In the ever-evolving landscape of cybersecurity, the application of game theoretic models has emerged as a powerful and innovative approach to enhance our understanding and management of cyber threats. This abstract explores the application of a variant of game theoretic models within the context of a Cyber Threat Intelligence (CTI) framework. With the proliferation of cyber-attacks targeting critical infrastructure, sensitive data, and national security, it has become imperative to develop proactive and adaptive strategies for threat detection, mitigation, and response. The variant of game theoretic models discussed in this abstract departs from traditional game theory by incorporating elements of dynamic adaptation and machine learning. This adaptation enables the framework to model and analyze the intricate and rapidly changing interactions between threat actors and defenders in real-time, thereby providing a more accurate representation of the evolving threat landscape. By leveraging machine learning algorithms, the model can continuously learn and adapt to new threats and tactics, making it a versatile tool for CTI. This abstract also explores the practical applications of the variant model in various aspects of cybersecurity, including threat actor profiling, vulnerability assessment, and decision support for incident response. By considering the strategic motivations and behaviors of threat actors, organizations can make informed decisions regarding resource allocation, risk assessment, and security investments. The integration of this variant of game theoretic models into CTI holds great potential to revolutionize our approach to cybersecurity, enabling organizations to stay one step ahead of adversaries. As the digital world becomes increasingly complex, the ability to predict, mitigate, and adapt to cyber threats is crucial for safeguarding critical assets and ensuring the resilience of digital infrastructure. This paper highlights the significance of this innovative approach and its potential to shape the future of cyber threat intelligence and cybersecurity practices.

A new species of Chlorophytum is described and illustrated in this article. Morphological, root anatomical, pollen and molecular features were compared with its allied species C. laxum R. Br. which has apiculate anther, lanceolate bract, 16-18 nerved flat leaf and ellipsoid pollen with contrast to obtuse anther, ovate bract, 11-13 nerved conduplicate leaf and ovoid pollen. The molecular features too compliment the differences.

Objective: This case series explored the integration of smartwatches in a community mental health service to support severe mental illness (SMI) management and intervention. We examined whether biometric data provided by smartwatches could help to predict relapse and inform treatment decisions. Method: Four SMI patients were selected from a prior study. Clinicians accessed patients’ biometric data (activity, sleep, heart rate, and electrodermal activity) through smartwatches. Results: Changes in circadian rhythm and electrodermal activity preceded hospitalization in two cases. Additionally, smartwatch data was effectively used to guide targeted interventions, improving patient treatment outcomes. Conclusion: Integrating smartwatches in community mental health services offers promise as adjunct tools for severe mental illness management. However, ethical considerations on data privacy and technology reliance require further evaluation.

Background: Evidence supporting a correlation between unconjugated bilirubin and schizophrenia is considerable. Most previous studies have reported a statistically relevant link between the two variables. Aim of the Work: To assess the level of unconjugated bilirubin in patients with schizophrenia in acute episode and to analyse its correlation with the psychopathological, psychosocial and neuropsychological dimensions. Patients and Methods: A sample of 80 subjects with schizophrenia; divided into two major groups: Cases (40 patients in relapse) and Controls (40 patients in remission) were recruited. Subjects were diagnosed by DSM-IV and underwent the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I), Positive and Negative Syndrome Scale (PANSS), General Assessment of Function (GAF), and Trail Making Test (TMT) were used to assess severity of symptoms, social functioning, and cognitive functioning respectively. Subjects underwent a blood draw to measure serum bilirubin level. We analysed the relation and correlation of unconjugated bilirubin with the previous scales scores. Results: The study found that patients with schizophrenia had significantly higher levels of total bilirubin, and indirect bilirubin than healthy control subjects. Only one subject (with schizophrenia) had an abnormally elevated total bilirubin level (> 1.2 mg/dL). None of the subjects had a clinically abnormal direct (> 0.3 mg/dl) or indirect bilirubin level (> 1.2 mg/dL). A statistically significant positive correlation was found between PANSS total score, PANSS N score, and PANSS G score with total, direct, and indirect bilirubin levels. Linear regression analysis showed that none of the variables entered into the analysis (age, gender, smoking, BMI, Total PANSS, PANSS P, PANSS N, PANSS G, GAF, TMT-A, TMT-B, duration of psychotic disorder, duration of untreated psychosis, and antipsychotic medications) were predictive for total or indirect bilirubin levels. However, Total PANSS, PANSS N, and PANSS G were significantly predictive for direct bilirubin levels. Conclusion: Our study managed to find a statistically significant difference for total and unconjugated bilirubin mean serum levels between patients with schizophrenia and healthy individuals. However further longitudinal studies are needed to reveal the contradictory results in literature on the unconjugated bilirubin and Schizophrenia.

