Practical Limitations Research Articles

Optimal control of axial dispersion tubular reactors with recycle: Addressing state‐delay through transport PDEs

AbstractThe optimal control of an axial tubular reactor with a recycle stream is addressed as a key type of setting for distributed parameter systems in chemical engineering. The intrinsic time delay from the recycle process, thus far overlooked in relevant literature, is modelled as a transport partial differential equation (PDE), resulting in a system of coupled parabolic and hyperbolic PDEs. Utilizing Danckwerts boundary conditions, the reactor is boundary‐controlled with the control input at the inlet. A continuous‐time optimal linear quadratic regulator is developed to stabilize the infinite‐dimensional system, employing a late lumping approach in order to preserve the properties of the original infinite dimensional system in controller design. The full‐state feedback regulator is designed by solving the Operator Riccati Equation (ORE), leveraging the system's Riesz‐spectral properties. To address practical limitations of full‐state feedback, a Luenberger observer is also proposed, enabling state reconstruction from boundary measurements. Numerical simulations are conducted to evaluate the proposed control strategies. The results demonstrate that the full‐state feedback regulator effectively stabilizes the system. A comparison is made between two configurations where different numbers of eigenmodes were selected to design the controller. The observer‐based regulator also stabilizes the system successfully using merely output measurements, effectively overcoming the challenge of limited state access.

Real-world outcomes of maintenance therapy post-autologous stem cell transplantation in newly diagnosed multiple myeloma

BackgroundIn the Republic of Korea, only lenalidomide, bortezomib, ixazomib, and thalidomide monotherapy are available as maintenance therapy post-autologous stem cell transplantation (ASCT).MethodsTo determine whether maintenance therapy confers a survival benefit in the real world, we compared treatment outcomes according to the use and type of maintenance therapy in patients who underwent ASCT following frontline therapy with the triplet regimen of bortezomib, thalidomide, and dexamethasone for newly diagnosed multiple myeloma in 15 nationwide centers.ResultsA total of 512 patients were analyzed (no-maintenance group, n = 359, and maintenance group, n = 153 patients). Among those receiving maintenance therapy, 104 (68%) received thalidomide, 33 (21%) lenalidomide, and 16 (10%) bortezomib or ixazomib. The median progression-free survival (PFS) from the time of ASCT was 26.4 and 44.1 months in the no-maintenance and maintenance groups, respectively. In the multivariate analysis, the use of maintenance therapy was significantly associated with better PFS. After adjustment for the type and duration of maintenance therapy, the use of bortezomib or ixazomib was associated with better PFS than other drugs. Longer duration of therapy was associated with improved PFS. No statistically significant difference was observed in overall survival and secondary malignancy rates by use or type of maintenance.ConclusionDespite practical limitations, maintenance therapy after ASCT demonstrated a gain in PFS in the real world, and there was no clear increase in the risk of secondary malignancy. Therefore, it may be prudent to consider implementing maintenance therapy in a feasible manner.

How can blue biomass contribute to a more sustainable built environment?

Abstract The implementation of a circular bioeconomy in the construction industry is a necessary strategy to tackle our global climate crisis. With any single solution having practical and environmental limitations, it is clear that creating a material palette of renewable biogenic building materials will expands access to bio-based construction. Photosynthetic organisms, including marine biomass such as seaweeds and microalgae, utilise solar energy to sequester CO₂, producing biomolecules that can be harnessed for a variety of biomaterials. Organisms such as mussels and oysters mineralise carbon into shells that are often dis-carded as residues. These second and third-generation feedstocks present an opportunity to decarbonise the construction industry. However, we need to better understand how to renew our relationship to this resource in a sustainable manner. This question seeks to explore how we can design and fabricate with, and for, blue biomass materials

Optimal limits of continuously monitored thermometers and their Hamiltonian structure

We investigate the fundamental and practical precision limits of thermometry in bosonic and fermionic environments by coupling an N-level probe to them and continuously monitoring it. Our findings show that the ultimate precision limit, quantified by the Fisher information, scales linearly with N, offering an exponential improvement over equilibrium thermometry, where the scaling is only log2N. For a fixed Hamiltonian structure, we develop a maximum-likelihood estimation strategy that maps the observed continuously monitored trajectories of the probe into temperature estimates with minimal error. By optimizing over all possible Hamiltonian structures, we discover that the optimal configuration is an effective two-level system, with both levels exhibiting degeneracy that increases with N—a stark contrast to equilibrium thermometry, where the ground state remains nondegenerate. Our results have practical implications. First, continuous monitoring is experimentally feasible on several platforms and accounts for the preparation time of the probe, which is often overlooked in other approaches such as prepare and reset. Second, the linear scaling is robust against deviations from the effective two-level structure of the optimal Hamiltonian. Additionally, this robustness extends to cases of initial ignorance about the temperature. Thus, in global estimation problems, the linear scaling remains intact even without adaptive strategies. Published by the American Physical Society 2025

