The operation of offshore vessels is directly related to the use of flexible pipelines. The article describes in detail the analysis of power, geometric, kinematic and technological parameters that affect the main operational characteristics of these pipes during their operation under water, in rough sea conditions and under wind loads. The article describes the degree of dependence between loads on the pipeline and velocity of the oncoming flow, the geometry of the pipe and the distance to the rigid surface of the ship’s hull or the seabed. It was determined how the flow velocity during parametric oscillations of the pipeline in unrestricted flow and near the surface of the seabed affects the change in its drag and lift coefficients. An estimate of operational limits of flexible pipeline instability was obtained. On the base of changes in distributed load, specific values for safe lengths of pipelines were formulated. It has been stated that the probability of failure-free operation of a flexible pipeline at a level of 0.99 is directly determined by the frequency of its oscillation. Its numerical values should always be at a level that does not exceed 3.7% of the frequency of pipe dynamic oscillations.

Introduction:Thrombophilia can be defined as an increased tendency to develop a thrombus. Thrombophilia aetiology divides into either heritable defects, such as mutations in the genes encoding the natural anticoagulants antithrombin, protein C, protein S, clotting factors, prothrombin, and factor V, or acquired defects, such as antiphospholipid syndrome (1).Antiphospholipid syndrome (APS) is an autoimmune disease characterised by the presence of antiphospholipid antibodies, such as lupus anticoagulant, anticardiolipin antibodies, and anti-β2-glycoprotein 1. APS can present with a variety of clinical phenotypes, including arterial, venous thrombosis, and obstetric complications (2).Patients with APS may have diverse neurological condition these include Cerebrovascular accident , epilepsy, cognitive disorders, headaches/migraine, chorea, multiple sclerosis-like, transverse myelitis, ocular symptoms, and Guillain-Barré syndrome (3).Certain projections suggest that the occurrence of APS stands at approximately 5 fresh instances per year for every 100,000 individuals, with a prevalence of roughly 40 to 50 cases per 100,000 people (4). A study done in 1990 found that in a series of 51 unselected patients presenting with stroke and transient ischemic attacks, three had antiphospholipid syndrome(5).Another cause of thrombophilia is protein c and s deficiency. Protein C and protein S are glycoproteins, predominantly synthesised in the liver, that are important components of the natural anticoagulation system in the body. They are vitamin K-dependent and serve as essential components in the maintenance of physiologic hemostasis (1).Individuals with inherited abnormalities in the protein C and protein S pathways have an increased susceptibility to thromboembolic occurrences like deep vein thrombosis, pulmonary embolism, stroke, and organ ischemia [6].Cerebral venous thrombosis (CVT) is considered as a rare cause of stroke (represent 1% of all stroke form in adult) (1). It tends to affect females which may he attributed to some gender-associated risks as pregnancy and oral contraceptive use (2).Due to its variable presentation; the diagnosis of CVT is still challenging. However, there are common clinical manifestations which include headache, seizure, focal neurological deficit, and altered sensorium. These symptoms may evolve over several days. Risk factors of CVT include hereditary thrombophilia, autoimmune disorder, malignancy and chronic inflammatory diseases. It is worth mentioning that patients with CVT may have more than one risk factor (3).Venous sinus thrombosis can be seen, with or without other peripheral thrombotic events, especially in patients with antiphospholipid syndrome (7).

This research deals with the Kaup-Newell model (KNM), a class of nonlinear Schrödinger equations with important applications in plasma physics and nonlinear optics. Soliton solutions are essential for analyzing nonlinear wave behaviors in different physical systems, and the KNM is also significant in this context. The model’s ability to represent sub-picosecond pulses makes it a significant tool for the research of nonlinear optics and plasma physics. Overall, the KNM is an important research domain in these areas, with ongoing efforts focused on understanding its various solutions and potential applications. A new version of the generalized exponential rational function method (nGERFM) and ( G ′ G 2 ) -expansion function methods are utilized to discover diverse soliton solutions. The nGERFM facilitates the generation of multiple solution types, including singular, shock, singular periodic, exponential, combo trigonometric, and hyperbolic solutions in mixed forms. Thanks to ( G ′ G 2 ) -expansion function method, we obtain trigonometric, hyperbolic, and rational solutions. The modulation instability (MI) of the proposed model is examined, with numerical simulations complementing the analytical results to provide a better understanding of the solutions’ dynamic behavior. These results offer a foundation for future research, making the solutions effective, manageable, and reliable for tackling complex nonlinear problems. The methodologies used in this study are robust, influential, and practicable for diverse nonlinear partial differential equations (NLPDEs); to our knowledge, for this equation, these methods of investigation have not been explored before. The accuracy of each solution has been verified using the Maple software program.