Background: Radiation-induced lung injury (RILI) is a common consequence of thoracic radiation therapy that lacks effective preventative and treatment strategies. Dihydroartemisinin (DHA), a derivative of artemisinin, affects oxidative stress, immunomodulation, and inflammation. It’s uncertain, nevertheless, whether DHA reduces RILI. In this work, we looked into the specific mechanisms of action of DHA in RILI. Methods: The mice were irradiated with 20 Gy 6 MV irradiation dose followed by administration of DHA and Brusatol for 30 days. Pathologic changes in the lungs were observed thereafter. TNF-α, TGF-β, glutathione peroxidase (GPX4), Nuclear factor erythroid 2-related factor 2 (NRF2), and heme oxygenase-1 (HO-1) expression in lung tissues were detected. In addition, mitochondrial ultrastructural changes in lung tissues were also observed, and the GSH content in lung tissues was assessed. Results: DHA attenuated radiation-induced pathological lung injury and inflammatory cell infiltration. Additionally, it decreased the synthesis of inflammatory substances like TNF-α and TGF-β. DHA additionally stimulated the Nrf2/HO-1 pathway. DHA inhibited cellular ferroptosis and upregulated GPX4 and GSH levels. The Nrf2 inhibitor Brusatol reduced DHA’s inhibitory effect on ferroptosis. Conclusion: DHA modulated the Nrf2/HO-1 pathway to prevent cellular ferroptosis, hence reducing RILI. Therefore, DHA could be a potential drug for the treatment of RILI.

Background: Benzothiazole and its derivatives have been extensive studied due to their versatile biological properties and pharmaceutical applications. We recently found that the BMP326 (1-(1,3-benzothiazol-2-yl)-3-(2-methoxyphenyl)-1H-pyrazol-5-ol), a novel benzothiazole derivative, have anti-inflammatory properties in lipopolysaccharide(LPS)-induced RAW264.7 macrophages and there were no relevant reports previously. Methods and Results: Treatment with BMP326(5, 10 and 20 μM) can significantly inhibit nitric oxide production and down-regulate mRNA expression of nitric oxide synthase (iNOS) and cyclooxygenase-2 (COX-2) but did not cause significant cytotoxicity on RAW264.7 macrophages. It is also observed BMP326 can inhibit LPS-stimulated interleukin (IL)-6, interleukin(IL)-1β, tumor necrosis factor (TNF)-α production depending on its dosage. The gene transcription levels of IL-6, IL-1β and TNF-α were reduced under BMP326 exposure in LPS-treated RAW264.7 cells. In addition, we explored the inhibitory mechanisms of BMP326 on the production of pro-inflammatory mediators. The results showed that BMP326 inhibited nuclear factor kappa B (NF-κB) activation by reducing the phosphorylation of p65 and IκBα. Moreover, the phosphorylation of p38 MAPK (p38), extracellular signal-regulated kinases 1/2 (ERK1/2), and c-Jun N-terminal kinase (JNK) in RAW264.7 cells which are stimulated with LPS were suppressed in a dose-dependent manner. Conclusions: In summary, these results suggest that BMP326 exerts anti-inflammatory properties via suppression of the NF-κB and MAPKs signaling pathways.

a new species, Fritillaria pavehensis from Kermanshah province in western Iran was described in the present study. F. pavehensis is similar to F. crassifolia, F. kurdica and F. hakkarensis in F. crassifolia group in general facies but differs mainly by the shape and size of its lowest leaves and bracts, shape and colour of perigone segments. The detailed taxonomic descriptions, diagnostic characters, original photographs, geographical distributions, habitat, phenology and ecology, etymology, conservation status, and phylogenetic dendrogram of the new and the related species are presented in the present study.

