Abstract:

Background/Objectives: Sarcopenia, obesity, and sarcopenic obesity (SO) are common in older adults and may be associated with functional limitations in basic (ADL) and instrumental (IADL) activities of daily living. This study aimed to evaluate the association between body composition phenotypes and ADL/IADL limitations among older adults. Methods: A cross-sectional study included 440 community-dwelling adults aged ≥60 years (281 women, 159 men; mean age 74.7 ± 7.8 years). Sarcopenia was diagnosed according to EWGSOP2 criteria, obesity was defined as percent body fat >42% in women and >30% in men, and SO was classified based on the ESPEN/EASO recommendations. Participants without obesity or sarcopenia were categorized as ‘normal’ phenotype. Functional status was evaluated using the Katz and Lawton scales, with limitations defined as ADL ≤5 and IADL ≤26 points, respectively. Multivariate logistic regression analysis was performed to determine factors associated with ADL and IADL limitations. Results: Over half of the participants (57.1%) had abnormal body composition: 31.6% obesity, 11.4% sarcopenia, and 13.2% SO. SO was associated with a nearly threefold higher risk of ADL limitations (OR = 2.86; p = 0.003) and a 3.7-fold higher risk of IADL limitations (OR = 3.68; p < 0.001) compared to the normal phenotype. Sarcopenia was associated with IADL limitations in the unadjusted model (OR = 2.44; p = 0.010). Independent predictors of ADL and IADL limitations included reduced muscle strength, a higher number of chronic diseases, and a worse nutritional status. Conclusions SO was linked to higher risk of both ADL and IADL limitations, while sarcopenia was associated only with IADL deficits. Obesity severity may be relevant, but its impact on daily functioning in older adults requires further study.

Abstract:

Introduction: We hypothesised that vitamin K (VK) may have potential effect on insulin secretion and FGF-19 and FGF 21 may modulate the vitamin K/insulin pathway. We investigated whether vitamin K1 or K2 supplementation for 18 months can affect insulin secretion and FGF19 and FGF21 production. Methods: We conducted exploratory analyses using stored samples from an 18-month randomised double-blind placebo controlled trial of VK1 (1 mg/day) or VK2 (menaquinone-4, MK4 45 mg/day)) in 105 post-menopausal women with osteoporosis (PMO) aged between 55-85 years which looked at the effect of VK supplementation on bone mineral density. In the current study, plasma insulin (primary outcome), FGF19 and FGF21 (secondary outcomes) were measured at baseline, 6 and 18 months. Results: Plasma insulin at 6 and 18 months increased significantly compared to baseline value in both treatment arms (VK1 and VK2 (MK4) ) (Median Insulin [IQR] VK1: baseline : 41.2 [29.3, 54.3] pmol/L, 6 months: 59.7 [37.8, 89.5] pmol/L p<0.001, 18 months: 54.3[43.5, 73] pmol/L (p= 0.05), VK2 (MK4) arm (Median Insulin [IQR]: baseline: 44.3[30.6, 60.9], 6 months: 63.2[43.5, 97] pmol/L p=0.011, 18 months: 54.2[40.7, 103.5] pmol/L p=0.05) in within-group analyses. No significant changes were seen in the placebo group. Circulating FGF21 tended to be higher at 6 months (p=0.045) compared to baseline following VK2 (MK4) only. Conclusions: Improving VK status in post-menopausal women may improve insulin secretion. Our data suggest that MK4’s effect on the insulin axis may be mediated, at least in part, by FGF21. Further studies are needed for confirmation.

