Background: Currently, Indonesia is entering an era that is all digital and uses technology in all fields of activity. The internet has a lot to do with their behavior or character. Millennials are the nation's next generation. The emergence of the digital era caused by globalization has made the millennial generation less appreciative and practicing the values ​​of Pancasila. In this case, character education is something that must be applied to the millennial generation. Purpose: This study aims to analyze the characteristics of the millennial generation, the role of character education in realizing the values ​​of Pancasila in the daily life of the millennial generation, how to cultivate an attitude of patriotism and nationalism towards the nation by practicing Pancasila, and provide motivation for the millennial generation to realize these values. Pancasila values. Methods: This study uses a literature review method. The search for journals was carried out using the google scholar database with the keywords “Character Education”, “millenial generation”, and “Pancasila”. The journals selected are journals from 2019 to 2020. Results: By applying character education to the millennial generation, it will make it easier for them to practice the values ​​of Pancasila. Pancasila should be the way of life of the millennial generation. Recommendation and limitation: As millennials, we must protect the country from values ​​that are contrary to Pancasila. Character education must be applied following the nature of the millennial generation itself. Of course, the applied character education must prioritize and be based on the values ​​of Pancasila as well.

Character education is essential for the current millennial generation and must be applied in everyday life in the surrounding community. The character of the millennial generation is different from the previous generation, which requires us to pay more attention to character education which is starting to erode along with the times. The Millennial generation is a generation that in everyday life can never be separated from science and technology. In this digital era, the millennial generation has a social function of strength in technology. In this study, there are research questions that will be discussed in this article, namely the first regarding what problems occur in the millennial generation who occupy the digital era?. Second, what is the important role and influence of the digital era on character education for the millennial generation in Indonesia?. Writing this article uses a qualitative research method, namely a literature review study, where researchers use or look for references from journals or books. Samples of respondents were taken randomly from each region, and there were ten respondents. From this research, it is found that the millennial generation in the digital era chooses to use social media to access the latest news and information rather than reading print media that contains education. This article aims to find out the importance of character education for the millennial generation, which is starting to erode with the times in the digital era. Many people underestimate character education, especially for the current millennial generation. Therefore, we must implement educational programs at any level, especially in Indonesia, because the character shows the national identity. This article will discuss the vital role and influence of character education for millennials who live in the digital era to be aware of the importance of character education in citizenship.

Covid-19 has become a non-natural national disaster that affects the national resilience of the Indonesian state. In maintaining national resilience, the implementation of state defense is needed. This research aims to describe the awareness of defending the state of millennials during the current situation of the Covid-19 pandemic in Indonesia by using a quantitative approach with descriptive analysis methods with survey techniques. The results of this study indicate that most millennials are aware of the obligation to defend the state amid the current Covid-19 pandemic, namely by implementing health protocols such as preparing cleaning equipment, conducting social distancing, and working from home. However, there are still millennials who cannot run it for some reason. Based on the results of this study, it concluded that most millennials are aware of the obligation to defend the state during a pandemic by complying with health protocols as a form of state defense character.

The research objective was to determine the problem of bullying in teenagers. The method used is a qualitative approach with literature study methods and a quantitative approach with the e-survey method. The results showed that bullying was rife in the school environment with teenagers aged 12-15. Verbal bullying occurs the most because it is the easiest to do. Bullying occurs with a group of people against one person because of peer influence. Family factors, school, the influence of friends, environmental conditions, and television shows influence bullying. Character Education can help overcome bullying in teenagers because it teaches the value of virtue in daily activities if given early and not during teenager. The conclusion found in this activity is that teenagers can become bullies because of family, school, peer influence, social conditions, and television broadcasts. Character Education is more effective if it is implemented since early childhood education and all relevant stakeholders must be actively involved in providing the Character Education.

Automatic Number Plate Recognition is a computer vision technology that provides a way to recognize the vehicles number plates without direct human intervention. Developing Automatic Number Plate Recognition methodologies is a widely studied topic among the computer vision community to increase the accuracy rates. Although there are many studies, the research in character segmentation and improving the recognition accuracy remains limited. In this study, a new methodology is proposed to reduce the character recognition errors of Automatic Number Plate Recognition systems. To achieve this, it will be determined whether the characters are letters or numbers, and the number plates will be expressed in the form of letters - digit. The method suggested for segmenting blobs correctly worked with an accuracy of 96.12% on the test dataset. The method suggested for generating letter-digit expression for the number plates correctly worked with an accuracy of 99.28% on the test dataset. The proposed methodology can work only on Turkish number plates. In the future studies, the proposed methodology can be expanded by using the number plate dataset of a different country.

For the ground-state properties of gas-phase nanomolecules with multi-reference character, thermally-assisted-occupation density functional theory (TAO-DFT) has been recently found to outperform the widely used Kohn-Sham density functional theory, when the conventional exchange-correlation energy functionals are employed. Aiming to explore solvation effects on the ground-state properties of nanomolecules with multi-reference character at a minimal computational cost, we combine TAO-DFT with the polarizable continuum model (PCM). To show its usefulness, TAO-DFT-based PCM (TAO-PCM) is employed to study the electronic properties of linear acenes in three different solvents (toluene, chlorobenzene, and water). According to TAO-PCM, in the presence of these solvents, the smaller acenes should have nonradical nature, and the larger acenes should have increasing polyradical nature, showing remarkable similarities to the past findings in the gas phase.

