This study aimed to evaluate the effectiveness of various corticotomy techniques based on digital dentistry in improving orthodontic treatment in adult patients. A total of 60 adult patients requiring…
This study aimed to evaluate the effectiveness of various corticotomy techniques based on digital dentistry in improving orthodontic treatment in adult patients. A total of 60 adult patients requiring orthodontic treatment were included and divided into two groups: a conventional orthodontic treatment group and a digitally guided corticotomy-assisted orthodontic treatment group. Digital imaging, three-dimensional treatment planning, and individualized surgical protocols were used to optimize clinical outcomes. The findings demonstrated that digitally guided corticotomy significantly accelerated orthodontic tooth movement and reduced the overall treatment duration compared with conventional treatment. Patients treated with corticotomy also exhibited favorable periodontal conditions, minimal postoperative complications, and a high level of treatment satisfaction. Digital dentistry improved the accuracy of diagnosis, surgical planning, and treatment monitoring, resulting in more predictable clinical outcomes. The integration of digital dentistry with modern corticotomy techniques represents an effective and reliable approach for enhancing orthodontic treatment efficiency, reducing treatment time, and improving patient-centered clinical outcomes in adult orthodontic patients.
Analisis Pengaruh Diabetes Mellitus Self Management terhadap Resiko Penyakit Komplikasi di Desa Saentis Kabupaten Deli Serdang (Studi Kasus pada Klinik Harapan Jaya)
CoReDD Bench: An Open Benchmark for Defect Detection in Code Review with Quantified Label Error
July, 2026 • Dataset
Kolanowski, Jawan
CoReDD Bench measures whether the defective lines in a proposed change can be identified before it is merged. A detector receives the change as it stood before integration and marks the lines it consi…
CoReDD Bench measures whether the defective lines in a proposed change can be identified before it is merged. A detector receives the change as it stood before integration and marks the lines it considers defective; those marks are scored against the lines that caused a later correction.
Labels are reconstructed rather than annotated. For every correction observed after integration, language model agents search the commit history for the change that introduced the defect and mark the lines within it that caused the correction. Reconstruction is stochastic and imperfect, so a manual audit estimates its error rate and that estimate is propagated into every reported score as an interval.
The release covers 360 reviewed pull requests from six Python repositories with observable review and integration workflows. It contains the labels, the audit records, the uncertainty model, and the evaluation software. The repositoryhistories and timestamped GitHub review context the labels were reconstructed from are archived separately as CoReDD Corpus.
Results hold within the documented scope. The benchmark makes no claim to represent code review practice at large.
MOTIBASYON SA PAGKATUTO NG MGA ATLETANG MAG-AARAL SA ASIGNATURANG FILIPINO AT MGA SALIK SA PAGTUTURO NG MGA GURO
July, 2026 • Journal article • Ignatian International Journal for Multidisciplinary Research
Rosales, Robelyn May T., Sinfuego, Roel A.
Hamon para sa mababang motibasyon ng mga atletang mag-aaral sa asignaturang Filipino dahil sa mabigat nilang tungkulin sa akademiko at palakasan. Sinuri ang mga manipestasyon ng motibasyon sa pagkatut…
Hamon para sa mababang motibasyon ng mga atletang mag-aaral sa asignaturang Filipino dahil sa mabigat nilang tungkulin sa akademiko at palakasan. Sinuri ang mga manipestasyon ng motibasyon sa pagkatuto ng mga atletang mag-aaral sa Filipino at ang mga salik na nag-uudyok sa mga guro sa kanilang pagtuturo. Ipinahayag ang kanilang motibasyon gamit ang Self-Determination Theory nina Deci at Ryan, partikular sa dimensyon ng awtonomiya, kakayahan, at ugnayan. Gumamit ng deskriptibo-kwalitatibong disenyo. Walong gurong nagtuturo ng Filipino sa mga atletang mag-aaral sa isang pampublikong paaralan sa Davao City ang lumahok. Ipinakita ng mga atletang mag-aaral ang motibasyon sa pamamagitan ng aktibong pakikilahok, pagiging responsable, pagpupursige, at interes sa Filipino. Ang mga guro naman ay naudyukan ng dedikasyon sa propesyon, hangaring mapaunlad ang mga mag-aaral, at pagpapanatili ng positibong ugnayan sa klase. Mahalaga rin ang awtonomiya, kakayahan, at ugnayan sa pagpapaigting ng motibasyon. Mahalaga ang suportibong kapaligiran at mga estratehiyang nakasentro sa pangangailangan ng mga mag-aaral upang mapanatili ang kanilang motibasyon. Inirerekomenda ang mas matibay na ugnayan ng paaralan, pamilya, at mga guro upang masuportahan ang kanilang akademikong pag-unlad.