Abstract: I propose a resource-sensitive theory of truth grounded in the structure of linear logic. On this view, a proposition counts as true for an agent only when it can be derived from the finite informational resources the agent currently possesses such as data, concepts, tools or premises, through a form of inference that tracks how those resources are used. Rather than treating truth as a static or purely metaphysical attribute, my account emphasizes that truth emerges within the constraints of actual reasoning. A key distinction is drawn between local derivability, which concerns what an agent can establish with the resources immediately available and global derivability, which reflects what could be established under idealized conditions. This allows my approach to preserve objectivity while acknowledging that access to truth is often limited and uneven. The framework yields a new perspective on classical epistemological issues, including the nature of justification and the structure of rational inference, while clarifying how inferential breakdowns can occur when the resources supporting a reasoning process are incomplete or unreliable. It also provides a natural lens for examining truth in science, legal reasoning and artificial intelligence, domains in which information is finite, traceable and central to responsible decision-making.

Abstract:

Previous research showed that a strain of Leuconostoc mesenteroides, isolated from goat’s raw milk cheese, was effective in slowing down the growth and reducing the maximum concentration of L. monocytogenes when evaluated in a milk model; and, furthermore, that the extent of inhibition was dependent on the milk initial pH. The objectives of this study were: (1) to determine whether the growth of L. monocytogenes in goat’s pasteurized milk cheese during maturation could be approximated from growth data obtained in the milk model medium, either in monoculture or in coculture with L. mesenteroides; and if so; (2) to model a milk-to-cheese conversion factor (Cf) for L. monocytogenes growth rate. Challenge tests were conducted by inoculating L. monocytogenes in monoculture and in coculture with L. mesenteroides in goat’s pasteurized milk adjusted at initial pH levels of 5.5, 6.0 and 6.5. The process of cheesemaking went on, and cheeses were ripened at 12 ºC during 12 days. Each experimental growth curve was adjusted to a pH-driven dynamic model where the microbial maximum growth rate is a function of pH. As observed in the milk model medium, in coculture with L. mesenteroides, the optimum growth rate (μ_opt) of L. monocytogenes in maturing cheese was affected by the initial pH of milk: the lowest rate of 0.863 ± 0.042 day^-1 was obtained at the initial pH 5.5, in comparison to 1.239 ± 0.208 and 1.038 ± 0.308 day-¹ at pH 6.0 and 6.5, respectively. Regardless of the milk initial pH, L. mesenteroides did not reduce the maximum load of L. monocytogenes in maturing cheeses, as it did in the milk medium. By contrary, at the milk initial pH of 5.5, 6.0, and 6.5, L. mesenteroides was able to decrease, on average, 2.2-fold, 1.5-fold and 1.9-fold the μ_opt of L. monocytogenes in both milk medium and cheese, without significant differences between matrices. Following such validation in goat’s cheese, the square-root of milk-to-cheese Cf for L. monocytogenes was estimated as 0.751 (SE=0.0108), and type of culture (monoculture, coculture) was not found to affect Cf (p=0.320). In conclusion, this work validated pre-acidification of milk as an efficient strategy that, when combined with the use of a protective culture, can synergically enhance the control of L. monocytogenes in cheese.

Abstract: Radar signal coherent integration technology is a critical method to improve the performance of detection systems. However, existing techniques face challenges regarding real-time performance and the flexibility of multi-pulse coherent accumulation. In this paper, a dynamically configurable multi-pulse multi-frame real-time coherent integration system based on FPGA is designed and implemented, and the dynamic configuration of the number of pulses and the number of frames stored for each pulse is realized through the host computer. The experimental results show that the output signal delay of coherent integration is 33 microseconds at 40 pulses, and the energy gain reaches 16 dB at 40 pulses, which provides a dynamically configurable hardware platform and solution for real-time coherent integration of high-frame-count, multi-pulse radar signals.

