Miracle-dz/UniFAR-FTUs huggingface dataset:
Intensity modulated conformal radiotherapy of a jugulo-tympanic paraganglioma

Jugulo-tympanic paragangliomas are rare benign tumors arising from the neuroectodermal cells of the tympanic cavity and the dome of the jugular vein. Surgical resection has long been the first-line treatment. However, when this is not possible, radiotherapy remains a therapeutic alternative allowing local control with less morbidity. We report the case of a patient with an unresectable tympano-jugular paraganglioma, the symptomalagy was dominted by chronic headaches and right sided hypoacousie, and the treatment consisted of external radiation therapy with a total dose of 50 Gy in 25 fractions, one fraction per day, 2 Gy per fraction using the IMRT technique. The evolution was good with disappearance of clinical symptomatology, significant local control with less toxicity.
Diagrid Façade Design for Public Pool Building Using Differential Evolution

This paper discusses a set of façade design alternatives for form-finding problem focusing on conceptual phase. In this respect, the aim of the research is to propose a multi-objective optimization approach for a façade design of public pool building. We present a set of solutions belonging to Self-adaptive Multi-objective Ensemble Differential Evolution (JE_DEMO) and Self-adaptive MultiObjective Differential Evolution (JDEMO) algorithm. We focus on maximization of daylight performance and minimization of structural displacement. Based on results, two algorithms presented competitive results. Contributions are presented based on objectives functions as new trade-offs and proposed JE_DEMO algorithm for design problems.
University of Birmingham Redefining thymus medulla specialization for central tolerance

and Anderson, 2017). d uring αβ t cell development, the thymus medulla represents an essential microenvironment for t cell tolerance. this functional specialization is attributed to its typical organized topology consisting of a branching structure that contains medullary thymic epithelial cell (mtEc) networks to support negative selection and Foxp3 + t-regulatory cell (t-reg) development. Here, by performing tEc-specific deletion of the thymus medulla regulator lymphotoxin β receptor (Lt β r), we show that thymic tolerance mechanisms operate independently of Lt β r-mediated mtEc development and organization. consistent with this, mtEcs continue to express Fezf2 and Aire, regulators of intrathymic self-antigens, and support t-reg development despite loss of Lt β r-mediated medulla organogenesis. Moreover, we demonstrate that Lt β r controls thymic tolerance by regulating the frequency and makeup of intrathymic dendritic cells (dcs) required for effective thymocyte negative selection. In all, our study demonstrates that thymus medulla specialization for thymic tolerance segregates from medulla organogenesis and instead involves Lt β r-mediated regulation of the thymic dc pool.
Gpr40 is expressed in enteroendocrine cells and mediates FFA stimulation of incretin secretion

Objective: The G-protein coupled receptor Gpr40 is expressed in β -cells where it contributes to free fatty acid (FFA) enhancement of glucose stimulated insulin secretion (1-4). Other sites of Gpr40 expression, including the intestine, have however been suggested. The transcription factor IPF1/PDX1 was recently shown to bind to an enhancer element within the 5’ flanking region of Gpr40 (5), implying that IPF1/PDX1 might regulate Gpr40 expression. Here we addressed whether i) Gpr40 is expressed in the intestine and ii) Ipf1/Pdx1 function is required for Gpr40 expression. Research Design and Methods: In the present study Gpr40 expression was monitored by X-gal staining using Gpr40 reporter mice and by in situ hybridization. Ipf1/Pdx1 null and β -cell specific mutants were used to investigate whether Ipf1/Pdx1 controls Gpr40 expression. Plasma insulin, GIP, GLP-1 and glucose levels in response to acute oral fat diet were determined in Gpr40 mutant and control mice. Results: Here we show that Gpr40 is expressed in endocrine cells of the gastrointestinal (GI) tract, including cells expressing the incretin hormones GLP-1 and GIP, and that Gpr40 mediates FFA stimulated incretin secretion. We also show that Ipf1/Pdx1 is required for expression of Gpr40 in β -cells and endocrine cells of the anterior GI tract. Conclusion: Together our data provide evidence that Gpr40 modulates FFA stimulated insulin secretion from β -cells not only directly but also indirectly via regulation of incretin secretion. Moreover, our data suggest a conserved role for Ipf1/Pdx1 and Gpr40 in FFA-mediated secretion of hormones that regulate glucose and overall energy homeostasis.
Teilfolgen gleichverteilter Folgen.

