Search Results (152)

As fundamental units of forest ecosystems, individual trees provide essential structural characteristics for forest resource assessment. However, existing LiDAR-based individual tree segmentation methods are often limited by a trade-off between information preservation and computational efficiency. This study proposes a novel framework for individual tree segmentation from LiDAR data based on canopy surface points (CSP), aiming to balance this trade-off. The framework introduces a Snow-Covered Filter (SCF) that simulates snow deposition to extract surface points from the point cloud. After removing ground points from these surface points, the resulting CSP retains the core 3D structure of the canopy while significantly reducing data volume. We validate the proposed framework on four multi-platform datasets using four algorithms that represent the evolution of individual tree segmentation methods: Dalponte2016, K-means, Li2012, and SegmentAnyTree. The results demonstrate that: (a) the SCF effectively extracts surface points, with an average F1-score of 0.703; (b) segmentation using CSP achieves accuracy comparable to that obtained using all points or raster data (mean ΔF = 0.027), with the primary gap observed for SegmentAnyTree (maximum F-score reduction of 0.259); (c) the framework offers substantial efficiency gains: >40% point reduction, ~38.4% average runtime reduction (maximum saving ~4660 s), and lower memory consumption. By providing a lightweight yet structurally rich data representation, this work presents an innovative and efficient approach to individual tree segmentation, with promising potential for large-scale forest resource management. Full article

Millions of people across rural and peri-urban regions worldwide remain exposed to unsafe concentrations of naturally occurring fluoride in groundwater. In West Bengal, India, community-level water purification plants (CWPPs) have been widely installed to remove excess fluoride, yet their long-term operational performance remains minimally documented. This study assessed the pre-filter and post-filter water quality of 58 such groundwater-based CWPPs across the fluoride-affected districts of Bankura and Purulia in West Bengal, to evaluate in-field fluoride removal performance and potential hydrogeochemical, operational, and management drivers. Evaluation included fluoride concentration and key physicochemical parameters such as pH, temperature, electrical conductivity (EC), oxidation-reduction potential (ORP), total dissolved solids (TDS), and other anions including bromide, chloride, bicarbonate, nitrite, nitrate, phosphate, and sulphate. Fluoride concentration ranged from 1.7 mg/L to 8.2 mg/L and 1.6 mg/L to 3.9 mg/L in the sampled source water of Bankura and Purulia respectively, with both pre- and post-filter water of all the observed treatment units exceeding the WHO guideline of 1.5 mg/L. Potential contributors to underperformance may include inappropriate filter media selection, insufficient backwashing and regeneration, limited operational oversight and/or non-tailored treatment approaches. However, details on the adsorbent media and operational details were not available, and thus findings reflect observed field performance rather than necessarily causal relationships. These operational insights will contribute to the global discussion on improving decentralized groundwater treatment systems in resource-constrained settings. Full article

Submerged aquatic macrophytes and their microbiomes can help mitigate eutrophication, yet how microbial communities and functions differ across specific plant-associated and surrounding niches remains unclear. Here, we profiled bacterial community composition (16S rRNA gene sequencing) and quantified nitrogen and phosphorus cycling genes (narG, nirK, nirS, nosZ, phoD by qPCR) across eight distinct compartments associated with the submerged macrophyte Hydrilla verticillata in a eutrophic freshwater wetland. The niches spanned open water, bulk sediment, rhizosphere, and plant phyllosphere (leaf/stem surfaces) and endosphere (leaf/stem/root interiors). Alpha diversity differed significantly among niches: sediments (non-rhizosphere and rhizosphere) exhibited the highest Operational Taxonomic Unit (OTU) richness and diversity, whereas leaf-associated niches (phyllosphere and endosphere) had the lowest. Beta diversity showed clear separation by niche, indicating strong habitat filtering. Community composition also varied markedly: the water column was dominated by Bacteroidota (~51% of sequences), plant-associated communities were enriched in Pseudomonadota (43–90%), and sediment niches were dominated by Firmicutes (23~48%). Functional gene abundances showed pronounced niche partitioning. Nitrate/nitrite reduction genes (narG, nirK, nirS) were most enriched on leaf phyllosphere, with narG abundance equally high in the water, whereas the N₂O reductase gene nosZ peaked in sediment niches. The alkaline phosphatase gene phoD had its highest copy numbers in leaf biofilms, with significantly lower levels in internal plant tissues. Overall, neutral processes explained ~61% of community variation, but deterministic assembly was evident in the well-connected water and leaf surface niches. These findings reveal strong niche differentiation in plant-associated microbiomes and suggest that compartmentalized microbial functional capacity within the H. verticillata holobiont enhances nitrogen removal and phosphorus cycling in eutrophic waters. Full article

