Miracle-dz/UniFAR-FTUs huggingface dataset:
Automatic calculation of patient size metrics in computed tomography: What level of computational accuracy do we need?

Abstract Objectives To compare the effectiveness of two different patient size metrics based on water equivalent diameter (D w), the mid‐scan water equivalent diameter D w_c, and the mean (average) water equivalent diameter in the imaged region, D w_ave, for automatic detection of accidental changes in computed tomography (CT) acquisition protocols. Methods Patient biometric data (height and weight) were available from a previous survey for 80 adult chest examinations, and 119 adult single‐acquisition chest–abdomen–pelvis (CAP) examinations for two 16 slice scanners (GE LightSpeed and Toshiba Aquilion RXL) equipped with automatic tube current modulation (ATCM). D w_c and D w_ave were calculated from the archived CT images. Size‐specific dose estimates (SSDE) were obtained from volume CT dose index (CTDI vol), using the conversion factors for a patient diameter of D w_c. Results CTDI vol and SSDE correlate better with D w_ave than with D w_c. R‐squared values of linear fits to CTDI vol of CAP examinations were 0.81–0.89 for D w_c and 0.93–0.94 for D w_ave (SSDE: 0.69–080 for D w_c, 0.87–0.92 for D w_ave). Percentage differences between D w_c and D w_ave were −4 ± 4% for chest and +5 ± 4% for CAP examinations (in % of D w_ave). However, small D w variations translated as larger variations in CTDI vol for these ATCM systems (e.g., a 24% increase in D w doubled CTDI vol). The dependence of CTDI vol on D w_ave was similar for chest and CAP examinations performed with similar ATCM parameters, while use of D w_c resulted in a clear separation of the same data according to examination type. Maximum D w variation in the imaged region was 5.6 ± 1.6 cm for chest and 6.5 ± 1.4 cm for CAP examinations. Conclusions D w_ave is a better metric than D w_c for binning similar‐sized patients in dose comparison studies, despite the additional computational effort required for its calculation Therefore, when implementing automatic determination of D w for SSDE calculations, automatic calculation of D w_ave should be considered.
Generative Adversarial Networks (GANs): What it can generate and What it cannot?

In recent years, Generative Adversarial Networks (GANs) have received significant attention from the research community. With a straightforward implementation and outstanding results, GANs have been used for numerous applications. Despite the success, GANs lack a proper theoretical explanation. These models suffer from issues like mode collapse, non-convergence, and instability during training. To address these issues, researchers have proposed theoretically rigorous frameworks inspired by varied fields of Game theory, Statistical theory, Dynamical systems, etc. In this paper, we propose to give an appropriate structure to study these contributions systematically. We essentially categorize the papers based on the issues they raise and the kind of novelty they introduce to address them. Besides, we provide insight into how each of the discussed articles solves the concerned problems. We compare and contrast different results and put forth a summary of theoretical contributions about GANs with focus on image/visual applications. We expect this summary paper to give a bird's eye view to a person wishing to understand the theoretical progress in GANs so far.
PD-1 Inhibition Minimally Affects Cisplatin-Induced Toxicities in a Murine Model

Immune checkpoint inhibition used in combination with standard cisplatin-based chemotherapy regimens is currently under evaluation in clinical trials for head and neck squamous cell carcinoma (HNSCC). The impact of anti–PD-1 therapy on cisplatin-induced ototoxicity and nephrotoxicity has not been established. Here we use a murine model of cisplatin-induced hearing loss to investigate the impact of anti–PD-1 immunotherapy on auditory brainstem responses (ABRs), distortion product otoacoustic emissions (DPOAEs), serum creatinine, and hair cell and renal histology. We demonstrate only mild worsening of DPOAEs at 14.4 and 16 kHz as well as a mild increase in serum creatinine. Renal and hair cell histology as well as ABR measures were unchanged by PD-1 inhibition. Thus, our data suggest that the use of PD-1 inhibition in conjunction with cisplatin results in toxicities that are similar to those of cisplatin alone.
Computational Models for Calcium-Mediated Astrocyte Functions

