The surge in opioid use disorder (OUD) over the past decade escalated opioid overdoses to a leading cause of death in the United States. With adverse effects on cognition, risk-taking, and decision-making, OUD may negatively influence financial well-being. This study examined the financial health of individuals diagnosed with OUD by reviewing financial beliefs and financial behaviors. We evaluated quality of life, perceptions of financial condition during active use and recovery, and total debt. We distributed a 20-item survey to 150 individuals in an outpatient treatment program for OUD in a large metropolitan area, yielding a 56% response rate. The results revealed low overall financial health, with a median debt of USD 12,961 and a quality-of-life score of 72.80, 9.4% lower than the U.S. average (82.10). Most participants (65.75%) reported improved financial health during recovery, while a higher majority (79.45%) worsened during active use. Unemployment affected 42% of respondents, and 9.52% were employed only part-time. Regression analysis highlighted a strong association between lack of full-time employment and a lack of financial advising with total debt. High financial anxiety and active use were associated with lower quality of life. Individuals with OUD may benefit from financial interventions, resources, and counseling to improve their financial health. Full article

The study of dynamic singularity formation in spacetime, focusing on scalar field collapse models, is analyzed. We revisit key findings regarding open spatial topologies, concentrating on minimal conditions necessary for singularity and apparent horizon formation. Moreover, we examine the stability of initial data in the dynamical system governed by Einstein’s equations, considering variations in parameters that influence naked singularity formation. We illustrate how these results apply to a family of scalar field models, concluding with a discussion on the concept of genericity in singularity studies. Full article

Glioblastoma (GBM) is the most common malignancy of the central nervous system in adults. GBM has high levels of therapy failure and its prognosis is usually dismal. The phenotypic heterogeneity of the tumor cells, dynamic complexity of non-tumor cell populations within the GBM tumor microenvironment (TME), and their bi-directional cross-talk contribute to the challenges of current therapeutic approaches. Herein, we discuss the etiology of GBM, and describe several major types of non-tumor cells within its TME, their impact on GBM pathogenesis, and molecular mechanisms of such an impact. We also discuss their value as potential therapeutic targets or prognostic biomarkers, with reference to the most recent works on this subject. We conclude that unless all “key player” populations of non-tumor cells within the TME are considered, no breakthrough in developing treatment for GBM can be achieved. Full article

Photovoltaic (PV) power forecasting plays a crucial role in optimizing renewable energy integration into the grid, necessitating accurate predictions to mitigate the inherent variability of solar energy generation. We propose a novel forecasting model that combines improved variational mode decomposition (IVMD) with the temporal convolutional network-gated recurrent unit (TCN-GRU) architecture, enriched with a multi-head attention mechanism. By focusing on four key environmental factors influencing PV output, the proposed IVMD-TCN-GRU framework targets a significant research gap in renewable energy forecasting methodologies. Initially, leveraging the sparrow search algorithm (SSA), we optimize the parameters of VMD, including the mode component K-value and penalty factor, based on the minimum envelope entropy principle. The optimized VMD then decomposes PV power, while the TCN-GRU model harnesses TCN’s proficiency in learning local temporal features and GRU’s capability in rapidly modeling sequence data, while leveraging multi-head attention to better utilize the global correlation information within sequence data. Through this design, the model adeptly captures the correlations within time series data, demonstrating superior performance in prediction tasks. Subsequently, the SSA is employed to optimize GRU parameters, and the decomposed PV power mode components and environmental feature attributes are inputted into the TCN-GRU neural network. This facilitates dynamic temporal modeling of multivariate feature sequences. Finally, the predicted values of each component are summed to realize PV power forecasting. Validation using real data from a PV station corroborates that the novel model demonstrates a substantial reduction in RMSE and MAE of up to 55.1% and 54.5%, respectively, particularly evident in instances of pronounced photovoltaic power fluctuations during inclement weather conditions. The proposed method exhibits marked improvements in accuracy compared to traditional PV power prediction methods, underscoring its significance in enhancing forecasting precision and ensuring the secure scheduling and stable operation of power systems. Full article