GreenNet: Unified and Explainable AI Framework for Environmental and Remote Sensing Data
July, 2026 • Conference proceeding • Indiana Journal of Multidisciplinary Research
Saila, S, Rachel, Julanta Leela J, Nagaraj, Jayashree, Rajeswari, M
Abstract: Deep learning has great potential for environmental monitoring, yet real-world applications often face challenges from large-scale, multimodal, and noisy datasets. We introduce GreenNet, a f…
Abstract: Deep learning has great potential for environmental monitoring, yet real-world applications often face challenges from large-scale, multimodal, and noisy datasets. We introduce GreenNet, a flexible and open-source framework that makes it easier to build and scale deep learning models for remote sensing and environmental data. GreenNet offers reusable neural network modules, simple data integration tools, and built-in explainability features tailored for geospatial applications. To demonstrate its effectiveness, we apply it to case studies such as deforestation detection, urban heat island mapping, and air quality forecasting. These examples show that GreenNet delivers strong predictive performance while significantly reducing the effort needed to develop models. By connecting domain-specific data processing with modern deep learning techniques, GreenNet aims to make AI more accessible, reproducible, and interpretable for researchers and practitioners in environmental science.
Deep learning, Explainable AI (XAI), Spatio-temporal modeling, Sustainable AI, GreenNet
Innovation Design, Mathematical Modeling, and Thermodynamic Analysis of a 700 W Thermophotovoltaic Generator System Based on Nanostructured Components
July, 2026 • Proposal
Keshavarz Azhdari, Milad
Thermophotovoltaic (TPV) systems present a promising solid-state technology for direct conversion of infrared thermal radiation into electricity. However, conventional TPV devices rely heavily on expe…
Thermophotovoltaic (TPV) systems present a promising solid-state technology for direct conversion of infrared thermal radiation into electricity. However, conventional TPV devices rely heavily on expensive, rare III-V semiconductors or germanium (Ge) substrates, which restrict scalable commercial deployment. This paper presents a research and development proposal for a low-cost, high-efficiency, Germanium-Free Perovskite Thermophotovoltaic (TPV) solar cell architecture. The proposed design features a narrow-bandgap halide perovskite absorber integrated into a hole-transport-layer-free (HTL-free) cell configuration with a carbon top electrode. By integrating bandgap engineering, interfacial defect passivation, and optimized radiative spectral management, the system maximizes near-infrared (NIR) photon harvesting while minimizing non-radiative recombination losses. Optical and device physics simulations demonstrate high power conversion efficiencies under moderate thermal emitter temperatures (~1000–1400 K) with substantially reduced fabrication costs. This HTL-free perovskite TPV paradigm offers a durable, scalable, and economical blueprint for next-generation industrial waste-heat recovery, concentrated solar thermal energy harvesting, and thermal energy storage systems.
O'ZBEKISTON RESPUBLIKASIDA PEDAGOG XODIMLARGA KASBIY FAOLIYATI DAVOMIDA YETKAZILGAN ZARARNI QOPLASH: XUSUSIYATLARI, MUAMMOLARI VA YECHIMLARI
July, 2026 • Journal article
Anvarov Demirali Taxir o'g'li
Maqolada pedagog xodimlarning kasbiy faoliyati davomida ularning sog’lig’iga yetkazilgan zararni qoplashning huquqiy mexanizmlari - mehnat va fuqarolik huquqi tutashgan nuqtada - tahlil qi…
Maqolada pedagog xodimlarning kasbiy faoliyati davomida ularning sog’lig’iga yetkazilgan zararni qoplashning huquqiy mexanizmlari - mehnat va fuqarolik huquqi tutashgan nuqtada - tahlil qilinadi. Muallif pedagoglik kasbiga xos, ammo milliy huquqiy adabiyotda deyarli e’tibordan chetda qolgan muammoni - ovoz apparatining kasbiy shikastlanishi (kasbiy disfoniya, surunkali laringit) misolida - butun maqola davomida izchil ochib beradi va bunday holatlarning “birdaniga yuz beruvchi shikastlanish” emas, balki asta-sekin to’planib boruvchi xarakterga ega ekanligi sababli amaldagi kompensatsiya tizimiga qanchalik yaxshi sig’ishini tanqidiy baholaydi. “Pedagogning maqomi to’g’risida”gi Qonun, Mehnat va Fuqarolik kodekslari, Vazirlar Mahkamasining ishchilarga yetkazilgan zararni qoplash qoidalari hamda tibbiy-mehnat ekspertizasiga oid normativ hujjatlar milliy va xorijiy huquqshunoslarning, jumladan Xalqaro Mehnat Tashkiloti materiallarining, ilmiy-nazariy qarashlari bilan qiyoslanadi.
Muallif tomonidan pedagoglarning kasbiy kasalliklarini erta aniqlash va qoplashning maxsus, differensiallashtirilgan tartibini joriy etish modeli taklif etiladi.
There is an increasing interest in upgrading the EModel, a parametric tool for speech quality estimation, to the wideband and super-wideband contexts. The
Contemporary models of Unmanned Aerial Vehicles (UAVs) are largely developed using simulators. In a typical scheme, a flight simulator is dovetailed with a
Undertaking engineering research can be compounding for beginning graduate students and thwarting even for seasoned researchers. With a wealth of academic
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