Reference values for the 1-minute sit-to-stand test to assess functional capacity and short-term mortality in people with idiopathic pulmonary fibrosis and fibrotic connective tissue related interstitial lung diseases: a prospective real-world cohort study

BackgroundEarly identification of functional decline in fibrotic interstitial lung disease (F-ILD) is crucial for timely treatment and improved survival. While the 6-minute walk test (6MWT) is the standard for functional evaluation, it has practical limitations. The 1-minute sit-to-stand test (1MSTS) offers a simpler alternative; however, its correlation with the 6MWT in F-ILD patients remains unclear. This study aims to establish reference values for the 1MSTS in assessing functional capacity, evaluate its correlation with the 6MWT, and explore its utility in predicting 18-month mortality in F-ILD patients.MethodsThis prospective study enrolled participants diagnosed with F-ILD based on multidisciplinary team discussions. Assessments included the 1MSTS, 6MWT, pulmonary function test (PFT), GAP score, mMRC scale, and Charlson Comorbidity Index (CCI). The association between 1MSTS repetitions and other variables was calculated using Spearman’s rho. Bland-Altman plots assessed the agreement between 1MSTS repetitions and the 6MWT. Predictors of 18-month mortality were evaluated using ROC curve and Kaplan-Meier curve.ResultsOf the 150 F-ILD patients, 37 (24.6%) had idiopathic pulmonary fibrosis (IPF), and 113 (75.4%) had connective tissue disease-related ILD (CTD-ILD). Using ≤ 23 repetitions as the cutoff for functional impairment in 1MSTS, 74 (47.3%) patients were classified as impaired. The 1MSTS significantly predicted 18-month mortality and demonstrated moderate correlations with GAP score (rs = -0.49), mMRC scale (rs = -0.47), and 6MWT distance (rs = 0.65). Bland-Altman analysis indicated agreement between 1MSTS repetitions and 6MWT distance. Using ≤ 23 repetitions as the cutoff value for the 1MSTS to predict 18-month mortality, the mortality rate was 76.4%, with an AUC of 0.81.ConclusionsThe findings suggest that ≤ 23 repetitions in the 1MSTS can serve as an indicator of functional impairment, demonstrate a good correlation with 6MWT distance, and effectively predict 18-month mortality in patients with F-ILD.Clinical trial numberNot applicable.

Landau levels induced by synthetic strain in plasmonic metasurface

The quantum Hall effect arises when electrons in a two-dimensional plane are subjected to a magnetic field, causing them to undergo cyclotron motion and form discrete energy levels, known as Landau levels. These levels play a critical role in condensed matter physics. However, practical limitations of applying a magnetic field have led to the introduction of pseudomagnetic fields, which can similarly induce Landau levels. Such pseudomagnetic fields are typically generated through synthetic strain, achieved by deforming geometric patterns, and have been applied to systems like graphene, photons, and phonon crystals. Building on previous research in electronics and optics, we present a plasmonic metasurface that induces Landau levels via synthetic strain in the microwave frequency range. This strain is realized by printing metal structures of specific shapes on a dielectric substrate using printed circuit board technology. The fundamental unit of the plasmonic metasurface is a C6 symmetric structure composed of six localized surface plasmon patches. By applying a displacement function along the transmission direction, we discretize the dispersion curve, leading to band degeneration and the emergence of edge states. The distribution of these edge states is influenced by the strength of the pseudomagnetic field, which is controlled by the magnitude of the displacement function. We validate our design through fabricated models and demonstrate the existence of edge states using near-field scanning experiments. Our work, which combines synthetic magnetic fields and plasmonic metasurface, provides valuable insights for the development and application of integrated photonic devices.

