Abstract: Just as Large Language Models (LLMs) are now commonly used to generate solutions to problems, biological organisms since the dawn of life have been generating solutions for survival as they continuously face novel challenges in dynamic environments. Collectives of cells must coordinate to solve problems they have never encountered before, generating adaptive responses not explicitly specified in their genome. Understanding how this kind of collective intelligence emerges from local interactions among agents with heterogeneous capabilities remains a central challenge in systems biology. Meanwhile, LLMs continue to struggle with creative problem-solving beyond their training data, especially in solving complex problems, such as mathematical discoveries. These challenges are complementary. Insights from biological collectives can guide the design of more capable LLM systems, while controlled study of LLMs may reveal mechanisms difficult to isolate in living systems. This study introduces LLM-simulated expert conferences as a controllable in silico model system for studying collective problem-solving dynamics. The LLM was prompted to simulate conferences among synthetic agents, each assigned a distinct expertise profile, to solve a mathematical problem (Yu Tsumura's 554th problem) that otherwise could not be solved via direct prompting. Analysis of problem-solving dynamics revealed three hallmarks known for biological collective intelligence. First, division of labor emerged without pre-assignment, with errors detected by agents whose expertise matched the error type (p < 0.05). Second, functional repair chains arose spontaneously following a Detect, Confirm, Repair, Validate sequence analogous to sequential task handoffs in biological systems at multiple scales, such as error correction in DNA or social insect behavior. Third, discourse dynamics exhibited a phase transition from stochastic verification to ordered consensus ultimately providing the solution to the problem. Transition entropy dropped from 2.27 bits in the verification phase to 0.25 bits at consensus, representing a 9-fold collapse. This entropy collapse provided an intrinsic termination signal that characterizes consensus formation in biological collectives. Thus, the result supports the view that the mechanisms and information processing underlying collective intelligence is substrate-independent (either biological or silicon-based) and can be further studied using the new synthetic collective model mainframe. Furthermore, LLM-simulated expert conferences offer a disruptive innovation in LLMs’ problem-solving capabilities (beyond their training data) and may be applied to any complex problem in mathematics or other scientific disciplines that need creative or novel solutions.

Abstract: Objectives: To summarize the best evidence regarding folic acid supplementation for preventing neural tube defects (NTDs) in women of childbearing age and to develop a structured evidence summary for guiding clinical practice. Methods: We systematically searched multiple databases and professional websites from January 1, 2013, to September 18, 2025. Sources included 7 databases (PubMed, Embase, CINAHL, Web of Science, CNKI, Wanfang, VIP) and 20 professional websites (e.g., Medlive, GIN, NICE, ACOG, UpToDate, Chinese Medical Knowledge Database, etc.). The search targeted clinical guidelines, expert consensuses, and recommended practices on folic acid supplementation for NTD prevention in women of childbearing age. The retrieved literature underwent quality assessment, evidence extraction, and summarization. Results: The review included 17 publications: 8 guidelines, 4 expert consensuses, and 5 recommended practices. From these, we synthesized 14 distinct evidence statements, organized into five thematic dimensions: risks of neural tube defects and the role of folic acid, time window of neural tube closure, timing and dosage of folic acid supplementation, relationship between dietary folic acid and folic acid tablets, and folic acid-related testing. Conclusions: his study synthesized the best available evidence regarding folic acid supplementation for preventing NTDs in women of childbearing age, providing an evidence-based foundation to inform clinical practice. Future implementation efforts should focus on integrating recommendations into electronic health systems, developing precision public health interventions, and employing visual aids for health education.

Abstract: This paper proposes a comprehensive framework for integrating Digital Twins (DT) with real-time traffic optimization systems to enhance urban mobility management in Smart Cities. Using the Pobitno Roundabout in Rzeszów as a case study, we established a cali-brated microsimulation model (validated via the GEH statistic) that serves as the core of the proposed Digital Twin. The study goes beyond static scenario analysis by introducing an Adaptive Inflow Metering (AIM) logic designed to interact with IoT sensor data. While traditional geometrical upgrades (e.g., turbo-roundabouts) were analyzed, simulation re-sults revealed that geometrical changes alone—without dynamic control—may fail under peak load conditions (resulting in LOS F). Consequently, the research demonstrates how the DT framework allows for the testing of "Software-in-the-Loop" (SiL) solutions where Python-based algorithms dynamically adjust inflow parameters to prevent gridlock. The findings confirm that combining physical infrastructure changes with digital, real-time optimization algorithms is essential for achieving sustainable "green transport" goals and reducing emissions in congested urban nodes.