Efficient resource allocation is crucial in clusters with frugal Single-Board Computers (SBCs) possessing limited computational resources. These clusters are increasingly being deployed in edge computing environments in resource-constrained settings where energy efficiency and cost-effectiveness are paramount. A major challenge in Hadoop scheduling is load balancing, as frugal nodes within the cluster can become overwhelmed, resulting in degraded performance and frequent occurrences of out-of-memory errors, ultimately leading to job failures. In this study, we introduce an Adaptive Multi-criteria Selection for Efficient Resource Allocation (AMS-ERA) in Frugal Heterogeneous Hadoop Clusters. Our criterion considers CPU, memory, and disk requirements for jobs and aligns the requirements with available resources in the cluster for optimal resource allocation. To validate our approach, we deploy a heterogeneous SBC-based cluster consisting of 11 SBC nodes and conduct several experiments to evaluate the performance using Hadoop wordcount and terasort benchmark for various workload settings. The results are compared to the Hadoop-Fair, FOG, and IDaPS scheduling strategies. Our results demonstrate a significant improvement in performance with the proposed AMS-ERA, reducing execution time by 27.2%, 17.4%, and 7.6%, respectively, using terasort and wordcount benchmarks. Full article

This study offers, by an empirical analysis, another perspective on post-socialist development, highlighting the role of the urban–rural interface in regional dynamics. The current literature on the relationships between both issues is not too rich and our paper analyzes the relationships between core cities, their peri-urban areas, and their regions, through a comparative overview of their growth over the last three decades. Romania, as a special case study for a contradictory transition, due to the great step from a drastic dictatorial regime to a democracy and a market economy, is a good example to test these complex relationships. Considering the new development trend at the urban–rural interfaces, our key idea was to depict their contribution to regional development (NUTS 3) compared to city cores. The second question was how this differentiated contribution can be measured, using the simplest tool. The starting point was the fact that population dynamics reflect all changes in the city core and at the urban–rural interface, and less so at a regional level. Consequently, we selected the dynamics of the number of inhabitants for the first two, as well as the dynamics of GDP per capita at the regional level. We found higher and significant correlations between GDP per capita and urban–rural interfaces, but no significant correlations in the case of city cores. Our conclusion is that, in the transition period, the dynamics of urban–rural interfaces influenced more regional development dynamics, than those of city cores. This means that urban–rural interfaces amplify the development coming from cities, adding their own contribution and then dissipating it regionally. Future research should identify what the urban–rural interface offers to regions, in addition to the city core. Full article

Different factors, not limited to the lung, influence the progression of ILDs. A “treatable trait” strategy was recently proposed for ILD patients as a precision model of care to improve outcomes. However, no data have been published so far on the prevalence of TTs in ILD. A prospective, observational, cohort study was conducted within the ILD Program at the IRCCS Humanitas Research Hospital (Milan, Italy) between November 2021 and November 2023. TTs were selected according to recent literature and assigned during multidisciplinary discussion (MDD) to one of the following categories: pulmonary, etiological, comorbidities, and lifestyle. Patients were further divided into four groups according to their post-MDD diagnosis: idiopathic ILD, sarcoidosis, connective tissue disease–ILD, and other ILD. The primary study outcome was the prevalence of each TT in the study population. A total of 116 patients with ILD [63.9% male; median (IQR) age: 69 (54–78) years] were included in the study. All the TTs identified in the literature were found in our cohort, except for intractable chronic cough. We also recognized differences in TTs across the ILD groups, with less TTs in patients with sarcoidosis. This analysis provides the first ancillary characterization of TTs in ILD patients in a real setting to date. Full article

A breakthrough “Green Revolution” in rice enhanced lodging resistance by using gibberellin-deficient semi-dwarf varieties. However, the gibberellic acid (GA) signaling regulation on rice disease resistance remains unclear. The resistance test showed that a positive GA signaling regulator DWARF1 mutant d1 was more susceptible while a negative GA signaling regulator Slender rice 1 (SLR1) mutant was less susceptible to sheath blight (ShB), one of the major rice diseases, suggesting that GA signaling positively regulates ShB resistance. To isolate the regulator, which simultaneously regulates rice lodging and ShB resistance, SLR1 interactors were isolated. Yeast two-hybrid (Y2H), bimolecular fluorescence complementation (BiFC), and Co-IP assay results indicate that SLR1 interacts with Calcineurin B-like-interacting protein kinase 31 (CIPK31). cipk31 mutants exhibited normal plant height, but CIPK31 OXs showed semi-dwarfism. In addition, the SLR1 level was much higher in CIPK31 OXs than in the wild-type, suggesting that CIPK31 OX might accumulate SLR1 to inhibit GA signaling and thus regulate its semi-dwarfism. Recently, we demonstrated that CIPK31 interacts and inhibits Catalase C (CatC) to accumulate ROS, which promotes rice disease resistance. Interestingly, CIPK31 interacts with Vascular Plant One Zinc Finger 2 (VOZ2) in the nucleus, and expression of CIPK31 accumulated VOZ2. Inoculation of Rhizoctonia solani AG1-IA revealed that the voz2 mutant was more susceptible to ShB. Thus, these data prove that CIPK31 promotes lodging and ShB resistance by regulating GA signaling and VOZ2 in rice. This study provides a valuable reference for rice ShB-resistant breeding. Full article

