Miracle-dz/UniFAR-FTUs huggingface dataset:
Soft Computing-Based Schemes for Handover Management in Future Networks

The progression to next generation networks is replete with abundant co-existing technologies. To comply with the Always Best Connected paradigm, several vertical handover decision approaches have been proposed in literature, using advanced techniques and tools. This paper discusses the application of soft computing techniques in the vertical handover decision making process with emphasis on the state of the art techniques. For a comprehensive evaluation, the algorithms are classified into three sets based on the soft computing technique used namely, Fuzzy Logic, Machine Learning and Evolutionary Algorithms and representative handover algorithms in each group are discussed. These papers are categorized in a well-defined structure to bring out their contribution, to underline the pretermitted notions, and to bring forth the emerging issues for future research. This paper summarizes the Soft Computing concepts and reviews its applications in candidate network selection, QoE enhancement, and reducing the unnecessary handovers.
Method of generating face image based on text description of generating adversarial network

Abstract. Generative adversarial networks (GANs) can generate sentences that imitate real language features from discrete spaces, and the implicit expression space learned by training can continuously generate credible sentences. We solve the problem of face image restoration of different genders, different skin colors, and different hair colors through a method of generating face images, in which the face image generated by text description has a better generation effect. We propose a face image generation method (T-GAN) based on generating confrontational text. Due to the particulars of a face, a Word-long short-term memory model is used to extract the text features corresponding to the face. Then combined with the idea of generating a game against “game,” a counter-text network is created, next a third type of input is added to the discriminator, and the real image with unmatched text is composed to strengthen the discriminator’s training effect and force discrimination. The device determines whether the generated image conforms to the text description, so the discriminator can better learn the relationship between the text description and the image content. The experimental results show that, compared with other image generation methods, the face image generated by the proposed method can give high quality generated images with a better effect and less distortion, which can better maintain the original attributes of the image, has the use value, and increases the reduction degree by 3.84%.
Psychopathological and Psychosocial Risk Profile, Styles of Interaction and Mentalization of Adolescent and Young Mother–Infant Dyads

This study examined the psychopathological and psychosocial risk profile and the quality of mother–infant interaction in 98 adolescent and young mother–infant dyads. At their infant’s age of 3 months, mothers filled in a socio-demographic form and completed a test battery: EPDS for depression, STAY-I for anxiety, PSI-SF for parenting stress, MPSS for social support, AAI for maternal attachment and reflective functioning, CECA for adverse childhood experiences, Care-Index and Mind-mindedness coding system for mother–infant interaction. Results showed that motherhood in adolescence was associated with several psychosocial risk factors. Adolescent and young mothers have depression (25%), anxiety (29%) and insecure attachment (65%), with low reflective functioning, of whom 18% have disorganized attachment. A total of 54% of the mothers had at least one adverse childhood experience. Furthermore, adolescent mothers had low sensitivity and mind-mindedness and high intrusiveness, and their infant had low responsiveness and high passive behaviors. Mothers under 18 have experienced more sexual abuse, are more likely to be single and have been followed by child social services more than mothers aged 18–21. Adolescent mothers have a high-risk psychopathological and psychosocial profile that affects their ability to mentalize and build an adequate relationship with the child. It appears to be important to support the adolescent mother–child relationship.
Aperture effect on Rayleigh wave measurements on cement media

Elastic waves are commonly used for the evaluation of concrete structural health. Wave speed is firmly connected to the stiffness and is indicative of strength and damage condition. When access to multiple sides is limited, the evaluation takes place solely from the open surface where all sensors are placed. In this case, the size of the sensor is crucial because of the “aperture effect”. This is basically the phenomenon of wavelengths shorter than the sensor size cancelling each other since both their positive and negative phases act simultaneously on the sensor’s surface. Although this effect has been studied relatively to the amplitude and the frequency content of the surface wave pulses, its influence on velocity has not been similarly studied, even though the velocity value is connected to concrete stiffness, porosity, damage degree and is even empirically used to evaluate the compressive strength. In this study, numerical simulations are conducted with virtual sensors of different sizes to measure the surface wave velocity as well as the dispersion (or its dependence on frequency) in relation to the sensor size on homogeneous and heterogeneous material. The strong effect of sensor size is indicated and suggestions towards rules for reliable measurements on a concrete surface are made. Experimental measurements on cementitious media by sensors of different sizes are also conducted validating the numerical results.
Work-family integration and segmentation in the gig economy: An exploratory study on Airbnb hosts' experiences

