Abstract: This paper examines the empirical evidence on the use of generative artificial intelligence (GenAI) in scientific writing. A search was conducted in Google Scholar and PubMed, followed by an analysis of the included studies, which was performed according to the academic field, AI tool, writing task, study design, and main findings. Following the PRISMA guide, this scoping review included 18 studies published between 1st January 2023 and 1st January 2026, representing the disciplines of medicine, education, dentistry, radiology, humanities, library, information science and cognitive science. The evidence base was dominated by studies on ChatGPT, making it the most empirically researched GenAI tool in this field. According to the studies reviewed, GenAI performed well on an array of measures (readability, fluency, and organization) and efficiency (the latter especially in terms of manuscript drafting, abstract writing, proposal development, and literature reviewing). However, the findings also disclosed several limitations, including incorrect or falsified references, inaccurate bibliographical metadata, shallow analysis, lack of originality, and insufficient methodological depth. Based on comparative evidence, newer model versions show improved coherence and reasoning and although improved with the newer GenAI versions, reference reliability still appears to be a recurring problem. Overall, GenAI can be a useful assistive tool for scientific writing; however, its usefulness is dependent upon human supervision and the task at hand, especially with regard to the accuracy of facts and their sources.

Abstract: This paper presents OSI4IOT, an open-source software platform designed to support the integration of sensor-driven Internet of Things (IoT), Asset Information Modelling (AIM), Geographical Information Systems (GIS), and data-driven analysis within a Digital Twin (DT) framework. The platform provides a modular architecture for connecting heterogeneous data sources and enabling the coupling between physical assets and numerical models. In particular, it supports the integration of Finite Element Method (FEM)-based structural models for simulation and comparison with monitored responses. A case study involving a structural frame is used to demonstrate the platform workflow, including data acquisition, model execution, and result visualisation. The results are used to assess the consistency between analytical, numerical, and monitored responses under varying loading conditions. The paper focuses on the system architecture and the coupling strategy between data acquisition and simulation components within an open-source environment.

Abstract: The landscapes of most tropical regions have been shaped by the indigenous peoples’ and their livelihood practices. The utility of plants within these landscapes for traditional purposes has been facing intense competition from commercial logging. To gain insights into this conflict, this paper examined how landscape conditions may influence the presence and spatial distribution of indigenous subsistence and commercial logging ecosystem services relative to one another. Data on the ecosystem services and landscape conditions in the form of physical environment variables were obtained for twelve indigenous villages in the Rupununi, Southern Guyana. For each village, the relative log risk ratios of subsistence values to logging values were computed and regressed against six physical environment variables – village presence, distance to village, distance to road, distance to waterways, elevation, and slope – to examine if and how landscape conditions may favor the presence of one service over the other. The estimates were then used to map the relative differences in the spatial distributions of subsistence and commercial logging services in each village. It was found that mean relative log risk ratios for the villages were generally positive, indicating an inclination towards the presence of subsistence services. However, the maps revealed that while some areas within a given village were indeed more favorable for the presence of subsistence services, other areas within the same village were inclined towards the presence of logging services. Similar spatial analyses can be explored to guide policy-makers in developing land-use strategies that allocate forest lands between competing users by identifying areas that are best suited for indigenous peoples’ subsistence activities and for commercial logging operations.

Abstract: Biofilms (BFs) bacteria are dramatically intensifying tolerance to conventional antibiotics, no longer effective. Therefore, the research for new antibiofilm (ABF) compounds are noticeably increasing the studies proliferation rate. In this regard, intriguing questions should raise to be debated. To this end, the problematics of BF, mainly in medical setting, have been afforded here in an original way, examining the tension “between efficacy and understanding”. Questions include: are BF mechanistic studies indispensable and strictly required especially at academic levels with poor economic support? When may a purely phenotypic approach still hold scientific value? Could be demonstrate empirical efficacy alone, sufficient for scientific relevance of the study? Do high costs, long times mechanistic insights, also associated to environmental issues, represent the necessary key to defeating BFs and the benchmark that determines the robustness and impact of ABF research? The state of the art of global challenge against BF, responsible for difficult-to-treat and even lethal chronic infection, has been provided. The available armamentarium of best functioning antibiotics/combinations has been discussed, while the correct way to investigate ABF mechanisms has been clarified. Among 102 studies on the ABF activity, considered, distributed in Tables and discussed, mechanistic investigations carried out correctly have been found in only 34 ones. Only efficacy screens, stopping at phenotypic descriptions, as reported in 68 out of 102 papers, are considered essential for discovering efficacious ABF compounds and are welcome by Editors and scientific community. Such approach represents the main trend of most recent literature and is strongly desirable for publication.

