Upper Tract Urothelial Tumor with Renal Vein and Inferior Vena Cava Thrombus Case Report

Introduction: Urothelial tumors of upper tract are uncommon in clinical practice compared to other renal malignancy. Presentation of Case: A 71-year-old man with multiple co-morbidities who presented with generalized non-specific symptoms was worked up for his abnormal lab results. On imaging he was found to have an enlarged left kidney with perinephric fat stranding and inferior vena cava thrombus. Biopsy of the thrombus showed morphological features characteristic of malignant tumors with a papillary growth pattern. Preoperative diagnosis pointed towards Renal Cellular Carcinoma with IVC thrombus. The patient underwent left radical nephrectomy and IVC thrombectomy. Surgical pathology of the retrieved specimens showed high-grade urothelial (transitional cell) carcinoma of the renal pelvis with multiple lymph nodes and high-grade urothelial carcinoma and high-grade papillary urothelial carcinoma of the IVC thrombus, tumor stage (AJCC 7th edition): pT4b, N3, MX. Discussion: vascular involvement make small portion of renal malignancy but with urothelial origin make it more rare and few cases are reported in literature. Conclusion: To our knowledge this is the first reported case of upper tract urothelial cell carcinoma with IVC thrombus that mimics renal cell carcinoma in the Kingdom of Saudi Arabia and middle east

Application of Universal Distribution Factors for Real-Time Complex Power Flow Calculation

Complex power flow distribution factors, which relate line complex power flows to the bus injected complex powers, have been widely used in various power system planning and analysis studies. In particular, AC distribution factors have been used extensively in the recent power and energy pricing studies in free electricity market field. As was demonstrated in the existing literature, many of the electricity market related costing studies rely on the use of the distribution factors. These known distribution factors, whether the injection shift factors (ISF's) or power transfer distribution factors (PTDF's), are linear approximations of the first order sensitivities of the active power flows with respect to various variables. This paper presents a novel model for evaluating the universal distribution factors (UDF's), which are appropriate for an extensive range of power systems analysis and free electricity market studies. These distribution factors are used for the calculations of lines complex power flows and its independent of bus power injections, they are compact matrix-form expressions with total flexibility in determining the position on the line at which line flows are measured. The proposed approach was tested on IEEE 9-Bus system. Numerical results demonstrate that the proposed approach is very accurate compared with exact method

Statistical Model Checking of RANDAO’s Resilience Against Pre-computed Reveal Strategies

Decentralized (pseudo-)random number generation (RNG) is a core process of many emerging distributed systems, including perhaps most prominently, the upcoming Ethereum 2.0 (a.k.a. Serenity) protocol. To ensure security and proper operation, the randomness beacon must be unpredictable and hard to manipulate. A commonly accepted implementation scheme for decentralized RNG is a commit-reveal scheme, known as RANDAO, coupled with a reward system that incentivizes successful participation. However, this approach may still be susceptible to look-ahead attacks, in which an attacker (controlling a certain subset of participants) may attempt to pre-compute the outcomes of (possibly many) reveal strategies, and thus may bias the generated random number to his advantage. To formally evaluate resilience of RANDAO against such attacks, we develop a probabilistic model in rewriting logic of the RANDAO scheme (in the context of Serenity), and then apply statistical model checking and quantitative verification algorithms (using Maude and PVeStA) to analyze two different properties that provide different measures of bias that the attacker could potentially achieve using pre-computed strategies. We show through this analysis that unless the attacker is already controlling a sizable portion of validators and is aggressively attempting to maximize the number of last compromised proposers in the proposers list, the expected achievable bias is quite limited. The full specification of the models developed in this work are available online at https://github.com/runtimeverification/rdao-smc.Ope

On security analysis of periodic systems: expressiveness and complexity

Development of automated technological systems has seen the increase in interconnectivity among its components. This includes Internet of Things (IoT) and Industry 4.0 (I4.0) and the underlying communication between sensors and controllers. This paper is a step toward a formal framework for specifying such systems and analyzing underlying properties including safety and security. We introduce automata systems (AS) motivated by I4.0 applications. We identify various subclasses of AS that reflect different types of requirements on I4.0. We investigate the complexity of the problem of functional correctness of these systems as well as their vulnerability to attacks. We model the presence of various levels of threats to the system by proposing a range of intruder models, based on the number of actions intruders can use

Task-technology fit and technology acceptance model application to structure and evaluate the adoption of social media in academia