Abstract: We formulate an operational hypothesis—the Synchronization Latency Principle—as a disciplined extension of an “Information Audit” viewpoint within a locality-preserving quantum cellular automaton (QCA) framework. The central claim is scoped in a referee-proof way: matter-like excitations are auditable images that are not certified at a single-site update, but only after an audit closes over a minimal local neighborhood. In three dimensions, a nearest-neighbor stencil suggests a (1 + 6) block of cardinality 7; under explicit circuit-locality and audit assumptions, we show a clean lower bound Daudit ≥ 7 on the micro-depth needed to incorporate all neighbor links into a joint certification. To strengthen the theory beyond narrative plausibility, we add: (i) an operational definition of copy time via hypothesis-testing distinguishability (Helstrom bound), (ii) a quantum-speed-limit style lower bound on τcopy via quantum Fisher information and an explicit “stiffness” parameter χ, (iii) a reproducibility / audit-trail protocol separating priors (calibration) from validation (comparison tables), and (iv) an explicit toy construction with a 7-layer gate schedule. We also separate particle masses (PDG), atomic/isotopic masses (NIST), and nuclear masses (AME-style conversion), with electron and electronic-binding corrections stated and numerically illustrated.

Abstract: We investigate the time-dependent physical spectrum of the driven Jaynes-Cummings model, where both the atom and the quantized field are simultaneously driven by an external classical field. By leveraging the mapping of the time-dependent Hamiltonian onto the standard stationary Jaynes-Cummings form via unitary transformations, we determine the exact two-time correlation functions for both the atomic and field subsystems. These are then employed to compute the time-dependent physical spectrum using the Eberly-Wódkiewicz formalism. Our results demonstrate that the atomic spectral features are significantly reshaped by the external driving, exhibiting tunable asymmetries and shifts. Notably, we find that the driving parameters can be tuned to exactly cancel the initial coherent field amplitude, leading to an effective vacuum limit that recovers the fundamental vacuum Rabi splitting. This provides a clear interpretation of the emission dynamics in terms of the coherent displacement of the cavity field induced by the external drive.

Abstract: Background: Fabry disease (FD) exhibits a spectrum of clinical manifestations ranging from mild to severe, posing a diagnostic challenge, particularly in non-classic subtypes. Genetic testing remains a gold standard for precise diagnosis of FD and is pivotal in genetic counseling. Although conventional approaches such as Sanger sequencing and short-read next-generation sequencing (NGS) have been successfully used to diagnose FD, they often fail to detect deep intronic variants, complex rearrangements, or large deletions or duplications. In contrast, long-read sequencing (LRS) enables comprehensive coverage of intronic and repetitive regions, facilitating precise identification of atypical variants missed by conventional methods. Objective: This case series report two unrelated male patients with clinical, enzymatic, and pathological features consistent with FD, who tested negative for alpha-galactosidase A (GLA) mutations via Sanger sequencing and NGS. LRS, RNA sequencing, quantitative real-time PCR (qRT-PCR), and bioinformatic analysis were employed to investigate potential atypical GLA variants. Results: LRS identified novel non-coding variants in both patients. Patient 1 carried a ~1.7-kb insertion within intron 4, corresponding to part of a long interspersed nuclear element-1, while RNA sequencing revealed two new GLA transcripts. Patient 2 harbored a ~2.5-kb insertion within a SINE-VNTR-Alu retroposon element located in the 5′-untranslated region, with qRT-PCR showing significantly reduced expression of normal GLA transcripts. Conclusions: These findings reveal non-coding variants that contribute to the missing heritability in FD, highlight this genomic region as a priority for future investigation, and demonstrate the potential utility of LRS in diagnostic workflows for unresolved FD cases.

