Lithium-ion batteries are widely used in electric vehicles and renewable energy storage systems due to their superior performance in most aspects. Battery parameter identification, as one of the core technologies to achieve an efficient battery management system (BMS), is the key to predicting and managing the performance of Li-ion batteries. However, due to the complex chemical reactions and thermodynamic processes inside lithium-ion batteries, coupled with the influence of the external environment, accurate identification of lithium-ion battery parameters has become an urgent problem to be solved. In addition, data-driven parameter identification can enable battery models to better understand battery behavior, which is one of the focuses of future research. For this reason, this paper comprehensively reviews the application of data-driven parameter identification methods in different scenarios. Firstly, the research briefly explains the working principle of lithium-ion batteries and the key parameters affecting their performance. Secondly, this paper deeply discusses data-driven methods for parameter identification, which are widely used nowadays, and provides improvement ideas to address the shortcomings of traditional methods. Finally, the paper discusses the challenges faced by parameter identification technology for lithium-ion batteries and envisages future prospects. Full article

This paper presents the results of an extensive investigation into the durability of cold spray repairs to corrosion damage in AA7075-T7351 aluminium alloy specimens where, prior to powder deposition, the surface preparation involved grit blasting. In this context, it is shown that the growth of small naturally occurring cracks in cold spray repairs to simulated corrosion damage can be accurately computed using the Hartman–Schijve crack growth equation in a fashion that is consistent with the requirements delineated in USAF Structures Bulletin EZ-SB-19-01, MIL-STD-1530D, and the US Joint Services Structural Guidelines JSSG2006. The relatively large variation in the da/dN versus ΔK curves associated with low values of da/dN highlights the fact that, before any durability assessment of a cold spray repair to an operational airframe is attempted, it is first necessary to perform a sufficient number of tests so that the worst-case small crack growth curve needed to perform the mandated airworthiness certification analysis can be determined. Full article

Amidst rapid urbanization and escalating environmental degradation in China’s urban areas due to climate change, traditional drainage systems struggle to cope with rainfall, resulting in frequent flood disasters. In response, rain gardens have emerged as ecologically practical stormwater management solutions that integrate urban flood control with landscape design. Leveraging the dual benefits of rainwater purification and aesthetic enhancement provided by vegetation, herbaceous plant-based rain gardens have assumed a pivotal role in green infrastructure. However, dedicated research on the application of herbaceous plants in rain garden design is limited, especially within China’s water-stressed context. This study employs a literature review and case analysis to explore this critical issue. Initially, it delineates the concept of the sponge city introduced by the Chinese government. Subsequently, it reviews concepts and methods of plant biodiversity design in urban settings and rain gardens and elucidates the structure and function of rain gardens. Four Chinese rain gardens in different urban environments (old industrial areas, university campuses, urban villages, and urban highway green belts) were selected to examine the selection and arrangement of herbaceous plants while identifying deficiencies in their designs. Finally, feasibility suggestions are provided for the design of herbaceous plant diversity in Chinese rain gardens. This study’s findings can provide a reference for the planting design of herbaceous plants in rain gardens for other countries and regions with similar climates and environmental conditions. Full article

This paper presents a comprehensive review of the design and implementation methods of low-power piezoelectric energy harvesting circuits, which in the last few years have gained an extremely large range of applications like the power sources of wearable electronic devices, such as biometrical sensors. Before examining the electronic circuitries of the self-supplied power devices, an overview of the structure, equivalent electrical circuits, and basic parameters of the piezoelectric generators and MEMSs as energy harvesting elements is presented. The structure of energy storage elements (parallel-plate capacitors and thin-film supercapacitors), suitable for this type of application, is also presented. The description of these components from an electrical point of view allows them to be easily workable when connected to the various power conversion electronic circuits. Based on an overview of the structure and the principles of operation, as well as some analytical expressions for energy efficiency evaluation, a comprehensive comparative analysis is presented. Depending on the advantages and disadvantages of the known circuit configurations, the basic electrical and design parameters are systematized in tabular form. Practical realizations of piezoelectric power conversion circuits are also presented in graphic form, ensuring the optimal value of energy efficiency and compactness in the construction of the devices. Full article