Ist Jf metrisierbar, so zeigt man leicht, da es zu einer gegebenen μ-glv. Folge (*n)^°=1 stets Teilmengen M von N mit beliebig vorgegebener Dichte oder sogar mit oberer Dichte Null gibt, so da (xn)neM wieder μ-glv. ist. Allgemeiner gilt: Sind (Χ, μ), (7, v) kompakte, metrisierbare Wahrscheinlichkeitsr ume, und ist (xn)iT=1 M"gl· i X> dann gibt es stets eine Folge O„) in 7, so da (xn, yn) μ ® v-glv. ist in Xx Υ (Gerl [1]). Ist Υ zweipunktig, so ergibt sich sofort obiges Resultat.
Porovnání manuálních a automatických měření vybraných meteorologických prvků v síti stanic ČHMÚ

Z důvodu automatizace sitě stanic CHMU je od roku 1999 na některých stanicich zavaděno měřeni sražek automatickým clunkovým sražkoměrem MR3H. Naplni teto diplomove prace je na zakladě statistickeho porovnani řad sražkových uhrnů standardniho (manualniho) sražkoměru METRA a automatickeho clunkoveho sražkoměru MR3H na 31 stanicich v siti CHMU a na zakladě znalosti systematických chyb sražkoměru METRA podle dostupne literatury odhadnout systematicke chyby automatickeho sražkoměru MR3H, jejich přibližnou velikost a přiciny. Dale je cilem prace odhalit připadnou souvislost mezi diferencemi uhrnů měřených oběma sražkoměry a nadmořskou výskou. Soucasti je i navrh využiti tematu „metody měřeni meteorologických prvků“ v gymnazialnim vzdělavani formou experimentalniho měřeni sražek.
PioABC-Dependent Fe(II) Oxidation during Photoheterotrophic Growth on an Oxidized Carbon Substrate Increases Growth Yield

The simultaneous use of carbon and reduced metals such as Fe(II) by bacteria is thought to be widespread in aquatic environments, and a mechanistic description of this process could improve our understanding of biogeochemical cycles. Anoxygenic phototrophic bacteria like Rhodopseudomonas palustris typically use light for energy and organic compounds as both a carbon and an electron source. ABSTRACT Microorganisms that carry out Fe(II) oxidation play a major role in biogeochemical cycling of iron in environments with low oxygen. Fe(II) oxidation has been largely studied in the context of autotrophy. Here, we show that the anoxygenic phototroph, Rhodopseudomonas palustris CGA010, carries out Fe(II) oxidation during photoheterotrophic growth with an oxidized carbon source, malate, leading to an increase in cell yield and allowing more carbon to be directed to cell biomass. We probed the regulatory basis for this by transcriptome sequencing (RNA-seq) and found that the expression levels of the known pioABC Fe(II) oxidation genes in R. palustris depended on the redox-sensing two-component system, RegSR, and the oxidation state of the carbon source provided to cells. This provides the first mechanistic demonstration of mixotrophic growth involving reducing power generated from both Fe(II) oxidation and carbon assimilation. IMPORTANCE The simultaneous use of carbon and reduced metals such as Fe(II) by bacteria is thought to be widespread in aquatic environments, and a mechanistic description of this process could improve our understanding of biogeochemical cycles. Anoxygenic phototrophic bacteria like Rhodopseudomonas palustris typically use light for energy and organic compounds as both a carbon and an electron source. They can also use CO2 for carbon by carbon dioxide fixation when electron-rich compounds like H2, thiosulfate, and Fe(II) are provided as electron donors. Here, we show that Fe(II) oxidation can be used in another context to promote higher growth yields of R. palustris when the oxidized carbon compound malate is provided. We further established the regulatory mechanism underpinning this observation.
Near-memory Computing on FPGAs with 3D-stacked Memories: Applications, Architectures, and Optimizations