The computational neuroscience field has heavily concentrated on the modeling of neuronal functions, largely ignoring other brain cells, including one type of glial cell, the astrocytes. Despite the short history of modeling astrocytic functions, we were delighted about the hundreds of models developed so far to study the role of astrocytes, most often in calcium dynamics, synchronization, information transfer, and plasticity in vitro, but also in vascular events, hyperexcitability, and homeostasis. Our goal here is to present the state-of-the-art in computational modeling of astrocytes in order to facilitate better understanding of the functions and dynamics of astrocytes in the brain. Due to the large number of models, we concentrated on a hundred models that include biophysical descriptions for calcium signaling and dynamics in astrocytes. We categorized the models into four groups: single astrocyte models, astrocyte network models, neuron-astrocyte synapse models, and neuron-astrocyte network models to ease their use in future modeling projects. We characterized the models based on which earlier models were used for building the models and which type of biological entities were described in the astrocyte models. Features of the models were compared and contrasted so that similarities and differences were more readily apparent. We discovered that most of the models were basically generated from a small set of previously published models with small variations. However, neither citations to all the previous models with similar core structure nor explanations of what was built on top of the previous models were provided, which made it possible, in some cases, to have the same models published several times without an explicit intention to make new predictions about the roles of astrocytes in brain functions. Furthermore, only a few of the models are available online which makes it difficult to reproduce the simulation results and further develop the models. Thus, we would like to emphasize that only via reproducible research are we able to build better computational models for astrocytes, which truly advance science. Our study is the first to characterize in detail the biophysical and biochemical mechanisms that have been modeled for astrocytes.
Security analysis in role-based access control

Delegation is often used in administrative models for Role-Based Access Control (RBAC) systems to decentralize administration tasks. While the use of delegation greatly enhances flexibility and scalability, it may reduce the control that an organization has over its resources, thereby diminishing a major advantage RBAC has over Discretionary Access Control(DAC). We propose to use security analysis techniques to maintain desirable security properties while delegating administrative privileges. We give a precise definition of a family of security analysis problems in RBAC, which is more general than safety analysis that is studied in the literature. We also show that two classes of problems in the family can be reduced to similar analysis in the RT0 trust-management language, thereby establishing an interesting relationship between RBAC and the RT (Role-based Trust-management) framework. The reduction gives efficient algorithms for answering most kinds of queries in these two classes and establishes the complexity bounds for the intractable cases.
One port to 4 port power divider using SIW technology for 60GHz applications

In this paper, 1 to 4 power divider is designed for 60GHz in the millimeter wave frequency range for upcoming new technologies in wireless communications. To design this power divider Rogers RT/Duriod 5880 Substrate material is used with a dielectric constant as 2.2 and electric loss tangent as 0.0009. This power divider analyzed the characteristic like reflection coefficient, voltage standing wave ratio and electric fields. This power divider gives max reflection coefficient of −39.95 dB at 60GHz, voltage standing wave ratio of 1.02 and transmission coefficients are −6.67dB and −5.7 dB at 60GHz. This power divider gives 2.42 GHz as bandwidth. Dimensions of the 1 to 4 power divider are 6∗16∗0.508mm3. Due to its dimensions and bandwidth this power divider is more suitable for millimeter wave applications like RADAR and 5G applications at 60 GHz for today's society need.
Photoconductive devices for terahertz pulsed spectroscopy: a review [Invited]

Photoconductive switches were the key components that allowed the generation and detection of coherent broadband electromagnetic pulses at terahertz frequencies, opening the possibility for performing spectroscopy and, therefore, measuring complex dielectric properties of materials in this band, which was mostly unexplored. In this paper, we present a brief introduction to the operation principles of these devices. Subsequently, we present a review of the current state-of-the-art in this field and discuss the challenges to be faced in future development of these devices.
Low-Profile Low-Cost High Gain 60 GHz Antenna

A new design perspective that utilizes the diffracted fields from planar metallic sheets to implement high gain, low profile, and low-cost antenna at 60 GHz is presented. The proposed antenna is matched over the 60-GHz ISM band (57–64 GHz). The proposed antenna can be employed in a linear antenna array with one wavelength distance between the array elements without generating grating lobes. The proposed antenna structure is suitable for short range, low power applications. The proposed antenna is vialess planar structure. The simplicity of the structure is advantageous in relaxing the fabrication process requirements.
In-vivo imaging of neural activity with dynamic vision sensors

Optical recording of neural activity using calcium or voltage indicators requires cameras capable of detecting small temporal contrast in light intensity with sample rates of 10 Hz to 1 kHz. Large pixel scientific CMOS image sensors (sCMOS) are typically used due to their high resolution, high frame rate, and low noise. However, using such sensors for long-term recording is challenging due to their high data rates of up to 1 Gb/s. Here we studied the use of dynamic vision sensor (DVS) event cameras for neural recording. DVS have high dynamic range and a sparse asynchronous output consisting of brightness change events. Using DVS for neural recording could avoid transferring and storing redundant information. We compared the use of a Hamamatsu Orca V2 sCMOS with two advanced DVS sensors (a higher temporal contrast sensitivity 188×180 pixel SDAVIS and a 346×260 pixel higher light sensitivity back-side-illuminated BSIDAVIS) for neural activity recordings with fluorescent calcium indicators both in brain slices and awake mice. The DVS activity responds to the fast dynamics of neural activity, indicating that a sensor combining SDAVIS and BSIDAVIS technologies would be beneficial for long-term in-vivo neural recording using calcium indicators as well as potentially faster voltage indicators.
Clustering analysis of phonetic and text feature vectors

