Search Results (421)

This study utilized an experimental single-case design to evaluate a professional development package to support educators’ implementation of an augmentative and alternative communication (AAC)-supported, play-based naturalistic developmental behavioral intervention (NDBI), which we called naturalistic AAC intervention (N-AAC). Participants were three minimally speaking students with autism (4–8 years of age), each paired with one of their educators (i.e., speech-language pathologist, pre-service special education teacher, early childhood assistant teacher). The primary aim was to examine the effects of professional development on educator implementation of N-AAC. We also descriptively examined changes in students’ communication and language use during educator–child play and generalization to peer interactions. The findings showed that professional development was effective at teaching educators to implement N-AAC with fidelity. Student communication outcomes showed descriptive improvements following educator training and coaching and N-AAC implementation. However, as expected, gains did not generalize to peer interactions. The findings suggest that professional development improves educator implementation of AAC-supported NDBI strategies during play and that their increased implementation fidelity is accompanied by promising descriptive changes in student communication. Future research is needed to further examine the impact on student communication, promote generalization to peer interactions, and evaluate the potential for larger-scale implementation. Full article

This manuscript presents a patent-based engineering case study of a compact LiBr–H₂O evaporator–absorber unit, tracing its progression from conceptual embodiment to laboratory validation through contextualized technology-readiness assessment and bounded data-driven analysis. The study reconstructs three successive prototypes, applies the international Technology Readiness Level (TRL) framework together with the Mexican TRL guideline, and includes an exploratory artificial neural network (ANN) analysis of the validated Prototype III. The results show a maturation pathway: Prototype I corresponded to conceptual embodiment, Prototype II provided proof-of-concept evidence through observable cooling, and Prototype III was a protected, instrumented, and experimentally validated laboratory prototype, conservatively assigned to TRL 4 as the highest level supported by the evidence. The auxiliary ANN gave only a limited approximation of the thermal response (mean test R² = 0.41, dispersion ±0.32), consistent with a single-run laboratory-scale dataset rather than robust predictive modeling. Overall, the study integrates prototype trajectory, intellectual-property protection, TRL assessment, and bounded analysis into a rigorous evaluation of a protected pre-commercial thermal subsystem. Beyond this device, the framework offers inventors, designers, and research groups a transferable reference, letting them build on a documented pathway rather than restarting from the lowest readiness levels and identifying the evidence needed for each TRL transition. Full article

Near-field direct illumination from extended luminaires presents a fundamental modeling challenge in automated visual inspection: standard far-field IES (Illuminating Engineering Society) photometric data treat luminaires as point sources, an assumption that breaks down when source-to-target distances are comparable to luminaire dimensions. This paper addresses this breakdown by establishing, both analytically and experimentally, the conditions under which IES-based point-source discretization remains valid and the minimum discretization required when it does not. A solid-angle-based illuminance formulation on triangular meshes is coupled with a controlled virtual-emitter discretization of elongated luminaires, and a reproducible selection workflow is derived that relates emitter count to the source–target distance ratio and a specified error criterion. The dependence of discretization requirements on source–target distance is characterized by an angular-subtense argument, yielding the scaling relation $N\sim (L/H)·C$, where L is the luminaire length, H the working distance, and C a constant determined by the IES angular gradient and the required accuracy. Validation experiments with one and two industrial linear luminaires (1.2 m, Banner Engineering WLS15xDW1200Dx) include single-luminaire heights of $H=20\mathrm{cm}$, $25\mathrm{cm}$, $35\mathrm{cm}$, $50\mathrm{cm}$, and $60\mathrm{cm}$, as well as effective-length reduction cases produced by opaque end masking at $H=35\mathrm{cm}$. The single-luminaire validation set compares $N=1$–7 virtual emitters for all cases, with the $H=20\mathrm{cm}$ case extended to $N=9$. The selected emitter counts are chosen as the best-performing candidate simulations after considering scalar error, smoothness, and profile consistency. The selected uncovered cases are $N=9$ at $H=20\mathrm{cm}$, $N=7$ at $H=25\mathrm{cm}$, $N=5$ at $H=35\mathrm{cm}$, and $N=3$ at $H=50$–$60\mathrm{cm}$. The masked-source experiments confirm that reducing the effective source length at fixed height reduces the required emitter count. The fitted selection relation developed from these cases indicates that the working distance H has the stronger influence within the tested range. The method provides a computationally efficient, practitioner-ready tool for inspection-lighting design when near-field goniophotometry or optical ray tracing is unavailable. Full article

