In this paper, we introduce a model designed to predict human error probability (HEP) in the context of fishing boat operations utilizing the cognitive reliability and error analysis method (CREAM). We conducted an analysis of potential accidents on fishing boats and calculated the cognitive failure probability (CFP) for each identified accident. The common performance conditions (CPCs) from the original CREAM were adapted to better reflect the conditions on fishing boats, with the adapted CPCs’ validity confirmed through expert consultations. To apply CREAM, data were gathered via a survey of fishermen, with the uncertainty in the collected data addressed through the application of fuzzy set theory (FST). We then established a Bayesian network (BN) model to elucidate the relationship between the fuzzy data and HEP, utilizing a weighted sum algorithm to determine conditional probabilities within the BN. Both basic and extended versions of CREAM were applied to analyze the most common accidents among fishermen, calculating the CFP for each type of accident. According to our analysis, the poorer the dynamic CPC, the higher the probability that a fall accident will occur inside the boat due to human error, necessitating a countermeasure. The paper proposes safety enhancements for small fishing boats and illustrates the increased precision of human reliability analysis (HRA) models in forecasting human error by incorporating quantitative methods. It calls for further data collection and refinement of the model for more accurate operational risk assessments. Full article

This study aims to analyze the impact of uniform and eccentric load conditions on the performance of internal feedback hydrostatic thrust and journal bearing. Two distinct models are established: a three-degrees-of-freedom uniform load model and a five-degrees-of-freedom eccentric load model. The support stiffness, overturning stiffness, and flow rate for both thrust and journal bearings are calculated. Additionally, numerical analysis is conducted to examine the influence of oil film thickness, inlet pressure, and restrictor size on the operational characteristics of the bearings, revealing the interplay between an eccentric load and journal bearing speed. The validity of the theoretical algorithm is verified through finite element simulation. The research outcomes hold significant guiding implications for the design and application of internal feedback hydrostatic bearings. Full article

The meaning of justice can be defined according to a juridical, human, theological, ethical, biomedical, or social perspective. It should guarantee the protection of life and health, personal, civil, political, economic, and religious rights, as well as non-discrimination, inclusion, protection, and access to care. In this review, we deal with three theoretical concepts that define justice in all its aspects. (1) The utilitarian theory, which justifies moral statements on the basis of the evaluation of the consequences that an action produces, elaborating a pragmatic model of medical science. (2) The libertarian theory, which considers freedom as the highest political aim, thus absolutizing the rights of the individual; here, the principle of self-determination, with respect to which the principle of permission/consent is the fundamental presupposition, plays a central role in the definition of the person. (3) The iusnaturalist theory, in which man’s moral freedom is identified with the ability to act by choosing what the intellect indicates to him as good; the natural moral law that drives every conscience to do good is therefore realized in respect for the person in the fullness of his rights. In conclusion, different forms and conceptions of justice correspond to different organizations of society and different ways of addressing ethical issues in the biomedical domain. Full article

Atherosclerotic disease, including coronary heart disease (CHD), is one of the chronic inflammatory conditions, and an imbalance between pro-inflammatory and anti-inflammatory cytokines plays a role in the process of atherosclerosis. Interleukin (IL)-27, one of the IL-12 family members, is recognized to play a dual role in regulating immune responses with both pro-inflammatory and anti-inflammatory properties. IL-27 is secreted from monocytes, T cells, and endothelial cells, and its expression is upregulated in atherosclerotic plaques. We previously reported that no significant difference was observed in plasma IL-27 levels between patients with stable CHD and those without it. However, the prognostic value of IL-27 levels has not been fully elucidated. We studied the relation of plasma IL-27 levels to cardiovascular events in 402 patients undergoing elective coronary angiography for suspected CHD. We defined cardiovascular events as cardiovascular death, myocardial infarction, unstable angina, stroke, or coronary revascularization. Of the 402 study patients, CHD was present in 209 (52%) patients. Plasma IL-27 levels were not markedly different between patients with CHD and those without it (median 0.23 vs. 0.23 ng/mL). During a follow-up of 7.6 ± 4.5 years, cardiovascular events were observed in 70 patients (17%). In comparison to the 332 patients with no event, the 70 patients who had cardiovascular events showed significantly higher IL-27 levels (median 0.29 vs. 0.22 ng/mL) and more frequently had an IL-27 level of >0.25 ng/mL (59% vs. 40%) (p < 0.01). The Kaplan–Meier analysis demonstrated a lower event-free survival rate in patients with an IL-27 level >0.25 ng/mL than in those with an IL-27 level ≤0.25 ng/mL (p < 0.02). The multivariate Cox proportional hazards regression analysis showed that IL-27 level (>0.25 ng/mL) was a significant predictor for cardiovascular events (hazard ratio: 1.82; 95%CI: 1.13–2.93, p < 0.02), independent of CHD. Thus, high IL-27 levels in plasma were related to an increased risk of further cardiovascular events in patients who underwent elective coronary angiography. Full article

