. The role of oxides in CoPtCr-oxide composite targets in forming nanostructures for the granular layer was investigated under the distinctive conditions of a roll-to-roll sputtering system. It was confirmed that: 1) increasing the amount of Co3O4 in the CoPtCr-SiO2-Co3O4 composite target improved the magnetic isolation between magnetic grains and the magnetic anisotropy of the granular recording layer due to diffusion of Si and Cr from within magnetic grains to oxide grain boundaries by oxidation; 2) this magnetic isolation led to 3.6 dB improvement in the broadband signal-to-noise ratio (BB-SNR) at a linear density of 353 kfci through suppression of noise; and 3) overlaying CoPtCrB alloy layer to this sample as a cap layer brought the higher BB-SNR of 2.3 dB than that for the sample reported by us in TMRC2017. Applying the latest track-following technology, this SNR improvement was estimated to have the potential to achieve an areal density of 375 Gb/in2.