Search Results (304)

This study examines patterns of Information and Communication Technology (ICT) use during leisure time among non-university students in the Autonomous Community of Andalusia (Spain) and explores their potential to inform environmental education initiatives. Two research questions guided the study: (1) Which devices and usage times characterize students’ digital leisure according to gender and educational level? (2) How can these patterns inform the design of contextualized environmental education actions? A cross-sectional quantitative study was conducted using a survey administered to 1251 students enrolled in Primary Education, Compulsory Secondary Education, Upper Secondary Education (Baccalaureate), and Vocational Training in the cities of Seville, Malaga, Cádiz, and Granada. The questionnaire, consisting of 49 items, assessed the use of television, tablets, mobile phones, computers, and video games during leisure time. Data were analysed using descriptive statistics, inferential analysis (ANOVA), and multivariate analysis (MANOVA). The results highlight the central role of the mobile phone as the dominant device across all educational stages, as well as significant age-related differences in the use of television, tablets, and video games. Gender differences were found only in the time devoted to video gaming. The main contribution of this study lies in providing updated empirical evidence on youth digital leisure within a specific geographical context, identifying opportunities to integrate digital resources into environmental education initiatives that are sensitive to educational stage and gender and aligned with sustainability goals. The use of ICTs is proposed to create interactive educational experiences that prepare students to address ecosocial challenges, promote sustainable development, and foster a stronger connection with the natural environment. Full article

Background: Mild cognitive impairment (MCI) is a high-risk prodromal stage of dementia. While tablet/computer-based computerized cognitive training (CCT) is widely used, its efficacy and gamification’s role need clarification. Objective: This study aimed to evaluate the effect of tablet/computer-based CCT on global cognition in older adults with MCI and explore the impact of gamification. Methods: We systematically searched five databases for RCTs (through October 2025) involving individuals aged ≥55 with MCI. The intervention was task-based CCT via tablets/computers. Primary outcome was global cognition. We used random-effects meta-analysis and subgroup analyses. Results: Nineteen RCTs (1013 participants) were included. CCT demonstrated a significant, moderate positive effect on global cognition (Hedges’ g = 0.57, 95% CI [0.36, 0.78]). A trend suggesting greater benefits with higher gamification was observed: high (g = 0.71), medium (g = 0.46), and low (g = 0.45) degrees. However, subgroup differences were not statistically significant (p = 0.4333). Results were robust in sensitivity analyses. Conclusions: Tablet/computer-based CCT effectively improves global cognition in MCI. The potential additive value of gamification highlights its promise for enhancing engagement and effects, warranting further investigation in larger trials. This systematic review was registered with PROSPERO (CRD420251231618). Full article

Access to Information and Communication Technologies (ICTs) is a critical component for social inclusion and population development. This study aimed to analyze ICT access in Argentine households, considering its distribution according to deprivation conditions and area of residence (urban–rural) at the regional level, and incorporating a spatial association perspective at the departmental level. The percentage of households with Internet access, computers (or tablets), and cell phones with connectivity was examined at the regional level, according to household deprivation type and area of residence. At the departmental level, the analysis was conducted through thematic maps and the estimation of spatial autocorrelation patterns (global and local Moran’s Index). Indicators were constructed using data from the 2022 Population, Household, and Housing Census. Results revealed significant disparities in ICT access, attributable to deprivation conditions and the geographic distribution of households. Spatial autocorrelation patterns with low ICT access were mainly identified in the Northwest (NOA) and Northeast (NEA) regions, while the highest coverage levels were concentrated in the Buenos Aires Metropolitan Area (AMBA), the Pampeana, and Patagonia regions. The evidence highlights the need to design public policies aimed at reducing digital divides. Full article