The purpose of this study was to explore the effects of the integration of machine learning into daily radiological diagnostics, using the example of the machine learning software mdbrain^® (Mediaire GmbH, Germany) in the diagnostic MRI workflow of patients with multiple sclerosis at the University Medicine Greifswald. The data were assessed through expert interviews, a comparison of analysis times with and without the machine learning software, as well as a process analysis of MRI workflows. Our results indicate a reduction in the screen-reading workload, improved decision-making regarding contrast administration, an optimized workflow, reduced examination times, and facilitated report communication with colleagues and patients. Our results call for a broader and quantitative analysis. Full article

Bearings are crucial components of machinery and equipment, and it is essential to inspect them thoroughly to ensure a high pass rate. Currently, bearing scratch detection is primarily carried out manually, which cannot meet industrial demands. This study presents research on the detection of bearing surface scratches. An improved YOLOV5 network, named YOLOV5-CDG, is proposed for detecting bearing surface defects using scratch images as targets. The YOLOV5-CDG model is based on the YOLOV5 network model with the addition of a Coordinate Attention (CA) mechanism module, fusion of Deformable Convolutional Networks (DCNs), and a combination with the GhostNet lightweight network. To achieve bearing surface scratch detection, a machine vision-based bearing surface scratch sensor system is established, and a self-made bearing surface scratch dataset is produced as the basis. The scratch detection final Average Precision (AP) value is 97%, which is 3.4% higher than that of YOLOV5. Additionally, the model has an accuracy of 99.46% for detecting defective and qualified products. The average detection time per image is 263.4 ms on the CPU device and 12.2 ms on the GPU device, demonstrating excellent performance in terms of both speed and accuracy. Furthermore, this study analyzes and compares the detection results of various models, demonstrating that the proposed method satisfies the requirements for detecting scratches on bearing surfaces in industrial settings. Full article

A kind of surface plasmon waveguide composed of two nested cylindrical dielectric parallel nanowire pairs coated with graphene was designed and studied. The dependence of the mode characteristics and the normalized gradient force of the lowest two modes supported by the waveguide on the parameters involved were analyzed by using the multipole method. To ensure rigor, the finite element method was employed to verify the accuracy of the multipole method, thus confirming its results. The results show that the multipole method is a powerful tool for handling this type of waveguide. The real part of the effective refractive index, the propagation length, the figure of merit, and the normalized gradient force can be significantly affected by the operating wavelength, the Fermi energy of graphene, the waveguide geometric parameters, and the refractive index of the inner dielectric nanowire. Due to the employment of nested dielectric nanowire pairs coated with graphene, this waveguide structure exhibits significant gradient force that surpasses 100 nN·μm⁻¹·mW⁻¹. The observed phenomena can be attributed to the interaction of the field with graphene. This waveguide holds promising potential for applications in micro/nano integration, optical tweezers, and sensing technologies. Full article

This paper addresses the optimal sizing of Hybrid Renewable Energy Systems (HRESs), encompassing wind, solar, and battery systems, with the aim of delivering reliable performance at a reasonable cost. The focus is on mitigating unscheduled outages on the national grid in Iraq. The proposed On–off-grid HRES method is implemented using MATLAB and relies on an iterative technique to achieve multi-objectives, balancing reliability and economic constraints. The optimal HRES configuration is determined by evaluating various scenarios related to energy flow management, electricity prices, and land cover effects. Consumer requirements regarding cost and reliability are factored into a 2D optimization process. A battery model is developed to capture the dynamic exchange of energy among different renewable sources, battery storage, and energy demands. A detailed case study across fifteen locations in Iraq, including water, desert, and urban areas, revealed that local wind speed significantly affects the feasibility and efficiency of the HRES. Locations with higher wind speeds, such as the Haditha lake region (payback period: 7.8 years), benefit more than urban areas (Haditha city: payback period: 12.4 years). This study also found that not utilizing the battery, particularly during periods of high electricity prices (e.g., 2015), significantly impacts the HRES performance. In the Haditha water area, for instance, this technique reduced the payback period from 20.1 to 7.8 years by reducing the frequency of charging and discharging cycles and subsequently mitigating the need for battery replacement. Full article

