Search Results (309)

We develop SAFIRE (Self-Attention Fuzzy-Inspired Rule Estimator), a differentiable fuzzy-inspired rule-scoring surrogate for binary medical tabular classification coupling multi-head self-attention, Gaussian membership functions, and Hard Concrete gates for continuous rule scoring. We position SAFIRE as a smooth surrogate of the discrete $L_0$-regularised rule-selection problem and establish five mathematical results and one complexity remark: (1) the relaxed objective is differentiable almost everywhere under positive Gaussian widths (enforced by a Softplus reparameterisation) and fixed batch-normalisation statistics; (2) the deterministic-inference active threshold is strictly stricter than the expected-nonzero training threshold, identifying Hard Concrete gates as continuous rule-scoring devices rather than automatic pruning mechanisms; (3) per-sample forward complexity identifies attention and rule layers as the dominant terms; (4) the Softplus–BatchNorm–linear rule operator violates all four triangular-norm axioms—with necessary and sufficient conditions per axiom and a no-finite-parameterisation impossibility result—while a Softplus reparameterisation restores coordinate-wise monotonicity; (5) a margin-based upper bound characterises disagreement between the full classifier and a top-k rule-only surrogate; and (6) the Softplus-reparameterised constrained variant is provably coordinate-wise monotone with explicit asymptotic regimes. Evaluated on four University of California, Irvine (UCI), medical binary tabular benchmarks under repeated stratified cross-validation, SAFIRE-Prog is statistically competitive with strong interpretable, modern, and gradient-boosting baselines, with one Bonferroni-significant gain over RuleFit on the Diabetic Retinopathy Debrecen corpus. The 48-configuration Hard Concrete sweep, constrained-variant comparison, and a top-k fidelity analysis (per-fold range 0.73–0.95) provide quantitative companion measurements for the mathematical framework. A supplementary large-scale hospital electronic health record (EHR) benchmark (Diabetes 130-US Hospitals, $n=\mathrm{101,766}$) shows the rule-scoring mechanism scales to ∼${10}^5$ records and, under severe class imbalance, statistically matches gradient boosting on accuracy while significantly exceeding it on macro-F1. The results offer a mathematically auditable pathway towards interpretable, auditable rule scoring for medical tabular classification, with rule signatures defined in a projected latent space rather than over raw clinical variables. Full article

Different approaches to describing the kinematics and dynamics of a mobile robot equipped with four Mecanum wheels are compared. Due to the no-slip rolling condition, the kinematic constraints imposed on the system are nonholonomic; therefore, the equations of nonholonomic mechanics must be used to model such a system. The necessary and sufficient conditions under which the dynamics of this system can be described using Lagrange equations of the second kind are derived. The solvability of the kinematic constraint equations using the pseudoinverse matrix is also analyzed. Full article

This study examines whether digital capabilities constitute a necessary condition for green innovation and firm competitiveness in the context of increasing sustainability and digital transformation pressures. Although prior research frequently links digitalization to improved environmental and business outcomes, limited evidence exists on whether firms must achieve a minimum level of digital capability to successfully generate green innovation and sustain competitive performance. To address this gap, the study investigates the relationships among digital capabilities, green innovation, and firm competitiveness using Partial Least Squares Structural Equation Modelling (PLS-SEM) and Necessary Condition Analysis (NCA). Using survey data from 740 firms across Hungary, Romania, Poland, Austria, and other Central and Eastern European (CEE) countries, the findings demonstrate that digital capabilities significantly enhance both green innovation and firm competitiveness. Green innovation further acts as a mediating mechanism through which digital capabilities translate into superior competitive outcomes. Importantly, the NCA results reveal that digital capabilities are not merely beneficial but represent a necessary condition for achieving high levels of green innovation and competitiveness within the studied sample of CEE firms, suggesting a threshold relationship that warrants further causal investigation. Firms with higher digital maturity consistently outperform less digitally developed firm. Firms with higher digital maturity consistently outperform less digitally developed firms in leveraging sustainability-oriented innovation strategies. The study contributes to the literature by advancing understanding of how digital transformation capabilities support sustainable competitiveness and by combining sufficiency and necessity analytical approaches to examine these relationships. The findings also provide practical implications for managers and policymakers by highlighting the strategic importance of investing in digital capabilities to simultaneously support environmental sustainability and long-term competitive performance. Full article