Abstract: Background/Objectives: Treatment decisions for elderly patients with diffuse large B-cell lymphoma (DLBCL) often rely on subjective clinical impression rather than systematic frailty assessment. We evaluated whether a modified simplified frailty score (mSFS)—a binary adaptation of the Isaksen score—predicts treatment selection, toxicity, and survival. Methods: In this retrospective study of 117 patients aged ≥65 years with DLBCL treated with rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone (R-CHOP) or dose-attenuated R-CHOP (R-mini-CHOP) at MedStar Health community hospitals (2000–2025), the mSFS assigned one point each for age ≥80, Eastern Cooperative Oncology Group (ECOG) performance status ≥2, and ≥5 comorbidities; score ≥2 defined frailty. Results: Among 86 R-CHOP recipients, 17 (19.8%) were mSFS-frail; among 31 R-mini-CHOP recipients, 15 (48.4%) were mSFS-fit. In R-CHOP recipients, frailty independently predicted worse overall survival (adjusted hazard ratio [aHR] 7.67, 95% confidence interval [CI] 2.36–24.97), progression-free survival (aHR 2.90, 95% CI 1.18–7.13), grade ≥3 adverse events (adjusted odds ratio [aOR] 3.90, p = 0.035), and early discontinuation (aOR 4.41, p = 0.034). Frail R-CHOP patients had lower complete response rates (aOR 0.24, p = 0.038). Fit R-mini-CHOP patients had 88% lower odds of complete response versus fit R-CHOP patients (aOR 0.12, p = 0.003). Among R-mini-CHOP recipients, frailty was not significantly associated with outcomes. Conclusions: The mSFS revealed bidirectional discordance with oncologist-assessed frailty and independently predicted survival, toxicity, and response, supporting its integration into community oncology practice.

Abstract: Background/Objectives: Type 2 diabetes mellitus (T2DM) is a chronic multifactorial metabolic disorder requiring multi-target therapeutic strategies. This study aimed to clarify the potential material basis, key targets and molecular mechanisms by which PuRenDan (PRD) acts against T2DM through an integrated network pharmacology and molecular simulation approach. Methods: Active compounds of PRD were screened from TCMSP, HERB 2.0 and the literature, and compound-related targets were predicted using TCMSP, SwissTargetPrediction and PharmMapper. T2DM-associated targets were collected from OMIM, DrugBank, DisGeNET, HPO, ClinPGx and GeneCards to obtain drug-disease intersection targets. Cytoscape was used to construct herb-compound-target and protein-protein interaction (PPI) networks, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. Molecular docking was performed using AutoDock Vina, and representative ligand-receptor complexes were further assessed by 100 ns molecular dynamics (MD) simulations and molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA) binding free-energy analysis. Results: A total of 163 active compounds, 597 PRD-related targets, 9138 T2DM-associated targets and 483 intersection targets were identified. β-sitosterol, emodin, quercetin, kaempferol and formononetin were predicted as major active compounds, whereas AKT1, TP53, SRC, IL6, TNF, EGFR and ESR1 were identified as core targets. KEGG enrichment highlighted the PI3K-Akt, MAPK, HIF-1, FoxO, mTOR, AGE-RAGE and TNF signalling pathways. Docking suggested strong multi-target binding potential for β-sitosterol. MD and MM/PBSA analyses further indicated favourable dynamic stability for β-sitosterol-TNF, β-sitosterol-AKT1, β-sitosterol-SRC and emodin-EGFR complexes, with β-sitosterol-TNF showing the lowest binding free energy. Conclusions: PRD may exert therapeutic effects against T2DM through coordinated multi-compound, multi-target and multi-pathway regulation involving inflammation, insulin signalling, oxidative stress and metabolic pathways. β-sitosterol may represent an important candidate material basis of PRD, with TNF, AKT1, SRC and EGFR as potential key targets.