The actuator line method (ALM) is a widely-used tool for the modelling of horizontal axis turbines and wind and tidal farm flows. The method uses a virtual blade representation to simulate the dynamics of wind turbines without the computational expense associated with resolving the blade geometry. Within the ALM the flow is first sampled at each blade section, allowing for the calculation of the sectional lift and drag forces that are in turn imposed on the flow domain using a smearing kernel. In this work the effect of the flow sampling method on the robustness of the ALM is discussed. Implementations of two widely-used types of methods for horizontal axis wind turbines are tested: point sampling, where the flow is sampled at or near the collocation point, and volume average sampling where flow field information from multiple points centered at the collocation point is averaged into a representative blade-local velocity vector. A third method, line average sampling, that was initially proposed for sampling flows from blade resolved simulations is adapted for the ALM framework. This method samples the flow symmetrically around a control element in order to eliminate the interference of the bound circulation, thus allowing the inflow velocity at the aerofoil to be determined. When evaluating power and thrust coefficients as well as the flow field at the rotor plane predicted by the ALM, the line average sampling approach is demonstrated to be more robust and converges faster with time step for two different rotors: a small wind rotor and a high solidity tidal rotor. This suggests that carefully selecting the sampling method could be key in alleviating the very strict time step restriction imposed by the ALM, a widely acknowledged limitation of the method. Such an advancement could contribute towards improving the computational efficiency and tractability of the method.

Background: Peripheral blood-derived natural killer (NK) cells spontaneously lyse tumor cells without prior sensitization. However, NK cells in peripheral blood (PBNK cells) are in a resting state and exhibit inhibitory phenotypes and impaired cytotoxicity. Thus, strengthening the cytotoxic effector function of PBNK cells and improving NK cell expansion in vitro for a convenient allogeneic therapy are essential. Materials and Methods: Pure cytokine activation and expansion of NK cells [super NK (SNK)] from peripheral blood mononuclear cells were studied. Markers of activated and inhibited NK cells and cytokine secretion by NK cells were examined using flow cytometry. NK cell antitumor activity in vitro was assessed using lactate dehydrogenase (LDH) cytotoxicity assay and an Incucyte real-time imaging system. Additionally, the function of SNK cells against ascites caused by ovarian cancer in NOD-Prkdc(em26Cd52)il2rg(em26Cd22)/Nju (NCG) mice were determined. In a further investigation of the differences between PBNK and SNK, the mRNA of both cells was sequenced and analyzed. Results: Human peripheral blood mononuclear cells showed selective NK cell expansion upon cytokine activation and culture. Both SNK and PBNK cells expressed activation markers, but at different levels, and SNK cells secreted more cytokines related to cytotoxicity than PBNK cells did. Accordingly, SNK cells exhibited strong antitumor activity ex vivo and improved NCG mice survival after intraperitoneal ovarian cancer transplantation. Mechanistically, SNK cells expressed more genes associated with nucleotide metabolism, fatty acid, and ATP metabolism than PBNK cells. Conclusion: SNK cells derived from peripheral blood mononuclear cells have sufficiently activated mature characteristics and high antitumor activity, rendering them a highly promising and essential therapeutic approach for cancer treatment. KEYWORDS Natural killer cell; Peripheral blood; Ovarian cancer; Ascites

We developed a highly versatile transition metal-free Suzuki type cross-coupling protocol. Alkenyl/aryl boronic acids could couple smoothly with bulky Csp3 electrophiles in the presence of mild bases. The counterion in the base plays a crucial role for the reactivity. Our metal-free condition is orthogonal towards the classic transition metal catalyzed Suzuki reactions.

Fairness plays a pivotal role in moral development, and need-based allocation, as a form of equitable resource distribution, entails allocating resources to individuals with greater need. Children’s need-based behavior is influenced by a variety of factors, including situational, personal, and social aspects. Currently, the motivational explanations for children’s need-based allocation are not fully understood. Here, we present an explanatory model for comprehending children’s motivation to allocate based on needs. We propose that children’s motivation to engage in need-based behavior is a dynamic process that unfolds in three stages: the balancing tendency stage (4-5 years old), the balancing-altruistic dual-motivation stage (6-7 years old), and the altruistic tendency stage (8 years old and above). In conclusion, we offer a perspective on future research directions aimed at gaining a deeper understanding of the developmental process underlying children’s fair decision-making.

In the realm of social media, cyberbullying’s pervasive impact raises urgent concerns about its emotional and psychological toll on victims. This study addresses the imperative of effectively detecting cyberbullying. By leveraging ML and DL techniques, we aim to develop reliable methods that accurately identify instances of cyberbullying in social media data, enhancing detection efficiency and accuracy. This facilitates timely intervention and support for affected individuals. In this comprehensive analysis of existing systems, various ML and DL models are extensively texted for cyberbullying detection. The evaluated models include Random Forest, XgBoost, Naive Bayes, SVM, CNN, RNN, and BERT. Pre-processed datasets are utilized to train and evaluate the models. To evaluate the ability of each model to reliably identify cyberbullying in social media data, performance metrics such as F1 score, recall, precision, and accuracy are used. The findings of this study demonstrate the efficacy of different ML and DL models in monitoring cyberbullying in social media data. Among the models evaluated, the BERT model exhibits exceptional performance, achieving the highest accuracy rates of 88 .8% for binary classification and 86 .6% for multiclass classification.