The near-memory computing (NMC) paradigm has transpired as a promising method for overcoming the memory wall challenges of future computing architectures. Modern systems integrating 3D-stacked DRAM memory can be leveraged to prevent unnecessary data movement between the main memory and the CPU. FPGA vendors have started introducing 3D memories to their products in an effort to remain competitive on bandwidth requirements of modern memory-intensive applications. Recent NMC proposals target various types of data processing workloads such as graph processing, MapReduce, sorting, machine learning, and database analytics. In this article, we conduct a literature survey on previous proposals of NMC systems on FPGAs integrated with 3D memories. By leveraging the high bandwidth offered from such memories together with specifically designed hardware, FPGA architectures have become a competitor to GPU solutions in terms of speed and energy efficiency. Various FPGA-based NMC designs have been proposed with software and hardware optimization methods to achieve high performance and energy efficiency. Our review investigates various aspects of NMC designs such as platforms, architectures, workloads, and tools. We identify the key challenges and open issues with future research directions.
Ocean salinity intelligent prediction model based on particle swarm optimization LSTM neural network

Propose a prediction model of salinity time series model based on PSO particle swarm optimization for LSTM neural network. In order to solve the problem that some hyperparameters are difficult to determine and the efficiency is low in the classic LSTM neural network, this paper introducing PSO algorithm model into small-scale training of preset neural network and hierarchical structure of LSTM neural network training is determined and given in the iteration, the experimental results are compared with those of the original LSTM neural network model in addition. The model is used to predict and verify the actual salinity time series in the sea area near a certain coordinate and shows the feasibility and optimization.
Research and Application of Range Anxiety in Electric Vehicle Drivers

This paper studied the influence of various factors on range anxiety of electric vehicle drivers, and proposed a prediction model of anxiety range based on historical driving data of electric vehicle drivers. The model USES the particle swarm algorithm to optimize the BP neural network that PSO - BP neural network, BP neural network for predicting model of slow convergence speed, and easy to fall into local optimum problem, BP neural network are optimized by the particle swarm optimization (PSO) algorithm to update of all the weight and improve the connection layer in the forecast for the current range of anxiety in the electric car driver, Based on data and experience, the influencing factors that are positively correlated with driver's range anxiety are selected from real data to extract the influencing factors of driver's range anxiety. The predicted anxiety mileage can directly show the current driver's range anxiety, and can also be differentiated by a specific algorithm, which can provide theoretical and data support for future related applications.
Research on Thermal Dissipation Characteristics of Power Lithium-Ion Battery Module with Phase Change Cooling

As an important part of battery electric vehicles, lithium-ion batteries will generate much heat in the working process. If heat dissipation measures are not taken in time, the accumulated heat will have a great impact on the battery temperature rise, seriously causing some battery safety incidents. To solve the cooling problem of lithium-ion batteries during charging and discharging cycle, in this paper, a square cooling module of lithium-ion power battery with phase change material (PCM) was designed, whose heat production and heat dissipation were established, which were coupled with the air-cooling heat dissipation model. Finally, a two-dimensional active and passive heat dissipation model of lithium battery module was formed, based on the thermal model, the simulation module in ANSYS Fluent was made use of simulating the thermal dissipation characteristics. The simulation results show that when the coefficient of convective heat transfer is 12, 60, 120W/(m2·K), the highest temperature of the battery module is 142.8℃, 74.6℃, 41.9℃, respectively, which indicates that the coefficient has an important influence on its maximum temperature. Secondly, during the whole charging-discharging cycle, its maximum temperature is 82.2℃, 79.1℃, 77.7℃and 75.1℃, respectively, when the standing time is 0, 5, 10 and 20min. Obviously, increasing the standing time can reduce its maximum temperature. In addition, the continuous heat accumulation will lead to the failure of PCM, at this time, the PCM needs to be coupled with other cooling technologies such as forced air cooling.
C-PAK: Correcting and Completing Variable-Length Prefix-Based Abbreviated Keystrokes

