Large Complex Research Articles

CFD Analysis on Novel Vertical Axis Wind Turbine (VAWT)

The operation of vertical axis wind turbines (VAWTs) to generate low-carbon electricity is growing in popularity. Their advantages over the widely used horizontal axis wind turbine (HAWT) include their low tip speed, which reduces noise, and their cost-effective installation and maintenance. A Farrah turbine equipped with 12 blades was designed to enhance performance and was recently the subject of experimental investigation. However, little research has been focused on turbine configurations with more than three blades. The objective of this study is to employ numerical methods to analyse the performance of the Farrah wind turbine and to validate the findings in comparison with experimental results. The investigated blade pitch angles included both positive and negative angles of 7, 15, 20 and 40 degrees. The k-ω SST model with the sliding mesh technique was used to perform simulations of a 14.4 million element unstructured mesh. Comparable trends of power output results in the experimental investigation were obtained and the assumptions of mechanical losses discussed. Wake recovery was determined at an approximate distance of nine times the turbine diameter. Two large complex quasi-symmetric vortical structures were observed between positive and negative blade pitch angles, located in the near wake region of the turbine and remaining present throughout its rotation. It is demonstrated that a number of recognised vortical structures are transferred towards the wake region, further contributing to its formation. Additional notable vortical formations are examined, along with a recirculation zone located in the turbine’s core, which is described to exhibit quasi-symmetric behaviour between positive and negative rotations.

Driving Forces in the Formation of Biocondensates of Highly Charged Proteins: A Thermodynamic Analysis of the Binary Complex Formation

A thermodynamic analysis of the binary complex formation of the highly positively charged linker histone H1 and the highly negatively charged chaperone prothymosin α (ProTα) is detailed. ProTα and H1 have large opposite net charges (−44 and +53, respectively) and form complexes at physiological salt concentrations with high affinities. The data obtained for the binary complex formation are analyzed by a thermodynamic model that is based on counterion condensation modulated by hydration effects. The analysis demonstrates that the release of the counterions mainly bound to ProTα is the main driving force, and effects related to water release play no role within the limits of error. A strongly negative Δcp (=−0.87 kJ/(K mol)) is found, which is due to the loss of conformational degrees of freedom.

Characteristics of Volatile Organic Compounds Emissions and Odor Impact in the Pharmaceutical Industry

Volatile Organic Compounds (VOCs) are not only essential precursors for the formation of ozone and PM2.5, but also hazardous to human health and responsible for unpleasant odors. The pharmaceutical industry has become an important industrial source of VOCs due to China’s large emissions and complex emission chains. In total, 245 VOCs samples were collected and analyzed from 11 typical pharmaceutical companies in Zibo City of the North China Plain, in order to investigate the VOCs emission characteristics and odor impacts. The emission factor for the pharmaceutical industry was 7.97 ± 8.21 g/kg pharmaceuticals, while the main emission links were chimney emissions, equipment sealing leakage, and so on. Finally, considering both purifying efficiency and economic benefits, the multistage absorption (AB) method is most effective for VOCs concentrations below 100 mg/m3, while UV photo-oxygenation combined with adsorption (UVA) is more suitable for concentrations below 300 mg/m3. The Regenerative Thermal Oxidizer (RTO), Catalytic Oxidizer (CO), and Condensation + Adsorption (CA) technologies demonstrated greater stability and efficiency, particularly in the treatment of complex organic pollutants, highlighting their advantages in both VOCs and odor removal at higher concentrations.

Photosystem rearrangements, photosynthetic efficiency, and plant growth in far red-enriched light.

