Miracle-dz/UniFAR-FTUs huggingface dataset:
An Adaptation of the Coping Cat Program

Generalized anxiety disorder (GAD) during childhood is a common condition with negative implications. This case study describes the successful cognitive-behavioral treatment of a 6-year-old boy with excessive worry and sleep disturbances. Because of the patient’s age, treatment methods were adapted for an early reader. The frequency and intensity of his symptoms (e.g., physiologic arousal, apprehensive expectations, sleep disturbances) were measured over the course of treatment and at 3 and 7 years after treatment. Recommendations are provided for clinicians and students who aim to treat young children with GAD. The results of this intervention suggest a durable and meaningful reduction in GAD-related symptoms.
Influences of an academically oriented preschool curriculum on the development of children – are there negative consequences for the children's socio-emotional competencies?

As a result of public discussions regarding Germany's standing on international rankings of student achievement, increased attention was focused on enhancing cognitive stimulation in preschools. There are some concerns that preschool curricula that focus more on cognitive stimulation rather than on socio-emotional skills might neglect the socio-emotional development of children. These concerns are rooted in the tradition of German preschools focussing more on the stimulation of social than of cognitive skills. This paper examines these claims by drawing on the German preschool programme ‘KiDZ’ in order to analyse the socio-emotional development (well-being, joy of learning, and worry) of children attending a preschool with a more academically oriented curriculum. This study also investigates effects of domain-specific preschool quality and if any effects of participation in KiDZ might be explained by the quality of the preschools. Positive effects of the children's participation in KiDZ are found and will be discussed.
Interference Alignment Transceiver Design by Minimizing the Maximum Mean Square Error for MIMO Interfering Broadcast Channel

An interference alignment (IA) transceiver design scheme for multiple-input-multiple-output (MIMO) multicell multiuser wireless communication systems is proposed by minimizing the maximum mean square error (MSE) of the received symbols to improve fairness among users. The formulated Min-Max MSE optimization problem is not jointly convex on the transmit precoders and receive filters and, thus, is very difficult to solve directly. An iterative method is proposed to solve the optimization problem to get a suboptimal solution instead. Considering that if the receive filters are fixed, the Min-Max MSE problem can be reformulated as a second-order cone programming problem, and if the transmit precoders are fixed, the closed-form receive filters minimizing the receive MSE can be easily obtained, and the formulated Min-Max MSE problem is solved by alternatively optimizing the transmit precoders and the receive filters. The convergence of the proposed algorithm is proved, which shows its feasibility. Furthermore, a robust Min-Max MSE algorithm is proposed to counter the channel uncertainty. Simulation results show that the proposed Min-Max MSE algorithm can achieve IA when the antennas are configured to be strong IA proper and when the users in the network are of the same signal-to-noise ratio (SNR). Analysis indicates that the proposed Min-Max IA transceiver design scheme can significantly improve user fairness with a possible cost of sum-rate reduction. Results also show that the proposed robust design algorithm provides better performance when lacking perfect channel state information (CSI).
Rating Intimacy of Self-Disclosure

Several investigators (cf. 1 ) have discussed the usefulness of distinguishing between the dimensions of breadth (range or amount) and depth (intimacy) in the measurement of self-disclosure. A rather extensive scaling of stimuli for intimacy has been reported ( 2 ) . These authors presented a large number of "statements about various aspects of the self" which had been scaled for intimacy, using both college students and military personnel as raters. However, the large number (671) of items and the large standard deviations associated with many of these items prompted the present re-scaling. The Intimacy Rating Scale represents an attempt to utilize the Taylor and Altman material in such a way as to increase its empirical usefulness. Initially, the 671 items on the 10-point Taylor and Altman inventory were re-scaled to form a three-point system (low, medium, and high intimacy), based on the mean scores from their college student sample. The re-scaled items were then inspected to detect similarities in content so that the number of items might be reduced by generating fewer, but more inclusive, categories. At completion, the scale consisted of 35 categories approximately evenly divided among the three scale values. Twenty-one varied personal statements were then rated by the authors using the Intimacy Rating Scale. These statements were presented to 62 college students (11 male, 51 female), who were asked to rate the intimacy of each statement according to the following system: ( a ) non-intimate, information people would probably be willing to share with someone they did not know well; (b) moderately intimate, information people would probably share only with someone with whom they were fairly close and; ( c ) highly intimate, material people probably would share only with one of their closest friends. The mean intimacy score for each of the 21 statements was then correlated with the ratings for these items established earlier by the authors using the Intimacy Rating Scale. The Pearson product-moment correlation was . 96. This high correspondence between the ratings of intimacy derived from the scale and the ratings by students indicates support for the consensual validity of the Intimacy Rating Scale.
On the $\mathbb{Z}_p$-extensions of a totally $p$-adic imaginary quadratic field -- With an appendix by Jean-Fran\c{c}ois Jaulent