The Intelligent Road Side Unit (RSU) is a crucial component of Intelligent Transportation Systems (ITSs), where roadside LiDAR are widely utilized for their high precision and resolution. However, water droplets and atmospheric particles in fog significantly attenuate and scatter LiDAR beams, posing a challenge to multi-target tracking and ITS safety. To enhance the accuracy and reliability of RSU-based tracking, a collaborative RSU method that integrates denoising and tracking for multi-target tracking is proposed. The proposed approach first dynamically adjusts the filtering kernel scale based on local noise levels to effectively remove noisy point clouds using a modified bilateral filter. Subsequently, a multi-RSU cooperative tracking framework is designed, which employs a particle Probability Hypothesis Density (PHD) filter to estimate target states via measurement fusion. A multi-target tracking system for intelligent RSUs in Foggy scenarios was designed and implemented. Extensive experiments were conducted using an intelligent roadside platform in real-world fog-affected traffic environments to validate the accuracy and real-time performance of the proposed algorithm. Experimental results demonstrate that the proposed method improves the target detection accuracy by 8% and 29%, respectively, compared to statistical filtering methods after removing fog noise under thin and thick fog conditions. At the same time, this method performs well in tracking multi-class targets, surpassing existing state-of-the-art methods, especially in high-order evaluation indicators such as HOTA, MOTA, and IDs. Full article

Control of elbow exoskeletons using muscular signals, although promising for the rehabilitation of millions of patients, has not yet been widely commercialized due to challenges in real-time intention estimation and management of dynamic uncertainties. From a practical perspective, millions of patients with stroke, spinal cord injury, or neuromuscular disorders annually require active rehabilitation, and elbow exoskeletons with precise and safe motion intention tracking capabilities can restore functional independence, reduce muscle atrophy, and lower treatment costs. In this research, an intelligent control framework was developed for an elbow joint exoskeleton, designed with the aim of precise and safe real-time tracking of the user’s motion intention. The proposed framework consists of two main stages: (a) real-time estimation of desired joint angle (as a proxy for movement intention) from High-Density Surface Electromyography (HD-sEMG) signals using an LSTM network and (b) implementation and comparison of three PID, impedance, and sliding mode controllers. A public EMG dataset including signals from 12 healthy individuals in four isometric tasks (flexion, extension, pronation, supination) and three effort levels (10, 30, 50 percent MVC) is utilized. After comprehensive preprocessing (Butterworth filter, 50 Hz notch, removal of faulty channels) and extraction of 13 time-domain features with 99 percent overlapping windows, the LSTM network with optimal architecture (128 units, Dropout, batch normalization) is trained. The model attained an RMSE of 0.630 Nm, R² of 0.965, and a Pearson correlation of 0.985 for the full dataset, indicating a 47% improvement in R² relative to traditional statistical approaches, where EMG is converted to desired angle via joint stiffness. An assessment of 12 motion–effort combinations reveals that the sliding mode controller consistently surpassed the alternatives, achieving the minimal tracking errors (average RMSE = 0.21 Nm, R² ≈ 0.96) and showing superior resilience across all tasks and effort levels. The impedance controller demonstrates superior performance in flexion/extension (average RMSE ≈ 0.22 Nm, R² > 0.94) but experiences moderate deterioration in pronation/supination under increased loads, while the classical PID controller shows significant errors (RMSE reaching 17.24 Nm, negative R² in multiple scenarios) and so it is inappropriate for direct myoelectric control. The proposed LSTM–sliding mode hybrid architecture shows exceptional accuracy, robustness, and transparency in real-time intention monitoring, demonstrating promising performance in offline simulation, with potential for real-time clinical applications pending hardware validation for advanced upper-limb exoskeletons in neurorehabilitation and assistive applications. Full article