Abstract: Electric vehicle (EV) transport by ship is expanding beyond industrial logistics centered on automobile production, trade, and pure car and truck carriers (PCTCs) into daily transportation for island tourism, commuting, and essential mobility. According to Korea Maritime Transportation Safety Authority (KOMSA) vessel status data as of March 2026, 104 of 146 domestic passenger ships were car-ferry passenger ships, accounting for 71.2% of the fleet and operating on 75 of 99 designated routes nationwide. Korea Shipping Association (KSA) operational records show that the EV transport rate on these routes increased from 0.76% in 2024 to 1.21% in 2025, with some routes exceeding 2.0–4.7%. Unlike enclosed multi-deck PCTC vehicle spaces, Korean coastal car-ferry passenger ships generally have single-tier open vehicle decks and bow ramp gates. Crosswinds on open decks may reduce smoke detector activation probability by 60–75%. Although Article 97 of the Standard for Ship Fire-Fighting Appliance newly requires dedicated EV fire-fighting equipment for car-ferry ships, it remains primarily equipment-prescriptive and does not yet provide open-deck-specific performance requirements for wind-resistant detection, fixed EV-zone cooling, EV-designated stowage arrangements, or passenger-operator safety management obligations. This study applies the five-step International Maritime Organization (IMO) Formal Safety Assessment (FSA) procedure to support improvements to EV fire-fighting equipment standards for coastal car-ferry passenger ships. Hazard Identification (HAZID) was conducted with a 15-member advisory panel, and probability elicitation was performed through a Delphi survey with 10 core experts, showing strong consensus (Kendall’s W = 0.74, p < 0.01). Fault Tree Analysis (FTA) and Event Tree Analysis (ETA) probabilities were derived from the Delphi results and international literature. H-07, representing wind-induced smoke dilution, was identified as the only first-order minimal cut set. Monte Carlo-based FTA–ETA analysis (n = 10,000) estimated annual fire frequencies of 5.9 × 10⁻², 1.8 × 10⁻¹, and 2.9 × 10⁻¹ yr⁻¹ at EV loading ratios of 10%, 30%, and 50%, respectively, with 2.47 expected fatalities per fire. Risk entered the IMO ALARP band above a 30% EV loading ratio and exceeded the maximum tolerable crew risk above 50%. The combined application of Risk Control Option (RCO) 2, 3, and 4 reduced annual expected fatalities by 85.6%. Based on these results, six RCOs and institutional recommendations are proposed, including strengthened safety management obligations for passenger ship operators.

Abstract: Atrial fibrillation (AF) is a prevalent cardiac arrhythmia associated with significant morbidity and mortality. Structural remodeling of the left atrium, particularly myocardial fibrosis, plays a key role in AF pathogenesis. Matrix metallo-proteinases (MMPs) are critical regulators of extracellular matrix remodeling and may contribute to atrial fibrosis through genetic variation. This case–control study included 179 patients with AF and 56 controls. Eight polymorphisms across five MMP genes (MMP1, MMP2, MMP3, MMP9, and MMP12) were analyzed using PCR-based methods. Associations between single nucleotide polymorphisms (SNPs), AF susceptibility, recurrence, haplotypes, and gene–gene interactions were assessed. The study population was ethnically ho-mogeneous (Polish), minimizing population stratification bias. No significant differences in allele frequencies were observed between AF and control groups in univariate analysis. However, multivariable logistic regression revealed significant associations for MMP1 rs1799750 and MMP2 rs243864 under recessive inheritance models. Haplotype analysis demonstrated a significant global association with AF (p = 0.027), with specific haplotypes showing markedly increased risk. Multifactor dimensionality reduction identified significant gene–gene interactions, particularly involving SNPs in MMP1, MMP2, MMP3, and MMP12. These findings support a polygenic model of AF susceptibility involving extra-cellular matrix remodeling pathways and highlight the importance of multi-locus genetic analyses.

Abstract: Naturally formed treefall gaps represent primary sources of environmental heterogeneity in tropical forests, yet their role in driving the components of beta diversity in specialized leaf-litter fauna remains poorly understood. We investigated the influence of natural treefall gaps on harvestmen (Arachnida: Opiliones) community structure and beta diversity partitioning in a well-preserved Atlantic Forest remnant in southern Bahia, Brazil. Using standardized nocturnal searches and leaf-litter sampling, we recorded 845 individuals across 23 species. Coverage-based rarefaction indicated higher estimated richness in gaps, although observed alpha diversity did not differ significantly among habitats. Community composition differed significantly along the gap–forest gradient, driven mainly by litter depth and microclimatic variation. Indicator species analysis identified Protimesius sp. as a robust gap-specialist. Beta diversity partitioning revealed that turnover accounted for 79.5% of total dissimilarity, while nestedness contributed 20.5%. Treefall gaps exhibited the highest internal beta diversity and species exclusivity, supporting their role as dynamic environmental filters that enhance regional diversity. Our findings highlight the ecological importance of natural disturbance and litter structure in maintaining biodiversity patterns in tropical forests.