Abstract: This study proposes an integrated agility assessment system that combines Millimeter-Wave (MMW) radar, Ultra-Wideband (UWB) ranging, and Mixed Reality (MR) technologies to quantitatively evaluate athlete performance with high accuracy. The system utilizes the fine motion-tracking capability of MMW radar and the immersive real-time visualization provided by MR to ensure reliable operation under low-light conditions and multi-object occlusion, thereby enabling precise measurement of mobility, reaction time, and movement distance.To address the challenge of player identification during doubles testing, a one-to-one UWB configuration was adopted, in which each base station was paired with a wearable tag to distinguish individual athletes. UWB identification was not required during single-player tests. The experimental protocol included three specialized agility assessments—Table Tennis Agility Test I (TTAT I), Table Tennis Doubles Agility Test II (TTAT II), and the Agility T-Test (ATT)—conducted with more than 80 table tennis players of different technical levels (80% male and 20% female). Each athlete completed two sets of two trials to ensure measurement consistency and data stability.Experimental results demonstrated that the proposed system effectively captured displacement trajectories, movement speed, and reaction time. The MMW radar achieved an average measurement error of less than 10%, and the overall classification model attained an accuracy of 91%, confirming the reliability and robustness of the integrated sensing pipeline. Beyond local storage and MR-based live visualization, the system also supports cloud-based data uploading for graphical analysis and enables MR content to be mirrored on connected computer displays. This feature allows coaches to monitor performance in real time and provide immediate feedback.By integrating the environmental adaptability of MMW radar, the real-time visualization capability of MR, UWB-assisted athlete identification, and cloud-based data management, the proposed system demonstrates strong potential for professional sports training, technical diagnostics, and tactical optimization. It delivers timely and accurate performance metrics and contributes to the advancement of data-driven sports science applications.

Abstract: Current management strategies for sorghum aphids heavily rely on indiscriminate chemical application, leading to severe environmental consequences and impacting food safety. While precision spraying offers a viable remediation for pesticide overuse, its effectiveness depends on accurate pest location and classification. To address the critical challenge of segmenting small, swarming aphids in complex field environments, we propose FESW-UNet, a dual-domain attention network that integrates Fourier-enhanced attention, spatial attention, and wavelet-based downsampling into a UNet backbone. We introduce an Efficient Multi-scale Aggregation (EMA) module between the encoder and decoder to improve global context perception, allowing the model to better capture relationships between global and local features in the field. In the feature extraction stage, we embed a Similarity-Aware Activation module (SimAM) to target key infestation regions while suppressing background noise, thereby enhancing pixel-level discrimination. Furthermore, we replace conventional downsampling with Haar Wavelet Decomposition (HWD) to reduce resolution while preserving structural edge details. Finally, a Fourier-enhanced attention module (FEAM) is added to the skip-connection layers. By using complex-valued weights to regulate frequency-domain features, FEAM fuses global low-frequency structures with local high-frequency details, improving feature representation diversity. Experiments on the Aphid Cluster Segmentation dataset show that FESW-UNet outperforms other models, achieving an mIoU of 68.76% and mPA of 78.19%. The model also demonstrated strong adaptability on the AphidSeg-Sorghum dataset, reaching an mIoU of 81.22% and mPA of 87.97%. The proposed method provides an efficient and feasible technical solution for monitoring and controlling sorghum aphids via image segmentation and demonstrates broad application potential.

Abstract:

This study empirically investigates the impact of both the level and risk of cash dividend distributions on the stock value of companies listed on the Saudi Stock Exchange (Tadawul). Utilizing a proportional stratified random sample of 120 companies across 21 sectors over the period 2020-2024, the research employs third-degree polynomial regression models to analyze complex, non-linear relationships. The findings reveal a significant cubic relationship, identifying an optimal dividend per share of 5.91 SAR that maximizes stock price. Furthermore, dividend volatility (risk) exhibits an inverted S-shaped relationship with price, with an optimal standard deviation of 5.04 SAR, indicating that the market rewards a dynamically stable payout policy. The study also uncovers strong sectoral effects, with Telecommunication, Health Care, and Energy sectors commanding significant valuation premiums, while Real Estate and Financial Services trade at discounts. The results robustly confirm that both dividend level and stability are critical, sector-dependent determinants of firm value in the Saudi market. These insights provide valuable guidance for corporate dividend strategy, investment decision-making, and policy formulation within the context of Saudi Vision 2030.