Grid-scale battery energy storage systems (BESSs) are becoming central flexibility assets in electricity systems with rising renewable penetration, changing demand profiles, and increasing system security requirements. This review examines BESS development in Australia, Singapore, China, and New Zealand, comparing strategic policy drivers, market access arrangements, revenue mechanisms, bankability conditions, support instruments, regulatory frameworks, and key deployment risks. Across all four jurisdictions, BESSs are moving from demonstration assets to core infrastructure for renewable integration, frequency control, reserve provision, congestion management, and short-duration energy shifting. The comparison shows that no single business model dominates. Australia relies heavily on volatile wholesale arbitrage, ancillary services, and government underwriting; Singapore emphasises grid resilience, dispatch precision, safety, and space-efficient deployment; China combines national strategic direction with province-specific market implementation; and New Zealand is developing a market-led, location-specific storage model within a high-renewables, hydro-dominated system. The review finds that bankable BESS deployment depends on revenue stacking, fit-for-purpose market rules, clear bidirectional asset classification, robust grid-connection processes, lifecycle safety management, and credible degradation and augmentation strategies. It concludes that BESSs are essential but not sufficient for deep decarbonisation, since long-duration flexibility and wider system reform remain necessary. Full article

Background and Objectives: Surgical site infections (SSIs) remain common after elective colorectal surgery. This systematic review and meta-analysis evaluated whether adding oral antibiotic bowel preparation (OAB) to mechanical bowel preparation (MBP) reduces SSIs compared with MBP alone. Materials and Methods: PubMed, the Cochrane Library, Scopus, and ClinicalTrials.gov were searched for English-language randomized controlled trials published from January 2005 to January 2025. Eligible trials enrolled adults undergoing elective colorectal surgery and compared MBP+OAB versus MBP alone, with standard intravenous prophylaxis in both groups. The primary outcome was overall SSI; secondary outcomes were incisional SSI and organ-space SSI. Risk of bias was assessed with RoB 2, certainty with GRADE, and odds ratios (ORs) were pooled using DerSimonian–Laird random-effects models. The protocol was prespecified but not prospectively registered. Results: Twelve trials including 4073 patients were included (MBP+OAB, n = 2069; MBP, n = 2004). MBP+OAB reduced overall SSI (OR 0.53, 95% CI 0.37–0.75; p < 0.001; I² = 62.5%; 95% prediction interval 0.17–1.66), incisional SSI (OR 0.52, 95% CI 0.34–0.80; p = 0.003; I² = 57.5%), and organ-space SSI (OR 0.63, 95% CI 0.45–0.88; p = 0.007; I² = 8.3%). The effect was preserved in metronidazole-containing regimens (OR 0.46, 95% CI 0.33–0.65), but this subgroup was exploratory. Excluding high-risk-of-bias studies supported the primary result. Publication-bias assessment was underpowered. Overall and organ-space SSI were moderate-certainty outcomes; incisional SSI was low-certainty, and anastomotic leak was very low-certainty. Conclusions: In contemporary elective colorectal surgery when MBP is used, adding preoperative OAB probably reduces SSIs. Findings do not establish whether OAB alone is sufficient or whether MBP is necessary; stewardship-relevant outcomes remain insufficiently reported. Funding was provided by ISCIII grant PI25/01285. Full article

Small and medium-sized enterprises (SMEs) face mounting pressure to advance their digital transformation while integrating sustainability practices. However, the relationship between digital maturity and ESG (Environmental, Social, and Governance) integration in SMEs remains insufficiently comprehended, especially in regional contexts. This study examines how digital maturity shapes the scope and development of ESG practices in six Quebec SMEs using a qualitative multiple-case study design guided by Yin’s framework. Data were collected through a structured 54-item diagnostic protocol generating Digital Maturity Scores (DMSs), Sustainability Management Indices (SMIs), and Digital Literacy Indices (DLIs), complemented by thematic coding in NVivo. Cross-case analysis reveals that higher digital maturity is broadly associated with more diversified ESG practices, though this alignment is uneven and conditioned by governance mechanisms, firm size, and sectoral dynamics. An inductive typology distinguishes three profiles: compliance-oriented firms, ESG diversifiers, and strategic integrators. Findings further indicate that governance structures are necessary but not sufficient conditions for sustainability outcomes, as their effectiveness depends on alignment with operational routines and data practices. This study contributes to the literature by providing a combined digital maturity–ESG diagnostic framework adapted to the realities of SMEs. It also advances three theoretical propositions suitable for testing in larger and more diverse samples. Full article

