Uncertain Behavior Research Articles

A Robust Spectrum Allocation Framework Towards Inference Management in Multichannel Cognitive Radio Networks

ABSTRACTRecently, there has been research on using cognitive radio to increase the effectiveness of spectrum resources. Secondary users (SUs) sense, identify, and access frequency bands presently unoccupied by primary users (PUs). Indeed, the precise communication methods of PUs remain consistently unknown to SUs. Designing an appropriate system for spectrum monitoring along with access is necessary to address the challenging problem of guaranteeing the quality of service (QoS) for PUs and satisfying the demand of SUs for spectrum resources. When several SUs and different channels are available, spectrum allocation and sharing must be considered. This work proposes a system for allocating spectrum to multiple users and sharing multiple channels for SUs dealing with PUs with uncertain behavior. The study focuses on analyzing the interference caused to PUs by the dynamic access of SUs. The analysis of the interference produced by SUs is conducted using renewal theory. Queuing theory determines the highest average data rate achievable by SUs while considering the limitations imposed by interference to PUs and the need to maintain stability in the secondary network. Comprehensive simulations validate the efficacy of this approach.

Evaluating the role of prosumers in providing energy systems with flexibility products

AbstractIncreasing the penetration of renewables on the demand side causes operational challenges in distribution grids due to their variable and uncertain behaviour. These resources have increased distribution grid net load fluctuation during recent years, which needs to be covered by demand side flexibility (DSF). DSF should be quantified and measured by a suitable index to show the level of a system DSF in different situations. In this paper, the flexibility area index of distribution systems as a suitable metric for prosumers’ DSF evaluation, especially in the presence of renewable sources, is calculated. This index is defined first for one prosumer and then extended to a distribution system by a combination of prosumer indices. The mentioned index is decomposed into two components, one for ramp‐up (negative flexibility) and another for ramp‐down (positive flexibility). To calculate and manage prosumers’ flexibility, a novel flexibility‐oriented stochastic framework for prosumers is suggested. The amount of load shedding is under control by the risk‐management strategy in the proposed framework, which can facilitate distribution system operator operation. The results obtained from the implementation of the case study validate the major features of the proposed framework more efficiently.

NARA: Network-Aware Resource Allocation mechanism for minimizing quality-of-service impact while dealing with energy consumption in volunteer networks

A large-scale volunteer computing system is a type of distributed system in which contributors volunteer their computing resources, such as personal computers or mobile devices, to contribute to a larger computing effort. Volunteer resources are connected over the Internet and together form a powerful computing system capable of providing a service without depending on a service provider. Volunteer network resource allocation is the process of assigning computing tasks or services to a network of volunteer resources. The allocation process includes identifying the needed resources, selecting appropriate volunteers, and assigning tasks or services based on their capabilities. Volunteer computing systems consist of a large number of heterogeneous resources - in terms of processing power, storage, and availability - belonging to different authorities - users or organizations - and exhibiting uncertain behavior in terms of connection, disconnection, capacity, and failure. All of this makes resource allocation a challenging task in terms of ensuring a minimum quality of service, requiring complex algorithms and optimization techniques to ensure that services are efficiently allocated while respecting the constraints of the available resource. This paper introduces the Network-Aware Resource Allocation mechanism, which leverages the location, connectivity, and network latency of volunteer nodes to minimize the time a service runs with degraded quality of service and aims to deal with the energy consumption resulting from data replication requirements. This resource allocation mechanism applies to both the initial deployment of the service in the network and to the reallocation of nodes in the event that one of the allocated nodes fails or becomes unavailable. Our method has been validated in a simulation environment of a realistic volunteer system. The analysis of the results shows how our mechanism meets the quality requirements of users while minimizing the synchronization and replication times of service data replicas, as well as the time that services run with degraded quality of service, reducing the times by more than 70% in the service deployment phase and by more than 60% in the service execution phase. It also helps to reduce overall energy consumption.