Abstract: 5G systems have delivered on their promise of seamless connectivity and efficiency improvements since their global rollout began in 2020. However, maintaining subscriber identity privacy on the network remains a critical challenge. The 3GPP specifications define numerous identifiers associated with the subscriber and their activity, all of which are critical to the operations of cellular networks. While the introduction of the Subscription Concealed Identifier (SUCI) protects users across the air interface, the 5G Core Network (CN) continues to operate largely on the basis of the Subscription Permanent Identifier (SUPI)--the 5G-equivalent to the IMSI from prior generations--for functions such as authentication, billing, session management, emergency services, and lawful interception. Furthermore, the SUPI relies solely on the transport layer's encryption for protection from malicious observation and tracking of the SUPI across activities. The crucial role of the largely unprotected SUPI and other closely related identifiers creates a high-value target for insider threats, malware campaigns, and data exfiltration, effectively rendering the Mobile Network Operator (MNO) a single point of failure for identity privacy. In this paper, we analyze the architectural vulnerabilities of identity persistence within the CN, challenging the legacy "honest-but-curious" trust model. To quantify the extent of subscriber identities at flight in the CN, we conducted a study of the occurrence of SUPI as a parameter throughout the collection of 5G VNF (Virtual Network Function) API (Application Programming Interface) schemas. Our extensive analysis of the 3GPP specifications for 3GPP Release 18 revealed a total of 5,670 distinct parameter names being used across all API calls, with a total of 22,478 occurrences across the API schema. More importantly, it revealed a highly skewed distribution in which subscriber identity plays a pivotal role. Specifically, the SUPI parameter ranks as the second most frequent field. We found that SUPI occurs both as a direct parameter ("supi") and 43 other parameter names that are all related to the use of SUPI. For these 44 different parameter names we could track a total of 1,531 occurrences. At over 6.8\% of all parameter occurrences, this constitutes a disproportionately large share of total references. We also detail scenarios where subscriber privacy can be compromised by internal actors and review future privacy-preserving frameworks that aim to decouple subscriber identity from network operations. By suggesting a shift towards a zero-trust model for CN architecture and providing subscribers with greater control over their identity management, this work also offers a potential roadmap for mitigating insider threats in current deployments and influencing specific standardization and regulatory requirements for future 6G and Beyond-6G networks.

Abstract: This study investigates how different business model configurations impact the performance of physiotherapy practices within a competitive healthcare environment. Specifically, it examines the influence of business model efficiency and novelty on organizational outcomes, considering the moderating effect of managed competition contracts. Using quantitative analysis of data from Dutch physiotherapy primary healthcare organizations, the research reveals nuanced relationships between business model design and performance, highlighting the importance of contractual factors in shaping these dynamics.

Abstract:

Background: Intensive poultry production systems can act as reservoirs for antibiotic-resistant and multidrug-resistant (MDR) Escherichia coli, posing a public health risk through food and environmental transmission.Methods: This study investigated the genomic characteristics of antibiotic-resistant E. coli isolated from an intensive poultry production system in the uMgungundlovu District, KwaZulu-Natal, South Africa. Chicken litter, wastewater, and floor swab samples were collected over three consecutive production cycles. Putative E. coli isolates were detected using the Colilert-18 system, cultured on eosin methylene blue agar, and genomically confirmed by quantitative PCR (q-PCR) targeting the uidA gene. Whole-genome sequencing was performed using the Illumina MiSeq platform, followed by bioinformatic analyses to assess resistance genes, mobile genetic elements, and phylogenetic relationships. Results: Of 150 isolates, 70 were genomically confirmed as E. coli and resistant to at least one antibiotic, with 74% exhibiting multidrug resistance. Resistance was highest to tetracycline (100%), ampicillin (94%), and trimethoprim-sulfamethoxazole (76%), while ciprofloxacin resistance was rare (3%). Genomic analysis identified multiple antibiotic resistance genes conferring resistance to fluoroquinolones, β-lactams, aminoglycosides, amphenicols, fosfomycin, and sulfonamides, as well as the disinfectant resistance gene qacI. These genes were frequently associated with mobile genetic elements, including plasmids, integrons, transposons, and insertion sequences. Predominant sequence types included ST155, ST48, ST1286, and ST602, with phylogenetic relatedness to poultry-associated isolates from Cameroon, Ghana, Nigeria, and Tanzania, as well as environmental E. coli strains previously identified in South Africa and Ghana. The detection of diverse, mobile MDR E. coli lineages in poultry environments clearly signals a substantial risk for resistance gene dissemination into the food chain and surrounding ecosystems. Immediate attention and intervention are warranted to mitigate public health threats.