Smallholder farming in dryland areas plays a crucial role in global food security, yet there is limited research on factors influencing the adoption of soil and water conservation (SWC) measures in these regions. This study addresses this gap by investigating SWC practices in Dass, Nigeria, and identifying key determinants affecting their implementation. Data were gathered through structured questionnaires, interviews, and focus groups with farmers across ten wards. Statistical analyses like logistic regression were used to assess socio-demographic influences on SWC utilization. The study highlights that factors such as income, education, distance to farmland, access to financial resources, and participation in farmer groups significantly influence SWC adoption. Interestingly, higher income and education levels were associated with lower SWC utilization, contrary to some existing literature. Conversely, longer distances to farmland increased SWC adoption rates. The findings underscore the importance of tailored strategies, directed to settings of a specific area, for promoting SWC. For the study area, such strategies should include enhancing extension services, improving financial accessibility, supporting farmer organizations, and enhancing education and training initiatives. These no doubt emphasize the need for locally specific approaches to enhance sustainable agriculture practices and food security in dryland farming ecosystems.

Eleven species of Thrixspermum are newly recorded from Thailand, three from sect. Thrixspermum: T. lampongense (Eastern floristic region), T. latisaccatum (Peninsular), and T. tortum (Peninsular); and eight from sect. Dendrocolla: T. anceps (Peninsular), T. bromeliforme (of unknown provenance), T. crassilabre (South-Western), T. duplocallosum (Peninsular), T. merapohense (Peninsular), T. pardale (Peninsular), T. patkaiense (Eastern), and T. pulchellum (Peninsular). Descriptions, photographs, and notes on distribution, ecology, phenology, vernacular names, and recognition are provided. Five species are considered to be uncommon in the wild: T. anceps, T. crassilabre, T. duplocallosum, T. patkaiense, T. tortum; and no precise localities are known for T. bromeliforme.

Recently, PDGFRB rearrangements located on chromosome 5q have been documented in Philadelphia chromosome-like (Ph-like) B-progenitor acute lymphoblastic leukemia (B-ALL). Five genes were reported to be fused with PDGFRB in Ph-like ALL. Only the transcripts EBF1 and ATF7IP, have already been reported as regions targetable by tyrosine kinase inhibitor (TKI). The EBF1-PDGFRB gene fusion is rare, in B-ALL cases, and is typically found within the Ph-like ALL subtype. Evidence from several studies suggests that EBF1-PDGFRB-positive patients who do not respond to conventional chemotherapy may achieve complete responses when treated with TKI such as imatinib. We present the case of an adult patient diagnosed with B-ALL. Following conventional induction chemotherapy, according to GRAALL-2005 protocol, the patient’s disease showed resistance and failed to achieve remission. Cytogenetic study showed 46,XY,del(5)(q23q33) as the sole clonal abnormality. the research for the PDGFRB transcript could not be carried out due to the unavailability of a specialized laboratory allowing this research. Due to induction failure and the risk of abnormal activation of tyrosine kinases, particularly involving PDGFRB on chromosome 5q, the decision was to initiate imatinib at a dosage of 400 mg per day, in combination with conventional chemotherapy. Complete cytologic and cytogenetic remission was achieved one month after starting imatinib with profound negativity of MRD. The patient was treated with the GRALL 2005 protocol in combination with imatinib continuously at a dose of 400 mg/day. The patient still in continuous remission with a negative MRD, after 23 months of starting imatinib treatment.