Background: Polyols are widely used as tablet diluents due to their high solubility, favourable taste, and ability to form robust tablets. Thus, commercially available polyols, such as mannitol and isomalt, can be considered for the preparation of low-drug-dose formulations with a high polyol load. Methods/Results: This study investigated spray-dried mannitol (Mannogem^® XL Opal SD and Pearlitol^® 200 SD) and fluid-bed granulated isomalt (galenIQ™ 720 and galenIQ™ 721) at magnesium stearate levels of 0.5 and 3.0 wt.% and consolidation pressures of 100 and 300 MPa. During the tableting of 100 consecutive tablets, materials displayed different ejection force profiles: galenIQ™ 720 and galenIQ™ 721 demonstrated low and stable ejection pressures; Mannogem^® displayed a lubricant- and compaction pressure-dependent profile, whereas Pearlitol^® produced the highest ejection forces, particularly at 0.5 wt.% magnesium stearate. To elucidate these differences, the used materials were characterised in terms of SEM imaging, moisture content, surface area and porosity analysis, particle size distribution, pXRD, and densification kinetics. Using a compaction simulator, key parameters including pressure–displacement profiles, mean yield pressure, and strain rate sensitivity of the unlubricated materials were experimentally determined, while pressure transmission, residual die-wall pressure, and friction coefficient were computed. Conclusions: The study concluded that variations in tableting properties were primarily governed by moisture content and, for mannitol grades, by manufacturing method-dependent differences in particle microstructure. These insights provide guidance for the rational selection of polyol excipients and appropriate lubrication levels in direct compression tablet formulations. Full article

Background: Tablet manufacturing is challenged by strong dynamic coupling of process parameters, significant material property fluctuations, and delayed quality control, with tablet weight stability being particularly critical in high-speed production. Traditional static optimization methods relying on empirical judgment struggle to manage these dynamics, leading to substantial variations in tablet weight and hardness that severely compromise production efficiency. Methods: This study proposes a data-driven closed-loop control system centered on a novel Iterative Learning Model Predictive Control (IL-MPC) architecture. The core innovation lies in directly integrating iterative learning constraints within the MPC optimization framework. This constraint-embedding mechanism enables systematic utilization of historical batch data while preserving real-time optimization capabilities. The IL-MPC approach achieves enhanced batch-to-batch performance consistency with reduced computational burden, effectively combining the dual advantages of learning and optimization. Results: Simulation experiments and industrial production data validate the practical feasibility of the IL-MPC algorithm. Implementation results demonstrate that the proposed system effectively manages dynamic process variations, significantly improving control precision for both tablet weight and hardness, outperforming conventional control methods. Conclusions: This research breaks through the technical bottleneck of dynamic regulation in tablet manufacturing. The developed IL-MPC framework provides a reproducible closed-loop control paradigm for intelligent pharmaceutical manufacturing, promoting the industry’s transformation toward data-driven models and advancing intelligent drug production. Full article

Background: Hereditary hemorrhagic telangiectasia (HHT) is an inherited vascular bleeding disorder. The most common symptoms are recurrent, severe nosebleeds that occasionally necessitate intervention by an ENT (Ear, Nose, and Throat) specialist, as well as iron-deficiency anemia. Telangiectasia is typically located in the nasal cavity, lips, tongue, fingertips, and the gastrointestinal mucosa. Arteriovenous malformations (AVMs) are located in internal organs (brain, lungs, liver, etc.). The family history is positive for HHT. The diagnosis is based on the Curacao criteria. The endoglin and activin receptor-like kinase 1 genes (ENG and ACVRL1) are the most common mutation sites, leading to elevated endothelial growth factor (VEGF) levels. Methods: We conducted a retrospective analysis in the Department of Internal Medicine, Division of Hematology, and Center of Expertise for Rare Diseases at the University of Debrecen, spanning the period from 2010 to 2025. Records of patients referred with HHT were reviewed concerning demographic data, clinical presentations, laboratory findings, and treatment approaches. To evaluate management options, epistaxis severity was assessed using the Epistaxis Severity Score (ESS). Results: 48 HHT patients (21 male and 27 female) were included in this retrospective study. Genetic testing was positive in each case, showing mutations in the ENG (HHT1 subgroup) or ACVRL1 (HHT2 subgroup) genes. Most of the patients are followed-up with in our department. ESS was calculated at baseline and 6 months after antiangiogenic treatment by two independent physicians. Detailed computed tomography (CT) was performed in all patients. Seven patients were administered desmopressin, a synthetic analog of antidiuretic hormone (ADH), based on our previous experience in reducing bleeding in von Willebrand disease. Antiangiogenic therapy with thalidomide (50 mg oral tablets) was used in 24 patients, while bevacizumab was administered to 5 patients. Most patients experienced a remarkable decrease in epistaxis severity and a reduction in the need for transfusions (ESS before treatment: HHT1 patients, 4.15 ± 1.91 vs. ESS after treatment, 2.62 ± 0.99; HHT2 patients, 3.79 ± 3.19 vs. 2.02 ± 1.91). Subgroup analysis using paired ESS data showed a significant reduction in ESS in both HHT1 and HHT2 patients (p = 0.003 and p = 0.043, respectively). Bevacizumab further reduced the ESS, but the few cases were not suitable for statistical analysis. Serum iron levels significantly increased after antiangiogenic treatment in the HHT2 group (p = 0.01). Conclusions: HHT is a rare vascular bleeding disorder. Daily nosebleeds impair the patients’ quality of life and sometimes lead to severe transfusion-dependent iron-deficient anemia. Frequent hospitalization places a significant burden on the healthcare system. Thus, we have used treatment options for HHT patients that primarily act by inhibiting VEGF, and these treatment modalities have yielded successful results in our hands. Full article