Let $k$ be an imaginary quadratic field, and let $p$ be an odd prime number split in $k$. We analyze some properties of arbitrary $\mathbb{Z}_p$-extensions K/k. These properties are governed by the Hase norm residue symbol of the fundamental $p$-unit of $k$, in terms of the valuation $\delta_p(k)$ of a Fermat quotient, which determines the order of the logarithmic class group $\widetilde{\mathcal{H}_k}$ (Theorem 2.2) and leads, under some conditions, to generalizations of Gold's criterion characterizing $\lambda_p(K/k) = 1$ (Theorems 3.3, 5.1, 5.3). This uses the higher rank Chevalley-Herbrand formulas, for the filtrations of the p-class groups in $K$, that we gave in the 1994's, and the theorem of $\lambda$-stability (2022). This study is in connection with articles of Gold, Sands, Dummit-Ford-Kisilevsky-Sands, Ozaki, Jaulent, Fujii. In Appendix A, is given a general proof, by Jaulent, of the link between $\widetilde{\mathcal{H}_k}$ and $\delta_p(k)$ in a broader context. Numerical illustrations (with pari/gp programs) are given.
Photograph Presentation Order and Range Effects in Visual-Based Outdoor Recreation Research

Visual-based research methods are commonly used to provide an empirical basis for formulating evaluative standards related to recreation use levels. Visual research methods applied in this context are subject to several potential measurement biases. This article examines two such potential biases in visual-based recreation research methods: order effect bias and range effect bias. In a lab setting, respondents evaluated recreation photographs from Rocky Mountain National Park regarding the acceptability of people at one time (PAOT). Results indicated photo presentation order and the PAOT range depicted both had an effect on photograph acceptability ratings. Potential methodological revisions to the visual-based method are discussed.
Non-contact detecting solution ionic strength in microfluidic channel utilizing GHz complementary split-ring resonator (CSRR)

This paper presents a novel microchip integrated with a GHz complementary split-ring resonator (CSRR) and a microfluidic channel for non-contact detecting the ionic strength of solutions. An upper C-ring resonator induced with an underneath linear micro-strip is used to generate the complementary resonance. The induced electromagnetic resonance is sensitive to surrounding material properties including complex permittivity and thickness of materials. The insertion loss of the GHz signal increases with the increasing material permittivity nearby the CSRR. Therefore, this technique is good to measure the ionic strength of solutions without using physical electrodes to contact the solutions. Results show that the developed CSRR chip is capable of detecting NaCl solutions of the concentration ranging in 10−3∼5.0 M with a sensitivity of 1.5 dB/M at high concentration range. The CSRR chip is also capable of distinguishing solutions of same concentration but different ionic charges. The developed CSRR chip has shown its potentials for remote monitoring the solution properties.
StorM: Enabling Tenant-Defined Cloud Storage Middle-Box Services

In an Infrastructure-as-a-Service cloud, tenants rely on the cloud provider to provide "value-added" services such as data security and reliability. However, this provider-controlled service model is less flexible and cannot be customized to meet individual tenants' needs. In this paper, we present StorM, a novel middle-box service platform that allows each tenant to deploy tenant-specific security and reliability services -- in virtualized middle-boxes -- for their cloud data. With such middle-boxes, StorM divides the responsibilities of service creation between tenants and the provider by allowing tenants to customize their own cloud data polices and the provider to offer corresponding infrastructural support. In developing StorM, we address key challenges including network splicing, platform efficiency, and semantic gap. We implement a StorM prototype on top of OpenStack and demonstrate three tenant-defined security/reliability middle-box services, with low performance overhead (<; 10%).
Communication over a wireless network with random connections

A network of nodes in which pairs communicate over a shared wireless medium is analyzed. We consider the maximum total aggregate traffic flow possible as given by the number of users multiplied by their data rate. The model in this paper differs substantially from the many existing approaches in that the channel connections in this network are entirely random: rather than being governed by geometry and a decay-versus-distance law, the strengths of the connections between nodes are drawn independently from a common distribution. Such a model is appropriate for environments where the first-order effect that governs the signal strength at a receiving node is a random event (such as the existence of an obstacle), rather than the distance from the transmitter. It is shown that the aggregate traffic flow as a function of the number of nodes n is a strong function of the channel distribution. In particular, for certain distributions the aggregate traffic flow is at least n/(logn)/sup d/ for some d>0, which is significantly larger than the O(/spl radic/n) results obtained for many geometric models. The results provide guidelines for the connectivity that is needed for large aggregate traffic. The relation between the proposed model and existing distance-based models is shown in some cases.
Holography inspired self-controlled reconfigurable intelligent surface