This study represents a comprehensive analysis of the implementation of twin counter-rotating common-axis (coaxial) rotor systems in the design process and technical application of rotorcraft and Unmanned Aerial Vehicles (UAVs). In detail, the conducted literature review clearly illustrates the already usable vehicles and the existing experimental models. The application of a system of two coaxial rotors, one above the other, rotating in opposite directions, eliminates the need for a tail rotor for the provision of directional stability and leads to several additional advantages such as the reduction in the rotorcraft’s weight and enhancement of the directional stability qualities in comparison with the single main rotor configurations. However, the inclusion of two rotors, one above the other, affects lift generation, reducing its magnitude on the lower rotor, while the lift and the thrust of the upper rotor remain relatively unchanged. The implementation of two-rotor systems requires complex algorithms with respect to cyclic and collective pitch control. Ultimately, the analyzed cases indicate the existing gap in the research into coaxial systems concerning the influence of the distance between the two rotors and the collective pitch on the generated thrust and the interferences in cross-flow conditions. Full article

Smart waste systems can support sustainable recycling only when sensing, classification, and routing decisions are linked to transparent uncertainty management. This study aims to develop and evaluate a measurement-calibrated, risk-aware selective routing prototype for sustainable smart waste sorting under bench-scale conditions. The proposed prototype integrates an HC-SR04 ultrasonic sensing layer, Arduino Nano control, ESP8266 wireless synchronization, calibration-based fill level conversion, median filtering, exponential smoothing, hysteresis, and persistence-driven alert logic with a conveyor-based single-item vision-routing layer. The sorting layer routes items into glass, metal, plastic, trash, or a reject stream using a reject-aware VGG19 classifier with true logit temperature scaling and calibrated confidence gating. A quantitative prototype-level experimental evaluation was conducted using a five class benchmark of 2527 TrashNet images under a stratified 75/10/15 hold-out design, with cardboard and paper serving as outlier-exposure samples for the reject class. The final model achieved 88.13% test accuracy, 88.15% weighted F1, and 96.60% reject class F1. With a final policy tau = 0.70, the system routed 76.09% of routing class test items with 92.66% routed precision, while reject recall reached 98.66% and reject false acceptance was limited to 1.34%. Structured perturbation testing showed that severe visual degradation reduced automatic routing coverage but mostly shifted uncertain cases toward rejection. The contribution of this work is a transparent prototype-level mechanism that links calibrated sensing, calibrated visual confidence, selective rejection, and actuation-aware routing to support recycling stream purity under bounded uncertainty. Future work should validate the approach under multi-bin, multi-object, and field deployment conditions. Full article

Transformative therapeutic innovation should not begin with a molecule—or even a molecular target. It should begin with a clearly defined unmet clinical need. Here, we present a seven-step Translational Therapeutic Development Roadmap that systematically connects an unmet medical need to a developable drug candidate through the disciplined sequence of (i) defining the need, (ii) understanding disease and resistance biology, (iii) building a mechanistic hypothesis, (iv) defining a target product profile (TPP), (v) molecular design and experimental validation, (vi) developability and manufacturability assessment, and (vii) clinical translation. A central conclusion emerging from this review is that resistance biology should be viewed not merely as a cause of therapeutic failure, but as a primary design input for next-generation therapeutic innovation. Our analysis identifies continuous alignment among unmet clinical needs, resistance biology, mechanistic hypothesis, molecular design, developability, and clinical translation as the defining characteristic of successful therapeutic development. We use dual-payload antibody–drug conjugates (ADCs) as a contemporary and highly illustrative case study of this resistance-informed therapeutic development approach. Single-payload ADCs such as trastuzumab deruxtecan and sacituzumab govitecan have transformed treatment across multiple solid tumors, yet most patients ultimately relapse through antigen loss, defective intracellular trafficking, drug efflux, payload-target alterations, and tumor heterogeneity, creating an emerging post-ADC treatment gap. Dual-payload ADCs, which deliver two mechanistically distinct warheads from a single antibody, represent a form of molecular combination therapy designed to increase the barrier to resistance and address multiple escape pathways simultaneously, as well as provide a clinically relevant model for resistance-informed therapeutic design. Using dual-payload ADCs as a worked example, we demonstrate how resistance biology directly informs payload pairing, molecular architecture, conjugation strategy, experimental validation, and developability. Our analysis indicates that successful dual-payload ADC design depends not simply on combining two cytotoxic payloads, but on selecting complementary mechanisms with non-overlapping resistance liabilities while satisfying predefined target product profiles and manufacturability requirements. We further summarize resistance-guided payload pairing strategies, including topoisomerase I plus tubulin inhibitors, topoisomerase I plus DNA-damage-response inhibitors, cytotoxic plus immunomodulatory payloads, and cell-permeable plus non-permeable combinations; the conjugation chemistries that enable defined dual-payload products; the preclinical validation, pharmacological optimization, and developability hurdles that separate promising biology from viable therapeutics; and the rapidly expanding clinical landscape, including the first-in-human program KH815 and emerging bispecific dual-payload constructs. Finally, we demonstrate that the same translational roadmap extends beyond ADCs to radiopharmaceutical conjugates, multispecific antibodies, targeted protein degraders, and cell and gene therapies, indicating that it represents a general framework for therapeutic innovation rather than an ADC-specific strategy. Collectively, this review supports the concept that therapeutic innovation is most successful when unmet clinical needs, resistance biology, molecular design, developability, and clinical translation are considered as an integrated continuum rather than as independent stages of drug discovery. This Translational Therapeutic Development Roadmap provides an organizing framework for guiding the rational development of next-generation targeted therapeutics across diverse therapeutic modalities. Full article

