Optimized design and preliminary prototype test of a superconducting magnet for 170 GHz gyrotron

Technological advancements driven by engineering have become key factors in elevating Türkiye's global standing in health tourism, greatly strengthening its competitiveness and attracting a growing number of international patients. Emin Taner Elmas is not a dentist or endodontist, but a Mechanical Engineer and academic. His work focuses not directly on classical dental clinical practice or endodontics, but rather on interdisciplinary fields such as thermodynamics, energy transfer, fluid mechanics, and biomedical engineering. However, Elmas's engineering approach has the potential to contribute to the medical field, including dentistry, indirectly through biomedical and health technologies: Biomedical Approach: Treating the human body as a "bio-machine," Elmas develops theories on the natural vibration frequencies of organs and tissues. This "bio-robotic resonance" theory can inspire the design of next-generation devices for tissue healing or disease diagnosis at a theoretical level. Medical Device Modeling: His expertise in thermodynamics and fluid mechanics is used in the design and simulation of medical devices (e.g., hemodialysis machines or drug delivery algorithms). The mechanical strength of surgical instruments used in dentistry or the thermal effects of dental lasers are engineering problems that fall within Elmas's area of ​​expertise. Interdisciplinary Technologies: He has studies on machine learning and artificial intelligence-supported diagnostic systems. These technologies are increasingly used in the field of endodontics today, such as caries detection and root canal anatomy analysis. In summary, Emin Taner Elmas is not a dentist, therefore he does not develop clinical endodontic procedures. However, his work applying engineering principles to the biomedical field has the potential to contribute to the scientific infrastructure of future dental technologies (device design, diagnostic algorithms, etc.). The "Bio-robotic Resonance and Thermodynamic Interaction" theory and medical technology models developed by Emin Taner Elmas can be indirectly adapted to the fields of dentistry and endodontics. The potential contributions of Elmas's work to dental technologies can be evaluated under the following headings: Bio-robotic Resonance and Diagnosis: Elmas views the body as a "bio-machine," arguing that each tissue has its own unique natural vibration frequency. This approach could form the basis for the development of next-generation diagnostic devices that can detect the condition of tooth canals or microcracks in the tooth root using acoustic signal analysis and Fourier transforms in endodontics. Smart Drug Algorithms: His work focuses on smart drug algorithms and simulations via "Frequency Modulation". This modeling can be used to optimize the thermodynamic interaction of disinfectants or drugs applied into the root canal with the tissue in endodontic treatments. Medical Device Modeling: As a thermodynamics and fluid mechanics specialist, Elmas works on the prototype design and simulation of medical devices (such as hemodialysis machines). This engineering knowledge can directly address specific engineering problems in dentistry, such as controlling the thermal effects of dental lasers or increasing the mechanical efficiency of surgical instruments. Interdisciplinary Approach: His work generally focuses on "Medical Technology," combining mechanical engineering and medical sciences. This perspective contributes to the development of the mechanical and software infrastructure of advanced technologies such as digital intraoral scanners and robotic surgical support systems, which are becoming increasingly common in dentistry today. In summary, Elmas's contribution focuses on the engineering design and theoretical physics of smart devices and diagnostic systems used in dentistry, rather than a clinical application.[1-73]

This paper presents Alumni Connect, a Web app and Website developed using code platforms and AI-assisted tools to bridge the gap between college alumni and current students. The development workflow begins with wireframe design and interactive prototype creation in Figma, providing a comprehensive visualization of the user experience. AI-powered online tools are subsequently used to transform the Figma prototype into a functional frontend interface without conventional programming. Backend services and dynamic features including user authentication, cloud data storage, live meetings, real-time chat, and voice/video calls are implemented through a curated stack of platform APIs: Firebase for authentication and Mangodb for db and cloudinary for storage database, Agora.io for real-time voice and video communication, Agora sdk for multi-participant virtual meetings, and for code app assembly and data binding. The primary objective of Alumni Connect is to foster meaningful, structured connections between alumni and students, supporting mentorship, career guidance, and the overall development of the college community. Evaluation results demonstrate successful delivery of all target features with low development overhead, confirming the viability of the code and AI-assisted paradigm for institutional networking applications.