This research described the fundamental inspiration behind the implementation of a humanistic approach to the principal's leadership and the steps of the principal's humanistic approach that have an impact on optimizing the implementation of the program for strengthening character education. This research used a qualitative approach, a case study design. The data collection was performed through in-depth interviews, participant observation, and documentation studies to achieve the research objectives. Data analysis used a modified analytic analysis method. The level of credibility, transferability, dependability, and confirmability was the basis of data validity. The research findings explained that personal excellence (integrity, wholeness, and self-authenticity) and the humanistic spirituality of inspirational figures inspired the principal’s humanistic approach. In addition, the application of the principal's humanistic approach had adequate impacts on optimizing the implementation of a program for strengthening character education and influenced the strengthening of the student's character. Through the principal's humanistic approach, school becomes an environment for empowering the character of the students.

While adequate for English-speaking users in the United States, as well as many Commonwealth countries and other English-speaking jurisdictions (e.g., Canada, Australia, New Zealand or South Africa among others), typing in Romance Languages (Spanish, French, Portuguese and Italian) by using a standard US-QWERTY Keyboard is not easy since it is not adapted to special characters such as accented vowels, tildes and cedillas or ligatures, used in Romance Languages. With regard to the International Layout, intended to enable access to the most common diacritics used in Western European Languages, the problem comes from the fact that accented vowels are spread throughout the Keyboard layout, and their uppercase versions need chord combinations which can require good manual dexterity. This paper will analyze how the Spanish or Portuguese Keyboards are the best options for these users since they are QWERTY-based and the most compatible ones for the different character sets in Spanish, French, Portuguese and Italian Languages.

Abstract Objectives: Aging may challenge life and even affect individuals' well-being and flourishing. This includes challenges of shrinking social relations and being by yourself in old age while using your personal strengths. The current study examines two important personal resources, i.e., the skill of positive solitude and the 24 character-strengths, that may be associated with flourishing in old age. Methods: A convenience sample of 1085 community-dwelling adults (M = 57.20, SD = 6.24, range = 50-87), completed an online self-report survey with demographic measures and scales measuring personal strengths, the skill of positive solitude, and flourishing. Results: As hypothesized, the 24 character-strengths and positive solitude, were each associated with flourishing, and positive solitude moderated the relationships between the 24 character-strengths and flourishing. The 24 character-strengths and flourishing relationship was stronger among participants with lower levels of positive solitude. Conclusion: These findings highlight that despite the decrease in social relations which often characterizes old age, the skill of positive solitude serves as a valuable resource for flourishing in the later stages of life.

Social character is the key for someone to interact with the surrounding community. Interaction and socialization need to be introduced early by parents. If the results turned in reverse, then there must be other ways to be learned and practiced in family life. This study aims to cultivate social characters to children in the Juvenile Rehabilitation Institution through poetry learning. Changes continue to occur in handling and coaching juvenile delinquency in Indonesia. Regulations for the management of coaching continue to be carried out from Law No. 3 of 1997 concerning the Law on Juvenile Justice, then it was changed to Act No. 11 of 2012 concerning the System of Juvenile Criminal Justice. Characteristics of this relatively new law contain the main mechanisms of protecting children, who have problems with the law and following the Convention on the Rights of the Child. Education in the Juvenile Rehabilitation Institution has been carried out with all the limitations and can bring changes in the correctional behavior of children to be better that makes education restore the child's identity. Education held at this institution is expected to be able to achieve the ideals of children to be more beneficial after completing a kind of inclusive education. By applying a pragmatic approach, the study expects that there will be a change in children since they can learn the contents of poems, and at the same time, they are able to express their feeling by writing poems as well. From the process of learning, social characters in children such as honesty, openness, tolerance, cooperation, will be growing step by step.

Recently, oriented external electric fields (OEEFs) have earned much attention due to the possibility of tuning the properties of electronic systems. From a theoretical perspective, one can resort to electronic structure calculations to understand how the direction and strength of OEEFs affect the properties of electronic systems. However, for multi-reference (MR) systems, calculations employing the popular Kohn-Sham density functional theory with the traditional semilocal and hybrid exchange-correlation energy functionals can yield erroneous results. Owing to its decent compromise between accuracy and efficiency for MR systems at the nanoscale (i.e., MR nanosystems), in this study, thermally-assisted-occupation density functional theory (TAO-DFT) is adopted to explore the electronic properties of n-acenes (n = 2--10), containing n linearly fused benzene rings, in OEEFs, where the OEEFs of various electric field strengths are applied along the long axes of n-acenes. According to our TAO-DFT calculations, the ground states of n-acenes in OEEFs are singlets for all the cases examined. The effect of OEEFs is shown to be significant on the vertical ionization potentials and vertical electron affinities of ground-state n-acenes with odd-number fused benzene rings. Moreover, the MR character of ground-state n-acenes in OEEFs increases with the increase of the acene length and/or the electric field strength.

The automated transcription of handwritten characters into a legible output is a multi-faceted process with diverse applications. In this paper, a novel approach to optical character recognition (OCR) for handwritten digits is proposed that, in certain components, exceeds current architectures in terms of accuracy, effectiveness, adjustability, temporal efficiency, and/or computational simplicity. This model succeeds in the adoption and enhancement of deprecated or obsolete algorithms across eight steps of image pre-processing—normalization, grayscaling, thresholding/binarization, noise removal, skew-correction, skeletonization/thinning, line separation, and character segmentation. The aforementioned model is evaluated with the use of a Convolutional Neural Network (CNN) leveraging the Balanced eMNIST dataset for training and testing. By suggesting contour-based feature extraction methods as alternatives to pixel-by-pixel iteration, the proposed paradigm demonstrates its capacity to serve as a suitable alternative to current, commonly used algorithms and computational techniques for textual image classification.