Objective: This study aimed to determine whether robot-assisted therapy, low-frequency rTMS, or intensive therapist-guided upper-limb training provides additional recovery beyond self-directed training in individuals 4–9 months post-stroke. Design: A five-phase single-case experimental study was conducted with two baseline phases and three randomized 3-week intervention phases. Subjects/Patients: Sixteen adults with moderate-to-severe upper-limb motor impairment in the late subacute phase after stroke (4–9 months post-stroke) were included. Methods: Participants completed intensive task-oriented training, low-frequency rTMS, and robot-assisted therapy in a randomized order. Primary outcomes were Fugl–Meyer Assessment for the Upper Extremity (FMA-UE), active range of motion, and muscle strength. Secondary outcomes included EQ-5D and WHODAS 2.0. Results: FMA-UE motor scores improved significantly over the study period (8–10 points). However, comparable gains occurred during baseline phases. rTMS and intensive training produced within-phase improvements, whereas robotic therapy did not. Participants with higher initial FMA-UE scores improved, while those with severe paresis showed minimal benefit and occasional decline during rTMS. Disability and quality-of-life measures remained stable. Gains were maintained at 1-year follow-up. Conclusions: In the late subacute phase after stroke, modest upper-limb motor improvements occurred, but effects were not clearly attributable to specific interventions beyond ongoing recovery. Treatment response depended strongly on baseline motor severity, with limited benefit in severe paresis. Full article

Background: The global prevalence of anxiety and internalizing disorders in adolescence has increased epidemiologically over the past decade, compounded by the impact of the COVID-19 pandemic and the expansion of digital social networks. Despite the availability of empirically based interventions, their systematic implementation in Spanish educational settings—especially in socioeconomically vulnerable environments—remains insufficient. This study aimed to assess the emotional symptomatology profile in a sample of adolescents enrolled in the 2nd year of Compulsory Secondary Education (CSE) and to describe the changes in symptomatology observed after implementation of a multicomponent intervention program in an ordinary school setting. Methods: a quasi-experimental single-group repeated-measures design was used, with pretest–posttest measurements (T1–T2). The sample included 79 participants (age in completed years: M = 13.28 years, SD = 0.64; range: 12–15; 49.4% female, 44.3% male, 6.3% undisclosed), selected by convenience at IES Estuaria (Huelva). The assessment instrument was the Revised Child Anxiety and Depression Scale (RCADS-47), which measures total anxiety, total internalization, and six clinical subdimensions aligned with DSM-5: generalized anxiety disorder (GAD), major depressive disorder (MDD), panic disorder (PD), separation anxiety (SA), social phobia (SP), and obsessive–compulsive disorder (OCD). The intervention consisted of five multicomponent group workshops (45 min/session; three class groups) integrating emotional psychoeducation, receptive music therapy, cognitive–behavioral emotional regulation, assertive communication, and body expression/mindfulness. Results: At pretest, Social Phobia (SP) showed the highest clinical impairment, significantly affecting more females (66.67%) than males (20.00%). Generalized Anxiety Disorder (GAD) also presented high impairment in females. Significant correlations between pairs of subdimensions revealed a high comorbidity pattern. Following the intervention, reductions in clinically significant levels were observed across all dimensions. Matched-pairs Wilcoxon signed-rank tests confirmed statistically significant score reductions from T1 to T2 in Total Anxiety, Total Internalization, Social Phobia, and Generalized Anxiety Disorder (all p < 0.05), with the largest effect for Social Phobia (r = 0.46); no significant change was detected for Panic Disorder, Separation Anxiety, Major Depressive Disorder, or Obsessive–Compulsive Disorder, although the direction of change favored improvement in all cases. Conclusions: The multicomponent intervention program produced improvements in emotional symptomatology over the short-term follow-up period, although without achieving complete clinical remission in any subdimension. The persistent sex differences—with greater residual impairment in the female group after intervention—underscore the need to incorporate a gender perspective in the design of school emotional health programs. High comorbidity rates between subdimensions support the utility of transdiagnostic approaches. Implications for school nursing practice and future research are discussed. Full article