Abstract:

Background: Smoking remains a major global public health challenge. Given that smoking often begins in early adolescence, early preventive programs are essential. This study aimed to measure smoking prevalence, assess knowledge and attitudes toward smoking, and evaluate the impact of a school-based smoking intervention program among students aged 12–13 years in Larissa, Greece. Methods: A total of 769 students participated in the study, yielding an overall response rate of 75.5%. All participants’ knowledge, attitudes, and smoking prevalence were assessed at baseline. The intervention group (n = 316) was then exposed to audiovisual and printed materials, and both intervention and control group participants were followed up at three- and twelve-months post-intervention. Multivariable linear mixed-effects models and generalized estimating equations models were used to evaluate the effects of the intervention. Results: Baseline characteristics of the study participants were balanced between groups. A statistically significant stage × group interaction was observed for both outcomes, indicating improvements in smoking-related knowledge and attitudes (p < 0.001) and a reduction in smoking prevalence (p = 0.026). Conclusions: This school-based intervention effectively improved smoking-related knowledge and attitudes and reduced smoking prevalence among participants. These findings support the integration of early prevention programs into school curricula as a potentially effective approach to improving smoking-related outcomes.

Abstract: Large Language Models (LLMs) have demonstrated remarkable capabilities in reasoning tasks, yet their ability to execute long-horizon processes with sustained accuracy remains a fundamental challenge. This survey provides a comprehensive examination of reasoning in LLMs, spanning from foundational prompting techniques to emerging massively decomposed agentic processes. We first establish a taxonomy that categorizes reasoning approaches into three primary paradigms: prompting-based methods including Chain-of-Thought, Tree of Thoughts, and Graph of Thoughts; training-based methods encompassing reinforcement learning from human feedback, process reward models, and self-taught reasoning; and multi-agent systems that leverage decomposition and collaborative error correction. We analyze the persistent error rate problem that prevents LLMs from scaling to extended sequential tasks, where recent experiments demonstrate performance collapse beyond a few hundred dependent steps. We then examine MAKER, a breakthrough framework that achieves over one million LLM steps with zero errors through extreme task decomposition combined with multi-agent voting schemes. Our analysis reveals that massively decomposed agentic processes represent a promising paradigm shift from relying solely on improving individual model capabilities toward orchestrating ensembles of focused microagents. We synthesize empirical findings across major benchmarks including GSM8K, MATH, MMLU, and PlanBench, and identify critical open challenges including compositional generalization, error propagation mitigation, and the computational costs of inference-time scaling. This survey aims to provide researchers and practitioners with a unified perspective on the landscape of LLM reasoning and illuminate pathways toward solving problems at organizational and societal scales.

Abstract:

Hydroxyprogesterone (HP) is a synthetic progestogen widely used in obstetric care, and its potential influence on breast cancer biology has become an emerging area of interest. Despite its clinical use, the molecular mechanisms by which HP affects tumor tissue remain insufficiently explored. In this study, transcriptomic profiling was performed to investigate gene expression changes associated with HP in operable breast cancer. Pre-operative 17-OHPC exposure was associated, in normal adjacent tissue (NAT), with activation of steroid-hormone and lipid/xenobiotic-metabolism programs and crosstalk to PI3K–Akt and NF-κB. In NAT, these pathways showed the largest absolute log2 fold-change (|log2FC|); significance is reported as FDR throughout (e.g., FKBP5↑ with HP). In tumor tissue, the dominant signal reflected tight-junction/apical-junction and ECM-receptor remodeling (e.g., CLDN4↑). We prioritized FKBP5 (HP pharmacodynamics) and CLDN4 (tumor baseline) as the main candidates; TSPO and SGK1 are reported as exploratory. These findings provide mechanistic insight into HP’s molecular effects in breast cancer and suggest potential applications in biomarker perioperative management.