Abstract: The sterility of injection pharmaceutical preparation is the most crucial requirement to achieve, as it is injected directly to human body, either intravenously, intramuscularly, or other injection routes and once drug is injected, it moves to other parts of the body through blood flow follows the rules of drug distribution and will have direct contact to all tissues and organ [1]. Theoretically, in order to prevent contamination of microbial by inhibiting the proliferation process, especially in multiple dose of injection drugs, in the final formulation of the drug may need special addition of suitable preservative agent in the preparation [2]. The first step to perform this experimental study was by preparing the sterile pharmaceutical preparation, Diphenhydramine Hydrochloride injection at Sterile Pharmaceutical Preparation Laboratory, of Universitas Muhammadiyah Malang, Indonesia. Once the injection drug was ready, the second step conducted sterility test. The most common method used for sterility test in injection drugs is named direct inoculation. It was conducted by preparing sample from diluted solution of the injection drug, and the concentration was divided into five groups of sample 1:1, 1:2, 1:3, 1:4, 1:5, and undiluted sample (with three times replications) has determined certain level of inactivation of benzyl alcohol as its preservative agent, that was undiluted sample in Thioglycolate medium and 1:1 in Casamino medium. The indicator of bacterial growth in the study was Bacillus subtilis for Thioglycolate medium on range of temperature 30°-35 °C, and Candida albicans as an indicator of fungal growth in Casamino medium on range of temperature 20°-25 °C, both of Thioglycolate and Casamino medium were observed for 14 days. Inactivation of preservative agent and sterility test were performed under LAFC condition and it required some controls of LAFC environment to ensure that experiment was conducted under optimum condition and to avoid false positive result. According to those results of our study, the sterility test has indicated that our Diphenhydramine Hydrochloride injection was sterile after over a period of 14 days of observation.

Abstract: Inventory systems are typically evaluated using aggregate performance metrics such as out-of-stock and average inventory. In supply chain management, it is important to understand the underlying reasons for a period's performance— specifically, how previous inventory management decisions, such as order placement, lead to the result and what their contributions are. Traditional methods are often restrictive and cannot be applied to broader cases. This paper proposes a Shapley-based decomposition framework that attributes the realized performance gap between the observed inventory policy and optimized reference policy to individual decisions. A numerical experiment on a simulated finite-horizon periodic-review inventory system with stochastic demand and lead time is conducted to illustrate the basic idea of the method. Compared to traditional methods, the proposed approach directly explains a realized benchmark-relative performance difference and is applicable to integer-constrained, non-differentiable, and simulation-based inventory systems. It enables transparent inventory management performance evaluation and effective root-cause analysis.

Abstract: Asymmetry Theory (AT) is derived from a single empirically validated principle: light propagates at constant speed c from its emission origin, addressing the foundational question: is STR's principle of relativity empirically necessary? AT transformation covers Lorentz and Galilean transformations as limiting cases while retaining absolute time. AT unifies classical and relativistic physics: In “Transverse Regime” — observer motion is perpendicular to the ‘source-observer’ line — AT is equivalent to Lorentz transformation, preserving Lorentz invariance and reproducing all validated predictions of STR, while naturally handling non-inertial frames. In “Longitudinal Regime”, AT reduces to Galilean transformation. A central insight is that “Transverse Regime” is the natural equilibrium state of conservative systems in motion. This explains why established high-precision Lorentz invariance tests operate predominantly in the transverse regime and are therefore consistent with both AT and STR. The longitudinal regime is the untested empirical frontier where AT makes testable novel predictions distinguishing it from STR: (1) Sagnac phase shift in inertial frame; (2) momentum asymmetry for parallel acceleration versus deceleration. AT derives: (1) a light observed velocity formula explaining Sagnac effect, GPS one-way light speed, stellar aberration, and optical clock variation; (2) a unified formula encompassing both classical and relativistic Doppler effects, cosmological redshift, and Cherenkov radiation; (3) electrodynamics equations addressing particle acceleration, mass-energy equivalence, and matter waves; (4) a unified Maxwell's equations yielding classical and transverse Doppler and Sagnac effects as solutions.AT maintains consistency with all established empirical evidence: Michelson-Morley, optical cavity resonators, Hafele-Keating, optical clock, Ives-Stilwell spectroscopy, particle accelerators, muon decay, nuclear reactions and GPS Sagnac corrections. AT is also consistent with the anomalous Gezari lunar ranging and Thim microwave results, which remain unexplained within STR. A first-order sensitive motion-controlled interferometer is proposed for the decisive test of AT. In summary, AT is a mathematically rigorous, self-consistent and empirically supported framework that unifies classical and relativistic physics under a single derivable principle, with a decisive test proposed.