Relationships between the Farey sequence and the Riemann hypothesis other than the Franel-Landau theorem are discussed. Whether a function similar to Chebyshev’s second function is square-root close to a line having a slope different from 1 is discussed. The nontrivial zeros of the Riemann zeta function can be used to approximate many functions in analytic number theory. For example, it could be said that the nontrival zeta function zeros and the Möbius function generate in essence the same function - the Mertens function. A different approach is to start with a sequence that is analogous to the nontrivial zeros of the zeta function and follow the same procedure with both this sequence and the nontrivial zeros of the zeta function to generate in essence the same function. A procedure for generating such a function is given.

Characters are one of the most important elements in composing digital animation. The appear-ance and voice of a character should be designed to express the personality and values of the character. However, it is not easy for animation producers to harmoniously match the appear-ance and voice of a character. Advances in deep learning technology have made it possible to overcome this limitation. To achieve this, firstly, an audio-visual dataset of characters is required. In this study, we construct and verify a Korean audio-visual dataset consisting of frontal face im-ages of various characters and short voice clips. We developed an application that can automati-cally extract the frontal face image and a short voice clip of a character by collecting videos up-loaded to YouTube. Through this, a dataset consisting of a total of 1,522 face images and a total of 7,999 seconds of voice clips was built based on 490 characters. Furthermore, we automatically la-bel characters by gender and age to validate the dataset. The dataset built in this study is expected to be used in various deep learning fields, such as classification, generative adversarial networks, and speech synthesis.

We study factorization properties of continuous homomorphisms defined on subgroups (or submonoids) of products of (para)topological groups (or monoids). A typical result is the following one: Let $D=\prod_{i\in I}D_i$ be a product of paratopological groups, $S$ be a dense subgroup of $D$, and $\chi$ a continuous character of $S$. Then one can find a finite set $E\subset I$ and continuous characters $\chi_i$ of $D_i$, for $i\in E$, such that $\chi=\big(\prod_{i\in E} \chi_i\circ p_i\big)\hs1\res\hs1 S$, where $p_i\colon D\to D_i$ is the projection.

Optical Character Recognition (OCR) on historical printings is a challenging task mainly due to the complexity of the layout and the highly variant typography. Nevertheless, in the last few years great progress has been made in the area of historical OCR, resulting in several powerful open-source tools for preprocessing, layout recognition and segmentation, character recognition and post-processing. The drawback of these tools often is their limited applicability by non-technical users like humanist scholars and in particular the combined use of several tools in a workflow. In this paper we present an open-source OCR software called OCR4all, which combines state-of-the-art OCR components and continuous model training into a comprehensive workflow. A comfortable GUI allows error corrections not only in the final output, but already in early stages to minimize error propagations. Further on, extensive configuration capabilities are provided to set the degree of automation of the workflow and to make adaptations to the carefully selected default parameters for specific printings, if necessary. Experiments showed that users with minimal or no experience were able to capture the text of even the earliest printed books with manageable effort and great quality, achieving excellent character error rates (CERs) below 0.5%. The fully automated application on 19th century novels showed that OCR4all can considerably outperform the commercial state-of-the-art tool ABBYY Finereader on moderate layouts if suitably pretrained mixed OCR models are available. The architecture of OCR4all allows the easy integration (or substitution) of newly developed tools for its main components by standardized interfaces like PageXML, thus aiming at continual higher automation for historical printings.

Nowadays people express their opinions on social media. Also provides product reviews on eCommerce websites and responds to various news as comments. It is necessary to know the polarity and aspect of various posts and comments for business, education and security. Aspect-based sentiment analysis (ABSA) predicts text category and polarity. In this paper, we proposed a deep learning framework Deep-ABSA for aspect-based sentiment analysis from Bangla texts. Our proposed framework is a multi-channel architecture. We implemented the word embedding, Bi-LSTM with the attention mechanism for one channel. And for another channel, we adopted the character-embedded convolutional neural network. Finally, we concatenated both channels for adjoining the features of each channel. We obtained an adequate performance from our proposed framework for aspect term analysis from Bangla sentences.

Robots for communication are developed extensively with emphasis on sympathy. This study deals with the growth of character and the control of its operation accordingly. The child has time to be alone with the nature of his/her robot friend. The child can interact with other people's emotional expressions through a robot. Step by step, the robot character will grow as the child grows. Through design studies, qualitative processes such as {customer experience audit, eye tracking, mental model diagrams, semantic differences} have been executed for the results. The participatory behavior research approach through user travel is mapped from the user's lead to the evidence-based design. This research considers how the synthetic characteristics can be applied to the physical growth of robot toys through the product design process. With the development of robot toy "Buddy", we tried making two variations on the robot to achieve recognizable growth. (1) A one-dimensional height scaling and (2) facial expression including the distance between two eyes on the screen. Observations represented children's reactions when "Buddy" was released to with the children. As an independent synthetic character, the robot was recognized by children who had the designed function. Robots for training may require more experimentation.

Heritage conservation area designation is often resisted by communities due to concerns with overly strict regulations for property alterations and negative impacts on property values. This paper addresses these concerns by examining Freemans Bay and Onehunga – two Special Character Areas (SCAs) in Auckland, New Zealand. A property value analysis was used to assess the impact of SCA designation on property values and an online questionnaire survey gathered information on homeowners’ experiences and levels of satisfaction with living in an SCA. The results indicate that designated SCA properties have higher average values than non-designated properties and homeowners are overwhelmingly satisfied with living in a SCA. The main benefits are a sense of community and having certainty around the look and feel of their neighbourhood into the future. The main issue identified by respondents is the requirement for Resource Consent. The majority of people who had gone through the process found it to be a negative experience because of the high cost in terms of time and money. A historic urban landscape approach to the development of management plans and design guidelines is recommended to improve the implementation of the Special Character Areas in Auckland and beyond.