Pitfalls and practical suggestions for using local field potential recordings in DBS clinical practice and research

Objective. Local field potential (LFP) recordings using chronically implanted sensing-enabled stimulators are a powerful tool for indexing symptom presence and severity in neurological and neuropsychiatric disorders, and for enhancing our neurophysiological understanding of brain processes. LFPs have gained interest as input signals for closed-loop deep brain stimulation (DBS) and can be used to inform DBS parameter selection. LFP recordings using chronically implanted sensing-enabled stimulators have various implementational challenges.Approach. Here we describe our collective experience using BrainSense (Medtronic®) for clinical and research work. We aim to provide insightful tips and practical advice to empower readers with the knowledge needed to navigate the intricacies of the device and make the most out of its features.Main results. The central issues that apply to several BrainSense features encompass restricted compatibility of stimulation configuration with sensing, differences in electrophysiological signal properties between 'stimulation OFF' and 'stimulation ON at 0.0 mA', and challenges associated with the internal clock of the neurostimulator. In addition, since recordings are obtained from bipolar and not monopolar channels, spatial certainty regarding the distribution of LFPs around the DBS electrode is limited. Several options exist to synchronize LFP time series with external data streams, but standardization and generalization are lacking. The use of at-home chronic LFP recording is limited by a low temporal and spectral resolution. Regarding at-home LFP snapshots, LFP time series are not stored, parts of the power spectrum are censored when stimulating at high or low frequencies, and the stimulation amplitude is not readily available.Significance. We discussed practical applications, implementation, system limitations, and pitfalls with the aim that sensing can be better applied for clinical practice and research.

The Spectrum of Genetic Risk in Alzheimer Disease.

Alzheimer disease (AD), the most common dementing syndrome in the United States, is currently established by the presence of amyloid-β and tau protein biomarkers in the setting of clinical cognitive impairment. These straightforward diagnostic parameters belie an immense complexity of genetic architecture underlying risk and presentation in AD. In this review, we provide a focused overview of the current state of AD genetics. We discuss the discovery of familial autosomal dominant genes, the identification of candidate genes associated with AD, and genetic variants conferring higher risk of developing AD compared with the general population. In particular, we discuss important features of AD risk due to the APOE ε4 allele. In addition to risk, we describe how the field has made headway understanding genetic factors that may protect from AD. The biological implications and practical limitations of information gleaned from genome-wide association studies in AD over the years are also discussed. The readers will have an up-to-date understanding of where we are in our efforts to understand the layers of genetic complexity in AD.

Stochastic feature selection with annealing and its applications to streaming data

Feature selection is an important topic in high-dimensional statistics and machine learning, for prediction and understanding the underlying phenomena. It has many applications in computer vision, natural language processing, bioinformatics, etc. However, most feature selection methods in the literature have been proposed for offline learning, and the existing online feature selection methods have theoretical and practical limitations in true support recovery. This paper proposes two novel online feature selection methods by stochastic gradient descent with a hard thresholding operator. The proposed methods can simultaneously select the relevant features and build linear regression or classification models based on the selected variables. The theoretical justification is provided for the consistency of the proposed methods. Numerical experiments on simulated and real sparse datasets show that the proposed methods compare favourably with state-of-the-art online methods from the literature.

Nondestructive testing of GFRP composites with compressive sensing-based terahertz single-pixel imaging

ABSTRACT Terahertz (THz) imaging technique has a wide range of applications, from industrial non-destructive testing (NDT) to various biomedical applications. Although the capabilities of terahertz radiation in defect detection are well-proven, the practical limitations have been associated with the long image acquisition time. Hence, to improve the image acquisition speed, the compressive sensing technique has been employed. However, the challenge is identifying the optimal modulation mask for compressive sensing as the image reconstruction metrics hugely depend on the mask. Hence, a systematic investigation of the different modulation masks has been done to reconstruct THz images of glass fibre-reinforced polymer (GFRP) composites using TVAL3 (Total Variation minimization by Augmented Lagrangian and ALternating direction Algorithm). The image reconstruction quality has been studied using mean square error, peak signal-to-noise ratio, and structural similarity index. From the results, it can be noticed with a 0.3 sampling ratio, reliable reconstruction of the THz image is possible, saving 70% of the image acquisition time. Further, the discrete cosine transform (DCT) mask is ideal for high frame rate NDT in low and medium noise scenarios. However, the Bernoulli basis offers high resistance to noise by resulting in the best image reconstruction results at high noise cases, outperforming the DCT.