Osteoporosis is the most common metabolic bone disorder and is characterized by decreased bone density, which has a relationship with the quality of life among the aging population. Previous research has found that activation of the dopamine D1 receptor can improve bone mass formation. SKF38393 is an agonist of dopamine D1 receptors. However, as a small-molecule drug, SKF38393 is unstable and releases quickly. The aim of this study was to prototype polylactic-co-glycolic acid (PLGA)/SKF38393 microspheres and assess their potential osteogenic effects compared to those under the free administration of SKF38393. The cytocompatibility of PLGA/SKF38393 was determined via CCK-8 and live/dead cell staining; the osteogenic effects in vitro were determined with ALP and alizarin red staining, qRT-PCR, and Western blotting; and the in vivo effects were assessed using 25 Balb/c mice. We also used a PCR array to explore the possible signaling pathway changes after employing PLGA/SKF38393. Our experiments demonstrated that the osteogenic effect of D1Rs activated by the PLGA/SKF38393 microsphere was better than that under free administration, both in vitro and in vivo. According to the PCR array, this result might be associated with six signaling pathways (graphical abstract). Ultimately, in this study, we prototyped PLGA/SKF38393, demonstrated its effectiveness, and preliminarily analyzed its mechanism of action. Full article

The global increase in the pet trade and ownership of pet birds has heightened the introduction of emerging invasive vertebrate species. We analyzed online databases of lost, found, and sighted non-native pet bird reports in South Africa to evaluate non-native pet bird statuses, investigate geographic patterns, assess species trends, and determine the factors associated with lost pet birds. We identified a total of 1467 case reports representing 77 species across nine families from websites (n = 3) and Facebook pages (n = 13). Most reports of lost birds were within large cities, in populated provinces, including Gauteng, KwaZulu-Natal, and Western Cape. Psittacidae, Psittaculidae, and Cacatuidae were the most dominant families, with African grey (Psittacus erithacus), Cockatiel (Nymphicus hollandicus), and Rose-ringed parakeet (Psittacula krameri) among the top species reported as lost. Lower-priced species were commonly reported as lost, and there was no association between the species’ price and the likelihood of being found. In addition, we found a positive relationship between species reported as lost and the number of pet shops, human population size, species size, and docility. There was a sharp increase in lost cases from 2019 onwards; however, males were more frequently lost. Our findings highlight challenges in regulating and monitoring the pet ownership and trade of non-native pet birds and the need to address commonly kept species in conservation efforts. Online resources can be effective tools for passive surveillance of non-native pet bird species, especially potentially invasive ones. Full article

To establish a responsible business environment, it is important to analyze the way corporate social responsibility (CSR) is implemented within the business world. In this respect, managers play a crucial role in designing and applying the CSR concept and practices. Therefore, this paper aims to identify and analyze the perceptions and attitudes of medium-sized enterprises (SMEs) and multinational companies (MNCs) managers in the Romanian retail sector related to CSR implementation. A documentary research approach and a qualitative research methodology through the use of four focus groups were utilized to fulfill the above-mentioned purpose. Additionally, the authors employed content analysis and Nvivo 14 software to process the collected data. The findings indicate that the size of firms represents a key element of managers’ perceptions and attitudes regarding CSR. Particularly, SME managers have a lower level of familiarity with the concept and the potential advantages for business compared to MNC managers. Furthermore, when it comes to CSR practices, MNCs use a comprehensive approach to meeting the demands of their stakeholders, whereas SMEs prioritize the requirements of their employees. One major obstacle in implementing the CSR concept continues to be the high expenses involved in the businesses. Full article