With the development of educational technology, machine learning and deep learning provide technical support for traditional classroom observation assessment. However, in real classroom scenarios, the technique faces challenges such as lack of clarity of raw images, complexity of datasets, multi-target detection errors and complexity of character interactions.Based on the above problems, a student classroom behavior recognition network incorporating super-resolution and target detection is proposed. To cope with the problem of unclear original images in the classroom scenario, SRGAN (Super Resolution Generative Adversarial Network for Images) is used to improve the image resolution and thus the recognition accuracy.To address the dataset complexity and multi-targeting problems, feature extraction is optimized and multi-scale feature recognition is enhanced by introducing AKConv and LASK attention mechanisms into the Backbone module of YOLOv8s algorithm. To improve the character interaction complexity problem, the CBAM attention mechanism is integrated to enhance the recognition of important feature channels and spatial regions. Experiments show that it can detect six behaviors of students raising their hands, reading, writing, playing cell phones, looking down, and lying on the table in high-definition images. And the accuracy and robustness of this network are verified.Compared with small target detection algorithms such as Faster R-CNN, YOLOv5, and YOLOv8s, this network has better detection performance and can efficiently deal with the behavior recognition of multiple students.

This paper propose an original approach of achieving a Cymatics based visual perception of image-extracted text. In this context, an effective approach for automated text detection and recognition for the natural scene images is proposed. The incoming image is firstly enhanced by employing CLAHE and DWT. Afterwards, the text regions of the enhanced image are detected by employing the MSER feature detector. The non-text MSERs are removed by employing the geometrical and contour based filters. The remaining MSERs are grouped into words or phrases by finding out similarities between them. The text recognition is performed by employing an OCR function. The extracted text is sequentially analysed on character by character basis. Each character is converted into a methodical acoustic excitation. Finally, these excitations are converted into the systematic visual perceptions by using the phenomenon of Cymatics. The system functionality is tested with an experimental setup. For the case of studied natural scenes, the suggested approach achieves 80% precision in text localization and 53% precision in end-to-end text recognition. The devised system principle is novel and can be employed in various applications like visual art, encryption, education, integration of impaired people, etc.

Taking a DNA-sequence, a word with letters/bases A, T, G and C, as the relation between the generators of an infinite group $\pi$, one can discriminate two important families: (i) the cardinality structure for conjugacy classes of subgroups of $\pi$ is that of a free group on $1$ to $4$ bases and the DNA word, viewed as a substitution sequence, is aperiodic. (ii) The cardinality structure for conjugacy classes of subgroups of $\pi$ is not that of a free group, the sequence is generally not aperiodic and topological properties of $\pi$ have to be determined differently. The two cases rely on DNA conformations such as A-DNA, B-DNA, Z-DNA, G-quadruplexes, etc. We found a few salient results: Z-DNA, when involved in transcription, replication and regulation in a healthy situation implies (i). The sequence of telomeric repeats comprising $3$ distinct bases, most of the time, satisfies (i). For $2$-base sequences in the free case (i) or non free case (ii), the topology of $\pi$ may be found in terms of the $SL(2,\mathbb{C})$ character variety of $\pi$ and the attached algebraic surfaces. The linking of two unknotted curves --the Hopf link-- may occur in the topology of $\pi$ in cases of biological importance, in telomeres, G-quadruplexes, hairpins and junctions, a feature we already found in the context of models of topological quantum computing. For $3$- and $4$ base sequences, other knotting configurations are noticed and a building block of the topology is the $4$-punctured sphere. Our methods have the potential to discriminate potential diseases associated to the sequences.

Many children who live in the interior and mountainous areas of Papua-Indonesia do not get the right of education. This research aims to formulate a theoretical concept of boarding school-based character education by implementing Papuan cultural contextual education in the process of education. The method used is a qualitative method with a grounded theory approach. The research participants were 14 people. Data were collected through semi-structured interviews and textual analysis of the interview results. The data analysis technique uses the Atlas.ti application by using three levels of coding: open coding, axial coding, and selective coding. The research results show that there are six main concepts as a model of boarding school character education: personal development, spiritual development, extracurricular activities, clean and healthy lifestyles, learning from inspirational figures, and academic development. These six theoretical concepts can be divided into internal and external character building. One of the uniqueness of character education is the integration of local cultural values in the whole process of character education of the children, both in the school environment and in the dormitory. The results of the study provide insights for educators, schools, and government on different forms of character education models.

In this computational study, we investigate the electronic properties of zigzag graphene nano-parallelograms (GNPs), which are parallelogram-shaped graphene nanoribbons of various widths and lengths, using thermally-assisted-occupation density functional theory (TAO-DFT). Our calculations reveal a monotonic decrease in the singlet-triplet energy gap as the GNP length increases. The GNPs possess singlet ground states for all the cases examined. With the increase of GNP length, the vertical ionization potential and fundamental gap decrease monotonically, while the vertical electron affinity increases monotonically. Besides, as the GNP length increases, the symmetrized von Neumann entropy increases monotonically, denoting an increase in the degree of multi-reference character associated with ground-state GNPs. The occupation numbers and real-space representation of active orbitals indicate that there is a transition from the nonradical nature of the shorter GNPs to the increasing polyradical nature of the longer GNPs. In addition, the edge/corner localization of active orbitals is found for the wider and longer GNPs.