Abstract:

Background/Objectives: Energy availability (EA) is associated with Relative Energy Deficiency in Sport syndrome. This study assessed ΕΑ, body composition, and phase angle (φ) of adolescent artistic gymnasts during a competitive season. Methods: Thirty artistic gymnasts aged 11-14 years participated in the study. Anthropometric data were collected and body mass index (BMI) was assessed using the World Health Organization growth charts. Bioelectrical impedance analysis was performed and diet and physical activity were recorded for three days. Dietary and physical activity records were analyzed to estimate energy intake, total energy expenditure (TEE), and exercise energy expenditure, from which energy balance (EB) and EA were calculated. The 95% confidence ellipses of the impedance (Z) vectors were compared with a reference population using the two-sample Hotelling’s T² test. Correlations between conceptually relevant study variables were examined by Pearson’s or Spearman’s correlation analysis. Statistical significance was set at α = 0.05. Results: All participants were classified within the normal BMI category, except for one classified as overweight. Mean (± SD) fat mass, fat-free mass (FFM), and φ were 16.1 ± 3.4%, 83.9 ± 3.4%, and 6.0 ± 0.6°, respectively. The 95% confidence ellipses of Z vectors differed significantly from the reference population. Energy balance was 32 ± 223 kcal/day and EA was 49.2 ± 11.4 kcal/kg FFM/day. Energy availability was significantly correlated with EB, TEE, and body composition variables. Phase angle was significantly correlated with anthropometric and body composition variables. Conclusions: Adolescent non-elite artistic gymnasts exhibited normal body composition and EA during the competitive season.

Abstract:

Introduction Cutibacterium species, common commensal gram-positive bacteria, present a diagnostic challenge for arthroplasty surgeons. While Cutibacterium infections have been well characterized in shoulder surgery, their presentation and clinical significance in total hip (THA) and total knee arthroplasty (TKA) remain less understood. Methods A retrospective chart review identified patients with positive Cutibacterium cultures following THA or TKA. Demographics, laboratory values, and microbiologic data were collected. Statistical comparisons were performed using t-tests and chi-squared analysis. One-year outcomes were evaluated using the MSIS ORT criteria among patients undergoing further surgical intervention. Results Twenty-nine patients with Cutibacterium-positive cultures were identified (21 THA, 8 TKA); 15 (52%) were polymicrobial. Ten THA patients (47.6%) and seven TKA patients (87.5%) met MSIS criteria for infection. Mean time to culture positivity was similar between THA (6.8 days) and TKA (7.4 days; p = 0.57). Sonication cultures were positive in 24% of THA and 12.5% of TKA cases. Mean ESR was 36.4 mm/h for THA and 51.5 mm/h for TKA (p = 0.21); mean CRP was 35.2 and 36.8 mg/dL, respectively (p = 0.95). Mean synovial cell counts were 27,055 for THA and 22,194 for TKA, with PMN percentages of 68% and 73.9% (p = 0.72, 0.70). Monomicrobial infections demonstrated a mean cell count of 24,143 with 58.9% PMNs, compared to 25,903 and 78.8% in polymicrobial cases. At one year, 72% of patients undergoing subsequent surgery achieved successful outcomes. Higher ASA classification was the only significant predictor of failure (mean 3.0 vs. 2.75). Conclusion Cutibacterium-associated THA and TKA infections often present with delayed culture growth, mild inflammatory markers, and frequent polymicrobial involvement. Most patients experience favorable outcomes following surgical management, though greater medical comorbidity may predict treatment failure.

Abstract:

The concept of individual cellular intelligence reframes cells as dynamic entities endowed with sensory, reactive, adaptive, and memory-like capabilities, enabling them to navigate lifelong metabolic and extrinsic stressors. A likely vital component of this intelligence system are stress-responsive G protein-coupled receptor (GPCR) networks, interconnected by common signaling adaptors. These stress-regulating networks orchestrate the detection, processing, and experience retention of environmental cues, events, and stressors. These networks, along with other sensory mechanisms such as receptor-mediated signaling and DNA damage detection, allow cells to acknowledge and interpret stressors such as oxidative stress or nutrient scarcity. Reactive responses, including autophagy and apoptosis, mitigate immediate damage, while adaptive strategies, such as metabolic rewiring, receptor expression alteration and epigenetic modifications, enhance long-term survival. Cellular experiences that are effectively translated into ‘memories’, both transient and heritable, likely relies on GPCR-induced epigenetic and mitochondrial adaptations, enabling anticipation of future insults. Dysregulation of these processes and networks can drive pathological states, shaping resilience or susceptibility to chronic diseases like cancer, neurodegeneration, and metabolic disorders. Employing molecular evidence, here we underscore the presence of an effective cellular intelligence, supported by multi-level sensory GPCR networks. The quality of this intelligence acts as a critical determinant of somatic health and a promising frontier for therapeutic innovation. Future research leveraging single-cell omics and systems biology may unravel the molecular underpinnings of these capabilities, offering new strategies to prevent or reverse stress-induced pathologies.