Traditional volumetric asphalt mix design methods do not directly evaluate cracking and rutting resistance, which may result in mixtures with inadequate field performance despite satisfying conventional volumetric requirements. Balanced Mix Design (BMD) has been introduced to address this limitation by incorporating performance testing. However, it remains unclear whether additive modification alone can recover mixtures that do not satisfy BMD criteria, or whether volumetric redesign (binder content optimization) is necessary. Therefore, this study investigated the effectiveness of additive modification before and after BMD redesign using IDEAL-CT and IDEAL-RT performance indices. Three additive systems were evaluated: SBS polymer, nano-silica, and hybrid modification. Performance threshold values for CT and RT Indices were established using a percentile-based statistical approach derived from an experimental database of 18 asphalt mixtures prepared with different aggregate gradations, filler types, and asphalt binder contents. The 25th percentile (P25) was adopted as the minimum performance criterion. The experimental program consisted of three evaluation cases. The first case investigated the ability of additives to recover initially performance-deficient mixtures before and after BMD redesign. Results showed that additive incorporation alone was insufficient to recover deficient mixtures and, in some cases, reduced cracking resistance due to excessive stiffness. However, after BMD redesign, the modified mixtures achieved balanced cracking and rutting performance above the adopted threshold values. The second case, based on a single initially compliant mixture, suggested that additives may be more effective when applied to mixtures that already satisfy performance requirements; however, this observation is preliminary and requires validation with a broader range of passing mixtures. The hybrid modification system provided the best overall balance. The third case isolated the effect of SBS polymer after BMD redesign using paired t-tests and Cohen’s d analysis. Statistical results confirmed a significant and very large positive effect of polymer modification on rutting resistance, whereas the effect on cracking resistance depended strongly on filler type. Overall, the findings indicate that additive modification cannot reliably compensate for deficient mixture design, while the combination of BMD redesign and additive modification can successfully achieve balanced performance. In addition, filler characteristics were found to play a critical role in controlling modifier effectiveness. These findings are based on a limited number of mixtures and additive combinations, and the proposed thresholds (CT ≥ 52, RT ≥ 44) should be validated using independent datasets before general application. Full article

Existing target sorting methods suffer severe performance degradation or even failure under inherent severe spectrum overlap, homogeneous protocol parameters, and scarce single-source points in Synchronous Non-Orthogonal Frequency Hopping (SNOFH) scenarios. To address this challenge, this paper proposes a passive sorting framework for SNOFH UAV swarm signals based on multi-station relative hopping time difference. The proposed framework constructs a spatial-location-driven sorting feature system, designs a kernel joint distribution adaptation module to eliminate inter-station measurement discrepancies, and develops a multi-scale wavelet-based method to achieve sub-sampling level hopping time extraction, reducing the dependence on prior FH parameters and hardware radio frequency fingerprints. Experimental comparisons between the proposed and reference sorting methods are conducted on a simulated SNOFH dataset to validate the performance of the proposed sorting framework. The experimental results show that the proposed method achieves the highest sorting accuracy of 98%, outperforming adopted baselines in most SNOFH cases. The proposed method exhibits favorable robustness with noise interference, clock-synchronization error, carrier-frequency offset and multipath influence. It is a suitable choice for UAV swarm sorting under regular and slow-varying UAV formations. Full article