This article proposes an interest rate model for dual-currency interest rate markets. The model assumes that volatility is a deterministic function of time alone. This volatility structure can reduce the dimension of the required state variables. An important special case is presented, which corresponds essentially to a Vasicek/Hull-White yield curve model in each currency. The model is very useful for pricing cross-currency derivatives.Key Words: interest rate, cross currency, calibration, volatility structure.Introduction:An interest rate reflects the cost of borrowing or the reward of saving. Interest rate curve is the plot of maturities and associated interest rates that illustrates future interest rates in a clear and concise way. Interest rate curve is also called the term structure of interest rates.  Interest rate plays critical roles in finance and economy. It affects everyone and every business. One factor model is mathematically tractable, but may be insufficient to capture all dynamics of interest rate curve movements. As such, multi factor models of interest rates arise to have a better explanation of interest rate evolutions. A multi factor model assumes the movement of interest rates is determined by multiple state variables. The most important contracts for calibrating interest rate term structure models are caplets and swaptions. To get a fast and stable model calibration, it is important to have closed from or semi-closed form approximation for their values. There is a rich literature on interest rate modelling. The first analysis is one factor models, such as Vasicek (1977), and Cox, al et. (1985). These models assume that the movement of an interest rate curve is determined by a single state variable. This state variable is usually called the short rate that follows a stochastic diffusion process. Medova al et. (2006) study interest rate data by using a three-factor interest rate curve model and the Kalman filter. The model captures the salient features of the whole term structure in forward simulation. Yu and Ning (2019) propose an interest rate model by means of uncertain differential equations with jumps and derive a closed form price for zero-coupon bond. Verschuren (2019) develops a coherent framework on how to best incorporate negative interest rates in these studies through a single curve stochastic term structure model.  Kikuchi (2024) presents a new quadratic Gaussian short rate model with a stochastic lower bound to capture changes in the yield curve including negative interest rates. Akram (2020) presents a long-term interest rate model to reflect the central bank’s actions influence the long-term interest rate primarily through the short-term interest rate. Hansen (2023) presents a term structure model for no-arbitrage bond yields and realized bond market volatility and shows that conditional yield curve covariation is priced in long-term yields. Levrero and Matteo [2019] study the relationship between short- and long-term interest rates and outline an asymmetry in the relationship. Bauer and Hamilton (2019) conclude that conventional tests of whether variables other than the level, slope and curvature can help predict bond returns have significant size distortions. This article presents a new interest rate model for cross-currency fixed income derivatives.  These models have the property that all volatility is a deterministic function of time alone. In general, a deterministic volatility structure leads to a model such that if the underlying Brownian motion driving all uncertainty in both economies is of one dimension, then in general three-dimensional state variables are required to completely characterize the yield curve and exchange rate dynamics. The analytic tractability of the constant correlation of the separable deterministic volatility (SDV) model provide closed form formulas for these values as functions of the yield curves and exchange rate volatility (see https://finpricing.com/lib/FxVolIntroduction.html) . By a further judicious choice of volatility structure, one can reduce the dimension of the required state variable.  An important special case for applications is presented in which only three state variables are required.  This case corresponds essentially to a Vasicek/Hull-White yield curve model in each currency.  In this particular case, a general framework for European contingent claim valuation is also worked out. The model concentrates on the evolution of the instantaneous forward rate. We will summarise some standard results and introduce a number of financial variables and concepts such as changes ofnumeraire. The equations describing the dynamics involve a stochastic term which includes a multi-dimensional correlated Brownian motion. When calculating expected values of this Brownian motion it is necessary to specify a probability space and filtration to which the Brownian motion is adapted. The rest of this paper is organized as follows: The model is presented in Section 1; Section 2 studies the relationship with other well-known models. Section 3 elaborates calibration.  Numerical results are discussed in Section 4; the conclusions are given in Section 5.