In the face of increasing demands for tasks such as mountain rescue, geological exploration, and military operations in complex wilderness environments, planning an efficient walking route is crucial. To address the inefficiency of traditional two-dimensional path planning, this paper proposes a two-stage path planning algorithm. First, an improved Probabilistic Roadmap (PRM) algorithm is used to quickly and roughly determine the initial path. Then, the morphological dilation is applied to process the grid points of the initial path, retaining the surrounding area of the initial path for a precise positioning of the search range. Finally, the idea of the A^∗ algorithm is applied to achieve precise path planning in the refined search range. During the process of constructing the topology map, we utilized parallelization acceleration strategies to expedite the graph construction. In order to verify the effectiveness of the algorithm, we used terrain data to construct a wilderness environment model, and tests were conducted on off-road path planning tasks with different terrains and distances. The experimental results show a substantial enhancement in the computational efficiency of the proposed algorithm relative to the conventional A^∗ algorithm by 30 to 60 times. Full article

Egyptian Faience, a revolutionary innovation in ancient ceramics, was used for crafting various objects, including amulets, vessels, ornaments, and funerary figurines, like shabtis. Despite extensive research, many aspects of ancient shabti production technology, chemistry and mineralogy remain relatively understudied from the 21st to the 22nd Dynasty, belonging to a recovered 19th-century private collection. The fragments’ origin is tentatively identified in the middle Nile valley in the Luxor area. Our study focused on a modest yet compositionally interesting small collection of shabti fragments to provide information on the glaze’s components and shabti’s core. We found that the core is a quartz and K-feldspars silt blended with an organic component made of plastic resins and vegetable fibres soaked with natron. The studied shabti figurines, after being modelled, dried, and covered with coloured glaze, were subjected to a firing process. Sodium metasilicate and sulphate compounds formed upon contact of the glaze with the silica matrix, forming a shell that holds together the fragile inner matrix. The pigments dissolved in the sodic glaze glass, produced by quartz, K-feldspars, and natron frit, are mainly manganese (Mn) and copper (Cu) compounds. The ratio Cu₂O/CaO > 5 produces a blue colour; if < 5, the glaze is green. In some cases, Mg and As may have been added to produce a darker brown and an intense blue, respectively. Reaction minerals provided information on the high-temperature firing process that rapidly vitrified the glaze. These data index minerals for the firing temperature of a sodic glaze, reaching up to a maximum of 1050 °C. Full article

This study aims to improve the battery performance in hybrid electric vehicles (HEVs) by reducing the vehicle speed. We developed a specific protocol for managing battery use and optimizing the energy consumption rate to achieve this goal. The protocol automatically controls the driving operation, avoiding incompatible driving patterns with an energy-saving mode and performance improvement. This protocol was applied to a simulation process to predict energy rate lowering and battery performance enhancement. The proposed protocol applies to any hybrid electric vehicle type and any route conditions since it uses vehicle mass, drag and rolling coefficients, and road slope as variable parameters to determine the minimum energy consumption rate. We performed experimental tests to validate the simulation data and the proposed protocol. Furthermore, the protocol applies to variable starting vehicle speeds, from 10 to 50 km/h, corresponding to the current driving patterns, sport, normal, and eco, set up by car manufacturers. A reduction of 10% in vehicle speed in urban and peripheral routes achieves a minimum energy rate, enhancing battery management. Current vehicle speed shows a deviation from optimum management of 18% while applying vehicle speed reduction limits the deviation to 0.2%. Experimental results show a good agreement with simulation data, with 94% accuracy. We tested the protocol for urban and peripheral routes with maximum vehicle speed limits of 60 and 90 km/h. Full article

Residential historic areas are currently the main focus of urban renewal efforts in China, primarily consisting of traditional residential buildings with similar characteristics. Hence, the visual coherence of buildings (VCoB) plays a crucial role in such areas, not only pertaining to the visual quality of the urban landscape but also regarding the preservation of historic features. The accurate measurement of the VCoB is a prerequisite for undertaking optimization efforts. However, discussions of the VCoB in the built environment are limited and seldom address residential historic areas, and methods for measuring the VCoB have yet to be refined. Therefore, taking the Xiaoxihu Historic Area in Nanjing as a case study, this work aimed to develop a more refined method for measuring the VCoB in residential historic areas based on objective physical features. The method is mainly based on the human-level perspective, identifying three key visual elements within this perspective as the objects of measurement. It collected visual data through photography, with deep learning and computer graphics processing tools being utilized to identify and extract the visual elements. Then, the study established a corresponding framework of indicators for different visual elements and optimizes the methods for indicator calculation. Through an assessment involving professionals, we validated the high accuracy of the measurement method proposed in this study. Furthermore, the study discusses factors affecting the VCoB, methods to enhance the VCoB, and the required degree of the VCoB based on the results of the measurement. The method developed in this research will provide support for the visual analysis of the urban built environment and urban renewal practices. Full article