It is shown that the representation theory of some finitely presented groups thanks to their $SL_2(\mathbb{C})$ character variety is related to algebraic surfaces. We make use of the Enriques-Kodaira classification of algebraic surfaces and the related topological tools to make such surfaces explicit. We study the connection of $SL_2(\mathbb{C})$ character varieties to topological quantum computing (TQC) as an alternative to the concept of anyons. The Hopf link $H$, whose character variety is a Del Pezzo surface $f_H$ (the trace of the commutator), is the kernel of our view of TQC. Qutrit and two-qubit magic state computing, derived from the trefoil knot in our previous work, may be seen as TQC from the Hopf link. The character variety of some two-generator Bianchi groups as well as that of the fundamental group for the singular fibers $\tilde{E}_6$ and $\tilde{D}_4$ contain $f_H$. A surface birationally equivalent to a $K_3$ surface is another compound of their character varieties.

RNA transcripts play a crucial role as witnesses of gene expression health. Identifying disruptive short sequences in RNA transcription and regulation is essential for potentially treating diseases. Let’s delve into the mathematical intricacies of these sequences. We’ve previously devised a mathematical approach for defining a “healthy” sequence (10.14218/GE.2023.00079). This sequence is characterized by having at most four distinct nucleotides (denoted as nt≤4). It serves as the generator of a group denoted as fp. The desired properties of this sequence are as follows: fp should be close to a free group of rank nt−1, it must be aperiodic, fp should not have isolated singularities within its SL2(C) character variety (specifically within the corresponding Groebner basis). Now, let’s explore the concept of singularities. There are cubic surfaces associated with the character variety of a four-punctured sphere denoted as S24. When we encounter these singularities, we find ourselves dealing with some algebraic solutions of a dynamical second-order differential (and transcendental) equation known as the Painlevé VI equation (10.3390/dynamics4010001). In certain cases, S24 degenerates, in the sense that two punctures collapse, resulting in a “wild” dynamics governed by the Painlevé equations of an index lower than VI. In our paper, we provide examples of these fascinating mathematical structures within the context of miRNAs. Specifically, we find a clear relationship between decorated character varieties of Painlevé equations and the character variety calculated from the seed of oncomirs. These findings should find applications in cancer research.

Bipolar disorder (BD) is a high suicide-risk mental disorder. The purpose of this study was to identify the relationship between temperament and character traits with suicide probability, suicide attempt and perceived stress level in patients with BD. A total of 39 euthymic patients with bipolar disorder who had a history of suicide attempt and 39 euthymic patients without a history of suicide attempt were included in this study. Sociodemographic and clinical data form, Hamilton Depression Rating Scale (HDRS), Young Mania Rating Scale (YMRS), The Structured Clinical Interview for DSM-5-Clinician Version (SCID-5/CV), Temperament and Character Inventory (TCI), Perceived Stress Scale (PSS), Suicide Probability Scale were used for obtaining the data. HDRS, PSS and SPS scores of the group comprised of patients who attempted suicide were higher than the other group. There was no significant difference between the group of patients who had attempted suicide and the other group in terms of temperament characteristics. In the group of patients who had attempted suicide, self-directedness (SD) and cooperativeness (CO) scores were lower and self-transcendence (ST) score was higher than the other group. HA and ST were positively and SD negatively associated with SPS scores. In the regression analysis for suicide risk, the factors most associated with suicide risk were high HDRS and low CO score. Low SD in BD, high ST with CO may be associated with suicide attempt. Alongside low SD, high HA and ST may be associated with suicidal ideation. Treating residual depressive symptoms can reduce the risk of suicide.

The rural road landscape is crucial in forming rural areas' landscape character (LC). As a platform for portraying the rural landscape, the rural roads demonstrate the area's unique natural and cultural characteristics to the visitors. However, with the continuous development of rural areas, the rural LC has been severely impacted, thus impacting visitors' visual experience. In order to preserve and protect the rural landscape, this study aims to assess the visual quality of rural road landscapes based on public preference and heatmap analysis. The results indicated that most of the participants had a higher level of preference for rural landscapes with open horizontal views represented by agricultural areas such as paddy fields. It was also found that different paddy field characters based on their planting stages can also positively affect the visual quality of rural road landscapes. The study also revealed that rural LCs with roadside settlements, commercial structures, mixed agricultural crops, and vegetation received low preference ratings. These characters negatively impact the visual quality of the rural road landscape. These findings provide significant insight for planners and decision-makers regarding protecting and preserving the essential rural road landscapes for the rural tourism experience.

Conjugated singlet ground state diradicals have received remarkable attention owing to their potential applications in optoelectronic devices. A distinctive character of these systems is the location of the double exciton state, a low lying excited state dominated by the doubly excited H,H→L,L configuration, which may influence optical and other photophysical properties. In this contribution we investigate this specific excited state, for a series of recently synthesized conjugated diradicals, employing time dependent density functional theory based on the unrestricted parallel spin reference configuration in the spin-flip formulation (SF-TDDFT) and standard TD calculations based on the unrestricted antiparallel spin reference configuration (TDUDFT). The quality of the computed results is assessed considering diradical and multiradical descriptors and the excited state wavefunction composition.