Saltmarsh habitats sequester significant amounts of carbon from the atmosphere and provide vital habitats for various bird species but are eroding at increasingly rapid rates due to ongoing sea level rise. Yet, in some regions where space and topography permit, saltmarshes are transgressing into adjacent uplands, counterbalancing the lost area. In these areas, a greater proportion of saltmarsh is relatively young but it remains uncertain whether younger marshes support the same plant and animal communities as older ones. We compared soil organic matter (SOM), plant communities, and bird occupancy at 133 marsh patches on the Delmarva Peninsula, Virginia, USA. Marshes that converted from uplands since the early to mid-20th century exhibited lower SOM levels, were more closely situated to trees and snags, and were less likely to support obligate saltmarsh nesting bird species. Areas with past agricultural activity, characterized by features like berms and ditches, exhibited higher SOM levels, supported fewer of the most salt-tolerant plants and more of the least salt-tolerant species, and were more likely to support saltmarsh obligate bird species. We expect areas where a high proportion of relatively young marsh to shift away from the most salt-tolerant plants and birds, especially where an agricultural legacy can be found. We hypothesize that elevated organic carbon content found in formerly farmed fields may result from decreased inorganic sediment input, facilitated by restricted tidal flooding, rather than an enhanced capacity for carbon sequestration. However, further investigation is necessary to conclusively address this issue.

Background Perfluorooctanoic acid (PFOA) is widely used in daily life, however, research has shown its immune suppression function. Our aim is to investigate the relationship between prenatal exposure to PFOA and allergic diseases in children. Methods A prospective birth cohort study involving 648 pregnant women was conducted. Prenatal information was collected by an interview with the women and from medical records. Fetal umbilical cord blood was collected, and concentration of PFOA and genotype of IL-13 rs20541 were detected. Children were followed at 6, 12 and 24 months and information on the development of allergic diseases was recorded. Multivariate logistic regression analysis was used to examine the association between PFOA and allergic diseases. Stratified analysis was performed based on gender and genotype of IL-13 rs20541. Results In multivariate adjusted models, the highest PFOA quartile is associated with odds of atopic dermatitis (AD) (OR 1.66, 95% CI 1.09-2.55), wheezing (OR 4.06, 95% CI 1.30-12.68), and allergic diseases (OR 1.71, 95% CI 1.15-2.54). Female patients with the highest PFOA quartile have a higher odd of AD (OR 2.25, 95% CI 1.20-4.23) and allergic diseases (OR 1.93, 95% CI 1.07-3.46). Patients with GG genotype of IL-13 rs20541 and the highest PFOA quartile also have a higher odd of AD (OR 2.82, 95% CI 1.41-5.67), wheezing (OR 15.16, 95% CI 1.38-166.59), and allergic diseases (OR 2.42, 95% CI 1.27-4.61). Conclusions Prenatal exposure to PFOA increases the risk of developing allergic diseases in children, especially for the female patients and those with the genotype of IL-13 rs20541 GG.

Background: In SARS-CoV-2 infection, in addition to the production of virus-specific antibodies, autoantibodies can also be produced, which attack self-structures and worsen the prognosis. We hypothesized that overproduction of virus-specific antibodies may also trigger autoantibody production. Methods: To test this hypothesis, the antinuclear antibody (ANA) positivity rate was examined in samples with high and low (i.e., negative) anti-SARS-CoV-2 antibody levels. A quantitative ELISA test kit with a dynamic measurement range of 1-475 RU/mL was used to determine Sars-CoV-2 antibodies. In the high SARS-CoV-2 antibody criterion, it was required to have the last quarter antibody level (>235 RU/mL) in the ELISA calibration curve. For low antibody levels, the requirement was <15 RU/mL. Anti-SARS-CoV-2 antibody levels of 1222 samples were examined and 62 (33 men, 29 women) samples were determined to have high antibodies (high group; HG). Among the samples with low antibody levels, 62 gender-matched samples were selected by randomization (low group; LG). ANA positivity was analyzed with 3 different commercial ELISA test kits (anti-dsDNA, anti-ENA, anti-Hep-2 nucleus; Y immunoTEK, Turkey). Total IgG levels were also measured to evaluate the difference in total antibody levels. Results: Anti-SARS-CoV-2 antibody levels were 413 ± 72 RU/mL and 3.8 ± 1.4 RU/mL for HG and LG, respectively (p<0.001). The ANA positivity rate was found to be significantly higher in HG than in LG (anti-dsDNA 9/62, 14.5% - 19/62, 30.7%; anti- ENA 10/62, 16.1% - 22/62, 35.5%; anti- Hep-2 nükleus 8/62, 12.9% - 20/62, 32.3% respectively). There was no difference between total IgG levels (HG; 11.1 ± 3.0 and LG; 10.6 ± 3.4 mg/mL) (p>0.05). Conclusions: As a result, it was determined that high levels of SARS-CoV-2 antibody production were associated with the formation of ANA. This suggests that SARS-CoV-2 antibody and ANA production have similar mechanisms or pathways.