The global shift to sustainable materials has intensified research on agricultural waste materials like rice husk as they can produce high-purity silica. The process of silica extraction through traditional hot leaching methods requires excessive energy and creates environmental pollution. The research project aims to investigate how leaching processes affect material composition. The researchers assessed silica through multiple methods which included Scanning Electron microscopy-energy dispersive spectroscopy (SEM-EDS) X-ray fluorescence (XRF) X-ray Diffraction (XRD) and Thermogravimetric Analysis-Differential Thermal Analysis (TGA-DTA). The treated silica reached 97% purity while maintaining a dense structure and minimal impurities and it demonstrated thermal stability that extended beyond 600 °C. The H₂SO₄-treated silica achieved 96% purity but its thermal stability decreased to 680 °C while HNO₃-treated silica with 95% purity exhibited carbon content of 3.05% and reduced thermal stability because of incomplete organic matter removal. XRD confirmed that all the samples exist as amorphous materials. The SEM-EDS analysis showed that HCL treatment resulted in the most effective impurity reduction because this sample showed the best compact morphology. The (TGA-DTA) analysis demonstrated weight-loss at various stages which occurred during moisture loss and organic matter decomposition while the material maintained stable thermal properties at high temperatures.

Breast cancer causes the largest number of cancer-related deaths among women worldwide. With the aim of improving Positron Emission Tomography (PET) technology for accurate breast cancer diagnosis and staging, we propose a system design based on monolithic crystals with inherent Depth of Interaction (DOI) capabilities and an innovative edgeless detector ring. This approach eliminates the physical gaps between PET detectors, improving the system detection efficiency while potentially enhancing the image quality since edge effects are reduced. We have developed a dedicated breast PET system prototype (DeepBreast) to show the feasibility of this design. The system is composed of 14 curved LYSO monolithic scintillators of 12.5mm thickness glued side-by-side with a high-refractive index compound. The useful transaxial and axial Field of View (FOV) of the system are 160mm and 50mm, respectively. A Neural Network technique was used for the x- and y- photon impact position estimation. The impact DOI and energy values were determined using the Voronoi calibration methodology. An initial experimental evaluation of the DeepBreast system has been performed inspired by the NEMA protocols for whole-body and small-animals PET scanners. A nearly flat spatial resolution as a function of radial position was obtained, which indicates the DOI capability of the system to mitigate parallax errors. An average spatial resolution of 1.9 ± 0.1mm, 1.9 ± 0.1mm and 1.7 ± 0.1mm FWHM was achieved at the center of the axial FOV for the radial, tangential, and axial directions, respectively. A maximum sensitivity value of 2% was measured at the center of the FOV. The noise equivalent count rate peak reached 15 kcps at 13.4 MBq. Moreover, percent contrast values of 27.9%, 28.8%, 56.8%, 72.5%, 87.2% and 84.2% were achieved for 4.5mm, 6mm, 9mm, 12mm, 15mm and 20mm cylinders of a larger dedicated IQ phantom, respectively. The initial experimental results demonstrate the feasibility of the DeepBreast as an innovative PET scanner for breast cancer imaging.

Abstract Ionizing radiation has emerged as a potential limiting factor for superconducting quantum processors, inducing quasiparticle bursts and correlated errors that challenge fault-tolerant operation. Atmospheric muons are particularly problematic due to their high energy and penetration power, making passive shielding ineffective. Therefore, monitoring the real-time muon flux is crucial to guide the development of alternative error-correction or protection strategies. We present the design, simulation, and first operation of a cryogenic muon-tagging system based on Kinetic Inductance Detectors (KIDs), developed as a stand-alone cryogenic particle-tagging module for superconducting quantum processors. The system consists of two KIDs arranged in a vertical stack and operated at ∼20 mK. Monte Carlo simulations based on Geant4 guided the prototype design and provided reference expectations for muon-tagging efficiency and accidental coincidences due to ambient γ-rays. We observed a muon-induced coincidence rate among the top and bottom detectors of (192 ± 9)×10 -3 events/s, in excellent agreement with the Monte Carlo prediction. The prototype achieves a muon-tagging efficiency of about 90% with negligible dead time. These results demonstrate the feasibility of operating a muon-tagging system at millikelvin temperatures and represent a key step toward the integration of cryogenic veto systems with multi-qubit chips to mitigate muon-induced errors.