Improving keystroke savings is a long-term goal of text input research. We present a study into the design space of an abbreviated style of text input called C-PAK (Correcting and completing variable-length Prefix-based Abbreviated Keystrokes) for text entry on mobile devices. Given a variable length and potentially inaccurate input string (e.g., “li g t m”), C-PAK aims to expand it into a complete phrase (e.g., “looks good to me”). We develop a C-PAK prototype keyboard, PhraseWriter, based on a current state-of-the-art mobile keyboard consisting of 1.3 million n-grams and 164,000 words. Using computational simulations on a large dataset of realistic input text, we found that, in comparison to conventional single-word suggestions, PhraseWriter improves the maximum keystroke savings rate by 6.7% (from 46.3% to 49.4,), reduces the word error rate by 14.7%, and is particularly advantageous for common phrases. We conducted a lab study of novice user behavior and performance which found that users could quickly utilize the C-PAK style abbreviations implemented in PhraseWriter, achieving a higher keystroke savings rate than forward suggestions (25% vs. 16%). Furthermore, they intuitively and successfully abbreviated more with common phrases. However, users had a lower overall text entry rate due to their limited experience with the system (28.5 words per minute vs. 37.7). We outline future technical directions to improve C-PAK over the PhraseWriter baseline, and further opportunities to study the perceptual, cognitive, and physical action trade-offs that underlie the learning curve of C-PAK systems.
Toward a Practice of User-Centred Design for Shape-Changing Interfaces

Shape-changing User Interfaces (UIs) are maturing in application and complexity, and therefore are becoming a tangible reality with regards to commercialization and design in a wider context. Current prototypes support a variety of bespoke interactions and are extensively tested, but applications for these constructs are often limited to the research scenario, and within the limitations of academic institutions. Engaging with a wider audience to develop novel UIs and applications is a valuable addition to the early design process, and can elicit new directions for research. Additionally, focusing on the user fulfils a requirement for developing a User-Centred Design methodology for shape-change, as it presents novel challenges for interaction design. This position paper calls for early adoption of such processes to support the emerging technology of shape-change, and for the formation of a collaborative UCD working group in this field.
GPU Devices for Safety-Critical Systems: A Survey

Graphics Processing Unit (GPU) devices and their associated software programming languages and frameworks can deliver the computing performance required to facilitate the development of next-generation high-performance safety-critical systems such as autonomous driving systems. However, the integration of complex, parallel, and computationally demanding software functions with different safety-criticality levels on GPU devices with shared hardware resources contributes to several safety certification challenges. This survey categorizes and provides an overview of research contributions that address GPU devices’ random hardware failures, systematic failures, and independence of execution.
Memetic swarm clustering with deep belief network model for e‐learning recommendation system to improve learning performance

In this article, an efficient clustering and classification model using memetic swarm clustering and deep belief network called MSC‐DBN model, to derive a recommendation system for web‐based learning. In the proposed method, the three main phases are considered: (i) clustering, (ii) classification, and (iii) recommendation. In first phase, MSC uses ant bee colony, Particle swarm optimization and k‐MEANS clustering. In the second phase, DBN is used for classification in the clustered based users. Clustered based user's has three categories of learners. Finally, MSC‐DBN system is automatically recommends the learning materials to the learners based on the complexity level of the material and learner's capability. A detailed experimental analysis is conducted to ensure the effective recommendation performance. The proposed method is activated in Java. The proposed method attains higher precision 93.26%, 96.12%, and 91.11%, higher recall 89.56%, 92.36%, and 95.66% and higher F‐score 93.12%, 97.14%, and 92.11% compared with the existing approaches, like generalized sequential pattern (GSP) model with context aware (CA)‐collaborative filtering (CF) called (GSP‐CA‐CF), context aware (CA)‐collaborative filtering (CF) called (CF‐CA), and generalized sequential pattern (GSP). Finally, the simulation outcomes demonstrate that the proposed method can be able to find the optimal solutions efficiently and accurately.
Tendon pain – what are the mechanisms behind it?