Digital traceability has become an important capability in international trade, especially in high-regulation and high-risk supply chains. However, existing research has not fully explained how institutional, technological, and coordination-related conditions combine to produce successful outcomes. This study applies fuzzy-set Qualitative Comparative Analysis (fsQCA) to 24 trade-corridor/product-chain cases to identify the configurational drivers of Digital Traceability Success (DTS). The findings show that Digital Trade Readiness (DTR), Market Strictness (MKT), Digital Infrastructure (DIF), and Cross-border Coordination (COO) are highly consistent necessary conditions for DTS, whereas Blockchain-enabled Traceability (BCT) is not. The sufficiency analysis identifies one dominant pathway, DTR * PRK * MKT * DIF * COO, with perfect consistency and substantial coverage. These results indicate that traceability success emerges from the alignment of institutional readiness, regulatory pressure, infrastructural capacity, product-related risk, and cross-border coordination rather than from blockchain adoption alone. The study contributes to digital trade and supply-chain governance literature by offering a configurational explanation grounded in conjunctural causation and causal asymmetry. It also clarifies blockchain’s role as a contingent enabling component rather than a universally necessary determinant. Practically, the findings suggest that policymakers and firms should prioritize interoperable infrastructure, institutional readiness, and cross-border governance mechanisms over stand-alone technological solutions. Full article

Underground mine emergencies compromise fixed communication infrastructure exactly when situational awareness is most critical for effective rescue operations. Existing LoRa mesh protocols fail in underground mines because they ignore the structured topology of tunnel networks, specifically the waveguide effect along straight galleries, severe signal discontinuity at junctions, and the dead-end geometry of working faces. This paper presents the Topology-Aware Concurrent LoRa (TACL) mesh protocol, in which each node autonomously infers its structural role from local RF observations and packet header information, without GPS, pre-loaded mine maps, or central coordination. Role classification resolves the contender estimation problem $\left(N_h\right)$ left open in the prior concurrent transmission literature, enabling provably bounded timing offsets before transmission. TACL assigns a spreading factor (SF)12 to dead-end source nodes for maximum link robustness and SF7–SF10 to relay nodes to create the inter-SF orthogonality margin required for concurrent decoding at junction nodes. Monte Carlo simulation of over 2000 trials yields TACL a PDR of 80.5% versus near-zero for all three baselines, confirming that topology-aware SF diversity is the necessary and sufficient mechanism to prevent junction collision collapse. Hardware deployment at the Missouri S&T Experimental Mine yields a 4.0× PDR improvement over the topology-agnostic concurrent transmission (CT)-fixed baseline, a median end-to-end latency of 1815 ms with 84× tighter latency spread than ALOHA-based protocols and 2.5× lower energy per delivered packet. These results establish that explicit exploitation of underground mine topology is essential for reliable, predictable, and energy-efficient emergency mesh communications in post-disaster underground mine scenarios. Full article

Hyperscale data center construction has become one of the largest concentrated capital flows in the global built-environment sector, with global hyperscale capital expenditure exceeding USD 230 billion in 2024 and the leading hyperscalers committing more than USD 325 billion for 2025. Generative artificial intelligence workloads have driven a structural shift in mechanical and electrical design, increased delivery-pace demands, and concentrated supply-chain pressure on a small number of specialist general contractors. This paper develops and tests a microfoundational model of dynamic capabilities for hyperscale data center project delivery using fuzzy-set Qualitative Comparative Analysis (fsQCA) on a sample of N = 18 primarily North American hyperscale-active general contractors. Capabilities are formalized as fuzzy sets X ⊆ Ω with membership functions μ_X: Ω → [0, 1] over the case space Ω; necessity and sufficiency consistency are computed using the canonical formulas Cons_N(X→Y) = Σ_i min(μ_X(i), μ_Y(i))/Σ_i μ_Y(i) and Cons_S(C→Y) = Σ_i min(μ_C(i), μ_Y(i))/Σ_i μ_C(i), and necessity is interpreted as the fuzzy-set containment PDP_high ⊆ X. Capability scores are coded from secondary public sources—ENR rankings, SEC filings, trade press, and company disclosures—rather than from primary survey or interview data. Three findings emerge: process microfoundations and seizing capability are necessary conditions for both project delivery performance and competitive advantage (Cons_N ≥ 0.97); the dominant causal recipe for high project delivery performance is the conjunction SEN ∩ SEI ∩ TRA ∩ ED with consistency 1.000 and coverage 0.771; the dominant recipe for high sensing capability is the conjunction IND ∩ PRO ∩ STR ∩ INT with consistency 1.000 and coverage 0.799. The findings are positioned against prior dynamic-capabilities studies and microfoundations theory, confirming convergence on conjunctive bundle structure while extending literature into a previously unstudied AEC segment with sharper containment relations. Full article