Oncological patients show intense catabolic activity, as well as a susceptibility to higher nutritional risk and clinical complications. Thus, tools are used for monitoring prognosis. Our objective was to analyze the nutrition prognosis of patients who underwent radiotherapy, correlating it with outcomes and complications. We performed a retrospective transversal study based on secondary data from hospital records of patients who started radiotherapy between July 2022 and July 2023. We established Prognostic Scores through a combination of Prognostic Nutritional Index (PNI) and a Subjective Global Assessment (SGA), assessed at the beginning and end of treatment. Score 3 patients, with PNI ≤ 45.56 and an SGA outcome of malnutrition, initially presented a higher occurrence of odynophagia, later also being indicative of reduced diet volume, treatment interruption, and dysphagia. SGA alone showed sensitivity to altered diet volume, dysphagia, and xerostomia in the second assessment. Besides this, PNI ≤ 45.56 also indicated the use of alternative feeding routes, treatment interruption, and hospital discharge with more complications. We conclude that the scores could be used to indicate complications; however, further studies on combined biomarkers are necessary. Full article

This article examines the involvement of the brain-derived neurotrophic factor (BDNF) in the control of nociception and pain. BDNF, a neurotrophin known for its essential role in neuronal survival and plasticity, has garnered significant attention for its potential implications as a modulator of synaptic transmission. This comprehensive review aims to provide insights into the multifaceted interactions between BDNF and pain pathways, encompassing both physiological and pathological pain conditions. I delve into the molecular mechanisms underlying BDNF’s involvement in pain processing and discuss potential therapeutic applications of BDNF and its mimetics in managing pain. Furthermore, I highlight recent advancements and challenges in translating BDNF-related research into clinical practice. Full article

Mount Meager is a deeply eroded quaternary volcanic complex located in southwestern British Columbia (BC) and is known for its frequent large landslides. In 2010, the south face of Mount Meager collapsed, generating a long-runout debris avalanche that was one of the largest landslides (50 × 10⁶ m³) in Canadian history. Over the past 14 years, the landslide deposit has been reworked by stream action, delivering large amounts of sediment to Lillooet River, just downstream. In this study, we investigate 10 years of geomorphic evolution of the landslide deposit using orthophotos and digital elevation models (DEMs) generated using Structure from Motion (SfM) photogrammetry on aerial photographs acquired during unmanned aerial vehicle (UAV) and Global Navigation Satellite System (GNSS) surveys. The SfM products were used to produce a series of precise maps that highlight the geomorphological changes along the lower Meager Creek within the runout area of the landslide. Comparison of DEMs produced from 2010, 2012, 2015, and 2019 imagery allowed us to calculate deposit volume changes related to erosion, transport, and redeposition of landslide material. We estimate that about 1.1 × 10⁶ m³ of sediment was eroded from the landslide deposit over the period 2015–2019. About 5.2 × 10⁵ m³ of that sediment was redeposited inside the study area. About 5.8 × 10⁵ m³ of sediment, mainly sand, silt, and clay, were exported from the study area and are being carried by Lillooet River towards Pemberton, 40 km from Mount Meager, and farther downstream. These remobilized sediments likely reduce the Lillooet River channel capacity and thus increase flood hazards to the communities of Pemberton and Mount Currie. Our study indicates a landslide persistence in the landscape, with an estimated 47-year half-life decay, suggesting that higher flood hazard conditions related to increased sediment supply may last longer than previously estimated. This study shows the value of using SfM in tandem with historic aerial photographs, UAV photos, and high-resolution satellite imagery for determining sediment budgets in fluvial systems. Full article