Elaborate sound design, including background music, ambient sounds (sounds describing the game world), and character sounds (sounds generated by the character’s actions), plays a pivotal role in modern videogames. However, the influence of these different types of sound on the player experience has not been extensively researched. This study examines the influence of these sound types on immersion, avatar identification, fun and perceived competence. In two experiments, participants played League of Legends in four different sound conditions. The first experiment revealed a non-significant trend in the effect of character sound on avatar identification. Ambient sounds, however, were limited in this experiment because the task restricted participants’ movement across the game map. Consequently, we adapted the task to allow for a wider variety of ambient sounds in the second experiment. Here, a significant impact of character sounds on immersion, avatar identification, and fun, was observed, as well as an interaction effect of character sounds and ambient sounds on fun. Furthermore, we observed a trend, though not statistically significant, suggesting that ambient sounds may influence the player’s sense of flow. These findings underline the distinct effects of different sound types and we discuss implications for the design of sound in video games.

Quite a number of new metered parking systems have been introduced in recent years by the local authorities of various spa towns in Poland in connection with home zone conversion projects. The traffic signs posted in these locations were limited to the beginning and end of the demarcated parking area. Traffic circle (TC) is an example of traffic calming measures (TCM) used in home zones to slow down the traffic (case study – home zone in a small spa village). This article presents the results of a study investigating the speed reductions obtained with a home zone and traffic circle used as traffic calming measures. The indispensable speed surveys were carried out in relation to this study in two periods: in summer when the streets are crowded with tourists and in September with little pedestrian traffic. Two research hypotheses were formulated as part of the speed data analysis to verify the slowing effect of traffic circle and the relevance of traffic circles design parameters and location, road function and the surrounding streetscape. For each hypothesis statistical analyses were carried out using two nonparametric tests: two-sample Kolmogorov–Smirnov test and median test. The third research hypothesis formulated in this study was related to sustainable development factors related to fuel consumption and traffic-related air pollution including carbon dioxide, carbon monoxide, nitrogen oxide and hydrocarbons. This hypothesis was verified by estimating the amount of air pollution in the home zone under analysis in three different situations (scenarios): in summer with the travel speed reduced by pedestrian traffic to ca. 8–10 km/h and in September with a small number of pedestrians and 20–25 km/h resulting speed between traffic circles, reduced at traffic circle, and in a theoretical 30 km/h zone with 25–30 km/h assumed speed between traffic circles, dropping at traffic circle. These analyses confirmed the appropriateness of traffic circle as a home zone traffic calming measure, as long as its design is based on a detailed analysis of the relevant factors, including location, road function and the surrounding streetscape.

We recently proposed that topological quantum computing might be based on $SL(2,\mathbb{C})$ representations of the fundamental group $\pi_1(S^3\setminus K)$ for the complement of a link $K$ in the $3$-sphere. The restriction to links whose associated $SL(2,\mathbb{C})$ character variety $\mathcal{V}$ contains a Fricke surface $\kappa_d=xyz -x^2-y^2-z^2+d$ is desirable due to the connection of Fricke spaces to elementary topology. Taking $K$ as the Hopf link $L2a1$, one of the three arithmetic two-bridge links [the Whitehead link $5_1^2$, the Berge link $6_2^2$, the double-eight link $6_3^2$] or the link $7_3^2$, the $\mathcal{V}$ for those links contains the reducible component $\kappa_4$, the so-called Cayley cubic. In addition, the $\mathcal{V}$ for the later two links contains the irreducible component $\kappa_3$, or $\kappa_2$, respectively. Taking $\rho$ to be a representation with character $\kappa_d$ ($d<4$), with $|x|,|y|,|z| \le 2$, then $\rho(\pi_1)$ fixes a unique point in the hyperbolic space $\mathcal{H}_3$ and is conjugate to a $SU(2)$ representation (a qubit). Even though details on the physical implementation remain open, more generally, we show that topological quantum computing may be developed from the point of view of three-bridge links, the topology of the $4$-punctured sphere and Painlev\'e VI equation. The $0$-surgery on the $3$ circles of the Borromean rings L6a4 is taken as an example.

Our recent work has focused on the application of infinite group theory and related algebraic geometric tools in the context of transcription factors and microRNAs. We were able to differentiate between “healthy" nucleotide sequences and disrupted sequences that may be associated with various diseases. In this paper, we extend our efforts to the study of messenger RNA metabolism, showcasing the power of our approach. We investigate (i) mRNA translation in prokaryotes and eukaryotes, (ii) polyadenylation in eukaryotes, which is crucial for nuclear export, translation, stability, and splicing of mRNA, (iii) miRNAs involved in RNA silencing and post-transcriptional regulation of gene expression, and (iv) the identification of disrupted sequences that could lead to potential illnesses. To achieve this, we employ (a) infinite (finitely generated) groups fp, with generators representing the r+1 distinct nucleotides and a relation between them [e.g., the consensus sequence in the mRNA translation (i), the poly(A) tail in item (ii), and the miRNA seed in item (iii)], (b) aperiodicity theory, which connects “healthy groups" fp to free groups Fr of rank r and their profinite completion F^r, and (c) the representation theory of groups fp over the space-time-spin group SL2(C), highlighting the role of surfaces with isolated singularities in the character variety. Our approach could potentially contribute to the understanding of the molecular mechanisms underlying various diseases and help develop new diagnostic or therapeutic strategies.