Among various promising candidate technologies for the sixth-generation (6G) wireless communications, recent advances in microwave metasurfaces have sparked a new research area of reconfigurable intelligent surfaces (RISs). By controllably reprogramming the wireless propagation channel, RISs are envisioned to achieve low-cost wireless capacity boosting, coverage extension, and enhanced energy efficiency. To reprogram the channel, each meta-atom on RIS needs an external control signal, which is usually generated by base station (BS). However, BS-controlled RISs require complicated control cables, which hamper their massive deployments. Here, we eliminate the need for BS control by proposing a self-controlled RIS (SC-RIS), which is inspired by the optical holography principle. Different from the existing BS-controlled RISs, each meta-atom of SC-RIS is integrated with an additional power detector for holographic recording. By applying the classical Fourier-transform processing to the measured hologram, SC-RIS is capable of retrieving the user's channel state information required for beamforming, thus enabling autonomous RIS beamforming without control cables. Owing to this WiFi-like plug-and-play capability without the BS control, SC-RISs are expected to enable easy and massive deployments in the future 6G systems.
Connecting Scientific Reasoning and Causal Inference

Literature on multivariable causal inference (MCI) and literature on scientific reasoning (SR) have proceeded almost entirely independently, although they in large part address the same phenomena. An effort is made to bring these paradigms into close enough alignment with one another to compare implications of the two lines of work and examine how they might illuminate one another. The conclusion is that SR research stands to benefit from recognition that it addresses a broader set of cognitive phenomena than reasoning in contexts that are explicitly scientific, whereas MCI research stands to benefit from recognizing inter- and, especially, intra-individual variability that its methods may have masked. Data reported here based on a merging of the two methodological paradigms support a model in which individuals have available a repertory of different inference strategies or rules (reflecting different criteria for inferences of causality) from which they select variably across occasions, in a dynamic process of theory-evidence coordination.
Rule-Based Sentence Detection Method (RBSDM) for Turkish

The first process of generating a corpus, which is a representative of the language, is the determination of sen-tences, which is very complicated and hard to solve, but an important part of the corpus generation. Different approaches have been tried to find out sentence boundaries in some languages. In Turkish, the most known ways of determining sentence boundaries are using statistics and machine learning. In this study, to determine the sentence boundaries in contemporary Turkish, a rule-based method called “Rule-Based Sentence Detection Method for Turkish (RBSDM)” was developed by considering the agglutinative and rule based structure of Turkish. This method was tested on two different test sets generated by randomly selected columns from two Turkish newspapers. RBSDM determines end of sentences correctly and efficiently, about means of time and other costs, and provides success rate in a range of 99.60% and 99.80%.
A performance study of AsterixDB

Apache AsterixDB is a relatively new Big Data management platform providing ingestion, storage, management, indexing, querying, and analyses of vast quantities of semi-structured information on scalable computer clusters. This paper compares the execution and performance of an early release of Apache AsterixDB with two popular platforms, Apache Hadoop and HPCC Systems, over the 17 PigMix benchmark query scenarios. We discuss the results and also how they have influenced the AsterixDB effort.
Recognition and verification of unconstrained handwritten words

This paper presents a novel approach for the verification of the word hypotheses generated by a large vocabulary, offline handwritten word recognition system. Given a word image, the recognition system produces a ranked list of the N-best recognition hypotheses consisting of text transcripts, segmentation boundaries of the word hypotheses into characters, and recognition scores. The verification consists of an estimation of the probability of each segment representing a known class of character. Then, character probabilities are combined to produce word confidence scores which are further integrated with the recognition scores produced by the recognition system. The N-best recognition hypothesis list is reranked based on such composite scores. In the end, rejection rules are invoked to either accept the best recognition hypothesis of such a list or to reject the input word image. The use of the verification approach has improved the word recognition rate as well as the reliability of the recognition system, while not causing significant delays in the recognition process. Our approach is described in detail and the experimental results on a large database of unconstrained handwritten words extracted from postal envelopes are presented.
TEFL educational principles: a proposal for changing times

Today’s society is influenced by new information technologies, which cause important sociological changes that impact education. As such, the field of EFL today demands different abilities and attitudes from teachers. This paper has two objectives: first, to initiate a reflection on the EFL teachers’ role, taking as an assumption that teachers have been influenced by cultural background experiences in their professional development and that this has caused them to develop a narrow view of ideal methods which may not be appealing for situations, and second, to propose three principles in foreign language teaching that will allow seeing EFL tasks from a wider view: 1) evaluating what comes from one’s cultural background that conforms to a general understanding of what teaching is, 2) re-shaping the teachers’ role in order to align with society’s demands and 3) assuming a dialogic process to building classroom strategies for language teaching and learning.
Generative AI in Education: A Study of Educators' Awareness, Sentiments, and Influencing Factors