This study presents a refined approach to spatially identify carbon sequestration assets, crucial for effective climate action planning in Illinois. By integrating landscape analytical methods with species-specific carbon assessment techniques, we deliver a nuanced evaluation of forest area sequestration potential. Our methodology employs a combination of landscape imagery, deep learning analytics, Kriging interpolation, and i-Tree Planting tools to process forest sample data. The results reveal a spatial variability in sequestration capacities, highlighting significant carbon sinks in southern Illinois. This region, known for its historical woodland richness, showcases the distinct carbon sequestration abilities of various tree species. Findings emphasize the role of biodiversity in the carbon cycle and provide actionable insights for forest management and carbon neutral strategies. This study demonstrates the utility of advanced spatial analysis in environmental research, underscoring its potential to enhance accuracy in ecological quantification and conservation efforts. Full article

Pesticides play a critical role in pest management and agricultural productivity; however, their misuse or overuse can lead to adverse effects on human health and the environment, including impacts on ecosystems and contamination. Currently, neonicotinoids (NNIs) are the most widely used systemic insecticides and are questioned worldwide for their possible impacts on pollinators. After NNI application, a substantial portion is not absorbed by the plant and may accumulate in the soil, affecting the soil microbial community. In this review, we explore the main studies carried out either in the laboratory or in the field about this matter. The studies report that the application of NNIs affects soil microbial activity and can act on microbial communities differently due to their unique chemical properties, degradation in soil, soil type, effects on soil properties, and methods of application. NNIs alter the diversity, structure, and abundance of soil microbes, in some cases increasing or decreasing their representativeness in soil. Bacterial phyla like Pseudomonadota, Bacillota, Actinomycetota, and Nitrospirota increase after NNI exposure, just like the families Nitrosomonadaceae, Nitrososphaeraceae, Nitrospiraceae, Sphingomonadaceae, Streptomycetaceae, and Catenulisporaceae. At the bacterial genus level, Nitrospira was associated with a decrease in nitrification processes in soil. The bacterial genera Sphingomonas, Streptomyces, Catenulispora, Brevundimonas, Pedobacter, and Hydrogenophaga are related to NNI degradation after application. Microorganisms could minimize the impacts of NNIs in agricultural soil. Therefore, the use of bioinoculation as a bioremediation tool is explored as an alternative to contribute to agricultural sustainability. Full article

The marine dinoflagellate Alexandrium is known to form harmful algal blooms (HABs) and produces saxitoxin (STX) and its derivatives (STXs) that cause paralytic shellfish poisoning (PSP) in humans. Cell growth and cellular metabolism are affected by environmental conditions, including nutrients, temperature, light, and the salinity of aquatic systems. Abiotic factors not only engage in photosynthesis, but also modulate the production of toxic secondary metabolites, such as STXs, in dinoflagellates. STXs production is influenced by a variety of abiotic factors; however, the relationship between the regulation of these abiotic variables and STXs accumulation seems not to be consistent, and sometimes it is controversial. Few studies have suggested that abiotic factors may influence toxicity and STXs-biosynthesis gene (sxt) regulation in toxic Alexandrium, particularly in A. catenella, A. minutum, and A. pacificum. Hence, in this review, we focused on STXs production in toxic Alexandrium with respect to the major abiotic factors, such as temperature, salinity, nutrients, and light intensity. This review informs future research on more sxt genes involved in STXs production in relation to the abiotic factors in toxic dinoflagellates. Full article