Cyanobacterial blooms represent a common environmental issue in aquatic systems, and these blooms bring forth numerous hazards, with the generation of volatile organic compounds (VOCs) being one of them. Global climate change has led to alterations in various climatic factors affecting algal growth, indirectly impacting the quantity of VOCs released by algae. With advancements in remote sensing technology, exploration of the spatiotemporal distributions of algae in large water bodies has become feasible. This study focuses on Taihu Lake, characterized by frequent occurrences of cyanobacterial blooms. Utilizing MODIS satellite imagery from 2001 to 2020, we analyzed the spatiotemporal characteristics of cyanobacterial blooms in Taihu Lake and its subregions. Employing the LightGBM machine learning model and the (SHapley Additive exPlanations) SHAP values, we quantitatively analyzed the major meteorological drivers influencing cyanobacterial blooms in each region. VOC-related source spectra and emission intensities from cyanobacteria in Taihu Lake are collected based on the literature review and are used to compile the first inventory of VOC emissions from blue-green algae blooms in Taihu Lake. The results indicate that since the 21st century, the situation of cyanobacterial blooms in Taihu Lake has continued to deteriorate with increasing variability. The relative impact of meteorological factors varies across different regions, but temperature consistently shows the highest sensitivity in all areas. The VOCs released from the algal blooms increase with the proliferation of the blooms, posing a continuous threat to the atmospheric environment of the surrounding cities. This study aims to provide a scientific basis for further improvement of air quality in urban areas adjacent to large lakes. Full article

Acerola (Malpighia emarginata DC.) is a sub-tropical and tropical fruit renowned for its high levels of vitamin C and phenolic compounds, which offer health benefits. This study aimed to optimize the spray drying process by determining the inlet and outlet temperatures using response surface methodology (RSM) with the central composite design. Additionally, it aimed to evaluate the release kinetics in the hydrophilic food simulation environment and the stability of the resulting powder under various storage temperatures. The RSM method determined the optimal inlet and outlet temperatures as 157 °C and 91 °C, respectively. High-accuracy prediction equations (R² ≥ 0.88) were developed for moisture content (3.02%), process yield (91.15%), and the encapsulation yield of total polyphenol content (61.44%), total flavonoid content (37.42%), and vitamin C (27.19%), with a predicted monolayer moisture content below 4.01%, according to the BET equation. The powder exhibited good dissolution characteristics in the acidic hydrophilic food simulation environment and showed greater stability when stored at 10 °C for 30 days, compared to storage at 35 °C and 45 °C. Full article

The rapid spread of Internet of Things technologies has enabled a continuous monitoring of indoor environmental quality in office environments by integrating monitoring devices equipped with low-cost sensors and cloud platforms for data storage and visualization. Critical aspects in the development of such monitoring systems are effective data acquisition, processing, and visualization strategies, which significantly influence the performance of the system both at monitoring device and at cloud platform level. This paper proposes novel strategies to address the challenges in the design of a complete monitoring system for indoor environmental quality. By adopting the proposed solution, one can reduce the data rate transfer between the monitoring devices and the server without loss of information, as well as achieve efficient data storage and aggregation on the server side to minimize retrieval times. Finally, enhanced flexibility in the dashboard for data visualization is obtained, thus enabling graph modifications without extensive coding efforts. The functionality of the developed system was assessed, with the collected data in good agreement with those from other instruments used as references. Full article

Cow dung is a kind of high quality and renewable biological resource. Biochar made from cow dung can be used as a soil amendment to improve soil nutrient status. The relationship between soil water and phosphorus is very close, and the water status determines the form, content, and availability of phosphorus. In order to investigate the effects of biochar on soil inorganic phosphorus components, available phosphorus, enzyme activities related to the phosphorus cycle, microbial functional genes, and seedling growth under different soil water conditions were investigated. Field experiments were carried out by setting different water conditions (30%, 60%, and 100%) and biochar addition (0 t hm⁻², 2.63 t hm⁻², 5.26 t hm⁻², and 7.89 t hm⁻²). The results showed that applying biochar significantly increased the soil’s accessible phosphorus content and the phosphorus content in both the aboveground and subsurface parts of P. euphratica seedlings. This is mainly attributable to biochar’s direct and indirect effects on soil properties. Because biochar is naturally alkaline, it raises soil pH and reduces acid phosphatase activity in the soil around P. euphratica seedlings in the rhizosphere. Perhaps the alkaline phosphatase level first showed an upward trend due to the combined impacts of water and biochar, and then it started to decline when the biochar addition was increased. Soil phosphorus functional genes phoC, phoD, gcd, and pqqc had an increase in copy number with biochar addition but not without treatment. Indirectly, the biochar treatment increased the soil’s phosphorus availability by increasing the population of the phosphate-solubilizing bacteria Fusarium and Sphingomonas. Soil phosphorus availability is positively affected by biochar under various water conditions. This impact is due to chemical and microbiological mechanisms. Full article