This paper describes the development of an automated solid waste sorting system that integrates advanced computer vision pipelines with a robotic manipulator for real-time classification and actuation. The system consists of a Deep Neural Network (DNN) and a YOLOv8-based perception module. Thedeveloped model is capable of accurately detecting and classifying objects with confidence scores exceeding 0.71, and the overall system attained a sorting accuracy of approximately 81.8% across multiple test batches. From an integration perspective, the coordination among the Intel RealSense camera, Raspberry Pi 5, Arduino Uno, ultrasonic sensors, relay-switching circuit, and SCORBOT-ER 4U robotic arm demonstrated reliable communication and execution, enabling accurate pick-and-place operations. Overall, the results confirm that the proposed system provides a functional and scalable proof of concept for automated waste segregation in controlled environments. The study highlights that while current performance is sufficient for low-speed applications, further improvements in dataset diversity, perception robustness, mechanical gripping, and feedback control are necessary to achieve higher accuracy, reliability, and industrial applicability. Full article

Dust accumulation on photovoltaic (PV) modules reduces power generation efficiency, and traditional water-based cleaning is impractical in arid regions. Inspired by the classical acoustic phenomenon of Chladni figures—specifically the mechanism where an acoustic standing wave field drives the regular migration and accumulation of particles—this study proposes a waterless dust removal method using low-frequency ultrasonic vibration via piezoelectric excitation. Impedance analysis identifies optimal electromechanical coupling at 28 kHz. Experiments demonstrate that higher driving voltages accelerate cleaning, with recovery rates saturating beyond 125 V. Notably, intense friction and collisions between particles within high-density dust layers consume substantial kinetic energy, significantly multiplying the required cleaning time. Macroscopic transport analysis reveals that dust removal relies on the synergy of vibration-induced adhesion decoupling and gravity-driven transport. Sufficient tangential gravity is crucial for macroscopic particle removal, and tilt angles above 30° provide the necessary downward driving force to ensure smooth particle sliding. Under optimal conditions, the system achieves an over 97% short-circuit current recovery at a low power consumption of ~10 W, providing a theoretical basis for waterless PV self-cleaning systems. Full article

Industrial heritage adaptive reuse occupies a structurally privileged position for degrowth: heritage listing already institutionalises material sufficiency as a regulatory obligation, mandating low intervention and resisting the demolish-and-replace logic of resource-intensive development. Yet this regulatory floor imposes no ceiling on how protected structures are programmed or who benefits; the same statutory instrument can produce different schemes depending entirely on governance. This paper demonstrates that gap through two contrasting UK gasholder adaptive reuse projects: King’s Cross Gasholders in London (private-led, luxury residential) and Granton Gasholder in Edinburgh (council-led community park). Applying De Castro Mazarro et al.’s multi-scalar degrowth framework across building, neighbourhood, and city scales through document analysis and site observations, we identify structural mechanisms explaining why building-scale alignment fails to propagate upward. The findings indicate three governance conditions are necessary to convert the structural degrowth potential of industrial heritage into substantive outcomes: public control over development decisions, community participation extended to strategic priorities rather than design preferences, and explicit integration of degrowth values into upstream planning frameworks. Industrial heritage adaptive reuse is not inherently a degrowth practice, but it is one of the few urban development contexts where the regulatory preconditions for degrowth alignment are already in place. Realising that potential requires governance structures that treat sufficiency and collective wellbeing as binding objectives, not rhetorical claims. Full article