Data-driven stochastic dynamic economic dispatch for combined heat and power systems using particle swarm optimization

In modern power systems, the uncertain behavior of renewable energy sources (RESs) may result in deviations from the optimal operating dispatches for the various power sources. The electric power generation from Combined Heat and Power (CHP) units is characterized by high efficiency with less pollution. To use CHP units more efficiently, the dynamic economic dispatch problem is applied to obtain the optimal power and heat sources’ outputs to satisfy heat and power demands while meeting the different operational constraints. In this paper, data-driven stochastic optimization is used to model these uncertainties utilizing the Generative Adversarial Networks in scenario generation that are accurate and do not require fitting models or modeling probability distributions. Then, the Fast Forward Selection technique is used to decrease the number of scenarios to improve system tractability. The results obtained indicate that the variability in electrical load, photovoltaic (PV), and wind turbine (WT) output significantly impacts the overall operational costs of the power system. Therefore, it is essential to incorporate the uncertainties associated with electrical load, PV, and WT when aiming for accurate results in economic dispatch. the study found that the overall operation cost of the dynamic economic dispatch of the electrical system for 24 hours after integrating RES achieved a daily savings of 2.5 % in the first scenario. Furthermore, the findings demonstrate that RESs positively contribute to reducing the total operational costs of the power system. The economic dispatch of CHP systems is influenced by the integration of RESs and the uncertainties associated with electrical parameters.

Real-time data sensing and digital twin model development for pavement material mixing: enhancing workability and optimisation

ABSTRACT An essential aspect of pavement construction sustainability is its low-energy consumption and emissions. The study of pavement materials workability tests holds significant importance in terms of achieving well-mixed conditions with low-energy consumption. The complex components of the material and the uncertain kinematic behaviours of aggregates during mixing make this process challenging. And, few studies of the signal response of pavement materials have been found in the field of civil engineering. For this purpose, an accurate evaluation and monitoring approach for mixing are needed. In this paper, a wireless real-time sensing method is used to monitor the dynamic behaviour of aggregates during mixing. A 3D digital twin model, combining data-sensing techniques and numerical simulation, has been proposed for rapid identification of the mixing material. This model has been validated via a data-fusion algorithm. The application of this model makes a contribution to the data-intensive analysing jobs and decision-making tasks in pavement construction engineering.

Oncocytic Adrenal Neoplasms: Clinical Profiles and Long-Term Outcomes.

Background: Oncocytic adrenal neoplasms, defined by ≥90 % of oncocytic cells, are rare. The significance of oncocytic changes within an adrenal neoplasm remains unclear.Methods: A retrospective study of adults who underwent adrenalectomy at a large center identified pure oncocytic neoplasms on final pathology (1997-2022). Neoplasms were categorized based on Lin-Weiss-Bisceglia system as malignant, benign, or of uncertain malignant potential. Analysis was performed using Fisher exact, Kruskal-Wallis tests, and Kaplan-Meier analysis.Results: Among a total of 33 patients, 24% had benign, 36% malignant, and 39% neoplasm of uncertain malignant potential. None of the benign neoplasms recurred, while 50% of the malignant neoplasms recurred (median of 40 months). Two of 13 neoplasms initially thought to be of uncertain malignant potential recurred as distant metastatic adrenocortical carcinoma at 11 and 25 months, over a median follow-up duration of 31 months. Ki67% was available for 20 patients: median (IQR) Ki67% was 5 (1, 5) for benign, 10 (6, 15) for malignant, and 6.5 (5, 10) for neoplasms of uncertain behavior, P = 0.05. Recurred neoplasms had higher Ki67% at initial resection compared to cases that did not recur.Conclusion: While oncocytic adrenal neoplasms are rare, a significant proportion are malignant or have malignant potential. Judicious follow-up is required for oncocytic adrenal neoplasms of uncertain malignant potential, as they can recur as metastatic adrenocortical carcinoma. Ki67% should always be obtained in cases of malignancy or uncertain malignant potential as it can predict recurrence. Larger studies are needed to evaluate the appropriate follow-up protocols for these neoplasms.