In the context of micro-polluted water sources, the performance decline of filtration units is a major challenge for the operational management of water supply plants. Therefore, it is necessary to systematically analyze the mechanism underlying the decline in filter media activity and optimize the pre-filtration treatment. This study focuses on waterworks, aiming to enhance filtration performance through filter media modification and a combined coagulant-oxidant strategy. A key innovation of this work is the development of a macro-microscopic correlation evaluation system. The results showed that the modified filter media increased the turbidity removal rate by 10.48% compared to the unmodified media. Furthermore, the combined coagulation–pre-oxidation scheme increased the removal rates for turbidity and UV₂₅₄ by 3.24% and 19.03%, respectively, compared to the single-process scheme. Combined with filter media characterization results, the deactivation mechanism of filter media can be inferred. During the high-algae period, microorganisms on the filter media generate anaerobic Extracellular Polymeric Substances (EPS), which form a biofilm with bacteria and adhere to the filter media. The viscous matrix of these EPS then encapsulates inorganic substances, resulting in hard-to-remove clumps. These clumps clog pores and hinder the adsorption of subsequent pollutants, ultimately leading to continuous deterioration in filter media performance until failure. Full article

Background: Septic shock remains a critical challenge with high mortality, particularly in refractory cases requiring high doses of vasopressors. Hemoadsorption with the oXiris^® membrane, capable of simultaneously removing endotoxins, cytokines, and damage-associated molecular patterns (DAMPs), represents a personalized therapeutic strategy targeting the underlying pathophysiology. However, clinical evidence on its impact remains limited and lacks consensus. This study aims to analyze the effects of oXiris^® therapy on hemodynamic, inflammatory, and perfusion parameters in a real-world cohort of patients with septic shock. Methods: We conducted a retrospective cohort study in a surgical Intensive Care Unit (ICU) at a tertiary hospital, including 45 adult patients with septic shock treated with continuous renal replacement therapy using the oXiris^® membrane for at least 48 h. The institutional protocol involved filter changes at least every 24 h during the first 48 h of therapy. Hemodynamic variables, vasopressor doses, and biochemical markers were collected at baseline (T0), 24 h (T1), and 48 h (T2). The primary objective was to describe the evolution of these parameters. Secondary objectives included analysis of 30-day mortality and identification of prognostic factors. Results: The cohort consisted of 45 patients (80.0% male, median age 71 years), with a predominance of abdominal infectious focus (71.1%). A significant reduction in median norepinephrine requirements was observed from T0 to T2 (p < 0.00001), along with a significant increase in mean arterial pressure (MAP) (p < 0.00001). Key markers of perfusion and inflammation also improved, with a significant decrease in arterial lactate (p < 0.00001) and procalcitonin (p = 0.00082) at 48 h. No significant changes were observed in the Sequential Organ Failure Assessment (SOFA) score. The observed mortality rate in the ICU was 31.1%, lower than the median predicted mortality by Simplified Acute Physiology Score II (SAPS II) (37%). Baseline Charlson Comorbidity Index (CCI), creatinine, arterial lactate, and SOFA score were independent predictors of mortality. Conclusions: In this cohort of septic shock patients, therapy with oXiris^®, applied with a frequent filter exchange protocol, was associated with a significant reduction in vasopressor requirements and an improvement in key hemodynamic, perfusion, and inflammatory markers. The observed ICU mortality was lower than predicted by severity scores. These findings support the role of oXiris^® as a personalized adjuvant therapy in specific septic shock phenotypes and underscore the need for prospective randomized trials to confirm these benefits. Full article