Iodine-131 Therapy for Graves’ Disease: A Case Report of Radiation Thyroiditis and Its ManagementParry, R.1,2, Asokendaran, M.21School of Medicine, University of Western Australia, Perth, Australia.2Department of Nuclear Medicine, Fiona Stanley Hospital, Perth, Australia.

A document by Annie Jiao Wang. Click on the document to view its contents.

In recent years, artificial intelligence (AI) has made significant strides, primarily because of the widespread adoption and usage of open source machine learning models across various industries. Given the high resource demands of training the models with large datasets, many applications now rely on pre-trained models which save considerable time and resources, allowing organizations to concentrate on training and sharing these crucial models. However, using open-source models introduces risks issues in privacy and security that are often neglected. These models can sometimes harbor hidden functionalities that, when specific input patterns triggered , can alter system behavior, such as causing self-driving cars to disregard other vehicles. The impact of successful privacy and security attacks can range from minor disruptions in service to extremely serious consequences, which lead to outcomes such as physical harm or the disclosure of sensitive user information and data. This research offers an in-depth review of common privacy and security risks linked to open-source models, aiming to raise awareness and encourage the responsible and secure use of AI systems.

Unmanned Aerial Vehicles (UAVs) have become indispensable assets in various sectors, leveraging their mobility and data collection capabilities. However, privacy and security concerns have fueled interest in Federated Learning (FL) as a solution. FL, decentralized and collaborative, offers promise in addressing privacy risks inherent in centralized data processing while enhancing model performance. In this review, we explore FL’s privacy and security implications in UAV ecosystems. We highlight FL’s potential to mitigate privacy risks by aggregating model updates locally, minimizing data transmission needs. Additionally, we examine security challenges and evaluate protective mechanisms. Through a systematic literature review, we identify gaps and propose future research directions, aiming to enhance the security and privacy of FL in UAV applications.

Over the past two decades, patient-centered care has gained global prominence, emphasizing collaboration among patients, families, caregivers, and healthcare professionals to improve healthcare delivery. Recognizing the foundational role of patient participation in enhancing clinical outcomes, healthcare organizations increasingly integrate patient inputs and resources into their management strategies. Patient and Family Advisory Councils (PFACs) represent a primary form of collective patient engagement at the organizational level. PFACs actively engage in all levels of the hospital system to enhance quality improvement and meet the demands of patients. Despite PFACs’ recognized importance, empirical evidence regarding their roles as strategic resources and impact on hospital performance remains unexplored. Incorporating patient engagement into SRBV, this study addresses how comprehensive strategic resources are associated with a hospital’s quality of care and patient satisfaction outcomes. Utilizing hospital-level data from 2018 to 2020, a cross-sectional time-series ordered logit analysis examines the quality of care and satisfaction models. The findings reveal that patient engagement, physical resources, and human capital are positively associated with hospital quality of care and patient satisfaction. In contrast, a social resource – a minority population – is negatively associated with hospital outcomes. This study contributes theoretical and practical implications. It synthesizes patient engagement into the SRBV approach and provides consistent empirical evidence. In addition, it suggests evidence for practitioners to develop and manage patient engagement as a strategic resource.