Abstract: 3,4-Methylenedioxyamphetamine (MDMA) has been shown in multiple clinical trials to greatly reduce Post-Traumatic Stress Disorder (PTSD) symptoms, with many patients experiencing lasting improvement. However, recent regulatory rejection based on problems with blinding highlights a contradiction, with regulatory agencies demanding placebo-controlled trials, yet the strong psychoactive effects of MDMA-assisted therapy make true blinding impossible.This paper examines neurofunctional mechanisms and methodological challenges relevant to MDMA-assisted therapy research. First, it introduces the Trauma-Affective Memory Loop (TAML), a simple model of how traumatic memories are stored, reactivated, and reinforced through key brain regions. Second, it explains how MDMA works on a neurofunctional level, by reducing fear signals it creates a temporary “therapeutic window”. In this state, patients can revisit trauma safely, without being overwhelmed, and reprocess the memory in a healthier way.Third, the paper proposes that different types of trauma exposures respond differently to MDMA-assisted therapy. Acute, one-time traumas may often be resolved within one to three MDMA sessions, while complex or developmental trauma, formed over years, may need repeated and carefully structured treatment.Finally, a proposed clinical-trial framework, the Brinzei MDMA-PTSD Protocol (BMPP), is presented. The framework uses a role-separated, quadruple-masked structure intended to reduce expectancy-related bias while preserving therapeutic fidelity. The aim is to move beyond debates about flawed blinding methods and instead design trials that clarify why MDMA works, for whom it works best, and how to deliver it safely and effectively.

Abstract: Background: Hepatocellular carcinoma (HCC) is a leading cause of cancer-related mortality worldwide and remains therapeutically challenging owing to its marked inter- and intratumoral heterogeneity, diverse etiologies, and high rates of drug resistance. This review aims to summarize the current knowledge on the complexity of HCC and to evaluate emerging therapeutic strategies, with a particular focus on targeting the RNA-binding protein HuR as a novel approach to overcome treatment limitations. Methods: A narrative review was conducted of peer-reviewed publications focusing on HCC pathogenesis, tumor heterogeneity, resistance mechanisms, and therapeutic developments. Emphasis was placed on studies investigating the molecular drivers of HCC, tumor microenvironment interactions, and novel treatment strategies. Results: HCC progression is driven by complex interactions between genetic, epigenetic, and environmental factors, resulting in significant variability in treatment response. Tumor heterogeneity, cancer stem cell populations, and an immunosuppressive tumor microenvironment contribute to resistance to conventional therapies, including multikinase inhibitors and immune checkpoint inhibitors. Emerging strategies targeting these mechanisms, such as combination immunotherapies, metabolic targeting, and epigenetic modulation, show promise, but remain limited by incomplete efficacy. HuR is a central post-transcriptional regulator that stabilizes mRNAs encoding oncogenic and pro-survival factors. Preclinical studies have demonstrated that the pharmacological inhibition of HuR disrupts tumor-promoting pathways and enhances therapeutic sensitivity. Conclusions: The complexity of HCC necessitates multifaceted precision-based therapeutic approaches. Targeting HuR is a promising strategy for addressing tumor heterogeneity and drug resistance. Continued integration of molecular profiling, advanced technologies, and rational combination therapies is critical for translating these advances into improved clinical outcomes.