Cloud task scheduling is a critical optimization problem in cloud computing environments, aiming to allocate computational tasks to appropriate virtual machines while reducing execution time, balancing resource load, and minimizing scheduling cost. However, due to the high dimensionality, nonlinear characteristics, and complex constraints of cloud scheduling scenarios, traditional optimization methods often struggle to obtain high-quality solutions efficiently. To address these challenges, this paper proposes a Multi-strategy Improved Golden Sine Optimization Algorithm (MIGoldSA) for global optimization and cloud task scheduling problems. First, an adaptive chaotic opposition initialization strategy is incorporated to improve the distribution quality and diversity of the initial population. Second, a dynamic elite-guided sine evolution strategy is designed to reduce the dependence on a single best individual and improve the coordination between global exploration and local exploitation. Third, an Economic Investment Strategy is introduced to adaptively allocate search efforts according to the optimization potential of individuals. To verify the effectiveness of MIGoldSA, extensive experiments are conducted on the IEEE CEC2017 and CEC2022 benchmark suites and compared with nine advanced optimization algorithms. The results show that MIGoldSA obtains the best or tied-best mean fitness values on 60 out of 84 benchmark cases, accounting for 71.43% of all test cases. In the Wilcoxon signed-rank test, MIGoldSA achieves 662 wins, 57 ties, and 37 losses among 756 pairwise comparisons, corresponding to an overall win rate of 87.57% and a non-inferiority rate of 95.11%. In addition, the Friedman mean ranks of MIGoldSA are 1.47, 2.00, 3.98, and 4.17 under the four benchmark settings, which are reduced by 85.26%, 79.94%, 45.25%, and 42.32%, respectively, compared with the original GoldSA. Furthermore, the proposed algorithm is applied to cloud task scheduling problems under different task scales. The experimental results show that MIGoldSA maintains competitive time-cost performance and achieves clear reductions in load cost, price cost, and comprehensive scheduling cost. Compared with the original GoldSA, the normalized comprehensive scheduling cost is reduced by approximately 9–14% in small-scale scenarios and approximately 18–21% in large-scale scenarios. Meanwhile, the normalized load cost and price cost are reduced by about 18–25% and 10–18%, respectively, and the time cost shows an approximately 8–12% reduction in large-scale scheduling scenarios. These quantitative results demonstrate that MIGoldSA can improve the optimization accuracy, statistical robustness, and overall scheduling cost efficiency of the original GoldSA on most tested problems. Full article

The objective of this study is to recover the transient out-of-plane displacement field of clamped circular plates subjected to blast loading using a single high-speed camera, as a low-cost alternative to stereo Digital Image Correlation (DIC) for the specific class of axisymmetrical structural responses of circular plates. The dynamic response of thin metal plates to blast loading is a fundamental problem in protective structural design, traditionally investigated through DIC. Although it provides full-field displacement measurements with high spatial resolution, it requires stereo camera arrangements, controlled illumination, speckle pattern preparation, and elaborate calibration procedures that significantly increase experimental cost and complexity. This study introduces a monocular optical method applicable to axisymmetrically defined material testing applications, such as the response of circularly supported isotropic plates under a uniform impulsive load, to recover the transient out-of-plane displacement field without using DIC. Clamped circular aluminum plates are subjected to blast loading generated by PG-3 charges of variable mass detonated at the closed end of a shock tube, with the exposed face matching the tube cross-section so as to enforce axisymmetric pressure load. A diametral reference line marked on the rear face of each specimen was recorded by a single high-speed camera, and a perspective correction derived from the axisymmetric deformed geometry was then applied to reconstruct the time-resolved displacement profile along the diameter. The permanent post-test deformed shape of each plate was subsequently digitized through 3D scanning and used as ground truth to validate the optical reconstruction. The reconstructed profiles closely matched the scans: for the conventional responses the root-mean-square error was 1.251 mm with a normalized mean residual of 6.57% (Case A) and 1.793 mm (9.20%, Case B), while for the anomalous counterintuitive response it was 1.043 mm (14.93%, Case C). Symmetry can thus be exploited as an active measurement principle to obtain quantitative blast-response data with substantially reduced experimental burden and without specialized stereo-optical instrumentation. Full article