This paper presents the design, development, and evaluation of an embedded hardware and digital signal processing (DSP)-based real-time gesture-controlled system. The system architecture utilizes an MPU6050 inertial measurement unit (IMU), Arduino Uno microcontroller, and Python-based audio interface to recognize and classify directional hand gestures and transform them into auditory commands. Wrist tilts, i.e., left, right, forward, and backward, are recognized using a hybrid algorithm that uses thresholding, moving average filtering, and low-pass smoothing to remove sensor noise and transient errors. Hardware setup utilizes I²C-based sensor acquisition, onboard preprocessing on Arduino, and serial communication with a host computer running a Python script to trigger audio playing using the playsound library. Four gestures are programmed for basic needs: Hydration Request, Meal Support, Restroom Support, and Emergency Alarm. Experimental evaluation, conducted over more than 50 iterations per gesture in a controlled laboratory setup, resulted in a mean recognition rate of 92%, with system latency of 120–150 milliseconds. The approach has little calibration costs, is low-cost, and offers low-latency performance comparable to more advanced camera-based or machine learning-based methods, and is therefore suitable for portable assistive devices. Full article

Methane, a greenhouse gas which has a global warming potential 80 times greater than carbon dioxide on a 20-year time scale, greatly contributes to global warming. Removing 1 Gt of atmospheric methane by 2050 would limit global temperature increase from reaching 1.5 °C. Currently, biotrickling filter systems for removing atmospheric methane via methanotrophs exist, but not for very low methane concentrations (<1 v%). Recent work at the University of Washington to isolate and improve a microbial strain which thrives at 500 ppmv CH₄ has removed one obstacle in making this technology feasible. In this study, techno-economic and environmental life cycle assessment analyses conducted on this process have assessed its economic feasibility, greenhouse gas reduction potential, and possible areas of improvement. Study results show that at 500 ppmv CH₄, this process could remove atmospheric methane at a cost of USD 3992–5224/tCH₄. The best-performing case also produces annual net reductions in warming potential by 276–311 tCO₂e/120 m³ process unit deployed. Many opportunities exist to improve the outcomes of the baseline analysis even further, especially related to reducing the transport distance of media and harvested biomass. Full article

Background: Severe acute pancreatitis (SAP) presents with Multiple Organ Dysfunction Syndrome (MODS) in ~15% of cases, accounting for ~35% of early deaths within 48 h. Major complications—shock, renal failure, and respiratory insufficiency—arise from an overwhelming systemic inflammatory response driven by markedly elevated pro-inflammatory cytokines. Massive release of IL-2, IL-6, and TNF-α underlies the systemic inflammatory response syndrome (SIRS). Continuous veno-venous hemofiltration (CVVH) with the oXiris filter, adsorbing endotoxins and cytokines, has been used in sepsis and applied early in SAP to reduce cytokine load and organ injury. Aims: To evaluate the efficacy and safety of early CVVH with the oXiris filter in modulating the systemic inflammatory response by removing toxic cytokines from the bloodstream in patients with SAP complicated by organ dysfunction and refractory sepsis. Methods: This single-centre, retrospective, observational study was conducted at a tertiary university hospital between 2000 and 2022. Forty-eight consecutive patients with SAP at onset, defined according to the 2012 Atlanta Classification, with an APACHE II score ≥ 19 and persistent organ dysfunction (>48 h), were included. All patients were unresponsive to initial intensive care within the first 24 h and underwent urgent laparotomy with extensive peritoneal lavage, pancreatic necrosectomy, and placement of multiple abdominal drains, followed by transfer to the intensive care unit. CVVH (Prismax system) with the oXiris filter was initiated within 12 h post-surgery. IL-6 and TNF-α were selected as inflammatory markers and measured in both serum and ultrafiltrate at baseline (0 h) and at 24, 48, 72, and 96 h. These measurements were correlated with clinical parameters and prognostic scores (APACHE II, SOFA). Results: Treatment was well tolerated in all patients. The 28-day survival rate was 97.9%. There was a significant time-dependent decrease in IL-6 (p = 0.019) and TNF-α (p = 0.008) concentrations in the ultrafiltrate, consistent with high early adsorption followed by a reduced cytokine burden, whereas serum levels showed a non-significant downward trend (IL-6 p = 0.08; TNF-α p = 0.310). The APACHE II score decreased from 23 postoperatively to 8 by the second week (−65.2%; p = 0.013), with a statistically significant correlation between cytokine reduction and clinical improvement. Adverse events were rare and manageable. Conclusions: Early CVVH with the oXiris filter in SAP, complicated by MODS and refractory sepsis, proved safe, well-tolerated, and potentially effective in reducing cytokine burden and improving prognostic indices. These findings support the hypothesis of a relevant immunomodulatory effect, warranting prospective controlled trials to confirm its true impact on survival and organ recovery. Full article