Herbal medicine has been widely valued because of its remarkable efficacy and minimal side effects. The quantitative analysis of herbal medicines is essential to ensure their safety and efficacy. The simultaneous detection of multiple quality markers (Q-markers) has emerged as an important approach and trend in herbal medicine quality control. In recent years, non-targeted screening has become an effective strategy for the discovery and identification of unknown compounds. This study developed a non-targeted screening and quantitative analysis strategy to discover, identify and quantify the multiple components that truly represent the efficacy of Wuling capsule. Within this strategy, 18 types of flavonoids were tentatively discovered and identified from Wuling capsule by analyzing mass cleavage pathways, the precise molecular weights of compounds, and comparing the data with a database. Ten types of flavonoids were determined after the comparison of the standards. Additionally, following the evaluation of the regression equation, linear range, limit of detection (LOD), limit of quantitation (LOQ), precision, repeatability, and recovery of the proposed quantitative method, six flavonoids were quantified. This method successfully screened, identified, and quantified the potential active components in Wuling capsule, providing insights for improving the quality control standards in other herbal medicines. Full article

One of the major sources of catastrophic failures and deterioration of the mechanical properties of metals, such as ductility, toughness, and strength, in various engineering components during application is hydrogen embrittlement (HE). It occurs as a result of the adsorption, diffusion, and interaction of hydrogen with various metal defects like dislocations, voids, grain boundaries, and oxide/matrix interfaces due to its small atomic size. Over the years, extensive effort has been dedicated to understanding hydrogen embrittlement sources, effects, and mechanisms. This study aimed at assessing the tensile properties, toughness, ductility, and susceptibility to hydrogen embrittlement of cold-finished mild steel. Steel coupons were subjected to electrochemical hydrogen charging in a carefully chosen alkaline solution over a particular time and at various charging current densities. Tensile property tests were conducted immediately after the charging process, and the results were compared with those of uncharged steel. The findings revealed a clear drop in toughness and ductility with increasing hydrogen content. Fracture surfaces were examined to determine the failure mechanisms. This evaluation has enabled the prediction of steel’s ability to withstand environments with elevated hydrogen concentrations during practical applications. Full article

Introduction: The onset of the COVID-19 pandemic brought about global uncertainties and fears, escalating the dissemination of fake news. This study aims to analyze the impact of fake news on COVID-19 vaccine adherence among pregnant women, providing crucial insights for effective communication strategies during the pandemic. Methods: A cross-sectional, exploratory study was conducted with 113 pregnant women under care at a Women’s Health Reference Center. Data analysis included relative frequency and odds ratio to assess the relationship between sociodemographic and behavioral variables regarding vaccination. Results: In the behavioral context of vaccination, internet access shows a significant association with decision-making, influencing vaccine refusal due to online information. Nuances in the odds ratios results highlight the complexity of vaccine hesitancy, emphasizing the importance of information quality. Pre-vaccination sentiments include stress (87.61%), fear (50.44%), and anxiety (40.7%), indicating the need for sensitive communication strategies. Discussion: Results revealed that pregnant women with higher education tend to adhere more to vaccination. Exposure to news about vaccine inefficacy had a subtle association with hesitancy, while finding secure sources was negatively associated with hesitancy. The behavioral complexity in the relationship between online information access and vaccination decision underscores the need for effective communication strategies. Conclusions: In the face of this challenging scenario, proactive strategies, such as developing specific campaigns for pregnant women, are essential. These should provide clear information, debunk myths, and address doubts. A user-centered approach, understanding their needs, is crucial. Furthermore, ensuring information quality and promoting secure sources are fundamental measures to strengthen trust in vaccination and enhance long-term public health. Full article