Abstract: The H5N1 subtype of highly pathogenic avian influenza (HPAI) poses a major zoonotic threat due to its high fatality rate and capacity for cross species transmission. In early 2025, Argentina detected a novel triple reassortant A(H5N1) virus in Chaco Province, combining Eurasian, North American, and South American lineage segments. Genomic analyses of subsequent outbreaks in Buenos Aires and Entre Ríos confirmed persistence of this reassortant and additional HA substitutions (T204K, P251S) potentially linked to increased mammalian receptor affinity. Although PB2 sequences lacked canonical mammalian-adaptive markers (E627K, Q591K, D701N), all contained I292M, a mutation associated with human adaptation. Phylogenetic analyses revealed distinct genotypes and increasing divergence. These findings indicate ongoing viral evolution and adaptation within Argentina, emphasizing the urgent need for sustained genomic surveillance, timely data sharing, and integrated One Health strategies to mitigate zoonotic and socioeconomic risks associated with H5N1 spread in South America.

Abstract: Fungal endophytes have emerged as a promising source of bioactive compounds with potent antifungal properties for plant disease management. This study aimed to isolate and characterize fungal endophytes from Antillean avocado (Persea americana var. ameri-cana) trees in the Colombian Caribbean, capable of producing bio-fungicide metabolites against Fusarium solani and Fusarium equiseti. For this, dual-culture assays, liquid-state fermentation of endophytic isolates, and metabolite extractions were conducted. From 88 isolates recovered from leaves and roots, those classified within the Diaporthe genus ex-hibited the most significant antifungal activity. Their organic extracts displayed median inhibitory concentrations (IC₅₀) approaching 200 μg/mL. To investigate the mechanism of action, in silico studies targeting Chitin Synthase (CS) were performed, including homolo-gy models of the pathogens' CS generated using Robetta, followed by molecular docking with Vina, and interaction fingerprint similarity analysis of 15 antifungal metabolites produced by Diaporthe species using PROLIF. A consensus scoring strategy identified di-aporxanthone A (12) and diaporxanthone B (13) as the most promising candidates, achieving scores up to 0.73 against F. equiseti, comparable to the control Nikkomycin Z (0.82). These results suggest that Antillean avocado endophytes produce bioactive metab-olites that may inhibit fungal cell wall synthesis, offering a sustainable alternative for disease management.

Abstract: What does “Big Bang” actually mean? What was the origin of these two words? It has often been said that the expression “Big Bang” began as an insult. Even if this were true, it would be just an irrelevant part of the whole issue. There are many more as-pects hidden under this name, and which are seldom explained. They will be discussed in this work. In order to frame the analysis, help will be sought from the highly au-thoritative voices of two exceptional writers: William Shakespeare and Umberto Eco. Both Shakespeare and Eco have explored the tension existing between words and the realities they name. With the conclusion that names are, in general, just labels, simple stickers put to identify things. And this includes those given to great theorems or spectacular discoveries. Not even “Pythagoras’ theorem” was discovered by Pythago-ras, as is now well-known. Stigler's law of eponymy is recalled to further substantiate those statements. These points will be at the heart of the investigation carried out here, concerning the very important concept of “Big Bang”. Everybody thinks to know what “the Big Bang” is, but only very few do know it, in fact. When Fred Hoyle first pro-nounced these two words together, on a BBC radio program, listeners were actually left with the false image that Hoyle was trying to destroy. That is, the tremendous ex-plosion of Lemaître’s primeval atom (or cosmic egg), which scattered all its enormous matter and energy content throughout the rest of the Universe. This image is abso-lutely wrong! As will be concluded, today the label “Big Bang” is used in several dif-ferent contexts: (a) the Big Bang Singularity; (b) as the equivalent of cosmic inflation; (c) speaking of the Big Bang cosmological model; (d) to name a very popular TV pro-gram; and more.