Currently, there are four million hosts on Airbnb worldwide (Airbnb (2021). Although the number of Airbnb hosts keeps on rising, little is known about their experiences, as most studies on accommodation sharing services have predominantly focused on guests’ perspectives. This exploratory study investigates the work-family experiences of Airbnb hosts. Following preliminary interviews, we recruited Airbnb hosts to complete an online survey in which we examined the relationships between hosts’ preference for managing their work-family responsibilities (segmentation vs integration) in relation to work-family conflict, satisfaction, and intention to stay with Airbnb, and life satisfaction. Our results—from 136 respondents—indicated that Airbnb hosts who prefer segmentation (separating work and family) experience higher work-family conflict, which was associated with lower job satisfaction, life satisfaction, and intention to stay, compared to those who prefer integration (mixing work and family). Indirect effects were also found; work-family conflict mediated the relationship between segmentation preference and the studied outcomes. Findings suggest that work-family conflict needs to be re-examined in light of the unique demands associated with the gig economy. This study breaks new ground by investigating the work-family lives of Airbnb hosts, with important consequences for individuals, families, guests, and communities.
Optimal Weighted Logarithmic Transformation Converted HMOG Features for Automatic Smart Phone Authentication

This paper intends to develop an automatic behavior based smart phone authentication model by three major phases: Feature extraction Weighted logarithmic transformation and Classification. Initially, from the data related to the touches/gesture of the Smartphone user, Hand Movement, Orientation, and Grasp (HMOG) features are extracted with the aid of grasp resistance and grasp stability. These extracted features are mapped within the particular range by normalizing HMOG. These normalized data are multiplied with the weights followed by logarithmic transformation in the weighted logarithmic transformation phase. As a novelty, the decision making process related to the logarithmic and weight selection is based on the improved optimization algorithm, so called as Modified Threshold-based Whale Optimization Algorithm (MT-WOA). The final feature vectors are fed to DBN for recognizing the authorized users. Finally, a performance based evaluation is performed between the MT-WOA+DBN and the existing models like in terms of various relevant performance measures.
Gate‐Controlled Quantum Dots Based on 2D Materials

2D materials are a family of layered materials exhibiting rich exotic phenomena, such as valley‐contrasting physics. Down to single‐particle level, unraveling fundamental physics and potential applications including quantum information processing in these materials attracts significant research interests. To unlock these great potentials, gate‐controlled quantum dot architectures have been applied in 2D materials and their heterostructures. Such systems provide the possibility of electrical confinement, control, and manipulation of single carriers in these materials. In this review, efforts in gate‐controlled quantum dots in 2D materials are presented. Following basic introductions to valley degree of freedom and gate‐controlled quantum dot systems, the up‐to‐date progress in etched and gate‐defined quantum dots in 2D materials, especially in graphene and transition metal dichalcogenides, is provided. The challenges and opportunities for future developments in this field, from views of device design, fabrication scheme, and control technology, are discussed. The rapid progress in this field not only sheds light on the understanding of spin–valley physics but also provides an ideal platform for investigating diverse condensed matter physics phenomena and realizing quantum computation in the 2D limit.
Importance of and Satisfaction with Domains of Health-Related Quality of Life in Cancer Rehabilitation

Simple Summary Quality of life (QoL) has gained increasing importance in oncology in general, and in cancer rehabilitation in particular. Multiple instruments have been developed to measure QoL. These instruments generally comprise several aspects of QoL, but they do not consider the subjective importance of these aspects. In our study, we assess the satisfaction with such aspects of QoL and the subjective importance of these aspects as well, based on a large sample of participants of a cancer rehabilitation program. The main result was that the subjective importance of domains of QoL is only weakly correlated with the detriments in these dimensions and that health care professionals should also consider what importance the patients attribute to these dimensions of QoL. Abstract Instruments for measuring health-related quality of life (HRQoL) generally do not consider the subjective importance of the dimensions they comprise. The aims of this study were to analyze the subjectively perceived importance of the dimension of HRQoL and to investigate their relationship to the satisfaction ratings with these dimensions. A total of 1108 participants enrolled in a cancer rehabilitation program were surveyed. Patients rated eight dimensions of HRQoL (physical functioning, autonomy, emotional stability, cognitive functioning, social relationships, vitality, absence of pain, and sleep quality), as well as global health in terms of how important those dimensions are to them, and how satisfied they are with them. The dimensions with the highest importance ratings were autonomy and social relationships. There were only small sex differences in the importance ratings, but younger patients rated health as being more important than older patients did. The correlations between the importance ratings and the satisfaction ratings of the specific HRQoL dimensions ranged from −0.06 to 0.40, and the correlation between importance and satisfaction for global health was 0.01. Importance ratings provide relevant information for health care professionals in addition to the HRQoL assessments in the context of cancer rehabilitation.
Research On Embedded Electrical Impedance Measurement System