Abstract Objectives Management of chronic tendon pain is difficult and controversial. This is due to poor knowledge of the underlying pathophysiology of chronic tendon pain, priorly known as tendinitis but now termed tendinopathy. The objective of this topical review was to synthesize evolving information of mechanisms in tendon pain, using a comprehensive search of the available literature on this topic. Content This review found no correlations between tendon degeneration, collagen separation or neovascularization and chronic tendon pain. The synthesis demonstrated that chronic tendon pain, however, is characterized by excessive nerve sprouting with ingrowth in the tendon proper, which corresponds to alterations oberserved also in other connective tissues of chronic pain conditions. Healthy, painfree tendons are devoid of nerve fibers in the tendon proper, while innervation is confined to tendon surrounding structures, such as sheaths. Chronic painful tendons exhibit elevated amounts of pain neuromediators, such as glutamate and substance p as well as up-regulated expression and excitability of pain receptors, such as the glutamate receptor NMDAR1 and the SP receptor NK1, found on ingrown nerves and immune cells. Increasing evidence indicates that mast cells serve as an important link between the peripheral nervous system and the immune systems resulting in so called neurogenic inflammation. Summary Chronic painful tendons exhibit (1) protracted ingrowth of sensory nerves (2) elevated pain mediator levels and (3) up-regulated expression and excitability of pain receptors, participating in (4) neuro-immune pathways involved in pain regulation. Current treatments that entail the highest scientific evidence to mitigate chronic tendon pain include eccentric exercises and extracorporeal shockwave, which both target peripheral neoinnervation aiming at nerve regeneration. Outlook Potential mechanism-based pharmacological treatment approaches could be developed by blocking promotors of nerve ingrowth, such as NGF, and promoting inhibitors of nerve ingrowth, like semaphorins, as well as blocking glutamate-NMDA-receptor pathways, which are prominent in chronic tendon pain.
Manufacturable Ultra-Thin Resistive FSS for Challenging EM Mobile Environments

—This paper reports on recent developments in the manufacture and measured electromagnetic (EM) performance of a new class of thin microwave absorbers based on metal backed resistively loaded Frequency Selective Surfaces (FSS). Ink jet printing technology is shown to be a viable method for creating patterned FSS elements very close to the desired resistance values. This is demonstrated by comparing simulated and measured reflectivity plots for an ink jet and a stencil printed polarisation independent absorber that is designed to work in the frequency range 7.1 - 24 GHz. Numerical simulations show that thin FSS absorbers provide radar backscatter suppression, not only in the far field of the illuminating antenna, but also when the EM source is placed very close to the surface of the periodic array. This technology can therefore provide a solution for enhancing the performance of wireless sensors placed close to lossy loads such as the human body.
Methods of Creating Service-oriented Software Systems

The object of research is service-oriented architectures and ontological models. The aim of the work is to create a formalism for describing the interaction of services and algorithms for building web service interfaces for the implementation of an effective SOA-system using a paradigm based on ontologies of data access. The result is algorithms for automated construction of web service interfaces for SOA-architecture, which allow to automatically build web-service interfaces.
Investigations on Tissue-Simulating Medium for MRI RF Safety Assessment for Patients With Active Implantable Medical Devices

In this paper, a full-wave simulation-based method is proposed to determine the optimal tissue-simulating medium for magnetic resonance imaging radio-frequency safety assessment for patients with active implantable medical devices (AIMDs). Compared to the standard medium, the proposed tissue-simulating medium is optimized for each AIMD lead path in human bodies. The reciprocity-based transfer function model is used as a criterion for optimizing the medium parameters. Numerical investigations and validations are performed for a neurostimulator to demonstrate the method.
Method for Recognizing Linguistic Constructions Based on Stochastic Neural Networks

The paper proposes a method for recognizing linguistic constructions based on stochastic neural networks. The novelty of the study lies in the fact that in order to ensure the interaction of software agents representing subjects that operate within supply chains, two models of an artificial neural network were created to recognize natural language structures based on the restricted Boltzmann machine (in contrast to it, the neurons of the hidden layer were interconnected), a criterion for evaluating the effectiveness of training the proposed models was chosen, the parameters of the proposed models were identified based on the contrastive divergence. The proposed models and methods for their parametric identification make it possible to improve the recognition accuracy of natural language constructions. The proposed method for recognizing linguistic structures based on stochastic neural networks can be used in various intelligent systems that use the recognition of natural language structures.