Abstract:

One of the most numinous expressions in the gospel is the assertion by Jesus in Matthew 11:11 that amongst those born of women, none is greater than John the Baptist and yet the least in the kingdom is greater than John the Baptist. We show here that the obstacle to understanding the statement lies in the misconception that it is as a monovalent statement of fact rather than in actuality a riddle; the solution to which expresses multivalent realities. In form, Jesus employs the same lexical bauplan of the conundrum couplet as Sampson in his infamous riddle in Judges 14:14. We show that Jesus consistently phrases paedagogic riddles in this guise. The use of the phrase “of women born” to describe the pool of comparators necessarily includes Jesus and his mother, Mary. Hence continent in the riddle are two elements. Firstly is the question as to how John can be greater than Jesus or Mary. Since Jesus is making a comparison between those inside and outside of the Kingdom, the only possible solution to this moiety of the riddle is that Jesus and Mary are within the Kingdom. This re-affirms the Kingship of Jesus and Queenship of the Mary. By definition the King must be in the Kingdom. However it is the second limb that is even more instructive. The second question is why John is not in the Kingdom. Baptism is the means to enter the Kingdom. As Jesus himself confirms to Nicodemus in John 3:5, one must be baptised by Water and the Holy Spirit. St Thomas Aquinas explains that this is the means of removing the obstacles to the Kingdom. He adumbrates the Catholic Catechism. Both disclose the reality that original sin and personal sin are obstacles to entry into the Kingdom. Some traditions assert John the Baptist was “baptised” during the Visitation, but their remains, nonetheless, the impediment of personal sin. The only possible sequitur is that if Mary is in the Kingdom, before Jesus’ sacrifice and resurrection, she must have been born without original sin and must never have sinned, via the grace of God. The only other alternative is that she is outside of the Kingdom and not of equivalent greatness to John the Baptist, who said of himself he was not fit to untie of sandals of Jesus; but we must conclude is greater than she who was chosen to carry and nurture Jesus himself. This contradiction must be rejected. This puzzle, which compares of all those born of women, John the Baptist and those in the Kingdom, is in some ways a prolegomenon or pre-articulation of the words of our Lady to Saint Bernadette at Lourdes in 1858 that she is the Immaculate Conception and pre-affirmation of the dogma of the Catholic Church in 1854.

Abstract: The aim of this study was to investigate the biochemical properties of free and immobilized mushroom tyrosinase (EC 1. 14. 18. 1) entrapped in calcium alginate beads for phenol removal in batch system. Tyrosinase activity was determined spectrophotometrically at 400 nm under optimal conditions. The effects of key operational parameters on phenol oxidation kinetics were evaluated for both enzyme systems. The Michaelis–Menten constant (Km) of the immobilized enzyme (1.04 mM) was approximately twice that of the free enzyme (0.56 mM), while its maximum reaction velocity (Vmax = 139.02 EU) decreased by nearly thirtyfold (Vmax = 5.91 EU). Immobilization also shifted the optimal pH of the enzyme to pH 5.6. Optimum temperature and the activation energy for phenol oxidation were determined as 55°C and 50.4 kJ/mol for immobilized tyrosinase, whereas, 45°C and 39.5 kJ/mol for the free enzyme. The highest activity was obtained with alginate beads of 3.4 mm diameter, and the immobilized preparation exhibited enhanced operational stability, retaining totally its initial activity after 5 reuse cycles. Overall, these findings suggest that mushroom tyrosinase immobilized in alginate beads is a promising system for phenol removal from wastewater.