응급구조학 전공학생의 가상현실(VR)기반 환자안전 시뮬레이션 교육경험

Objectives This study aimed to explore the educational experiences of paramedic students in patient safety simu lations based on virtual reality (VR). It also sought to provide foundational data to support the future expansion of VR-based patient safety simulation education. Methods Thirteen paramedicine students from D Metropolitan City, who consented to participate in the study through a recruitment notice, were divided into three teams of 4-5 members each. A virtual reality-based patient safety simulation training was conducted for these teams. Subsequently, focus group interviews were carried out using open-ended and semi-structured questions. The interviews were audio-recorded and transcribed, and the collected data were analyzed through an in-depth discussion and categorization process following the consensual qualitative research method. Results The analysis of the experiences revealed two domains, six theme clusters, and thirteen themes. In the educational aspect, four theme clusters emerged: “Interest in the unfamiliar VR-based education,” “Easy acces sibility,” “Overcoming the limitations of clinical practice,” and “Functioning as an effective learning method.” In the equipment usage aspect, two theme clusters were identified: “Technical limitations of VR equipment” and “Physical sensitivity.” Conclusions The VR-based patient safety simulation education was identified as an effective teaching method, highlighting the need for its implementation. Suggestions for improvement to ensure safe operation were also derived. It is hoped that this study will serve as foundational data for future VR-based patient safety simulation programs.

Scientific and Regulatory Policy Committee Points to Consider: Proposal and Recommendations to Reduce Euthanasia of Control Nonhuman Primates in Nonclinical Toxicity Studies.

Nonhuman primates (NHPs) have been and remain a highly valuable animal model with an essential role in translational research and pharmaceutical drug development. Based on current regulatory guidelines, the nonclinical safety of novel therapeutics should be evaluated in relevant nonclinical species, which commonly includes NHPs for biotherapeutics. Given the practical and ethical limitations on availability and/or use of NHPs and in line with the widely accepted guiding "3Rs" (replace, reduce, and refine) principles, many approaches have been considered to optimize toxicity study designs to meaningfully reduce the number of NHPs used. Standard general toxicity studies usually include four groups of equal size, including one group of vehicle control animals. Here, we describe an approach to achieve an overall significant reduction in control animal use, while also resolving many of the issues that may limit application of fully virtual control animals. We propose in Good Laboratory Practice (GLP)-compliant toxicity studies to maintain concurrent control group animals for the in-life phase of the studies, but to limit euthanasia to a subset of control animals. The nonterminated control animals can then be returned to the facility colony for reuse in subsequent studies. The proposed study design could lead to a 15% to 20% reduction in NHP usage. The scientific, logistical, and animal welfare considerations associated with such an approach and suggested solutions are discussed in detail.

Blockchain in supply chains: an unfulfilled promise

Purpose This paper investigates the influence of blockchain technology on trust and transparency within supply chain management. While existing research suggests blockchain has revolutionary potential, real-world evidence remains limited. This study aims to bridge this gap. Design/methodology/approach The research relies on transaction cost analysis and principal-agent theory to develop a conceptual model. The model proposes how blockchain fosters trust and transparency, ultimately leading to a market-based governance model within supply chains. Five different blockchain applications were analyzed in a multi-case study through document reviews and expert interviews to test the model’s assumptions. Findings The study’s findings challenge initial assumptions. The complexity of blockchain networks and a reluctance to share information among participants hinder blockchain technology’s ability to increase trust and transparency. Consequently, the expected reduction in opportunism and uncertainties is not observed, and a market-based governance model fails to materialize. In practice, supply chain partners gravitate toward permissioned blockchains managed by established consortia. Acting as trusted third parties, these consortia assume control over network management, rendering blockchain essentially unnecessary. Originality/value This paper sheds light on the practical limitations of blockchain technology in revolutionizing supply chain management. While blockchain promises much, the findings suggest that established consortia currently play a more critical role in fostering trust and transparency within supply chains.