Background/Objectives: The intermediate femoral cutaneous nerve (IFCN), the saphenous nerve, and the medial femoral cutaneous nerve (MFCN) innervate the skin of the anteromedial knee region. However, it is unknown whether the MFCN has a deeper innervation. This would be relevant for total knee arthroplasty (TKA) that intersects deeper anteromedial genicular tissue layers. Primary aim: to investigate deeper innervation of the anterior and posterior MFCN branches (MFCN-A and MFCN-P). Secondary aim: to investigate MFCN innervation of the skin covering the anteromedial knee area and medial parapatellar arthrotomy used for TKA. Methods: This study consists of (1) a dissection study and (2) unpublished data and post hoc analysis from a randomized controlled double-blinded volunteer trial (EudraCT number: 2020-004942-12). All volunteers received bilateral active IFCN blocks (nerve block round 1) and saphenous nerve blocks (nerve block round 2). In nerve block round 3, all volunteers were allocated to a selective MFCN-A block. Results: (1) The MFCN-A consistently innervated deeper structures in the anteromedial knee region in all dissected specimens. No deep innervation from the MFCN-P was observed. (2) Sixteen out of nineteen volunteers had an unanesthetized skin gap in the anteromedial knee area and eleven out of the nineteen volunteers had an unanesthetized gap on the skin covering the medial parapatellar arthrotomy before the active MFCN-A block. The anteromedial knee area and medial parapatellar arthrotomy was completely anesthetized after the MFCN-A block in 75% and 82% of cases, respectively. Conclusions: The MFCN-A shows consistent deep innervation in the anteromedial knee region and the area of MFCN-A innervation overlaps the skin area covering the medial parapatellar arthrotomy. Further trials are mandated to investigate whether an MFCN-A block translates into a clinical effect on postoperative pain after total knee arthroplasty or can be used for diagnosis and interventional pain management for chronic neuropathic pain due to damage to the MFCN-A during surgery. Full article

In plant models such as Arabidopsis thaliana, phosphatidic acid (PA), a key molecule of lipid signaling, was shown not only to be involved in stress responses, but also in plant development and nutrition. In this article, we highlight lipid signaling existing in crop species. Based on open access databases, we update the list of sequences encoding phospholipases D, phosphoinositide-dependent phospholipases C, and diacylglycerol-kinases, enzymes that lead to the production of PA. We show that structural features of these enzymes from model plants are conserved in equivalent proteins from selected crop species. We then present an in-depth discussion of the structural characteristics of these proteins before focusing on PA binding proteins. For the purpose of this article, we consider RESPIRATORY BURST OXIDASE HOMOLOGUEs (RBOHs), the most documented PA target proteins. Finally, we discuss pioneering experiments that show, by different approaches such as monitoring of gene expression, use of pharmacological agents, ectopic over-expression of genes, and the creation of silenced mutants, that lipid signaling plays major roles in crop species. Finally, we present major open questions that require attention since we have only a perception of the peak of the iceberg when it comes to the exciting field of phospholipid signaling in plants. Full article

We aimed to study the impact of polymorphisms in the genes encoding interleukin-6 (IL6) and tumor necrosis factor receptor-2 (TNFR2), reported to be mortality risk predictors, in patients with end-stage kidney disease (ESKD) undergoing dialysis. TNFRSF1B (rs3397, rs1061624, and rs1061622) and IL6 (rs1800796, rs1800797, and rs1554606) polymorphisms were studied in patients with ESKD and controls; the genotype and allele frequencies and the associations with inflammatory and erythropoiesis markers were determined; deaths were recorded throughout the following two years. The genotype and allele frequencies for the TNFRSF1B rs3397 polymorphism were different in these patients compared to those in the controls and the global and European populations, and patients with the C allele were less common. Patients with the CC genotype for TNFRSF1B rs3397 presented higher hemoglobin and erythrocyte counts and lower TNF-α levels, suggesting a more favorable inflammatory response that seems to be associated with erythropoiesis improvement. Patients with the GG genotype for TNFRSF1B rs1061622 showed lower serum ferritin levels. None of the TNFRSF1B (rs3397, rs1061624, and rs1061622) or IL6 (rs1800796, rs1800797, and rs1554606) polymorphisms had a significant impact on the all-cause mortality rate of Portuguese patients with ESKD. Full article