Arabidopsis plants were grown in white light (400-700 nm) or in white light supplemented with far-red (FR) light peaking at 730 nm. FR-enriched light induced the typical shade avoidance syndrome characterized by enhanced length of seedling hypocotyl and leaf petiole. FR supplementation also caused a noticeable decrease in the carotenoid and chlorophyll content that was attributable to a block of pigment accumulation during plant development. The carotenoid decrease resulted from a downregulation of their biosynthesis pathway rather than carotenoid degradation. The losses of photosynthetic pigments are part of structural and functional rearrangements of the photosynthetic apparatus. The plastoquinone pool was chronically more oxidized in plants acclimated to white + FR light compared to white light-grown plants. Growth in FR-enriched light was associated with a higher photochemical efficiency of PSII compared to growth in white light and with a substantial increase in root and shoot biomass production. Light distribution between the photosystems was modified in favor of PSII by an increase in the PSII/PSI ratio and an inhibition of state transitions. Neither LHCII abundance nor nonphotochemical energy dissipation in the PSII chlorophyll antennae were modified significantly by the addition of FR light. A PSI supercomplex, not previously observed in Arabidopsis, was specifically found in plants grown in FR-enriched light. This large PSI complex contains a supplementary Lhca1-4 dimer, leading to a total of 6 LHCI antennae instead of 4 in the canonical PSI. Through those photosystem rearrangements and the synergistic interaction with white light, FR light is photosynthetically active and can boost photosynthesis and plant growth.

Extending GPU-accelerated Gaussian integrals in the TeraChem software package to f type orbitals: Implementation and applications.

The increasing availability of graphics processing units (GPUs) for scientific computing has prompted interest in accelerating quantum chemical calculations through their use. However, the complexity of integral kernels for high angular momentum basis functions often limits the utility of GPU implementations with large basis sets or for metal containing systems. In this work, we report the implementation of f function support in the GPU-accelerated TeraChem software package through the development of efficient kernels for the evaluation of Hamiltonian integrals. The high efficiency of the resulting code is demonstrated through density functional theory (DFT) calculations on increasingly large organic molecules and transition metal complexes, as well as coupled cluster singles and doubles calculations on water clusters. Preliminary investigations into Ni(I) catalysis with DFT and the photochemistry of MnH(CH3) with complete active space self-consistent field are also carried out. Overall, our GPU-accelerated software appears to be well-suited for fast simulation of large transition metal containing systems, as well as organic molecules.

Characterisation of LGP2 complex multitranscript system in humans: role in the innate immune response and evolution from non-human primates.

Retinoic acid inducible gene I (RIG-I)-like receptors (RLRs), including RIG-I, MDA5 and LGP2, recognize viral RNA to mount an antiviral interferon (IFN) response RLRs share three different protein domains: C-terminal domain, DExD/H box RNA helicase domain, and an N-terminal domain with two tandem repeats (CARDs). LGP2 lacks tandem CARD and is not able to induce an IFN response. However, LGP2 positively enhances MDA5 and negatively regulates RIG-I signaling. In this study, we determined the LGP2 alternative transcripts in humans to further comprehend the mechanism of its regulation, their evolutionary origin, and the isoforms functionallity. The results showed new eight alternative transcripts in the samples tested. The presence of these transcripts demonstrated that the main mechanisms for the regulation of LGP2 expression are both by insertion of introns and by the loss of exons. The phylogenetic analysis of the comparison between sequences from exon 1 to exon 3 of humans and those previously described in non-human primates showed three well-differentiated groups (lineages) originating from gorillas, suggesting that the transspecies evolution has been maintained for 10 million years. The corresponding protein models (isoforms) were also established, obtaining four isoforms: one complete and three others lacking the C-terminal domain or this domain and the partial or total He2 Helicase domain, which would compromise the functionality of LGP2. In conclusion, this is the first study that elucidate the large genomic organization and complex transcriptional regulation of human LGP2, its pattern of sequence generation, and a mode of evolutionary inheritance across species.