Based on S3C2440 processor and Linux3.6. 6 kernel, wedeveloped an embedded impedance measurement system. This embedded system employ AD5933 as the impedance sensor, and data communication between AD5933 and S3C2440 processor is implemented with IIC communication protocol. In addition, the measurement resultsare displayed on the interface that is developed with QT.After modeling and solving the inverse problem by Newton Gauss algorithm, the distribution images of the object in the field are finally reconstructed satisfactorily. The research work offers a feasible and portable solution for clinical application of digital medical technology. Introduction Biomedical electrical impedance tomography (BEIT), as a newly noninvasive medical imaging technique, has been attracted much attentions in the field of biomedical engineering [1,2,3]. Compared to traditional imaging techniques, it has many advantages such as low cost, reusable, non-destructive, et al[4]. The BEIT technique which can monitoring the impedance variations between different tissues and organs, provides a new way to diagnose diseases [5,6,7,8]. Currently, the data acquisition module of most impedance measurement system are implemented with field-programmable gate array(FPGA)or digital signal processor(DSP)or PCI extensions for Instrumentation(PXI) and the collected experimental data is send to the computer with USB or serial port to reconstruct the images of the diseased tissue[9,10,11]. However, it quite inconvenient for moving these equipment when displaying the reconstructed images on computer monitors. It doesn’t come near to the standard of current intellectualized medical instrument. In this regard, we in this paper develop aportable system that used for bioelectrical impedance measurement. Arm processor and Linux system are integrated into this embedded system. Impedance data are collected at the measuring end of this system, and the collected data are displayed with QT platform. This portable embedded based impedance measurement system integrate are more convenient and efficient when used for diagnosing diseases.
HLA-G and CD152 Expression Levels Encourage the Use of Umbilical Cord Tissue-Derived Mesenchymal Stromal Cells as an Alternative for Immunosuppressive Therapy

Mesenchymal stromal cells (MSCs) have been used in immunosuppressive therapy due to their therapeutic effects, with the HLA-G molecule seeming to play a fundamental role. This work evaluated alternative MSC sources to bone marrow (BM), namely, umbilical cord tissue (UC), adipose tissue (AD) and dental pulp tissue (DP), and the influence of interferon-γ (IFN-γ) and hypoxia on the cultivation of these cells for use in immunosuppression therapies. Expression of costimulatory markers CD40, CD80 and CD86 and immunosuppressive molecules CD152 and HLA-G was analyzed. Lymphocyte inhibition assays were also performed. Sequencing of the HLA-G gene from exons 1 to 5 was performed using next-generation sequencing to determine the presence of alleles. UC-derived MSCs (UCMSCs) expressed higher CD152 and HLA-G1 under standard cultivation. UCMSCs and DP-derived MSCs (DPSCs) secreted similar levels of HLA-G5. All MSC sources inhibited the proliferation of peripheral blood mononuclear cells (PBMCs); growth under regular versus hypoxic conditions resulted in similar levels of inhibition. When IFN-γ was added, PBMC growth was inhibited to a lesser extent by UCMSCs. The HLA-G*01:04:01:01 allele appears to generate a more efficient MSC response in inhibiting lymphocyte proliferation. However, the strength of this conclusion was limited by the small sample size. UCMSCs are an excellent alternative to BM in immunosuppressive therapy: they express high concentrations of inhibitory molecules and can be cultivated without stimuli, which minimizes cost.
Institutional structures and individual stories: experiences from the front lines of Indigenous educational development in higher education

Since the release of the Truth and Reconciliation Commission (TRC) of Canada’s Calls to Action in 2015, many post-secondary institutions have hired educational developers (EDs) to support instructors in the Indigenization of curricula and pedagogy. Drawing from a Canada-wide study, and best practices identified in the literature, this article explores the experiences of educational developers EDs in these roles, and proposes strategies for how institutions of higher education can better foster transformative change and practices inclusive of First Peoples in Canada.
Megaintegumenta, a seed size mutant of Arabidopsis thaliana.