Abstract: This study assessed the current status of irrigation systems and water management practices in Rwanda’s irrigated agricultural zones focusing on Nasho Government Funded Irrigation (GFI) scheme in Kirehe District and Kagitumba Irrigation Scheme in Nyagatare District. A mixed descriptive approach was applied combining field observation with structured questionnaires administered through Kobo Toolbox to 224 respondents in Nasho and 188 respondents in Kagitumba. Field observations were used to evaluate the physical condition and functionality of irrigation infrastructure while questionnaires captured stakeholder perceptions, water management practices, institutional arrangements and operational challenges. Results show that both irrigation schemes are operational but function below optimal efficiency due to multiple constraints. In Nasho, irrigation performance is mainly affected by sedimentation in canals and reservoirs, pump inefficiencies and inadequate maintenance practices leading to unreliable water delivery. In Kagitumba, despite the use of modern center pivot systems performance is constrained by pipeline corrosion, pressure losses, sediment-laden water and uneven water distribution. Across both schemes, more than 80% of respondents reported frequent system failures while over 95% indicated the absence of formal irrigation scheduling practices. Water management remains largely reactive with limited preventive maintenance and weak technical capacity among users and institutions. The study concludes that improving irrigation efficiency in Rwanda requires integrated interventions combining infrastructure rehabilitation, strengthened maintenance systems, improved water governance and farmer capacity development to enhance sustainable water use and agricultural productivity.

Abstract: Enzyme replacement therapy (ERT) for central nervous system symptoms and newborn screening (NBS) are available in Japan for patients with mucopolysaccharidosis type II (MPS II). The participants were individuals referred to our facility through NBS who were suspected of having neuronopathic MPS II. We reviewed the clinical course of patients who received intracerebroventricular (ICV)-ERT, idursulfase beta (Hunterase®), followed by hematopoietic stem cell transplantation (HSCT) using umbilical cord blood. Longitudinal measurements of heparan sulfate (HS) in the cerebrospinal fluid (CSF) were performed as a therapeutic biomarker, and developmental age was evaluated. Three patients diagnosed and treated with ICV-ERT received cord blood transplantation (CBT). All patients achieved successful engraftment with no severe complications except for one patient with sinusoidal obstruction syndrome. The HS in the CSF showed a temporary increase during the ERT discontinuation period owing to CBT and a subsequent reduction after the resumption of ICV-ERT. The patients exhibited age-appropriate development. The pattern of change in HS suggests the importance of continuing ICV-ERT even after HSCT. The combination of ICV-ERT and CBT may yield promising outcomes in patients with neuronopathic MPS II and underscores the importance of early intervention through NBS.

Abstract: This paper presents a novel optimal control-based beamforming framework for phased antenna arrays, targeting advanced wireless communication and radar applications, including 5G systems. Unlike conventional beamforming techniques such as Fourier-based methods and adaptive algorithms (e.g., LMS and RLS), the proposed approach formulates the beam synthesis problem as a discrete-time optimal control problem. The antenna array is modeled using a state-space representation, and a quadratic cost function is introduced to jointly minimize the deviation from a desired radiation pattern and the excitation power. The optimal excitation weights are derived using the Linear Quadratic Regulator (LQR) framework by solving the discrete-time algebraic Riccati equation. This formulation enables an effective trade-off between sidelobe suppression, main lobe accuracy, and power efficiency. Simulation results demonstrate that the proposed method achieves a well-focused main beam, significantly reduced sidelobe levels, and improved directivity compared to conventional approaches. Furthermore, the framework offers robustness and computational efficiency, making it suitable for real-time implementation, particularly on embedded platforms such as FPGA-based systems. Overall, the proposed optimal control-based beamforming approach provides a powerful and flexible solution for next-generation antenna systems in 5G and radar applications.