An increasing number of rehabilitation technologies are being developed to support upper limb rehabilitation after stroke, with smart textile solutions for surface electromyography (sEMG) emerging as a promising approach. Early end-user involvement is crucial for developing user-friendly and clinically valid rehabilitation tools. This study aims to refine and evaluate the prototype design and usability of a smart textile biofeedback system for self-administered upper limb training after stroke. The training system includes a knitted smart textile sleeve with integrated electrodes over the forearm muscles, an sEMG unit, and tablet-based biofeedback software. An iterative co-design process was followed, including initial testing, demonstration sessions with end users (9 clinicians and 10 individuals with stroke), and a final evaluation of the co-design process. Participants' experiences were gathered through semistructured interviews, analyzed using content analysis, and the User Experience Questionnaire. The co-design team included experts in stroke rehabilitation, textile engineering, biomedical engineering, software development, and human factors, as well as a research partner with lived experience after stroke. The perspectives of the end users and the expert team were collectively integrated into prototype refinements of the sleeve and training software to meet the needs of the intended target group. The experiences of end users formed 2 main categories: "This could be an exciting new training tool for stroke rehabilitation" and "The tool works well, but some changes could enhance independent training." End users found the smart textile sleeve and biofeedback system easy to use and saw potential for integrating it into their training routines. Both end-user groups rated the system as attractive, stimulating, and novel. The results of this study establish a necessary ground toward the development of a smart textile sEMG biofeedback system for self-administered upper limb training after stroke. Findings from the co-design process support the continued development and evaluation of the system as a self-administered upper limb training tool for individuals living with stroke.

1. Abstract The ever-increasing generation of municipal solid waste and the growing demand for electrical energy pose major environmental and economic challenges, particularly in developing nations. This research presents the design, fabrication, and experimental evaluation of a small-scale prototype for electricity generation from trash and plastic waste using thermoelectric conversion. The system employs a controlled combustion chamber to convert waste materials into thermal energy, which is transferred to a thermoelectric generator (TEG). The resulting temperature gradient across the TEG produces electrical energy based on the Seebeck effect. A DC boost converter is used to enhance the low‑voltage output, and the generated power is stored in a rechargeable battery for practical utilization. Experimental testing demonstrates stable low-power electricity generation capable of powering LED loads. The results confirm the feasibility of utilizing waste materials as a supplementary energy source while simultaneously reducing landfill dependency and environmental pollution. Key Words: Waste-to-Energy, Thermoelectric Generator, Solid Waste Management, Waste Heat Recovery, Renewable Energy.

This study aims to describe the concept of Immersive Commerce based on Augmented Reality (AR) in increasing consumer confidence in E-Commerce transactions and to design a conceptual prototype design framework for an AR E-Commerce system with a clear technical flow. The research method uses a literature study through a comprehensive review of AR-based E-Commerce implementations and needs analysis from the perspective of consumer problems and business opportunities. The main problem identified is consumer hesitation in purchasing products online due to limited visualization that relies solely on product photos, causing fears about differences in shape, size, and quality of goods. The research results produced a conceptual framework that includes an integrated system architecture with a frontend layer (AR visualization engine), backend layer (product database and 3D asset management), and integration layer, as well as a systematic user flow design from the discovery to the decision phase. Based on simulations using literature data, the designed framework has the potential to increase customer engagement by up to 169%, conversion rates by up to 11 times, and reduce product return rates by up to 50%. The benefits of this research include digital dimensions through E-Commerce technology innovation, social dimensions by increasing consumer trust and reducing product fraud, and environmental dimensions through the potential reduction of product returns. This conceptual prototype provides a foundation for digital innovation, social trust building, and environmental sustainability through reduced product returns.