Malignant melanotic nerve sheath tumor

Malignant melanotic nerve sheath tumor, previously known as melanotic schwannoma, is a rare variant of peripheral nerve sheath tumor composed of melanin-producing Schwann cells and clinically misdiagnosed as melanoma. Malignant melanotic nerve sheath tumor is a rare tumor with uncertain biological behavior and variable treatment recommendations. Despite the histological features that seem benign, with a low proliferation index, the clinical course of this tumor often becomes malignant, with a high frequency of local relapses and the presence of tumor metastasis signs. Distinctive features of malignant melanotic tumor of the nerve sheath are a relatively young age of patients, the presence of the Carney complex signs and psammomatous bodies in the tumor. The article presents a case of malignant melanotic tumor of the nerve sheath localized in the neck with a recurrent course. In the described clinical observation, the patient underwent surgical treatment twice. Microscopic and immunohistochemical analysis of postoperative materials gave a positive result for melanoma markers and showed the absence of psammoma bodies and low mitotic activity. The clinical course of the disease was malignant, with the appearance of a relapse in the postoperative scar. Diagnosis of malignant melanotic tumor of the nerve sheath is a complex task, both from the radiological and pathological points of view. Communication between the surgeon, radiologist and pathologist, understanding the anatomical relationships of the lesion and careful attention to the histological findings are critical to making the correct diagnosis.

HMGA2-positive salivary gland neoplasms with prominent trabecular/canalicular morphology: a focus on carcinomas arising within this phenotype.

Pleomorphic adenoma (PA) with a prominent trabecular/canalicular morphology has consistent HMGA2 protein expression, and association with HMGA2 fusions. We report our experience with this subtype, with emphasis on the carcinomas that can arise in this context. A retro- and prospective review (2013-2024) of major salivary gland tumours with prominent trabecular/canalicular morphology was performed. Twenty-one parotid tumours met the criteria: 14 benign (66.7%), six carcinomas (28.6%), and one of uncertain behaviour (4.7%). HMGA2 immunohistochemistry (IHC) was performed on all cases. Next-generation sequencing was successfully performed on 18. Seven benign cases had a conventional PA component. In all cases, the tumour cells in these trabecular/canalicular areas demonstrated variable papillary thyroid carcinoma-like nuclear changes, including chromatin clearing, overcrowding, membrane irregularities, and intranuclear pseudoinclusions. Benign tumours were well-demarcated, whereas carcinomas demonstrated either a multinodular pattern of invasion or subtle infiltration. Two carcinomas showed increased cytologic atypia and architectural complexity and one had perineural invasion. By IHC, all were positive for HMGA2. In the trabecular/canalicular areas, there was consistent strong expression of CAM5.2, S-100, and SOX-10 and variable expression of p63 but negative p40. HMGA2 alterations were detected in 16 of 18 cases (89%). Follow-up was available on two carcinomas, with one being locally recurrent. While most HMGA2-positive salivary gland neoplasms with a prominent trabecular/canalicular growth pattern are benign, they, like traditional PAs, may give rise to carcinomas that can locally recur. These carcinomas can be deceptively bland, subtly infiltrative, or have a multinodular pattern of invasion.

Optimizing Dermatological Care Triage in a Safety-Net Hospital: Retrospective Analysis of Diagnoses and In-Person Referrals.

Teledermatology is a cost-effective and efficient approach to delivering care and is particularly beneficial for patients with limited access to specialized services. Considering the rapid expansion of telehealth, it is crucial to focus on optimization. The purpose of our study was to evaluate the triaging of dermatologic care in an electronic consultation (e-consultation) service in a safety-net hospital. This was a 2-year retrospective review of a dermatology asynchronous store-and-forward e-consultation service. A total of 1425 patients completed 1502 e-consultation. Of these e-consultations, 46% of the patients had Medicaid and 44% were Black or African American. The top three diagnoses were dermatitis unspecified, neoplasm of uncertain behavior, and acne/rosacea. Most (68%) were managed via e-consultation and did not require an in-person appointment. Children and adolescents were more likely to require an in-person appointment (74%) compared with adults (30%, P < 0.0001). Patients with a chief complaint of hair loss or skin lesion were more likely to require in-person evaluation (58% and 41%, respectively) compared with rash (24%) and acne (18%) (P < 0.0001). There was no difference found in recommendations for in-person evaluation based on race, non-English-language preference, or insurance status. E-consultation services seem well suited for certain concerns, and underserved populations can be evaluated by teledermatology.