Important stages of seed development occur before fertilisation during ovule development when the embryo sac and the integuments are formed. This thesis describes the phenotypic and genetic study of a seed size mutant in Arabidopsis thaliana, megaintegumenta (<mnt). The size and weight of seed in this mutant are significantly increased due to extra cell division in the integuments surrounding mnt mutant ovules. The mnt mutation has pleiotropic effects on vegetative and floral development, caused by extra cell divisions and expansion in many organs. Genetic mapping identified the mnt as a mutant allele of AUXIN RESPONSE FACTOR 2 (ARF2), a member of a family of transcription factors that mediate gene expression in response to auxin. Detailed studies of the mnt/arf2 mutant phenotype and ARF2 gene expression provided evidence that ARF2 is a repressor of cell division and organ growth throughout the plant. With a view to using the Arabidopsis mnt/arf2 mutant as a model to investigate methods of seed size enhancement, a number of gene expression studies were conducted, which attempted to gain a deeper understanding of the genetic control of ARF2-Ied seed size control.
Duty cycling for energy efficiency in wireless sensor networks and applications

Wireless sensor networks (WSNs) offer a powerful combination of distributed sensing, computing and communication, which enable a broad spectrum of applications and, at the same time, lead numerous challenges due to their distinctiveness, primarily the non-negligible power consumption from especially radio activities and stringent energy constraints to which sensor nodes are typically subjected. The distinguishing traits of sensor networks have a direct impact on their protocol design at each layer, especially at the Medium Access Control (MAC) layer since it manages transmission scheduling as well as duty cycling for energy conservation. To maximize energy efficiency of WSNs, my thesis studies duty cycling in time and frequency domains for both MAC schedulers and applications. The first part of the thesis focuses on energy efficiency at the MAC layer, including modeling, evaluating and designing MAC schedulers with duty cycling; the second part of the dissertation investigates energy efficiency in applications, which introduces two duty-cycled sensor applications that are deployed in a large building. In the first part of this dissertation, I begin by studying the impact of perfect duty cycling, in addition to perfect transmission scheduling, on the capacity of random wireless networks with single and multiple channels. The analysis of the dutycycled throughput reveals nontrivial scaling gains resulting from the ability to avoid interference by spreading interferers to mutually exclusive times, which corroborates
Nondestructive Characterization of Citrus Fruit by near-Infrared Diffuse Reflectance Spectroscopy (NIRDRS) with Principal Component Analysis (PCA) and Fisher Linear Discriminant Analysis (FLDA)

Abstract The nondestructive characterization of citrus varieties (Egyptian sweet orange, Lane Late navel orange, Australian orange, and Blood orange) was developed based on near-infrared diffuse reflectance spectroscopy (NIRDRS) together with principal component analysis (PCA) and Fisher linear discriminant analysis (FLDA). An experiment for the penetration of NIRDRS into the peel was designed and the effects of different spectral acquisition points were investigated. Pretreatments were used to eliminate the spectral interferences. As an unsupervised pattern recognition method, PCA was used to establish the characterization models. Furthermore, supervised pattern recognition based on PCA and FLDA was employed to enhance the accuracy. The results of the penetration experiments show that near-infrared light enters the citrus peel and is able to characterize the internal composition. Even with the optimized spectral pretreatment, accurate characterization of citrus varieties was not achieved by PCA. However, the accurate characterization of citrus varieties was provided by PCA-FLDA. The accuracies of four spectral acquisition points are 95%, while the characterization accuracies of six spectral acquisition points are 100% combined with optimized spectral pretreatment. Therefore, NIRDRS with PCA-FLDA is suitable for the rapid and nondestructive characterization of citrus varieties.
Stabilization of the cart-inverted-pendulum system using trivial state-feedback to output-feedback control conversion

A new linear observer-free output-feedback controller with five adjustable parameters is proposed to stabilize the cart-inverted-pendulum system (CIP) at the unstable equilibrium point. The controller architecture is deduced from a trivial conversion of the linear state-feedback controller that is obtained using a two-step method. First, based on a set of cart change variables, a slightly modified state-feedback controller is developed. Then, the output-feedback controller is obtained through the judicious combination of the cart step reference input internal model and a convenient open-loop state estimator with the above modified state-feedback controller. The local stability of the output-based control system is conducted using the signature formulas method to get simplified conditions. A partial single parameter tuning method and optimal global single parameter tuning method are proposed for adjusting the controller gains to maximize a new efficiency-based objective function. Numerical simulations are first conducted to reveal the simplicity of output-feedback controller design using the partial tuning method, where the state-feedback gains are assumed to be known. Then, an optimal output-feedback controller is designed using the global tuning method. The proposed output-feedback controller is equivalent in terms of performance efficiency to the best five-parameter output-feedback two PID controller.