The rapid shift toward digital pedagogy has exposed a significant gap in Indonesian English as a Foreign Language (EFL) assessment practices, where traditional testing often fails to capture complex digital literacy. This study aimed to identify teacher needs in digital assessment and construct a validated digital literacy assessment framework that integrates critical thinking, collaboration, and technological proficiency. Employing a Research and Development (RD) design, the study progressed through three phases: needs analysis, prototype design, and expert validation. Data were collected from 45 secondary EFL teachers in South Sulawesi using questionnaires and semi-structured interviews, while three assessment experts evaluated the prototype using validation rubrics. Quantitative data were analyzed using descriptive statistics and Aiken’s V formula, while qualitative data underwent thematic analysis. The needs analysis revealed that current assessments heavily rely on isolated paper-based tests, neglecting students' multimodal skills. In response, a multidimensional framework was developed, encompassing technical competence, digital cognition, and socio-emotional awareness. Expert validation yielded an Aiken’s V coefficient range of 0.82 to 0.94 (mean = 0.88), indicating high content validity, with a practicality rating of 85% from teacher trials. This research concludes that the proposed framework provides a structured pedagogical guideline for educators to transition toward more holistic literacy assessments in the EFL classroom.

The designs and working principles of bioinspired inchworm-type piezoelectric actuators have been well studied in recent literature, with promising applications in precision engineering. However, it is challenging to extend the existing methods to cross-scale planar motion scenarios, which significantly limits the applicability of these actuators. In this article, a parallel, two-degree-of-freedom piezoelectric inchworm actuator is proposed, bioinspired by the skeletal structure of a snake’s spine with a novel active swing driving unit. Unlike conventional series-type actuators that utilize on separate modules for different directions of motion, the proposed design enables 2-D cross-scale parallel inchworm motion in the <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">XY</i> plane by actively switching between swing and translational modes using a shared clamp–drive–clamp assembly. A systematic design of the biomimetic piezoelectric actuator is presented, where modeling and analysis of the driving and clamping units are also supported by finite-element simulations. A design prototype was fabricated, and comprehensive experiments were conducted, demonstrating better performance than representative results in the literature. In particular, the actuator achieves high-performance planar cross-scale trajectory tracking and positioning with <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">XY</i> collaboration in full-step and sub-step scenarios. It has also been successfully applied in full-size chip stitching inspection experiments, highlighting significant potential for advanced semiconductor manufacturing, precision metrology, and inspection applications.

DEPHY is a research and development project supported by the IN2P3 institute, aiming to investigate the technologies required for the development of small-pixel detectors for trackers in future particle accelerators. Among its objectives, the project focuses on designing pixel readout circuits with high time resolution, capable of operating in extreme radiation environments. For timing-critical applications, the 28 nm CMOS process is of particular interest, as it enables the development of fast pixel designs while offering proven radiation tolerance. The design of the first pixel array chip prototype is presented, and its test results are shown and discussed.

The P̅ANDA experiment at FAIR employs a trigger-less data acquisition (DAQ) concept, requiring a scalable and high-performance readout architecture. In this contribution, a scalable data readout system for the P̅ANDA Micro-Vertex Detector (MVD) is presented. The readout architecture consists of the Torino Amplifier for silicon Strip detector (ToASt) front-end ASIC, the Module Data Concentrator (MDC) ASIC and the custom back-end electronics card based on the Advanced Mezzanine Card (AMC) standard. Based on an established prototype, the MVD readout chain was further developed through incremental integration, including its extension to multiple detector modules to demonstrate scalability. In addition, the system was operated over an extended period at high data throughput, showing stable and error-free operation. Moreover, the status of the design and production of the MDC ASIC and the back-end electronics card are reported in this work. The design progress and prototype results represent a step toward integration of the full readout chain into the P̅ANDA experiment. Furthermore, the back-end electronics card has been conceived as a flexible platform, enabling potential applications beyond this specific application.

Reduced-scale Hot Box design and validation for rapid thermal conductivity evaluation of insulating materials