Improved in-situ characterization for the scaling-induced wetting in membrane distillation: Unraveling the role of crystalline morphology

Despite being recognized as a promising technique for treating high salinity water, membrane distillation (MD) has been plagued by the scaling of sparingly soluble salts. The growth of crystals can not only create additional resistance to evaporating water at the feed-membrane interface, but also alter the hydrophobic network to bridge the feed and distillate (i.e., result in the phenomenon of wetting). When recognizing the uncertain behaviors of calcium sulfate (CaSO4) scaling in MD, this study was motivated to ascertain whether the crystal-membrane interactions could be dependent on the variation in crystalline morphology. In particular, optical coherence tomography (OCT) was employed to characterize the scaling-induced wetting via a direct-observation-through-the-membrane (DOTM) mode, which mitigated the effects of developing an external scaling layer on resolving the crystal-membrane interactions. The improved in-situ characterization suggests that the crystalline morphology of CaSO4 could be effectively regulated by varying the stoichiometry of crystallizing ions; the richness of calcium in the aqueous environment for crystallization would be in favor of weakening the crystal-membrane interactions. The stoichiometry-dependent growth of CaSO4 crystals can be exploited to develop an effective strategy for preventing the hydrophobic network from being wetted or irreversibly damaged.

Robust optimization of train timetables with short-length and full-length services considering uncertain passenger volume and service choice behavior

Train timetables with a combination of short-length and full-length services can adapt to spatial and temporal variations in demand. However, with such timetables, some passengers may choose to catch an earlier short-length service and then transfer to a full-length service to reach their destinations rather than waiting for a crowded full-length service. This uncertain service choice behavior frequently occurs, which, however, was not well considered in most studies on demand-oriented timetabling. Therefore, this study presents a robust timetabling approach based on the scenario-based method considering uncertain passenger volumes and service choice behavior for choosing different types of train services. A customized decomposition-based method with an iterative solution procedure is designed to solve the proposed model. In each iteration, a multi-agent-based simulation algorithm is developed to update passengers’ travel utility and the service choice preference proportion based on the previous iteration’s timetabling results. To obtain high-quality solutions in an acceptable computing time, a hybrid “ALNS + GUROBI” algorithm is developed to handle the timetabling problems for large-scale cases. The proposed method optimizes the train timetables for Xi’an Metro Line 3 in China. Our results indicate that the proposed method can account for uncertain passenger volumes and service choice behavior by adjusting the short-length plans and train headways to match the transport capacity to passenger demand.

Forest carbon payments: A multidisciplinary review of policy options for promoting carbon storage in EU member states

Forest carbon sinks can play an important role in mitigating climate change, but currently only a few policies exist globally where economic incentives are created for forest owners to maintain and strengthen sinks. This article aims to facilitate the design and implementation of governmental payment schemes for forest carbon uptake services by presenting a multidisciplinary analysis of the many challenges involved in such schemes and by proposing potential solutions. We assess the consequences, opportunities, and risks of carbon payment schemes from economic, ecological, social, and legal points of view based on existing literature. Our analysis is set in the context of the European Union (EU), but many of the central findings have relevance for a broader geographical area. The main economic challenges of implementing carbon payment schemes relate to potential leakage, the question of additionality, and uncertain forest-owner behavior. The most important ecological considerations include effects on soil carbon dynamics and biodiversity as well as issues of non-permanence and forest resilience. Our exploration of the social acceptance of carbon payments among the general public, key market actors such as forest owners and forest industry, and other stakeholders suggest that both the process of developing the scheme and its details are significant. Further, our legal analysis indicates that central challenges for carbon payment schemes within the EU rise from the requirement to comply with competition and state aid regulations. Finally, we synthesize our findings and suggest a two-step approach for introducing public carbon payments in an EU member state. Initially, the scheme could be launched via De minimis aid or the new aid scheme (GAFSRA). A low carbon price could be applied to moderate market effects, and the payments could be limited to additional carbon storage only. Peatlands, where tradeoffs exist between tree biomass carbon and soil carbon, should initially be excluded from the standard payment scheme, and regulated with command-and-control instruments and measure-based payments instead. In the future, an improved knowledge base and institutional changes may enable schemes that encompass all ecosystem carbon pools on all relevant soil types and create optimal incentives for both forest management and land-use choices by pricing all land-based sinks and emissions. Such schemes could utilize, e.g., cap-and-trade instruments and be complemented by import tariffs to control carbon leakage.

