Artificial intelligence (AI) has emerged as a transformative technology in modern orthodontics, redefining conventional diagnostic and therapeutic workflows through digital integration and predictive analytics. The incorporation of machine learning, deep learning, convolutional neural networks, and computer vision into orthodontic practice has significantly improved the accuracy of cephalometric landmark identification, malocclusion classification, treatment simulation, aligner therapy planning, and remote patient monitoring. Digital orthodontics, supported by intraoral scanners, cone-beam computed tomography (CBCT), three-dimensional imaging, and cloud-based systems, has created a robust data-driven ecosystem that facilitates AI-assisted clinical decision-making. AI-based software systems are increasingly capable of reducing operator variability, minimizing human error, and improving clinical efficiency while enabling personalized orthodontic care. Furthermore, teleorthodontics and AI-enabled remote monitoring systems have expanded patient accessibility and compliance tracking. Despite these advancements, important concerns remain regarding algorithm transparency, ethical considerations, data privacy, medico-legal accountability, and clinician dependency on automated systems. Current evidence suggests that AI should function as an adjunctive clinical tool rather than a replacement for professional judgment. The present review comprehensively discusses the evolution, applications, advantages, limitations, ethical implications, and future prospects of artificial intelligence in digital orthodontics. The article highlights the growing role of AI in precision orthodontics and emphasizes the need for standardized validation and responsible clinical integration.

Background: Conventional approaches to sustainable development have been criticized for their technocratic orientation and limited engagement with the knowledge systems embedded in culture. The orientation toward relational well-being, ecological care, and ethical coexistence with nature is the foundation of indigenous epistemologies developed through long-term relationships with the environment. North India alone has thousands of communities with a rich culture of indigenous knowledge that has traditionally underpinned sustainable resource management, but is now marginalized by modern development and conservation policies. The Bhil, Gaddi, Bhotia, and Van Gujjar are only some of them. Objective of the study: To analyze the interrelationship and connection between indigenous epistemology and the concept of sustainable development. Method: The research will be conducted as a meta-analytical study grounded in anthropological and development research. It is based on secondary literature (e.g., ethnographic case studies and policy literature). It uses a comparative framework to examine indigenous knowledge practices, their interactions with formal development projects, and the institutional and ethical contexts that shape these interactions. Findings: The findings indicate that knowledge can be mixed in different ways, including integration, parallel use, adaptation, and co-management. Although these processes lead to synergies, e.g., improved healthcare, enhanced conservation, and community-based governance of ecosystems, they also expose tensions arising from power asymmetries, limited policies, and the loss of intergenerational knowledge. This paper concludes that context-specific, rights-based, and participatory approaches play a pivotal role in achieving culturally grounded, environmentally friendly, sustainable development.

The fast usage of Internet of Things (IoT) device in industrial and consumer settings has dramatically expanded on the attack surface of embedded systems. This paper explores firmware security through reverse engineering and analysis of a firmware image of an IoT style with two open-source tools: Binwalk and Ghidra. An artificial representation of the structure of typical Linux-based IoT firmware was produced by a controlled firmware image which had a SquashFS file system and compiled binaries. Embedded file systems and binaries were extracted using Binwalk and Ghidra was used to do the static analysis and decompilation of extracted executable files. The vulnerability analysis showed that there are a number of deliberately introduced security flaws such as hard-coded credentials, unsecured input handling functions and insecure configuration practices. The success of the method was shown by the successful recovery of the firmware filesystem and detection of these types of vulnerabilities with the help of the strict reverse-engineering tool. The paper shows the possible contribution of open-source tools to the analysis of firmware-level vulnerabilities and enhancing security testing of embedded IoT systems.

Background: Actinomycosis is an uncommon, chronic, granulomatous disease that can be mistaken for a malignant tumor. Abdominopelvic actinomycosis constitutes about 20% of all actinomycosis cases and may mimic malignancy, tuberculosis, or other abdominopelvic inflammatory diseases. This condition is more prevalent in women who use an intrauterine device. We report the case of a 38 year old female, known case of type 2 diabetes mellitus with a down 3 year history of right sided abdominal pain and discomfort, weight loss with a previous history of intrauterine device for 5 years she has undergone evaluation for her complaints at multiple times in a peripheral health care centers with colonoscopy and mucosal biopsies and treated for inflammatory bowel disease. CECT Enterogram showed wall thickening involving the IC junction and medial wall of caecum and she undergone laprotomy and right hemicolectomy. Histopathologic evaluation of surgical specimens showed actinomycosis in the caecal wall. The findings were immediately informed to the clinician and advised for a prompt further evaluation and management.