Our goal is to show an example of using statistical methods to analyse some attributes of speeches. For this purpose, the New Year's Day speeches of Czech and Czechoslovak presidents are chosen. The aim of our study is researching similarities among these speeches and their recognizability through the history of Czechoslovak politics. All presidents are compared between each other. The comparison method is based on principal component analysis and cluster analysis. Important part is creating a feature vector. The feature vector doesn't have to be the same for successful clustering. There are many varieties and combinations of features that can be selected and used. Correlated variables must be discarded. The most significant features are chosen to represent and characterize the speaker. Some speakers can have something in common according to the chosen features. Or on the other hand they can differ much more from others. This kind of approach can help us to recognize a speech pattern of each spokesman independently.
Cellular Localization of the Signaling Components of Arabidopsis His-to-Asp Phosphorelay

In the higher plant, Arabidopsis thaliana, histidine-to-aspartate (His-to-Asp) phosphorelay signal transduction systems play crucial roles in propagation of environmental stimuli, including plant hormones. This plant has 11 sensor His-kinases, 5 histidine-containing phosphotransfer (HPt) factors (AHPs), and 20 response regulators (ARRs). To gain new insight into the functions of these phosphorelay components, their intracellular localization was examined with use of GFP-fusion proteins, constructed for certain representatives of HPt factors (AHP2) and type-A and type-B ARRs (ARR6/ARR7 and ARR10, respectively). The results showed that AHP2 is mainly located in the cytoplasmic space, while both the types of ARRs have an ability to enter preferentially into the nuclei, if not exclusively. Together with the results from an in vitro phosphorelay assay with AHP2 and ARRs, these results are discussed, in terms of a geneal framework of the Arabidopsis His-to-Asp phosphorelay network.
An FPGA-Based Open Architecture Industrial Robot Controller

Most robot controllers are proprietary and, therefore, they have a closed architecture, and it is typical for robot vendors not to provide support for old control units; hence, when a deprecated robot requires an update or even a simple preventive maintenance, the manufacturer tends to recommend disposing such a unit and to acquire a new one. In this paper, the development of a field programmable gate array-based motion control system is described as part of an open-architecture and vendor-independent control system tested on a Fanuc S420F. As a way to measure the performance of the developed system, an experimental test is carried out to achieve a path tracking RMS error lower than 20 mm at a Cartesian velocity of 500 mm/s. Results demonstrate that the proposed system achieves the same feed rates as the original controller with the significant advantage of being modular, flexible, scalable, and reconfigurable.
Real time control of induction motor using neural network

Induction Machine being simple in operation and highly reliable equipment with low cost involving minimal maintenance requirements it has become the most popular equipment in industry. With the development of power electronic technology, low cost DSP, micro-controllers and parameter estimation techniques the induction motor an attractive component for the future high performance drives induction motors have many applications in the industries. The PWM technique which drives a Voltage Source Inverter (VSI) in order to apply v/f control is used to control a 3 ph induction motor. In industrial applications the most widely used controllers are PI controllers because of their simple structure and their capability of delivering good performance over a large band of operating condition. PI and ANN controllers have been designed and developed using MATLAB/SIMULINK. Prototype model is developed to validate the effectiveness of the PI and ANN control of induction motor drive using dSPACE DS1104 controller. The performance of the SVPWM based induction motor in open loop and closed loop is presented with simulation. Artificial Neural Network and Conventional PI controllers have been practically implemented using SVPWM based VSI fed induction motor in open loop mode. Hardware set up has been developed using Inverter and dSPACE controller. The real time performance of ANN based induction motor is presented by validating simulation results with the hardware results.
SyncSQL: A Language to Express Views over Data Streams

Prior rvork on languages to e-xpress co~~tinuous queries over streatns has dejrled a stream as a sequetlce of tuples that represents an i~zj~zite appetld-only relation. 111 this paper, rve sl~o\. v that cornposition of queries is not possible in the appetzd-onlj. model. Query compositiorz is a fundamerztal properh of nrzy query language cotnposition makes it possible to build up cornplex queries from sbnpler queries. We tlze~z propose a query language, ternzed Synchron i z e d SQL (or syncSQL), tlm t defines a stream as a sequerzce of modifi. operatiotzs (i.e., insert, update, and delete) agaitlst a relatio~z wit11 a specijed schema. lr~puts and outputs in airy SyncSQL query are interpreted in the same rvay and, hence. SyncSQL e.xpressions can be cornposed. Coarser periodic refresh requirements are h p ically expressed as sliding-wirzdocv queries. We generalize this approach by i~ltroduci~zg the synclzronizatior? principle that etnpocvers SyncSQL with a fortnal meclznnism to express queries rvitlz arbitrary refresh conditions. Afrer introducing the setnuntics and s). ntax. we Iny the algebraic fou~zdatiorl for SyncSQL arzd propose a quen. matching algorithm for deciding cotltain~netzt of SyncSQL expressions.
Hybrid Storage Systems: A Survey of Architectures and Algorithms