Sludge dewatering remains a resource-intensive process, often constrained by high residual moisture content and inefficient chemical conditioning. Conventional systems typically rely on fixed polymer dosages and predetermined filtration pressures, which are unable to respond to variations in sludge characteristics, resulting in inconsistent and suboptimal performance. In this study, a real-time control system for municipal wastewater sludge dewatering was developed to dynamically regulate coagulant dosing and filtration pressure based on continuous monitoring of critical sludge parameters, including total solids (TS), viscosity, sludge temperature, and pH change following coagulant addition. The control logic, derived from empirical correlations between sludge dewaterability metrics such as time-to-filter (TTF) and capillary suction time (CST) and operational variables, enables adaptive adjustment of polyoxyethylene alkyl ether (POAE) injection and pressing conditions. Implementation of this system achieved a final cake moisture content of approximately 63% after 60 min of filtration, substantially lower than the ~84% moisture observed under static conditions. Real-time flux feedback facilitated timely pressure escalation (from 15 to 20 bar to 25–30 bar), improving water removal efficiency while avoiding premature cake blinding. The pH drop (~0.7 units) post-polymer addition served as a practical indicator of adequate flocculation, supporting dose optimization and minimizing chemical waste. The proposed system demonstrated enhanced dewatering performance, reduced polymer consumption, and greater operational robustness compared to conventional approaches. These findings highlight the potential of integrated sensor-based control to advance sludge treatment technologies by promoting smarter, adaptive, and resource-efficient dewatering operations. Full article

Bioethanol from sugarcane bagasse is a promising second-generation biofuel due to its abundance as a sugar industry by-product. Herein, enzymatic hydrolysate obtained from sugarcane bagasse pretreated with optimized hydrothermal alkaline sulfite (HAS) was evaluated for its fermentability using Saccharomyces cerevisiae PE-2 and Scheffersomyces stipitis CBS 5773. The HAS pretreatment achieved a high delignification rate (63%), resulting in a cellulose- and hemicellulose-enriched substrate (55% and 27%, respectively). While the cellulose content remained relatively constant, hemicellulose content was reduced by 25%, with significant removal of acetyl groups (80%) and arabinan groups (39%). The pretreated bagasse exhibited high digestibility, applying 10 FPU (filter paper unit) cellulase together with 10 CBU (cellobiose unit) β-glucosidase per gram of dry bagasse in the hydrolysis step, yielding 72% glucan and 66% xylan conversion within 72 h. The resulting hydrolysate was efficiently fermented by S. cerevisiae and S. stipitis, achieving ethanol yields of 0.51 and 0.43 g/g of sugars, respectively. The fermentation kinetics were comparable to those observed in a synthetic medium containing pure sugars, demonstrating the effectiveness of HAS pretreatment in generating readily fermentable, carbohydrate-rich substrates. HAS pretreatment enabled improved conversion of sugarcane bagasse into fermentation-ready sugars, constituting a potential resource for bioethanol synthesis applying both S. cerevisiae and S. stipitis in the future. Full article