Recent advancements in Artificial Intelligence (AI), Deep Learning (DL), and computer vision have revolutionized various industrial processes through image classification and object detection. State-of-the-art Optical Character Recognition (OCR) and Object Detection (OD) technologies, such as YOLO and PaddleOCR, have emerged as powerful solutions for addressing challenges in recognizing textual and non-textual information on printed stickers. However, a well-established framework integrating these cutting-edge technologies for industrial applications still needs to be discovered. In this paper, we propose an innovative framework that combines advanced OCR and OD techniques to automate visual inspection processes in an industrial context. Our primary contribution is a comprehensive framework adept at detecting and recognizing textual and non-textual information on printed stickers within a company, harnessing the latest AI tools and technologies for sticker information recognition. Our experiments reveal an overall macro accuracy of 0.88 for the sticker OCR across three distinct patterns. Furthermore, the proposed system goes beyond traditional Printed Character Recognition (PCR) by extracting supplementary information, such as barcodes and QR codes present in the image, significantly streamlining industrial workflows and minimizing manual labor demands.

In the field of computer vision, large-scale image classification tasks are both important and highly challenging. With the ongoing advances in deep learning and optical character recognition (OCR) technologies, neural networks designed to perform large-scale classification play an essential role in facilitating OCR systems. In this study, we developed an automatic OCR system designed to identify up to 13,070 large-scale printed Chinese characters by using deep learning neural networks and fine-tuning techniques. The proposed framework comprises four components, including training dataset synthesis and background simulation, image preprocessing and data augmentation, the process of training the model, and transfer learning. The training data synthesis procedure is composed of a character font generation step and a background simulation process. Three background models are proposed to simulate the factors of the background noise and anti-counterfeiting patterns on ID cards. To expand the diversity of the synthesized training dataset, rotation and zooming data augmentation are applied. A massive dataset comprising more than 19.6 million images was thus created to accommodate the variations in the input images and improve the learning capacity of the CNN model. Subsequently, we modified the GoogLeNet neural architecture by replacing the FC layer with a global average pooling layer to avoid overfitting caused by a massive amount of training data. Consequently, the number of model parameters was reduced. Finally, we employed the transfer learning technique to further refine the CNN model using a small number of real data samples. Experimental results show that the overall recognition performance of the proposed approach is significantly better than that of prior methods and thus demonstrate the effectiveness of proposed framework, which exhibited a recognition accuracy as high as 99.39% on the constructed real ID card dataset.

The symmetries of a Riemann surface $\Sigma \setminus \{a_i\}$ with $n$ punctures $a_i$ are encoded in its fundamental group $\pi_1(\Sigma)$. Further structure may be described through representations (homomorphisms) of $\pi_1$ over a Lie group $G$ as globalized by the character variety $\mathcal{C}=\mbox{Hom} (\pi_1,G)/G$. Guided by our previous work in the context of topological quantum computing (TQC) and genetics, we specialize on the $4$-punctured Riemann sphere $\Sigma=S_2^{(4)}$ and the \lq space-time-spin' group $G=SL_2(\mathbb{C})$. In such a situation, $\mathcal{C}$ possesses remarkable properties (i) a representation is described by a $3$-dimensional cubic surface $V_{a,b,c,d}(x,y,z)$ with $3$ variables and $4$ parameters, (ii) the automorphisms of the surface satisfy the dynamical (non linear and transcendental) Painlev\'e VI equation (or $P_{VI}$), (iii) there exists a finite set of $1$ (\mbox{Cayley-Picard})+$3$ (\mbox{continuous platonic})+$45$ (\mbox{icosahedral}) solutions of $P_{VI}$. In this paper we feature on the parametric representation of some solutions of $P_{VI}$, (a) solutions corresponding to algebraic surfaces such as the Klein quartic and (b) icosahedral solutions. Applications to the character variety of finitely generated groups $f_p$ encountered in TQC or DNA/RNA sequences are proposed.

Theories of reading comprehension emphasize decoding and listening comprehension as two essential components. The current study aimed to investigate how Chinese character decoding and context-driven auditory semantic integration contribute to reading comprehension in Chinese middle school students. Seventy-five middle school students were tested. Context-driven auditory semantic integration was assessed with speech-in-noise tests in which the fundamental frequency (F0) contours of spoken sentences were either kept natural or acoustically flattened with the latter requiring a higher degree of contextual information. Statistical modelling with hierarchical regression was conducted to examine the contributions of Chinese character decoding and context-driven auditory semantic integration to reading comprehension. Performance on Chinese character decoding and auditory semantic integration scores with the flattened (but not natural) F0 sentences significantly predicted reading comprehension. Furthermore, the contributions of these two factors to reading comprehension were better fitted with an additive model instead of a multiplicative model. These findings indicate that reading comprehension in middle schoolers is associated with not only character decoding but also the listening ability to make better use of the sentential context for semantic integration in a severely degraded speech-in-noise condition. The results add to our better understanding of the multi-faceted reading comprehension in children. Future research could further address the age-dependent development and maturation of reading skills by examining and controlling other important cognitive variables, and apply neuroimaging techniques such as functional magmatic resonance imaging to reveal the neural substrates for the contribution of auditory semantic integration and the observed additive model to reading comprehension.

Synesthesia is a psychological phenomenon where sensory signals become mixed. Input to one sensory modality produces an experience in a second, unstimulated modality. In “grapheme-color synesthesia”, viewed letters and numbers evoke mental imagery of colors. The study of this condition has implications for increasing our understanding of brain architecture and function, language, memory and semantics, and the nature of consciousness. In this work, we propose a novel application deep learning to model perception in grapheme-color synesthesia. Achromatic letter images, taken from database of handwritten characters, are used to induce synesthesia. Results show the model learns to accurately create a colored version of the inducing stimulus, according to a statistical distribution from experiments on a sample population of grapheme-color synesthetes. The spontaneous, creative mental imagery characteristic of the synesthetic perceptual experience is reproduced by the model. A model of synesthesia that generates testable predictions on brain activity and behavior is needed to complement large scale data collection efforts in neuroscience, especially when articulating simple descriptions of cause (stimulus) and effect (behavior). The research and modeling approach reported here begins to address this need.