Winter wheat is one of the major cereal crops globally and one of the top three cereal crops in China. The precise forecasting of the yield of winter wheat holds significant importance in the realms of agricultural management and ensuring food security. The use of multi-temporal remote sensing data for crop yield prediction has gained increasing attention. Previous research primarily focused on utilizing remote sensing data from individual or a few growth stages as input parameters or integrated data across the entire growth period. However, a detailed analysis of the impact of different temporal combinations on the accuracy of yield prediction has not been extensively reported. In this study, we optimized the temporal sequence of growth stages using interpolation methods, constructed a yield prediction model incorporating the enhanced vegetation index (EVI) at different growth stages as input parameters, and employed a random forest (RF) algorithm. The results indicated that the RF model utilizing the EVI from all the temporal combinations throughout the growth period as input parameters accurately predicted the winter wheat yield with an R² of the calibrated dataset exceeding 0.58 and an RMSE less than 1284 kg/ha. Among the 1023 yield models tested in this study with ten different growth stage combinations, the most accurate temporal combination comprised five stages corresponding to the regreening, erecting, jointing, heading, and filling stages, with an R² of 0.81 and an RMSE of 1250 kg/ha and an NRMSE of 15%. We also observed a significant decrease in estimation accuracy when the number of growth stages was fewer than five and a certain degree of decline when the number exceeded five. Our findings confirmed the optimal number and combination of growth stages for the best yield prediction, providing substantial insights for winter wheat yield forecasting. Full article

The Quintuple Aim seeks to improve healthcare by addressing social determinants of health (SDOHs), which are responsible for 70–80% of medical outcomes. SDOH-related concerns have traditionally been addressed through referrals to social workers and community-based organizations (CBOs), but these pathways have had limited success in connecting patients with resources. Given that health inequity is expected to cost the United States nearly USD 300 billion by 2050, new artificial intelligence (AI) technology may aid providers in addressing SDOH. In this commentary, we present our experience with using ChatGPT to obtain SDOH management recommendations for archetypal patients in Philadelphia, PA. ChatGPT identified relevant SDOH resources and provided contact information for local organizations. Future exploration could improve AI prompts and integrate AI into electronic medical records to provide healthcare providers with real-time SDOH recommendations during appointments. Full article

Batteryless, self-sustaining embedded sensing devices are key enablers for scalable and long-term operations of Internet of Things (IoT) applications. While advancements in both energy harvesting and intermittent computing have helped pave the way for building such batteryless IoT devices, a present challenge is a system design that can utilize intermittent energy to meet data requirements from IoT applications. In this paper, we take the requirement of periodic data sensing and describe the hardware and software of a batteryless IoT device with its model, design, implementation, and evaluation. A key finding is that, by estimating the non-linear hardware charging and discharging time, the device software can make scheduling decisions that both maintain the selected sensing period and improve transmission goodput. A hardware–software prototype was implemented using an MSP430 development board and LoRa radio communication technology. The proposed design was empirically compared with one that does not consider the non-linear hardware characteristics. The result of the experiments illustrated the nuances of the batteryless device design and implementation, and it demonstrated that the proposed design can cover a wider range of feasible sensing rates, which reduces the restriction on this parameter choice. It was further demonstrated that, under an intermittent supply of power, the proposed design could still keep the device functioning as required. Full article

Lithium-ion batteries are widely used in electric vehicles, energy storage power stations, and many other applications. Accurate and reliable monitoring of battery health status and remaining capacity is the key to establish a lithium-ion cell management system. In this paper, based on a Bayesian optimization algorithm, a deep neural network is structured to evaluate the whole charging curve of the battery using partial charging curve data as input. A 0.74 Ah battery is used for experiments, and the effect of different input data lengths is also investigated to check the high flexibility of the approach. The consequences show that using only 20 points of partial charging data as input, the whole charging profile of a cell can be exactly predicted with a root-mean-square error (RMSE) of less than 19.16 mAh (2.59% of the nominal capacity of 0.74 Ah), and its mean absolute percentage error (MAPE) is less than 1.84%. In addition, critical information including battery state-of-charge (SOC) and state-of-health (SOH) can be extracted in this way to provide a basis for safe and long-lasting battery operation. Full article