Abstract: Electricity trading is a critical revenue source for South African municipalities, enabling cross-subsidisation of basic services, debt repayment, and infrastructure financing, which is essential for sustainable municipal operations. Nevertheless, municipal electricity utilities consistently experience variances between budgeted and actual financial performances due to increasing Eskom bulk tariffs, technical and non-technical losses, a degrading distribution system, billing malpractices, and governance breakdown, thereby threatening service delivery sustainability. This paper examines the financial performance of four major distributors—City of Ekurhuleni, City of Cape Town, City Power (Johannesburg), and City of Tshwane—using a mixed documentary research approach, ensuring comprehensive sectoral analysis. Data sources include audited municipal financial statements, National Energy Regulator of South Africa (NERSA) tariff materials, Auditor-General findings, and national electricity statistics, supplemented by secondary literature on distribution losses and utility governance as well as international best practices. Key performance measures point out that an increase in bulk electricity cost and restricted variations in tariffs have enhanced trading limits, electricity theft, meter tampering, and billing inaccuracies, leading to massive revenue leakages, significantly undermining financial stability. The lack of investment in the maintenance of assets also increases such long-term costs. The paper recommends a set of five strategic interventions to be implemented, such as better revenue management, non-technical loss reduction, recovery of the infrastructure that is ring-fenced, transparent cost-reflective tariffs, and governance and institutional controls. A sequenced implementation framework entails the short-term protection of revenue, the medium-term deployment of smart meters, and the long-term reforms of assets. The findings emphasise that sustainable improvement requires integrating operational reform, technological advancement, financial discipline, and governance enhancement.

Abstract: We demonstrate that the approach to the balance manifold dynamically suppresses curvature contributions, yielding an effectively flat universe without requiring fine-tuned initial conditions or a turning point in the evolution. Inflation corresponds to a regime of entropy imbalance along the scale-flow trajectory, and its termination occurs naturally as the system reaches balance, without the need for engineered exit mechanisms, additional fields, or potential features. While the full mathematical structure of this result is developed within Newell’s stochastic framework, its cosmological interpretation is most transparently understood through the logarithmic gauge mapping inherent to the entropy-controlled evolution. This establishes the entropy clock as the minimal and physically natural description of early-universe dynamics in the Forced GUT setting. We show that within Newell’s stochastic Forced Grand Unification (Forced GUT) framework, accelerated expansion, spatial flatness, and exit from the inflationary regime arise as structural consequences of entropy-driven scale flow rather than from tuned dynamics or engineered model ingredients. The framework is governed by a stochastic controller whose natural evolution parameter is a logarithmic renormalization variable, σ=ln⁡(μ/μc), describing relaxation toward an entropy-balance (unification) manifold. In this formulation, the logarithmic growth of the scale factor, N=∫Hdt=ln⁡(af/ai), is shown to be purely kinematic, following directly from H=a˙/a, while the physical evolution is controlled by flow in σ.Moreover, in the high-energy limit, the relevant evolution parameter is logarithmic in scale and does not require dynamical normalization to be well-defined.

Abstract: In freeform optical metrology, wavefront fitting over non-circular apertures is hindered by the loss of Zernike polynomial orthogonality and severe sampling grid distortion inherent in standard conformal mappings. To address the resulting numerical instability and fitting bias, we propose a unified framework curve shortening flow (CSF)-guided progressive quasi-conformal mapping (CSF-QCM), which integrates geometric boundary evolution with topology-aware parameterization. CSF-QCM first smooths complex boundaries via curve-shortening flow, then solves a sparse Laplacian system for harmonic interior coordinates, thereby establishing a stable diffeomorphism between physical and canonical domains. For doubly connected apertures, it preserves topology by computing the conformal modulus via Dirichlet energy minimization and simultaneously mapping both boundaries. Benchmarked against state-of-the-art methods (e.g., Fornberg, Schwarz-Christoffel and Ricci flow) on representative irregular apertures, CSF-QCM suppresses area distortion and restores discrete orthogonality of the Zernike basis, reducing the Gram matrix condition number from >900 to < 8. This enables high-precision reconstruction with RMS residuals as low as $3\times10^{-3}\lambda$ and up to 92\% lower fitting errors than baselines. The framework provides a unified, computationally efficient, and numerically stable solution for wavefront reconstruction in complex off-axis and freeform optical systems.