Objectives:To analyze the function and roles of circRNAs in the peripheral blood mononuclear cells (PBMCs) of ankylosing spondylitis (AS) patients. Methods: The expression of AS-related circRNAs were detected by high-throughput RNA-sequencing within the PBMCs of 5 AS cases and healthy controls. After profiling circRNA expression in these samples, differentially expressed circRNAs (DECs) were identified, and a qPCR-based validation approach was used to confirm the differential expression of six of these DECs in patient samples. Spearman’s correlation tests and ROC curve analyses were further used to assess the relationship between disease severity and the expression of DECs of interest in AS patients, after which a putative circRNA-microRNAs (miRNAs) interaction network was constructed leading to the detection of six validated DECs with competing endogenous RNA (ceRNA) functionality. Besides, cell experiments were also performed to investigate the potential mechanism of key circRNA in AS. Results: 10,441 circRNAs were identified in these 10 PBMC samples, with 131 total DECs including 89 and 42 that were up- and down-regulated, respectively. In qPCR validation assays, patterns of hsa_circ_0000702, hsa_circ_0006209, hsa_circ_0047920, hsa_circ_0001543, hsa_circ_0072697 and hsa_circ_0005076 were confirmed to align well with RNA-seq results. In addition, the expression levels of hsa_circ_0006209, hsa_circ_0047920, and hsa_circ_0072697 were detected to be positively correlated with disease severity. ROC curve analyses suggested that hsa_circ_0072697 may offer value as a diagnostic biomarker for AS. Cell experiments indicated that hsa_circ_0072697 could suppress the progression of AS by targeting NF-κB pathway Conclusions: The identification of six circRNAs with putative ceRNA functionality in AS patients highlights potential molecular mechanisms governing this debilitating disease. However, further research will be necessary to formally confirm the roles of these DECs and their target miRNAs in AS. Further, hsa_circ_0072697 has a good diagnostic value in AS patients, and it could suppress the progression of AS by targeting NF-κB pathwa

The gut microbiota significantly impacts antitumour immunity and alters the effectiveness of cancer immunotherapy. Immunotherapies, notably inhibitors of immune checkpoints that target programmed death 1 (PD-1) and cytotoxic T lymphocyte-associated antigen 4 (CTLA-4)， have profoundly changed the way advanced and metastatic cancer is treated and dramatically improved overall and progression-free survival. However, the underlying molecular mechanisms by which the gut microbiota affects antitumour immunity and the efficacy of cancer immunotherapy remain elusive. In this review, we summarize the latest knowledge supporting the associations among the gut microbiota, antitumour immunity, and immunotherapy. The potential molecular mechanisms underlying these associations are explained in terms of four aspects.

The co-regulation of biological stress systems within the parent-infant dyad plays an important role in the development of infant stress regulation, affecting several physical and psychological processes across the lifespan. Infrared thermal imaging (ITI) allows to capture cutaneous temperature modulations under the control of the autonomic nervous system in a non-invasive and ecological manner. Here, we discuss potential applications of ITI to investigate dyadic autonomic responses in parent-infant interactions. We systematically review studies assessing infant or parent-infant facial temperature during social exchanges. Four studies were retrieved with sample sizes ranging from 10 to 18 and children’s ages ranging from 2 to 42 months. Initial evidence suggests that facial thermal variations are sensitive to social challenges early in life and that ITI can detect patterns of dyadic autonomic synchrony. Albeit preliminary, findings outline the potential of ITI as a new tool for the ecological investigation of autonomic regulatory processes in early interactions.

There are unique reef patches in the Biosphere Reserve Banco Chinchorro reef lagoon that have an unusual formation. They appear to be miniature atolls. These formations are at a depth of 2-6 m; however, a few meters away, presenting flowering microatolls occur while others are strongly impacted. In this context, to define the causality of this phenomenon, an analysis of three of these formations was carried out; to try to relate the structure of the corals that make up these formations to the factors of the environment. Records in nictemeral cycles, twelve environmental parameters, and micronutrients. Despite their closeness, the diversity of these patches is high in two of them and very low in the third. These results show notable differences that typify each of them, according to their position on the reef (leeward and windward), in addition, these patterns relate to the underwater scurry of possible relict water that drains from the lagoon microsystem of the main island of the reef, Cayo Centro, towards the microatolls.