Limitations of Standard Rain Erosion Tests for Wind Turbine Leading Edge Protection Evaluation

Blade leading edge erosion (LEE) is a persistent challenge in the wind industry, resulting in reduced aerodynamic efficiency and increased maintenance costs, with an estimated total expense of GBP 1.3M over a 25-year turbine lifetime. To mitigate these effects, leading edge protection (LEP) systems are widely used, but their real-world performance often falls short of predictions based on the standard rain erosion test (RET). This study investigates the limitations of current RET practices, which are designed to accelerate testing but fail to replicate the diverse environmental conditions experienced by wind turbines. Two LEPs with contrasting viscoelastic properties were tested using a novel design of experiments (DoEs) approach. The study explored the droplet impact frequency, combination and sequencing of high or low rainfall intensities, recovery during the inspection period and droplet size effects on erosion behaviour, to uncover significant differences in material performance compared to standard RET conditions. Results, supported by dynamic mechanical analysis (DMA), indicated that the chosen LEPs undergo a transition between elastic and brittle failure modes at a critical impact frequency, influenced by the viscoelastic properties of the material. Importantly, the findings emphasise the need for revised testing protocols across a range of parameters that incorporate realistic environmental conditions to improve the predictability of LEP performance.

Enhancing Reflexivity in Research and Practice in Healthcare Through Oral-Based Autoethnography.

Autoethnography is an increasingly used method to promote individual and group reflexivity in research, not the least in healthcare. However, autoethnography's uptake among practitioners is impeded by the fact that it has not been adequately adapted to practitioner settings from its academic origins. This article analyzes the experience of a research team comprised of practitioners/surgeons and social scientists using primarily oral-based autoethnographic practices to promote reflexive collaboration in a longitudinal research and innovation project on selection and training of surgical residents. Based on our case of innovative adaptation and application of autoethnography, which we term autoethnorality, several modifications in autoethnographic practice are suggested to make it more amenable to practitioner settings. These include adopting the collaborative and analytic forms of autoethnography and developing oral-based modalities for autoethnographic practice. The case also shows how these strategic choices along with successive adoption of autoethnographic practices can facilitate the resolution of tensions deriving from the differing timeframes, skillsets, and interests of practitioners on the one hand and academic researchers on the other, as well as paradigmatic differences in theory of science between the medical and social sciences. A table summarizing the advantages and disadvantages of different strategic choices and adaptations regarding autoethnography along with actionable recommendations is presented.

Closing the Circulation Budget

AbstractCirculation budgets can identify physical processes underpinning tropical cyclones, mesoscale convective vortices, and other weather systems where there are interactions across scales. It is unclear, however, how well these budgets close in practice. The present study uses the rapid intensification of Tropical Cyclone Nepartak (2016) as a case study to quantify the practical limitations of calculating circulation budgets using standard reanalyzes and numerical weather model data. First, we evaluate the circulation budget with ERA5. The budget residual can be reduced considerably by including contributions to circulation changes from subgrid‐scale momentum transports, and reduced further with 24‐hr smoothing, which dampens the discontinuous effects of data assimilation. Second, using a high‐resolution Met Office Unified Model simulation, we examine how the choice of the path used (the domain boundary) affects the budget closure. Third, the truncation errors associated with numerical differentiation in time and space are investigated. The circulation budget improves as the model data are analyzed with more frequent time output intervals, and as the output grid spacing decreases. For the tropical convective examples evaluated here, the column mean budget residuals increase by up to 50% as the output intervals increase from 5 min to 3 hr. Errors also increase if the data are regridded to a coarser horizontal grid spacing and when convection straddles the domain boundary. A key result is that the circulation budget need not close for physical inferences made about the circulation and its evolution to be meaningful, thus validating the use of the technique in prior studies.

Provision of contraception to adolescents in primary healthcare clinics in South Africa: Perspectives of healthcare practitioners

Introduction: The provision of contraception to adolescents is a fundamental public health strategy for preventing adolescent pregnancies and realising universal access to sexual and reproductive health. In the South African context, and as informed by national and provincial policy guidelines, this strategy is delivered at primary healthcare clinics. In this study, we sought to explore the barriers and enablers of providing contraception to adolescents in primary healthcare clinics from the perspectives of healthcare practitioners. Methods: We employed a qualitative research design. Using purposive sampling, we recruited senior managers and nurses involved in primary healthcare and sexual and reproductive health programmes in South Africa. We conducted semi-structured interviews with twenty-nine participants working in an urban or rural district. Subsequently, we transcribed the interviews, verifying for errors. Guided by Braun and Clarke’s model of thematic analysis, we grouped the data into four themes derived from the healthcare access frameworks. Each of the four themes has sub-themes describing both enablers and barriers to providing contraception to adolescents. Results: The study revealed that practitioners’ knowledge of policy guidelines enabled them to provide contraception to adolescents effectively. However, the differences between what is stated in policy documents and practical limitations could impede the extent to which services reach adolescents. Other barriers to providing contraception to adolescents included language differences between healthcare practitioners and users, time constraints, and lack of privacy during consultations. Participants noted that appropriate nurse training and ensuring an accepting environment for adolescents facilitated the provision of contraception to this age group. Conclusion: Our study offers valuable insights into the perspectives of primary healthcare practitioners about the barriers and enablers in providing contraception to adolescents. Our results indicate that policy development and future research should focus on strengthening the delivery of contraception services for adolescents.