Characteristic of PM2.5 concentration and source apportionment during winter in Seosan, Korea

Seosan is a concentrated industrial complex in the midwestern region of Korea. A study was conducted from December 2020 to January 2021, measuring PM2.5 and chemical components in Seosan using online instruments every hour. The concentration of PM2.5 during the winter season was 31.4±17.8 μg/m3, exceeding the national ambient air quality standard of Korea. The mass fraction of organic matter, elemental carbon, three major ions, five minor ions, crustal elements, and trace elements in PM2.5 accounted for 24.5%, 4.36%, 32.0%, 2.82%, 4.11%, and 5.17% of the total PM2.5 mass concentration, respectively. Source identification was conducted using positive matrix factorization modeling, revealing eight sources of PM2.5: Secondary inorganic aerosol (SIA), vehicle exhaust, industry, coal combustion, biomass burning/incinerator, oil combustion, soil, and aged sea salt. Source contributions varied during high pollution episodes (HPE), with SIA dominating in HPE1 and soil and aged sea salt in HPE2. The potential source contribution function and conditional probability function were utilized to estimate the potential local and regional emission areas for the identified sources. In Seosan, vehicle exhaust and biomass burning/incinerator were primarily influenced by local sources. SIA, industry, and oil combustion sources were significantly affected by short-range transport from eastern China. Soil and aged sea salt, which exhibited high contributions during HPE2, were associated with long-range transport from Inner Mongolia. Coal combustion was attributed to both local sources, particularly large industrial complexes near Seosan, and long-range transport from Northeast China and Inner Mongolia.Graphical

Improved Rapid Equilibrium Dialysis-Mass Spectrometry (RED-MS) Method for Measuring Small Molecule-Protein Complex Binding Affinities in Solution.

Rapid equilibrium dialysis (RED) is predominantly used for the characterization of drug absorption, distribution, metabolism, and excretion (ADME) properties in plasma and biological fluids. We describe herein improvements in the use of RED in conjunction with mass spectrometry (RED-MS) to enable robust binding affinity measurements of small molecules for recombinant proteins and complexes from a single dialysis data set. The affinities calculated from RED-MS correlated well with measurements by both surface plasmon resonance (SPR) and affinity selection mass spectrometry (AS-MS). The method was particularly useful for quantifying the binding of small molecules to large protein complexes that were not amendable by common biophysical characterization techniques. Compound pooling and integration with automated liquid handling increased assay throughput and enabled the analysis of hundreds of measurements per week. RED-MS offers a viable option for measuring compound binding in solution and may facilitate small molecule affinity optimization toward difficult-to-drug protein complexes.

Perspectives Toward an Integrative Structural Biology Pipeline With Atomic Force Microscopy TopographicImages.

After the recent double revolutions in structural biology, which include the use of direct detectors for cryo-electron microscopy resulting in a significant improvement in the expected resolution of large macromolecule structures, and the advent of AlphaFold which allows for near-accurate prediction of any protein structures, the field of structural biology is now pursuing more ambitious targets, including several MDa assemblies. But complex target systems cannot be tackled using a single biophysical technique. The field of integrative structural biology has emerged as a global solution. The aim is to integrate data from multiple complementary techniques to produce a final three-dimensional model that cannot be obtained from any single technique. The absence of atomic force microscopy data from integrative structural biology platforms is not necessarily due to its nm resolution, as opposed to Å resolution for x-ray crystallography, nuclear magnetic resonance, or electron microscopy. Rather a significant issue was that the AFM topographic data lacked interpretability. Fortunately, with the introduction of the AFM-Assembly pipeline and other similar tools, it is now possible to integrate AFM topographic data into integrative modeling platforms. The advantages of single molecule techniques, such as AFM, include the ability to confirm experimentally any assembled molecular models or to produce alternative conformations that mimic the inherent flexibility of large proteins or complexes. The review begins with a brief overview of the historical developments of AFM data in structural biology, followed by an examination of the strengths and limitations of AFM imaging, which have hindered its integration into modern modeling platforms. This review discusses the correction and improvement of AFM topographic images, as well as the principles behind the AFM-Assembly pipeline. It also presents and discusses a series of challenges that need to be addressed in order to improve the incorporation of AFM data into integrative modeling platform.