Energy homeostasis requires precise coordination between brain-derived appetitive signals and peripheral nutrient-handling mechanisms. Although Neuropeptide F (NPF) and its mammalian homolog NPY are well-established central stimulators of feeding, whether and how they regulate nutrient assimilation in the gut remains unknown. Here, using Drosophila, we identify a previously unrecognized transcriptional circuit between NPF and the purine synthesis enzyme GART trifunctional enzyme (Gart) that governs feeding by controlling gut absorptive efficiency. We show that NPF signaling acts via its receptor NPFR to positively regulate Gart expression specifically within the intestine. Conversely, Gart activity exerts negative feedback on NPF expression, forming a reciprocal regulatory loop. Functionally, gut-specific, but not glial or fat body-specific, Gart is necessary and sufficient for promoting food absorption and consumption. Genetic epistasis experiments demonstrate that Gart acts downstream of NPF to execute its function. Strikingly, peripheral NPF from the fat body and gut, rather than brain-derived NPF, serves as the primary systemic signal driving this loop. Our findings reveal a gut-centered homeostatic module where NPF activates Gart to boost nutrient absorption, while the resultant feeding activity in turn curbs the signal, ensuring calibrated energy intake. This work redefines a canonical neuropeptide’s role from a pure behavioral driver to a key regulator of peripheral metabolic efficiency, and establishes a novel framework for understanding gut–brain communication in energy balance. Full article

Accurate damage characterization in thermoset Carbon Fiber-Reinforced Polymer (CFRP) composites using Acoustic Emission (AE) requires statistically robust and interpretable models. This study employs multinomial logistic regression with forward selection and Type III analysis to identify the minimal set of AE parameters necessary for classifying damage mechanisms (fiber breaks, delamination, matrix cracks) in quasi-isotropic thermoset CFRP laminates under synchronously recorded load conditions. Starting from 18 conventional time- and frequency-domain descriptors, forward selection yielded seven candidate predictors. However, Type III analysis revealed that only four parameters, Load, Initiation Frequency, Amplitude, and Average Frequency, provide unique, statistically significant contributions (p < 0.05). The remaining predictors became redundant once these four were included. Machine learning and deep learning models trained on this minimal feature set achieved validation accuracies up to 98.7% on external specimens. High-frequency components (>1 MHz), as recorded at the sensor location after propagation and sensor convolution, were associated with fiber break events at elevated loads, while delamination events exhibited higher amplitude and lower-frequency content (<200 kHz) compared to matrix crack events. These observed frequency ranges reflect the combined effects of source mechanisms, guided wave dispersion in the 2.4 mm thick laminate, PWAS sensor response, and HDT-based hit segmentation, and are consistent with established AE damage signatures in literature. The results indicate that this four-parameter set is sufficient to classify the labeled AE waveform classes under monotonic tensile loading of quasi-isotropic [45/90/−45/0]_2s laminates, achieving 98.7% agreement with reference labels assigned via waveform morphology and spectral analysis. The proposed approach reduces computational overhead and enhances interpretability for structural health monitoring applications, pending validation across broader material systems and loading scenarios. A limitation of this study is that reference labels were assigned using waveform morphology and spectral analysis, lacking independent physical validation (e.g., microscopy). Full article

The rapid digitalization of the media and publishing industry has deepened systemic asymmetries in resources, power, and institutional rights. These asymmetries create fundamental barriers to the economic–institutional sustainability of digital content dissemination. Existing governance frameworks have not yet comprehensively addressed the resulting competitive and informational imbalances. Adopting China’s publishing and media industry as a focal case, this study draws on symmetry theory to develop an integrated analytical framework. It reconceptualizes government regulation as a multi-dimensional governance mechanism operating across three dimensions: resource allocation, technological innovation, and rights protection. We test this framework empirically using Xinbang Index data covering the top 10 publishing and media enterprises from 24 January 2025 to 7 December 2025. Multiple regression analysis and Spearman rank correlation are applied to assess each dimension’s differential impact on content dissemination efficiency. The results yield four key findings. First, all three regulatory dimensions contribute positively to content dissemination efficiency. Second, technological innovation is the most potent symmetry-restoring lever, exerting a statistically robust direct effect on dissemination outcomes. Third, resource allocation provides a necessary foundational contribution, while rights protection operates conditionally—its effect is fully realized only alongside adequate technological and resource inputs. Fourth, an integrated multivariate regression confirms the cross-dimensional hierarchy: the standardized Beta coefficient for technological innovation (β = 0.394) exceeds those for rights protection (β = 0.294) and resource allocation (β = 0.125). No single regulatory instrument is sufficient to achieve dynamic equilibrium. A synergistic, technology-centered combination of all three dimensions is required. This study proposes a tripartite symmetry-based governance strategy for media platform ecosystems. The symmetry framework developed here offers an analytical template for diagnosing analogous asymmetries in other platform-dependent sectors. Empirical validation beyond the Chinese publishing and media context is recommended as a priority for future research. Full article