Planning and adjusting the COVID-19 booster vaccination campaign to reduce disease burden

As public health policies shifted in 2023 from emergency response to long-term COVID-19 disease management, immunization programs started to face the challenge of formulating routine booster campaigns in a still highly uncertain seasonal behavior of the COVID-19 epidemic. Mathematical models assessing past booster campaigns and integrating knowledge on waning of immunity can help better inform current and future vaccination programs. Focusing on the first booster campaign in the 2021/2022 winter in France, we used a multi-strain age-stratified transmission model to assess the effectiveness of the observed booster vaccination in controlling the succession of Delta, Omicron BA.1 and BA.2 waves. We explored counterfactual scenarios altering the eligibility criteria and inter-dose delay. Our study showed that the success of the immunization program in curtailing the Omicron BA.1 and BA.2 waves was largely dependent on the inclusion of adults among the eligible groups, and was highly sensitive to the inter-dose delay, which was changed over time. Shortening or prolonging this delay, even by only one month, would have required substantial social distancing interventions to curtail the hospitalization peak. Also, the time window for adjusting the delay was very short. Our findings highlight the importance of readiness and adaptation in the formulation of routine booster campaign in the current level of epidemiological uncertainty.

Optimal energy management via day-ahead scheduling considering renewable energy and demand response in smart grids

The energy optimization in smart power grids (SPGs) is crucial for ensuring efficient, sustainable, and cost-effective energy management. However, the uncertainty and stochastic nature of distributed generations (DGs) and loads pose significant challenges to optimization models. In this study, we propose a novel optimization model that addresses these challenges by employing a probabilistic method to model the uncertain behavior of DGs and loads. Our model utilizes the multi-objective wind-driven optimization (MOWDO) technique with fuzzy mechanism to simultaneously address economic, environmental, and comfort concerns in SPGs. Unlike existing models, our approach incorporates a hybrid demand response (HDR), combining price-based and incentive-based DR to mitigate rebound peaks and ensure stable and efficient energy usage. The model also introduces battery energy storage systems (BESS) as environmentally friendly backup sources, reducing reliance on fossil fuels and promoting sustainability. We assess the developed model across various distinct configurations: optimizing operational costs and pollution emissions independently with/without DR, optimizing both operational costs and pollution emissions concurrently with/without DR, and optimizing operational costs, user comfort, and pollution emissions simultaneously with/without DR. The experimental findings reveal that the developed model performs better than the multi-objective bird swarm optimization (MOBSO) algorithm across metrics, including operational cost, user comfort, and pollution emissions.

Unraveling the Molecular Landscape of Uterine Tumor Resembling Ovarian Sex Cord Tumor: Insights From A Clinicopathological, Morphologic, Immunohistochemical, and Molecular Analysis of 35 Cases

Uterine tumor resembling ovarian sex cord tumor (UTROSCT) is a rare tumor of uncertain lineage and low malignant potential. Most tumors behave in a benign manner, but a subset of UTROSCT exhibit an aggressive clinical course with recurrences and metastases. The recurrent molecular alterations in UTROSCT mostly represent gene fusions involving NCOA1-3. We performed a comprehensive clinicopathological, morphologic, immunohistochemical, and molecular analysis on a cohort of 35 UTROSCT. The tumors exhibited various architectural patterns (diffuse, corded/trabecular, tubular, sertoliform, fascicular, whorled, nested, microfollicular, and pseudoglandular), often in combination. The immunohistochemical analysis confirmed the polyphenotypic immunoprofile, often with coexpression of sex cord–stromal, smooth muscle, and epithelial markers, as well as hormone receptors. Next-generation sequencing RNA analysis revealed recurrent NCOA1-3 gene fusions in 22/32 analyzed cases (69%), including ESR1::NCOA3 (11/22), GREB1::NCOA2 (7/22), ESR1::NCOA2 (3/22), and GREB1::NCOA1 (1/22). Tumor mutation burden was low in all cases. The fusion-positive cases exhibited statistically significant association with whorled architecture, conversely necrosis was associated with fusion-negative status. We did not find a significant relationship between any architectural pattern and GREB1 alterations, but the NCOA2-altered tumors were associated with pseudoglandular architecture. The GREB1-altered cases occurred in older patients and tended to be more often intramural masses compared with ESR1-altered cases. On the contrary, the ESR1-altered cases presented more often like submucosal or polypoid tumors. Two tumors exhibited aggressive behavior with recurrent disease. Both of these cases harbored a GREB1::NCOA2 fusion. Unsupervised hierarchical cluster analysis of our cohort revealed 2 main clusters. The tumors with GREB1 or NCOA2 fusion cluster together, suggesting that there are underlying molecular differences between these cases and cases with ESR1::NCOA3 fusion or without fusion. Our findings contribute to the growing knowledge about a rare neoplasm with currently uncertain biological behavior.