Mitochondrial nucleoids

Eve Kakudji and Samantha Lewis discuss the structure and function of mitochondrial nucleoids - large nucleoprotein complexes containing mitochondrial DNA and the regulatory factors necessary for its packaging, replication, transcription, and repair.

Additive manufacturing of Fe–Mn–Al–C lightweight steel by laser powder bed fusion: The role of laser scanning speed on forming quality, microstructure and properties

The Fe–Mn–Al–C lightweight steels have attracted great attention in the military, aerospace, and automotive industries due to their high strength and lightweight design. Nevertheless, the excessive Mn and Al inclusions have led to poor formability and processability, which brings challenges to the manufacture of large size complex structural parts. In this study, the lightweight steel with a composition of Fe–Mn–Al–C was prepared by laser powder bed fusion for the first time, aimed at investigating the effects of laser scanning speed. The results show that different laser scanning speeds have significant effects on the process sensitivity of lightweight steel, and too low or too high laser scanning speeds may lead to suboptimal sample quality, increased porosity and surface roughness. At a scanning speed of 800 mm/s, the optimal conditions for the lowest porosity (0.03%) and surface roughness (Sa = 3.34 μm) are achieved, resulting in the highest quality of the formed products. Furthermore, an increase in scanning speed results in a reduction in grain size and an enhancement of dislocation strength. When the scanning speed is 800 mm/s, the significant enrichment of Ni–Mn phase helps to enhance the pinning ability of dislocations, while the precipitation of nanoscale small and dense κ-carbide optimizes the Orowan strengthening effect. As a result, dislocation movement is effectively impeded, leading to superior comprehensive mechanical properties of exceptional strength-plasticity matched with a tensile strength, yield strength, and elongation after fracture of 1125.2 MPa, 1019.8 MPa, and 41.9%, respectively.

Single-cell transcriptional analysis of murine norovirus infection in a human intestinal cell line.

Noroviruses are a major agent of acute gastroenteritis in humans, but host cell requirements for efficient replication in vitro have not been established. We engineered a human intestinal cell line (designated mCD300lf-hCaco2) expressing the murine norovirus (MNV) receptor, mouse CD300lf to become fully permissive for MNV replication. To explore the replicative machinery and host response of these cells, we performed a single-cell RNA sequencing (scRNA-seq) transcriptomics analysis of an MNV infection over time. Marked similarities were observed between certain global features of MNV infection in human cells compared to those previously reported in mouse cells by whole population transcriptomics such as downregulation of ribosome biogenesis, mitochondrial dysfunction, and cell cycle preference for G1. Our scRNA-seq analysis allowed further resolution of an infected cell population into distinct clusters with varying levels of viral RNA and interferon-stimulated gene ISG15 transcripts. Cells with high viral replication displayed downregulated ribosomal protein small (RPS) and large (RPL) genes and mitochondrial complexes I, III, IV, and V genes during exponential viral propagation. Ferritin subunit genes FTL and FTH1 were also downregulated during active MNV replication, suggesting that inhibition of iron metabolism may increase replication efficiency. Consistent with this, transcriptional activation of these genes with ferric ammonium citrate and overexpression of FTL lowered virus yields. Comparative studies of cells that support varying levels of norovirus replication efficiency, as determined by scRNA-seq may lead to improved human cell-based culture systems and effective viral interventions.IMPORTANCEHuman noroviruses cause acute gastroenteritis in all age groups. Vaccines and antiviral drugs are not yet available, in part, because it is difficult to propagate the viruses causing human disease in standard laboratory cell culture systems. In contrast, a norovirus found in mice [murine norovirus (MNV)] replicates efficiently in murine-based cell culture and has served as a model system. In this study, we established a new human intestinal cell line that was genetically modified to express the murine norovirus receptor so that the human cells became permissive to murine norovirus infection. We then defined the host response to MNV infection in the engineered human cell line at a single-cell resolution and identified cellular genes associated with the highest levels of MNV replication. This study may lead to the improvement of the current human norovirus cell culture systems and help to identify norovirus-host interactions that could be targeted for antiviral drugs.