Cerebrospinal fluid analysis is an important diagnostic test when assessing a neurological canine patient. For this analysis, the total nucleated cell count and differential cell counts are routinely taken, but both involve time-consuming manual methods. To investigate faster automated methods, in this study, the Sysmex XN-V body fluid mode and the deep-learning-based algorithm generated by the Olympus VS200 slide scanner were compared with the manual methods in 161 canine cerebrospinal fluid samples for the total nucleated cell count and in 65 samples with pleocytosis for the differential counts. Following incorrect gating by the Sysmex body fluid mode, all samples were reanalyzed with manually set gates. The Sysmex body fluid mode then showed a mean bias of 15.19 cells/μL for the total nucleated cell count and mean biases of 4.95% and −4.95% for the two-part differential cell count, while the deep-learning-based algorithm showed mean biases of −7.25%, −0.03% and 7.27% for the lymphocytes, neutrophils and monocytoid cells, respectively. Based on our findings, we propose that the automated Sysmex body fluid mode be used to measure the total nucleated cell count in canine cerebrospinal fluid samples after making adjustments to the predefined settings from the manufacturer. However, the two-part differential count of the Sysmex body fluid mode and the deep-learning-based algorithm require some optimization. Full article

Newcastle disease (ND) is a significant infectious disease in poultry, causing substantial economic losses in developing countries. To control ND, chickens must be vaccinated multiple times a year. In order to develop an improved vaccine that provides long-term protection, the F gene from genotype VII NDV was inserted into the herpesvirus of turkey (HVT) vaccine virus using CRISPR/Cas9-mediated NHEJ repair and Cre/LoxP technology. The immunogenicity and protective efficacy of the resulting recombinant vaccines were evaluated through antibody assays and virus challenge experiments. Two recombinant vaccines, rHVT-005/006-F and rHVT-US2-F, were generated, both exhibiting growth rates comparable with those of HVT in vitro and consistently expressing the F protein. One-day-old specific pathogen-free (SPF) chickens immunized with 2000 PFU/bird of either rHVT-005/006-F or rHVT-US2-F developed robust humoral immunity and were completely protected against challenge with the NDV F48E8 strain at 4 weeks post-vaccination (wpv). Furthermore, a single dose of these vaccines provided sustained protection for at least 52 wpv. Our study identifies rHVT-005/006-F and rHVT-US2-F as promising ND vaccine candidates, offering long-term protection with a single administration. Moreover, HVT-005/006 demonstrates promise for accommodating additional foreign genes, facilitating the construction of multiplex vaccines. Full article

RSV infection causes severe respiratory illness and mortality in the elderly, especially in the presence of comorbidities. Early identification of infection would result in appropriate clinical-therapeutic management, avoiding hospitalizations, the risk of healthcare-associated infections, and inappropriate antibiotic prescriptions, thus reducing healthcare costs and fighting antimicrobial resistance. The aim of this study was to assess RSV hospitalizations in subjects >64 years hospitalized in a large tertiary care hospital in Southern Italy, in order to assess their usefulness as a proxy for targeting a potential vaccination strategy. Fifty-two RSV-positive patients were identified from the 2014–2015 to the 2022–2023 seasons. RSV type B was found in 71.2% of cases. The median age was 78 years (IQR: 72–84) and 40.4% of the subjects had at least one comorbidity; 5.8% needed intensive care. The use of combined rapid tests for SARS-CoV-2/influenza/RSV identification in primary care settings may contribute to an improved definition of the burden of RSV in the elderly. The implementation of an anti-RSV vaccination strategy in the elderly population would reduce direct and indirect infection costs. More robust epidemiological data in Italy are needed for targeted preventive strategies. Full article

Situated within the context of a soft ground foundation at an iron ore mining site, this study investigates the impact of substantial surcharges on the settlement of such foundations and the adjacent infrastructure. By employing the finite-difference numerical software FLAC3D 6.0, a series of three-dimensional simulations were conducted to assess the stress response and deformation of gallery pile foundations, shallow foundations, and mine shed pile foundations to step loading. This study integrates the analysis of soil strength augmentation under considerable stress and its attenuation characteristics under significant deformation. Various reinforcement measures, such as the implementation of stone columns, prefabricated vertical drain, and surcharge preloading techniques, were examined for their capacity to consolidate the foundation, reduce settlement, and mitigate impacts on adjacent structures. The results reveal that horizontal displacements in the pile and shallow foundations escalate progressively with additional surcharge throughout the operational period. The most pronounced horizontal deviation in the pile foundations is observed at the juncture between sand and silt strata. Stone columns act effectively as a barrier to the sliding surface, consequently reducing the influence of surcharge on the movement of the foundation. Full article