Decentralized distributionally robust chance-constrained operation of integrated electricity and hydrogen transportation networks

Hydrogen energy offers a promising pathway to decarbonizing future energy systems. Renewable energy-based hydrogen production and road transportation-based hydrogen delivery have strengthened the coupling between the power distribution network (PDN) and the hydrogen transportation network (HTN). In this article, we propose a decentralized distributionally robust chance-constrained (DRCC) method for the integrated electricity and hydrogen transportation network (IEHTN) to foster synergies between PDN and HTN. First, an optimal scheduling framework is developed to coordinate hydrogen production and transportation in the IEHTN, where multiple operational states of water electrolyzers and the time-constrained tube trailer routing are modeled. Second, a data-driven DRCC approach is proposed to model the uncertain behaviors of renewable power generation and hydrogen demand. A conditional value-at-risk approximation is then employed to convert the DRCC problem to a tractable mixed-integer linear program that can be solved by the off-the-shelf solver. Third, an alternating direction method of multipliers (ADMM) based solving scheme is designed to solve the problem in a distributed manner with limited information exchange between PDN and HTN. To address the non-convexity brought by binary variables in the ADMM, a tractable alternating optimization procedure (AOP) strategy is utilized to guarantee the convergence of solution. Finally, case studies are conducted on an IEHTN composed of the modified IEEE 33-bus PDN and 52-node HTN to verify the validity of the proposed method.

The 2022 WHO classification of tumors of the pituitary gland: An update on aggressive and metastatic pituitary neuroendocrine tumors.

The vast majority of pituitary neuroendocrine tumors (PitNETs) are benign and slow growing with a low relapse rate over many years after surgical resection. However, about 40% are locally invasive and may not be surgically cured, and about one percentage demonstrate an aggressive clinical behavior. Exceptionally, these aggressive tumors may metastasize outside the sellar region to the central nervous system and/or systemically. The 2017 (4th Edition) WHO Classification of Pituitary Tumors abandoned the terminology "atypical adenoma" for tumors previously considered to have potential for a more aggressive behavior since its prognostic value was not established. The 2022 (5th Edition) WHO Classification of the Pituitary Tumors emphasizes the concept that morphological features distinguish indolent tumors from locally aggressive ones, however, the proposed histological subtypes are not consistent with the real life clinical characteristics of patients with aggressive tumors/carcinomas. So far, no single clinical, radiological or histological parameter can determine the risk of growth or malignant progression. Novel promising molecular prognostic markers, such as mutations in ATRX, TP53, SF3B1, and epigenetic DNA modifications, will need to be verified in larger tumor cohorts. In this review, we provide a critical analysis of the WHO guidelines for prognostic stratification and diagnosis of aggressive and metastatic PitNETs. In addition, we discuss the new WHO recommendations for changing ICD-O and ICD-11 codes for PitNET tumor behavior from a neoplasm either "benign" or "unspecified, borderline, or uncertain behavior" to "malignant" neoplasm regardless of the clinical presentation, histopathological subtype, and tumor location. We encourage multidisciplinary initiatives for integrated clinical, histological and molecular classification, which would enable early recognition of these challenging tumors and initiation of more appropriate and aggressive treatments, ultimately improving the outcome.