Paediatric systemic inflammatory response syndrome (SIRS) and the development of patient-specific therapy: ethical perspectives through experts’ opinions

BackgroundResearch for personalised therapies concerning the Systemic Inflammatory Response Syndrome (SIRS) in children involves the utilisation of OMICS technologies and Artificial Intelligence (AI).MethodsTo identify specific ethical challenges through the perspective of healthcare professionals, we conducted 10 semi-structured interviews. The development of interview questions for the interviews was preceded by a systematic review of the scientific literature. To address the complexities of paediatric emergency research, informed consent, and data processing, experts with expertise in paediatric intensive care, computer science, and medical law were sought. After the transcription and anonymisation, the analysis followed established guidelines for qualitative content and thematic analysis.ResultsInterviewees highlighted the intricacies of managing consent in personalised SIRS research due to the large amount and complexity of information necessary for autonomous decision-making. Thus, instruments aimed at enhancing the understanding of legal guardians and to empowering the child were appreciated and the need for specific guidelines and establishing standards was expressed. Medical risks were estimated to be low, but the challenges of securing anonymisation and data protection were expected. It was emphasised that risks and benefits cannot be anticipated at this stage. Social justice issues were identified because of possible biases within the research population. Our findings were analysed using current ethical and legal frameworks for research with a focus on the particularities of the patient group and the emergency background. In this particular context, experts advocated for an enabling approach pertaining to AI in combination with OMICS technologies.ConclusionAs with every new technological development, ethical and legal challenges cannot be foreseen for SIRS-personalised treatment. Given this circumstance, experts emphasised the importance of extending the ethics-legal discourse beyond mere restrictions. The organisation of supervision should be reconsidered and not limited only to the precautionary principle, which per se was seen as impeding both the medical progress and clinical flexibility. It was noted that the establishment and monitoring of guidelines were emergent and should evolve through an interdisciplinary discourse. Therefore, it was recommended to enhance the qualifications of physicians in the field of computer science, impart ethics training to AI developers, and involve experts with expertise in medical law and data protection.

Structural Analysis of the 20S Proteasome Using Native Mass Spectrometry and Ultraviolet Photodissociation.

Owing to the role of the 20S proteasome in a wide spectrum of pathologies, including neurodegenerative disorders, proteasome-associated autoinflammatory syndromes (PRAAS), and cardiovascular diseases, understanding how its structure and composition contribute to dysfunction is crucial. As a 735 kDa protein assembly, the 20S proteasome facilitates normal cellular proteostasis by degrading oxidized and misfolded proteins. Declined proteasomal activity, which can be attributed to perturbations in the structural integrity of the 20S proteasome, is considered one of the main contributors to multiple proteasome-related diseases. Devising methods to characterize the structures of 20S proteasomes provides necessary insight for the development of drugs and inhibitors that restore proper proteasomal function. Here, native mass spectrometry was combined with multiple dissociation techniques, including ultraviolet photodissociation (UVPD), to identify the protein subunits comprising the 20S proteasome. UVPD, demonstrating an ability to uncover structural features of large (>300 kDa) macromolecular complexes, provided complementary information to conventional collision-based methods. Additionally, variable-temperature electrospray ionization was combined with UV photoactivation to study the influence of solution temperature on the stability of the 20S proteasome.