Aeollanthus repens, native to East Africa, thrives in seasonally dry tropical biomes and boasts qualities ideal for both ornamental and ground cover purposes. However, despite its potential, its current resistance levels remain uncertain. Assessing its adaptability could offer valuable insights for its wider adoption and utilization. In this study, researchers employed 3-month-old cuttings of A. repens, subjecting them to six distinct environments by manipulating the temperature (25/20 °C and 35/30 °C) and soil moisture levels (100%, 20%, and 40%). Their leaf physiological and photosynthetic indices were assessed at intervals of 5, 10, and 15 days following exposure to stress. The findings unveiled that exposure to prolonged moisture, elevated temperatures, or a combination of both led to an increase in osmoregulatory substances in the leaves. This increase was accompanied by heightened enzyme activity and an increased intercellular carbon dioxide concentration, followed by a subsequent decline. Additionally, chlorophyll content, net photosynthetic rate, stomatal conductance, and transpiration rate exhibited a decreasing trend over time. Through a comprehensive assessment of stress tolerance utilizing a composite affiliation function value index, the study concluded that A. repens exhibits optimal growth in a certain high-temperature environments and demonstrates substantial resistance to waterlogging, drought, and simultaneous high-temperature stress. However, the resilience of A. repens appears to diminish under the compounded stresses of high temperature and drought. Full article

This article presents a detailed examination of the methodology and modeling tools utilized to analyze gas flows in pipelines, rooted in the fundamental principles of gas dynamics. The methodology integrates numerical simulations with modern neural network techniques, particularly focusing on the PINN utilizing the continuous symmetry data inherent in PDEs, which is called the symmetry-enhanced Physics-Informed Neural Network. This innovative approach combines artificial neural networks (ANNs) integrating physical equations, which provide enhanced efficiency and accuracy when modeling various complex processes related to physics with a symmetric and asymmetric nature. The presented mathematical model, based on the system of Euler equations, has been carefully implemented using Python language. Verification with analytical solutions ensures the accuracy and reliability of the computations. In this research, a comparative and comprehensive analysis was carried out comparing the outcomes obtained using the symmetry-enhanced PINN method and those from conventional computational fluid dynamics (CFD) approaches. The analysis highlighted the advantages of the symmetry-enhanced PINN method, which produced smoother pressure and velocity fluctuation profiles while reducing the computation time, demonstrating its capacity as a revolutionary modeling tool. The estimated results derived from this study are of paramount importance for ensuring ongoing energy supply reliability and can also be used to create predictive models related to gas behavior in pipelines. The application of modeling techniques for gas flow simulations has the potential to improve the integrity of our energy infrastructure and utilization of gas resources, contributing to advancing our understanding of symmetry principles in nature. However, it is crucial to emphasize that the effectiveness of such models relies on continuous monitoring and frequent updates to ensure alignment with real-world conditions. This research not only contributes to a deeper understanding of compressible gas flows but also underscores the crucial role of advanced modeling methodologies in the sustainable management of gas resources for both current and future generations. The numerical data covered the physics of the process related to the modeling of high-pressure gas flows in pipelines with regard to density, velocity and pressure, where the PINN model was able to outperform the classical CFD method for velocity by 170% and for pressure by 360%, based on $L_{\infty }$ values. Full article