Reasoning graph-based reinforcement learning to cooperate mixed connected and autonomous traffic at unsignalized intersections

Cooperation at unsignalized intersections in mixed traffic environments, where Connected and Autonomous Vehicles (CAVs) and Manually Driving Vehicles (MVs) coexist, holds promise for improving safety, efficiency, and energy savings. However, the mixed traffic at unsignalized intersections present huge challenges like MVs’ uncertainties, the chain reaction and diverse interactions. Following the thought of the situation-aware cooperation, this paper proposes a Reasoning Graph-based Reinforcement Learning (RGRL) method, which integrates a Graph Neural Network (GNN) based policy and an environment providing mixed traffic with uncertain behaviors. Firstly, it graphicly represents the observed scenario as a situation using the interaction graph with connected but uncertain (bi-directional) edges. The situation reasoning process is formulated as a Reasoning Graph-based Markov Decision Process which infers the vehicle sequence stage by stage so as to sequentially depict the entire situation. Then, a GNN-based policy is constructed, which uses Graph Convolution Networks (GCN) to capture the interrelated chain reactions and Graph Attentions Networks (GAT) to measure the attention of diverse interactions. Furthermore, an environment block is developed for training the policy, which provides trajectory generators for both CAVs and MVs. A reward function that considers social compliance, collision avoidance, efficiency and energy savings is also provided in this block. Finally, three Reinforcement Learning methods, D3QN, PPO and SAC, are implemented for comparative tests to explore the applicability and strength of the framework. The test results demonstrate that the D3QN outperformed the other two methods with a larger converged reward while maintaining a similar converged speed. Compared to multi-agent RL (MARL), the RGRL approach showed superior performance statistically, reduced the number of severe conflicts by 77.78–94.12 %. The RGRL reduced average and maximum travel times by 13.62–16.02 %, and fuel-consumption by 3.38–6.98 % in medium or high Market Penetration Rates (MPRs). Hardware-in-the-loop (HIL) and Vehicle-in-the-loop (VehIL) experiments were conducted to validate the model effectiveness.

Interdigitating Dendritic Cell Tumour: A Rare Case Report with Review of Literature

Background and Aims: Interdigitating dendritic cell tumour/sarcoma (IDCS) is an exceedingly uncommon and aggressive tumour with a dismal prognosis. IDCS arises from antigen-presenting cells, which involve nodal and extranodal sites. The aim of the study is to evaluate a case of IDCS and its diagnostic challenges. Methods: A 21-year-old female with no comorbidities, a bone marrow aspirate and biopsy and an excision biopsy of the lymph node shows atypical mononuclear infiltrates that were immunohistochemically positive for S100-diffuse, CD68, LCA and Ki67. Results: Here, we report a single case of IDCS with a tumour arising from the lymph node and bone marrow infiltration. Discussion: IDCS is an aggressive disease with uncertain behaviour; strong suspicion is required to establish a diagnosis.

Descriptive epidemiology of 399 histologically confirmed newly diagnosed meningeal solitary fibrous tumours and haemangiopericytomas in France: 2006-2015.

Meningeal solitary fibrous tumour (SFT) and haemangiopericytoma (HPC) are uncommon tumours that have been merged into a single entity in the last 2021 WHO Classification of Tumors of the Central Nervous System. To describe the epidemiology of SFT/HPC operated in France and, to assess their incidence. We processed the French Brain Tumour Database (FBTDB) to conduct a nationwide population-based study of all histopathologically confirmed SFT/HPC between 2006 and 2015. Our study included 399 SFT/HPC patients, operated in France between 2006 and 2015, in one of the 46 participating neurosurgical centres. The incidence reached 0.062, 95%CI[0.056-0.068] for 100,000 person-years. SFT accounted for 35.8% and, HPC for 64.2%. The ratio of SFT/HPC over meningioma operated during the same period was 0.013. SFT/HPC are about equally distributed in women and men (55.9% vs. 44.1%). For the whole population, mean age at surgery was 53.9 (SD ± 15.8) years. The incidence of SFT/HPC surgery increases with the age and, is maximal for the 50-55years category. Benign SFT/HPC accounted for 65.16%, SFT/HPC of uncertain behaviour for 11.53% and malignant ones for 23.31%. The number of resection progresses as the histopathological behaviour became more aggressive. 6.7% of the patients with a benign SFT/HPC had a second surgery vs.16.6% in case of uncertain behaviour and, 28.4% for malignant SFT/HPC patients. Meningeal SFT and HPC are rare CNS mesenchymal tumours which both share common epidemiological characteristics, asserting their merging under a common entity. SFT/HPC incidence is less that one case for 1 billion per year and, for around 100 meningiomas-like tumours removed, one SFT/HPC may be diagnosed. SFT/HPC are equally distributed in women and men and, are mainly diagnosed around 50-55years. The more aggressive the tumour, the higher the probability of recurrence.