Lightweight Implementation of the Signal Enhancement Model for Early Wood-Boring Pest Monitoring

Wood-boring pests are one of the most destructive forest pests. However, the early detection of wood-boring pests is extremely difficult because their larvae live in tree trunks and have high invisibility. Borehole listening technology is a new and effective method to detect the larvae of insect pests. It identifies infested trees by analyzing wood-boring vibration signals. However, the collected wood-boring vibration signals are often disturbed by various noises existing in the field environment, which reduces the accuracy of pest detection. Therefore, it is necessary to filter out the noise and enhance the wood-boring vibration signals to facilitate the subsequent identification of pests. The current signal enhancement models are all designed based on deep learning models, which have complex scales, a large number of parameters, high demands for storage resources, large computational complexity, and high time costs. They often run on resource-rich computers or servers, and they are difficult to deploy to resource-limited field environments to realize the real-time monitoring of pests; as well, they have low practicability. Therefore, this study designs and implements two model lightweight optimization algorithms, one is a pre-training pruning algorithm based on masks, and the other is a knowledge distillation algorithm based on the separate transfer of vibration signal knowledge and noise signal knowledge. We apply the two lightweight optimization algorithms to the signal enhancement model T-CENV with good performance outcomes and conduct a series of ablation experiments. The experimental results show that the proposed methods effectively reduce the volume of the T-CENV model, which make them useful for the deployment of signal enhancement models on embedded devices, improve the usability of the model, and help to realize the real-time monitoring of wood-boring pest larvae.

A New Iterative Algorithm for Magnetic Motion Tracking

Motion analysis is of great interest to a variety of applications, such as virtual and augmented reality and medical diagnostics. Hand movement tracking systems, in particular, are used as a human–machine interface. In most cases, these systems are based on optical or acceleration/angular speed sensors. These technologies are already well researched and used in commercial systems. In special applications, it can be advantageous to use magnetic sensors to supplement an existing system or even replace the existing sensors. The core of a motion tracking system is a localization unit. The relatively complex localization algorithms present a problem in magnetic systems, leading to a relatively large computational complexity. In this paper, a new approach for pose estimation of a kinematic chain is presented. The new algorithm is based on spatially rotating magnetic dipole sources. A spatial feature is extracted from the sensor signal, the dipole direction in which the maximum magnitude value is detected at the sensor. This is introduced as the “maximum vector”. A relationship between this feature, the location vector (pointing from the magnetic source to the sensor position) and the sensor orientation is derived and subsequently exploited. By modelling the hand as a kinematic chain, the posture of the chain can be described in two ways: the knowledge about the magnetic correlations and the structure of the kinematic chain. Both are bundled in an iterative algorithm with very low complexity. The algorithm was implemented in a real-time framework and evaluated in a simulation and first laboratory tests. In tests without movement, it could be shown that there was no significant deviation between the simulated and estimated poses. In tests with periodic movements, an error in the range of 1° was found. Of particular interest here is the required computing power. This was evaluated in terms of the required computing operations and the required computing time. Initial analyses have shown that a computing time of 3 μs per joint is required on a personal computer. Lastly, the first laboratory tests basically prove the functionality of the proposed methodology.

CryoSTAR: leveraging structural priors and constraints for cryo-EM heterogeneous reconstruction.

Resolving conformational heterogeneity in cryogenic electron microscopy datasets remains an important challenge in structural biology. Previous methods have often been restricted to working exclusively on volumetric densities, neglecting the potential of incorporating any preexisting structural knowledge as prior or constraints. Here we present cryoSTAR, which harnesses atomic model information as structural regularization to elucidate such heterogeneity. Our method uniquely outputs both coarse-grained models and density maps, showcasing the molecular conformational changes at different levels. Validated against four diverse experimental datasets, spanning large complexes, a membrane protein and a small single-chain protein, our results consistently demonstrate an efficient and effective solution to conformational heterogeneity with minimal human bias. By integrating atomic model insights with cryogenic electron microscopy data, cryoSTAR represents a meaningful step forward, paving the way for a deeper understanding of dynamic biological processes.

Can a zero-shot learning Large Language Model code complex interview data?