Abstract:

In endemic regions where simultaneous larval tick bites are common, early species-level information obtained from eschar lesions can meaningfully change pre-symptomatic triage. We report a 78-year-old woman found after ~24 hours of wandering with multiple clustered eschars on the legs and attached ticks on the trunk. PCR and Sanger sequencing of two removed ticks and ten representative eschars identified Amblyomma testudinarium in all samples. Because A. testudinarium is a known vector of severe fever with thrombocytopenia syndrome (SFTS) virus but not of Rickettsia japonica, we deprioritized Japanese spotted fever and focused targeted monitoring on early SFTS features. The patient remained asymptomatic and was transferred to long-term care. This case illustrates that, particularly in high-incidence settings with numerous bite sites, selective PCR of representative eschars provides a rapid and resource-sparing means to infer vector species and tailor risk assessment before symptom onset. Emphasizing eschar-based species identification in endemic areas can concentrate testing where pretest probability is highest, streamline surveillance, and support shared decision-making in frontline practice.

Abstract:

Background/Objectives: Biomarker-based prevention is rapidly expanding, driven by advances in molecular diagnostics, genetic profiling, and commercial direct-to-consumer (DTC) testing. General practitioners (GPs) increasingly encounter biomarker results of uncertain relevance, often introduced outside the guideline frameworks. This creates new challenges in interpretation, communication, and equitable resource use in primary care. Methods: This narrative review synthesizes evidence from population-based studies, guideline frameworks, consensus statements, and communication research to evaluate the predictive value, limitations, and real-world implications of biomarkers in asymptomatic adults. Attention is given to polygenic risk scores, DTC genetic tests, neurodegenerative and cardiovascular biomarkers, and emerging multi-omics and aging markers. Results: Several biomarkers, including high-sensitivity cardiac troponins, N-terminal pro–B-type natriuretic peptide, lipoprotein(a), coronary artery calcium scoring, and plasma p-tau species, showed robust predictive validity. However, many widely marketed biomarkers lack evidence of clinical utility, offer limited actionable benefits, or perform poorly in primary care populations. Unintended consequences, such as overdiagnosis, false positives, psychological distress, diagnostic cascades, and widening inequities, are well documented. Patients often misinterpret unvalidated biomarker results, whereas DTC testing amplifies demand without providing adequate counseling or follow-up. Conclusions: Only a minority of biomarkers currently meet the thresholds of analytical validity, clinical validity, and clinical utility required for preventive use in general practices. GPs play a critical role in contextualizing biomarker results, guiding shared decision-making, and mitigating potential harm. The responsible integration of biomarkers into preventive medicine requires clear communication, strong ethical safeguards, robust evidence, and system-level support for equitable, patient-centered care.

Abstract: In this paper, we propose an alternative kernel estimator for the regression operator of a scalar response variable S given a functional random variable T that takes values in a semi-metric space. The new estimator is constructed through the minimization of the least absolute relative error (LARE). The latter is characterized by its ability to provide a more balanced and scale-invariant measure of prediction accuracy compared to traditional standard absolute or squared error criterion. The LARE is an appropriate tool for reducing the influence of extremely large or small response values, enhancing robustness against heteroscedasticity or/and outliers. This feature makes LARE suitable for functional or high-dimensional data, where variations in scale are common. The high feasibility and strong performance of the proposed estimator is theoretically supported by establishing its stochastic consistency. The latter is derived with precision of the converge rate under mild regularity conditions. The ease implementation and the stability of the estimator are justified by simulation studies and an empirical application to near-infrared (NIR) spectrometry data. Of course the to explore the functional architecture of this data, we employ random matrix theory (RMT) which is a principal analytical tool of econophysics.