The rapid advancement of artificial intelligence (AI) and the expanding integration of large language models (LLMs) have ignited a debate about their application in education. This study delves into university instructors' experiences and attitudes toward AI language models, filling a gap in the literature by analyzing educators' perspectives on AI's role in the classroom and its potential impacts on teaching and learning. The objective of this research is to investigate the level of awareness, overall sentiment towardsadoption, and the factors influencing these attitudes for LLMs and generative AI-based tools in higher education. Data was collected through a survey using a Likert scale, which was complemented by follow-up interviews to gain a more nuanced understanding of the instructors' viewpoints. The collected data was processed using statistical and thematic analysis techniques. Our findings reveal that educators are increasingly aware of and generally positive towards these tools. We find no correlation between teaching style and attitude toward generative AI. Finally, while CS educators show far more confidence in their technical understanding of generative AI tools and more positivity towards them than educators in other fields, they show no more confidence in their ability to detect AI-generated work.
Tuning in to fit in? Acculturation and media use among Chinese students in the United States

This study approaches media use among international students from a uses-and-gratifications perspective to explore the relationship between need for acculturation, acculturative motives, and media use among Chinese students in the United States. Eighty-four Chinese students participated in a survey at a large research university in the Midwestern United States. Results indicate that need for acculturation is, in fact, correlated with media use motives and patterns. An acculturative motive, for example, is correlated with watching US-based TV news programs and using US-based news websites and BBS. Implications and directions for future research are discussed.
Pet companionship and depression: Results from a United States Internet sample

Abstract Using Internet survey data from 2,291 respondents from the United States, we examined socio-demographic predictors of living with a cat or dog. Logistic regressions showed that, for men, being married, living with children, being Midwestern and non-urban increased odds of living with a pet. For women, being White, having a high income, living with children, and living in a rural setting increased odds for pet ownership. Multivariate analyses examining influences of gender, marital status, and pet ownership on depression (CES-D) scores, adjusting for potential confounders, revealed that unmarried women who live with a pet have the fewest depressive symptoms, and unmarried men who live with a pet have the most. These findings suggest that single women benefit from pet companionship, whereas single men may be burdened by it.
A New Ensemble Learning Approach for Microcalcification Clusters Detection

A new microcalcification clusters (MCs) detection method in mammograms is proposed, which is based on a new ensemble learning method. In this paper, , we propose a bagging with adaptive cost adjustment ensemble algorithm; and a new ensemble strategy, called boosting with relevance feedback, by embedding the relevance feedback technique into the heterogenous base learner training, and meanwhile carefully design an effectively systematical feedback scheme, which promise the preventing of overfitting. The ground truth of MCs is assumed to be known as a priori. In our algorithm, each MCs is enhanced by a well designed high-pass filter. Then the 116 dimentional image features are extracted by the feature extractor and fed to the ensemble decision model. In image feature domain, the MCs detection procedure is formulated as a supervised learning and classification problem, and the trained ensemble model is used as a classifier to decide the presence of MCs or not. Case study on microcalcification clusters detection for breast cancer diagnosis illustrates that the proposed algorithm is not only effective but also efficient.
The Need of a Development Assessment Index for e-Governance in India

The purpose of this paper is to discuss and argue on the need of an assessment framework for the development of E-Governance services & practices in various states of India. This can be used to compare the states against each other so as to evaluate their status as per the national & international standards. The study is exploratory in nature as it develops arguments over an Index based on combination of theory, past literature and international reports w.r. t. E-Governance services and associated available infrastructure. It considers research papers from 2000-2015 and major reports on E-Governance after 2006. The need to develop an index based on different parameters is identified. The major areas to be covered up in the development index are online availability and performance of E-Governance service, telecommunication infrastructure, human capital, infrastructure availability and electronic participation by the citizens. Other areas are security and ease of access of the services. Development Index formulation will suggest that the development status for various Indian states, w.r. t. E-Governance, is based on lot of factors like the geographical location, demographic distribution, quality of human resources, and infrastructure present. A state merely having large number of E-Governance services does not become an automatic choice of best state for E-Governance development in the country. The state should be able to justify the overall development rather than being beneficial to just a small section of its population. Indian national E-Governance plan needs to assess the weak zones of the country so as to take initiatives to upgrade them and bid for overall higher ranking in the E-Governance Development Index of United Nations. There is no overall quantitative assessment framework available for E-Governance development in India as of now. So this research is novel with respect to E-Governance development and its assessment.