This study investigates the subsurface rooting of the Merija anticline in the Missour Basin, Morocco, with a focus on copper mineralization exploration. A sequential geophysical workflow was implemented, combining gravity surveys, electrical resistivity (ER), and induced polarization (IP) methods. The gravity data, acquired along spaced profiles extending from outcropping areas to Quaternary-covered zones, clearly delineated the structural continuity of the anticline beneath the cover. The application of trend filtering in covered areas allowed the removal of regional effects, successfully isolating residual anomalies associated with the buried continuation of the anticline. Interpolated Bouguer anomaly maps highlighted a major regional fault, interpreted as controlling the deep rooting of the anticline. A resistivity profile was then deployed perpendicular to this fault, providing detailed imaging of the anticline’s geometry and lithological contrasts. Complementary IP profiles conducted near the mine site targeted the detection of chargeability anomalies associated with copper mineralization dominated by malachite, confirming the electrical signature of copper mineralization, particularly within the sandstone and conglomerate formations of the Lower Cretaceous. To validate the geophysical interpretations, a drilling campaign was conducted, which confirmed the presence of the identified lithological units and the anticline rooting, as revealed by geophysical data. This approach provides a robust framework for copper exploration in the Merija area and can be adapted to similar geological contexts elsewhere. Full article

Background: Patients in Intensive Care Units (ICUs) often develop non-thyroidal illness syndrome. Potentially, thyroid hormones may be removed during continuous veno-venous hemodiafiltration (CVVHDF), as their molecular size is smaller than the filter pores’ cutoff. The study’s main aim was to assess whether the serum concentration of thyroid hormones changes over time during CVVHDF. Methods: This was a prospective observational trial that included 30 patients treated in an ICU. All patients developed acute kidney injury (AKI) and had clinical indications for implementation of CVVHDF. Blood samples were collected before initiation of CVVHDF and at 1, 2, 3, 6, 9 and 12 days after. The last sample was collected three days after CVVHDF withdrawal. Thyroid function was evaluated by determining the serum concentration of TSH, thyrotropin-releasing hormone (TRH), free triiodothyronine (fT₃), free thyroxine (fT₄), total triiodothyronine (tT₃), total thyroxine (tT₄) and reverse triiodothyronine (rT₃). We additionally calculated the total activity of peripheral deiodinases (G_D) using a mathematical model. Results: TRH and TSH levels remained mostly within normal ranges. fT4 and tT4 were in normal range or slightly below. In contrast, fT3 and tT3 were undetectably low in most patients throughout. Reverse T3 levels remained within normal limits. There were no statistically significant changes in any thyroid hormone levels over the CVVHDF treatment period. The calculated peripheral G_D activity was lower than normal, but importantly, it did not change significantly over time. Conclusions: Thyroid hormones are not lost due to hemodiafiltration. Decreased deiodinases activity is responsible for alterations in serum concentrations of thyroid hormones in patients during CVVHDF. Full article

Deep drilling and horizontal wells, as important means of unconventional oil and gas development, face problems with the high energy consumption but low removal efficiency of traditional well washing equipment, the uneven cleaning of horizontal well intervals, and an insufficient degree of automation. This paper proposes a novel hydraulic drive well washing device which consists of two main units. The wellbore cleaning unit comprises a hydraulic drive cutting–flushing module, a well cleaning mode-switching module, and a filter storage module. The unit uses hydraulic and mechanical forces to perform combined cleaning to prevent mud and sand from settling. By controlling the flow direction of the well washing fluid, it can directly switch between normal and reverse washing modes in the downhole area, and at the same time, it can control the working state of corresponding modules. The assembly control unit includes the chain lifting module and the arm assembly module, which can lift and move the device through the chain structure, allow for the rapid assembly of equipment through the use of a mechanical arm, and protect the reliability of equipment through the use of a centering structure. The device converts some of the hydraulic power into mechanical force, effectively improving cleaning and plugging removal efficiency, prolonging the downhole continuous working time of equipment, reducing manual operation requirements, and comprehensively improving cleaning efficiency and energy utilization efficiency. Full article