Abstract: Food adulteration has become one of Bangladesh’s most urgent public health and governance challenges, affecting everything from everyday groceries to street foods. This review draws on secondary research to examine why the problem persists, revealing a system driven by profit incentives, weak oversight, and poor consumer awareness. Adulteration thrives at wholesale and processing stages, where harmful chemicals, dyes, and fillers are routinely introduced into essential foods, leading to rising rates of poisoning, chronic illness, and long-term organ damage. The crisis also undermines economic stability, erodes public trust, and disproportionately harms low-income communities. Although Bangladesh has established regulatory structures like the BFSA, persistent gaps in funding, laboratory capacity, coordination, and enforcement limit their effectiveness. The study proposes a path forward anchored in stronger institutions, specialized courts, modern testing and traceability technologies, farm-to-fork certification, and greater public transparency. Meaningful reform requires collective responsibility across government, industry, and society.

Abstract: Urban Green Space Per Capita (UGSPC) is one of the oldest and most widely applied indicators in urban planning, providing a measure of green areas in relation to the population size. Despite its century-long application and decades of research, no global systematic review has previously synthesized how UGSPC has been applied, interpreted, and evolved across different contexts. This study aims to fill that gap by conducting the first comprehensive systematic review, following PRISMA guidelines, examining the usage, trends, and effectiveness of UGSPC in both developed and developing countries. Thematic analysis revealed that most studies were published in journals focused on sustainability and environmental science. The results show a surge in publications following the COVID-19 pandemic, reflecting a growing recognition of the importance of urban green spaces for public health and livability. Moreover, 67% of the studies were conducted in developing countries, while 30% of the publications were in developed countries. Higher UGSPC values are generally found in developed cities; however, this was not a rule. Time series studies showed a decline in UGSPC in some developed and developing countries, influenced by factors such as population density, urbanization stage, climate, and economic conditions. Although UGSPC is widely used, most municipalities typically develop their plans based on this measurement. 95% of the included research incorporated additional measurements, including accessibility, social equity, spatial patterns, ecological services, ecosystem benefits, and human health. This study suggests that UGSPC is still used as an indicator in urban planning and policy and integrating it with other indicators can serve as contemporary indicators to capture better equity, functionality, and sustainability in urban environments.

Abstract: This paper introduces the Sextuple Helix Innovation Model as an extension of the Quintuple Helix Innovation Model by Carayannis and Campbell. It considers the understanding of generative AI (GenAI) as a sixth helix of knowledge production in sustainable innovation ecosystems. Accordingly, the knowledge economy of GenAI will be discussed in the context of innovation processes of cultural and creative industries. While GenAI is largely described in social discourses as a tool that potentially replaces human creativity and thus destroys jobs, this paper discusses GenAI as an entity with a specific knowledge economy that contributes to creative innovation processes in exchange with the five established helices of science, politics, economy, the media- and culture-based public and the natural environment of societies. With the help of a scoping review, a comprehensive evaluation of academic literature from the fields of creative industries, cultural policy, and innovation research, based on a constructivist epistemological approach and knowledge economy theory, confirmed that the positioning of GenAI as an epistemic actor in the Sextuple Helix Innovation Model reframes and redefines discourses beyond the prevailing narratives of disruption and regulation.