This paper describes the development of an Early Stroke Specialist Vocational Rehabilitation intervention to support return to work following stroke and its delivery in the RETAKE trial. Iterative three stage, target population approach to intervention development and evaluation informed by the Medical Research Council Framework. Stage 1 (Initial codevelopment): interviews with key stakeholder service providers and users' and mapping of services supporting return to work after stroke to identify and explore barriers to and unmet needs for support; intervention codevelopment with experts and patient and public involvement (PPI). Stage 2 (Refinement): expert panel codevelopment workshops and systematic review to identify vocational rehabilitation intervention mechanisms of change in supporting return to work after stroke. Stage 3 (Testing): intervention piloting in two case studies, feasibility testing in a randomised controlled trial, acceptability interviews with stroke and employer participants. Further intervention refinement following delivery in the RETAKE randomised controlled trial. Stage 1: service mapping and 25 stakeholder interviews identified service gaps and unmet needs relating to early identification of employed stroke survivors, mild stroke, and hidden disabilities. Access to timely support relied on geographical proximity to a specialist hub and tacit knowledge of complex health, education and employment services and provider roles. Return to work issues reported by stroke survivors informed Early Stroke Specialist Vocational Rehabilitation prototype design objectives. Iterative developments following piloting included fatigue management, involvement of general practitioners, work simulation and liaison with other healthcare services. Interviews with 12 recipient stroke survivors and 6 employers identified additional features including occupational therapist negotiation skills, ability to respond to changing needs over time and patient empowerment to self-re-refer. The review corroborated intervention components and mechanisms and identified additional mechanisms, for example, peer support, supported self-management. Intervention mechanisms identified across the three stages were early intervention, understanding the impact of stroke on the person, their job and work environment, vocational goal setting, implementing workplace accommodations, individual tailoring, work preparation, colocation, case co-ordination, Multidisciplinary Team (MDT) working, employer engagement and education, and responsiveness, which involved monitoring work stability, providing feedback, and responding to changing needs over time and participant self-re-referral. In RETAKE, Early Stroke Specialist Vocational Rehabilitation was successfully delivered to 95.4% of allocated participants with 75.3% compliance. Intervention commenced a median 38 days (interquartile range 23-56, range 6-216) post stroke and continued for ≤ 12 months. Participants had a median seven intervention sessions (interquartile range 4-12, range 0-37), with discharge a median 10.3 months (interquartile range 5.5-12.0, range 0-15.4) post randomisation. Most intervention sessions were delivered via telerehabilitation (51.7%), in participants' homes (35.9%) or workplaces (6.4%). There was little difference between the number of sessions offered [mean 9.6 (standard deviation 7.46, range 0-39)] and attended [mean 9.0 (standard deviation 7.16), range 0-37]. However, occupational therapist contact with employers only occurred for 109 (36.8%) participants and employer visits occurred for 74 (25.0%). The Early Stroke Specialist Vocational Rehabilitation focus changed between the feasibility and definitive trial, with greater emphasis on current issues, fatigue management and informal psychological support, possibly due to the coronavirus disease discovered in 2019 pandemic. A programme theory and logic model illustrating the refined intervention and a description of Early Stroke Specialist Vocational Rehabilitation delivered in the RETAKE trial is reported. This comprehensive description of Early Stroke Specialist Vocational Rehabilitation will enable occupational therapists to implement Early Stroke Specialist Vocational Rehabilitation in practice and facilitative future evaluation. This article presents independent research funded by the National Institute for Health and Care Research (NIHR) Health Technology Assessment programme as award number 15/130/11.

Objective.Previous MR guided radiation therapy (MRgRT) radiofrequency coil arrays have been limited to one to two rows of coils in the head-foot direction because of the desire to place radiation-opaque coil circuitry outside the window through which the radiation beam travels. However, such layouts limit parallel imaging undersampling in the head-foot direction. We recently demonstrated a three-row array with a remote coil circuit that improved parallel imaging performance, while preserving the signal-to-noise ratio (SNR) and the radiolucent window. Here we evaluate a four-row prototype design to determine if further parallel imaging advantages could be realized.Approach.We built remote circuits that allowed radio-opaque components to be placed outside the field of view through which the radiation beam is expected to travel. The circuit consisted of a phase shifter to cancel the phase introduced by the radiolucent coaxial link between the circuit and coil, followed by standard components for tuning, matching, detuning, and preamplifier decoupling. Measurements were performed on an abdominal phantom to compare single-channel coils with remote or local circuits, followed by tests on a 16-channel four-row array.Main results.The four-row array maintained SNR comparable to two- and three-row designs while supporting 3× head-foot acceleration (minimum reciprocalg-factor = 0.74) and 2 × 3 multi-directional acceleration (minimum reciprocalg-factor = 0.72), capabilities which were not achievable with previous designs.Significance.These results demonstrate the technical feasibility of four-row designs, which may benefit MRgRT applications that require high SNR and temporal-resolution.