Abstract: The impact of jawbone diseases extends far beyond the mouth. Worldwide, cancer patients completing chemotherapy often have routine dental checkups, with about 70% of patients with breast and prostate cancer and 30–40% of those with lung and other solid tumours being diagnosed with bone metastases. Oncologists treating these patients usually prescribe bisphosphonates to protect their bones, a common and necessary treatment. Yet determining whether the jawbone is starting to deteriorate is something neither the patient nor the dentist can easily detect. Studies show that medication-related osteonecrosis of the jaw (MRONJ) affects a growing share of the millions of patients on antiresorptive therapies across Egypt, the Gulf, and North Africa (up to 15%, compared to just 0.01% in the general population). Nevertheless, by the time it becomes clinically visible, the bone damage is often already irrecoverable. Patients recovering from head and neck radiotherapy, elderly patients with chronic bone loss, and those living with metabolic bone disorders face the same invisible progression. Moreover, all experience the same diagnostic gap, as the primary imaging tool, CBCT, has major drawbacks: its interpretation relies heavily on visual inspection, making conclusions highly subjective, along with the shortage of specialists in many areas, causing patients’ conditions to deteriorate between visits. Globally, more than 12.5 million Cone Beam Computed Tomography (CBCT) scans are performed annually, with total imaging volume increasing by over 50% in the last five years. Additionally, in the Middle East and Africa alone, the CBCT imaging market is projected to grow at a compound annual rate of 12.91% through 2032. This growth creates an expanding diagnostic workload that current practices are unable to meet, highlighting the need for new automated and reliable imaging models. In this work, we propose AutoCBCT, an automated CBCT model that combines Attention U-Net segmentation — which learns to focus on anatomically relevant structures while ignoring noise — with Euclidean Distance Transform-based thickness mapping to produce a spatial heatmap of the entire jaw. Indicators for MRONJ, osteoradionecrosis, fibrous dysplasia, and resorption are based on established clinical criteria. The proposed framework serves as a support tool for clinical decision-making through resorption grading (based on the Cawood and Howell classification) and automated detection of abnormal bone density patterns. The proposed approach is evaluated using 443 CBCT scans from the ToothFairy international dataset, obtained from three commercial scanner platforms with voxel spacings of 0.160–0.300 mm. Bone segmentation achieved a mean Dice coefficient of 0.884 ± 0.020 (range 0.798–0.938), with all 443 cases exceeding the clinical acceptance threshold of 0.7. The thickness estimation of the bone showed a mean absolute error of 0.209 ± 0.094 mm, with 99% of patients below 0.5 mm and every patient below 1.0 mm. The total mean thickness of the bone was 2.797 ±0.410 mm. The clinical data showed that 73.6% of the patients required augmentation or reconstruction. There was no abnormal bone in this dataset.

Abstract: Indoor robots continuously capture and process camera images, heavily taxing battery life and bandwidth. While approximate analog computing offers massive power savings by deliberately degrading sensor precision, its impact on closed-loop robotic autonomy remains largely unexplored. In this work, we introduce the first system-level evaluation framework explicitly linking analog circuit-level imperfections—including low-bit quantization, read noise, and dynamic-range clipping—with downstream 3D navigation. Through 10,500 end-to-end planning evaluations combined with 1,996 geometric mapping evaluations using diverse perception and mapping algorithms, we uncover a severe non-linear "error cascade" across the software stack. Crucially, we identify a fundamental perception paradigm shift: while semantic free-space segmentation exhibits extreme fault tolerance down to 4-bit precision, geometric perception tasks have task-specific minimum precision requirements: visual odometry remains viable at 6-bit, while monocular depth estimation acts as the system’s tightest constraint, demanding a full 8-bit baseline. Furthermore, our energy-quality Pareto analysis reveals a counter-intuitive anomaly: deliberately applying an aggressive 0.8V dynamic range clipping acts as an analog-domain noise filter, which, when paired with TSDF mapping and Theta* planning, simultaneously reduces front-end energy and increases the overall navigation success rate from 61% to 64%. Ultimately, this work provides actionable quantitative guidelines for interdisciplinary hardware-algorithm co-design in next-generation edge robotics.

Abstract: Production of a biodegradable, environmentally friendly polymer film material, composed of potato starch (PS), xanthan gum (XG), and plasticizers: glycerin, sorbitol, and citric acid, was carried out. The effect of these components on the structural and biopolymer composite mechanical properties, including elasticity and tensile strength, was investigated. The addition of XG significantly reduces the hardness for the film forming materials, thereby lowering the difficulty of gelatinization. It was demonstrated that increasing the plasticizers mass during composite blend preparation improved elasticity but reduced the mechanical strength of the films. It is assumed that these additives in the biopolymer disrupted hydrogen bonds and other intermolecular contacts between starch and gum macro chains. Glycerol influences the elasticity of the bioplastic, while sorbitol influences its strength. Taking various factors into account, the optimal combined concentration of glycerol, sorbitol and citric acid was determined in composite during film preparation. Based on the results of the new polymeric films’ flexibility study, it was concluded that they could be used as a replacement for traditional, non-biodegradable polymeric materials. At the optimal concentration of components, the strength of polymer films is 1.6 MPa, and the relative elongation is 45%.