International evidence positions the built environment as an active component of the quality of life of older adults; however, the empirical quantification of that relationship and its hierarchization to guide design decisions in Latin American geriatric residences remain a persistent gap. Against this background, the present study examined how biophilic architecture relates to the quality of life of older adults residing in a geriatric residence in the Cercado de Lima district, adopting a single-case study approach. A quantitative approach with a non-experimental, cross-sectional, and correlational design was adopted. The sample comprised 81 proxy informants, relatives in close and ongoing contact with the residents, recruited by non-probabilistic convenience sampling. A structured questionnaire of 25 Likert-scale items, each with five response categories, was used to gather the data, administered through the QuestionPro platform. Content validity was established through the judgment of three architecture specialists; reliability was confirmed through Cronbach’s alpha coefficient ($\alpha$ = 0.943). Given that the data did not follow a normal distribution (Shapiro–Wilk, p < 0.05 in 9 of 10 variables), the inferential analysis relied on Spearman’s rho coefficient, with Kendall’s Tau-b as a complement. The results revealed a positive, statistically significant, and large-magnitude association between biophilic architecture and quality of life ($\rho$ = 0.792, p < 0.001). Dimensional analysis identified a hierarchical pattern organized in two statistically distinguishable levels. In biophilic architecture, a first level comprised the nature of the space ($\rho$ = 0.792) and sensory stimulation ($\rho$ = 0.783), and a second significantly lower level comprised natural analogs ($\rho$ = 0.621) and nature in the space ($\rho$ = 0.605). In quality of life, a first level comprised physical health ($\rho$ = 0.763), social relationships ($\rho$ = 0.753), and psychological health ($\rho$ = 0.720), and a second level comprised environment ($\rho$ = 0.564); coefficients within each level did not differ significantly, whereas the difference between levels was significant. The obtained empirical hierarchization was translated into evidence-informed design orientations, offering architects and facility managers a non-prescriptive guide for setting design priorities where infrastructure is limited, in alignment with Sustainable Development Goals (SDGs) 3 and 11. The study was conducted through proxy informants, family members with direct and sustained contact with the resident, a methodological configuration recognized in the specialized literature on institutionalized older adults and whose perceptual mediation remains as a residual consideration of the design when interpreting the findings. As a single-case study, the findings characterize the analyzed institutional context and constitute transferable hypotheses to be verified in further residences rather than generalizations to the broader population of geriatric residences. Full article

Social problem-solving (SPS) difficulties may affect social, communicative, and adaptive functioning among individuals with autism. This study conducted a three-level meta-analysis of SPS interventions in single-case experimental design (SCED) research. Twenty-one SCED studies published between 2002 and 2025 met the inclusion criteria, yielding 114 dependent-variable-level effect sizes nested within 59 participant clusters. The unconditional three-level model showed a positive and statistically significant pooled effect, 1.741 (SE = 0.087, 95% CI [1.570, 1.911], p < 0.001), with low approximate total heterogeneity (I² = 24.48%). Moderator analyses did not identify clear statistically significant predictors of effect-size variability across SPS centrality, intervention setting, intervention type, implementer type, participant characteristics, or methodological quality. Sensitivity and study-level publication-bias analyses provided no clear indication that the findings were driven by a single influential study or by obvious small-study effects. Overall, targeted outcomes improved from baseline to intervention phases in studies of SPS-related intervention packages. Because many studies used multi-component intervention packages, the observed effects reflect the combined impact of interventions in which SPS-related components were embedded, and it is not possible to isolate the independent contribution of SPS components based on the available SCED evidence. Full article

Small businesses face many of the same cyber threats as larger organisations but often lack equivalent budgets, specialist personnel, and formal security operations capability. This paper proposes Agile Resilience in Security for Enterprises (ARISE), a lightweight cyber-resilience framework and maturity model designed for resource-constrained small businesses. ARISE adapts prevention, detection, response, and recovery into an agile lifecycle so that organisations can improve cybersecurity maturity progressively rather than through a single large compliance project. The study combines framework benchmarking, a practical interpretive case used to position ARISE within reflexive thematic analysis (RTA) and maturity-model benchmarking, and quantitative machine-learning experiments using the UNSW-NB15 intrusion-detection dataset. The experimental component evaluates selected Weka classifiers, including J48, JRip, Random Tree, Decision Table, and Naive Bayes, to examine whether low-cost tools can support network intrusion detection in small-business contexts. Results show very high aggregate performance for tree- and rule-based classifiers, while class-level outcomes highlight that overall accuracy can conceal weak detection of minority attack categories. The paper therefore positions ARISE as a practical, iterative, and standards-informed framework that complements, rather than replaces, enterprise-grade security operations. Its value lies in giving small businesses an accessible starting point for identifying risk, selecting controls, improving cyber awareness, detecting suspicious activity, responding consistently, and learning from incidents. Full article