Humanity’s strive to understand why and how life appeared on planet Earth dates back to prehistoric times. At the beginning of the 19th century, empirical biology started to tackle this question yielding both Charles Darwin’s Theory of Evolution and the paradigm that the crucial trigger putting life on its tracks was the appearance of organic molecules. In parallel to these developments in the biological sciences, physics and physical chemistry saw the fundamental laws of thermodynamics being unraveled. Towards the end of the 19th century and during the first half of the 20th century, the tensions between thermodynamics and the “organic-molecules-paradigm” became increasingly difficult to ignore, culminating in Erwin Schrödinger’s 1944 formulation of a thermodynamics-compliant vision of life and, consequently, the prerequisites for its appearance. We will first review the major milestones over the last 200 years in the biological and the physical sciences, relevant to making sense of life and its origins and then discuss the more recent reappraisal of the relative importance of metal ions vs. organic molecules in performing the essential processes of a living cell. Based on this reassessment and the modern understanding of biological free energy conversion (aka bioenergetics), we consider that scenarios wherein life emerges from an abiotic chemiosmotic process are both thermodynamics-compliant and the most parsimonious proposed so far. Full article

Background: Percutaneous dilatational tracheostomy (PDT) is the most commonly performed minimally invasive intensive care unit procedure worldwide. Methods: This study evaluated the percentage of consistency between the entry site observed with fiberoptic bronchoscopy (FOB) and the prediction for the PDT level based on pre-procedural ultrasonography (USG) in PDT procedures performed using the forceps dilatation method. The effect of morphological features on intervention sites was also investigated. Complications that occurred during and after the procedure, as well as the duration, site, and quantity of the procedures, were recorded. Results: Data obtained from a total of 91 patients were analyzed. In 57 patients (62.6%), the USG-estimated tracheal puncture level was consistent with the intercartilaginous space observed by FOB, while in 34 patients (37.4%), there was a discrepancy between these two methods. According to Bland Altman, the agreement between the tracheal spaces determined by USG and FOB was close. Regression formulas for PDT procedures defining the intercartilaginous puncture level based on morphologic measurements of the patients were created. The most common complication related to PDT was cartilage fracture (17.6%), which was proven to be predicted with maximum relevance by punctured tracheal level, neck extension limitation, and procedure duration. Conclusions: In PDT procedures using the forceps dilatation method, the prediction of the PDT intervention level based on pre-procedural USG was considerably in accordance with the entry site observed by FOB. The intercartilaginous puncture level could be estimated based on morphological measurements. Full article

In this paper, computational fluid dynamics (CFD) numerical simulation is employed to analyze and discuss the effect of obstacle gradient on the flame propagation characteristics of premixed hydrogen/air in a closed chamber. With a constant overall volume of obstacles, the obstacle blocking rate gradient is set at +0.125, 0, and −0.125, respectively. The study focuses on the evolution of the flame structure, propagation speed, the dynamic process of overpressure, and the coupled flame–flow field. The results demonstrate that the flame front consistently maintains a jet flame as the obstacle gradient increases, with the wrinkles on the flame front becoming increasingly pronounced. When the blocking rate gradients are +0.125, 0, and −0.125, the corresponding maximum flame propagation speeds are measured at 412 m/s, 344 m/s, and 372 m/s, respectively, indicating that the obstacle gradient indeed increases the flame propagation speed. Moreover, the distribution of pressure is closely related to changes in the flame structure, with the overpressure decreasing in the obstacle channel as the obstacle gradient increases. Furthermore, the velocity vector and vortex distribution in the flow field are revealed and compared. It is found that the obstacle tail vortex is the main factor inducing flame evolution and flow field changes in a closed chamber. The effect of the blocking rate gradient on flow velocity is also quantified, with instances of deceleration occurring when the blocking rate gradient is −0.125. Full article