Background: Metabolic syndrome (MetS) is a cluster of metabolic abnormalities including central obesity, hypertension, dyslipidemia, and impaired glucose metabolism that significantly increase the risk of cardiovascular disease and type 2 diabetes. The prevalence of MetS has risen worldwide due to sedentary lifestyles, urbanization, and dietary changes. Early identification of its clinical characteristics and predictors in hospital-based populations is important for effective prevention, timely diagnosis, and appropriate management of associated health complications. Objectives: To determine the prevalence, clinical characteristics, and predictors of metabolic syndrome among adults attending a hospital-based healthcare facility. Methods: This hospital-based cross-sectional study was conducted at Ibn Sina Diagnostic & Consultation Center, Uttara, from June 2018 to May 2019. A total of 226 adult participants were included. Data were collected using structured questionnaires, clinical measurements, and laboratory records. Variables included age, gender, BMI, blood pressure, and biochemical parameters. Data were analyzed using Statistical Package for the Social Sciences (SPSS) with descriptive statistics and Chi-square tests; p<0.05 was considered significant. Results: Among 226 participants, the mean age was 42.6 ± 11.8 years, with 56.6% males. Metabolic syndrome was present in 86 (38.1%) individuals. The highest prevalence occurred in the 41–50 years group (30.2%). Overweight and obesity were observed in 40.7% and 24.8% respectively. Hypertension affected 51.3% participants. Abdominal obesity (46.0%) and low HDL (41.6%) were common components. Smoking (30.1%) and physical inactivity (68.1%) were notable lifestyle risk factors.

Large scale urban infrastructure projects such as metro systems, tunnels, highways, and bridges require strict quality management during construction. These projects often involve complex subsurface conditions, dense urban surroundings, and multiple construction activities occurring simultaneously. Quality assurance (QA), quality control (QC), and geotechnical monitoring therefore remain central components of construction supervision. Conventional monitoring practices rely on inspection reports, laboratory testing records, and field instrumentation systems that often operate within separate information platforms. This separation restricts coordinated evaluation of construction quality and ground behavior during project execution. This study presents a Digital Twin enabled Geo-BIM framework for integrated QA, QC, and geotechnical compliance monitoring in urban infrastructure construction. The proposed framework links geotechnical investigation data, monitoring sensors, QA inspection documentation, and QC testing results within a unified digital environment. A Geotechnical Compliance Index (GCI) model is introduced to evaluate construction conditions and identify zones requiring inspection attention. The framework was examined through a simulation scenario representing common urban infrastructure construction activities. Results indicate that the integrated system supports continuous monitoring, automated compliance evaluation, and inspection prioritization based on geotechnical performance. The proposed framework provides a structured digital approach for managing construction quality and subsurface monitoring in complex infrastructure projects.

This study examined how well monetary policy tools worked in helping Nigeria to achieving its inflation targets from 1981-2023. To achieve this, the study collected data on inflation rate, monetary policy rate, broad money supply, exchange rate, lending interest rate and real gross domestic product from reports by Nigeria's central bank and the World Bank. An Autoregressive Distributed Lag - ARDL technique was used as the main tool of analysis. The findings from this method showed that there is a long-term relationship between the different factors studied. In the long run, the monetary policy rate, money supply, and lending interest rate had a negative but not strong connection with inflation rate. On the other hand, exchange rate and real gross domestic product showed a positive but not strong relationship with inflation rate. In the short term, the monetary policy rate, money supply, and exchange rates had a positive and strong link with inflation. Meanwhile, lending interest rate and real gross domestic product had a negative and strong link with inflation rate. Based on the findings, this study concluded that in Nigeria, inflation is highly sensitive to monetary expansion, interest rate adjustments, and exchange rate movements, but the effects are inflation-enhancing rather than stabilizing highlighting the need for a more coordinated and structurally grounded monetary policy framework rather than relying on MPR adjustments alone. From a policy standpoint, the study recommended amongst others that broad money supply growth must be carefully controlled to avoid liquidity-driven inflation. The central bank should continue to use lending rate adjustments as an effective short-run inflation control tool, but with caution to avoid credit starvation in the economy. Inflation targeting should be complemented with policies that expand real output (RGDP), since growth itself helps reduce inflationary pressures.