NurulAmalinMohamad2020_VocationalEducationforAutismSpectrumThe purpose of this article was to reduce the dissimilarities in the literature regarding the use of social media for training and its impact on students' academic performance in higher education institutions. The main method of data collection for task-technology fit (TTF) and the technology acceptance model (TAM) was a questionnaire survey. This research hypothesizes that TTF applied to social media for learning will affect technology, task, and social characteristics that in turn improve students' satisfaction and students' academic performance. It also posits that the behavioral intent to use social media for learning will affect comprehension efficiency, ease of use, and enjoyment, all of which also improve students' satisfaction and students' academic performance. The data collection questionnaire was conducted with 162 students familiar with social media. Quantitative structural equation modeling was employed to analyze the results. A significant relationship was found between technology, task, and social features with TTF for utilizing social media for academic purposes, all of which fostered student enjoyment and improved outcomes. Similarly, a clear relationship was found between comprehension efficiency, ease of use, and enjoyment with behavioral intentions to utilize social media for academic purposes that positively affected satisfaction and achievement. Therefore, the study indicates that TTF and behavioral intentions to use social media improve the active learning of students and enable them to efficiently share knowledge, information, and discussions. We recommend that students utilize social media in pursuit of their educational goals. Educators should also be persuaded to incorporate social media into their classes at higher education institutions

Extending the Real-Time Maude Semantics of Ptolemy to Hierarchical DE Models

This paper extends our Real-Time Maude formalization of the semantics of flat Ptolemy II discrete-event (DE) models to hierarchical models, including modal models. This is a challenging task that requires combining synchronous fixed-point computations with hierarchical structure. The synthesis of a Real-Time Maude verification model from a Ptolemy II DE model, and the formal verification of the synthesized model in Real-Time Maude, have been integrated into Ptolemy II, enabling a model-engineering process that combines the convenience of Ptolemy II DE modeling and simulation with formal verification in Real-Time Maude.Comment: In Proceedings RTRTS 2010, arXiv:1009.398

Integrative effects of biostimulants and salinity on vegetables: Contribution of bioumik and Lithovit®-urea50 to improve salt-tolerance of tomato

Received: June 1st, 2021 ; Accepted: July 5th, 2021 ; Published: November 3rd, 2022 ; Correspondence: [email protected] separate and combined effect of lithovit-urea50 and bioumik was tested on salt-stressed tomato crops. Salinity was induced using three different NaCl solutions (2, 4 and 8 dS m-1 ). Under the salinity effect, all aspects of plant growth were inhibited. Total chlorophyll and carotenoids reduced from mg g-1 FW and 1.1 mg g-1 FW at 2 dS m-1 to reach 1.01 mg g-1 FW and 0.66 mg g-1 FW at 8 dS m-1 in control plants. Plants treated by the combination of both products had the highest chlorophyll and carotenoids content with 2.24 mg g-1 FW and 1.34 mg g-1 FW, 1.88 mg g-1 FW and 1.05 mg g-1 FW, and 1.39 mg g-1 FW and 0.86 mg g-1 FW respectively at 2, 4 and 8 dS m-1 . Treating plants by this combination maximized flower number, fruit weight, yield and fruit diameter at 2 dS m-1 (17 flowers, 47.93 g, 431.1 g plant-1 and 3.23 cm respectively) and 4 dS m-1 (15flowers, 36.45 g, 291.85 g plant-1 and 2.8 cm respectively). The separate application of bioumik minimized cell electrolyte leakage at 2 dS m-1 (8.82%) compared to control (11.43%). Additionally, plants treated by lithovit-urea and bioumik had the highest relative water content with 107.3%, 96.5% and 91.2% respectively at 2, 4 and 8 dS m-1 . N, Ca and Mg in roots were significantly the highest at 2 dS m-1 (4.5%, 2.6% and 0.5% respectively), at 4 dS m-1 (3.74%, 2.49% and 0.48% respectively) and at 8 dS m-1 (3.21%, 2.61% and 0.32% respectively). K content in roots was maximized following the separate application of bioumik with 3.21% at 2 dS m-1 and 2.55% at 8 dS m-1 . Conclusively, lithovit-urea and bioumik helped plants in tolerating salt-stress with an optimal effect obtained after their combination

Resilience or robustness : identifying topological vulnerabilities in rail networks

Many critical infrastructure systems have network structure and are under stress. Despite their national importance, the complexity of large-scale transport networks means we do not fully understand their vulnerabilities to cascade failures. The research in this paper examines the interdependent rail networks in Greater London and surrounding commuter area. We focus on the morning commuter hours, where the system is under the most demand stress. There is increasing evidence that the topological shape of the network plays an important role in dynamic cascades. Here, we examine whether the different topological measures of resilience (stability) or robustness (failure) are more appropriate for understanding poor railway performance. The results show that resilience and not robustness has a strong correlation to the consumer experience statistics. Our results are a way of describing the complexity of cascade dynamics on networks without the involvement of detailed agent-based-models, showing that cascade effects are more responsible for poor performance than failures. The network science analysis hints at pathways towards making the network structure more resilient by reducing feedback loops