Objective To report a case of Granulomatosis with Polyangiitis (GPA)with Diffuse alveolar hemorrhage(DAH)that developed following Coronavirus disease 2019 (COVID-19) in an adolescent boy, and perform a literature review to better understand this disorder.Methods Retrospectively analyze the data of a case of GPA following COVID-19 infection, to summarize the clinical characteristics of GPA following COVID-19 infection by searching the database (PubMed,Wanfang Data,CNKI) and comprehensively analyze the literature results. Results 9 cases were reported，combined with our case，there were 10 cases of GPA following COVID-19 infection,including 4 males and 6 females,with an average age of(40.6±18.6)years,and the time interval between COVID-19 and diagnosis of GPA ranged from 1 day to 3 months for all 10 cases. The rate of mortality was 10.0%(1/10).Commonly seen clinical manifestations were cough(70.0%),dyspnea(50.0%),and Arthralgia/Myalgia(40.0%). CT scans showed ground-glass opacities，multifocal pulmonary nodules.Of all these patients, c-ANCA and PR3-antibody positivity were found .Conclusion COVID-19 pneumonia and COVID-19- induced new-onset GPA share many clinical and radiological features, making it challenging for clinicians to distinguish between the two. Our study also provided some clues about the diagnostic challenge of GPA induced by COVID-19.

Previous studies have demonstrated the negative impacts of ostracism on primary needs and moods, particularly children and adolescents. Given children’s early exposure to the Internet, online ostracism could potentially affect their primary needs and moods at an earlier age. To investigate this, the present study utilized the Cyberball paradigm to manipulate the exclusion and re-inclusion and examined the threats to primary needs (sense of belonging, self-esteem, control, meaningful existence) and emotions (happiness, sadness, anger) in school-aged children (163 children aged 6-8, 8-10, and 10-11) following social exclusion and subsequent inclusion. The findings revealed that the threats to the four primary needs due to ostracism began to emerge around the age of 8-10 years and persisted until the age of 10-12 years. Regarding moods, the negative effects of ostracism appeared from the age of 6-8 years and worsened with age. This suggests the existence of a critical period during which ostracism poses a threat to children’s primary needs and has adverse effects on their moods. Moreover, the study demonstrated that brief inclusion following exclusion effectively restores the primary needs and moods of ostracized children. These findings provide insights into how to support children in recovering from the negative effects of ostracism.

Background. Mental illnesses mostly occur before 25 years of age when early identification and intervention could delay, ameliorate, or prevent lifelong disability. However, several challenges hinder optimal psychiatric care in youth due to the diversity of presentations, comorbidities, illness courses, and treatment responses. It is increasingly clear that one-size-fits-all approaches will not be effective and personalised approaches are needed to guide therapeutic pathways for individuals. Following precedents in other medical fields, machine learning approaches may address these needs by providing decision support tools that predict diagnoses, prognoses, and therapies. This paper outlines how such a future of augmented care may be facilitated through the establishment of the world’s first ‘Prediction of Early Mental Disorder and Preventative Treatment Centre of Research Excellence’ (PRE-EMPT). Methods. Five key components of the Centre will be addressed, including interdisciplinary collaboration, data harmonization, methods sharing, development of decision support tools, and capacity building. Conclusion. Implementation of research methodology guidelines within the Centre will assist in the production of reproducible, transparent, and open-source techniques and models. When combined, this paper will address key challenges facing the future of psychiatric care for youth and a roadmap of how to address them.