This study tackled the critical public health threat of counterfeit drugs in Nigeria’s pharmaceutical industry. Deceptive medicines, containing incorrect or harmful ingredients, are difficult to identify and have a significant impact on low- and middle-income countries, where estimates suggest over 10% of medicines are fake. To combat this issue, a CNN Hybrid model was developed to analyze a self-captured dataset of medicine packages in the form of images and National Agency for Food and Drug Administration Control (NAFDAC) numbers. Only 10 of Nigeria’s registered pharmaceutical brands were taken into consideration due to the availability of products. Few samples of counterfeit drugs were obtained from NAFDAC. Other samples were constructed using adapted techniques from existing studies; this was achieved by modifying the original graphics slightly to create the counterfeit logos. The proposed model leveraged pre-trained deep learning architectures, ResNet-50 and VGG16 (V16RN-50), to extract features from the images that were used for classification. The extracted features were concatenated and fed into the custom trainable dense and output layer designed to identify counterfeit and real medicines. The model achieved an impressive result in multi-classification with a training accuracy of 95.83%, a validation accuracy of 94.82%, and a test accuracy of 95.1%. Counterfeit medicine detection also yielded an excellent training accuracy of 98.8%, a validation accuracy of 98.1%, and a test accuracy of 97.3%. The findings were further strengthened by high precision, recall, and F1-score metrics of 0.951, 0.951, and 0.951 for brand recognition and 0.973, 0.973, and 0.973 for detection of counterfeit medicines respectively. Additionally, the model outperformed the benchmark studies in counterfeit detection. The research demonstrated the potential of the proposed models to detect counterfeit drugs and contribute to improved public health in Nigeria .

Climate change and human influence are transforming mountain ecosystems, significantly impacting species distributions and biodiversity. Among these changes, the upward migration of lowland species into mountain regions stands out. This study examines the ecogeographical niche overlap and genetic diversity among three Leucanthemum species in the Carpathian Mountains distributed along an altitudinal gradient: the lowland L. ircutianum (4x), the montane L. rotundifolium (2x), and the alpine L. gaudinii (2x). By genotyping over 600 individuals using SNP analysis, followed by Principal Coordinate Analysis (PCoA), Neighbor-Net Network, and Structure clustering, we reveal not just distinct genetic groups but also hybridization across all species, suggesting the potential for triple hybrids. Genetic admixture is further supported by environmental background and niche overlap analyses that reveal substantial overlap among species, particularly in line with their vertical distribution. Climate envelope plots indicate a likely reduction in available habitat for mountainous species due to climate change, leading to an increase in competition and an intensification of hybridization. Anthropogenic influences are further intensifying these hybridization trends. Among the studied species, L. gaudinii is most at risk of overwhelming hybridization, whereas L. ircutianum may experience habitat expansion. By providing a comprehensive genetic and ecological overview, our research highlights the significance of hybridization in biodiversity conservation and the challenges posed by environmental changes and anthropogenic activities in mountain environments. This study not only contributes to the understanding of genetic diversity in the Carpathians but also underscores the broader implications for molecular ecology and conservation strategies in mountain ecosystems.

An aortic periannular abscess (PA) is a critical consequence of infective endocarditis (IE). In our case report, the patient’s clinical symptoms were only fever, cough, and shortness of breath. Then he was diagnosed with aortic PA, which was overlooked in the initial transthoracic echocardiography (TTE) assessment but later identified through transesophageal echocardiography (TEE). The patient underwent surgery immediately and recovered well. This case underscores the importance of TEE in revealing small, yet critical, intracardiac lesions that may be missed by TTE.

Plant genetic engineering technology can rapidly and precisely improve desired traits in plants, overcoming conventional breeding bottlenecks, achieving simultaneous enhancement of plant quality and yield to meet human needs. Compared to conventional plant genetic transformation methods, nanomaterials, as carriers for the intracellular delivery of exogenous genetic material, possess advantages such as being independent of genotype restrictions, strong biological affinity, biocompatibility, high cell permeability, enabling targeted transformation of functional genes, effective protection of exogenous genetic material from degradation and damage, as well as simple operation. Therefore, in recent years, nanomaterials as external biological molecular delivery tools in plant genetic transformation have received widespread attention. Due to the various requirements for nanocarriers used in plant genetic transformation, designing and synthesizing effective nanomaterials suitable for nucleic acid delivery is not easy. Therefore, the review aims to analyze and summarize the recent advances in the application of nanomaterials in plant genetic transformation, explore the mechanisms of nanomaterial-nucleic acid complexes entering plant cells/organelles and their main influencing factors, thus providing a preliminary understanding of the interaction mechanism between nanocarriers and plant cells/organelles. Meanwhile, the application of different types of nanocarriers in plant genetic transformation was classified and summarized to promote the rational design of nanocarriers for plant genetic transformation and enhance their effective utilization in plant genetic transformation.