Abstract: Background: Squamous cell carcinoma of the skin (SCC) is the second most common neoplasm in humans and the most frequent in Brazil (80% in the head and neck region, 20% mortality). Brazil is a world leader in organ transplants (more than 30,000 transplants in 2019). The risk of transplant patients (Tx) developing SCC is 65-250 times higher, with deeper infiltration, advanced stage, higher local recurrence, occult metastases and worse survival. Objective: To investigate the prognostic factors of locally advanced cutaneous squamous cell carcinoma (LASCC) of the head and neck region in transplant patients. Methods:16-year retrospective, single-center series of patients with LASCC in the head and neck region who underwent surgical treatment. Were analyzed: clinical and Tx data, clinical/pathological stage, surgical treatment, parotid/regional and distant metastases, recurrence and survival. Results: 156 patients were included: 69.2% women, 65.3 years; mean primary size: 4.24 cm, 66% T3/T4 tumors, 71% grade 2/3 differentiation, 20.5% transplant recipients, follow-up: 33.6 months. Most affected regions: malar/nasal (28.8%), auricular (19.2%). Surgeries: wide resection with reconstruction (58.9%), exenteration (14.1%), temporalectomy (11.5%). Univariate analysis: Recurrence: immunosuppressor drugs (p=0.009), transplanted (p=0.006), compromised margin (p=0.049), Mortality: immunosuppression (p=0.028), Total Resection and reconstruction (p=0.013), Stage(8ed) III-IV (p&lt;0.001), compromised margin (p&lt;0.001), neck metastasis with extranodal extension (p=0.018). Multivariate analysis: Recurrence: Transplanted HR:3.69 (p&lt;0.001), Neck metastasis extranodal extension HR:5.41 (p&lt;0.001), Evolution to Distant metastasis HR:5.27 (p&lt;0.001); Mortality: Neck metastasis extranodal extension HR:1.94, (p=0.032), Compromised Margins HR:1.87 (p=0.001), Main Surgical Procedures: Temporalectomy HR:2.83 (p=0.007); Major Rhinectomy HR:2.47 (p=0.005); Worst Overall Survival: Tx compared to NonTx (p=0.069), Worst Survival with Recurrence: Tx compared to NonTx (p=0.005). Conclusions: The LASCC and Transplanted (immunosuppressed) group present low survival, worse prognosis, high risk of recurrence and mortality outcome, formulation of specific guidelines to standardize treatment and predict outcomes in this population are strictly necessary.

Abstract: Entrepreneurship in South Africa extends beyond conventional sustainable development, incorporating several viewpoints that mirror the nation's distinct socio-economic and cultural context. This study examines several perspectives, emphasising the interaction of technical, artistic, socio-economic, historical, and institutional elements in influencing entrepreneurial activity. Technological advancements and management innovations create new opportunities for small and medium-sized enterprises (SMEs), while cultural diversity fosters creativity and innovation. Socio-economic issues, such as elevated unemployment rates and historical disparities, necessitate targeted entrepreneurial activities to promote job creation and community empowerment. This study elucidates how entrepreneurship in South Africa can extend beyond sustainable development, thereby fostering economic growth and social transformation by examining various perspectives. The qualitative study utilised original data collected from selected participants through interviews. The data was analysed through a thematic data analysis, and results show that entrepreneurship in South Africa is a dynamic and complex phenomenon that transcends the conventional emphasis on sustainable development. This study elucidates the critical influence of technology breakthroughs, cultural diversity, socio-economic issues, and historical disparities on entrepreneurial activity. These elements collectively enhance the resilience, inventiveness, and innovation of South African entrepreneurs.

Abstract: The advance and delay of the rainy season is among the most frequently cited effects of climate change by Ecuadorian farmers. However, its assessment is not feasible using the conventional indicators recommended by the standardized indices of the Expert Team on Climate Change Detection and Indices (ETCCDI). This study aims to analyze such advances and delays through harmonic analysis in Tungurahua, a predominantly agricultural province in the Tropical Central Andes, where in-situ data are scarce. Daily in-situ data from five meteorological stations were used, including precipitation, maximum, and minimum temperature records spanning 39 to 68 years. The study involved an analysis of the region’s climatology, climate change indices, and harmonic analysis using Cross Wavelet Transform (XWT) and Wavelet Coherence Transform (WCT) to identify seasonal patterns and their variability (advance or delay) by comparing historical and recent time series, and Kriggin for regionalization. The year 2000 was used as a breakpoint for comparing past and present trends. Results show a generalized increase in both minimum and maximum temperatures. In the case of extreme rainfall events, no significant changes were detected. Harmonic analysis was found to be sensitive to missing data. Furthermore, the observed advances and delays in seasonality were not statistically significant and appeared to be more closely related to the geographic location of the stations than to temporal shifts.