Assessing Pedagogical Strategies Integrating ChatGPT in English Language Teaching: A Structural Equation Modelling-Based Study

This research investigates the impact of AI-powered ChatGPT technology on current pedagogical strategies, focusing on student engagement, language proficiency, and perceived usability. Data was collected through structured surveys from 301 English language learners at Ajman University (49.9%) and University of Hail (50.1%) in the United Arab Emirates and Saudi Arabia respectively. Grounded in constructivist learning theory, the results reveal strong positive outcomes. The integration of ChatGPT into pedagogical strategies significantly enhances student engagement, improves language proficiency (β=0.698, p<0.000), and increases perceived usability among English language learners in higher education institutions in the UAE and Saudi Arabia. Respondents reported that these strategies made lessons more engaging and interactive, improved their language skills, and provided a user-friendly learning interface. These findings underscore the potential of AI tools like ChatGPT to revolutionize language education by offering interactive, personalized, and effective learning experiences. Additionally, the study supports the principles of constructivist learning theory, highlighting students’ positive attitudes and perceptions towards the integration of ChatGPT-enhanced pedagogical strategies,. Practical recommendations and study limitations are also discussed.

Carbon nanotubes stabilized in chitosan sponge (CNT-CS) as a new alternative clean-up sorbent for pesticide multiresidue determination in eggplants using QuEChERS and UHPLC-MS/MS.

The continuous development and application of pesticides in agriculture require robust multiresidue detection methods to guarantee food safety. This study introduces a novel method for multiresidue determination of pesticides in eggplants using the QuEChERS procedure, incorporating a clean-up step using carbon nanotubes stabilized in chitosan sponge (CNT-CS) and ultra-high performance liquid chromatography with tandem mass spectrometry (UHPLC-MS/MS) for analysis. Upon identifying the optimal extraction conditions, various sorbents were assessed for their efficacy in the dispersive solid-phase extraction (d-SPE). Among these, the biosorbent CNT-CS emerged as the most efficient and cost-effective material, showing the best recovery results from spiked blank samples. The validation demonstrated that the method was adequate for analyzing 111 pesticides in eggplant samples with practical method quantification limits from 5 to 25µgkg-1. When applied to commercial eggplant samples, 27 pesticides were detected, demonstrating the importance of the proposed method. It is noteworthy that the conducted work represents the first report on the use of the biosorbent CNT-CS in the clean-up step of the QuEChERS method. The results obtained in the validation and application steps demonstrate that the proposed method is an excellent alternative for monitoring programs.

Influence of Organic Mulching on Soil Thermoregulation in the Tocantina Region of Maranhão

Objective: This study investigates the influence of organic mulching on soil thermoregulation in the Tocantina Region of Maranhão, evaluating its thermal effects and implications for the sustainable management of agricultural production. Theoretical Framework: The research discusses the benefits of mulching for sustainable agriculture, such as thermal regulation, moisture conservation, and soil biological activity, providing a solid foundation for the study. Methodology: The experiment was conducted at the Agricultural Sciences Center of UEMASUL, using two 1 m² plots: one covered with straw mulch and the other uncovered (control). Soil temperature measurements were taken at depths of 2.5 cm and 7.5 cm using a digital thermometer, with data collected every 5 minutes between 2:00 p.m. and 3:00 p.m. Results and Discussion: Organic mulch significantly reduced soil temperature, with an average of 36.13°C in covered areas compared to 48.09°C in uncovered ones. Depth also influenced temperature, with the mulch showing a more pronounced effect. These findings were contextualized within the theoretical framework, highlighting practical implications and study limitations. Implications: The research provides insights into agricultural management practices, emphasizing thermal efficiency, water conservation, increased productivity in tropical climates, sustainability, and adaptation to climate change. Originality/Value: This study contributes by exploring soil thermoregulation through organic mulching in a tropical region, promoting low-cost agricultural practices relevant to family farming and mitigating high temperatures.