Thin ice with a thickness of less than half a meter produces strong salt and heat fluxes which affect deep water circulation and weather in the polar oceans. The identification of thin ice areas is essential for ship navigation. We have developed thin ice detection algorithms for the AMSR2 and FY-3C MWRI radiometer data over the Arctic Ocean. Thin ice (<20 cm) is detected based on the classification of the H-polarization 89–36-GHz gradient ratio (GR8936H) and the 36-GHz polarization ratio (PR36) signatures with a linear discriminant analysis (LDA) and thick ice restoration with GR3610H. The brightness temperature ($T_B$) data are corrected for the atmospheric effects following an EUMETSAT OSI SAF correction method in sea ice concentration retrieval algorithms. The thin ice detection algorithms were trained and validated using MODIS ice thickness charts covering the Barents and Kara Seas. Thin ice detection is applied to swath $T_B$ datasets and the swath charts are compiled into a daily thin ice chart using 10 km pixel size for AMSR2 and 20 km for MWRI. On average, the likelihood of misclassifying thick ice as thin in the ATIDA2 daily charts is 7.0% and 42% for reverse misclassification. For the MWRI chart, these accuracy figures are 4% and 53%. A comparison of the MWRI chart to the AMSR2 chart showed a very high match (98%) for the thick ice class with SIC > 90% but only a 53% match for the thin ice class. These accuracy disagreements are due to the much coarser resolution of MWRI, which gives larger spatial averaging of $T_B$ signatures, and thus, less detection of thin ice. The comparison of the AMSR2 and MWRI charts with the SMOS sea ice thickness chart showed a rough match in the thin ice versus thick ice classification. The AMSR2 and MWRI daily thin ice charts aim to complement SAR data for various sea ice classification tasks. Full article

Photocatalysis is a fascinating process in which a photocatalyst plays a pivotal role in driving a chemical reaction when exposed to light. Its capacity to harness light energy triggers a cascade of reactions that lead to the formation of intermediate compounds, culminating in the desired final product(s). The essence of this process is the interaction between the photocatalyst’s excited state and its specific interactions with reactants, resulting in the creation of intermediates. The process’s appeal is further enhanced by its cyclic nature—the photocatalyst is rejuvenated after each cycle, ensuring ongoing and sustainable catalytic action. Nevertheless, comprehending the photocatalytic process through the modeling of photoactive materials and molecular devices demands advanced computational techniques founded on effective quantum chemistry methods, multiscale modeling, and machine learning. This review analyzes contemporary theoretical methods, spanning a range of lengths and accuracy scales, and assesses the strengths and limitations of these methods. It also explores the future challenges in modeling complex nano-photocatalysts, underscoring the necessity of integrating various methods hierarchically to optimize resource distribution across different scales. Additionally, the discussion includes the role of excited state chemistry, a crucial element in understanding photocatalysis. Full article

The effects of initial small-scale material nonlinearity on the pre-yield and pre-buckling response of externally pressurized metallic (plane strain) perfect rings (very long cylindrical shells) is investigated. The cylindrically curved 16-node element, based on an assumed quadratic displacement field (in surface-parallel coordinates) and the assumption of linear distribution of displacements through thickness (LDT), is employed to obtain the discretized system equations. The effect of initial small-scale material nonlinearity (assumed hypo-elastic) on the deformation and stress in the pre-yield and pre-buckling regime of a very long relatively thin metallic cylindrical shell (plane strain ring) is numerically investigated. These numerical results demonstrate that the enhanced responses for metallic rings due to initial small-scale nonlinearity are significant enough to not miss attentions from designers and operators of submersibles alike. Full article

Extracellular vesicles (EVs) are tools for intercellular communication, mediating molecular transport processes. Emerging studies have revealed that EVs are significantly involved in immune processes, including sepsis. Sepsis, a dysregulated immune response to infection, triggers systemic inflammation and multi-organ dysfunction, posing a life-threatening condition. Although extensive research has been conducted on animals, the complex inflammatory mechanisms that cause sepsis-induced organ failure in humans are still not fully understood. Recent studies have focused on secreted exosomes, which are small extracellular vesicles from various body cells, and have shed light on their involvement in the pathophysiology of sepsis. During sepsis, exosomes undergo changes in content, concentration, and function, which significantly affect the metabolism of endothelia, cardiovascular functions, and coagulation. Investigating the role of exosome content in the pathogenesis of sepsis shows promise for understanding the molecular basis of human sepsis. This review explores the contributions of activated immune cells and diverse body cells’ secreted exosomes to vital organ dysfunction in sepsis, providing insights into potential molecular biomarkers for predicting organ failure in septic shock. Full article