The memory demand of modern applications has been rapidly increasing with the continuous growth of data volume across industrial and academic domains. As a result, computing devices (i.e., IoT devices, smartphones, and tablets) often experience memory shortages that degrade system performance and quality of service by wasting CPU cycles and energy. Thus, most operating systems rely on the swap mechanism to mitigate the memory shortage situation in advance, even if the swap memory fragmentation problem occurs over time. In this paper, we analyze the fragmentation behavior of the swap memory space within storage devices over time and demonstrate that the latency of swap operations increases significantly under aged conditions. We also propose a new extension of the traditional swap mechanism, called VSwap, that mitigates the swap memory fragmentation problem in advance by introducing two core techniques, virtual migration and address remapping. In VSwap, virtual migration gathers valid swap pages scattered across multiple clusters into contiguous regions within the swap memory space, while address remapping updates the corresponding page table entries to preserve consistency after migration. For experiments, we enable VSwap on the traditional swap mechanism (i.e., kswapd) by implementing it with simple code modifications. To confirm the effectiveness of VSwap, we performed a comprehensive evaluation based on various workloads. Our evaluation results confirm that VSwap is more useful and highly valuable than the original swap mechanism. In particular, VSwap improves the overall performance up to 48.18% by harvesting available swap memory space in advance with negligible overhead; it performs close to the ideal performance. Full article

Every element of our contemporary lives has changed as a result of the widespread use of computing infrastructure and information technology in daily life. Less focus has been placed on the hardware components that underpin the computing revolution, despite the fact that its effects on software applications have been the most obvious. The computer chip is the most basic component of computer hardware and powers all digital devices. Every gadget, including mainframes, laptops, cellphones, tablets, desktop PCs, and supercomputers, is powered by different computer chips. Although there are many different types of these chips, the biggest producers in this field are AMD (Advanced Micro Devices), Intel, and ARM (Advanced RISC Machines). These companies make processors for both consumer and business markets. Users have compared their products based on a number of factors, including pricing, cache and memory, approaches, etc. This paper provides a comprehensive comparative analysis of Intel, AMD, and ARM processors, focusing on their architectural characteristics and performance within the context of burgeoning artificial intelligence applications. The detailed architectural features, performance evaluation for AI workloads, a comparison of power efficiency and cost, and analysis for current market trends are presented. By thoroughly examining core architectural elements and key performance factors, this work provides valuable insights for users and developers to seek optimal processor choices to maximize AI tool utilization in the contemporary era. Full article

Ensemble techniques are crucial for preprocessing near-infrared (NIR) data, yet effectively integrating information from multiple preprocessing methods remains challenging. While multi-block approaches have been introduced to optimize preprocessing selection, they face issues such as block order dependency, slow optimization, and limited interpretability. This study proposes PFCOVSC—a fast, order-independent, and interpretable ensemble preprocessing strategy integrating multi-block fusion and variable selection. The method combines diverse preprocessed data into a unified matrix and employs the efficient fCovsel technique to select informative variables and construct an ensemble model. Evaluated against SPORT and PROSAC on three public datasets, PFCOVSC substantially reduced prediction root mean squared error (RMSE) on wheat and meat datasets by 17%, 13% and 49%, 20%, respectively, while performing comparably on tablet data. The method also demonstrated advantages in computational speed and model interpretability, offering a promising new direction for preprocessing ensemble strategies. Full article