Seagrass ecosystems play a vital role in marine environments, providing essential services, and supporting a diversity of fauna and algae that are critical components in marine trophic structures. However, global and local seagrass declines due to various influences raise concerns about the health of these ecosystems. This study investigated the structural and environmental drivers influencing epifaunal communities associated with the dwarf eelgrass ( Zostera capensis), in a temperate lagoon ecosystem. Variation in epifaunal patterns across phenotypically distinct seagrass populations were observed. Large-leaved morphotypes in deeper intertidal stands near the lagoon mouth exhibited higher species diversity and richness. Conversely, small-leaved populations in higher shore stands supported greater species abundances, notably, two desiccation-resistant gastropods, Assiminea sp. and Siphonaria compressa. Seasonal differences in epifauna were significant, with higher abundances observed during spring and summer, while diversity and richness peaked in autumn and winter. Several key factors influencing epifaunal abundances were identified. The results of structural equation modelling showed seagrass shoot densities and leaf width to have positive direct effects, with light (turbidity) and oxygen levels also playing important roles. Temperature, pH, and exposure indirectly affected epifaunal abundances, however, temperature had a direct effect on seagrass structure and significantly influenced five out of six seagrass metrics measured. Ongoing assessments of seagrass distribution in the lagoon indicate more significant declines in populations near to the lagoon mouth, suggesting a simultaneous reduction in associated epifaunal communities reliant on large-leaved seagrass beds. As climate change-induced warming continues, further declines in seagrass populations are anticipated, particularly in large-leaved varieties. This trend is likely to have adverse consequences for the associated epifaunal communities and other trophic levels within the ecosystem. Given the significance of seagrass habitats for food provision and sustaining livelihoods, the loss of these ecosystems could have far-reaching consequences. Preserving seagrass ecosystems is therefore crucial to ensuring the continued provision of these ecosystem services.

As an important endogenous gasotransmitter, hydrogen sulfide (H2S) plays a critical role in various physiological functions, and has been regarded as a biomarker of cancer due to its overexpression in cancer cells. In addition, the early stages of cancer are often accompanied by abnormalities in the intracellular microenvironments. However, deep insights into the simultaneous detection of H2S and viscosity/polarity variations in cancer cells/tissues are rarely reported. In this work, we developed a near-infrared (NIR) and mitochondria-targeting fluorescent probe PDQHS, which exhibits high selectivity for H2S with an emission peak around 632 nm, and excellent response to viscosity/polarity through NIR emission beyond 706 nm. Meanwhile, PDQHS shows good biocompatibility, and can specifically accumulate into mitochondria. Using PDQHS, the visual distinguishing cancer cells from normal cells was achieved via dual-channel detection of H2S and viscosity/polarity. More importantly, PDQHS has been successfully applied to visual diagnosis of tumor tissue. Obviously, this simultaneous monitoring multi-markers via dual-channel is conducive to amplify the detection signal compared to the de-tection of a single biomarker, thus providing a more sensitive and reliable imaging tool for cancer diagnosis.

This study evaluates the effect of clustered care based on individualized developmental care on comfort level and physiological parameters of premature infants in the intensive care unit. In the study, data of 128 premature infants born between 28 and 37 weeks of gestation were collected. Individualized clustered care was applied to the infants and the results were analyzed. According to these results, there was a significant increase in the comfort levels of the infants with the implementation of clustered care. In addition, it was found that there was no difference in the heart rate and respiratory rate of the infants immediately after the clustered care, but one hour after the clustered care, both respiratory rate and heart rate decreased significantly. These results suggest that clustered care based on individualized developmental care can increase the comfort level and improve the physiological parameters of infants.

As a commodity, wind energy is typically traded in ex-ante time frames and is dependent on forecasts to secure physical positions up to 36 hours after gate closure for trading in Day-Ahead markets. Wind energy is traded in discrete quantities, however it is generated from an intermittent and variable resource. Deterministic forecasts are preferred for energy trading as the most compatible solution to provide a defined forecast quantity. However, deterministic forecasts cannot capture the stochastic nature of the underlying power source and are therefore sub-optimal. Ensemble based forecasts have the potential to reduce forecast error by accounting for uncertainties not captured in deterministic models. However, ensemble forecasts are not always available at the vertical levels at which wind turbines operate. Therefore, a method is needed to apply ensemble information to turbine hub heights for energy forecasting purposes. This paper presents a novel machine learning based method that translates the perturbations from a localised Numerical Weather Prediction model’s 10m wind speed component to an ensemble energy forecast at 100m. The extrapolated ensemble based forecast has improved the forecast accuracy by 9% when compared to the deterministic output.  The findings will have important implications for future energy trading, transmission system operation and meteorological forecasting.

Peperomia (Piperaceae) is a Pantropical genus with approximately 1,700 species, distributed mainly in the Neotropics. In this study, three new species of Peperomia, P. bahiensis, P. ilheusensis and P. mendanhensis belong to subg. Multipalmata are described for the Brazilian Atlantic Forest. Detailed descriptions, illustrations, distribution maps and an identification key for the species are provided. Keywords: Rio de Janeiro, Bahia, Piperales, Neotropics.