Abstract Background Psychological autopsy is essential to establish theories, explore trends and identify previously unexplored psychosocial risk factors in suicide research. However, qualitative research has been scrutinized for being prone to interpretation bias, problems with accuracy, challenges to reproducibility, and is very time- and cost intensive. The current study aimed to investigate if a Large Language Model can achieve sufficient agreement with a researcher in the deductive coding of interview data obtained in a psychological autopsy study of suicide, to be integrated with qualitative research procedures. Methods Data from 38 interviews was deductively coded by a researcher and a LLAMA 3 based language model. The model performance was evaluated in four increasingly difficult coding tasks, including binary classification and data summarization. Intercoder agreement scores were calculated using Cohen’s Kappa. Results The preliminary results showed that the LLM achieved substantial agreement with the human coders for the binary classification task (.78). The variability in performance was influenced by code definitions. The results of the quality of LLM interpretation and summarization will also be presented. Conclusions State-of-the-art LLM can be easily integrated into the qualitative analyses of psychological autopsy interviews and may improve real time monitoring of suicides. We recommend a human-AI collaborative model, whereby deductive coding by the LLM is complemented by human inductive coding and further interpretation. Key messages • Integrating an LLM with qualitative research procedures is feasible in a collaborative model. • Integrating an LLM with qualitative research procedures allows near real-time monitoring based on qualitative data, which extends to other public health fields.

Tuberculosis pericarditis: a case report

Tuberculosis (TB) is still prevalent in the world. In 2020, 1.5 million people died from TB.18 TB accounts for 4% of acute pericarditis. Tuberculous pericarditis (TBP) is due to hypersensitivity to tuberculin protein produced by Mycobacterium tuberculosis and develops in 1-2% of pulmonary TB cases, representing about 1-2% of extrapulmonary tuberculosis. Complications occur in the form of acute pericarditis (4%) and cardiac tamponade (7%), which may require life-saving invasive procedures. Tuberculous pericarditis has an overall mortality rate of 1.43 per 100 person-months over a median follow-up of 11.97 months. Risk factors include diabetes, substance use disorder, HIV-positivity, renal insufficiency, biological or immunosuppressive therapy, and exposure to regions with a high prevalence of tuberculosis. We present a 49-year-old diabetic male with a large complex pericardial effusion occurring three months after a diagnosis of TB pleurisy on antituberculosis drugs, which required pericardiocentesis and pericardial window in the context of cardiac tamponade. Cases of TB pericarditis in developed countries are rarely reported, and there are even fewer in the US. Along with a literature review of the road map for its accurate diagnosis and treatment, this case highlights the relevance of TB in the differential of pericarditis worldwide, even in developed countries.

Monitoring and Modelling Fluxes of Water and Nutrients to Surface Drainage Network From Irrigated Agricultural Fields in a Hydraulically Reclaimed Coastal Area

ABSTRACTThis paper describes the application of a physically based agrohydrological model (named FLOWS), coupled with a kinematic wave approach model (named KWV) for water and solute runoff routing, for interpreting the fate of water and nutrients coming from cultivated fields to surface drainage network located in ‘Piana del Sassu’ in the Arborea plain, a hydraulically reclaimed area with shallow groundwater. Modelling was supported by a large complex database on soil, groundwater and surface drainage water, which was used for establishing the boundary conditions for simulations, as well as for calibrating and validating the model. The model FLOWS provided the water and nutrient fluxes to the surface water, which were passed to the KWV model for their routing along the elementary fields in the experimental area and from these to the ditches and finally to the drainage channel. The modelling approach effectively predicted the water and solute distribution along the soil profile, as well as the losses of water and nutrients to the surface water. The results showed a significant amount of water and dissolved nutrients to flow quickly from the soil uppermost layer to the surface drainage network during both the irrigation season and during rainfall events. During irrigation applications, losses were mostly due to rainfall intensity exceeding the maximum infiltration velocity of the shallow soil layer in the case of sprinkler irrigation and to subsurface lateral drainage in the case of exceeding irrigation water provided by drip irrigation. This makes the Sassu plain a significant contributor of nutrients (nitrate and phosphorus) to the surface water. Consequently, even though the agricultural activities might not be an important issue for the groundwater vulnerability, the management of water and nutrients should be significantly improved to avoid ecohydrological threats to the important coastal water bodies present in the area.