This paper describes a small, quasi-experimental, mixed method study investigating teacher and child outcomes for a preschool data science intervention condition compared to a business-as-usual comparison condition. The intervention included both hands-on activities and a free digital tool called the Preschool Data Toolbox to engage young children in foundational data science activities. The intervention activities aligned with a learning blueprint that articulated a set of early childhood data science learning goals based on K-12 computer science and early mathematics standards. The intervention supports teachers to implement foundational data science investigations using an intuitive tablet app that scaffolds the DS process through structured and open-ended instructional experiences. Findings from classroom observations, teacher surveys, and interviews indicate high feasibility and engagement, with teachers reporting ease of use, developmental appropriateness, and positive impacts on children’s data acumen and math skills (n = 217). After controlling pre-test scores, children who participated in the intervention demonstrated statistically higher post-test scores (p = 0.001) compared to those in the comparison group, highlighting the effectiveness of the program in fostering early STEM skills. The study underscores the potential of developmentally appropriate DS experiences to foster early learning, support teacher confidence, and prepare children for future academic success, while highlighting the need for further research and professional development to scale such interventions effectively. Full article

According to previous research, young children’s numeracy skills may be scaffolded by practicing on the number line. A number line estimation task (NLET) is often conducted with pen and paper, while linear number games are often implemented on a computer or a tablet. If and how the format—physical or digital—influences the accuracy of the estimations is, however, not well-known. If regarding NLET performance as dependent on specific strategies and hypothesizing that these strategies may be affected by the material used, we may also assume that different materials may either support or hinder children’s learning. In this paper, we explore whether training with a physical versus a virtual NLET game will affect children’s strategies when solving NLETs, and if these strategies relate to the accuracy of the estimations. Sixty-two 6-year-old children played an NLET game (virtual or physical) for three sessions, being scaffolded and guided by a researcher. NLET performance was measured by pre- and post-tests, as well as during the intervention. The results show that even if the condition did not significantly affect the children’s overall numeracy skills, the children in the physical condition did express more advanced strategies during the intervention. These strategies, in turn, predicted NLET performance. Full article

Background/Objective: Film coatings are vital components of many pharmaceutical products consumed orally in solid dosage form, and the optimization of the film coating unit operation is critical to the success of these products. It is essential to maintain adequate film coat thickness on tablets to ensure the elegance, mechanical integrity, and controlled-release functionality of active pharmaceutical ingredients. We aim to evaluate techniques for measuring the film coat thickness of tablets in the pharmaceutical drug product development space as current research primarily focuses on in-line methods at the manufacturing scale. Methods: A total of four tablet types, varying in size, shape, and coating thickness were assessed using Optical Coherence Tomography and X-ray Computed Tomography. The data was then compared to baseline reference values gathered by examining tablets with a Confocal Microscope. A second trial was performed using an alternative Optical Coherence Tomography instrument to verify the accuracy of the data. The methods were also evaluated on additional criteria utilizing a Pugh Matrix. Results: The initial Optical Coherence Tomography yielded measurements that were inconsistent with the values provided by the control for three of the four tablet types; however, the follow-up study provided values within an acceptable range. The X-ray Computed Tomography also provided accurate measurements but presented challenges for precision in relation to the instrument’s resolution capabilities. Based on the assessment of selected criteria, Optical Coherence Tomography is ideal for all clear-coated tablets, while X-ray Computed Tomography is better suited for small tablets with either opaque or clear coats. Conclusions: Optical Coherence Tomography, X-ray Computed Tomography, and the use of a Confocal Microscope are all viable methods for measuring the film coat thickness of tablets. Method selection is not absolute and depends on factors such as safety, ease of use, adaptability, and tablet characteristics. The results of this study will help provide guidance for selecting the most appropriate method for measuring the film coat thickness of a specific tablet. Full article