Data center storage architectures face rapidly increasing demands for data volume and quality of service requirements today. Hybrid storage systems have turned out to be the one of the most popular choices in fulfilling these demands. A mixture of various types of storage devices and structures enables architects to address performance and capacity concerns of users within one storage infrastructure. In this paper, we present an extensive literature review on the state-of-the-art research for hybrid storage systems. First, different types of hybrid storage architectures are explored and categorized thoroughly. Second, the corresponding algorithms and policies, such as caching, scheduling, resource allocation and so on, are discussed profoundly. Finally, the advantages and disadvantages of these hybrid storage architectures are compared and analyzed intensively, in terms of system performance, solid state drive lifespan, energy consumption, and so on, in order to motivate some future research directions.
Learning and Mining Player Motion Profiles in Physically Interactive Robogames

Physically-Interactive RoboGames (PIRG) are an emerging application whose aim is to develop robotic agents able to interact and engage humans in a game situation. In this framework, learning a model of players’ activity is relevant both to understand their engagement, as well as to understand specific strategies they adopted, which in turn can foster game adaptation. Following such directions and given the lack of quantitative methods for player modeling in PIRG, we propose a methodology for representing players as a mixture of existing player’s types uncovered from data. This is done by dealing both with the intrinsic uncertainty associated with the setting and with the agent necessity to act in real time to support the game interaction. Our methodology first focuses on encoding time series data generated from player-robot interaction into images, in particular Gramian angular field images, to represent continuous data. To these, we apply latent Dirichlet allocation to summarize the player’s motion style as a probabilistic mixture of different styles discovered from data. This approach has been tested in a dataset collected from a real, physical robot game, where activity patterns are extracted by using a custom three-axis accelerometer sensor module. The obtained results suggest that the proposed system is able to provide a robust description for the player interaction.
QoS-Aware Routing in Wireless Networks Using Aerial Vehicles

The next generation wireless networks need efficient mechanisms for data dissemination that should support users with better Quality of Service (QoS). Nevertheless, the existing solutions are unable to handle this demand and require either network redeployment or replanning. Moreover, this upsurges the overall operational cost and complexity of the network. This problem can be addressed by deploying Unmanned Aerial Vehicles (UAVs), which can act as on-demand relays in next generation wireless networks. In this work, a novel strategy comprising a series of algorithms based on neural networks is devised, which resolves the issues related to data dissemination, QoS, capacity, and coverage. When compared with the existing methods, the proposed approach demonstrates better outcomes for various parameters, namely, throughput, message disseminations, service dissemination rate, UAV allocation time, route acquisition delay, link utilization and signal to noise ratio for end users. The experimental results exhibit the fact that the proposed approach utilizes 39.6%, 41.6%, 43.5%, 44.4%, and 46.9% lesser iterations than the EEDD, A-Star, OCD, GPCR, and GyTAR, respectively. Therefore, it is evident that the proposed approach surpasses the existing methods by means of superior performance and augmented efficiency.
A QoE-aware quality selection controller for HTTP adaptive streaming

In this paper, we propose a quality of experience (QoE)-aware quality selection controller for HTTP adaptive streaming. The proposed method improves QoE by using two types of control: insertion of intermediate quality and suppression of quality switching. We implement the proposed method on dynamic adaptive streaming over HTTP (DASH) system and evaluate QoE. We show that the proposed method improves QoE by subjective evaluation using the scale of absolute category rating (ACR) method.
Subspace-Orbit Randomized Decomposition for Low-Rank Matrix Approximations

An efficient, accurate, and reliable approximation of a matrix by one of lower rank is a fundamental task in numerical linear algebra and signal processing applications. In this paper, we introduce a new matrix decomposition approach termed subspace-orbit randomized singular value decomposition (SOR-SVD), which makes use of random sampling techniques to give a low-rank approximation to an input matrix. Given a large and dense data matrix of size <inline-formula><tex-math notation="LaTeX">$m\times n$</tex-math></inline-formula>, the algorithm requires a few passes through data to compute a rank-<inline-formula><tex-math notation="LaTeX">$k$</tex-math></inline-formula> approximation in <inline-formula><tex-math notation="LaTeX">$O(mnk)$</tex-math></inline-formula> floating-point operations. Moreover, the SOR-SVD algorithm can utilize advanced computer architectures and, as a result, it can be optimized for maximum efficiency. The SOR-SVD algorithm is simple, accurate, and provably correct, and outperforms previously reported techniques in terms of accuracy and efficiency. Our numerical experiments support these claims.