Cyber–physical systems involve the creation, continuous updating, and monitoring of virtual replicas that closely mirror their physical counterparts. These virtual representations are fed by real-time data from sensors, Internet of Things (IoT) devices, and other sources, enabling a dynamic and accurate reflection of the state of the physical system. This emphasizes the importance of data synchronization, visualization, and interaction within virtual environments as a means to improve decision-making, training, maintenance, and overall operational efficiency. This paper presents a novel approach to a cyber–physical system that integrates virtual reality (VR)-based digital twins and 3D SCADA in the context of Industry 4.0 for the monitoring and optimization of an olive mill. The methodology leverages virtual reality to create a digital twin that enables immersive data-driven simulations for olive mill monitoring. The proposed CPS takes data from the physical environment through the existing sensors and measurement elements in the olive mill, concentrates them, and exposes them to the virtual environment through the Open Platform Communication United Architecture (OPC-UA) protocol, thus establishing bidirectional and real-time communication. Furthermore, in the proposed virtual environment, the digital twin is interfaced with the 3D SCADA system, allowing it to create virtual models of the process. This innovative approach has the potential to revolutionize the olive oil industry by improving operational efficiency, product quality, and sustainability while optimizing maintenance practices. Full article

This study employs an adaptive neuro-fuzzy inference system (ANFIS) to identify critical success factors (CSFs) crucial for the success of pavement construction projects. Challenges such as construction cost delays, budget overruns, disputes, claims, and productivity losses underscore the need for effective project management in pavement projects. In contemporary construction management, additional performance criteria play a vital role in influencing the performance and success of pavement projects during construction operations. This research contributes to the existing body of knowledge by comprehensively identifying a multidimensional set of critical success performance factors that impact pavement and utility project management. A rigorous literature review and consultations with pavement experts identified sixty CSFs, categorized into seven groups. The relative importance of each element and group is determined through the input of 287 pavement construction specialists who participated in an online questionnaire. Subsequently, the collected data undergo thorough checks for normality, dependability, and independence before undergoing analysis using the relative importance index (RII). An ANFIS is developed to quantitatively model critical success factors and assess the implementation performance of construction operations management (COM) in the construction industry, considering aspects such as clustering input/output datasets, fuzziness degree, and optimizing five Gaussian membership functions. The study confirms the significance of three primary CSFs (financial, bureaucratic, and governmental) and communication-related variables through a qualitative structural and behavioral validation process, specifically k-fold cross-validation. The outcomes of this research hold practical implications for the management and assessment of overall performance indices in pavement construction projects. The ANFIS model, validated through robust testing methodologies, provides a valuable tool for industry professionals seeking to enhance the success and efficiency of pavement construction endeavors. Full article

The building and construction sector in the Kingdom of Saudi Arabia (KSA), experiencing rapid growth, is in the early stages of embracing sustainability measures. In the years ahead, the booming building sector in business-as-usual scenarios may pose serious energy and environmental challenges for the Kingdom. This situation will require the Saudi building sector to adopt robust sustainability measures. Embedding life cycle assessment (LCA) as a standard practice can be a useful strategy for improving the energy and environmental footprint of buildings. This paper proposes a theoretical framework within which to promote LCA in the Saudi Arabian construction industry. This framework comprises three pillars: policy, social, and technical. The framework covers the role of the Saudi building sector’s stakeholders such as policy makers, building industry professionals, representatives of relevant governmental bodies, and academics. Adaptation of this LCA framework can help substantially improve the energy and environmental performance of buildings. The proposed LCA framework is aligned with the international as well as the Saudi government’s drive for sustainability in the building sector. Full article