Digital competence refers to the integration of digital technology in teaching and learning, as outlined in the national curriculum of Estonia for upper secondary schools. This study presents original research findings on Estonian science teachers’ use of digital tools and materials, their digital competence, and the main benefits and challenges they face. The findings emphasize the need for continued professional development, accessible digital resources, and equitable digital infrastructure to maintain Estonia’s leadership in digital science education. A survey of 58 secondary school science teachers revealed that computers (desktops, laptops, and tablets) are the primary digital tools used. The article explores digital literacy advancements in secondary science education, research methodologies used to assess digital tool usage, and key findings from recent studies. However, challenges such as digital equity, technological barriers, and digital fatigue persist. Additionally, discrepancies were found in teachers’ responses regarding digital tool effectiveness, implementation strategies, and perceived barriers. While some teachers reported a successful integration and improved student outcomes, others highlighted difficulties in aligning digital resources with curriculum requirements and pedagogical approaches. Full article

Data over sound (DoS) is an established technique that has experienced a resurgence in recent years, finding applications in areas such as contactless payments, device pairing, authentication, presence detection, toys, and offline data transfer. This study introduces CardiaWhisper, a system that extends the DoS concept to the medical domain by using a medical data-over-sound (MDoS) framework. CardiaWhisper integrates wearable biomedical sensors with home care systems, edge or IoT gateways, and telemedical networks or cloud platforms. Using a transmitter device, vital signs such as ECG (electrocardiogram) signals, PPG (photoplethysmogram) signals, RR (respiratory rate), and ACC (acceleration/movement) are sensed, conditioned, encoded, and acoustically transmitted to a nearby receiver—typically a smartphone, tablet, or other gadget—and can be further relayed to edge and cloud infrastructures. As a case study, this paper presents the real-time transmission and processing of ECG signals. The transmitter integrates an ECG sensing module, an encoder (either a PLL-based FM modulator chip or a microcontroller), and a sound emitter in the form of a standard piezoelectric speaker. The receiver, in the form of a mobile phone, tablet, or desktop computer, captures the acoustic signal via its built-in microphone and executes software routines to decode the data. It then enables a range of control and visualization functions for both local and remote users. Emphasis is placed on describing the system architecture and its key components, as well as the software methodologies used for signal decoding on the receiver side, where several algorithms are implemented using open-source, platform-independent technologies, such as JavaScript, HTML, and CSS. While the main focus is on the transmission of analog data, digital data transmission is also illustrated. The CardiaWhisper system is evaluated across several performance parameters, including functionality, complexity, speed, noise immunity, power consumption, range, and cost-efficiency. Quantitative measurements of the signal-to-noise ratio (SNR) were performed in various realistic indoor scenarios, including different distances, obstacles, and noise environments. Preliminary results are presented, along with a discussion of design challenges, limitations, and feasible applications. Our experience demonstrates that CardiaWhisper provides a low-power, eco-friendly alternative to traditional RF or Bluetooth-based medical wearables in various applications. Full article

Parkinson’s disease (PD) is a progressive neurodegenerative disorder that impairs motor function, including the fine motor control required for handwriting. Traditional diagnostic methods often lack sensitivity and objectivity in the early stages, limiting opportunities for timely intervention. There is a growing need for non-invasive, accessible tools capable of capturing subtle motor changes that precede overt clinical symptoms. Among early PD manifestations, handwriting impairments such as micrographia have shown potential as digital biomarkers. However, conventional handwriting analysis remains subjective and limited in scope. Recent advances in artificial intelligence (AI) and machine learning (ML) enable automated analysis of handwriting dynamics, such as pressure, velocity, and fluency, collected via digital tablets and smartpens. These tools support the detection of early-stage PD, monitoring of disease progression, and assessment of therapeutic response. This paper highlights how AI-enhanced handwriting analysis provides a scalable, non-invasive method to support diagnosis, enable remote symptom tracking, and personalize treatment strategies in PD. This approach integrates clinical neurology with computer science and rehabilitation, offering practical applications in telemedicine, digital health, and personalized medicine. By capturing dynamic features often missed by traditional assessments, AI-based handwriting analysis contributes to a paradigm shift in the early detection and long-term management of PD, with broad relevance across neurology, digital diagnostics, and public health innovation. Full article