Transcription factors (TFs) and microRNAs (miRNAs) are co-actors in genome-scale decoding and regulatory networks, often targeting common genes. In this paper, we describe the algebraic geometry of both TFs and miRNAs thanks to group theory. In TFs, the generator of the group is a DNA-binding domain while, in miRNAs, the generator is the seed of the sequence. For such a generated (infinite) group $\pi$, we compute the $SL(2,\mathbb{C})$ character variety, where $SL(2,\mathbb{C})$ is simultaneously a \lq space-time' (a Lorentz group) and a \lq quantum' (a spin) group. A noteworthy result of our approach is to recognize that optimal regulation occurs when $\pi$ looks like a free group $F_r$ ($r =1$ to $3$) in the cardinality sequence of its subgroups, a result obtained in our previous papers. A non free group structure features a potential disease. A second noteworthy result is about the structure of the Groebner basis $\mathcal{G}$ of the variety. A surface with simple singularities (like the well known Cayley cubic) within $\mathcal{G}$ is a signature of a potential disease even when $G$ looks like a free group $F_r$ in its structure of subgroups. Our methods apply to groups with a generating sequence made of two to four distinct DNA/RNA bases in $\{A,T/U,G,C\}$. Several human TFs and miRNAs are investigated in detail thanks to our approach.

Social media platforms have been entirely an undeniable part of the lifestyle for the past decade. Analyzing the information being shared is a crucial step to understanding human behavior. Social media analysis aims to guarantee a better experience for the user and risen user satisfaction. For deriving any further conclusion, first, it is necessary to know how to compare users. In this paper, a hybrid model has been proposed to measure Twitter profiles’ similarity and quantifies the likeness degree of profiles by calculating features considering users’ behavioral habits. For this, first, the timeline of each profile has been extracted using the official TwitterAPI. Then, in parallel, three aspects of a profile are deliberated. Behavioral ratios are time-series-related information showing the consistency and habits of the user. Dynamic time warping has been utilized to compare the behavioral ratios of two profiles. Next, the audience network is extracted for each user, and for estimating the similarity of two sets, Jaccard similarity is used. Finally, for the Content similarity measurement, the tweets are preprocessed respecting the feature extraction method; TF-IDF and DistilBERT for feature extraction are employed and then compared using the cosine similarity method. Results have shown that TF-IDF has slightly better performance; therefore, the more straightforward solution is selected for the model. Similarity level of different profiles. As in the case study, a Random Forest classification model was trained on almost 20000 users revealed a 97.24% accuracy. This comparison enables us to find duplicate profiles with nearly the same behavior and content.

Keywords: Interspecific competition; Character displacements, Behavioral syndrome; Foraging; Pecking; Probing; Sweeping; Ballistic transport, Surface tension transport; Lingual transport

Revealing the time structure of physical or biological objects is usually performed thanks to the tools of signal processing like the fast Fourier transform, Ramanujan sum signal processing and many other techniques. For space-time topological objects in physics and biology, we propose a type of algebraic processing based on schemes in which the discrimination of singularities within objects is based on the space-time-spin group SL(2,C). Such topological objects possess an homotopy structure encoded in their fundamental group and the related SL(2,C) multivariate polynomial character variety contains a plethora of singularities somehow analogous to the frequency spectrum in time structures. Our approach is applied to an Akbulut cork in exotic R4, to an hyperbolic model of topological quantum computing based on algebraic surfaces and to microRNAs in genetics. Such diverse topics reveal the manifold of possibilities of using the concept of a scheme spectrum.

Thermally-assisted-occupation density functional theory (TAO-DFT) has been an efficient electronic structure method for studying the ground-state properties of large electronic systems with multi-reference character over the past few years. To explore the time-dependent (TD) properties of electronic systems (e.g., subject to an intense laser pulse), in this work, we propose a real-time (RT) extension of TAO-DFT, denoted as RT-TAO-DFT. Besides, we employ RT-TAO-DFT to study the high-order harmonic generation (HHG) spectra and related TD properties of molecular hydrogen H2 at the equilibrium and stretched geometries, aligned along the polarization of an intense linearly polarized laser pulse. The TD properties obtained with RT-TAO-DFT are compared with those obtained with the widely used time-dependent Kohn-Sham (TDKS) method. In addition, issues related to the possible spin-symmetry breaking effects in the TD properties are discussed.

Intuitionistic fuzzy set, which can be represented using the triangular intuitionistic fuzzy number (TIFN), is a more generalized platform for expressing imprecise, incomplete and inconsistent information when solving multi-criteria decision-making problems, as well as for reflecting the evaluation information exactly in different dimensions. In this paper, the TIFN has been applied for solving some multi-criteria decision-making problems by developing a new triangular intuitionistic fuzzy geometric aggregation operator, that is the generalized triangular intuitionistic fuzzy ordered weighted geometric averaging (GTIFOWGA) operator, and defining some triangular intuitionistic fuzzy geometric aggregation operators including the triangular intuitionistic fuzzy weighted geometric averaging (TIFWGA) operator, the ordered weighted geometric averaging (TIFOWGA) operator and the hybrid geometric averaging (TIFHWGA) operator. Based on these operators, a new approach for solving multicriteria decision-making problems when the weight information is fixed has been proposed. Finally, the proposed method has been compared with some similar existing computational approaches by virtue of a numerical example to verify its feasibility and rationality.