The number of rescue interventions by the fire brigade in Poland is growing. The answer to the need to check places contaminated with substances hazardous to human health and life is the design of a wheeled inspection robot supporting firefighting operations. The device is equipped with a mobile platform, a control system, appropriate sensors, a vision system and a transmitter that extends the scope of its revision capabilities. The project additionally covers the issues of adapting the device to real conditions, and also addresses selected issues of mechatronic design and rapid prototyping. The primary goals of the robot are to support the Fire Brigade in activities in the contaminated area, search for injured people, carry out inspections without exposing rescuers to direct exposure to harmful factors. The aspect of possible savings of financial resources in the fire brigade unit, where the discussed solution would be implemented, was also discussed. As part of the work, a prototype of the PoC (Proof of Concept) type was built and programmeds.

Secondary pharmaceutical packaging is essential for medication safety and patient adherence, yet its performance in resource-constrained, import-dependent markets such as Libya remains underexplored. This study systematically evaluated the quality, regulatory compliance, and usability of carton packaging under real-world conditions. A cross-sectional survey of 201 end-users was designed to examine public perspectives on the usability, readability, and safety of pharmaceutical cartons that are used as secondary packaging in everyday use to identify practical challenges. This study revealed substantial variability in material quality, with notable deficiencies in moisture resistance and structural integrity. Survey findings highlighted widespread readability issues due to small fonts and poor layout, alongside strong demand for multilingual labeling and tamper-evident features. These insights informed the development of seven prototype designs that integrate enhanced mechanical robustness, high-contrast graphics, and intuitive access features. The study demonstrates that an evidence-based, user-centered approach can effectively bridge technical performance with patient needs, offering a practical framework for safer, more inclusive pharmaceutical packaging in challenging market contexts

Abstract - This dissertation investigates how vernacular construction materials in the Eastern Himalayas—particularly locally known Icra/Ikra bamboo-based structures in Darjeeling—can be adapted into prefabricated systems without losing cultural authenticity. The study responds to the growing urgency of disaster displacement in India and globally, where prolonged post-disaster shelter conditions expose communities to social, climatic, and psychological vulnerability. Through field-informed analysis, material studies, stakeholder observations, and design prototyping, this research proposes a hybrid prefabricated framework rooted in vernacular logic rather than imposed industrial standardization. The study demonstrates that cultural continuity, climatic intelligence, and scalability are not mutually exclusive when prefabrication evolves from local knowledge systems. Key Words: Vernacular Architecture, Prefabrication, Disaster-Resilient Housing, Cultural Authenticity, Timber Framing

Purpose Ongoing shortages of mental health professionals in the USA underscore the need for scalable, technology-mediated supports. Such supports should not only extend access but also preserve core therapeutic ingredients, including human-like conversational scaffolding via AI and immersive, therapy-like contexts via VR. This paper reports on the design and formative pilot evaluation of a low-fidelity prototype for a conceptual AI-based, VR-supported mental health application. Design/methodology/approach Because the goal was to probe usability and perceptions at an early stage, we used low-fidelity materials to simulate the VR therapy flow and conceptual AI-assisted interactions rather than implementing full AI or VR functionality. Ten young adults with mild to moderately severe depression interacted with the low-fidelity prototype, completed the Usefulness, Satisfaction, and Ease of use questionnaire, and joined semi-structured interviews. Findings Quantitative ratings indicated that the prototype was learnable and generally acceptable for this population. Thematic analysis of the interviews yielded two broad areas of concern – (1) current mental health care barriers and (2) expectations for AI- and VR-supported therapeutic experiences – which pointed to design needs such as anonymity, culturally sensitive options, lightweight onboarding, and more human-like timing and nonverbal cues. Taken together, these findings suggest that the proposed AI-supported VR concept is understandable and worth further digital prototyping, but future work must move beyond low-fidelity simulations to evaluate real interactions and emotional engagement. Originality/value This study demonstrates the feasibility of AI and VR-supported mental health interventions and provides early insights to guide the design of engaging, and accessible digital therapy.