Background and Objectives: Transurethral urologic surgeries frequently lead to hypothermia due to bladder irrigation. Prewarming in the preoperative holding area can reduce the risk of hypothermia but disrupts surgical workflow, preventing it from being of practical use. This study explored whether early intraoperative warming during induction of anesthesia, known as peri-induction warming, using a forced-air warming device combined with warmed intravenous fluid could prevent intraoperative hypothermia. Materials and Methods: Fifty patients scheduled for transurethral resection of the bladder (TURB) or prostate (TURP) were enrolled and were randomly allocated to either the peri-induction warming or control group. The peri-induction warming group underwent whole-body warming during anesthesia induction using a forced-air warming device and was administered warmed intravenous fluid during surgery. In contrast, the control group was covered with a cotton blanket during anesthesia induction and received room-temperature intravenous fluid during surgery. Core temperature was measured upon entrance to the operating room (T₀), immediately after induction of anesthesia (T₁), and in 10 min intervals until the end of the operation (T_end). The incidence of intraoperative hypothermia, change in core temperature (T₀–T_end), core temperature drop rate (T₀–T_end/[duration of anesthesia]), postoperative shivering, and postoperative thermal comfort were assessed. Results: The incidence of intraoperative hypothermia did not differ significantly between the two groups. However, the peri-induction warming group exhibited significantly less change in core temperature (0.61 ± 0.3 °C vs. 0.93 ± 0.4 °C, p = 0.002) and a slower core temperature drop rate (0.009 ± 0.005 °C/min vs. 0.013 ± 0.004 °C/min, p = 0.013) than the control group. The peri-induction warming group also reported higher thermal comfort scores (p = 0.041) and less need for postoperative warming (p = 0.034) compared to the control group. Conclusions: Brief peri-induction warming combined with warmed intravenous fluid was insufficient to prevent intraoperative hypothermia in patients undergoing urologic surgery. However, it improved patient thermal comfort and mitigated the absolute amount and rate of temperature drop. Full article

Organic amendment is an effective method to reclaim salt-affected soil. However, in coastal land with shallow saline groundwater, it is limited known about the mechanism of organic amendment on soil desalinization. Thus, to examine the effect of topsoil organic matter content on soil water/salt transport and distribution, two-year field observations in Bohai coastal land, North China, and soil column experiments simulating salt accumulation and salt leaching were conducted, respectively. There were different organic fertilizer amendment rates in 0–20 cm topsoil, 0% (CK), 50% (OA 0.5), and 100% (OA 1.0) (w/w) for soil column experiments. Field observation showed that after organic amendment (OA), the soil’s physical structure was improved, and less of the increase in topsoil salt content was observed, with more salt accumulated in deep soil layers during the dry season. In addition, OA greatly promoted salt leaching during the rainy seasons. The results of the soil column tests further indicated that OA treatments significantly inhibited soil evaporation, with less salt accumulated in the topsoil. Although there was no difference in soil water distribution between the CK and OA 0.5 treatment, the topsoil EC for the OA 0.5 treatment was significantly lower than that for CK. During soil water infiltration, the OA 0.5 and OA 1.0 treatments significantly increased the infiltration rates, enhanced the wetting front, and promoted salt leaching to deeper soil layers, compared with CK. The improvement of soil organic amounts could make the soil more self-resistant to the coastal salinization. The findings of this study provide some insights into soil water/salt regulation in heterogeneous soil masses and on the permanent management of coastal saline farmland. Full article

The optimal PMU placement problem is placing the minimum number of PMUs in the network to ensure complete network observability. It is an NP-complete optimization problem. PMU placement based on cost and critical nodes is solved separately in the literature. This paper proposes a novel approach, a degree of centrality in the objective function, to combine the effect of both strategies to place PMUs in the power network optimally. The contingency analysis and the effect of zero-injection buses are solved to ensure the reliability of network monitoring and attain a minimum number of PMUs. Integer linear programming is used on the IEEE 7-bus, IEEE 14-bus, IEEE 30-bus, New England 39-bus, IEEE 57-bus, and IEEE 118-bus systems to solve this problem. The results are evaluated based on two performance measures: the bus observability index (BOI) and the sum of redundancy index (SORI). On comparison, it is found that the proposed methodology has significantly improved results, i.e., a reduced number of PMUs and increased network overall observability (SORI). This methodology is more practical for implementation as it focuses on critical nodes. Along with improvement in the results, the limitations of existing indices are also discussed for future work. Full article