The brown alga Padina (Dictyotales, Ochrophyta) is found worldwide, predominantly in tropical to subtropical waters. Due to their similar appearances, distinguishing between different Padina species is challenging. Historically, morphological characteristics such as the degree of calcification and thallus color were the primary methods for identifying and differentiating Padina species, which often led to misidentifications. The advent of molecular-aided taxonomic identification has allowed for more reliable classification of species. In this study, we utilized sequence comparisons of two genes, the chloroplast rbcL and the mitochondrial cox3, to identify Padina specimens collected from six sites along the Israeli coast of the Mediterranean Sea. Our results revealed the presence of three distinct Padina species: P. pavonica, P. boergesenii, and P. pavonicoides, the latter of which has not been previously reported in this region. Additionally, we observed that the distribution of these species along the shores was not homogeneous: P. pavonica was predominantly found along the northern shores, while P. boergesenii was mostly found along the southern shores.

As a young scientist in Brazil, my journey began in a public school, where I faced the typical challenges of the Brazilian public education system, such as a lack of resources and support. With immense dedication and resilience, I successfully gained admission to the University of São Paulo (USP), a prestigious institution and one of the top universities in Latin America. Currently, my research focuses on the relationship between the nervous and immune systems in psychosis, a topic I am deeply passionate about. In this piece, I will delve deeper into the challenges and achievements of being a young scientist in Brazil. I also discuss the systemic issues within the Brazilian education and research system, and the changes needed to foster a more supportive and resourceful environment for emerging scientists.

A document by Maisha Maliha. Click on the document to view its contents.

Visual search is guided by mental representations of target-defining features (attentional templates) that are activated in a preparatory fashion. It remains unknown how many templates can be maintained concurrently, and what kind of costs are associated with multiple-template versus single-template search. Here, we compared the operation of attentional templates during three-colour and single-colour search tasks. Preparatory template activation processes were tracked by measuring N2pc components to task-irrelevant singleton colour probes that appeared in rapid succession during the interval between search displays. These probes attract attention (as indexed by an N2pc) if the corresponding colour template is active at the time when the probe appears. In a three-colour search task where target identity was fully predictable (Experiment 1), only probes that matched the upcoming target colour triggered N2pcs, demonstrating that only a single target template was activated. When three possible colour targets appeared randomly and unpredictably (Experiment 2), probes that matched any of these colours triggered N2pcs, demonstrating that all three templates were activated concurrently. However, relative to a single-colour search task, clear costs emerged in this three-colour task for the attentional guidance towards search targets and for search performance. These costs appear to be linked to inhibitory interactions between simultaneously active search templates. These findings show that while at least three target templates can be maintained in parallel, multiple-template search is still subject to capacity limitations which affect both template-guided attentional guidance and the subsequent selective processing of search targets.

Research has shown that exposure to higher rates of neighborhood disadvantage and contextual threat increases risk for the development of psychopathology in youth, with some evidence that these effects may differ across racial/ethnic groups. Although studies have shown that direct exposure to stress impacts neural responses to threat-relevant stimuli, less is known about how neighborhood characteristics more generally (e.g., living in neighborhood characterized by high crime risk, whether or not the individual directly experiences any crime) may impact children’s neural responses to threat. To address this question, we examined links between census-derived indices of neighborhood crime and neural reactivity to emotional stimuli in a sample of 100 children (Mage = 9.64, 54% girls, 65% non-Hispanic White) and whether these relations differ for children from minority backgrounds compared to non-Hispanic White children. Focusing on the late positive potential (LPP) event-related potential (ERP) component, we examined neural reactivity to threat-relevant stimuli (fearful faces) as well as non-threat relevant negative (sad faces) and positive (happy faces) stimuli across low, medium, and high intensities (morph levels). We found that levels of neighborhood crime were associated with LPP response to high intensity fearful, but not happy or sad, faces, but only among children from racial/ethnic minority backgrounds. This suggests that levels of crime within one’s neighborhood may be a more salient stressor for children from minority racial-ethnic groups than for non-Hispanic White children.